// dist/human.esm.js
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    }
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      return X("addN");
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      return X("subtract");
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      return X("multiply");
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      return X("sum");
    }, n.prototype.prod = function(t, e) {
      return X("prod");
    }, n.prototype.unsortedSegmentSum = function(t, e, r) {
      return X("unsortedSegmentSum");
    }, n.prototype.argMin = function(t, e) {
      return X("argMin");
    }, n.prototype.argMax = function(t, e) {
      return X("argMax");
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      return X("equal");
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      return X("less");
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      return X("lessEqual");
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      return X("maximum");
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      return X("all");
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      return X("any");
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      return X("squaredDifference");
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      return X("ceil");
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      return X("floor");
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      return X("isNaN");
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      return X("isInf");
    }, n.prototype.isFinite = function(t) {
      return X("isFinite");
    }, n.prototype.pow = function(t, e) {
      return X("pow");
    }, n.prototype.exp = function(t) {
      return X("exp");
    }, n.prototype.expm1 = function(t) {
      return X("expm1");
    }, n.prototype.softmax = function(t, e) {
      return X("softmax");
    }, n.prototype.log = function(t) {
      return X("log");
    }, n.prototype.log1p = function(t) {
      return X("log1p");
    }, n.prototype.sqrt = function(t) {
      return X("sqrt");
    }, n.prototype.rsqrt = function(t) {
      return X("rsqrt");
    }, n.prototype.square = function(t) {
      return X("square");
    }, n.prototype.reciprocal = function(t) {
      return X("reciprocal");
    }, n.prototype.relu = function(t) {
      return X("relu");
    }, n.prototype.relu6 = function(t) {
      return X("relu6");
    }, n.prototype.prelu = function(t, e) {
      return X("prelu");
    }, n.prototype.elu = function(t) {
      return X("elu");
    }, n.prototype.eluDer = function(t, e) {
      return X("eluDer");
    }, n.prototype.selu = function(t) {
      return X("selu");
    }, n.prototype.int = function(t) {
      return X("int");
    }, n.prototype.clip = function(t, e, r) {
      return X("clip");
    }, n.prototype.abs = function(t) {
      return X("abs");
    }, n.prototype.complexAbs = function(t) {
      return X("complexAbs");
    }, n.prototype.sigmoid = function(t) {
      return X("sigmoid");
    }, n.prototype.softplus = function(t) {
      return X("softplus");
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      return X("sin");
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      return X("cos");
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      return X("tan");
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      return X("asin");
    }, n.prototype.acos = function(t) {
      return X("acos");
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      return X("atan");
    }, n.prototype.atan2 = function(t, e) {
      return X("atan2");
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    }, n.prototype.cosh = function(t) {
      return X("cosh");
    }, n.prototype.tanh = function(t) {
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      return X("acosh");
    }, n.prototype.atanh = function(t) {
      return X("atanh");
    }, n.prototype.erf = function(t) {
      return X("erf");
    }, n.prototype.step = function(t, e) {
      return X("step");
    }, n.prototype.fusedConv2d = function(t) {
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    }, n.prototype.conv2d = function(t, e, r) {
      return X("conv2d");
    }, n.prototype.conv2dDerInput = function(t, e, r) {
      return X("conv2dDerInput");
    }, n.prototype.conv2dDerFilter = function(t, e, r) {
      return X("conv2dDerFilter");
    }, n.prototype.fusedDepthwiseConv2D = function(t) {
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      return X("fusedDepthwiseConv2D");
    }, n.prototype.depthwiseConv2D = function(t, e, r) {
      return X("depthwiseConv2D");
    }, n.prototype.depthwiseConv2DDerInput = function(t, e, r) {
      return X("depthwiseConv2DDerInput");
    }, n.prototype.depthwiseConv2DDerFilter = function(t, e, r) {
      return X("depthwiseConv2DDerFilter");
    }, n.prototype.conv3d = function(t, e, r) {
      return X("conv3d");
    }, n.prototype.conv3dDerInput = function(t, e, r) {
      return X("conv3dDerInput");
    }, n.prototype.conv3dDerFilter = function(t, e, r) {
      return X("conv3dDerFilter");
    }, n.prototype.maxPool = function(t, e) {
      return X("maxPool");
    }, n.prototype.maxPoolBackprop = function(t, e, r, i) {
      return X("maxPoolBackprop");
    }, n.prototype.avgPool = function(t, e) {
      return X("avgPool");
    }, n.prototype.avgPoolBackprop = function(t, e, r) {
      return X("avgPoolBackprop");
    }, n.prototype.avgPool3d = function(t, e) {
      return X("avgPool3d");
    }, n.prototype.avgPool3dBackprop = function(t, e, r) {
      return X("avgPool3dBackprop");
    }, n.prototype.maxPool3d = function(t, e) {
      return X("maxPool3d");
    }, n.prototype.maxPool3dBackprop = function(t, e, r, i) {
      return X("maxPool3dBackprop");
    }, n.prototype.reshape = function(t, e) {
      return X("reshape");
    }, n.prototype.cast = function(t, e) {
      return X("cast");
    }, n.prototype.tile = function(t, e) {
      return X("tile");
    }, n.prototype.pad = function(t, e, r) {
      return X("pad");
    }, n.prototype.transpose = function(t, e) {
      return X("transpose");
    }, n.prototype.gather = function(t, e, r) {
      return X("gather");
    }, n.prototype.gatherND = function(t, e) {
      return X("gatherND");
    }, n.prototype.scatterND = function(t, e, r) {
      return X("scatterND");
    }, n.prototype.batchToSpaceND = function(t, e, r) {
      return X("batchToSpaceND");
    }, n.prototype.spaceToBatchND = function(t, e, r) {
      return X("spaceToBatchND");
    }, n.prototype.resizeBilinear = function(t, e, r, i) {
      return X("resizeBilinear");
    }, n.prototype.resizeBilinearBackprop = function(t, e, r) {
      return X("resizeBilinearBackprop");
    }, n.prototype.resizeNearestNeighbor = function(t, e, r, i) {
      return X("resizeNearestNeighbor");
    }, n.prototype.resizeNearestNeighborBackprop = function(t, e, r) {
      return X("resizeNearestNeighborBackprop");
    }, n.prototype.batchNorm = function(t, e, r, i, a, s) {
      return X("batchNorm");
    }, n.prototype.localResponseNormalization4D = function(t, e, r, i, a) {
      return X("localResponseNormalization4D");
    }, n.prototype.LRNGrad = function(t, e, r, i, a, s, o) {
      return X("LRNGrad");
    }, n.prototype.multinomial = function(t, e, r, i) {
      return X("multinomial");
    }, n.prototype.oneHot = function(t, e, r, i) {
      return X("oneHot");
    }, n.prototype.cumsum = function(t, e, r, i) {
      return X("cumsum");
    }, n.prototype.nonMaxSuppression = function(t, e, r, i, a) {
      return X("nonMaxSuppression");
    }, n.prototype.fft = function(t) {
      return X("fft");
    }, n.prototype.ifft = function(t) {
      return X("ifft");
    }, n.prototype.complex = function(t, e) {
      return X("complex");
    }, n.prototype.real = function(t) {
      return X("real");
    }, n.prototype.imag = function(t) {
      return X("imag");
    }, n.prototype.cropAndResize = function(t, e, r, i, a, s) {
      return X("cropAndResize");
    }, n.prototype.depthToSpace = function(t, e, r) {
      return X("depthToSpace");
    }, n.prototype.split = function(t, e, r) {
      return X("split");
    }, n.prototype.sparseToDense = function(t, e, r, i) {
      return X("sparseToDense");
    }, n.prototype.diag = function(t) {
      return X("diag");
    }, n.prototype.fill = function(t, e, r) {
      return X("fill");
    }, n.prototype.onesLike = function(t) {
      return X("onesLike");
    }, n.prototype.zerosLike = function(t) {
      return X("zerosLike");
    }, n.prototype.linspace = function(t, e, r) {
      return X("linspace");
    }, n.prototype.dispose = function() {
      return X("dispose");
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  }();
  function X(n) {
    throw new Error("'" + n + "' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen");
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    E(n != null, function() {
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  }
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      if (n[i] >= 0)
        e *= n[i];
      else if (n[i] === -1) {
        if (r !== -1)
          throw Error("Shapes can only have 1 implicit size. " + ("Found -1 at dim " + r + " and dim " + i));
        r = i;
      } else if (n[i] < 0)
        throw Error("Shapes can not be < 0. Found " + n[i] + " at dim " + i);
    if (r === -1) {
      if (t > 0 && t !== e)
        throw Error("Size(" + t + ") must match the product of shape " + n);
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    }
    if (e === 0)
      throw Error("Cannot infer the missing size in [" + n + "] when there are 0 elements");
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    var a = n.slice();
    return a[r] = t / e, a;
  }
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      return ot(r);
    }), function() {
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      return r < 0 ? e + r : r;
    });
  }
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      if (a != null) {
        if (a[s] === o && n[o] !== 1)
          throw new Error("Can't squeeze axis " + o + " since its dim '" + n[o] + "' is not 1");
        (a[s] == null || a[s] > o) && n[o] === 1 && (e.push(n[o]), r.push(o)), a[s] <= o && s++;
      }
      n[o] !== 1 && (e.push(n[o]), r.push(o));
    }
    return {newShape: e, keptDims: r};
  }
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    else if (n === "int32")
      e = new Int32Array(t);
    else if (n === "bool")
      e = new Uint8Array(t);
    else
      throw new Error("Unknown data type " + n);
    return e;
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      e = new Float32Array(t);
    else if (n === "int32")
      e = new Int32Array(t);
    else if (n === "bool")
      e = new Uint8Array(t);
    else if (n === "string")
      e = new Array(t);
    else
      throw new Error("Unknown data type " + n);
    return e;
  }
  function df(n, t) {
    for (var e = 0; e < n.length; e++) {
      var r = n[e];
      if (isNaN(r) || !isFinite(r))
        throw Error("A tensor of type " + t + " being uploaded contains " + r + ".");
    }
  }
  function pf(n) {
    return n === "bool" || n === "complex64" || n === "float32" || n === "int32" || n === "string";
  }
  function ff(n, t) {
    return t === "complex64" || (t === "float32" && n !== "complex64" || t === "int32" && n !== "float32" && n !== "complex64") ? false : !(t === "bool" && n === "bool");
  }
  function Ft(n) {
    return n instanceof Float32Array || n instanceof Int32Array || n instanceof Uint8Array;
  }
  function mf(n) {
    if (n === "float32" || n === "int32")
      return 4;
    if (n === "complex64")
      return 8;
    if (n === "bool")
      return 1;
    throw new Error("Unknown dtype " + n);
  }
  function gf(n) {
    if (n == null)
      return 0;
    var t = 0;
    return n.forEach(function(e) {
      return t += e.length;
    }), t;
  }
  function or(n) {
    return typeof n == "string" || n instanceof String;
  }
  function yf(n) {
    return typeof n == "boolean";
  }
  function vf(n) {
    return typeof n == "number";
  }
  function _s(n) {
    return Array.isArray(n) ? _s(n[0]) : n instanceof Float32Array ? "float32" : n instanceof Int32Array || n instanceof Uint8Array ? "int32" : vf(n) ? "float32" : or(n) ? "string" : yf(n) ? "bool" : "float32";
  }
  function cr(n) {
    return !!(n && n.constructor && n.call && n.apply);
  }
  function Cs(n, t) {
    for (var e = t; e < n; ++e)
      if (n % e === 0)
        return e;
    return n;
  }
  function bi(n) {
    var t = n.length;
    if (t < 2)
      return [];
    var e = new Array(t - 1);
    e[t - 2] = n[t - 1];
    for (var r = t - 3; r >= 0; --r)
      e[r] = e[r + 1] * n[r + 1];
    return e;
  }
  function wf(n, t, e) {
    var r = new Array();
    if (t.length === 1)
      for (var i = t[0], a = 0; a < i; a++)
        r[a] = e[n + a];
    else
      for (var i = t[0], s = t.slice(1), o = s.reduce(function(l, u) {
        return l * u;
      }), a = 0; a < i; a++)
        r[a] = wf(n + a * o, s, e);
    return r;
  }
  function xi(n, t) {
    if (n.length === 0)
      return t[0];
    var e = n.reduce(function(r, i) {
      return r * i;
    });
    if (e === 0)
      return [];
    if (e !== t.length)
      throw new Error("[" + n + "] does not match the input size " + t.length + ".");
    return wf(0, n, t);
  }
  function yc(n, t) {
    for (var e = Li(n, t), r = 0; r < e.length; r++)
      e[r] = 1;
    return e;
  }
  function Li(n, t) {
    if (t == null || t === "float32" || t === "complex64")
      return new Float32Array(n);
    if (t === "int32")
      return new Int32Array(n);
    if (t === "bool")
      return new Uint8Array(n);
    throw new Error("Unknown data type " + t);
  }
  function AL(n, t) {
    var e = n.reduce(function(r, i) {
      return r * i;
    }, 1);
    if (t == null || t === "float32")
      return xi(n, new Float32Array(e));
    if (t === "int32")
      return xi(n, new Int32Array(e));
    if (t === "bool")
      return xi(n, new Uint8Array(e));
    throw new Error("Unknown data type " + t);
  }
  function vc(n) {
    n.forEach(function(t) {
      E(Number.isInteger(t) && t >= 0, function() {
        return "Tensor must have a shape comprised of positive integers but got " + ("shape [" + n + "].");
      });
    });
  }
  function TL(n, t, e) {
    if (t === 0)
      return 0;
    if (t === 1)
      return n[0];
    for (var r = n[n.length - 1], i = 0; i < n.length - 1; ++i)
      r += e[i] * n[i];
    return r;
  }
  function NL(n, t, e) {
    if (t === 0)
      return [];
    if (t === 1)
      return [n];
    for (var r = new Array(t), i = 0; i < r.length - 1; ++i)
      r[i] = Math.floor(n / e[i]), n -= r[i] * e[i];
    return r[r.length - 1] = n, r;
  }
  function wc(n) {
    return n && n.then && typeof n.then == "function";
  }
  var bf = "tfjsflags", xf = function() {
    function n(t) {
      this.global = t, this.flags = {}, this.flagRegistry = {}, this.urlFlags = {}, this.populateURLFlags();
    }
    return n.prototype.setPlatform = function(t, e) {
      this.platform != null && console.warn("Platform " + this.platformName + " has already been set. " + ("Overwriting the platform with " + e + ".")), this.platformName = t, this.platform = e;
    }, n.prototype.registerFlag = function(t, e, r) {
      if (this.flagRegistry[t] = {evaluationFn: e, setHook: r}, this.urlFlags[t] != null) {
        var i = this.urlFlags[t];
        console.warn("Setting feature override from URL " + t + ": " + i + "."), this.set(t, i);
      }
    }, n.prototype.getAsync = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r;
        return fe(this, function(i) {
          switch (i.label) {
            case 0:
              return t in this.flags ? [2, this.flags[t]] : (e = this.flags, r = t, [4, this.evaluateFlag(t)]);
            case 1:
              return e[r] = i.sent(), [2, this.flags[t]];
          }
        });
      });
    }, n.prototype.get = function(t) {
      if (t in this.flags)
        return this.flags[t];
      var e = this.evaluateFlag(t);
      if (wc(e))
        throw new Error("Flag " + t + " cannot be synchronously evaluated. Please use getAsync() instead.");
      return this.flags[t] = e, this.flags[t];
    }, n.prototype.getNumber = function(t) {
      return this.get(t);
    }, n.prototype.getBool = function(t) {
      return this.get(t);
    }, n.prototype.getFlags = function() {
      return this.flags;
    }, Object.defineProperty(n.prototype, "features", {get: function() {
      return this.flags;
    }, enumerable: true, configurable: true}), n.prototype.set = function(t, e) {
      if (this.flagRegistry[t] == null)
        throw new Error("Cannot set flag " + t + " as it has not been registered.");
      this.flags[t] = e, this.flagRegistry[t].setHook != null && this.flagRegistry[t].setHook(e);
    }, n.prototype.evaluateFlag = function(t) {
      if (this.flagRegistry[t] == null)
        throw new Error("Cannot evaluate flag '" + t + "': no evaluation function found.");
      return this.flagRegistry[t].evaluationFn();
    }, n.prototype.setFlags = function(t) {
      this.flags = Object.assign({}, t);
    }, n.prototype.reset = function() {
      this.flags = {}, this.urlFlags = {}, this.populateURLFlags();
    }, n.prototype.populateURLFlags = function() {
      var t = this;
      if (typeof this.global == "undefined" || typeof this.global.location == "undefined" || typeof this.global.location.search == "undefined")
        return;
      var e = _L(this.global.location.search);
      if (bf in e) {
        var r = e[bf].split(",");
        r.forEach(function(i) {
          var a = i.split(":"), s = a[0], o = a[1];
          t.urlFlags[s] = CL(s, o);
        });
      }
    }, n;
  }();
  function _L(n) {
    var t = {};
    return n.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g, function(e) {
      for (var r = [], i = 1; i < arguments.length; i++)
        r[i - 1] = arguments[i];
      return RL(t, r[0], r[1]), r.join("=");
    }), t;
  }
  function RL(n, t, e) {
    n[decodeURIComponent(t)] = decodeURIComponent(e || "");
  }
  function CL(n, t) {
    if (t = t.toLowerCase(), t === "true" || t === "false")
      return t === "true";
    if ("" + +t === t)
      return +t;
    throw new Error("Could not parse value flag value " + t + " for flag " + n + ".");
  }
  function Ge() {
    return A.ENV;
  }
  A.ENV = null;
  function OL(n) {
    A.ENV = n;
  }
  var bc;
  function Lf() {
    if (bc == null) {
      var n = void 0;
      if (typeof window != "undefined")
        n = window;
      else if (typeof global != "undefined")
        n = global;
      else if (typeof process != "undefined")
        n = process;
      else if (typeof self != "undefined")
        n = self;
      else
        throw new Error("Could not find a global object");
      bc = n;
    }
    return bc;
  }
  function EL() {
    var n = Lf();
    return n._tfGlobals == null && (n._tfGlobals = new Map()), n._tfGlobals;
  }
  function Sf(n, t) {
    var e = EL();
    if (e.has(n))
      return e.get(n);
    var r = t();
    return e.set(n, r), e.get(n);
  }
  var xc = "Abs", Lc = "Acos", Sc = "Acosh", Rs = "Add", Ic = "AddN", If = "All", Af = "Any", Ac = "ArgMax", Tc = "ArgMin", Nc = "Asin", _c = "Asinh", Cc = "Atan", Rc = "Atanh", Oc = "Atan2", Ec = "AvgPool", Tf = "AvgPoolBackprop", Dc = "AvgPool3D", Nf = "AvgPool3DBackprop", kc = "BatchMatMul", Fc = "BatchToSpaceND", Wc = "BroadcastTo", Os = "Cast", Uc = "Ceil", Bc = "ClipByValue", _f = "Complex", zc = "Concat", Pc = "Conv2D", Cf = "Conv2DBackpropFilter", Mc = "Conv2DBackpropInput", Hc = "Conv3D", Rf = "Conv3DBackpropFilterV2", Of = "Conv3DBackpropInputV2", Vc = "Cos", Gc = "Cosh", qc = "Cumsum", Ef = "CropAndResize", Df = "DepthToSpace", Yc = "DepthwiseConv2dNative", kf = "DepthwiseConv2dNativeBackpropFilter", Ff = "DepthwiseConv2dNativeBackpropInput", Wf = "Diag", Kc = "Dilation2D", Uf = "Dilation2DBackpropInput", Bf = "Dilation2DBackpropFilter", jc = "Div", $c = "Elu", zf = "EluGrad", Xc = "Erf", Pf = "Equal", Jc = "Exp", Zc = "Expm1", Mf = "FFT", Hf = "Fill", Vf = "FlipLeftRight", Qc = "Floor", el = "FloorDiv", tl = "FusedBatchNorm", nl = "GatherV2", Gf = "GatherNd", qf = "Greater", rl = "GreaterEqual", il = "Identity", Yf = "IFFT", Kf = "Imag", al = "IsFinite", sl = "IsInf", ol = "IsNan", jf = "Less", $f = "LessEqual", Xf = "LinSpace", cl = "Log", ll = "Log1p", Jf = "LogicalAnd", Zf = "LogicalNot", Qf = "LogicalOr", ul = "LogSoftmax", hl = "LRN", em = "LRNBackprop", dl = "Max", pl = "Maximum", fl = "MaxPool", tm = "MaxPoolBackprop", ml = "MaxPool3D", nm = "MaxPool3DBackprop", rm = "MaxPoolWithArgmax", im = "Mean", gl = "Min", yl = "Minimum", vl = "MirrorPad", wl = "Mod", bl = "Multiply", xl = "Negate", am = "NotEqual", sm = "NonMaxSuppressionV3", om = "NonMaxSuppressionV4", cm = "NonMaxSuppressionV5", Ll = "OnesLike", Sl = "OneHot", Il = "PadV2", DL = "Pool", Al = "Pow", Tl = "Prelu", lm = "Prod", um = "Range", hm = "Real", Nl = "Reciprocal", _l = "Relu", Cl = "Reshape", Rl = "ResizeNearestNeighbor", dm = "ResizeNearestNeighborGrad", Ol = "ResizeBilinear", pm = "ResizeBilinearGrad", El = "Relu6", Dl = "Reverse", kl = "Round", Fl = "Rsqrt", fm = "ScatterNd", Wl = "SelectV2", Ul = "Selu", Bl = "Slice", zl = "Sin", Pl = "Sinh", Ml = "Sign", Hl = "Sigmoid", Vl = "Softplus", Gl = "Sqrt", ql = "Sum", Yl = "SpaceToBatchND", Kl = "SplitV", jl = "Softmax", $l = "SquaredDifference", mm = "Square", Xl = "Sub", gm = "SparseToDense", ym = "StridedSlice", Jl = "Tan", Zl = "Tanh", Ql = "Tile", vm = "TopK", eu = "Transpose", wm = "Unique", tu = "Unpack", nu = "UnsortedSegmentSum", ru = "ZerosLike", iu = "Step", au = "FromPixels", bm = "RotateWithOffset", su = "_FusedMatMul", ou = "FusedConv2D", cu = "FusedDepthwiseConv2D";
  var Si = Sf("kernelRegistry", function() {
    return new Map();
  }), va = Sf("gradRegistry", function() {
    return new Map();
  });
  function uu(n, t) {
    var e = lu(n, t);
    return Si.get(e);
  }
  function hu(n) {
    return va.get(n);
  }
  function Es(n) {
    for (var t = Si.entries(), e = []; ; ) {
      var r = t.next(), i = r.done, a = r.value;
      if (i)
        break;
      var s = a[0], o = a[1], c = s.split("_")[0];
      c === n && e.push(o);
    }
    return e;
  }
  function xm(n) {
    var t = n.kernelName, e = n.backendName, r = lu(t, e);
    Si.has(r) && console.warn("The kernel '" + t + "' for backend " + ("'" + e + "' is already registered")), Si.set(r, n);
  }
  function Lm(n) {
    var t = n.kernelName;
    va.has(t) && (Ge().getBool("DEBUG") && console.warn("Overriding the gradient for '" + t + "'")), va.set(t, n);
  }
  function kL(n, t) {
    var e = lu(n, t);
    if (!Si.has(e))
      throw new Error("The kernel '" + n + "' for backend " + ("'" + t + "' is not registered"));
    Si.delete(e);
  }
  function FL(n) {
    if (!va.has(n))
      throw new Error("The gradient '" + n + "' for backend is not registered");
    va.delete(n);
  }
  function WL(n, t) {
    var e = Es(n);
    e.forEach(function(r) {
      var i = Object.assign({}, r, {backendName: t});
      xm(i);
    });
  }
  function lu(n, t) {
    return t + "_" + n;
  }
  function UL(n, t) {
    return t === "string" ? du(n) : Ds([n], t);
  }
  function BL(n, t) {
    return n instanceof Float32Array && t === "float32" || n instanceof Int32Array && t === "int32" || n instanceof Uint8Array && t === "bool";
  }
  function Ds(n, t) {
    if (t === "string")
      throw new Error("Cannot convert a string[] to a TypedArray");
    if (Array.isArray(n) && (n = Br(n)), Ge().getBool("DEBUG") && df(n, t), BL(n, t))
      return n;
    if (t == null || t === "float32" || t === "complex64")
      return new Float32Array(n);
    if (t === "int32")
      return new Int32Array(n);
    if (t === "bool") {
      for (var e = new Uint8Array(n.length), r = 0; r < e.length; ++r)
        Math.round(n[r]) !== 0 && (e[r] = 1);
      return e;
    } else
      throw new Error("Unknown data type " + t);
  }
  function pu() {
    return Ge().platform.now();
  }
  function zL(n, t) {
    return Ge().platform.fetch(n, t);
  }
  function du(n, t) {
    return t === void 0 && (t = "utf-8"), t = t || "utf-8", Ge().platform.encode(n, t);
  }
  function fu(n, t) {
    return t === void 0 && (t = "utf-8"), t = t || "utf-8", Ge().platform.decode(n, t);
  }
  var PL = {__proto__: null, createScalarValue: UL, toTypedArray: Ds, now: pu, fetch: zL, encodeString: du, decodeString: fu, shuffle: cf, clamp: ga, nearestLargerEven: gL, sum: yL, randUniform: vL, distSquared: wL, assert: E, assertShapesMatch: Pe, assertNonNull: Ur, flatten: Br, sizeFromShape: pt, isScalarShape: bL, arraysEqual: fn, isInt: ot, tanh: xL, sizeToSquarishShape: LL, createShuffledIndices: SL, rightPad: ya, repeatedTry: IL, inferFromImplicitShape: lf, parseAxisParam: rt, squeezeShape: uf, getTypedArrayFromDType: Ns, getArrayFromDType: hf, checkConversionForErrors: df, isValidDtype: pf, hasEncodingLoss: ff, isTypedArray: Ft, bytesPerElement: mf, bytesFromStringArray: gf, isString: or, isBoolean: yf, isNumber: vf, inferDtype: _s, isFunction: cr, nearestDivisor: Cs, computeStrides: bi, toNestedArray: xi, makeOnesTypedArray: yc, makeZerosTypedArray: Li, makeZerosNestedTypedArray: AL, assertNonNegativeIntegerDimensions: vc, locToIndex: TL, indexToLoc: NL, isPromise: wc};
  var VL = function() {
    function n(t, e) {
      this.backendTimer = t, this.logger = e, e == null && (this.logger = new HL());
    }
    return n.prototype.profileKernel = function(t, e, r) {
      for (var i, a = function() {
        i = r();
      }, s = this.backendTimer.time(a), o = function(u) {
        var h = i[u];
        h.data().then(function(d) {
          ML(d, h.dtype, t);
        });
      }, c = 0; c < i.length; c++)
        o(c);
      var l = {kernelName: t, outputs: i, inputs: e, timeMs: s.then(function(u) {
        return u.kernelMs;
      }), extraInfo: s.then(function(u) {
        return u.getExtraProfileInfo != null ? u.getExtraProfileInfo() : "";
      })};
      return l;
    }, n.prototype.logKernelProfile = function(t) {
      var e = this, r = t.kernelName, i = t.outputs, a = t.timeMs, s = t.inputs, o = t.extraInfo;
      i.forEach(function(c) {
        Promise.all([c.data(), a, o]).then(function(l) {
          e.logger.logKernelProfile(r, c, l[0], l[1], s, l[2]);
        });
      });
    }, n;
  }();
  function ML(n, t, e) {
    if (t !== "float32")
      return false;
    for (var r = 0; r < n.length; r++) {
      var i = n[r];
      if (isNaN(i) || !isFinite(i))
        return console.warn("Found " + i + " in the result of '" + e + "'"), true;
    }
    return false;
  }
  var HL = function() {
    function n() {
    }
    return n.prototype.logKernelProfile = function(t, e, r, i, a, s) {
      var o = typeof i == "number" ? ya(i + "ms", 9) : i.error, c = ya(t, 25), l = e.rank, u = e.size, h = ya(e.shape.toString(), 14), d = "";
      for (var p in a) {
        var f = a[p];
        if (f != null) {
          var m = f.shape || e.shape, g = m.length;
          d += p + ": " + g + "D " + (g > 0 ? m : "") + " ";
        }
      }
      console.log("%c" + c + "	%c" + o + "	%c" + l + "D " + h + "	%c" + u + "	%c" + d + "	%c" + s, "font-weight:bold", "color:red", "color:blue", "color: orange", "color: green", "color: steelblue");
    }, n;
  }();
  function GL(n, t, e) {
    for (var r = {}, i = {}, a = 0; a < t.length; a++)
      r[t[a].id] = true;
    for (var a = 0; a < n.length; a++) {
      var s = n[a], o = s.inputs;
      for (var c in o) {
        for (var l = o[c], u = false, h = 0; h < t.length; h++)
          if (r[l.id]) {
            s.outputs.forEach(function(b) {
              return r[b.id] = true;
            }), u = true, i[s.id] = true;
            break;
          }
        if (u)
          break;
      }
    }
    var d = {};
    d[e.id] = true;
    for (var p = {}, a = n.length - 1; a >= 0; a--)
      for (var s = n[a], o = s.inputs, h = 0; h < s.outputs.length; h++)
        if (d[s.outputs[h].id]) {
          for (var c in o)
            d[o[c].id] = true, p[s.id] = true;
          break;
        }
    for (var f = [], a = 0; a < n.length; a++) {
      var s = n[a];
      if (i[s.id] && p[s.id]) {
        var m = {};
        for (var c in s.inputs) {
          var g = s.inputs[c];
          r[g.id] && (m[c] = g);
        }
        var y = Object.assign({}, s);
        y.inputs = m, y.outputs = s.outputs, f.push(y);
      }
    }
    return f;
  }
  function qL(n, t, e, r) {
    for (var i = function(s) {
      var o = t[s], c = [];
      if (o.outputs.forEach(function(d) {
        var p = n[d.id];
        p != null ? c.push(p) : c.push(null);
      }), o.gradient == null)
        throw new Error("Cannot compute gradient: gradient function not found " + ("for " + o.kernelName + "."));
      var l = o.gradient(c), u = function(d) {
        if (!(d in l))
          throw new Error("Cannot backprop through input " + d + ". " + ("Available gradients found: " + Object.keys(l) + "."));
        var p = e(function() {
          return l[d]();
        });
        if (p.dtype !== "float32")
          throw new Error("Error in gradient for op " + o.kernelName + ". The gradient of input " + (d + " must have 'float32' dtype, but has '" + p.dtype + "'"));
        var f = o.inputs[d];
        if (!fn(p.shape, f.shape))
          throw new Error("Error in gradient for op " + o.kernelName + ". The gradient of input " + ("'" + d + "' has shape '" + p.shape + "', which does not match ") + ("the shape of the input '" + f.shape + "'"));
        if (n[f.id] == null)
          n[f.id] = p;
        else {
          var m = n[f.id];
          n[f.id] = r(m, p), m.dispose();
        }
      };
      for (var h in o.inputs)
        u(h);
    }, a = t.length - 1; a >= 0; a--)
      i(a);
  }
  var Sm = 20, wa = 3, mu = 7;
  function KL(n, t, e, r) {
    var i = bi(t), a = YL(n, t, e, i), s = t.length, o = ks(n, t, e, i, a), c = ["Tensor"];
    return r && (c.push("  dtype: " + e), c.push("  rank: " + s), c.push("  shape: [" + t + "]"), c.push("  values:")), c.push(o.map(function(l) {
      return "    " + l;
    }).join(`
`)), c.join(`
`);
  }
  function YL(n, t, e, r) {
    var i = pt(t), a = r[r.length - 1], s = new Array(a).fill(0), o = t.length, c = e === "complex64" ? xa(n) : n;
    if (o > 1)
      for (var l = 0; l < i / a; l++)
        for (var u = l * a, h = 0; h < a; h++)
          s[h] = Math.max(s[h], ba(c[u + h], 0, e).length);
    return s;
  }
  function ba(n, t, e) {
    var r;
    return Array.isArray(n) ? r = parseFloat(n[0].toFixed(mu)) + " + " + (parseFloat(n[1].toFixed(mu)) + "j") : or(n) ? r = "'" + n + "'" : e === "bool" ? r = Im(n) : r = parseFloat(n.toFixed(mu)).toString(), ya(r, t);
  }
  function Im(n) {
    return n === 0 ? "false" : "true";
  }
  function ks(n, t, e, r, i, a) {
    a === void 0 && (a = true);
    var s = e === "complex64" ? 2 : 1, o = t[0], c = t.length;
    if (c === 0) {
      if (e === "complex64") {
        var l = xa(n);
        return [ba(l[0], 0, e)];
      }
      return e === "bool" ? [Im(n[0])] : [n[0].toString()];
    }
    if (c === 1) {
      if (o > Sm) {
        var u = wa * s, h = Array.from(n.slice(0, u)), d = Array.from(n.slice((o - wa) * s, o * s));
        return e === "complex64" && (h = xa(h), d = xa(d)), ["[" + h.map(function(I, C) {
          return ba(I, i[C], e);
        }).join(", ") + ", ..., " + d.map(function(I, C) {
          return ba(I, i[o - wa + C], e);
        }).join(", ") + "]"];
      }
      var p = e === "complex64" ? xa(n) : Array.from(n);
      return ["[" + p.map(function(I, C) {
        return ba(I, i[C], e);
      }).join(", ") + "]"];
    }
    var f = t.slice(1), m = r.slice(1), g = r[0] * s, y = [];
    if (o > Sm) {
      for (var w = 0; w < wa; w++) {
        var b = w * g, L = b + g;
        y.push.apply(y, ks(n.slice(b, L), f, e, m, i, false));
      }
      y.push("...");
      for (var w = o - wa; w < o; w++) {
        var b = w * g, L = b + g;
        y.push.apply(y, ks(n.slice(b, L), f, e, m, i, w === o - 1));
      }
    } else
      for (var w = 0; w < o; w++) {
        var b = w * g, L = b + g;
        y.push.apply(y, ks(n.slice(b, L), f, e, m, i, w === o - 1));
      }
    var x = c === 2 ? "," : "";
    y[0] = "[" + y[0] + x;
    for (var w = 1; w < y.length - 1; w++)
      y[w] = " " + y[w] + x;
    for (var N = `,
`, w = 2; w < c; w++)
      N += `
`;
    return y[y.length - 1] = " " + y[y.length - 1] + "]" + (a ? "" : N), y;
  }
  function xa(n) {
    for (var t = [], e = 0; e < n.length; e += 2)
      t.push([n[e], n[e + 1]]);
    return t;
  }
  var Fs = function() {
    function n(t, e, r) {
      var i = this;
      if (this.dtype = e, this.shape = t.slice(), this.size = pt(t), r != null) {
        var a = r.length;
        E(a === this.size, function() {
          return "Length of values '" + a + "' does not match the size " + ("inferred by the shape '" + i.size + "'.");
        });
      }
      if (e === "complex64")
        throw new Error("complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).");
      this.values = r || hf(e, this.size), this.strides = bi(t);
    }
    return n.prototype.set = function(t) {
      for (var e = this, r = [], i = 1; i < arguments.length; i++)
        r[i - 1] = arguments[i];
      r.length === 0 && (r = [0]), E(r.length === this.rank, function() {
        return "The number of provided coordinates (" + r.length + ") must " + ("match the rank (" + e.rank + ")");
      });
      var a = this.locToIndex(r);
      this.values[a] = t;
    }, n.prototype.get = function() {
      for (var t = [], e = 0; e < arguments.length; e++)
        t[e] = arguments[e];
      t.length === 0 && (t = [0]);
      for (var r = 0, i = 0, a = t; i < a.length; i++) {
        var s = a[i];
        if (s < 0 || s >= this.shape[r]) {
          var o = "Requested out of range element at " + t + ". " + ("  Buffer shape=" + this.shape);
          throw new Error(o);
        }
        r++;
      }
      for (var c = t[t.length - 1], l = 0; l < t.length - 1; ++l)
        c += this.strides[l] * t[l];
      return this.values[c];
    }, n.prototype.locToIndex = function(t) {
      if (this.rank === 0)
        return 0;
      if (this.rank === 1)
        return t[0];
      for (var e = t[t.length - 1], r = 0; r < t.length - 1; ++r)
        e += this.strides[r] * t[r];
      return e;
    }, n.prototype.indexToLoc = function(t) {
      if (this.rank === 0)
        return [];
      if (this.rank === 1)
        return [t];
      for (var e = new Array(this.shape.length), r = 0; r < e.length - 1; ++r)
        e[r] = Math.floor(t / this.strides[r]), t -= e[r] * this.strides[r];
      return e[e.length - 1] = t, e;
    }, Object.defineProperty(n.prototype, "rank", {get: function() {
      return this.shape.length;
    }, enumerable: true, configurable: true}), n.prototype.toTensor = function() {
      return Rn().makeTensor(this.values, this.shape, this.dtype);
    }, n;
  }(), Rn = null, Ii = null;
  function jL(n) {
    Rn = n;
  }
  function $L(n) {
    Ii = n;
  }
  var K = function() {
    function n(t, e, r, i) {
      this.kept = false, this.isDisposedInternal = false, this.shape = t.slice(), this.dtype = e || "float32", this.size = pt(t), this.strides = bi(t), this.dataId = r, this.id = i, this.rankType = this.rank < 5 ? this.rank.toString() : "higher";
    }
    return Object.defineProperty(n.prototype, "rank", {get: function() {
      return this.shape.length;
    }, enumerable: true, configurable: true}), n.prototype.buffer = function() {
      return pe(this, void 0, void 0, function() {
        var t;
        return fe(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.data()];
            case 1:
              return t = e.sent(), [2, Ii.buffer(this.shape, this.dtype, t)];
          }
        });
      });
    }, n.prototype.bufferSync = function() {
      return Ii.buffer(this.shape, this.dtype, this.dataSync());
    }, n.prototype.array = function() {
      return pe(this, void 0, void 0, function() {
        var t;
        return fe(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.data()];
            case 1:
              return t = e.sent(), [2, xi(this.shape, t)];
          }
        });
      });
    }, n.prototype.arraySync = function() {
      return xi(this.shape, this.dataSync());
    }, n.prototype.data = function() {
      return pe(this, void 0, void 0, function() {
        var t, e;
        return fe(this, function(r) {
          switch (r.label) {
            case 0:
              return this.throwIfDisposed(), t = Rn().read(this.dataId), this.dtype === "string" ? [4, t] : [3, 2];
            case 1:
              e = r.sent();
              try {
                return [2, e.map(function(i) {
                  return fu(i);
                })];
              } catch (i) {
                throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().");
              }
              r.label = 2;
            case 2:
              return [2, t];
          }
        });
      });
    }, n.prototype.dataSync = function() {
      this.throwIfDisposed();
      var t = Rn().readSync(this.dataId);
      if (this.dtype === "string")
        try {
          return t.map(function(e) {
            return fu(e);
          });
        } catch (e) {
          throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().");
        }
      return t;
    }, n.prototype.bytes = function() {
      return pe(this, void 0, void 0, function() {
        var t;
        return fe(this, function(e) {
          switch (e.label) {
            case 0:
              return this.throwIfDisposed(), [4, Rn().read(this.dataId)];
            case 1:
              return t = e.sent(), this.dtype === "string" ? [2, t] : [2, new Uint8Array(t.buffer)];
          }
        });
      });
    }, n.prototype.dispose = function() {
      if (this.isDisposed)
        return;
      Rn().disposeTensor(this), this.isDisposedInternal = true;
    }, Object.defineProperty(n.prototype, "isDisposed", {get: function() {
      return this.isDisposedInternal;
    }, enumerable: true, configurable: true}), n.prototype.throwIfDisposed = function() {
      if (this.isDisposed)
        throw new Error("Tensor is disposed.");
    }, n.prototype.print = function(t) {
      return t === void 0 && (t = false), Ii.print(this, t);
    }, n.prototype.clone = function() {
      return this.throwIfDisposed(), Ii.clone(this);
    }, n.prototype.toString = function(t) {
      t === void 0 && (t = false);
      var e = this.dataSync();
      return KL(e, this.shape, this.dtype, t);
    }, n.prototype.cast = function(t) {
      return this.throwIfDisposed(), Ii.cast(this, t);
    }, n.prototype.variable = function(t, e, r) {
      return t === void 0 && (t = true), this.throwIfDisposed(), Rn().makeVariable(this, t, e, r);
    }, n;
  }();
  Object.defineProperty(K, Symbol.hasInstance, {value: function(n) {
    return !!n && n.data != null && n.dataSync != null && n.throwIfDisposed != null;
  }});
  var La = function(n) {
    qn(t, n);
    function t(e, r, i, a) {
      var s = n.call(this, e.shape, e.dtype, e.dataId, a) || this;
      return s.trainable = r, s.name = i, s;
    }
    return t.prototype.assign = function(e) {
      if (e.dtype !== this.dtype)
        throw new Error("dtype of the new value (" + e.dtype + ") and " + ("previous value (" + this.dtype + ") must match"));
      if (!fn(e.shape, this.shape))
        throw new Error("shape of the new value (" + e.shape + ") and " + ("previous value (" + this.shape + ") must match"));
      Rn().disposeTensor(this), this.dataId = e.dataId, Rn().incRef(this, null);
    }, t.prototype.dispose = function() {
      Rn().disposeVariable(this), this.isDisposedInternal = true;
    }, t;
  }(K);
  Object.defineProperty(La, Symbol.hasInstance, {value: function(n) {
    return n instanceof K && n.assign != null && n.assign instanceof Function;
  }});
  (function(n) {
    n.R0 = "R0", n.R1 = "R1", n.R2 = "R2", n.R3 = "R3", n.R4 = "R4", n.R5 = "R5", n.R6 = "R6";
  })(A.Rank || (A.Rank = {}));
  var gu;
  (function(n) {
    n.float32 = "float32", n.int32 = "int32", n.bool = "int32", n.complex64 = "complex64";
  })(gu || (gu = {}));
  var yu;
  (function(n) {
    n.float32 = "float32", n.int32 = "int32", n.bool = "bool", n.complex64 = "complex64";
  })(yu || (yu = {}));
  var vu;
  (function(n) {
    n.float32 = "float32", n.int32 = "float32", n.bool = "float32", n.complex64 = "complex64";
  })(vu || (vu = {}));
  var wu;
  (function(n) {
    n.float32 = "complex64", n.int32 = "complex64", n.bool = "complex64", n.complex64 = "complex64";
  })(wu || (wu = {}));
  var XL = {float32: vu, int32: gu, bool: yu, complex64: wu};
  function Ws(n, t) {
    if (n === "string" || t === "string") {
      if (n === "string" && t === "string")
        return "string";
      throw new Error("Can not upcast " + n + " with " + t);
    }
    return XL[n][t];
  }
  function JL(n) {
    return Ws(n, "int32");
  }
  function ct(n, t) {
    if (n.dtype === t.dtype)
      return [n, t];
    var e = Ws(n.dtype, t.dtype);
    return [n.cast(e), t.cast(e)];
  }
  function Am(n, t) {
    E(n.dtype === t.dtype, function() {
      return "The dtypes of the first(" + n.dtype + ") and" + (" second(" + t.dtype + ") input must match");
    });
  }
  function ZL(n, t) {
    return t.some(function(e) {
      return e.id === n.id;
    });
  }
  function bu(n) {
    var t = [], e = new Set();
    return Tm(n, t, e), t;
  }
  function Tm(n, t, e) {
    if (n == null)
      return;
    if (n instanceof K) {
      t.push(n);
      return;
    }
    if (!QL(n))
      return;
    var r = n;
    for (var i in r) {
      var a = r[i];
      e.has(a) || (e.add(a), Tm(a, t, e));
    }
  }
  function QL(n) {
    return Array.isArray(n) || typeof n == "object";
  }
  var eS = {__proto__: null, makeTypesMatch: ct, assertTypesMatch: Am, isTensorInList: ZL, getTensorsInContainer: bu};
  var Nm = function() {
    function n() {
      this.registeredVariables = {}, this.nextTapeNodeId = 0, this.numBytes = 0, this.numTensors = 0, this.numStringTensors = 0, this.numDataBuffers = 0, this.gradientDepth = 0, this.kernelDepth = 0, this.scopeStack = [], this.numDataMovesStack = [], this.nextScopeId = 0, this.tensorInfo = new WeakMap(), this.profiling = false, this.activeProfile = {newBytes: 0, newTensors: 0, peakBytes: 0, kernels: [], result: null};
    }
    return n.prototype.dispose = function() {
      for (var t in this.registeredVariables)
        this.registeredVariables[t].dispose();
    }, n;
  }(), rS = function() {
    function n(t) {
      this.ENV = t, this.registry = {}, this.registryFactory = {}, this.pendingBackendInitId = 0, this.state = new Nm();
    }
    return n.prototype.ready = function() {
      return pe(this, void 0, void 0, function() {
        var t, e, r, i;
        return fe(this, function(a) {
          switch (a.label) {
            case 0:
              if (this.pendingBackendInit != null)
                return [2, this.pendingBackendInit.then(function() {
                })];
              if (this.backendInstance != null)
                return [2];
              t = this.getSortedBackends(), e = 0, a.label = 1;
            case 1:
              return e < t.length ? (r = t[e], [4, this.initializeBackend(r).success]) : [3, 5];
            case 2:
              return i = a.sent(), i ? [4, this.setBackend(r)] : [3, 4];
            case 3:
              return a.sent(), [2];
            case 4:
              return e++, [3, 1];
            case 5:
              throw new Error("Could not initialize any backends, all backend initializations failed.");
          }
        });
      });
    }, Object.defineProperty(n.prototype, "backend", {get: function() {
      if (this.pendingBackendInit != null)
        throw new Error("Backend '" + this.backendName + "' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods");
      if (this.backendInstance == null) {
        var t = this.initializeBackendsAndReturnBest(), e = t.name, r = t.asyncInit;
        if (r)
          throw new Error("The highest priority backend '" + e + "' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods");
        this.setBackend(e);
      }
      return this.backendInstance;
    }, enumerable: true, configurable: true}), n.prototype.backendNames = function() {
      return Object.keys(this.registryFactory);
    }, n.prototype.findBackend = function(t) {
      if (!(t in this.registry))
        if (t in this.registryFactory) {
          var e = this.initializeBackend(t).asyncInit;
          if (e)
            return null;
        } else
          return null;
      return this.registry[t];
    }, n.prototype.findBackendFactory = function(t) {
      return t in this.registryFactory ? this.registryFactory[t].factory : null;
    }, n.prototype.registerBackend = function(t, e, r) {
      return r === void 0 && (r = 1), t in this.registryFactory ? (console.warn(t + " backend was already registered. Reusing existing backend factory."), false) : (this.registryFactory[t] = {factory: e, priority: r}, true);
    }, n.prototype.setBackend = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r, i, a, s;
        return fe(this, function(o) {
          switch (o.label) {
            case 0:
              if (this.registryFactory[t] == null)
                throw new Error("Backend name '" + t + "' not found in registry");
              return this.backendName = t, this.registry[t] == null ? (this.backendInstance = null, e = this.initializeBackend(t), r = e.success, i = e.asyncInit, i ? [4, r] : [3, 2]) : [3, 4];
            case 1:
              return s = o.sent(), [3, 3];
            case 2:
              s = r, o.label = 3;
            case 3:
              if (a = s, !a)
                return [2, false];
              o.label = 4;
            case 4:
              return this.backendInstance = this.registry[t], this.setupRegisteredKernels(), this.profiler = new VL(this.backendInstance), [2, true];
          }
        });
      });
    }, n.prototype.setupRegisteredKernels = function() {
      var t = this, e = Es(this.backendName);
      e.forEach(function(r) {
        r.setupFunc != null && r.setupFunc(t.backendInstance);
      });
    }, n.prototype.disposeRegisteredKernels = function(t) {
      var e = this, r = Es(t);
      r.forEach(function(i) {
        i.disposeFunc != null && i.disposeFunc(e.registry[t]);
      });
    }, n.prototype.initializeBackend = function(t) {
      var e = this, r = this.registryFactory[t];
      if (r == null)
        throw new Error("Cannot initialize backend " + t + ", no registration found.");
      try {
        var i = r.factory();
        if (i && !(i instanceof of) && typeof i.then == "function") {
          var a = ++this.pendingBackendInitId, s = i.then(function(o) {
            return a < e.pendingBackendInitId ? false : (e.registry[t] = o, e.pendingBackendInit = null, true);
          }).catch(function(o) {
            return a < e.pendingBackendInitId || (e.pendingBackendInit = null, console.warn("Initialization of backend " + t + " failed"), console.warn(o.stack || o.message)), false;
          });
          return this.pendingBackendInit = s, {success: s, asyncInit: true};
        } else
          return this.registry[t] = i, {success: true, asyncInit: false};
      } catch (o) {
        return console.warn("Initialization of backend " + t + " failed"), console.warn(o.stack || o.message), {success: false, asyncInit: false};
      }
    }, n.prototype.removeBackend = function(t) {
      if (!(t in this.registryFactory))
        throw new Error(t + " backend not found in registry");
      this.backendName === t && this.pendingBackendInit != null && this.pendingBackendInitId++, t in this.registry && (this.disposeRegisteredKernels(t), this.registry[t].dispose(), delete this.registry[t]), delete this.registryFactory[t], this.backendName === t && (this.pendingBackendInit = null, this.backendName = null, this.backendInstance = null);
    }, n.prototype.getSortedBackends = function() {
      var t = this;
      if (Object.keys(this.registryFactory).length === 0)
        throw new Error("No backend found in registry.");
      return Object.keys(this.registryFactory).sort(function(e, r) {
        return t.registryFactory[r].priority - t.registryFactory[e].priority;
      });
    }, n.prototype.initializeBackendsAndReturnBest = function() {
      for (var t = this.getSortedBackends(), e = 0; e < t.length; e++) {
        var r = t[e], i = this.initializeBackend(r), a = i.success, s = i.asyncInit;
        if (s || a)
          return {name: r, asyncInit: s};
      }
      throw new Error("Could not initialize any backends, all backend initializations failed.");
    }, n.prototype.moveData = function(t, e) {
      var r = this.state.tensorInfo.get(e), i = r.backend, a = this.readSync(e);
      i.disposeData(e), r.backend = t, t.move(e, a, r.shape, r.dtype), this.shouldCheckForMemLeaks() && this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1]++;
    }, n.prototype.tidy = function(t, e) {
      var r = this, i = null;
      if (e == null) {
        if (typeof t != "function")
          throw new Error("Please provide a function to tidy()");
        e = t;
      } else {
        if (typeof t != "string" && !(t instanceof String))
          throw new Error("When calling with two arguments, the first argument to tidy() must be a string");
        if (typeof e != "function")
          throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");
        i = t;
      }
      var a;
      return this.scopedRun(function() {
        return r.startScope(i);
      }, function() {
        return r.endScope(a);
      }, function() {
        return a = e(), a instanceof Promise && console.error("Cannot return a Promise inside of tidy."), a;
      });
    }, n.prototype.scopedRun = function(t, e, r) {
      t();
      try {
        var i = r();
        return e(), i;
      } catch (a) {
        throw e(), a;
      }
    }, n.prototype.nextTensorId = function() {
      return n.nextTensorId++;
    }, n.prototype.nextVariableId = function() {
      return n.nextVariableId++;
    }, n.prototype.clone = function(t) {
      var e = this.makeTensorFromDataId(t.dataId, t.shape, t.dtype), r = {x: t}, i = function(s) {
        return {x: function() {
          var o = "float32", c = {x: s}, l = {dtype: o};
          return z.runKernelFunc(function(u) {
            return u.cast(s, o);
          }, c, null, Os, l);
        }};
      }, a = [];
      return this.addTapeNode(this.state.activeScope.name, r, [e], i, a, {}), e;
    }, n.prototype.runKernel = function(t, e, r, i, a) {
      var s = null, o = null;
      return this.runKernelFunc(s, e, o, t, r, i, a);
    }, n.prototype.shouldCheckForMemLeaks = function() {
      return this.ENV.getBool("IS_TEST");
    }, n.prototype.checkKernelForMemLeak = function(t, e, r) {
      var i = this.backend.numDataIds(), a = 0;
      r.forEach(function(c) {
        a += c.dtype === "complex64" ? 3 : 1;
      });
      var s = this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1], o = i - e - a - s;
      if (o > 0)
        throw new Error("Backend '" + this.backendName + "' has an internal memory leak " + ("(" + o + " data ids) after running '" + t + "'"));
    }, n.prototype.runKernelFunc = function(t, e, r, i, a, s, o) {
      var c = this, l, u = [], h = this.isTapeOn();
      i == null && (i = this.state.activeScope != null ? this.state.activeScope.name : "");
      var d = this.state.numBytes, p = this.state.numTensors;
      this.shouldCheckForMemLeaks() && this.state.numDataMovesStack.push(0);
      var f, m = uu(i, this.backendName), g;
      if (m != null)
        f = function() {
          var b = c.backend.numDataIds();
          g = m.kernelFunc({inputs: e, attrs: a, backend: c.backend});
          var L = Array.isArray(g) ? g : [g];
          c.shouldCheckForMemLeaks() && c.checkKernelForMemLeak(i, b, L);
          var x = L.map(function(C) {
            var O = C.dataId, D = C.shape, F = C.dtype;
            return c.makeTensorFromDataId(O, D, F);
          });
          if (h) {
            var N = c.getTensorsForGradient(i, e, x);
            if (N == null) {
              o == null && (o = []);
              var I = x.filter(function(C, O) {
                return o[O];
              });
              N = (s || []).slice().concat(I);
            }
            u = c.saveTensorsForBackwardMode(N);
          }
          return x;
        };
      else {
        var y = function(b) {
          if (!h)
            return;
          u = b.map(function(L) {
            return c.keep(c.clone(L));
          });
        };
        f = function() {
          var b = c.backend.numDataIds();
          g = c.tidy(function() {
            return t(c.backend, y);
          });
          var L = Array.isArray(g) ? g : [g];
          return c.shouldCheckForMemLeaks() && c.checkKernelForMemLeak(i, b, L), L;
        };
      }
      var w;
      return this.scopedRun(function() {
        return c.state.kernelDepth++;
      }, function() {
        return c.state.kernelDepth--;
      }, function() {
        !c.ENV.getBool("DEBUG") && !c.state.profiling ? l = f() : (w = c.profiler.profileKernel(i, e, function() {
          return f();
        }), c.ENV.getBool("DEBUG") && c.profiler.logKernelProfile(w), l = w.outputs);
      }), h && this.addTapeNode(i, e, l, r, u, a), this.state.profiling && this.state.activeProfile.kernels.push({name: i, bytesAdded: this.state.numBytes - d, totalBytesSnapshot: this.state.numBytes, tensorsAdded: this.state.numTensors - p, totalTensorsSnapshot: this.state.numTensors, inputShapes: Object.keys(e).map(function(b) {
        return e[b] != null ? e[b].shape : null;
      }), outputShapes: l.map(function(b) {
        return b.shape;
      }), kernelTimeMs: w.timeMs, extraInfo: w.extraInfo}), Array.isArray(g) ? l : l[0];
    }, n.prototype.saveTensorsForBackwardMode = function(t) {
      var e = this, r = t.map(function(i) {
        return e.keep(e.clone(i));
      });
      return r;
    }, n.prototype.getTensorsForGradient = function(t, e, r) {
      var i = hu(t);
      if (i != null) {
        var a = i.inputsToSave || [], s = i.outputsToSave || [], o = void 0;
        i.saveAllInputs ? (E(Array.isArray(e), function() {
          return "saveAllInputs is true, expected inputs to be an array.";
        }), o = Object.keys(e).map(function(l) {
          return e[l];
        })) : o = a.map(function(l) {
          return e[l];
        });
        var c = r.filter(function(l, u) {
          return s[u];
        });
        return o.concat(c);
      }
      return null;
    }, n.prototype.makeTensor = function(t, e, r, i) {
      if (t == null)
        throw new Error("Values passed to engine.makeTensor() are null");
      r = r || "float32", i = i || this.backend;
      var a = t;
      r === "string" && or(t[0]) && (a = t.map(function(u) {
        return du(u);
      }));
      var s = i.write(a, e, r), o = new K(e, r, s, this.nextTensorId());
      if (this.incRef(o, i), r === "string") {
        var c = this.state.tensorInfo.get(s), l = gf(a);
        this.state.numBytes += l - c.bytes, c.bytes = l;
      }
      return o;
    }, n.prototype.makeTensorFromDataId = function(t, e, r, i) {
      r = r || "float32";
      var a = new K(e, r, t, this.nextTensorId());
      return this.incRef(a, i), a;
    }, n.prototype.makeVariable = function(t, e, r, i) {
      e === void 0 && (e = true), r = r || this.nextVariableId().toString(), i != null && i !== t.dtype && (t = t.cast(i));
      var a = new La(t, e, r, this.nextTensorId());
      if (this.state.registeredVariables[a.name] != null)
        throw new Error("Variable with name " + a.name + " was already registered");
      return this.state.registeredVariables[a.name] = a, this.incRef(a, this.backend), a;
    }, n.prototype.incRef = function(t, e) {
      var r = this.state.tensorInfo.has(t.dataId) ? this.state.tensorInfo.get(t.dataId).refCount : 0;
      if (this.state.numTensors++, t.dtype === "string" && this.state.numStringTensors++, r === 0) {
        this.state.numDataBuffers++;
        var i = 0;
        t.dtype !== "complex64" && t.dtype !== "string" && (i = t.size * mf(t.dtype)), this.state.tensorInfo.set(t.dataId, {backend: e || this.backend, dtype: t.dtype, shape: t.shape, bytes: i, refCount: 0}), this.state.numBytes += i;
      }
      this.state.tensorInfo.get(t.dataId).refCount++, t instanceof La || this.track(t);
    }, n.prototype.disposeTensor = function(t) {
      if (!this.state.tensorInfo.has(t.dataId))
        return;
      this.state.numTensors--, t.dtype === "string" && this.state.numStringTensors--;
      var e = this.state.tensorInfo.get(t.dataId), r = e.refCount;
      r <= 1 ? (t.dtype !== "complex64" && (this.state.numBytes -= e.bytes), this.state.numDataBuffers--, e.backend.disposeData(t.dataId), this.state.tensorInfo.delete(t.dataId)) : this.state.tensorInfo.get(t.dataId).refCount--;
    }, n.prototype.disposeVariables = function() {
      for (var t in this.state.registeredVariables) {
        var e = this.state.registeredVariables[t];
        this.disposeVariable(e);
      }
    }, n.prototype.disposeVariable = function(t) {
      this.disposeTensor(t), this.state.registeredVariables[t.name] != null && delete this.state.registeredVariables[t.name];
    }, n.prototype.memory = function() {
      var t = this.backend.memory();
      return t.numTensors = this.state.numTensors, t.numDataBuffers = this.state.numDataBuffers, t.numBytes = this.state.numBytes, this.state.numStringTensors > 0 && (t.unreliable = true, t.reasons == null && (t.reasons = []), t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")), t;
    }, n.prototype.profile = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r, i, a, s, o, c, l;
        return fe(this, function(u) {
          switch (u.label) {
            case 0:
              return this.state.profiling = true, e = this.state.numBytes, r = this.state.numTensors, this.state.activeProfile.kernels = [], i = this.state.activeProfile, [4, t()];
            case 1:
              i.result = u.sent(), this.state.profiling = false, this.state.activeProfile.peakBytes = Math.max.apply(Math, this.state.activeProfile.kernels.map(function(h) {
                return h.totalBytesSnapshot;
              })), this.state.activeProfile.newBytes = this.state.numBytes - e, this.state.activeProfile.newTensors = this.state.numTensors - r, a = 0, s = this.state.activeProfile.kernels, u.label = 2;
            case 2:
              return a < s.length ? (o = s[a], c = o, [4, o.kernelTimeMs]) : [3, 6];
            case 3:
              return c.kernelTimeMs = u.sent(), l = o, [4, o.extraInfo];
            case 4:
              l.extraInfo = u.sent(), u.label = 5;
            case 5:
              return a++, [3, 2];
            case 6:
              return [2, this.state.activeProfile];
          }
        });
      });
    }, n.prototype.isTapeOn = function() {
      return this.state.gradientDepth > 0 && this.state.kernelDepth === 0;
    }, n.prototype.addTapeNode = function(t, e, r, i, a, s) {
      var o = this, c = {id: this.state.nextTapeNodeId++, kernelName: t, inputs: e, outputs: r, saved: a}, l = hu(t);
      l != null && (i = l.gradFunc), i != null && (c.gradient = function(u) {
        return u = u.map(function(h, d) {
          if (h == null) {
            var p = r[d], f = Li(p.size, p.dtype);
            return o.makeTensor(f, p.shape, p.dtype);
          }
          return h;
        }), i(u.length > 1 ? u : u[0], a, s);
      }), this.state.activeTape.push(c);
    }, n.prototype.keep = function(t) {
      return t.kept = true, t;
    }, n.prototype.startTape = function() {
      this.state.gradientDepth === 0 && (this.state.activeTape = []), this.state.gradientDepth++;
    }, n.prototype.endTape = function() {
      this.state.gradientDepth--;
    }, n.prototype.startScope = function(t) {
      var e = {track: [], name: "unnamed scope", id: this.state.nextScopeId++};
      t && (e.name = t), this.state.scopeStack.push(e), this.state.activeScope = e;
    }, n.prototype.endScope = function(t) {
      for (var e = this, r = bu(t), i = new Set(r.map(function(c) {
        return c.id;
      })), a = 0; a < this.state.activeScope.track.length; a++) {
        var s = this.state.activeScope.track[a];
        !s.kept && !i.has(s.id) && s.dispose();
      }
      var o = this.state.scopeStack.pop();
      this.state.activeScope = this.state.scopeStack.length === 0 ? null : this.state.scopeStack[this.state.scopeStack.length - 1], r.forEach(function(c) {
        !c.kept && c.scopeId === o.id && e.track(c);
      });
    }, n.prototype.gradients = function(t, e, r, i) {
      var a = this;
      if (i === void 0 && (i = false), E(e.length > 0, function() {
        return "gradients() received an empty list of xs.";
      }), r != null && r.dtype !== "float32")
        throw new Error("dy must have 'float32' dtype, but has '" + r.dtype + "'");
      var s = this.scopedRun(function() {
        return a.startTape();
      }, function() {
        return a.endTape();
      }, function() {
        return a.tidy("forward", t);
      });
      E(s instanceof K, function() {
        return "The result y returned by f() must be a tensor.";
      });
      var o = GL(this.state.activeTape, e, s);
      if (!i && o.length === 0 && e.length > 0)
        throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");
      return this.tidy("backward", function() {
        var c = {};
        c[s.id] = r == null ? tS(s.shape) : r, qL(c, o, function(u) {
          return a.tidy(u);
        }, nS);
        var l = e.map(function(u) {
          return c[u.id];
        });
        return a.state.gradientDepth === 0 && (a.state.activeTape.forEach(function(u) {
          for (var h = 0, d = u.saved; h < d.length; h++) {
            var p = d[h];
            p.dispose();
          }
        }), a.state.activeTape = null), {value: s, grads: l};
      });
    }, n.prototype.customGrad = function(t) {
      var e = this;
      return E(cr(t), function() {
        return "The f passed in customGrad(f) must be a function.";
      }), function() {
        for (var r = [], i = 0; i < arguments.length; i++)
          r[i] = arguments[i];
        E(r.every(function(o) {
          return o instanceof K;
        }), function() {
          return "The args passed in customGrad(f)(x1, x2,...) must all be tensors";
        });
        var a, s = {};
        return r.forEach(function(o, c) {
          s[c] = o;
        }), e.runKernelFunc(function(o, c) {
          return a = t.apply(void 0, r.concat([c])), E(a.value instanceof K, function() {
            return "The function f passed in customGrad(f) must return an object where `obj.value` is a tensor";
          }), E(cr(a.gradFunc), function() {
            return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function.";
          }), a.value;
        }, s, function(o, c) {
          var l = a.gradFunc(o, c), u = Array.isArray(l) ? l : [l];
          E(u.length === r.length, function() {
            return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...).";
          }), E(u.every(function(d) {
            return d instanceof K;
          }), function() {
            return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.";
          });
          var h = {};
          return u.forEach(function(d, p) {
            h[p] = function() {
              return d;
            };
          }), h;
        });
      };
    }, n.prototype.readSync = function(t) {
      var e = this.state.tensorInfo.get(t);
      return e.backend.readSync(t);
    }, n.prototype.read = function(t) {
      var e = this.state.tensorInfo.get(t);
      return e.backend.read(t);
    }, n.prototype.time = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r;
        return fe(this, function(i) {
          switch (i.label) {
            case 0:
              return e = pu(), [4, this.backend.time(t)];
            case 1:
              return r = i.sent(), r.wallMs = pu() - e, [2, r];
          }
        });
      });
    }, n.prototype.track = function(t) {
      return this.state.activeScope != null && (t.scopeId = this.state.activeScope.id, this.state.activeScope.track.push(t)), t;
    }, Object.defineProperty(n.prototype, "registeredVariables", {get: function() {
      return this.state.registeredVariables;
    }, enumerable: true, configurable: true}), n.prototype.reset = function() {
      this.pendingBackendInitId++, this.state.dispose(), this.ENV.reset(), this.state = new Nm();
      for (var t in this.registry)
        this.disposeRegisteredKernels(t), this.registry[t].dispose(), delete this.registry[t];
      this.backendName = null, this.backendInstance = null, this.pendingBackendInit = null;
    }, n.nextTensorId = 0, n.nextVariableId = 0, n;
  }();
  function tS(n) {
    var t = yc(pt(n), "float32");
    return z.makeTensor(t, n, "float32");
  }
  function _m() {
    var n = Lf();
    if (n._tfengine == null) {
      var t = new xf(n);
      n._tfengine = new rS(t);
    }
    return OL(n._tfengine.ENV), jL(function() {
      return n._tfengine;
    }), n._tfengine;
  }
  var z = _m();
  function nS(n, t) {
    var e = {a: n, b: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.add(n, t);
      return i([n, t]), a;
    }, e, null, Rs);
  }
  function iS() {
    return typeof navigator != "undefined" && navigator != null;
  }
  function aS() {
    if (iS()) {
      var n = navigator.userAgent || navigator.vendor || window.opera;
      return /(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(n) || /1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(n.substr(0, 4));
    }
    return false;
  }
  function Cm() {
    return typeof window != "undefined" && window.document != null || typeof WorkerGlobalScope != "undefined";
  }
  var sS = {__proto__: null, isMobile: aS, isBrowser: Cm};
  var Yn = Ge();
  Yn.registerFlag("DEBUG", function() {
    return false;
  }, function(n) {
    n && console.warn("Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.");
  });
  Yn.registerFlag("IS_BROWSER", function() {
    return Cm();
  });
  Yn.registerFlag("IS_NODE", function() {
    return typeof process != "undefined" && typeof process.versions != "undefined" && typeof process.versions.node != "undefined";
  });
  Yn.registerFlag("IS_CHROME", function() {
    return typeof navigator != "undefined" && navigator != null && navigator.userAgent != null && /Chrome/.test(navigator.userAgent) && /Google Inc/.test(navigator.vendor);
  });
  Yn.registerFlag("PROD", function() {
    return false;
  });
  Yn.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY", function() {
    return Yn.getBool("DEBUG");
  });
  Yn.registerFlag("DEPRECATION_WARNINGS_ENABLED", function() {
    return true;
  });
  Yn.registerFlag("IS_TEST", function() {
    return false;
  });
  function On(n, t) {
    var e = n;
    if (Ft(n))
      return t === "string" ? [] : [n.length];
    if (!Array.isArray(n))
      return [];
    for (var r = []; Array.isArray(e) || Ft(e) && t !== "string"; )
      r.push(e.length), e = e[0];
    return Array.isArray(n) && Ge().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY") && Rm(n, r, []), r;
  }
  function Rm(n, t, e) {
    if (e = e || [], !Array.isArray(n) && !Ft(n)) {
      E(t.length === 0, function() {
        return "Element arr[" + e.join("][") + "] is a primitive, " + ("but should be an array/TypedArray of " + t[0] + " elements");
      });
      return;
    }
    E(t.length > 0, function() {
      return "Element arr[" + e.join("][") + "] should be a primitive, " + ("but is an array of " + n.length + " elements");
    }), E(n.length === t[0], function() {
      return "Element arr[" + e.join("][") + "] should have " + t[0] + " " + ("elements, but has " + n.length + " elements");
    });
    for (var r = t.slice(1), i = 0; i < n.length; ++i)
      Rm(n[i], r, e.concat(i));
  }
  function Om(n, t, e, r) {
    if (n == null)
      return;
    if (n !== "numeric" && n !== t || n === "numeric" && t === "string")
      throw new Error("Argument '" + e + "' passed to '" + r + "' must " + ("be " + n + " tensor, but got " + t + " tensor"));
  }
  function R(n, t, e, r) {
    if (r === void 0 && (r = "numeric"), n instanceof K)
      return Om(r, n.dtype, t, e), n;
    var i = _s(n);
    if (i !== "string" && ["bool", "int32", "float32"].indexOf(r) >= 0 && (i = r), Om(r, i, t, e), n == null || !Ft(n) && !Array.isArray(n) && typeof n != "number" && typeof n != "boolean" && typeof n != "string") {
      var a = n == null ? "null" : n.constructor.name;
      throw new Error("Argument '" + t + "' passed to '" + e + "' must be a " + ("Tensor or TensorLike, but got '" + a + "'"));
    }
    var s = On(n, i);
    !Ft(n) && !Array.isArray(n) && (n = [n]);
    var o = true, c = i !== "string" ? Ds(n, i) : Br(n, [], o);
    return z.makeTensor(c, s, i);
  }
  function Sa(n, t, e, r) {
    if (r === void 0 && (r = "numeric"), !Array.isArray(n))
      throw new Error("Argument " + t + " passed to " + e + " must be a `Tensor[]` or `TensorLike[]`");
    var i = n;
    return i.map(function(a, s) {
      return R(a, t + "[" + s + "]", e);
    }, r);
  }
  var Em = "__op";
  function U(n) {
    var t = Object.keys(n);
    if (t.length !== 1)
      throw new Error("Please provide an object with a single key (operation name) mapping to a function. Got an object with " + (t.length + " keys."));
    var e = t[0], r = n[e];
    e.endsWith("_") && (e = e.substring(0, e.length - 1)), e = e + Em;
    var i = function() {
      for (var a = [], s = 0; s < arguments.length; s++)
        a[s] = arguments[s];
      z.startScope(e);
      try {
        var o = r.apply(void 0, a);
        return wc(o) && console.error("Cannot return a Promise inside of tidy."), z.endScope(o), o;
      } catch (c) {
        throw z.endScope(null), c;
      }
    };
    return Object.defineProperty(i, "name", {value: e, configurable: true}), i;
  }
  function oS(n, t) {
    var e = R(n, "real", "complex"), r = R(t, "imag", "complex");
    Pe(e.shape, r.shape, "real and imag shapes, " + e.shape + " and " + r.shape + ", must match in call to tf.complex().");
    var i = function(s) {
      return s.complex(e, r);
    }, a = {real: e, imag: r};
    return z.runKernelFunc(i, a, null, _f);
  }
  var lr = U({complex_: oS});
  function ur(n, t, e, r) {
    if (r == null && (r = _s(n)), r === "complex64")
      throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");
    if (!Ft(n) && !Array.isArray(n) && typeof n != "number" && typeof n != "boolean" && typeof n != "string")
      throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");
    if (t != null) {
      vc(t);
      var i = pt(t), a = pt(e);
      E(i === a, function() {
        return "Based on the provided shape, [" + t + "], the tensor should have " + (i + " values but has " + a);
      });
      for (var s = 0; s < e.length; ++s) {
        var o = e[s], c = s === e.length - 1 ? o !== pt(t.slice(s)) : true;
        E(e[s] === t[s] || !c, function() {
          return "Error creating a new Tensor. Inferred shape " + ("(" + e + ") does not match the provided ") + ("shape (" + t + "). ");
        });
      }
    }
    return !Ft(n) && !Array.isArray(n) && (n = [n]), t = t || e, n = r !== "string" ? Ds(n, r) : Br(n, [], true), z.makeTensor(n, t, r);
  }
  function hr(n, t, e) {
    var r = On(n, e);
    return ur(n, t, r, e);
  }
  var xu = {float32: 4, float16: 2, int32: 4, uint16: 2, uint8: 1, bool: 1, complex64: 8};
  var Us = 4;
  function lS(n, t) {
    return pe(this, void 0, void 0, function() {
      var e, r, i, a, s, o, c = this;
      return fe(this, function(l) {
        switch (l.label) {
          case 0:
            for (e = [], r = [], i = Array.isArray(n) ? n.map(function(u) {
              return u.name;
            }) : Object.keys(n), a = function(u) {
              var h = i[u], d = Array.isArray(n) ? n[u].tensor : n[h];
              if (d.dtype !== "float32" && d.dtype !== "int32" && d.dtype !== "bool" && d.dtype !== "string" && d.dtype !== "complex64")
                throw new Error("Unsupported dtype in weight '" + h + "': " + d.dtype);
              var p = {name: h, shape: d.shape, dtype: d.dtype};
              if (d.dtype === "string") {
                var f = new Promise(function(m) {
                  return pe(c, void 0, void 0, function() {
                    var g, y, w, b, L, x, N;
                    return fe(this, function(I) {
                      switch (I.label) {
                        case 0:
                          return [4, d.bytes()];
                        case 1:
                          for (g = I.sent(), y = g.reduce(function(C, O) {
                            return C + O.length;
                          }, 0) + Us * g.length, w = new Uint8Array(y), b = 0, L = 0; L < g.length; L++)
                            x = g[L], N = new Uint8Array(new Uint32Array([x.length]).buffer), w.set(N, b), b += Us, w.set(x, b), b += x.length;
                          return m(w), [2];
                      }
                    });
                  });
                });
                r.push(f);
              } else
                r.push(d.data());
              t != null && (p.group = t), e.push(p);
            }, s = 0; s < i.length; ++s)
              a(s);
            return [4, Promise.all(r)];
          case 1:
            return o = l.sent(), [2, {data: cS(o), specs: e}];
        }
      });
    });
  }
  function Dm(n, t) {
    for (var e = {}, r, i = 0, a = 0, s = t; a < s.length; a++) {
      var o = s[a], c = o.name, l = o.dtype, u = o.shape, h = pt(u), d = void 0;
      if ("quantization" in o) {
        var p = o.quantization;
        if (p.dtype === "uint8" || p.dtype === "uint16") {
          if (!("min" in p && "scale" in p))
            throw new Error("Weight " + o.name + " with quantization " + p.dtype + " doesn't have corresponding metadata min and scale.");
        } else if (p.dtype === "float16") {
          if (l !== "float32")
            throw new Error("Weight " + o.name + " is quantized with " + p.dtype + " " + ("which only supports weights of type float32 not " + l + "."));
        } else
          throw new Error("Weight " + o.name + " has unknown " + ("quantization dtype " + p.dtype + ". ") + "Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.");
        var f = xu[p.dtype], m = n.slice(i, i + h * f), g = p.dtype === "uint8" ? new Uint8Array(m) : new Uint16Array(m);
        if (l === "float32")
          if (p.dtype === "uint8" || p.dtype === "uint16") {
            d = new Float32Array(g.length);
            for (var y = 0; y < g.length; y++) {
              var w = g[y];
              d[y] = w * p.scale + p.min;
            }
          } else if (p.dtype === "float16")
            r === void 0 && (r = uS()), d = r(g);
          else
            throw new Error("Unsupported quantization type " + p.dtype + " for weight type float32.");
        else if (l === "int32") {
          if (p.dtype !== "uint8" && p.dtype !== "uint16")
            throw new Error("Unsupported quantization type " + p.dtype + " for weight type int32.");
          d = new Int32Array(g.length);
          for (var y = 0; y < g.length; y++) {
            var w = g[y];
            d[y] = Math.round(w * p.scale + p.min);
          }
        } else
          throw new Error("Unsupported dtype in weight '" + c + "': " + l);
        i += h * f;
      } else if (l === "string") {
        var b = pt(o.shape);
        d = [];
        for (var y = 0; y < b; y++) {
          var L = new Uint32Array(n.slice(i, i + Us))[0];
          i += Us;
          var x = new Uint8Array(n.slice(i, i + L));
          d.push(x), i += L;
        }
      } else {
        var N = xu[l], m = n.slice(i, i + h * N);
        if (l === "float32")
          d = new Float32Array(m);
        else if (l === "int32")
          d = new Int32Array(m);
        else if (l === "bool")
          d = new Uint8Array(m);
        else if (l === "complex64") {
          d = new Float32Array(m);
          for (var I = new Float32Array(d.length / 2), C = new Float32Array(d.length / 2), y = 0; y < I.length; y++)
            I[y] = d[y * 2], C[y] = d[y * 2 + 1];
          var O = hr(I, u, "float32"), D = hr(C, u, "float32");
          e[c] = lr(O, D), O.dispose(), D.dispose();
        } else
          throw new Error("Unsupported dtype in weight '" + c + "': " + l);
        i += h * N;
      }
      l !== "complex64" && (e[c] = hr(d, u, l));
    }
    return e;
  }
  function cS(n) {
    if (n === null)
      throw new Error("Invalid input value: " + JSON.stringify(n));
    var t = 0, e = [];
    n.forEach(function(a) {
      if (t += a.byteLength, e.push(a.byteLength === a.buffer.byteLength ? a : new a.constructor(a)), !(a instanceof Float32Array || a instanceof Int32Array || a instanceof Uint8Array))
        throw new Error("Unsupported TypedArray subtype: " + a.constructor.name);
    });
    var r = new Uint8Array(t), i = 0;
    return e.forEach(function(a) {
      r.set(new Uint8Array(a.buffer), i), i += a.byteLength;
    }), r.buffer;
  }
  var Lu = typeof Buffer != "undefined" && (typeof Blob == "undefined" || typeof atob == "undefined" || typeof btoa == "undefined");
  function km(n) {
    return Lu ? Buffer.byteLength(n) : new Blob([n]).size;
  }
  function hS(n) {
    if (Lu)
      return Buffer.from(n).toString("base64");
    for (var t = new Uint8Array(n), e = "", r = 0, i = t.length; r < i; r++)
      e += String.fromCharCode(t[r]);
    return btoa(e);
  }
  function dS(n) {
    if (Lu) {
      var t = Buffer.from(n, "base64");
      return t.buffer.slice(t.byteOffset, t.byteOffset + t.byteLength);
    }
    for (var e = atob(n), r = new Uint8Array(e.length), i = 0; i < e.length; ++i)
      r.set([e.charCodeAt(i)], i);
    return r.buffer;
  }
  function Su(n) {
    if (n.length === 1)
      return n[0];
    var t = 0;
    n.forEach(function(i) {
      t += i.byteLength;
    });
    var e = new Uint8Array(t), r = 0;
    return n.forEach(function(i) {
      e.set(new Uint8Array(i), r), r += i.byteLength;
    }), e.buffer;
  }
  function Fm(n) {
    var t = "/";
    for (n = n.trim(); n.endsWith(t); )
      n = n.slice(0, n.length - 1);
    var e = n.split(t);
    return e[e.length - 1];
  }
  function Ia(n) {
    if (n.modelTopology instanceof ArrayBuffer)
      throw new Error("Expected JSON model topology, received ArrayBuffer.");
    return {dateSaved: new Date(), modelTopologyType: "JSON", modelTopologyBytes: n.modelTopology == null ? 0 : km(JSON.stringify(n.modelTopology)), weightSpecsBytes: n.weightSpecs == null ? 0 : km(JSON.stringify(n.weightSpecs)), weightDataBytes: n.weightData == null ? 0 : n.weightData.byteLength};
  }
  function pS() {
    var n = function(r) {
      for (var i = r << 13, a = 0; (i & 8388608) === 0; )
        a -= 8388608, i <<= 1;
      return i &= ~8388608, a += 947912704, i | a;
    }, t = new Uint32Array(2048);
    t[0] = 0;
    for (var e = 1; e < 1024; e++)
      t[e] = n(e);
    for (var e = 1024; e < 2048; e++)
      t[e] = 939524096 + (e - 1024 << 13);
    return t;
  }
  function fS() {
    var n = new Uint32Array(64);
    n[0] = 0, n[31] = 1199570944, n[32] = 2147483648, n[63] = 3347054592;
    for (var t = 1; t < 31; t++)
      n[t] = t << 23;
    for (var t = 33; t < 63; t++)
      n[t] = 2147483648 + (t - 32 << 23);
    return n;
  }
  function mS() {
    for (var n = new Uint32Array(64), t = 0; t < 64; t++)
      n[t] = 1024;
    return n[0] = n[32] = 0, n;
  }
  function uS() {
    var n = pS(), t = fS(), e = mS();
    return function(r) {
      for (var i = new ArrayBuffer(4 * r.length), a = new Uint32Array(i), s = 0; s < r.length; s++) {
        var o = r[s], c = n[e[o >> 10] + (o & 1023)] + t[o >> 10];
        a[s] = c;
      }
      return new Float32Array(i);
    };
  }
  var rn = function() {
    function n() {
      this.saveRouters = [], this.loadRouters = [];
    }
    return n.getInstance = function() {
      return n.instance == null && (n.instance = new n()), n.instance;
    }, n.registerSaveRouter = function(t) {
      n.getInstance().saveRouters.push(t);
    }, n.registerLoadRouter = function(t) {
      n.getInstance().loadRouters.push(t);
    }, n.getSaveHandlers = function(t) {
      return n.getHandlers(t, "save");
    }, n.getLoadHandlers = function(t, e) {
      return n.getHandlers(t, "load", e);
    }, n.getHandlers = function(t, e, r) {
      var i = [], a = e === "load" ? n.getInstance().loadRouters : n.getInstance().saveRouters;
      return a.forEach(function(s) {
        var o = s(t, r);
        o !== null && i.push(o);
      }), i;
    }, n;
  }(), gS = function(n) {
    return rn.registerSaveRouter(n);
  }, yS = function(n) {
    return rn.registerLoadRouter(n);
  }, vS = function(n) {
    return rn.getSaveHandlers(n);
  }, wS = function(n, t) {
    return rn.getLoadHandlers(n, t);
  };
  var Iu = "tensorflowjs", Au = 1, zr = "models_store", dr = "model_info_store";
  function Wm() {
    if (!Ge().getBool("IS_BROWSER"))
      throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");
    var n = typeof window == "undefined" ? self : window, t = n.indexedDB || n.mozIndexedDB || n.webkitIndexedDB || n.msIndexedDB || n.shimIndexedDB;
    if (t == null)
      throw new Error("The current browser does not appear to support IndexedDB.");
    return t;
  }
  function Tu(n) {
    var t = n.result;
    t.createObjectStore(zr, {keyPath: "modelPath"}), t.createObjectStore(dr, {keyPath: "modelPath"});
  }
  var Ai = function() {
    function n(t) {
      if (this.indexedDB = Wm(), t == null || !t)
        throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");
      this.modelPath = t;
    }
    return n.prototype.save = function(t) {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(e) {
          if (t.modelTopology instanceof ArrayBuffer)
            throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");
          return [2, this.databaseAction(this.modelPath, t)];
        });
      });
    }, n.prototype.load = function() {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(t) {
          return [2, this.databaseAction(this.modelPath)];
        });
      });
    }, n.prototype.databaseAction = function(t, e) {
      var r = this;
      return new Promise(function(i, a) {
        var s = r.indexedDB.open(Iu, Au);
        s.onupgradeneeded = function() {
          return Tu(s);
        }, s.onsuccess = function() {
          var o = s.result;
          if (e == null) {
            var c = o.transaction(zr, "readonly"), l = c.objectStore(zr), u = l.get(r.modelPath);
            u.onsuccess = function() {
              if (u.result == null)
                return o.close(), a(new Error("Cannot find model with path '" + r.modelPath + "' in IndexedDB."));
              i(u.result.modelArtifacts);
            }, u.onerror = function(g) {
              return o.close(), a(u.error);
            }, c.oncomplete = function() {
              return o.close();
            };
          } else {
            var h = Ia(e), d = o.transaction(dr, "readwrite"), p = d.objectStore(dr), f = p.put({modelPath: r.modelPath, modelArtifactsInfo: h}), m;
            f.onsuccess = function() {
              m = o.transaction(zr, "readwrite");
              var g = m.objectStore(zr), y = g.put({modelPath: r.modelPath, modelArtifacts: e, modelArtifactsInfo: h});
              y.onsuccess = function() {
                return i({modelArtifactsInfo: h});
              }, y.onerror = function(w) {
                p = d.objectStore(dr);
                var b = p.delete(r.modelPath);
                b.onsuccess = function() {
                  return o.close(), a(y.error);
                }, b.onerror = function(L) {
                  return o.close(), a(y.error);
                };
              };
            }, f.onerror = function(g) {
              return o.close(), a(f.error);
            }, d.oncomplete = function() {
              m == null ? o.close() : m.oncomplete = function() {
                return o.close();
              };
            };
          }
        }, s.onerror = function(o) {
          return a(s.error);
        };
      });
    }, n.URL_SCHEME = "indexeddb://", n;
  }(), Um = function(n) {
    return Ge().getBool("IS_BROWSER") && (!Array.isArray(n) && n.startsWith(Ai.URL_SCHEME)) ? bS(n.slice(Ai.URL_SCHEME.length)) : null;
  };
  rn.registerSaveRouter(Um);
  rn.registerLoadRouter(Um);
  function bS(n) {
    return new Ai(n);
  }
  function xS(n) {
    return n.startsWith(Ai.URL_SCHEME) ? n.slice(Ai.URL_SCHEME.length) : n;
  }
  var LS = function() {
    function n() {
      this.indexedDB = Wm();
    }
    return n.prototype.listModels = function() {
      return pe(this, void 0, void 0, function() {
        var t = this;
        return fe(this, function(e) {
          return [2, new Promise(function(r, i) {
            var a = t.indexedDB.open(Iu, Au);
            a.onupgradeneeded = function() {
              return Tu(a);
            }, a.onsuccess = function() {
              var s = a.result, o = s.transaction(dr, "readonly"), c = o.objectStore(dr), l = c.getAll();
              l.onsuccess = function() {
                for (var u = {}, h = 0, d = l.result; h < d.length; h++) {
                  var p = d[h];
                  u[p.modelPath] = p.modelArtifactsInfo;
                }
                r(u);
              }, l.onerror = function(u) {
                return s.close(), i(l.error);
              }, o.oncomplete = function() {
                return s.close();
              };
            }, a.onerror = function(s) {
              return i(a.error);
            };
          })];
        });
      });
    }, n.prototype.removeModel = function(t) {
      return pe(this, void 0, void 0, function() {
        var e = this;
        return fe(this, function(r) {
          return t = xS(t), [2, new Promise(function(i, a) {
            var s = e.indexedDB.open(Iu, Au);
            s.onupgradeneeded = function() {
              return Tu(s);
            }, s.onsuccess = function() {
              var o = s.result, c = o.transaction(dr, "readwrite"), l = c.objectStore(dr), u = l.get(t), h;
              u.onsuccess = function() {
                if (u.result == null)
                  return o.close(), a(new Error("Cannot find model with path '" + t + "' in IndexedDB."));
                var d = l.delete(t), p = function() {
                  h = o.transaction(zr, "readwrite");
                  var f = h.objectStore(zr), m = f.delete(t);
                  m.onsuccess = function() {
                    return i(u.result.modelArtifactsInfo);
                  }, m.onerror = function(g) {
                    return a(u.error);
                  };
                };
                d.onsuccess = p, d.onerror = function(f) {
                  return p(), o.close(), a(u.error);
                };
              }, u.onerror = function(d) {
                return o.close(), a(u.error);
              }, c.oncomplete = function() {
                h == null ? o.close() : h.oncomplete = function() {
                  return o.close();
                };
              };
            }, s.onerror = function(o) {
              return a(s.error);
            };
          })];
        });
      });
    }, n;
  }();
  var Kn = "/", Ti = "tensorflowjs_models", Bm = "info", SS = "model_topology", IS = "weight_specs", AS = "weight_data", TS = "model_metadata";
  function zm(n) {
    return {info: [Ti, n, Bm].join(Kn), topology: [Ti, n, SS].join(Kn), weightSpecs: [Ti, n, IS].join(Kn), weightData: [Ti, n, AS].join(Kn), modelMetadata: [Ti, n, TS].join(Kn)};
  }
  function NS(n) {
    var t = n.split(Kn);
    if (t.length < 3)
      throw new Error("Invalid key format: " + n);
    return t.slice(1, t.length - 1).join(Kn);
  }
  function _S(n) {
    return n.startsWith(Ni.URL_SCHEME) ? n.slice(Ni.URL_SCHEME.length) : n;
  }
  var Ni = function() {
    function n(t) {
      if (!Ge().getBool("IS_BROWSER") || typeof window == "undefined" || typeof window.localStorage == "undefined")
        throw new Error("The current environment does not support local storage.");
      if (this.LS = window.localStorage, t == null || !t)
        throw new Error("For local storage, modelPath must not be null, undefined or empty.");
      this.modelPath = t, this.keys = zm(this.modelPath);
    }
    return n.prototype.save = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r, i;
        return fe(this, function(a) {
          if (t.modelTopology instanceof ArrayBuffer)
            throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");
          e = JSON.stringify(t.modelTopology), r = JSON.stringify(t.weightSpecs), i = Ia(t);
          try {
            return this.LS.setItem(this.keys.info, JSON.stringify(i)), this.LS.setItem(this.keys.topology, e), this.LS.setItem(this.keys.weightSpecs, r), this.LS.setItem(this.keys.weightData, hS(t.weightData)), this.LS.setItem(this.keys.modelMetadata, JSON.stringify({format: t.format, generatedBy: t.generatedBy, convertedBy: t.convertedBy, userDefinedMetadata: t.userDefinedMetadata})), [2, {modelArtifactsInfo: i}];
          } catch (s) {
            throw this.LS.removeItem(this.keys.info), this.LS.removeItem(this.keys.topology), this.LS.removeItem(this.keys.weightSpecs), this.LS.removeItem(this.keys.weightData), this.LS.removeItem(this.keys.modelMetadata), new Error("Failed to save model '" + this.modelPath + "' to local storage: size quota being exceeded is a possible cause of this failure: " + ("modelTopologyBytes=" + i.modelTopologyBytes + ", ") + ("weightSpecsBytes=" + i.weightSpecsBytes + ", ") + ("weightDataBytes=" + i.weightDataBytes + "."));
          }
          return [2];
        });
      });
    }, n.prototype.load = function() {
      return pe(this, void 0, void 0, function() {
        var t, e, r, i, a, s, o;
        return fe(this, function(c) {
          if (t = JSON.parse(this.LS.getItem(this.keys.info)), t == null)
            throw new Error("In local storage, there is no model with name '" + this.modelPath + "'");
          if (t.modelTopologyType !== "JSON")
            throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");
          if (e = {}, r = JSON.parse(this.LS.getItem(this.keys.topology)), r == null)
            throw new Error("In local storage, the topology of model '" + this.modelPath + "' is missing.");
          if (e.modelTopology = r, i = JSON.parse(this.LS.getItem(this.keys.weightSpecs)), i == null)
            throw new Error("In local storage, the weight specs of model '" + this.modelPath + "' are missing.");
          if (e.weightSpecs = i, a = this.LS.getItem(this.keys.modelMetadata), a != null && (s = JSON.parse(a), e.format = s.format, e.generatedBy = s.generatedBy, e.convertedBy = s.convertedBy, e.userDefinedMetadata = s.userDefinedMetadata), o = this.LS.getItem(this.keys.weightData), o == null)
            throw new Error("In local storage, the binary weight values of model " + ("'" + this.modelPath + "' are missing."));
          return e.weightData = dS(o), [2, e];
        });
      });
    }, n.URL_SCHEME = "localstorage://", n;
  }(), Pm = function(n) {
    return Ge().getBool("IS_BROWSER") && (!Array.isArray(n) && n.startsWith(Ni.URL_SCHEME)) ? CS(n.slice(Ni.URL_SCHEME.length)) : null;
  };
  rn.registerSaveRouter(Pm);
  rn.registerLoadRouter(Pm);
  function CS(n) {
    return new Ni(n);
  }
  var RS = function() {
    function n() {
      E(Ge().getBool("IS_BROWSER"), function() {
        return "Current environment is not a web browser";
      }), E(typeof window == "undefined" || typeof window.localStorage != "undefined", function() {
        return "Current browser does not appear to support localStorage";
      }), this.LS = window.localStorage;
    }
    return n.prototype.listModels = function() {
      return pe(this, void 0, void 0, function() {
        var t, e, r, i, a, s;
        return fe(this, function(o) {
          for (t = {}, e = Ti + Kn, r = Kn + Bm, i = 0; i < this.LS.length; ++i)
            a = this.LS.key(i), a.startsWith(e) && a.endsWith(r) && (s = NS(a), t[s] = JSON.parse(this.LS.getItem(a)));
          return [2, t];
        });
      });
    }, n.prototype.removeModel = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r;
        return fe(this, function(i) {
          if (t = _S(t), e = zm(t), this.LS.getItem(e.info) == null)
            throw new Error("Cannot find model at path '" + t + "'");
          return r = JSON.parse(this.LS.getItem(e.info)), this.LS.removeItem(e.info), this.LS.removeItem(e.topology), this.LS.removeItem(e.weightSpecs), this.LS.removeItem(e.weightData), [2, r];
        });
      });
    }, n;
  }();
  var _i = "://", pr = function() {
    function n() {
      this.managers = {};
    }
    return n.getInstance = function() {
      return n.instance == null && (n.instance = new n()), n.instance;
    }, n.registerManager = function(t, e) {
      E(t != null, function() {
        return "scheme must not be undefined or null.";
      }), t.endsWith(_i) && (t = t.slice(0, t.indexOf(_i))), E(t.length > 0, function() {
        return "scheme must not be an empty string.";
      });
      var r = n.getInstance();
      E(r.managers[t] == null, function() {
        return "A model store manager is already registered for scheme '" + t + "'.";
      }), r.managers[t] = e;
    }, n.getManager = function(t) {
      var e = this.getInstance().managers[t];
      if (e == null)
        throw new Error("Cannot find model manager for scheme '" + t + "'");
      return e;
    }, n.getSchemes = function() {
      return Object.keys(this.getInstance().managers);
    }, n;
  }();
  function Bs(n) {
    if (n.indexOf(_i) === -1)
      throw new Error("The url string provided does not contain a scheme. Supported schemes are: " + ("" + pr.getSchemes().join(",")));
    return {scheme: n.split(_i)[0], path: n.split(_i)[1]};
  }
  function Mm(n, t, e) {
    return e === void 0 && (e = false), pe(this, void 0, void 0, function() {
      var r, i, a, s, o, c, l, u, h;
      return fe(this, function(d) {
        switch (d.label) {
          case 0:
            return E(n !== t, function() {
              return "Old path and new path are the same: '" + n + "'";
            }), r = rn.getLoadHandlers(n), E(r.length > 0, function() {
              return "Copying failed because no load handler is found for source URL " + n + ".";
            }), E(r.length < 2, function() {
              return "Copying failed because more than one (" + r.length + ") " + ("load handlers for source URL " + n + ".");
            }), i = r[0], a = rn.getSaveHandlers(t), E(a.length > 0, function() {
              return "Copying failed because no save handler is found for destination " + ("URL " + t + ".");
            }), E(a.length < 2, function() {
              return "Copying failed because more than one (" + r.length + ") " + ("save handlers for destination URL " + t + ".");
            }), s = a[0], o = Bs(n).scheme, c = Bs(n).path, l = o === Bs(n).scheme, [4, i.load()];
          case 1:
            return u = d.sent(), e && l ? [4, pr.getManager(o).removeModel(c)] : [3, 3];
          case 2:
            d.sent(), d.label = 3;
          case 3:
            return [4, s.save(u)];
          case 4:
            return h = d.sent(), e && !l ? [4, pr.getManager(o).removeModel(c)] : [3, 6];
          case 5:
            d.sent(), d.label = 6;
          case 6:
            return [2, h.modelArtifactsInfo];
        }
      });
    });
  }
  function OS() {
    return pe(this, void 0, void 0, function() {
      var n, t, e, r, i, a, s, o;
      return fe(this, function(c) {
        switch (c.label) {
          case 0:
            n = pr.getSchemes(), t = {}, e = 0, r = n, c.label = 1;
          case 1:
            return e < r.length ? (i = r[e], [4, pr.getManager(i).listModels()]) : [3, 4];
          case 2:
            a = c.sent();
            for (s in a)
              o = i + _i + s, t[o] = a[s];
            c.label = 3;
          case 3:
            return e++, [3, 1];
          case 4:
            return [2, t];
        }
      });
    });
  }
  function ES(n) {
    return pe(this, void 0, void 0, function() {
      var t, e;
      return fe(this, function(r) {
        return t = Bs(n), e = pr.getManager(t.scheme), [2, e.removeModel(t.path)];
      });
    });
  }
  function DS(n, t) {
    return pe(this, void 0, void 0, function() {
      var e;
      return fe(this, function(r) {
        return e = false, [2, Mm(n, t, e)];
      });
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  }
  function kS(n, t) {
    return pe(this, void 0, void 0, function() {
      var e;
      return fe(this, function(r) {
        return e = true, [2, Mm(n, t, e)];
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  }
  var FS = function() {
    function n() {
    }
    return n.prototype.fetch = function(t, e) {
      return fetch(t, e);
    }, n.prototype.now = function() {
      return performance.now();
    }, n.prototype.encode = function(t, e) {
      if (e !== "utf-8" && e !== "utf8")
        throw new Error("Browser's encoder only supports utf-8, but got " + e);
      return this.textEncoder == null && (this.textEncoder = new TextEncoder()), this.textEncoder.encode(t);
    }, n.prototype.decode = function(t, e) {
      return new TextDecoder(e).decode(t);
    }, n;
  }();
  if (Ge().get("IS_BROWSER")) {
    Ge().setPlatform("browser", new FS());
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      pr.registerManager(Ai.URL_SCHEME, new LS());
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    function n() {
      this.util = sf(), this.textEncoder = new this.util.TextEncoder();
    }
    return n.prototype.fetch = function(t, e) {
      return Ge().global.fetch != null ? Ge().global.fetch(t, e) : (Nu == null && (Nu = WS.importFetch()), Nu(t, e));
    }, n.prototype.now = function() {
      var t = process.hrtime();
      return t[0] * 1e3 + t[1] / 1e6;
    }, n.prototype.encode = function(t, e) {
      if (e !== "utf-8" && e !== "utf8")
        throw new Error("Node built-in encoder only supports utf-8, but got " + e);
      return this.textEncoder.encode(t);
    }, n.prototype.decode = function(t, e) {
      return t.length === 0 ? "" : new this.util.TextDecoder(e).decode(t);
    }, n;
  }();
  Ge().get("IS_NODE") && Ge().setPlatform("node", new US());
  function En(n, t, e) {
    return t === void 0 && (t = "float32"), t = t || "float32", vc(n), new Fs(n, t, e);
  }
  function BS(n, t) {
    var e = R(n, "x", "cast");
    if (!pf(t))
      throw new Error("Failed to cast to unknown dtype " + t);
    if (t === "string" && e.dtype !== "string" || t !== "string" && e.dtype === "string")
      throw new Error("Only strings can be casted to strings");
    var r = {x: e}, i = {dtype: t};
    return z.runKernelFunc(function(a) {
      return a.cast(e, t);
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  var he = U({cast_: BS});
  function zS(n) {
    var t = R(n, "x", "clone", null), e = function() {
      return z.makeTensorFromDataId(t.dataId, t.shape, t.dtype);
    }, r = {x: t};
    return z.runKernelFunc(e, r, null, il);
  }
  var Pr = U({clone_: zS});
  function Hm(n, t) {
    t === void 0 && (t = false), console.log(n.toString(t));
  }
  _m();
  var PS = {buffer: En, cast: he, clone: Pr, print: Hm};
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  var MS = "model", HS = ".json", VS = ".weights.bin";
  function Vm(n) {
    return new Promise(function(t) {
      return setTimeout(t);
    }).then(n);
  }
  var _u = function() {
    function n(t) {
      if (!Ge().getBool("IS_BROWSER"))
        throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");
      t.startsWith(n.URL_SCHEME) && (t = t.slice(n.URL_SCHEME.length)), (t == null || t.length === 0) && (t = MS), this.modelTopologyFileName = t + HS, this.weightDataFileName = t + VS;
    }
    return n.prototype.save = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r, i, a, s, o;
        return fe(this, function(c) {
          switch (c.label) {
            case 0:
              if (typeof document == "undefined")
                throw new Error("Browser downloads are not supported in this environment since `document` is not present");
              if (e = window.URL.createObjectURL(new Blob([t.weightData], {type: "application/octet-stream"})), !(t.modelTopology instanceof ArrayBuffer))
                return [3, 1];
              throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");
            case 1:
              return r = [{paths: ["./" + this.weightDataFileName], weights: t.weightSpecs}], i = {modelTopology: t.modelTopology, format: t.format, generatedBy: t.generatedBy, convertedBy: t.convertedBy, weightsManifest: r}, a = window.URL.createObjectURL(new Blob([JSON.stringify(i)], {type: "application/json"})), s = this.jsonAnchor == null ? document.createElement("a") : this.jsonAnchor, s.download = this.modelTopologyFileName, s.href = a, [4, Vm(function() {
                return s.dispatchEvent(new MouseEvent("click"));
              })];
            case 2:
              return c.sent(), t.weightData != null ? (o = this.weightDataAnchor == null ? document.createElement("a") : this.weightDataAnchor, o.download = this.weightDataFileName, o.href = e, [4, Vm(function() {
                return o.dispatchEvent(new MouseEvent("click"));
              })]) : [3, 4];
            case 3:
              c.sent(), c.label = 4;
            case 4:
              return [2, {modelArtifactsInfo: Ia(t)}];
          }
        });
      });
    }, n.URL_SCHEME = "downloads://", n;
  }(), GS = function() {
    function n(t) {
      if (t == null || t.length < 1)
        throw new Error("When calling browserFiles, at least 1 file is required, " + ("but received " + t));
      this.files = t;
    }
    return n.prototype.load = function() {
      return pe(this, void 0, void 0, function() {
        var t, e, r = this;
        return fe(this, function(i) {
          return t = this.files[0], e = this.files.slice(1), [2, new Promise(function(a, s) {
            var o = new FileReader();
            o.onload = function(c) {
              var l = JSON.parse(c.target.result), u = l.modelTopology;
              if (u == null) {
                s(new Error("modelTopology field is missing from file " + t.name));
                return;
              }
              e.length === 0 && a({modelTopology: u});
              var h = l.weightsManifest;
              if (h == null) {
                s(new Error("weightManifest field is missing from file " + t.name));
                return;
              }
              var d;
              try {
                d = r.checkManifestAndWeightFiles(h, e);
              } catch (g) {
                s(g);
                return;
              }
              var p = [], f = [], m = [];
              h.forEach(function(g) {
                g.paths.forEach(function(y) {
                  f.push(y), m.push(null);
                }), p.push.apply(p, g.weights);
              }), h.forEach(function(g) {
                g.paths.forEach(function(y) {
                  var w = new FileReader();
                  w.onload = function(b) {
                    var L = b.target.result, x = f.indexOf(y);
                    m[x] = L, m.indexOf(null) === -1 && a({modelTopology: u, weightSpecs: p, weightData: Su(m), format: l.format, generatedBy: l.generatedBy, convertedBy: l.convertedBy, userDefinedMetadata: l.userDefinedMetadata});
                  }, w.onerror = function(b) {
                    return s("Failed to weights data from file of path '" + y + "'.");
                  }, w.readAsArrayBuffer(d[y]);
                });
              });
            }, o.onerror = function(c) {
              return s("Failed to read model topology and weights manifest JSON " + ("from file '" + t.name + "'. BrowserFiles supports loading ") + "Keras-style tf.Model artifacts only.");
            }, o.readAsText(t);
          })];
        });
      });
    }, n.prototype.checkManifestAndWeightFiles = function(t, e) {
      for (var r = [], i = e.map(function(l) {
        return Fm(l.name);
      }), a = {}, s = 0, o = t; s < o.length; s++) {
        var c = o[s];
        c.paths.forEach(function(l) {
          var u = Fm(l);
          if (r.indexOf(u) !== -1)
            throw new Error("Duplicate file basename found in weights manifest: " + ("'" + u + "'"));
          if (r.push(u), i.indexOf(u) === -1)
            throw new Error("Weight file with basename '" + u + "' is not provided.");
          a[l] = e[i.indexOf(u)];
        });
      }
      if (r.length !== e.length)
        throw new Error("Mismatch in the number of files in weights manifest " + ("(" + r.length + ") and the number of weight files provided ") + ("(" + e.length + ")."));
      return a;
    }, n;
  }(), YS = function(n) {
    return Ge().getBool("IS_BROWSER") && (!Array.isArray(n) && n.startsWith(_u.URL_SCHEME)) ? qS(n.slice(_u.URL_SCHEME.length)) : null;
  };
  rn.registerSaveRouter(YS);
  function qS(n) {
    return n === void 0 && (n = "model"), new _u(n);
  }
  function KS(n) {
    return new GS(n);
  }
  function Gm(n, t, e, r) {
    s(n), e = e == null ? 0 : e, r = r == null ? 1 : r, o(e, r);
    var i = 0, a = function(c) {
      return c.then(function(l) {
        var u = e + ++i / n.length * (r - e);
        return t(u), l;
      }), c;
    };
    function s(c) {
      E(c != null && Array.isArray(c) && c.length > 0, function() {
        return "promises must be a none empty array";
      });
    }
    function o(c, l) {
      E(c >= 0 && c <= 1, function() {
        return "Progress fraction must be in range [0, 1], but " + ("got startFraction " + c);
      }), E(l >= 0 && l <= 1, function() {
        return "Progress fraction must be in range [0, 1], but " + ("got endFraction " + l);
      }), E(l >= c, function() {
        return "startFraction must be no more than endFraction, but " + ("got startFraction " + c + " and endFraction ") + ("" + l);
      });
    }
    return Promise.all(n.map(a));
  }
  function qm(n, t) {
    return pe(this, void 0, void 0, function() {
      var e, r, i, a, s, o, c, l, u, h, d;
      return fe(this, function(p) {
        switch (p.label) {
          case 0:
            return t == null && (t = {}), e = t.fetchFunc == null ? Ge().platform.fetch : t.fetchFunc, r = n.map(function(f) {
              return e(f, t.requestInit, {isBinary: true});
            }), i = 0, a = 0.5, t.onProgress == null ? [4, Promise.all(r)] : [3, 2];
          case 1:
            return o = p.sent(), [3, 4];
          case 2:
            return [4, Gm(r, t.onProgress, i, a)];
          case 3:
            o = p.sent(), p.label = 4;
          case 4:
            return s = o, c = s.map(function(f) {
              return f.arrayBuffer();
            }), l = 0.5, u = 1, t.onProgress == null ? [4, Promise.all(c)] : [3, 6];
          case 5:
            return d = p.sent(), [3, 8];
          case 6:
            return [4, Gm(c, t.onProgress, l, u)];
          case 7:
            d = p.sent(), p.label = 8;
          case 8:
            return h = d, [2, h];
        }
      });
    });
  }
  function jS(n, t, e, r) {
    return t === void 0 && (t = ""), pe(this, void 0, void 0, function() {
      var i, a;
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        return i = function(o) {
          return qm(o, {requestInit: r});
        }, a = Ym(i), [2, a(n, t, e)];
      });
    });
  }
  function Ym(n) {
    var t = this;
    return function(e, r, i) {
      return r === void 0 && (r = ""), pe(t, void 0, void 0, function() {
        var a, s, o, c, l, u, h, d, p, f;
        return fe(this, function(m) {
          switch (m.label) {
            case 0:
              if (a = e.map(function() {
                return false;
              }), s = {}, o = i != null ? i.map(function() {
                return false;
              }) : [], c = [], e.forEach(function(g, y) {
                var w = 0;
                g.weights.forEach(function(b) {
                  var L = "quantization" in b ? b.quantization.dtype : b.dtype, x = xu[L] * pt(b.shape), N = function() {
                    a[y] = true, s[y] == null && (s[y] = []), s[y].push({manifestEntry: b, groupOffset: w, sizeBytes: x});
                  };
                  i != null ? i.forEach(function(I, C) {
                    I === b.name && (N(), o[C] = true);
                  }) : N(), c.push(b.name), w += x;
                });
              }), !o.every(function(g) {
                return g;
              }))
                throw l = i.filter(function(g, y) {
                  return !o[y];
                }), new Error("Could not find weights in manifest with names: " + (l.join(", ") + `. 
`) + "Manifest JSON has weights with names: " + (c.join(", ") + "."));
              return u = a.reduce(function(g, y, w) {
                return y && g.push(w), g;
              }, []), h = [], u.forEach(function(g) {
                e[g].paths.forEach(function(y) {
                  var w = r + (r.endsWith("/") ? "" : "/") + y;
                  h.push(w);
                });
              }), [4, n(h)];
            case 1:
              return d = m.sent(), p = {}, f = 0, u.forEach(function(g) {
                for (var y = e[g].paths.length, w = 0, b = 0; b < y; b++)
                  w += d[f + b].byteLength;
                for (var L = new ArrayBuffer(w), x = new Uint8Array(L), N = 0, I = 0; I < y; I++) {
                  var C = new Uint8Array(d[f + I]);
                  x.set(C, N), N += C.byteLength;
                }
                var O = s[g];
                O.forEach(function(D) {
                  var F = L.slice(D.groupOffset, D.groupOffset + D.sizeBytes), k = Dm(F, [D.manifestEntry]);
                  for (var B in k)
                    p[B] = k[B];
                }), f += y;
              }), [2, p];
          }
        });
      });
    };
  }
  var $S = "application/octet-stream", XS = "application/json", Km = function() {
    function n(t, e) {
      if (this.DEFAULT_METHOD = "POST", e == null && (e = {}), this.weightPathPrefix = e.weightPathPrefix, this.onProgress = e.onProgress, this.weightUrlConverter = e.weightUrlConverter, e.fetchFunc != null ? (E(typeof e.fetchFunc == "function", function() {
        return "Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)";
      }), this.fetch = e.fetchFunc) : this.fetch = Ge().platform.fetch, E(t != null && t.length > 0, function() {
        return "URL path for http must not be null, undefined or empty.";
      }), Array.isArray(t) && E(t.length === 2, function() {
        return "URL paths for http must have a length of 2, " + ("(actual length is " + t.length + ").");
      }), this.path = t, e.requestInit != null && e.requestInit.body != null)
        throw new Error("requestInit is expected to have no pre-existing body, but has one.");
      this.requestInit = e.requestInit || {};
    }
    return n.prototype.save = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r, i, a;
        return fe(this, function(s) {
          switch (s.label) {
            case 0:
              if (t.modelTopology instanceof ArrayBuffer)
                throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");
              return e = Object.assign({method: this.DEFAULT_METHOD}, this.requestInit), e.body = new FormData(), r = [{paths: ["./model.weights.bin"], weights: t.weightSpecs}], i = {modelTopology: t.modelTopology, format: t.format, generatedBy: t.generatedBy, convertedBy: t.convertedBy, userDefinedMetadata: t.userDefinedMetadata, weightsManifest: r}, e.body.append("model.json", new Blob([JSON.stringify(i)], {type: XS}), "model.json"), t.weightData != null && e.body.append("model.weights.bin", new Blob([t.weightData], {type: $S}), "model.weights.bin"), [4, this.fetch(this.path, e)];
            case 1:
              if (a = s.sent(), a.ok)
                return [2, {modelArtifactsInfo: Ia(t), responses: [a]}];
              throw new Error("BrowserHTTPRequest.save() failed due to HTTP response status " + (a.status + "."));
          }
        });
      });
    }, n.prototype.load = function() {
      return pe(this, void 0, void 0, function() {
        var t, e, r, i, a, s, o, c, l, u, h, d, p, f, m;
        return fe(this, function(g) {
          switch (g.label) {
            case 0:
              return [4, this.fetch(this.path, this.requestInit)];
            case 1:
              if (t = g.sent(), !t.ok)
                throw new Error("Request to " + this.path + " failed with status code " + (t.status + ". Please verify this URL points to ") + "the model JSON of the model to load.");
              g.label = 2;
            case 2:
              return g.trys.push([2, 4, , 5]), [4, t.json()];
            case 3:
              return e = g.sent(), [3, 5];
            case 4:
              throw r = g.sent(), i = "Failed to parse model JSON of response from " + this.path + ".", this.path.endsWith(".pb") ? i += " Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository." : i += " Please make sure the server is serving valid JSON for this request.", new Error(i);
            case 5:
              if (a = e.modelTopology, s = e.weightsManifest, o = e.generatedBy, c = e.convertedBy, l = e.format, u = e.userDefinedMetadata, a == null && s == null)
                throw new Error("The JSON from HTTP path " + this.path + " contains neither model topology or manifest for weights.");
              return s != null ? [4, this.loadWeights(s)] : [3, 7];
            case 6:
              p = g.sent(), h = p[0], d = p[1], g.label = 7;
            case 7:
              return f = {modelTopology: a, weightSpecs: h, weightData: d, userDefinedMetadata: u, generatedBy: o, convertedBy: c, format: l}, m = e.modelInitializer, m && (f.modelInitializer = m), [2, f];
          }
        });
      });
    }, n.prototype.loadWeights = function(t) {
      return pe(this, void 0, void 0, function() {
        var e, r, i, a, s, o, c, l, u, h, d, p, f, m, g, y, w, b, L, x, N;
        return fe(this, function(I) {
          switch (I.label) {
            case 0:
              for (e = Array.isArray(this.path) ? this.path[1] : this.path, r = JS(e), i = r[0], a = r[1], s = this.weightPathPrefix || i, o = [], c = 0, l = t; c < l.length; c++)
                u = l[c], o.push.apply(o, u.weights);
              for (h = [], d = [], p = 0, f = t; p < f.length; p++)
                for (m = f[p], g = 0, y = m.paths; g < y.length; g++)
                  w = y[g], this.weightUrlConverter != null ? d.push(this.weightUrlConverter(w)) : h.push(s + w + a);
              return this.weightUrlConverter ? (L = (b = h.push).apply, x = [h], [4, Promise.all(d)]) : [3, 2];
            case 1:
              L.apply(b, x.concat([I.sent()])), I.label = 2;
            case 2:
              return [4, qm(h, {requestInit: this.requestInit, fetchFunc: this.fetch, onProgress: this.onProgress})];
            case 3:
              return N = I.sent(), [2, [o, Su(N)]];
          }
        });
      });
    }, n.URL_SCHEME_REGEX = /^https?:\/\//, n;
  }();
  function JS(n) {
    var t = n.lastIndexOf("/"), e = n.lastIndexOf("?"), r = n.substring(0, t), i = e > t ? n.substring(e) : "";
    return [r + "/", i];
  }
  function Cu(n) {
    return n.match(Km.URL_SCHEME_REGEX) != null;
  }
  var jm = function(n, t) {
    if (typeof fetch == "undefined" && (t == null || t.fetchFunc == null))
      return null;
    var e = true;
    return Array.isArray(n) ? e = n.every(function(r) {
      return Cu(r);
    }) : e = Cu(n), e ? Ru(n, t) : null;
  };
  rn.registerSaveRouter(jm);
  rn.registerLoadRouter(jm);
  function Ru(n, t) {
    return new Km(n, t);
  }
  function ZS(n, t) {
    return Ru(n, t);
  }
  var Ou = function() {
    function n(t) {
      this.modelArtifacts = t;
    }
    return n.prototype.load = function() {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(t) {
          return [2, this.modelArtifacts];
        });
      });
    }, n;
  }(), QS = function() {
    function n(t) {
      this.saveHandler = t;
    }
    return n.prototype.save = function(t) {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(e) {
          return [2, this.saveHandler(t)];
        });
      });
    }, n;
  }();
  function eI(n, t, e, r) {
    if (arguments.length === 1) {
      var i = n.modelTopology != null || n.weightSpecs != null;
      return i ? new Ou(n) : (console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."), new Ou({modelTopology: n}));
    } else
      return console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."), new Ou({modelTopology: n, weightSpecs: t, weightData: e, trainingConfig: r});
  }
  function tI(n) {
    return new QS(n);
  }
  var nI = {__proto__: null, browserFiles: KS, browserHTTPRequest: ZS, concatenateArrayBuffers: Su, decodeWeights: Dm, encodeWeights: lS, fromMemory: eI, getLoadHandlers: wS, getModelArtifactsInfoForJSON: Ia, getSaveHandlers: vS, http: Ru, isHTTPScheme: Cu, loadWeights: jS, registerLoadRouter: yS, registerSaveRouter: gS, weightsLoaderFactory: Ym, withSaveHandler: tI, copyModel: DS, listModels: OS, moveModel: kS, removeModel: ES};
  function rI(n, t) {
    var e = R(n, "x", "reshape", null), r = {x: e}, i = {shape: t}, a = function(s, o) {
      return t = lf(t, e.size), E(e.size === pt(t), function() {
        return "new shape and old shape must have the same number of elements.";
      }), o([e]), s.reshape(e, t);
    };
    return z.runKernelFunc(a, r, null, Cl, i);
  }
  var Y = U({reshape_: rI});
  function iI(n, t, e, r) {
    var i;
    e === void 0 && (e = false), r === void 0 && (r = false);
    var a = R(n, "a", "matMul"), s = R(t, "b", "matMul");
    i = ct(a, s), a = i[0], s = i[1];
    var o = function(u, h) {
      h([a, s]);
      var d = e ? a.shape[a.rank - 2] : a.shape[a.rank - 1], p = r ? s.shape[s.rank - 1] : s.shape[s.rank - 2], f = e ? a.shape[a.rank - 1] : a.shape[a.rank - 2], m = r ? s.shape[s.rank - 2] : s.shape[s.rank - 1], g = a.shape.slice(0, -2), y = s.shape.slice(0, -2), w = pt(g), b = pt(y), L = w === b || w === 1 || b === 1;
      E(a.rank >= 2 && s.rank >= 2 && L, function() {
        return "Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input " + ("batch dimensions of (" + g + ") and (" + y + ").");
      }), E(d === p, function() {
        return "Error in matMul: inner shapes (" + d + ") and (" + (p + ") of Tensors with shapes " + a.shape + " and ") + (s.shape + " and transposeA=" + e) + (" and transposeB=" + r + " must match.");
      });
      var x = w > b ? g : y, N = x.concat([f, m]), I = e ? Y(a, [w, d, f]) : Y(a, [w, f, d]), C = r ? Y(s, [b, m, p]) : Y(s, [b, p, m]), O = u.batchMatMul(I, C, e, r);
      return Y(O, N);
    }, c = {a, b: s}, l = {transposeA: e, transposeB: r};
    return z.runKernelFunc(o, c, null, kc, l);
  }
  var Ue = U({matMul_: iI});
  function aI(n, t, e, r) {
    if (e === void 0 && (e = 1), r === void 0 && (r = 0), t < 2)
      throw new Error("Error in oneHot: depth must be >=2, but it is " + t);
    var i = R(n, "indices", "oneHot", "int32"), a = i.shape.concat([t]), s = function(l, u) {
      return u([i]), Y(l.oneHot(Y(i, [i.size]), t, e, r), a);
    }, o = {indices: i}, c = {depth: t, onValue: e, offValue: r};
    return z.runKernelFunc(s, o, null, Sl, c);
  }
  var zs = U({oneHot_: aI});
  function sI(n, t) {
    var e = R(n, "x", "transpose");
    if (t == null && (t = e.shape.map(function(a, s) {
      return s;
    }).reverse()), E(e.rank === t.length, function() {
      return "Error in transpose: rank of input " + e.rank + " " + ("must match length of perm " + t + ".");
    }), t.forEach(function(a) {
      E(a >= 0 && a < e.rank, function() {
        return "All entries in 'perm' must be between 0 and " + (e.rank - 1) + (" but got " + t);
      });
    }), e.rank <= 1)
      return e.clone();
    var r = {x: e}, i = {perm: t};
    return z.runKernelFunc(function(a) {
      return a.transpose(e, t);
    }, r, null, eu, i);
  }
  var Tt = U({transpose_: sI});
  function oI(n, t, e) {
    var r = R(n, "labels", "confusionMatrix"), i = R(t, "predictions", "confusionMatrix");
    E(e == null || e > 0 && Number.isInteger(e), function() {
      return "If provided, numClasses must be a positive integer, " + ("but got " + e);
    }), E(r.rank === 1, function() {
      return "Expected the rank of labels to be 1, but got " + r.rank;
    }), E(i.rank === 1, function() {
      return "Expected the rank of predictions to be 1, " + ("but got " + i.rank);
    }), E(r.shape[0] === i.shape[0], function() {
      return "Mismatch in the number of examples: " + (r.shape[0] + " vs. " + i.shape[0] + ". ") + "Labels and predictions should have the same number of elements.";
    }), E(e > 0 && Number.isInteger(e), function() {
      return "numClasses is required to be a positive integer, but got " + ("" + e);
    });
    var a = zs(he(r, "int32"), e), s = zs(he(i, "int32"), e), o = Tt(a), c = Ue(o, s);
    return he(c, "int32");
  }
  var cI = U({confusionMatrix_: oI});
  var lI = {__proto__: null, confusionMatrix: cI};
  function $m(n, t, e) {
    if (Ur(n), t != null && t.length !== 3)
      throw new Error("tensor3d() requires shape to have three numbers");
    var r = On(n, e);
    if (r.length !== 3 && r.length !== 1)
      throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");
    if (r.length === 1 && t == null)
      throw new Error("tensor3d() requires shape to be provided when `values` are a flat array");
    return ur(n, t, r, e);
  }
  var Ci;
  function uI(n, t) {
    if (t === void 0 && (t = 3), t > 4)
      throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");
    if (n == null)
      throw new Error("pixels passed to tf.browser.fromPixels() can not be null");
    var e = false, r = false, i = false, a = false, s = false;
    if (n.data instanceof Uint8Array)
      e = true;
    else if (typeof ImageData != "undefined" && n instanceof ImageData)
      r = true;
    else if (typeof HTMLVideoElement != "undefined" && n instanceof HTMLVideoElement)
      i = true;
    else if (typeof HTMLImageElement != "undefined" && n instanceof HTMLImageElement)
      a = true;
    else if (n.getContext != null)
      s = true;
    else
      throw new Error("pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, " + ("but was " + n.constructor.name));
    if (i) {
      var o = 2;
      if (i && n.readyState < o)
        throw new Error("The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element.");
    }
    var c = uu(au, z.backendName);
    if (c != null) {
      var l = {pixels: n}, u = {numChannels: t};
      return z.runKernel(au, l, u);
    }
    var h = i ? [n.videoWidth, n.videoHeight] : [n.width, n.height], d = h[0], p = h[1], f;
    s ? f = n.getContext("2d").getImageData(0, 0, d, p).data : r || e ? f = n.data : (a || i) && (Ci == null && (Ci = document.createElement("canvas").getContext("2d")), Ci.canvas.width = d, Ci.canvas.height = p, Ci.drawImage(n, 0, 0, d, p), f = Ci.getImageData(0, 0, d, p).data);
    var m;
    if (t === 4)
      m = new Int32Array(f);
    else {
      var g = d * p;
      m = new Int32Array(g * t);
      for (var y = 0; y < g; y++)
        for (var w = 0; w < t; ++w)
          m[y * t + w] = f[y * 4 + w];
    }
    var b = [p, d, t];
    return $m(m, b, "int32");
  }
  function hI(n, t) {
    return pe(this, void 0, void 0, function() {
      var e, r, i, a, s, o, c, l, u, h, d, p, f, m, g, y;
      return fe(this, function(w) {
        switch (w.label) {
          case 0:
            if (e = R(n, "img", "toPixels"), n instanceof K || (r = e, e = he(r, "int32"), r.dispose()), e.rank !== 2 && e.rank !== 3)
              throw new Error("toPixels only supports rank 2 or 3 tensors, got rank " + e.rank + ".");
            if (i = e.shape.slice(0, 2), a = i[0], s = i[1], o = e.rank === 2 ? 1 : e.shape[2], o > 4 || o === 2)
              throw new Error("toPixels only supports depth of size " + ("1, 3 or 4 but got " + o));
            if (e.dtype !== "float32" && e.dtype !== "int32")
              throw new Error("Unsupported type for toPixels: " + e.dtype + ". Please use float32 or int32 tensors.");
            return [4, e.data()];
          case 1:
            for (c = w.sent(), l = e.dtype === "float32" ? 255 : 1, u = new Uint8ClampedArray(s * a * 4), h = 0; h < a * s; ++h) {
              for (d = [0, 0, 0, 255], p = 0; p < o; p++) {
                if (f = c[h * o + p], e.dtype === "float32") {
                  if (f < 0 || f > 1)
                    throw new Error("Tensor values for a float32 Tensor must be in the " + ("range [0 - 1] but encountered " + f + "."));
                } else if (e.dtype === "int32" && (f < 0 || f > 255))
                  throw new Error("Tensor values for a int32 Tensor must be in the " + ("range [0 - 255] but encountered " + f + "."));
                o === 1 ? (d[0] = f * l, d[1] = f * l, d[2] = f * l) : d[p] = f * l;
              }
              m = h * 4, u[m + 0] = Math.round(d[0]), u[m + 1] = Math.round(d[1]), u[m + 2] = Math.round(d[2]), u[m + 3] = Math.round(d[3]);
            }
            return t != null && (t.width = s, t.height = a, g = t.getContext("2d"), y = new ImageData(u, s, a), g.putImageData(y, 0, 0)), e !== n && e.dispose(), [2, u];
        }
      });
    });
  }
  var dI = U({fromPixels_: uI}), pI = {__proto__: null, toPixels: hI, fromPixels: dI};
  function Xm(n, t) {
    if (n.rank < 1)
      throw new Error("tf.gatherND() expects the input to be rank 1 or higher," + (" but the rank was " + n.rank + "."));
    if (t.rank < 1)
      throw new Error("tf.gatherND() expects the indices to be rank 1 or higher," + (" but the rank was " + t.rank + "."));
    if (t.dtype !== "int32")
      throw new Error("tf.gatherND() expects the indices to be int32 type," + (" but the dtype was " + t.dtype + "."));
    if (t.shape[t.rank - 1] > n.rank)
      throw new Error("index innermost dimension length must be <= tensor rank; saw: " + (t.shape[t.rank - 1] + " vs. " + n.rank));
    if (n.size === 0)
      throw new Error("Requested more than 0 entries, but input is empty." + (" Input shape: " + n.shape + "."));
    for (var e = t.shape, r = e[e.length - 1], i = 1, a = 0; a < e.length - 1; ++a)
      i *= e[a];
    var s = n.shape, o = e.slice();
    o.pop();
    for (var c = 1, a = r; a < n.rank; ++a)
      c *= s[a], o.push(s[a]);
    var l = bi(n.shape).map(function(u) {
      return u / c;
    }).concat([1]).slice(0, r);
    return [o, i, c, l];
  }
  var fI = {__proto__: null, prepareAndValidate: Xm};
  function Eu(n, t, e) {
    var r = t.rank > 1 ? t.shape[t.rank - 1] : 1, i = t.rank > 1 ? t.rank - 1 : 1, a = "Must have updates.shape = indices.shape[:batchDim] + " + ("shape[sliceDim:], got updates.shape: " + e.shape) + (", indices.shape: " + t.shape + ", shape: " + n) + (", sliceDim: " + r + ", and batchDim: " + i + ".");
    if (e.rank < i)
      throw new Error(a + (" update.rank < " + i + ". "));
    if (n.length < r + (e.rank - i))
      throw new Error(a + (" Output shape length < " + (r + (e.rank - i))));
    if (e.rank !== i + n.length - r)
      throw new Error(a + (" update.rank != " + (i + n.length - r)));
    for (var s = 0; s < i; ++s)
      if (e.shape[s] !== t.shape[s])
        throw new Error(a + (" updates.shape[" + s + "] (" + e.shape[s] + ") != indices.shape[" + s + "] (" + t.shape[s] + ")."));
    for (var s = 0; s < e.rank - i; ++s)
      if (e.shape[s + i] !== n[s + r])
        throw new Error(a + (" updates.shape[" + (s + i) + "] (" + e.shape[s + i] + ") != shape[" + (s + i) + "] (" + n[s + i] + ")"));
  }
  function Du(n, t, e) {
    if (t.rank < 1)
      throw new Error("tf.scatterND() expects the indices to be rank 1 or higher," + (" but the rank was " + t.rank + "."));
    if (n.rank < 1)
      throw new Error("tf.scatterND() expects the updates to be rank 1 or higher," + (" but the rank was " + n.rank + "."));
    if (t.dtype !== "int32")
      throw new Error("The dtype of 'indices' should be int32, but got dtype: " + t.dtype);
    if (e.length < 1)
      throw new Error("Output rank must be greater or equal to 1, but got shape: " + e);
    if (e.length === 0) {
      if (t.size === 0)
        throw new Error("Indices specified for empty output. indices shape: " + t.shape);
      if (n.size === 0)
        throw new Error("Updates specified for empty output. updates shape: " + n.shape);
    }
    Eu(e, t, n);
  }
  function Jm(n, t, e) {
    for (var r = t.shape.length, i = r > 1 ? t.shape[r - 1] : 1, a = e.length, s = 1, o = i; o < a; ++o)
      s *= e[o];
    var c = i < 1 ? 1 : i, l = pt(t.shape) / c, u = bi(e.slice(0, i)).concat([1]), h = pt(e);
    return {sliceRank: i, numUpdates: l, sliceSize: s, strides: u, outputSize: h};
  }
  var mI = {__proto__: null, validateUpdateShape: Eu, validateInput: Du, calculateShapes: Jm};
  function Zm(n, t, e) {
    var r = n.shape.length;
    E(r === t.length, function() {
      return "Error in slice" + r + "D: Length of begin " + t + " must " + ("match the rank of the array (" + r + ").");
    }), E(r === e.length, function() {
      return "Error in slice" + r + "D: Length of size " + e + " must " + ("match the rank of the array (" + r + ").");
    });
    for (var i = function(s) {
      E(t[s] + e[s] <= n.shape[s], function() {
        return "Error in slice" + r + "D: begin[" + s + "] + size[" + s + "] " + ("(" + (t[s] + e[s]) + ") would overflow input.shape[" + s + "] (" + n.shape[s] + ")");
      });
    }, a = 0; a < r; ++a)
      i(a);
  }
  function Ps(n) {
    for (var t = [], e = 0; n > 0; )
      n & 1 && t.push(e), n /= 2, e++;
    return t;
  }
  function Qm(n, t, e) {
    for (var r = [], i = 0; i < n.length; i++)
      r[i] = Math.ceil((t[i] - n[i]) / e[i]);
    return r;
  }
  function eg(n, t, e, r) {
    for (var i = n.slice(), a = i.length; a < r.length; a++)
      i.push(1);
    for (var a = 0; a < e; a++)
      a === 0 ? i[t] = 1 : (i.splice(t, 0, 1), i.pop());
    return i;
  }
  function tg(n, t, e) {
    return e <= n ? e : e - (t - 1);
  }
  function ng(n, t) {
    for (var e = [], r = 0; r < n; r++)
      e.push(t + r);
    return e;
  }
  function cg(n, t, e, r, i, a, s, o, c) {
    var l = n.length, u = new Array(l), h = new Array(l), d = new Array(l);
    if (t.length && e > 0) {
      var p = t[0], f = e + 1;
      u = rg(s, p, f, r, n), h = ig(o, p, f, i, n), d = eg(a, p, f, n);
    } else
      for (var m = 0; m < l; m++)
        u[m] = sg(s, r, a, n, m, c), h[m] = og(o, i, a, n, m, c), d[m] = ag(a, m, c);
    return {begin: u, end: h, strides: d};
  }
  function rg(n, t, e, r, i) {
    for (var a = i.slice(), s = ng(e, t), o = 0; o < a.length; o++)
      if (s.indexOf(o) > -1)
        a[o] = 0;
      else {
        var c = tg(t, e, o), l = r[c];
        n & 1 << c && (l = 0), a[o] = l;
      }
    return a;
  }
  function ig(n, t, e, r, i) {
    for (var a = i.slice(), s = ng(e, t), o = 0; o < a.length; o++)
      if (s.indexOf(o) > -1)
        a[o] = Number.MAX_SAFE_INTEGER;
      else {
        var c = tg(t, e, o), l = r[c];
        n & 1 << c && (l = Number.MAX_SAFE_INTEGER), a[o] = l;
      }
    for (var u = 0; u < a.length; u++) {
      var h = i[u];
      a[u] < 0 && (a[u] += h), a[u] = ga(0, a[u], i[u]);
    }
    return a;
  }
  function ag(n, t, e) {
    var r = n[t];
    return (e & 1 << t || r == null) && (r = 1), r;
  }
  function sg(n, t, e, r, i, a) {
    var s = t[i], o = e[i] || 1;
    (n & 1 << i || a & 1 << i || s == null) && (o > 0 ? s = Number.MIN_SAFE_INTEGER : s = Number.MAX_SAFE_INTEGER);
    var c = r[i];
    return s < 0 && (s += c), s = ga(0, s, c - 1), s;
  }
  function og(n, t, e, r, i, a) {
    var s = t[i], o = e[i] || 1;
    (n & 1 << i || a & 1 << i || s == null) && (o > 0 ? s = Number.MAX_SAFE_INTEGER : s = Number.MIN_SAFE_INTEGER);
    var c = r[i];
    return s < 0 && (s += c), o > 0 ? s = ga(0, s, c) : s = ga(-1, s, c - 1), s;
  }
  function gI(n, t, e) {
    for (var r = e.length, i = 0; i < e.length; i++)
      if (e[i] > 1) {
        r = i;
        break;
      }
    for (var i = r + 1; i < e.length; i++)
      if (t[i] > 0 || e[i] !== n[i])
        return false;
    return true;
  }
  function yI(n, t) {
    for (var e = n.length > 0 ? n[n.length - 1] : 1, r = 0; r < n.length - 1; r++)
      e += n[r] * t[r];
    return e;
  }
  function ku(n, t, e) {
    var r, i = n.shape.length;
    typeof t == "number" ? r = [t].concat(new Array(i - 1).fill(0)) : t.length < i ? r = t.concat(new Array(i - t.length).fill(0)) : r = t.slice(), r.forEach(function(s) {
      E(s !== -1, function() {
        return "slice() does not support negative begin indexing.";
      });
    });
    var a;
    return e == null ? a = new Array(i).fill(-1) : typeof e == "number" ? a = [e].concat(new Array(i - 1).fill(-1)) : e.length < i ? a = e.concat(new Array(i - e.length).fill(-1)) : a = e, a = a.map(function(s, o) {
      return s >= 0 ? s : (E(s === -1, function() {
        return "Negative size values should be exactly -1 but got " + (s + " for the slice() size at index " + o + ".");
      }), n.shape[o] - r[o]);
    }), [r, a];
  }
  var lg = {__proto__: null, assertParamsValid: Zm, maskToAxes: Ps, computeOutShape: Qm, stridesWithElidedDims: eg, getNormalizedAxes: cg, startIndicesWithElidedDims: rg, stopIndicesWithElidedDims: ig, stridesForAxis: ag, startForAxis: sg, stopForAxis: og, isSliceContinous: gI, computeFlatOffset: yI, parseSliceParams: ku};
  var ug = function() {
    function n() {
    }
    return n.prototype.getClassName = function() {
      return this.constructor.className;
    }, n.fromConfig = function(t, e) {
      return new t(e);
    }, n;
  }(), hg = function() {
    function n() {
      this.classNameMap = {};
    }
    return n.getMap = function() {
      return n.instance == null && (n.instance = new n()), n.instance;
    }, n.register = function(t) {
      n.getMap().classNameMap[t.className] = [t, t.fromConfig];
    }, n;
  }();
  function fr(n) {
    E(n.className != null, function() {
      return "Class being registered does not have the static className property defined.";
    }), E(typeof n.className == "string", function() {
      return "className is required to be a string, but got type " + typeof n.className;
    }), E(n.className.length > 0, function() {
      return "Class being registered has an empty-string as its className, which is disallowed.";
    }), hg.register(n);
  }
  var vI = {__proto__: null, Serializable: ug, SerializationMap: hg, registerClass: fr};
  var wI = 1e-3, dg = 0.1;
  function bI(n, t, e) {
    return e == null && (e = Fu()), Wu(n, t, function(r, i) {
      return Uu(r, i, e);
    });
  }
  function Fu() {
    return z.backend.floatPrecision() === 32 ? wI : dg;
  }
  function Wu(n, t, e) {
    var r = true;
    if ((Ft(n) || Ft(t)) && (r = false), Ft(n) && Ft(t) && (r = true), r) {
      var i = n.constructor.name, a = t.constructor.name;
      if (i !== a)
        throw new Error("Arrays are of different type. Actual: " + i + ". " + ("Expected: " + a));
    }
    if (Array.isArray(n) && Array.isArray(t)) {
      var s = On(n), o = On(t);
      if (!fn(s, o))
        throw new Error("Arrays have different shapes. " + ("Actual: [" + s + "]. Expected: [" + o + "]"));
    }
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      h = {top: N, bottom: I, left: C, right: O, front: L, back: x, type: "SAME"};
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        throw new Error("Unknown roundingMode " + t);
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    throw new Error("Unknown dataFormat " + n);
  }
  function mA(n, t, e, r, i) {
    var a = R(n, "x", "avgPool", "float32"), s = 1;
    E(Mt(e, s), function() {
      return "Error in avgPool: Either strides or dilations must be 1. " + ("Got strides " + e + " and dilations '" + s + "'");
    });
    var o = a, c = false;
    a.rank === 3 && (c = true, o = Y(a, [1, a.shape[0], a.shape[1], a.shape[2]])), E(o.rank === 4, function() {
      return "Error in avgPool: x must be rank 4 but got rank " + o.rank + ".";
    }), i != null && E(ot(r), function() {
      return "Error in avgPool: pad must be an integer when using, " + ("dimRoundingMode " + i + " but got pad " + r + ".");
    });
    var l = function(p, f) {
      var m = Ri(o.shape, t, e, 1, r, i);
      return f([o]), m.filterWidth === 1 && m.filterHeight === 1 && fn(m.inShape, m.outShape) ? o.clone() : p.avgPool(o, m);
    }, u = {x: o}, h = {filterSize: t, strides: e, pad: r, dimRoundingMode: i}, d = z.runKernelFunc(l, u, null, Ec, h);
    return d = he(d, a.dtype), c ? Y(d, [d.shape[1], d.shape[2], d.shape[3]]) : d;
  }
  var Hu = U({avgPool_: mA});
  function gA(n, t, e, r, i, a, s) {
    a === void 0 && (a = "NDHWC"), s == null ? s = [1, 1, 1] : Nt("dilations is deprecated, this field will be gone in v3.0.0.");
    var o = R(n, "x", "avgPool3d", "float32"), c = o, l = false;
    o.rank === 4 && (l = true, c = Y(o, [1, o.shape[0], o.shape[1], o.shape[2], o.shape[3]])), E(c.rank === 5, function() {
      return "Error in avgPool3d: x must be rank 5 but got rank " + c.rank + ".";
    }), E(a === "NDHWC", function() {
      return "Error in avgPool3d: Only NDHWC is currently supported, " + ("but got dataFormat of " + a);
    }), E(Mt(e, s), function() {
      return "Error in avgPool3d: Either strides or dilations must be 1. " + ("Got strides " + e + " and dilations '" + s + "'");
    }), i != null && E(ot(r), function() {
      return "Error in avgPool3d: pad must be an integer when using, " + ("dimRoundingMode " + i + " but got pad " + r + ".");
    });
    var u = function(f, m) {
      s == null && (s = [1, 1, 1]);
      var g = Na(c.shape, t, e, s, r, i, a);
      return m([c]), f.avgPool3d(c, g);
    }, h = {x: c}, d = {filterSize: t, strides: e, pad: r, dimRoundingMode: i, dataFormat: a, dilations: s}, p = z.runKernelFunc(u, h, null, Dc, d);
    return p = he(p, c.dtype), l ? Y(p, [p.shape[1], p.shape[2], p.shape[3], p.shape[4]]) : p;
  }
  var yA = U({avgPool3d_: gA});
  function Ng(n, t) {
    var e = n[0].length;
    n.forEach(function(i, a) {
      E(i.length === e, function() {
        return "Error in concat" + e + "D: rank of tensors[" + a + "] must be the same " + ("as the rank of the rest (" + e + ")");
      });
    }), E(t >= 0 && t < e, function() {
      return "Error in concat" + e + "D: axis must be between 0 and " + (e - 1) + ".";
    });
    var r = n[0];
    n.forEach(function(i, a) {
      for (var s = 0; s < e; s++)
        E(s === t || i[s] === r[s], function() {
          return "Error in concat" + e + "D: Shape of tensors[" + a + "] (" + i + ") " + ("does not match the shape of the rest (" + r + ") ") + ("along the non-concatenated axis " + a + ".");
        });
    });
  }
  function _g(n, t) {
    for (var e = n[0].slice(), r = 1; r < n.length; r++)
      e[t] += n[r][t];
    return e;
  }
  function vA(n, t) {
    t === void 0 && (t = 0), E(n.length >= 1, function() {
      return "Pass at least one tensor to concat";
    });
    var e = Sa(n, "tensors", "concat");
    e[0].dtype === "complex64" && e.forEach(function(s) {
      if (s.dtype !== "complex64")
        throw new Error(`Cannot concatenate complex64 tensors with a tensor
          with dtype ` + s.dtype + ". ");
    });
    var r = function(s, o) {
      var c = rt(t, e[0].shape)[0], l = _g(e.map(function(d) {
        return d.shape;
      }), c);
      if (pt(l) === 0)
        return hr([], l);
      if (e = e.filter(function(d) {
        return d.size > 0;
      }), e.length === 1)
        return e[0];
      var u = e.map(function(d) {
        return d.shape;
      });
      Ng(u, c);
      var h = s.concat(e, c);
      return o(e), h;
    }, i = e, a = {axis: t};
    return z.runKernelFunc(r, i, null, zc, a);
  }
  var Et = U({concat_: vA});
  function wA(n) {
    var t = R(n, "x", "sigmoid"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.sigmoid(t);
      return i([a]), a;
    }, e, null, Hl);
  }
  var Hr = U({sigmoid_: wA});
  function bA(n, t, e) {
    var r = R(n, "x", "slice");
    if (r.rank === 0)
      throw new Error("Slicing scalar is not possible");
    var i = function(o, c) {
      var l = ku(r, t, e), u = l[0], h = l[1];
      return Zm(r, u, h), c([r]), o.slice(r, u, h);
    }, a = {x: r}, s = {begin: t, size: e};
    return z.runKernelFunc(i, a, null, Bl, s);
  }
  var Me = U({slice_: bA});
  function xA(n) {
    var t = R(n, "x", "tanh"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.tanh(t);
      return i([a]), a;
    }, e, null, Zl);
  }
  var Vs = U({tanh_: xA});
  function LA(n, t, e, r, i, a) {
    var s = R(n, "forgetBias", "basicLSTMCell"), o = R(t, "lstmKernel", "basicLSTMCell"), c = R(e, "lstmBias", "basicLSTMCell"), l = R(r, "data", "basicLSTMCell"), u = R(i, "c", "basicLSTMCell"), h = R(a, "h", "basicLSTMCell"), d = Et([l, h], 1), p = Ue(d, o), f = ge(p, c), m = f.shape[0], g = f.shape[1] / 4, y = [m, g], w = Me(f, [0, 0], y), b = Me(f, [0, g], y), L = Me(f, [0, g * 2], y), x = Me(f, [0, g * 3], y), N = ge(Z(Hr(w), Vs(b)), Z(u, Hr(ge(s, L)))), I = Z(Vs(N), Hr(x));
    return [N, I];
  }
  var SA = U({basicLSTMCell_: LA});
  function IA(n, t, e) {
    var r = R(n, "x", "batchToSpaceND"), i = t.reduce(function(c, l) {
      return c * l;
    });
    E(r.rank >= 1 + t.length, function() {
      return "input rank is " + r.rank + " but should be > than blockShape.length " + t.length;
    }), E(e.length === t.length, function() {
      return "crops.length is " + e.length + " but should be equal to blockShape.length  " + t.length;
    }), E(r.shape[0] % i === 0, function() {
      return "input tensor batch is " + r.shape[0] + " but is not divisible by the product of " + ("the elements of blockShape " + t.join(" * ") + " === " + i);
    });
    var a = function(c) {
      return c.batchToSpaceND(r, t, e);
    }, s = {x: r}, o = {blockShape: t, crops: e};
    return z.runKernelFunc(a, s, null, Fc, o);
  }
  var Gs = U({batchToSpaceND_: IA});
  function AA(n) {
    var t;
    return n.rank === 0 || n.rank === 1 ? t = Y(n, [1, 1, 1, n.size]) : n.rank === 2 ? t = Y(n, [1, 1, n.shape[0], n.shape[1]]) : n.rank === 3 ? t = Y(n, [1, n.shape[0], n.shape[1], n.shape[2]]) : t = n, t;
  }
  function TA(n, t, e, r, i, a) {
    a == null && (a = 1e-3);
    var s = R(n, "x", "batchNorm"), o = R(t, "mean", "batchNorm"), c = R(e, "variance", "batchNorm"), l;
    i != null && (l = R(i, "scale", "batchNorm"));
    var u;
    r != null && (u = R(r, "offset", "batchNorm")), E(o.rank === c.rank, function() {
      return "Batch normalization gradient requires mean and variance to have equal ranks.";
    }), E(u == null || o.rank === u.rank, function() {
      return "Batch normalization gradient requires mean and offset to have equal ranks.";
    }), E(l == null || o.rank === l.rank, function() {
      return "Batch normalization gradient requires mean and scale to have equal ranks.";
    });
    var h = AA(s), d = function(g, y) {
      return y([h, o, c, l]), g.batchNorm(h, qs(o), qs(c), qs(u), qs(l), a);
    }, p = {x: h, scale: l, offset: u, mean: o, variance: c}, f = {varianceEpsilon: a}, m = z.runKernelFunc(d, p, null, tl, f);
    return Y(m, s.shape);
  }
  function qs(n) {
    return n == null ? null : n.rank === 0 ? Y(n, [n.size]) : n.rank === 1 ? n : n.rank === 2 ? Y(n, [1, 1, n.shape[0], n.shape[1]]) : n.rank === 3 ? Y(n, [1, n.shape[0], n.shape[1], n.shape[2]]) : n;
  }
  var _a = U({batchNorm_: TA});
  function NA(n, t, e, r, i, a) {
    var s = R(n, "x", "batchNorm"), o = R(t, "mean", "batchNorm"), c = R(e, "variance", "batchNorm"), l;
    i != null && (l = R(i, "scale", "batchNorm"));
    var u;
    return r != null && (u = R(r, "offset", "batchNorm")), E(s.rank === 2, function() {
      return "Error in batchNorm2D: x must be rank 2 but got rank " + (s.rank + ".");
    }), E(o.rank === 2 || o.rank === 1, function() {
      return "Error in batchNorm2D: mean must be rank 2 or rank 1 but " + ("got rank " + o.rank + ".");
    }), E(c.rank === 2 || c.rank === 1, function() {
      return "Error in batchNorm2D: variance must be rank 2 or rank 1 " + ("but got rank " + c.rank + ".");
    }), l != null && E(l.rank === 2 || l.rank === 1, function() {
      return "Error in batchNorm2D: scale must be rank 2 or rank 1 " + ("but got rank " + l.rank + ".");
    }), u != null && E(u.rank === 2 || u.rank === 1, function() {
      return "Error in batchNorm2D: offset must be rank 2 or rank 1 " + ("but got rank " + u.rank + ".");
    }), _a(s, o, c, u, l, a);
  }
  var _A = U({batchNorm2d_: NA});
  function CA(n, t, e, r, i, a) {
    var s = R(n, "x", "batchNorm"), o = R(t, "mean", "batchNorm"), c = R(e, "variance", "batchNorm"), l;
    i != null && (l = R(i, "scale", "batchNorm"));
    var u;
    return r != null && (u = R(r, "offset", "batchNorm")), E(s.rank === 3, function() {
      return "Error in batchNorm3D: x must be rank 3 but got rank " + (s.rank + ".");
    }), E(o.rank === 3 || o.rank === 1, function() {
      return "Error in batchNorm3D: mean must be rank 3 or rank 1 but " + ("got rank " + o.rank + ".");
    }), E(c.rank === 3 || c.rank === 1, function() {
      return "Error in batchNorm3D: variance must be rank 3 or rank 1 " + ("but got rank " + c.rank + ".");
    }), l != null && E(l.rank === 3 || l.rank === 1, function() {
      return "Error in batchNorm3D: scale must be rank 3 or rank 1 " + ("but got rank " + l.rank + ".");
    }), u != null && E(u.rank === 3 || u.rank === 1, function() {
      return "Error in batchNorm3D: offset must be rank 3 or rank 1 " + ("but got rank " + u.rank + ".");
    }), _a(s, o, c, u, l, a);
  }
  var RA = U({batchNorm3d_: CA});
  function OA(n, t, e, r, i, a) {
    var s = R(n, "x", "batchNorm"), o = R(t, "mean", "batchNorm"), c = R(e, "variance", "batchNorm"), l;
    i != null && (l = R(i, "scale", "batchNorm"));
    var u;
    return r != null && (u = R(r, "offset", "batchNorm")), E(s.rank === 4, function() {
      return "Error in batchNorm4D: x must be rank 4 but got rank " + (s.rank + ".");
    }), E(o.rank === 4 || o.rank === 1, function() {
      return "Error in batchNorm4D: mean must be rank 4 or rank 1 but " + ("got rank " + o.rank + ".");
    }), E(c.rank === 4 || c.rank === 1, function() {
      return "Error in batchNorm4D: variance must be rank 4 or rank 1 " + ("but got rank " + c.rank + ".");
    }), l != null && E(l.rank === 4 || l.rank === 1, function() {
      return "Error in batchNorm4D: scale must be rank 4 or rank 1 " + ("but got rank " + l.rank + ".");
    }), u != null && E(u.rank === 4 || u.rank === 1, function() {
      return "Error in batchNorm4D: offset must be rank 4 or rank 1 " + ("but got rank " + u.rank + ".");
    }), _a(s, o, c, u, l, a);
  }
  var EA = U({batchNorm4d_: OA});
  function DA(n, t) {
    var e = R(n, "broadcastTo", "x"), r = e.shape;
    if (t.some(function(d) {
      return !(d > 0) || d % 1 !== 0;
    }))
      throw new Error("broadcastTo(): Invalid broadcast shape [" + t + "].");
    if (t.length < e.rank)
      throw new Error("broadcastTo(): shape.length=" + t.length + " < input.rank=" + e.rank + ".");
    if (t.length > e.rank) {
      for (var i = e.shape.slice(); i.length < t.length; )
        i.unshift(1);
      e = Y(e, i);
    }
    for (var a = e.shape, s = Array.from(t), o = t.length - 1; o >= 0; o--)
      if (a[o] === t[o])
        s[o] = 1;
      else if (e.shape[o] !== 1)
        throw new Error("broadcastTo(): [" + r + "] cannot be broadcast to [" + t + "].");
    var c = s.map(function(d, p) {
      return d > 1 ? p : -1;
    }).filter(function(d) {
      return d >= 0;
    });
    if (c.length === 0)
      return Pr(e);
    var l = function(d) {
      return d.tile(e, s);
    }, u = {x: e}, h = {shape: t, inputShape: a};
    return z.runKernelFunc(l, u, null, Wc, h);
  }
  var Ys = U({broadcastTo_: DA});
  function kA(n) {
    var t = R(n, "x", "ceil"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.ceil(t);
    }, e, null, Uc);
  }
  var Cg = U({ceil_: kA});
  function FA(n, t, e) {
    var r = R(n, "x", "clipByValue");
    E(t <= e, function() {
      return "Error in clip: min (" + t + ") must be " + ("less than or equal to max (" + e + ").");
    });
    var i = {x: r}, a = {clipValueMin: t, clipValueMax: e};
    return z.runKernelFunc(function(s, o) {
      var c = s.clip(r, t, e);
      return o([r]), c;
    }, i, null, Bc, a);
  }
  var Rg = U({clipByValue_: FA});
  function WA(n) {
    return Et(n, 0);
  }
  var UA = U({concat1d_: WA});
  function BA(n, t) {
    return Et(n, t);
  }
  var zA = U({concat2d_: BA});
  function PA(n, t) {
    return Et(n, t);
  }
  var MA = U({concat3d_: PA});
  function HA(n, t) {
    return Et(n, t);
  }
  var VA = U({concat4d_: HA});
  function GA(n, t, e, r, i, a, s) {
    i === void 0 && (i = "NHWC"), a === void 0 && (a = [1, 1]);
    var o = R(n, "x", "conv2d"), c = R(t, "filter", "conv2d"), l = o, u = false;
    o.rank === 3 && (u = true, l = Y(o, [1, o.shape[0], o.shape[1], o.shape[2]])), E(l.rank === 4, function() {
      return "Error in conv2d: input must be rank 4, but got rank " + l.rank + ".";
    }), E(c.rank === 4, function() {
      return "Error in conv2d: filter must be rank 4, but got rank " + (c.rank + ".");
    }), s != null && E(ot(r), function() {
      return "Error in conv2d: pad must be an integer when using, " + ("dimRoundingMode " + s + " but got pad " + r + ".");
    });
    var h = i === "NHWC" ? l.shape[3] : l.shape[1];
    E(h === c.shape[2], function() {
      return "Error in conv2d: depth of input (" + h + ") must match " + ("input depth for filter " + c.shape[2] + ".");
    }), E(Mt(e, a), function() {
      return "Error in conv2D: Either strides or dilations must be 1. " + ("Got strides " + e + " and dilations '" + a + "'");
    });
    var d = function(g, y) {
      var w = Aa(i), b = gn(l.shape, c.shape, e, a, r, s, false, w), L = g.conv2d(l, c, b);
      return y([l, c]), L;
    }, p = {x: l, filter: c}, f = {strides: e, pad: r, dataFormat: i, dilations: a, dimRoundingMode: s}, m = z.runKernelFunc(d, p, null, Pc, f);
    return u ? Y(m, [m.shape[1], m.shape[2], m.shape[3]]) : m;
  }
  var Ei = U({conv2d_: GA});
  function qA(n, t, e, r, i, a, s) {
    i === void 0 && (i = "NWC"), a === void 0 && (a = 1);
    var o = R(n, "x", "conv1d"), c = R(t, "filter", "conv1d"), l = o, u = false;
    o.rank === 2 && (u = true, l = Y(o, [1, o.shape[0], o.shape[1]])), E(l.rank === 3, function() {
      return "Error in conv1d: input must be rank 3, but got rank " + l.rank + ".";
    }), E(c.rank === 3, function() {
      return "Error in conv1d: filter must be rank 3, but got rank " + (c.rank + ".");
    }), s != null && E(ot(r), function() {
      return "Error in conv1d: pad must be an integer when using, " + ("dimRoundingMode " + s + " but got pad " + r + ".");
    }), E(l.shape[2] === c.shape[1], function() {
      return "Error in conv1d: depth of input (" + l.shape[2] + ") must match " + ("input depth for filter " + c.shape[1] + ".");
    }), E(Mt(e, a), function() {
      return "Error in conv1D: Either stride or dilation must be 1. " + ("Got stride " + e + " and dilation '" + a + "'");
    }), E(i === "NWC", function() {
      return "Error in conv1d: got dataFormat of " + i + " but only NWC is currently supported.";
    });
    var h = Y(c, [1, c.shape[0], c.shape[1], c.shape[2]]), d = Y(l, [l.shape[0], 1, l.shape[1], l.shape[2]]), p = [1, e], f = [1, a], m = "NHWC", g = Ei(d, h, p, r, m, f, s);
    return u ? Y(g, [g.shape[2], g.shape[3]]) : Y(g, [g.shape[0], g.shape[2], g.shape[3]]);
  }
  var Og = U({conv1d_: qA});
  function YA(n, t, e, r, i, a, s) {
    a === void 0 && (a = "NHWC"), E(n.length === t.rank, function() {
      return "Length of inShape " + ("(" + n.length + ") and rank of dy (" + t.rank + ") must match");
    });
    var o = n, c = t, l = false;
    t.rank === 3 && (l = true, c = Y(t, [1, t.shape[0], t.shape[1], t.shape[2]]), o = [1, n[0], n[1], n[2]]), E(o.length === 4, function() {
      return "Error in conv2dDerInput: inShape must be length 4, but got length " + (o.length + ".");
    }), E(c.rank === 4, function() {
      return "Error in conv2dDerInput: dy must be rank 4, but got " + ("rank " + c.rank);
    }), E(e.rank === 4, function() {
      return "Error in conv2dDerInput: filter must be rank 4, but got " + ("rank " + e.rank);
    });
    var u = a === "NHWC" ? o[3] : o[1], h = a === "NHWC" ? c.shape[3] : c.shape[1];
    E(u === e.shape[2], function() {
      return "Error in conv2dDerInput: depth of input (" + u + ") must " + ("match input depth for filter " + e.shape[2] + ".");
    }), E(h === e.shape[3], function() {
      return "Error in conv2dDerInput: depth of output (" + h + ") must " + ("match output depth for filter " + e.shape[3] + ".");
    }), s != null && E(ot(i), function() {
      return "Error in conv2dDerInput: pad must be an integer when using, " + ("dimRoundingMode " + s + " but got pad " + i + ".");
    });
    var d = function(g, y) {
      var w = 1, b = Aa(a), L = gn(o, e.shape, r, w, i, s, false, b), x = g.conv2dDerInput(c, e, L);
      return y([c, e]), x;
    }, p = {dy: c, filter: e}, f = {strides: r, pad: i, dataFormat: a, dimRoundingMode: s, inputShape: o}, m = z.runKernelFunc(d, p, null, Mc, f);
    return l ? Y(m, [m.shape[1], m.shape[2], m.shape[3]]) : m;
  }
  var Vu = U({conv2DBackpropInput_: YA});
  function KA(n, t, e, r, i, a) {
    var s = R(n, "x", "conv2dTranspose"), o = R(t, "filter", "conv2dTranspose");
    return Vu(e, s, o, r, i, "NHWC", a);
  }
  var Eg = U({conv2dTranspose_: KA});
  function jA(n, t, e, r, i, a) {
    i === void 0 && (i = "NDHWC"), a === void 0 && (a = [1, 1, 1]);
    var s = R(n, "x", "conv3d"), o = R(t, "filter", "conv3d"), c = s, l = false;
    s.rank === 4 && (l = true, c = Y(s, [1, s.shape[0], s.shape[1], s.shape[2], s.shape[3]])), E(c.rank === 5, function() {
      return "Error in conv3d: input must be rank 5, but got rank " + c.rank + ".";
    }), E(o.rank === 5, function() {
      return "Error in conv3d: filter must be rank 5, but got rank " + (o.rank + ".");
    }), E(c.shape[4] === o.shape[3], function() {
      return "Error in conv3d: depth of input (" + c.shape[4] + ") must match " + ("input depth for filter " + o.shape[3] + ".");
    }), E(Mt(e, a), function() {
      return "Error in conv3D: Either strides or dilations must be 1. " + ("Got strides " + e + " and dilations '" + a + "'");
    }), E(i === "NDHWC", function() {
      return "Error in conv3d: got dataFormat of " + i + " but only NDHWC is currently supported.";
    });
    var u = function(f, m) {
      var g = Ta(c.shape, o.shape, e, a, r), y = f.conv3d(c, o, g);
      return m([c, o]), y;
    }, h = {x: c, filter: o}, d = {strides: e, pad: r, dataFormat: i, dilations: a}, p = z.runKernelFunc(u, h, null, Hc, d);
    return l ? Y(p, [p.shape[1], p.shape[2], p.shape[3], p.shape[4]]) : p;
  }
  var $A = U({conv3d_: jA});
  function XA(n, t, e, r, i) {
    E(n.length === t.rank, function() {
      return "Length of inShape " + ("(" + n.length + ") and rank of dy (" + t.rank + ") must match");
    });
    var a = n, s = t, o = false;
    t.rank === 4 && (o = true, s = Y(t, [1, t.shape[0], t.shape[1], t.shape[2], t.shape[3]]), a = [1, n[0], n[1], n[2], n[3]]);
    var c = a[4], l = s.shape[4];
    E(a.length === 5, function() {
      return "Error in conv3dDerInput: inShape must be length 5, but got length " + (a.length + ".");
    }), E(s.rank === 5, function() {
      return "Error in conv3dDerInput: dy must be rank 5, but got " + ("rank " + s.rank);
    }), E(e.rank === 5, function() {
      return "Error in conv3dDerInput: filter must be rank 5, but got " + ("rank " + e.rank);
    }), E(c === e.shape[3], function() {
      return "Error in conv3dDerInput: depth of input (" + c + ") must " + ("match input depth for filter " + e.shape[3] + ".");
    }), E(l === e.shape[4], function() {
      return "Error in conv3dDerInput: depth of output (" + l + ") must " + ("match output depth for filter " + e.shape[4] + ".");
    });
    var u = function(f) {
      var m = 1, g = Ta(a, e.shape, r, m, i);
      return f.conv3dDerInput(s, e, g);
    }, h = {dy: s, filter: e}, d = {pad: i, strides: r, inputShape: a}, p = z.runKernelFunc(u, h, null, Of, d);
    return o ? Y(p, [p.shape[1], p.shape[2], p.shape[3], p.shape[4]]) : p;
  }
  var Dg = U({conv3DBackpropInput_: XA});
  function JA(n, t, e, r, i) {
    var a = R(n, "x", "conv3dTranspose"), s = R(t, "filter", "conv3dTranspose");
    return Dg(e, a, s, r, i);
  }
  var ZA = U({conv3dTranspose_: JA});
  function QA(n) {
    var t = R(n, "x", "cos"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.cos(t);
      return i([t]), a;
    }, e, null, Vc);
  }
  var Ks = U({cos_: QA});
  function e5(n) {
    var t = R(n, "x", "cosh"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.cosh(t);
      return i([t]), a;
    }, e, null, Gc);
  }
  var Gu = U({cosh_: e5});
  function t5(n, t, e, r) {
    t === void 0 && (t = 0), e === void 0 && (e = false), r === void 0 && (r = false);
    var i = R(n, "x", "cumsum"), a = function(c, l) {
      var u = mn([t], i.rank), h = i;
      u != null && (h = Tt(i, u));
      var d = Dn(1, i.rank)[0], p = c.cumsum(h, d, e, r);
      if (l([i]), u != null) {
        var f = Ms(u);
        p = Tt(p, f);
      }
      return p;
    }, s = {x: i}, o = {axis: t, exclusive: e, reverse: r};
    return z.runKernelFunc(a, s, null, qc, o);
  }
  var qu = U({cumsum_: t5});
  function n5(n, t, e) {
    e === void 0 && (e = "NHWC");
    var r = R(n, "x", "depthToSpace"), i = e === "NHWC" ? r.shape[1] : r.shape[2], a = e === "NHWC" ? r.shape[2] : r.shape[3], s = e === "NHWC" ? r.shape[3] : r.shape[1];
    E(i * t >= 0, function() {
      return `Negative dimension size caused by overflow when multiplying
    ` + i + " and " + t + `  for depthToSpace with input shape
    ` + r.shape;
    }), E(a * t >= 0, function() {
      return `Negative dimension size caused by overflow when multiplying
    ` + a + " and " + t + ` for depthToSpace with input shape
        ` + r.shape;
    }), E(s % (t * t) === 0, function() {
      return "Dimension size must be evenly divisible by " + t * t + " but is " + s + " for depthToSpace with input shape " + r.shape;
    });
    var o = function(u) {
      return u.depthToSpace(r, t, e);
    }, c = {x: r}, l = {blockSize: t, dataFormat: e};
    return z.runKernelFunc(o, c, null, Df, l);
  }
  var kg = U({depthToSpace_: n5});
  function r5(n, t, e, r, i, a, s) {
    i === void 0 && (i = "NHWC"), a === void 0 && (a = [1, 1]);
    var o = R(n, "x", "depthwiseConv2d"), c = R(t, "filter", "depthwiseConv2d"), l = o, u = false;
    o.rank === 3 && (u = true, l = Y(o, [1, o.shape[0], o.shape[1], o.shape[2]])), E(l.rank === 4, function() {
      return "Error in depthwiseConv2d: input must be rank 4, but got " + ("rank " + l.rank + ".");
    }), E(c.rank === 4, function() {
      return "Error in depthwiseConv2d: filter must be rank 4, but got rank " + (c.rank + ".");
    }), E(l.shape[3] === c.shape[2], function() {
      return "Error in depthwiseConv2d: number of input channels " + ("(" + l.shape[3] + ") must match the inChannels dimension in ") + ("filter " + c.shape[2] + ".");
    }), s != null && E(ot(r), function() {
      return "Error in depthwiseConv2d: pad must be an integer when using, " + ("dimRoundingMode " + s + " but got pad " + r + ".");
    });
    var h = function(m, g) {
      a == null && (a = [1, 1]), E(Mt(e, a), function() {
        return "Error in depthwiseConv2d: Either strides or dilations must be " + ("1. Got strides " + e + " and dilations '" + a + "'");
      });
      var y = gn(l.shape, c.shape, e, a, r, s, true), w = m.depthwiseConv2D(l, c, y);
      return g([l, c]), w;
    }, d = {x: l, filter: c}, p = {strides: e, pad: r, dataFormat: i, dilations: a, dimRoundingMode: s}, f = z.runKernelFunc(h, d, null, Yc, p);
    return u ? Y(f, [f.shape[1], f.shape[2], f.shape[3]]) : f;
  }
  var Ca = U({depthwiseConv2d_: r5});
  function i5(n) {
    var t = R(n, "x", "diag"), e = function(i) {
      var a = Y(t, [t.size]), s = i.diag(a), o = n.shape.concat(n.shape);
      return Y(s, o);
    }, r = {x: t};
    return z.runKernelFunc(e, r, null, Wf);
  }
  var a5 = U({diag_: i5});
  function s5(n, t, e, r, i, a) {
    i === void 0 && (i = [1, 1]), a === void 0 && (a = "NHWC");
    var s = R(n, "x", "dilation2d"), o = R(t, "filter", "dilation2d");
    E(s.rank === 3 || s.rank === 4, function() {
      return "Error in dilation2d: input must be rank 3 or 4, but got rank " + (s.rank + ".");
    }), E(o.rank === 3, function() {
      return "Error in dilation2d: filter must be rank 3, but got rank " + (o.rank + ".");
    }), E(a === "NHWC", function() {
      return "Error in dilation2d: Only NHWC is currently supported, " + ("but got dataFormat of " + a);
    });
    var c = s, l = false;
    s.rank === 3 && (c = Y(s, [1, s.shape[0], s.shape[1], s.shape[2]]), l = true);
    var u = {x: c, filter: o}, h = {strides: e, pad: r, dilations: i}, d = z.runKernel(Kc, u, h);
    return l ? Y(d, [d.shape[1], d.shape[2], d.shape[3]]) : d;
  }
  var Fg = U({dilation2d_: s5});
  function o5(n, t) {
    for (var e = n.length, r = [], i = 0; i < e; i++) {
      var a = e - 1 - i, s = n[a] || 1, o = t[t.length - 1 - i] || 1;
      o > 1 && s === 1 && r.unshift(a);
    }
    return r;
  }
  function xt(n, t) {
    for (var e = [], r = 0; r < t.length; r++) {
      var i = n[n.length - r - 1], a = t.length - r - 1, s = t[a];
      (i == null || i === 1 && s > 1) && e.unshift(a);
    }
    return e;
  }
  function it(n, t) {
    for (var e = [], r = Math.max(n.length, t.length), i = 0; i < r; i++) {
      var a = n[n.length - i - 1];
      a == null && (a = 1);
      var s = t[t.length - i - 1];
      if (s == null && (s = 1), a === 1)
        e.unshift(s);
      else if (s === 1)
        e.unshift(a);
      else if (a !== s) {
        var o = "Operands could not be broadcast together with shapes " + (n + " and " + t + ".");
        throw Error(o);
      } else
        e.unshift(a);
    }
    return e;
  }
  function c5(n, t) {
    var e, r = R(n, "a", "equal"), i = R(t, "b", "equal");
    e = ct(r, i), r = e[0], i = e[1], it(r.shape, i.shape);
    var a = function(o) {
      return o.equal(r, i);
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, Pf);
  }
  var Ra = U({equal_: c5});
  function l5(n, t, e) {
    var r = R(t, "a", "where"), i = R(e, "b", "where"), a = R(n, "condition", "where", "bool"), s = it(r.shape, i.shape), o = Ys(r, s), c = Ys(i, s);
    a.rank === 1 && E(a.shape[0] === r.shape[0], function() {
      return "The first dimension of `a` must match the size of `condition`.";
    }), a.rank !== 1 && Pe(a.shape, c.shape, "Error in where: ");
    var l = function(h, d) {
      var p = h.select(a, o, c);
      return d([a]), p;
    }, u = {condition: a, t: o, e: c};
    return z.runKernelFunc(l, u, null, Wl);
  }
  var yn = U({where_: l5});
  function u5(n) {
    var t = R(n, "x", "zerosLike"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.zerosLike(t);
    }, e, null, ru);
  }
  var ke = U({zerosLike_: u5});
  function h5(n, t) {
    var e, r = R(n, "a", "div"), i = R(t, "b", "div");
    e = ct(r, i), r = e[0], i = e[1];
    var a = Ne(r, i), s = ke(a), o = Ra(i, s);
    return yn(o, s, a);
  }
  var Wg = U({divNoNan_: h5});
  function d5(n, t) {
    var e = R(n, "t1", "dot"), r = R(t, "t2", "dot");
    E((e.rank === 1 || e.rank === 2) && (r.rank === 1 || r.rank === 2), function() {
      return "Error in dot: inputs must all be rank 1 or 2, but got ranks " + (e.rank + " and " + r.rank + ".");
    });
    var i = e.rank === 1 ? e.size : e.shape[1], a = r.rank === 1 ? r.size : r.shape[0];
    if (E(i === a, function() {
      return "Error in dot: inner dimensions of inputs must match, but got " + (i + " and " + a + ".");
    }), e.rank === 1 && r.rank === 1) {
      var s = Y(e, [1, -1]), o = Y(r, [-1, 1]), c = Ue(s, o);
      return Y(c, []);
    } else if (e.rank === 1 && r.rank === 2) {
      var s = Y(e, [1, -1]), o = Y(r, [r.shape[0], r.shape[1]]), c = Ue(s, o);
      return Y(c, [c.size]);
    } else if (e.rank === 2 && r.rank === 1) {
      var o = Y(r, [-1, 1]), c = Ue(e, o);
      return Y(c, [c.size]);
    } else {
      var o = Y(r, [r.shape[0], r.shape[1]]), c = Ue(e, o);
      return c;
    }
  }
  var Ug = U({dot_: d5});
  function p5(n) {
    var t = R(n, "x", "elu"), e = function(i, a) {
      var s = i.elu(t);
      return a([s]), s;
    }, r = {x: t};
    return z.runKernelFunc(e, r, null, $c);
  }
  var Yu = U({elu_: p5});
  function f5(n) {
    var t = R(n, "x", "erf");
    E(t.dtype === "int32" || t.dtype === "float32", function() {
      return "Input dtype must be `int32` or `float32`.";
    }), t.dtype === "int32" && (t = he(t, "float32"));
    var e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.erf(t);
      return i([t]), a;
    }, e, null, Xc);
  }
  var Bg = U({erf_: f5});
  function m5(n) {
    var t = R(n, "x", "exp"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.exp(t);
      return i([a]), a;
    }, e, null, Jc);
  }
  var vn = U({exp_: m5});
  function g5(n, t) {
    t === void 0 && (t = 0);
    var e = null, r = R(n, "x", "expandDims", e);
    E(t <= r.rank, function() {
      return "Axis must be <= rank of the tensor";
    });
    var i = r.shape.slice();
    return t < 0 && (E(-(r.rank + 1) <= t, function() {
      return "Axis must be in the interval [" + -(r.rank + 1) + ", " + r.rank + "]";
    }), t = r.rank + t + 1), i.splice(t, 0, 1), Y(r, i);
  }
  var wn = U({expandDims_: g5});
  function y5(n) {
    var t = R(n, "x", "expm1"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.expm1(t);
      return i([t]), a;
    }, e, null, Zc);
  }
  var zg = U({expm1_: y5});
  function v5(n, t) {
    var e = null, r = R(n, "x", "tile", e);
    E(r.rank === t.length, function() {
      return "Error in transpose: rank of input " + r.rank + " " + ("must match length of reps " + t + ".");
    });
    var i = function(c, l) {
      var u = c.tile(r, t);
      return l([r]), u;
    }, a = [r], s = {x: r}, o = {reps: t};
    return z.runKernelFunc(i, s, null, Ql, o, a);
  }
  var Di = U({tile_: v5});
  function w5(n, t, e, r) {
    r === void 0 && (r = "float32"), t == null && (t = n);
    for (var i = En([n, t], r), a = n <= t ? n : t, s = 0; s < a; ++s)
      i.set(1, s, s);
    var o = Y(i.toTensor(), [n, t]);
    if (e == null)
      return o;
    if (e.length === 1)
      return Di(wn(o, 0), [e[0], 1, 1]);
    if (e.length === 2)
      return Di(wn(wn(o, 0), 0), [e[0], e[1], 1, 1]);
    if (e.length === 3)
      return Di(wn(wn(wn(o, 0), 0), 0), [e[0], e[1], e[2], 1, 1]);
    throw new Error("eye() currently supports only 1D and 2D " + ("batchShapes, but received " + e.length + "D."));
  }
  var Pg = U({eye_: w5});
  function Ku(n, t, e) {
    var r = {shape: n, value: t, dtype: e};
    return z.runKernelFunc(function(i) {
      return i.fill(n, t, e);
    }, {}, null, Hf, r);
  }
  function b5(n) {
    var t = R(n, "x", "floor"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.floor(t);
    }, e, null, Qc);
  }
  var js = U({floor_: b5});
  var ju = 30;
  function x5(n) {
    return n <= ju ? n : Cs(n, Math.floor(Math.sqrt(n)));
  }
  function L5(n, t) {
    var e = false, r;
    for (n <= ju ? (r = n, e = true) : r = Cs(n, Math.floor(Math.sqrt(n))); !e; )
      r > t || r === n ? e = true : r = Cs(n, r + 1);
    return r;
  }
  function S5(n, t, e) {
    for (var r = [], i = n.length, a = 0; a < i; a++)
      a !== t ? r.push(n[a]) : r.push(e);
    return r;
  }
  function Mg(n, t, e) {
    for (var r = n.shape[e], i = [], a = 1, s = 1, o = 0; o < e; o++)
      i.push(n.shape[o]), a *= n.shape[o];
    for (var o = 0; o < t.rank; o++)
      i.push(t.shape[o]);
    for (var o = e + 1; o < n.rank; o++)
      i.push(n.shape[o]), s *= n.shape[o];
    return {batchSize: a, sliceSize: s, dimSize: r, outputShape: i};
  }
  var I5 = {__proto__: null, segOpComputeOptimalWindowSize: L5, computeOutShape: S5, collectGatherOpShapeInfo: Mg};
  function A5(n, t, e) {
    e === void 0 && (e = 0);
    var r = R(n, "x", "gather"), i = R(t, "indices", "gather", "int32"), a = {x: r, indices: i}, s = {axis: e}, o = function(c, l) {
      var u = rt(e, r.shape)[0], h = Mg(r, i, u), d = c.gather(r, Y(i, [i.size]), u);
      return l([r, i]), Y(d, h.outputShape);
    };
    return z.runKernelFunc(o, a, null, nl, s);
  }
  var $s = U({gather_: A5});
  function T5(n, t) {
    var e, r = R(n, "a", "greater"), i = R(t, "b", "greater");
    e = ct(r, i), r = e[0], i = e[1], it(r.shape, i.shape);
    var a = function(o) {
      return o.greater(r, i);
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, qf);
  }
  var gr = U({greater_: T5});
  function N5(n, t) {
    var e, r = R(n, "a", "greaterEqual"), i = R(t, "b", "greaterEqual");
    e = ct(r, i), r = e[0], i = e[1], it(r.shape, i.shape);
    var a = function(o, c) {
      var l = o.greaterEqual(r, i);
      return c([r, i]), l;
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, rl);
  }
  var Vr = U({greaterEqual_: N5});
  function _5(n) {
    var t = R(n, "input", "imag"), e = function(i) {
      return i.imag(t);
    }, r = {input: t};
    return z.runKernelFunc(e, r, null, Kf);
  }
  var Xs = U({imag_: _5});
  function C5(n) {
    var t = R(n, "x", "isFinite"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.isFinite(t);
    }, e, null, al);
  }
  var Hg = U({isFinite_: C5});
  function R5(n) {
    var t = R(n, "x", "isInf"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.isInf(t);
    }, e, null, sl);
  }
  var Vg = U({isInf_: R5});
  function O5(n) {
    var t = R(n, "x", "isNaN"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.isNaN(t);
    }, e, null, ol);
  }
  var Gg = U({isNaN_: O5});
  function E5(n, t) {
    var e, r = R(n, "a", "maximum"), i = R(t, "b", "maximum");
    e = ct(r, i), r = e[0], i = e[1], r.dtype === "bool" && (r = he(r, "int32"), i = he(i, "int32")), it(r.shape, i.shape);
    var a = function(o, c) {
      var l = o.maximum(r, i);
      return c([r, i]), l;
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, pl);
  }
  var ki = U({maximum_: E5});
  function Le(n, t) {
    if ((Ft(n) && t !== "string" || Array.isArray(n)) && t !== "complex64")
      throw new Error("Error creating a new Scalar: value must be a primitive (number|boolean|string)");
    if (t === "string" && Ft(n) && !(n instanceof Uint8Array))
      throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");
    var e = [], r = [];
    return ur(n, e, r, t);
  }
  function D5(n, t) {
    t === void 0 && (t = 0.2);
    var e = R(n, "x", "leakyRelu");
    return ki(Z(Le(t), e), e);
  }
  var qg = U({leakyRelu_: D5});
  function k5(n, t) {
    var e, r = R(n, "a", "less"), i = R(t, "b", "less");
    e = ct(r, i), r = e[0], i = e[1], it(r.shape, i.shape);
    var a = function(o) {
      return o.less(r, i);
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, jf);
  }
  var Js = U({less_: k5});
  function F5(n, t) {
    var e, r = R(n, "a", "lessEqual"), i = R(t, "b", "lessEqual");
    e = ct(r, i), r = e[0], i = e[1], it(r.shape, i.shape);
    var a = function(o, c) {
      var l = o.lessEqual(r, i);
      return c([r, i]), l;
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, $f);
  }
  var Gr = U({lessEqual_: F5});
  function W5(n, t, e) {
    if (e <= 0)
      throw new Error("The number of values should be positive.");
    var r = {start: n, stop: t, num: e};
    return z.runKernelFunc(function(i) {
      return i.linspace(n, t, e);
    }, {}, null, Xf, r);
  }
  function U5(n, t, e, r, i) {
    t === void 0 && (t = 5), e === void 0 && (e = 1), r === void 0 && (r = 1), i === void 0 && (i = 0.5);
    var a = R(n, "x", "localResponseNormalization");
    E(a.rank === 4 || a.rank === 3, function() {
      return `Error in localResponseNormalization: x must be rank 3 or 4 but got
               rank ` + a.rank + ".";
    }), E(ot(t), function() {
      return "Error in localResponseNormalization: depthRadius must be an " + ("integer but got depthRadius " + t + ".");
    });
    var s = a, o = false;
    a.rank === 3 && (o = true, s = Y(a, [1, a.shape[0], a.shape[1], a.shape[2]]));
    var c = function(d, p) {
      var f = d.localResponseNormalization4D(s, t, e, r, i);
      return p([s, f]), f;
    }, l = {x: s}, u = {depthRadius: t, bias: e, alpha: r, beta: i}, h = z.runKernelFunc(c, l, null, hl, u);
    return o ? Y(h, [h.shape[1], h.shape[2], h.shape[3]]) : h;
  }
  var Yg = U({localResponseNormalization_: U5});
  function B5(n) {
    var t = R(n, "x", "log"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.log(t);
      return i([t]), a;
    }, e, null, cl);
  }
  var qr = U({log_: B5});
  function z5(n) {
    var t = R(n, "x", "log1p"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.log1p(t);
      return i([t]), a;
    }, e, null, ll);
  }
  var $u = U({log1p_: z5});
  function P5(n) {
    return E(cr(n), function() {
      return "The f passed in grad(f) must be a function";
    }), function(t, e) {
      var r = R(t, "x", "tf.grad", null), i = e != null ? R(e, "dy", "tf.grad") : null;
      return z.tidy(function() {
        var a = z.gradients(function() {
          return n(r);
        }, [r], i), s = a.value, o = a.grads;
        return i != null && Pe(s.shape, i.shape, "The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"), Zs(o), o[0];
      });
    };
  }
  function M5(n) {
    return E(cr(n), function() {
      return "The f passed in grads(f) must be a function";
    }), function(t, e) {
      E(Array.isArray(t), function() {
        return "The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s";
      });
      var r = Sa(t, "args", "tf.grads", null), i = e != null ? R(e, "dy", "tf.grads") : null;
      return z.tidy(function() {
        var a = z.gradients(function() {
          return n.apply(void 0, r);
        }, r, i), s = a.value, o = a.grads;
        return i != null && Pe(s.shape, i.shape, "The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"), Zs(o), o;
      });
    };
  }
  function H5(n) {
    return E(cr(n), function() {
      return "The f passed in valueAndGrad(f) must be a function";
    }), function(t, e) {
      E(t instanceof K, function() {
        return "The x passed in valueAndGrad(f)(x) must be a tensor";
      }), E(e == null || e instanceof K, function() {
        return "The dy passed in valueAndGrad(f)(x, dy) must be a tensor";
      });
      var r = z.gradients(function() {
        return n(t);
      }, [t], e), i = r.grads, a = r.value;
      return Zs(i), {grad: i[0], value: a};
    };
  }
  function V5(n) {
    return E(cr(n), function() {
      return "The f passed in valueAndGrads(f) must be a function";
    }), function(t, e) {
      E(Array.isArray(t) && t.every(function(i) {
        return i instanceof K;
      }), function() {
        return "The args passed in valueAndGrads(f)(args) must be array of tensors";
      }), E(e == null || e instanceof K, function() {
        return "The dy passed in valueAndGrads(f)(args, dy) must be a tensor";
      });
      var r = z.gradients(function() {
        return n.apply(void 0, t);
      }, t, e);
      return e != null && Pe(r.value.shape, e.shape, "The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"), Zs(r.grads), r;
    };
  }
  function Kg(n, t) {
    E(cr(n), function() {
      return "The f passed in variableGrads(f) must be a function";
    }), E(t == null || Array.isArray(t) && t.every(function(h) {
      return h instanceof La;
    }), function() {
      return "The varList passed in variableGrads(f, varList) must be an array of variables";
    });
    var e = t != null;
    if (!e) {
      t = [];
      for (var r in z.registeredVariables)
        t.push(z.registeredVariables[r]);
    }
    var i = e ? t.filter(function(h) {
      return !h.trainable;
    }) : null, a = t.length;
    t = t.filter(function(h) {
      return h.trainable;
    }), E(t.length > 0, function() {
      return "variableGrads() expects at least one of the input variables to " + ("be trainable, but none of the " + a + " variables is ") + "trainable.";
    });
    var s = true, o = z.gradients(n, t, null, s), c = o.value, l = o.grads;
    E(l.some(function(h) {
      return h != null;
    }), function() {
      return "Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize().";
    }), E(c.rank === 0, function() {
      return "The f passed in variableGrads(f) must return a scalar, but it " + ("returned a rank-" + c.rank + " tensor");
    });
    var u = {};
    return t.forEach(function(h, d) {
      l[d] != null && (u[h.name] = l[d]);
    }), i != null && i.forEach(function(h) {
      return u[h.name] = null;
    }), {value: c, grads: u};
  }
  function kn(n) {
    return z.customGrad(n);
  }
  function Zs(n) {
    var t = n.filter(function(e) {
      return e == null;
    }).length;
    if (t > 0)
      throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that
    the f you passed encloses all operations that lead from x to y.`);
  }
  function G5(n) {
    var t = R(n, "x", "neg"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.neg(t);
    }, e, null, xl);
  }
  var Lt = U({neg_: G5});
  function q5(n) {
    var t = R(n, "x", "softplus"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.softplus(t);
      return i([t]), a;
    }, e, null, Vl);
  }
  var Xu = U({softplus_: q5});
  function Y5(n) {
    var t = R(n, "x", "logSigmoid"), e = kn(function(r) {
      var i = Lt(Xu(Lt(r))), a = function(s) {
        var o = Z(s, Hr(Lt(r)));
        return o;
      };
      return {value: i, gradFunc: a};
    });
    return e(t);
  }
  var jg = U({logSigmoid_: Y5});
  function K5(n, t, e) {
    t === void 0 && (t = null), e === void 0 && (e = false);
    var r = R(n, "x", "max"), i = function(o, c) {
      var l = rt(t, r.shape), u = l, h = mn(u, r.rank), d = r;
      h != null && (d = Tt(r, h), u = Dn(u.length, d.rank));
      var p = o.max(d, u);
      h != null && d.dispose();
      var f = p;
      if (e) {
        var m = an(f.shape, rt(t, r.shape));
        f = Y(f, m), p.dispose();
      }
      return c([r, f]), f;
    }, a = {x: r}, s = {reductionIndices: t, keepDims: e};
    return z.runKernelFunc(i, a, null, dl, s);
  }
  var Yr = U({max_: K5});
  function j5(n, t) {
    var e, r = R(n, "a", "sub"), i = R(t, "b", "sub");
    e = ct(r, i), r = e[0], i = e[1];
    var a = function(o, c) {
      var l = o.subtract(r, i);
      return c([r, i]), l;
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, Xl);
  }
  var be = U({sub_: j5});
  function $5(n, t, e) {
    t === void 0 && (t = null), e === void 0 && (e = false);
    var r = R(n, "x", "sum");
    r.dtype === "bool" && (r = he(r, "int32"));
    var i = function(o, c) {
      c([r]);
      var l = rt(t, r.shape), u = mn(l, r.rank), h = l, d = r;
      u != null && (d = Tt(r, u), h = Dn(h.length, r.rank));
      var p = o.sum(d, h);
      if (e) {
        var f = an(p.shape, l);
        p = Y(p, f);
      }
      return p;
    }, a = {x: r}, s = {axis: t, keepDims: e};
    return z.runKernelFunc(i, a, null, ql, s);
  }
  var _e = U({sum_: $5});
  function X5(n, t) {
    t === void 0 && (t = -1);
    var e = R(n, "logits", "logSoftmax");
    if (t === -1 && (t = e.rank - 1), t !== e.rank - 1)
      throw Error("Log Softmax along a non-last dimension is not yet supported. " + ("Logits was rank " + e.rank + " and axis was " + t));
    var r = function(s, o) {
      var c = true, l = Yr(n, t, true), u = be(n, l), h = be(he(u, "float32"), qr(_e(vn(u), t, c)));
      return o([h]), h;
    }, i = {logits: e}, a = {axis: t};
    return z.runKernelFunc(r, i, null, ul, a);
  }
  var $g = U({logSoftmax_: X5});
  function J5(n, t, e) {
    t === void 0 && (t = null), e === void 0 && (e = false);
    var r = R(n, "x", "logSumExp"), i = rt(t, r.shape), a = Yr(r, i, true), s = be(r, a), o = vn(s), c = _e(o, i), l = qr(c), u = ge(Y(a, l.shape), l);
    if (e) {
      var h = an(u.shape, i);
      return Y(u, h);
    }
    return u;
  }
  var Ju = U({logSumExp_: J5});
  function Z5(n, t) {
    var e = R(n, "a", "logicalAnd", "bool"), r = R(t, "b", "logicalAnd", "bool");
    it(e.shape, r.shape);
    var i = {a: e, b: r};
    return z.runKernelFunc(function(a) {
      return a.logicalAnd(e, r);
    }, i, null, Jf);
  }
  var Kr = U({logicalAnd_: Z5});
  function Q5(n) {
    var t = R(n, "x", "logicalNot", "bool"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.logicalNot(t);
    }, e, null, Zf);
  }
  var Qs = U({logicalNot_: Q5});
  function eT(n, t) {
    var e = R(n, "a", "logicalOr", "bool"), r = R(t, "b", "logicalOr", "bool");
    it(e.shape, r.shape);
    var i = {a: e, b: r};
    return z.runKernelFunc(function(a) {
      return a.logicalOr(e, r);
    }, i, null, Qf);
  }
  var Zu = U({logicalOr_: eT});
  function tT(n, t) {
    var e = R(n, "a", "logicalXor", "bool"), r = R(t, "b", "logicalXor", "bool");
    return it(e.shape, r.shape), Kr(Zu(n, t), Qs(Kr(n, t)));
  }
  var Xg = U({logicalXor_: tT});
  function nT(n, t, e, r, i) {
    var a = R(n, "x", "maxPool"), s = 1, o = a, c = false;
    a.rank === 3 && (c = true, o = Y(a, [1, a.shape[0], a.shape[1], a.shape[2]])), E(o.rank === 4, function() {
      return "Error in maxPool: input must be rank 4 but got rank " + o.rank + ".";
    }), E(Mt(e, s), function() {
      return "Error in maxPool: Either strides or dilations must be 1. " + ("Got strides " + e + " and dilations '" + s + "'");
    }), i != null && E(ot(r), function() {
      return "Error in maxPool: pad must be an integer when using, " + ("dimRoundingMode " + i + " but got pad " + r + ".");
    });
    var l = function(p, f) {
      var m = Ri(o.shape, t, e, 1, r, i), g;
      return m.filterWidth === 1 && m.filterHeight === 1 && fn(m.inShape, m.outShape) ? g = o.clone() : g = p.maxPool(o, m), f([o, g]), g;
    }, u = {x: o}, h = {filterSize: t, strides: e, pad: r, dimRoundingMode: i}, d = z.runKernelFunc(l, u, null, fl, h);
    return c ? Y(d, [d.shape[1], d.shape[2], d.shape[3]]) : d;
  }
  var Qu = U({maxPool_: nT});
  function rT(n, t, e, r, i, a, s) {
    t === void 0 && (t = [1, 1, 1]), a === void 0 && (a = "NDHWC"), s == null ? s = [1, 1, 1] : Nt("dilations is deprecated, this field will be gone in v3.0.0.");
    var o = R(n, "x", "maxPool3d"), c = o, l = false;
    o.rank === 4 && (l = true, c = Y(o, [1, o.shape[0], o.shape[1], o.shape[2], o.shape[3]])), E(c.rank === 5, function() {
      return "Error in maxPool3d: x must be rank 5 but got rank " + c.rank + ".";
    }), E(a === "NDHWC", function() {
      return "Error in maxPool3d: Only NDHWC is currently supported, " + ("but got dataFormat of " + a);
    }), E(Mt(e, s), function() {
      return "Error in maxPool3d: Either strides or dilations must be 1. " + ("Got strides " + e + " and dilations '" + s + "'");
    }), i != null && E(ot(r), function() {
      return "Error in maxPool3d: pad must be an integer when using, " + ("dimRoundingMode " + i + " but got pad " + r + ".");
    });
    var u = function(f, m) {
      s == null && (s = [1, 1, 1]);
      var g = Na(c.shape, t, e, s, r, i, a), y = f.maxPool3d(c, g);
      return m([c, y]), y;
    }, h = {x: c}, d = {filterSize: t, strides: e, pad: r, dimRoundingMode: i, dataFormat: a, dilations: s}, p = z.runKernelFunc(u, h, null, ml, d);
    return l ? Y(p, [p.shape[1], p.shape[2], p.shape[3], p.shape[4]]) : p;
  }
  var iT = U({maxPool3d_: rT});
  function aT(n, t, e, r, i) {
    i === void 0 && (i = false);
    var a = R(n, "x", "maxPoolWithArgmax"), s = {x: a}, o = {filterSize: t, strides: e, pad: r, includeBatchInIndex: i}, c = z.runKernel(rm, s, o);
    return {result: c[0], indexes: c[1]};
  }
  var sT = U({maxPoolWithArgmax_: aT});
  function jn(n, t) {
    if (t === void 0 && (t = "float32"), t === "complex64") {
      var e = jn(n, "float32"), r = jn(n, "float32");
      return lr(e, r);
    }
    var i = Li(pt(n), t);
    return z.makeTensor(i, n, t);
  }
  function Fi(n, t) {
    if (t === void 0 && (t = "float32"), t === "complex64") {
      var e = Fi(n, "float32"), r = jn(n, "float32");
      return lr(e, r);
    }
    var i = yc(pt(n), t);
    return z.makeTensor(i, n, t);
  }
  function oT(n, t, e) {
    t === void 0 && (t = null), e === void 0 && (e = false);
    var r = R(n, "x", "mean"), i = rt(t, r.shape), a = yg(r.shape, i), s = a[1], o = pt(s), c = {x: r}, l = {axis: t, keepDims: e}, u = function() {
      var d = Le(o), p = d.dtype === r.dtype ? r : he(r, d.dtype), f = Ne(p, d);
      return _e(f, t, e);
    }, h = kn(function(d) {
      var p = z.runKernelFunc(u, c, null, im, l), f = function(m) {
        var g = d.shape.slice();
        i.forEach(function(b) {
          g[b] = 1;
        });
        var y = Y(m, g), w = Ne(Z(y, Fi(d.shape, "float32")), o);
        return w;
      };
      return {value: p, gradFunc: f};
    });
    return h(r);
  }
  var Oa = U({mean_: oT});
  function cT(n, t, e) {
    t === void 0 && (t = null), e === void 0 && (e = false);
    var r = R(n, "x", "min"), i = function(o, c) {
      var l = rt(t, r.shape), u = l, h = mn(u, r.rank), d = r;
      h != null && (d = Tt(r, h), u = Dn(u.length, r.rank));
      var p = o.min(d, u);
      h != null && d.dispose();
      var f = p;
      if (e) {
        var m = an(f.shape, l);
        f = Y(p, m), p.dispose();
      }
      return c([r, f]), f;
    }, a = {x: r}, s = {axis: t, keepDims: e};
    return z.runKernelFunc(i, a, null, gl, s);
  }
  var eo = U({min_: cT});
  function lT(n, t) {
    var e, r = R(n, "a", "minimum"), i = R(t, "b", "minimum");
    e = ct(r, i), r = e[0], i = e[1], r.dtype === "bool" && (r = he(r, "int32"), i = he(i, "int32")), it(r.shape, i.shape);
    var a = function(o, c) {
      var l = o.minimum(r, i);
      return c([r, i]), l;
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, yl);
  }
  var to = U({minimum_: lT});
  function uT(n, t, e) {
    E(e === "reflect" || e === "symmetric", function() {
      return "Invalid mode. Mode must be either reflect or symmetric. " + ("Got " + e + ".");
    });
    var r = R(n, "x", "mirrorPad");
    if (r.rank === 0)
      throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");
    E(t.length === r.rank, function() {
      return "Padding doesn't match input. Must be " + r.rank + ". " + ("Got " + t.length + ".");
    });
    for (var i = e === "reflect" ? 1 : 0, a = function(l) {
      E(t[l].length === 2, function() {
        return "Invalid number of paddings. Must be length of 2 each.";
      }), E(t[l][0] >= 0 && t[l][0] <= r.shape[l] - i && t[l][1] >= 0 && t[l][1] <= r.shape[l] - i, function() {
        return "Padding in dimension " + l + " cannot be greater than or equal " + ("to " + (r.shape[l] - i) + " or less than 0 for input of ") + ("shape " + r.shape);
      });
    }, s = 0; s < r.rank; s++)
      a(s);
    var o = {paddings: t, mode: e}, c = {x: r};
    return z.runKernel(vl, c, o);
  }
  var Jg = U({mirrorPad_: uT});
  function hT(n, t) {
    var e, r = R(n, "a", "mod"), i = R(t, "b", "mod");
    e = ct(r, i), r = e[0], i = e[1];
    var a = function(o, c) {
      var l = o.mod(r, i);
      return c([r, i]), l;
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, wl);
  }
  var eh = U({mod_: hT});
  function dT(n) {
    var t = R(n, "x", "square"), e = {}, r = [t], i = [];
    return z.runKernelFunc(function(a, s) {
      return s([t]), a.square(t);
    }, {x: t}, null, "Square", e, r, i);
  }
  var $e = U({square_: dT});
  function pT(n, t, e) {
    t === void 0 && (t = null), e === void 0 && (e = false), n = R(n, "x", "moments");
    var r = rt(t, n.shape), i = Oa(n, r, e), a = i.shape;
    e || (a = an(i.shape, r));
    var s = $e(be(he(n, "float32"), Y(i, a))), o = Oa(s, r, e);
    return {mean: i, variance: o};
  }
  var fT = U({moments_: pT});
  function mT(n, t, e, r) {
    for (var i = R(t, "data", "multiRNNCell"), a = Sa(e, "c", "multiRNNCell"), s = Sa(r, "h", "multiRNNCell"), o = i, c = [], l = 0; l < n.length; l++) {
      var u = n[l](o, a[l], s[l]);
      c.push(u[0]), c.push(u[1]), o = u[1];
    }
    for (var h = [], d = [], l = 0; l < c.length; l += 2)
      h.push(c[l]), d.push(c[l + 1]);
    return [h, d];
  }
  var gT = U({multiRNNCell_: mT});
  function yT(n, t, e, r) {
    r === void 0 && (r = false);
    var i = R(n, "logits", "multinomial"), a = i.size, s = i.rank;
    if (a < 2)
      throw new Error("Error in multinomial: you need at least 2 outcomes, but got " + (a + "."));
    if (s > 2)
      throw new Error("Rank of probabilities must be 1 or 2, but is " + s);
    e = e || Math.random();
    var o = s === 1 ? Y(i, [1, -1]) : i, c = z.runKernelFunc(function(l) {
      return l.multinomial(o, r, t, e);
    }, {logits2D: o});
    return s === 1 ? Y(c, [c.size]) : c;
  }
  var vT = U({multinomial_: yT});
  function wT(n, t) {
    var e, r = R(n, "a", "notEqual"), i = R(t, "b", "notEqual");
    e = ct(r, i), r = e[0], i = e[1], it(r.shape, i.shape);
    var a = function(o) {
      return o.notEqual(r, i);
    }, s = {a: r, b: i};
    return z.runKernelFunc(a, s, null, am);
  }
  var no = U({notEqual_: wT});
  function bT(n) {
    var t = R(n, "input", "real"), e = function(i) {
      return i.real(t);
    }, r = {input: t};
    return z.runKernelFunc(e, r, null, hm);
  }
  var Ea = U({real_: bT});
  function xT(n) {
    var t = R(n, "x", "onesLike"), e = function(i, a) {
      if (t.dtype === "complex64") {
        var s = th(Ea(t)), o = ke(Xs(t));
        return lr(s, o);
      }
      return i.onesLike(t);
    }, r = {x: t};
    return z.runKernelFunc(e, r, null, Ll);
  }
  var th = U({onesLike_: xT});
  function LT(n, t) {
    var e = R(n, "v1", "outerProduct"), r = R(t, "v2", "outerProduct");
    E(e.rank === 1 && r.rank === 1, function() {
      return "Error in outerProduct: inputs must be rank 1, but got ranks " + (e.rank + " and " + r.rank + ".");
    });
    var i = Y(e, [-1, 1]), a = Y(r, [1, -1]);
    return Ue(i, a);
  }
  var ST = U({outerProduct_: LT});
  function IT(n, t, e) {
    e === void 0 && (e = 0);
    var r = R(n, "x", "pad");
    if (r.rank === 0)
      throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");
    var i = function(o, c) {
      return c([r]), o.pad(r, t, e);
    }, a = {paddings: t, constantValue: e}, s = {x: r};
    return z.runKernelFunc(i, s, null, Il, a);
  }
  var jr = U({pad_: IT});
  function AT(n, t, e) {
    return e === void 0 && (e = 0), E(t.length === 2, function() {
      return "Invalid number of paddings. Must be length of 2.";
    }), jr(n, [t], e);
  }
  var TT = U({pad1d_: AT});
  function NT(n, t, e) {
    return e === void 0 && (e = 0), E(t.length === 2 && t[0].length === 2 && t[1].length === 2, function() {
      return "Invalid number of paddings. Must be length of 2 each.";
    }), jr(n, t, e);
  }
  var _T = U({pad2d_: NT});
  function CT(n, t, e) {
    return e === void 0 && (e = 0), E(t.length === 3 && t[0].length === 2 && t[1].length === 2 && t[2].length === 2, function() {
      return "Invalid number of paddings. Must be length of 2 each.";
    }), jr(n, t, e);
  }
  var RT = U({pad3d_: CT});
  function OT(n, t, e) {
    return e === void 0 && (e = 0), E(t.length === 4 && t[0].length === 2 && t[1].length === 2 && t[2].length === 2 && t[3].length === 2, function() {
      return "Invalid number of paddings. Must be length of 2 each.";
    }), jr(n, t, e);
  }
  var ET = U({pad4d_: OT});
  function DT(n, t, e) {
    var r = R(n, "x", "spaceToBatchND");
    E(r.rank >= 1 + t.length, function() {
      return "input rank " + r.rank + " should be > than [blockShape] " + t.length;
    }), E(e.length === t.length, function() {
      return "paddings.shape[0] " + e.length + " must be equal to [blockShape] " + t.length;
    }), E(r.shape.reduce(function(o, c, l) {
      return l > 0 && l <= t.length ? o && (c + e[l - 1][0] + e[l - 1][1]) % t[l - 1] === 0 : o;
    }, true), function() {
      return "input spatial dimensions " + r.shape.slice(1) + " with paddings " + e.toString() + " must be divisible by blockShapes " + t.toString();
    });
    var i = function(o) {
      return o.spaceToBatchND(r, t, e);
    }, a = {x: r}, s = {blockShape: t, paddings: e};
    return z.runKernelFunc(i, a, null, Yl, s);
  }
  var ro = U({spaceToBatchND_: DT});
  function WT(n, t, e, r, i, a) {
    i == null && (i = [1, 1]), a == null && (a = 1), r === 0 && (r = "valid");
    var s = R(n, "x", "maxPool"), o = s, c = false;
    s.rank === 3 && (c = true, o = Y(s, [1, s.shape[0], s.shape[1], s.shape[2]])), E(Mt(a, i), function() {
      return "Error in pool: Either strides or dilations must be 1. " + ("Got strides " + a + " and dilations '" + i + "'");
    });
    var l = Ri(o.shape, t, a, i, r), u = [l.dilationHeight, l.dilationWidth], h;
    r === "same" ? h = FT([l.filterHeight, l.filterWidth], u) : h = [[0, 0], [0, 0]];
    var d = u[0] === 1 && u[1] === 1, p = kT([l.inHeight, l.inWidth], u, h), f = p[0], m = p[1], g = d ? r : "valid", y = d ? o : ro(o, u, f), w = e === "avg" ? function() {
      return Hu(y, t, a, g);
    } : function() {
      return Qu(y, t, a, g);
    }, b = w(), L = d ? b : Gs(b, u, m);
    return c ? Y(L, [L.shape[1], L.shape[2], L.shape[3]]) : L;
  }
  function kT(n, t, e) {
    var r = e.map(function(u) {
      return u[0];
    }), i = e.map(function(u) {
      return u[1];
    }), a = n.concat(r, i), s = t.map(function(u, h) {
      return (u - a[h] % u) % u;
    }), o = i.map(function(u, h) {
      return u + s[h];
    }), c = t.map(function(u, h) {
      return [r[h], o[h]];
    }), l = t.map(function(u, h) {
      return [0, s[h]];
    });
    return [c, l];
  }
  function FT(n, t) {
    var e = n.map(function(s, o) {
      return s + (s - 1) * (t[o] - 1);
    }), r = e.map(function(s) {
      return s - 1;
    }), i = r.map(function(s) {
      return Math.floor(s / 2);
    }), a = r.map(function(s, o) {
      return s - i[o];
    });
    return r.map(function(s, o) {
      return [i[o], a[o]];
    });
  }
  var Zg = U({pool_: WT});
  function UT(n, t) {
    var e, r = R(n, "base", "pow"), i = R(t, "exp", "pow");
    e = ct(r, i), r = e[0], i = e[1];
    var a = {a: r, b: i}, s = function(o, c) {
      var l = o.pow(r, i);
      return c([r, i, l]), l;
    };
    return z.runKernelFunc(s, a, null, Al);
  }
  var $n = U({pow_: UT});
  function BT(n, t) {
    var e = R(n, "x", "prelu"), r = R(t, "alpha", "prelu"), i = function(s, o) {
      var c = s.prelu(e, r);
      return o([e, r]), c;
    }, a = {x: e, alpha: r};
    return z.runKernelFunc(i, a, null, Tl);
  }
  var nh = U({prelu_: BT});
  function zT(n, t, e) {
    t === void 0 && (t = null), e === void 0 && (e = false);
    var r = R(n, "x", "prod");
    r.dtype === "bool" && (r = he(r, "int32"));
    var i = function(o) {
      var c = rt(t, r.shape), l = mn(c, r.rank), u = c, h = r;
      l != null && (h = Tt(r, l), u = Dn(u.length, r.rank));
      var d = o.prod(h, u);
      if (e) {
        var p = an(d.shape, c);
        d = Y(d, p);
      }
      return d;
    }, a = {x: r}, s = {axis: t, keepDims: e};
    return z.runKernelFunc(i, a, null, lm, s);
  }
  var Qg = U({prod_: zT});
  function PT(n, t, e) {
    var r = pt(n), i = null;
    if (e == null || e === "float32")
      i = new Float32Array(r);
    else if (e === "int32")
      i = new Int32Array(r);
    else if (e === "bool")
      i = new Uint8Array(r);
    else
      throw new Error("Unknown data type " + e);
    for (var a = 0; a < r; a++)
      i[a] = t();
    return z.makeTensor(i, n, e);
  }
  var MT = U({rand_: PT}), Wi = typeof globalThis != "undefined" ? globalThis : typeof window != "undefined" ? window : typeof global != "undefined" ? global : typeof self != "undefined" ? self : {};
  function $r(n, t) {
    return t = {exports: {}}, n(t, t.exports), t.exports;
  }
  var HT = $r(function(n) {
    (function(t, e, r) {
      function i(c) {
        var l = this, u = o();
        l.next = function() {
          var h = 2091639 * l.s0 + l.c * 23283064365386963e-26;
          return l.s0 = l.s1, l.s1 = l.s2, l.s2 = h - (l.c = h | 0);
        }, l.c = 1, l.s0 = u(" "), l.s1 = u(" "), l.s2 = u(" "), l.s0 -= u(c), l.s0 < 0 && (l.s0 += 1), l.s1 -= u(c), l.s1 < 0 && (l.s1 += 1), l.s2 -= u(c), l.s2 < 0 && (l.s2 += 1), u = null;
      }
      function a(c, l) {
        return l.c = c.c, l.s0 = c.s0, l.s1 = c.s1, l.s2 = c.s2, l;
      }
      function s(c, l) {
        var u = new i(c), h = l && l.state, d = u.next;
        return d.int32 = function() {
          return u.next() * 4294967296 | 0;
        }, d.double = function() {
          return d() + (d() * 2097152 | 0) * 11102230246251565e-32;
        }, d.quick = d, h && (typeof h == "object" && a(h, u), d.state = function() {
          return a(u, {});
        }), d;
      }
      function o() {
        var c = 4022871197, l = function(u) {
          u = u.toString();
          for (var h = 0; h < u.length; h++) {
            c += u.charCodeAt(h);
            var d = 0.02519603282416938 * c;
            c = d >>> 0, d -= c, d *= c, c = d >>> 0, d -= c, c += d * 4294967296;
          }
          return (c >>> 0) * 23283064365386963e-26;
        };
        return l;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.alea = s;
    })(Wi, n, false);
  }), VT = $r(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this, l = "";
        c.x = 0, c.y = 0, c.z = 0, c.w = 0, c.next = function() {
          var h = c.x ^ c.x << 11;
          return c.x = c.y, c.y = c.z, c.z = c.w, c.w ^= c.w >>> 19 ^ h ^ h >>> 8;
        }, o === (o | 0) ? c.x = o : l += o;
        for (var u = 0; u < l.length + 64; u++)
          c.x ^= l.charCodeAt(u) | 0, c.next();
      }
      function a(o, c) {
        return c.x = o.x, c.y = o.y, c.z = o.z, c.w = o.w, c;
      }
      function s(o, c) {
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (typeof u == "object" && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.xor128 = s;
    })(Wi, n, false);
  }), GT = $r(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this, l = "";
        c.next = function() {
          var h = c.x ^ c.x >>> 2;
          return c.x = c.y, c.y = c.z, c.z = c.w, c.w = c.v, (c.d = c.d + 362437 | 0) + (c.v = c.v ^ c.v << 4 ^ (h ^ h << 1)) | 0;
        }, c.x = 0, c.y = 0, c.z = 0, c.w = 0, c.v = 0, o === (o | 0) ? c.x = o : l += o;
        for (var u = 0; u < l.length + 64; u++)
          c.x ^= l.charCodeAt(u) | 0, u == l.length && (c.d = c.x << 10 ^ c.x >>> 4), c.next();
      }
      function a(o, c) {
        return c.x = o.x, c.y = o.y, c.z = o.z, c.w = o.w, c.v = o.v, c.d = o.d, c;
      }
      function s(o, c) {
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (typeof u == "object" && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.xorwow = s;
    })(Wi, n, false);
  }), qT = $r(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this;
        c.next = function() {
          var u = c.x, h = c.i, d, p;
          return d = u[h], d ^= d >>> 7, p = d ^ d << 24, d = u[h + 1 & 7], p ^= d ^ d >>> 10, d = u[h + 3 & 7], p ^= d ^ d >>> 3, d = u[h + 4 & 7], p ^= d ^ d << 7, d = u[h + 7 & 7], d = d ^ d << 13, p ^= d ^ d << 9, u[h] = p, c.i = h + 1 & 7, p;
        };
        function l(u, h) {
          var d, p, f = [];
          if (h === (h | 0))
            p = f[0] = h;
          else
            for (h = "" + h, d = 0; d < h.length; ++d)
              f[d & 7] = f[d & 7] << 15 ^ h.charCodeAt(d) + f[d + 1 & 7] << 13;
          for (; f.length < 8; )
            f.push(0);
          for (d = 0; d < 8 && f[d] === 0; ++d)
            ;
          for (d == 8 ? p = f[7] = -1 : p = f[d], u.x = f, u.i = 0, d = 256; d > 0; --d)
            u.next();
        }
        l(c, o);
      }
      function a(o, c) {
        return c.x = o.x.slice(), c.i = o.i, c;
      }
      function s(o, c) {
        o == null && (o = +new Date());
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (u.x && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.xorshift7 = s;
    })(Wi, n, false);
  }), YT = $r(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this;
        c.next = function() {
          var u = c.w, h = c.X, d = c.i, p, f;
          return c.w = u = u + 1640531527 | 0, f = h[d + 34 & 127], p = h[d = d + 1 & 127], f ^= f << 13, p ^= p << 17, f ^= f >>> 15, p ^= p >>> 12, f = h[d] = f ^ p, c.i = d, f + (u ^ u >>> 16) | 0;
        };
        function l(u, h) {
          var d, p, f, m, g, y = [], w = 128;
          for (h === (h | 0) ? (p = h, h = null) : (h = h + "\0", p = 0, w = Math.max(w, h.length)), f = 0, m = -32; m < w; ++m)
            h && (p ^= h.charCodeAt((m + 32) % h.length)), m === 0 && (g = p), p ^= p << 10, p ^= p >>> 15, p ^= p << 4, p ^= p >>> 13, m >= 0 && (g = g + 1640531527 | 0, d = y[m & 127] ^= p + g, f = d == 0 ? f + 1 : 0);
          for (f >= 128 && (y[(h && h.length || 0) & 127] = -1), f = 127, m = 4 * 128; m > 0; --m)
            p = y[f + 34 & 127], d = y[f = f + 1 & 127], p ^= p << 13, d ^= d << 17, p ^= p >>> 15, d ^= d >>> 12, y[f] = p ^ d;
          u.w = g, u.X = y, u.i = f;
        }
        l(c, o);
      }
      function a(o, c) {
        return c.i = o.i, c.w = o.w, c.X = o.X.slice(), c;
      }
      function s(o, c) {
        o == null && (o = +new Date());
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (u.X && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.xor4096 = s;
    })(Wi, n, false);
  }), KT = $r(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this, l = "";
        c.next = function() {
          var h = c.b, d = c.c, p = c.d, f = c.a;
          return h = h << 25 ^ h >>> 7 ^ d, d = d - p | 0, p = p << 24 ^ p >>> 8 ^ f, f = f - h | 0, c.b = h = h << 20 ^ h >>> 12 ^ d, c.c = d = d - p | 0, c.d = p << 16 ^ d >>> 16 ^ f, c.a = f - h | 0;
        }, c.a = 0, c.b = 0, c.c = 2654435769 | 0, c.d = 1367130551, o === Math.floor(o) ? (c.a = o / 4294967296 | 0, c.b = o | 0) : l += o;
        for (var u = 0; u < l.length + 20; u++)
          c.b ^= l.charCodeAt(u) | 0, c.next();
      }
      function a(o, c) {
        return c.a = o.a, c.b = o.b, c.c = o.c, c.d = o.d, c;
      }
      function s(o, c) {
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (typeof u == "object" && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.tychei = s;
    })(Wi, n, false);
  }), Xr = $r(function(n) {
    (function(t, e) {
      var r = this, i = 256, a = 6, s = 52, o = "random", c = e.pow(i, a), l = e.pow(2, s), u = l * 2, h = i - 1, d;
      function p(L, x, N) {
        var I = [];
        x = x == true ? {entropy: true} : x || {};
        var C = y(g(x.entropy ? [L, b(t)] : L == null ? w() : L, 3), I), O = new f(I), D = function() {
          for (var F = O.g(a), k = c, B = 0; F < l; )
            F = (F + B) * i, k *= i, B = O.g(1);
          for (; F >= u; )
            F /= 2, k /= 2, B >>>= 1;
          return (F + B) / k;
        };
        return D.int32 = function() {
          return O.g(4) | 0;
        }, D.quick = function() {
          return O.g(4) / 4294967296;
        }, D.double = D, y(b(O.S), t), (x.pass || N || function(F, k, B, V) {
          return V && (V.S && m(V, O), F.state = function() {
            return m(O, {});
          }), B ? (e[o] = F, k) : F;
        })(D, C, "global" in x ? x.global : this == e, x.state);
      }
      e["seed" + o] = p;
      function f(L) {
        var x, N = L.length, I = this, C = 0, O = I.i = I.j = 0, D = I.S = [];
        for (N || (L = [N++]); C < i; )
          D[C] = C++;
        for (C = 0; C < i; C++)
          D[C] = D[O = h & O + L[C % N] + (x = D[C])], D[O] = x;
        (I.g = function(F) {
          for (var k, B = 0, V = I.i, P = I.j, G = I.S; F--; )
            k = G[V = h & V + 1], B = B * i + G[h & (G[V] = G[P = h & P + k]) + (G[P] = k)];
          return I.i = V, I.j = P, B;
        })(i);
      }
      function m(L, x) {
        return x.i = L.i, x.j = L.j, x.S = L.S.slice(), x;
      }
      function g(L, x) {
        var N = [], I = typeof L, C;
        if (x && I == "object")
          for (C in L)
            try {
              N.push(g(L[C], x - 1));
            } catch (O) {
            }
        return N.length ? N : I == "string" ? L : L + "\0";
      }
      function y(L, x) {
        for (var N = L + "", I, C = 0; C < N.length; )
          x[h & C] = h & (I ^= x[h & C] * 19) + N.charCodeAt(C++);
        return b(x);
      }
      function w() {
        try {
          var L;
          return d && (L = d.randomBytes) ? L = L(i) : (L = new Uint8Array(i), (r.crypto || r.msCrypto).getRandomValues(L)), b(L);
        } catch (I) {
          var x = r.navigator, N = x && x.plugins;
          return [+new Date(), r, N, r.screen, b(t)];
        }
      }
      function b(L) {
        return String.fromCharCode.apply(0, L);
      }
      if (y(e.random(), t), n.exports) {
        n.exports = p;
        try {
          d = Ts();
        } catch (L) {
        }
      }
    })([], Math);
  });
  Xr.alea = HT;
  Xr.xor128 = VT;
  Xr.xorwow = GT;
  Xr.xorshift7 = qT;
  Xr.xor4096 = YT;
  Xr.tychei = KT;
  var jT = Xr, rh = jT.alea;
  var ih = function() {
    function n(t, e, r, i, a) {
      this.mean = t, this.stdDev = e, this.dtype = r, this.nextVal = NaN, this.truncated = i, this.truncated && (this.upper = this.mean + this.stdDev * 2, this.lower = this.mean - this.stdDev * 2);
      var s = a || Math.random();
      this.random = rh(s.toString());
    }
    return n.prototype.nextValue = function() {
      if (!isNaN(this.nextVal)) {
        var t = this.nextVal;
        return this.nextVal = NaN, t;
      }
      for (var e, r, i = false; !i; ) {
        var a = void 0, s = void 0, o = void 0;
        do
          a = 2 * this.random() - 1, s = 2 * this.random() - 1, o = a * a + s * s;
        while (o >= 1 || o === 0);
        var c = Math.sqrt(-2 * Math.log(o) / o);
        e = this.mean + this.stdDev * a * c, r = this.mean + this.stdDev * s * c, (!this.truncated || this.isValidTruncated(e)) && (i = true);
      }
      return (!this.truncated || this.isValidTruncated(r)) && (this.nextVal = this.convertValue(r)), this.convertValue(e);
    }, n.prototype.convertValue = function(t) {
      return this.dtype == null || this.dtype === "float32" ? t : Math.round(t);
    }, n.prototype.isValidTruncated = function(t) {
      return t <= this.upper && t >= this.lower;
    }, n;
  }(), $T = function() {
    function n(t, e, r, i) {
      this.alpha = t, this.beta = 1 / e, this.dtype = r;
      var a = i || Math.random();
      this.randu = rh(a.toString()), this.randn = new ih(0, 1, r, false, this.randu()), t < 1 ? this.d = t + 2 / 3 : this.d = t - 1 / 3, this.c = 1 / Math.sqrt(9 * this.d);
    }
    return n.prototype.nextValue = function() {
      for (var t, e, r, i, a, s; ; ) {
        do
          i = this.randn.nextValue(), s = 1 + this.c * i;
        while (s <= 0);
        if (s *= s * s, t = i * i, e = 1 - 0.331 * t * t, r = 0.5 * t + this.d * (1 - s + Math.log(s)), a = this.randu(), a < e || Math.log(a) < r)
          break;
      }
      return s = 1 / this.beta * this.d * s, this.alpha < 1 && (s *= Math.pow(this.randu(), 1 / this.alpha)), this.convertValue(s);
    }, n.prototype.convertValue = function(t) {
      return this.dtype === "float32" ? t : Math.round(t);
    }, n;
  }(), XT = function() {
    function n(t, e, r, i) {
      var a = this;
      if (t === void 0 && (t = 0), e === void 0 && (e = 1), this.canReturnFloat = function() {
        return a.dtype == null || a.dtype === "float32";
      }, this.min = t, this.range = e - t, this.dtype = r, i == null && (i = Math.random()), typeof i == "number" && (i = i.toString()), !this.canReturnFloat() && this.range <= 1)
        throw new Error("The difference between " + t + " - " + e + " <= 1 and dtype is not float");
      this.random = rh(i);
    }
    return n.prototype.convertValue = function(t) {
      return this.canReturnFloat() ? t : Math.round(t);
    }, n.prototype.nextValue = function() {
      return this.convertValue(this.min + this.range * this.random());
    }, n;
  }();
  function JT(n, t, e, r, i) {
    if (e === void 0 && (e = 1), r === void 0 && (r = "float32"), e == null && (e = 1), r == null && (r = "float32"), r !== "float32" && r !== "int32")
      throw new Error("Unsupported data type " + r);
    for (var a = new $T(t, e, r, i), s = En(n, r), o = 0; o < s.values.length; o++)
      s.values[o] = a.nextValue();
    return s.toTensor();
  }
  var ZT = U({randomGamma_: JT});
  function QT(n, t, e, r, i) {
    if (t === void 0 && (t = 0), e === void 0 && (e = 1), r != null && r === "bool")
      throw new Error("Unsupported data type " + r);
    for (var a = new ih(t, e, r, false, i), s = En(n, r), o = 0; o < s.values.length; o++)
      s.values[o] = a.nextValue();
    return s.toTensor();
  }
  var eN = U({randomNormal_: QT});
  function tN(n, t, e, r, i) {
    t === void 0 && (t = 0), e === void 0 && (e = 1), r === void 0 && (r = "float32");
    for (var a = En(n, r), s = new XT(t, e, null, i), o = 0; o < a.values.length; o++)
      a.values[o] = s.nextValue();
    return a.toTensor();
  }
  var e0 = U({randomUniform_: tN});
  function Ui(n, t) {
    Ur(n);
    var e = On(n, t);
    if (e.length !== 1)
      throw new Error("tensor1d() requires values to be a flat/TypedArray");
    var r = null;
    return ur(n, r, e, t);
  }
  function ah(n, t, e, r) {
    if (e === void 0 && (e = 1), r === void 0 && (r = "float32"), e === 0)
      throw new Error("Cannot have a step of zero");
    var i = function() {
      var s = n === t, o = n < t && e < 0, c = t < n && e > 1;
      if (s || o || c)
        return jn([0], r);
      var l = Math.abs(Math.ceil((t - n) / e)), u = Li(l, r);
      t < n && e === 1 && (e = -1), u[0] = n;
      for (var h = 1; h < u.length; h++)
        u[h] = u[h - 1] + e;
      return Ui(u, r);
    }, a = {start: n, stop: t, step: e, dtype: r};
    return z.runKernelFunc(i, {}, null, um, a);
  }
  function nN(n) {
    var t = R(n, "x", "reciprocal"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.reciprocal(t);
      return i([t]), a;
    }, e, null, Nl);
  }
  var t0 = U({reciprocal_: nN});
  function rN(n) {
    var t = R(n, "x", "relu"), e = function(i, a) {
      return a([t]), t.dtype === "bool" ? he(t, "int32") : i.relu(t);
    }, r = {x: t};
    return z.runKernelFunc(e, r, null, _l);
  }
  var Da = U({relu_: rN});
  function iN(n) {
    var t = R(n, "x", "relu6"), e = function(i, a) {
      return a([t]), t.dtype === "bool" ? he(t, "int32") : i.relu6(t);
    }, r = {x: t};
    return z.runKernelFunc(e, r, null, El);
  }
  var sh = U({relu6_: iN});
  function aN(n, t) {
    var e = R(n, "x", "reverse"), r = function(s) {
      var o = rt(t, e.shape);
      if (e.rank === 0)
        return Pr(e);
      var c = s.reverse(e, o);
      return Y(c, e.shape);
    }, i = {x: e}, a = {dims: t};
    return z.runKernelFunc(r, i, null, Dl, a);
  }
  var Xn = U({reverse_: aN});
  function sN(n) {
    var t = R(n, "x", "reverse");
    return E(t.rank === 1, function() {
      return "Error in reverse1D: x must be rank 1 but got rank " + t.rank + ".";
    }), Xn(t, 0);
  }
  var oN = U({reverse1d_: sN});
  function cN(n, t) {
    var e = R(n, "x", "reverse");
    return E(e.rank === 2, function() {
      return "Error in reverse2D: x must be rank 2 but got rank " + e.rank + ".";
    }), Xn(e, t);
  }
  var lN = U({reverse2d_: cN});
  function uN(n, t) {
    var e = R(n, "x", "reverse");
    return E(e.rank === 3, function() {
      return "Error in reverse3D: x must be rank 3 but got rank " + e.rank + ".";
    }), Xn(e, t);
  }
  var hN = U({reverse3d_: uN});
  function dN(n, t) {
    var e = R(n, "x", "reverse");
    return E(e.rank === 4, function() {
      return "Error in reverse4D: x must be rank 4 but got rank " + e.rank + ".";
    }), Xn(e, t);
  }
  var pN = U({reverse4d_: dN});
  function fN(n) {
    var t = R(n, "x", "round"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.round(t);
    }, e, null, kl);
  }
  var n0 = U({round_: fN});
  function mN(n) {
    var t = R(n, "x", "rsqrt"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.rsqrt(t);
      return i([t]), a;
    }, e, null, Fl);
  }
  var oh = U({rsqrt_: mN});
  function gN(n) {
    var t = R(n, "x", "selu"), e = function(i, a) {
      var s = i.selu(t);
      return a([t]), s;
    }, r = {x: t};
    return z.runKernelFunc(e, r, null, Ul);
  }
  var r0 = U({selu_: gN});
  function yN(n, t, e, r, i, a, s) {
    a === void 0 && (a = [1, 1]), s === void 0 && (s = "NHWC");
    var o = R(n, "x", "separableConv2d"), c = R(t, "depthwiseFilter", "separableConv2d"), l = R(e, "pointwiseFilter", "separableConv2d"), u = o, h = false;
    if (o.rank === 3 && (h = true, u = Y(o, [1, o.shape[0], o.shape[1], o.shape[2]])), s === "NCHW")
      throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");
    E(u.rank === 4, function() {
      return "Error in separableConv2d: input must be rank 4, but got " + ("rank " + u.rank + ".");
    }), E(c.rank === 4, function() {
      return "Error in separableConv2d: depthwise filter must be rank 4, but " + ("got rank " + c.rank + ".");
    }), E(l.rank === 4, function() {
      return "Error in separableConv2d: pointwise filter must be rank 4, but " + ("got rank " + c.rank + ".");
    }), E(l.shape[0] === 1, function() {
      return "Error in separableConv2d: the first dimension of pointwise filter " + (" must be 1, but got " + l.shape[0] + ".");
    }), E(l.shape[1] === 1, function() {
      return "Error in separableConv2d: the second dimension of pointwise " + ("filter must be 1, but got " + l.shape[1] + ".");
    });
    var d = c.shape[2], p = c.shape[3];
    E(l.shape[2] === d * p, function() {
      return "Error in separableConv2d: the third dimension of pointwise filter " + ("must be " + d * p + ", ") + ("but got " + l.shape[2] + ".");
    });
    var f = Ca(u, c, r, i, s, a), m = 1, g = Ei(f, l, m, "valid", s);
    return h ? Y(g, [g.shape[1], g.shape[2], g.shape[3]]) : g;
  }
  var i0 = U({separableConv2d_: yN});
  function vN(n, t) {
    return pe(this, void 0, void 0, function() {
      var e, r, i, a, s, o, c, l, u, c, h;
      return fe(this, function(d) {
        switch (d.label) {
          case 0:
            return e = R(n, "x", "setdiff1d"), r = R(t, "y", "setdiff1d"), E(e.dtype === r.dtype, function() {
              return "x and y should have the same dtype, but got x (" + e.dtype + ") and y (" + r.dtype + ").";
            }), E(e.rank === 1, function() {
              return "x should be 1D tensor, but got x (" + e.shape + ").";
            }), E(r.rank === 1, function() {
              return "y should be 1D tensor, but got y (" + r.shape + ").";
            }), [4, e.data()];
          case 1:
            return i = d.sent(), [4, r.data()];
          case 2:
            for (a = d.sent(), s = new Set(a), o = 0, c = 0; c < i.length; c++)
              s.has(i[c]) || o++;
            for (l = new Fs([o], e.dtype), u = new Fs([o], "int32"), c = 0, h = 0; c < i.length; c++)
              s.has(i[c]) || (l.values[h] = i[c], u.values[h] = c, h++);
            return [2, [l.toTensor(), u.toTensor()]];
        }
      });
    });
  }
  var wN = vN;
  function bN(n) {
    var t = R(n, "x", "sign"), e = {x: t};
    return z.runKernelFunc(function(r) {
      return r.sign(t);
    }, e, null, Ml);
  }
  var a0 = U({sign_: bN});
  function xN(n) {
    var t = R(n, "x", "sin"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.sin(t);
      return i([t]), a;
    }, e, null, zl);
  }
  var ch = U({sin_: xN});
  function LN(n) {
    var t = R(n, "x", "sinh"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.sinh(t);
      return i([t]), a;
    }, e, null, Pl);
  }
  var lh = U({sinh_: LN});
  function SN(n, t, e) {
    var r = R(n, "x", "slice1d");
    return E(r.rank === 1, function() {
      return "slice1d expects a rank-1 tensor, but got a rank-" + r.rank + " tensor";
    }), Me(r, [t], [e]);
  }
  var IN = U({slice1d_: SN});
  function AN(n, t, e) {
    var r = R(n, "x", "slice2d");
    return E(r.rank === 2, function() {
      return "slice2d expects a rank-2 tensor, but got a rank-" + r.rank + " tensor";
    }), Me(r, t, e);
  }
  var TN = U({slice2d_: AN});
  function NN(n, t, e) {
    var r = R(n, "x", "slice3d");
    return E(r.rank === 3, function() {
      return "slice3d expects a rank-3 tensor, but got a rank-" + r.rank + " tensor";
    }), Me(r, t, e);
  }
  var _N = U({slice3d_: NN});
  function CN(n, t, e) {
    var r = R(n, "x", "slice4d");
    return E(r.rank === 4, function() {
      return "slice4d expects a rank-4 tensor, but got a rank-" + r.rank + " tensor";
    }), Me(r, t, e);
  }
  var RN = U({slice4d_: CN});
  function ON(n, t) {
    t === void 0 && (t = -1);
    var e = R(n, "logits", "softmax", "float32");
    if (t === -1 && (t = e.rank - 1), t !== e.rank - 1)
      throw Error("Softmax along a non-last dimension is not yet supported. " + ("Logits was rank " + e.rank + " and dim was " + t));
    var r = {logits: e}, i = {dim: t};
    return z.runKernelFunc(function(a, s) {
      var o = a.softmax(e, t);
      return s([o]), o;
    }, r, null, jl, i);
  }
  var s0 = U({softmax_: ON});
  function EN(n) {
    E(n.dtype === "complex64", function() {
      return "The dtype for tf.spectral.fft() must be complex64 " + ("but got " + n.dtype + ".");
    });
    var t = {input: n};
    return z.runKernelFunc(function(e) {
      var r = n.shape[n.shape.length - 1], i = n.size / r, a = n.as2D(i, r), s = e.fft(a);
      return s.reshape(n.shape);
    }, t, null, Mf);
  }
  var io = U({fft_: EN});
  function DN(n) {
    E(n.dtype === "complex64", function() {
      return "The dtype for tf.spectral.ifft() must be complex64 " + ("but got " + n.dtype + ".");
    });
    var t = {input: n};
    return z.runKernelFunc(function(e) {
      var r = n.shape[n.shape.length - 1], i = n.size / r, a = Y(n, [i, r]), s = e.ifft(a);
      return Y(s, n.shape);
    }, t, null, Yf);
  }
  var ka = U({ifft_: DN});
  function kN(n) {
    var t = n.shape[n.shape.length - 1], e = n.size / t, r;
    if (t <= 2) {
      var i = Y(n, [e, t]);
      r = ka(i);
    } else {
      var a = [e, 2 * (t - 1)], s = Y(Ea(n), [e, t]), o = Y(Xs(n), [e, t]), c = Xn(Me(s, [0, 1], [e, t - 2]), 1), l = Z(Xn(Me(o, [0, 1], [e, t - 2]), 1), Le(-1)), u = Et([s, c], 1), h = Et([o, l], 1), i = Y(lr(u, h), [a[0], a[1]]);
      r = ka(i);
    }
    if (r = Ea(r), n.rank === 3 && n.shape[0] !== 0) {
      var d = r, p = n.shape[0];
      r = Y(r, [p, r.shape[0] / p, r.shape[1]]), d.dispose();
    }
    return r;
  }
  var uh = U({irfft_: kN});
  function o0(n, t, e) {
    e === void 0 && (e = 0);
    var r = [];
    if (typeof t == "number")
      E(n.shape[e] % t === 0, function() {
        return "Number of splits must evenly divide the axis.";
      }), r = new Array(t).fill(n.shape[e] / t);
    else {
      var i = t.reduce(function(o, c) {
        return c === -1 && (o += 1), o;
      }, 0);
      E(i <= 1, function() {
        return "There should be only one negative value in split array.";
      });
      var a = t.indexOf(-1);
      if (a !== -1) {
        var s = t.reduce(function(o, c) {
          return c > 0 ? o + c : o;
        });
        t[a] = n.shape[e] - s;
      }
      E(n.shape[e] === t.reduce(function(o, c) {
        return o + c;
      }), function() {
        return "The sum of sizes must match the size of the axis dimension.";
      }), r = t;
    }
    return r;
  }
  function FN(n, t, e) {
    e === void 0 && (e = 0);
    var r = R(n, "x", "split"), i = function(o, c) {
      var l = rt(e, r.shape)[0], u = o0(r, t, l);
      return o.split(r, u, l);
    }, a = {x: r}, s = {numOrSizeSplits: t, axis: e};
    return z.runKernelFunc(i, a, null, Kl, s);
  }
  var Bi = U({split_: FN});
  function WN(n, t) {
    E(n.dtype === "float32", function() {
      return "The dtype for rfft() must be real value but got " + n.dtype;
    });
    var e = n.shape[n.shape.length - 1], r = n.size / e, i;
    if (t != null && t < e) {
      var a = n.shape.map(function(y) {
        return 0;
      }), s = n.shape.map(function(y) {
        return y;
      });
      s[n.shape.length - 1] = t, i = Me(n, a, s), e = t;
    } else if (t != null && t > e) {
      var o = n.shape.map(function(y) {
        return y;
      });
      o[n.shape.length - 1] = t - e, i = Et([n, jn(o)], n.shape.length - 1), e = t;
    } else
      i = n;
    var c = ke(i), l = Y(lr(i, c), [r, e]), u = io(l), h = Math.floor(e / 2) + 1, d = Ea(u), p = Xs(u), f = Bi(d, [h, e - h], d.shape.length - 1), m = Bi(p, [h, e - h], p.shape.length - 1), g = i.shape.slice();
    return g[i.shape.length - 1] = h, Y(lr(f[0], m[0]), g);
  }
  var ao = U({rfft_: WN});
  function UN(n) {
    var t = R(n, "x", "sqrt"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.sqrt(t);
      return i([t]), a;
    }, e, null, Gl);
  }
  var Ht = U({sqrt_: UN});
  function BN(n, t) {
    var e, r = R(n, "a", "squaredDifference"), i = R(t, "b", "squaredDifference");
    e = ct(r, i), r = e[0], i = e[1], it(r.shape, i.shape);
    var a = function(c, l) {
      var u = c.squaredDifference(r, i);
      return l([r, i]), u;
    }, s = {a: r, b: i}, o = {};
    return z.runKernelFunc(a, s, null, $l, o);
  }
  var so = U({squaredDifference_: BN});
  function zN(n, t) {
    var e = R(n, "x", "squeeze");
    return Y(e, uf(e.shape, t).newShape);
  }
  var oo = U({squeeze_: zN});
  function PN(n, t) {
    t === void 0 && (t = 0);
    var e = Sa(n, "tensors", "stack");
    if (E(e.length >= 1, function() {
      return "Pass at least one tensor to tf.stack";
    }), e.length === 1)
      return wn(e[0], t);
    var r = e[0].rank, i = e[0].shape, a = e[0].dtype;
    E(t <= r, function() {
      return "Axis must be <= rank of the tensor";
    }), e.forEach(function(o) {
      Pe(i, o.shape, "All tensors passed to stack must have matching shapes"), E(a === o.dtype, function() {
        return "All tensors passed to stack must have matching dtypes";
      });
    });
    var s = e.map(function(o) {
      return wn(o, t);
    });
    return Et(s, t);
  }
  var Jr = U({stack_: PN});
  function MN(n, t) {
    t === void 0 && (t = 0);
    var e = R(n, "x", "step"), r = {x: e}, i = {alpha: t};
    return z.runKernelFunc(function(a) {
      return a.step(e, t);
    }, r, null, iu, i);
  }
  var zi = U({step_: MN});
  function HN(n, t, e, r, i, a, s, o, c) {
    i === void 0 && (i = 0), a === void 0 && (a = 0), s === void 0 && (s = 0), o === void 0 && (o = 0), c === void 0 && (c = 0);
    var l = R(n, "x", "stridedSlice"), u = function(p) {
      r == null && (r = new Array(t.length));
      var f = Ps(s);
      if (f.length > 1)
        throw new Error("Multiple ellipses in slice is not allowed.");
      if (s !== 0 && o !== 0)
        throw new Error("Using both ellipsisMask and newAxisMask is not yet supported.");
      if (s !== 0 && c !== 0)
        throw new Error("Using both ellipsisMask and shrinkAxisMask is not yet supported.");
      var m = l.rank - t.length, g = Ps(o), y = l.shape.slice();
      g.forEach(function(F) {
        t[F] = 0, e[F] = 1, y.splice(F, 0, 1);
      }), l = Y(l, y);
      var w = cg(l.shape, f, m, t, e, r, i, a, s), b = w.begin, L = w.end, x = w.strides;
      t = b, e = L, r = x;
      var N = Ps(c);
      N.forEach(function(F) {
        e[F] = t[F] + 1, r[F] = 1;
      });
      var I = Qm(t, e, r), C = I.filter(function(F, k) {
        return N.indexOf(k) === -1;
      }), O = r.every(function(F) {
        return F === 1;
      });
      if (O)
        return Y(Me(l, t, I), C);
      var D = p.stridedSlice(l, t, e, r);
      return Y(D, C);
    }, h = {x: l}, d = {begin: t, end: e, strides: r, beginMask: i, endMask: a, ellipsisMask: s, newAxisMask: o, shrinkAxisMask: c};
    return z.runKernelFunc(u, h, null, ym, d);
  }
  var c0 = U({stridedSlice_: HN});
  function VN(n) {
    var t = R(n, "x", "tan"), e = {x: t};
    return z.runKernelFunc(function(r, i) {
      var a = r.tan(t);
      return i([t]), a;
    }, e, null, Jl);
  }
  var l0 = U({tan_: VN});
  function Fa(n, t, e) {
    if (Ur(n), t != null && t.length !== 2)
      throw new Error("tensor2d() requires shape to have two numbers");
    var r = On(n, e);
    if (r.length !== 2 && r.length !== 1)
      throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");
    if (r.length === 1 && t == null)
      throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray");
    return ur(n, t, r, e);
  }
  function GN(n, t, e) {
    if (Ur(n), t != null && t.length !== 4)
      throw new Error("tensor4d() requires shape to have four numbers");
    var r = On(n, e);
    if (r.length !== 4 && r.length !== 1)
      throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");
    if (r.length === 1 && t == null)
      throw new Error("tensor4d() requires shape to be provided when `values` are a flat array");
    return ur(n, t, r, e);
  }
  function qN(n, t, e) {
    if (Ur(n), t != null && t.length !== 5)
      throw new Error("tensor5d() requires shape to have five numbers");
    var r = On(n, e);
    if (r.length !== 5 && r.length !== 1)
      throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");
    if (r.length === 1 && t == null)
      throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");
    return ur(n, t, r, e);
  }
  function YN(n, t, e) {
    if (Ur(n), t != null && t.length !== 6)
      throw new Error("tensor6d() requires shape to have six numbers");
    var r = On(n, e);
    if (r.length !== 6 && r.length !== 1)
      throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");
    if (r.length === 1 && t == null)
      throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");
    return t = t || r, ur(n, t, r, e);
  }
  function KN(n, t, e) {
    t === void 0 && (t = 1), e === void 0 && (e = true);
    var r = R(n, "x", "topk");
    if (r.rank === 0)
      throw new Error("topk() expects the input to be of rank 1 or higher");
    var i = r.shape[r.shape.length - 1];
    if (t > i)
      throw new Error("'k' passed to topk() must be <= the last dimension (" + i + ") " + ("but got " + t));
    var a = {x: r}, s = {k: t, sorted: e}, o = z.runKernelFunc(function(u) {
      return u.topk(r, t, e);
    }, a, null, vm, s), c = o[0], l = o[1];
    return {values: c, indices: l};
  }
  var u0 = U({topk_: KN});
  function jN(n, t, e, r, i) {
    if (t === void 0 && (t = 0), e === void 0 && (e = 1), r != null && r === "bool")
      throw new Error("Unsupported data type $ { dtype }");
    for (var a = new ih(t, e, r, true, i), s = En(n, r), o = 0; o < s.values.length; o++)
      s.values[o] = a.nextValue();
    return s.toTensor();
  }
  var $N = U({truncatedNormal_: jN});
  function XN(n, t) {
    t === void 0 && (t = 0);
    var e = R(n, "x", "unique", null);
    E(e.rank > 0, function() {
      return "The input tensor must be at least 1D";
    });
    var r = {x: e}, i = {axis: t}, a = z.runKernel(wm, r, i), s = a[0], o = a[1];
    return {values: s, indices: o};
  }
  var h0 = U({unique_: XN});
  function JN(n, t, e) {
    var r = R(n, "x", "unsortedSegmentSum"), i = R(t, "segmentIds", "unsortedSegmentSum", "int32");
    E(ot(e), function() {
      return "numSegments must be of dtype int";
    });
    var a = {x: r, segmentIds: i}, s = {numSegments: e}, o = function(c, l) {
      var u = c.unsortedSegmentSum(r, i, e);
      return l([i]), u;
    };
    return z.runKernelFunc(o, a, null, nu, s);
  }
  var hh = U({unsortedSegmentSum_: JN});
  function ZN(n, t) {
    t === void 0 && (t = 0);
    var e = R(n, "x", "unstack");
    E(t >= -e.shape.length && t < e.shape.length, function() {
      return "Axis = " + t + " is not in [-" + e.shape.length + ", " + e.shape.length + ")";
    }), t < 0 && (t += e.shape.length);
    var r = {value: e}, i = {axis: t}, a = function(s) {
      return s.unstack(e, t);
    };
    return z.runKernelFunc(a, r, null, tu, i);
  }
  var co = U({unstack_: ZN});
  function QN(n, t, e, r) {
    return t === void 0 && (t = true), z.makeVariable(n, t, e, r);
  }
  function d0(n, t) {
    for (var e = [], r = 0; r < t.length; r++)
      t[r] && e.push(r);
    for (var i = En(n, "int32"), a = En([e.length, n.length], "int32"), r = 0; r < e.length; r++) {
      var s = i.indexToLoc(e[r]), o = r * n.length;
      a.values.set(s, o);
    }
    return a.toTensor();
  }
  function e_(n) {
    return pe(this, void 0, void 0, function() {
      var t, e, r;
      return fe(this, function(i) {
        switch (i.label) {
          case 0:
            return t = R(n, "condition", "whereAsync", "bool"), [4, t.data()];
          case 1:
            return e = i.sent(), r = d0(t.shape, e), n !== t && t.dispose(), [2, r];
        }
      });
    });
  }
  var p0 = e_;
  function t_(n, t, e) {
    return pe(this, void 0, void 0, function() {
      var r, i, a, s, o, c, l, u, h, d, p, f, m;
      return fe(this, function(g) {
        switch (g.label) {
          case 0:
            for (r = R(n, "tensor", "boolMask"), i = R(t, "mask", "boolMask", "bool"), a = e == null ? 0 : e, s = i.rank, o = r.shape, E(s > 0, function() {
              return "mask cannot be scalar";
            }), Pe(o.slice(a, a + s), i.shape, "mask's shape must match the first K dimensions of tensor's shape,"), c = 1, l = a; l < a + s; l++)
              c *= o[l];
            return u = o.slice(0, a).concat([c], o.slice(a + s)), h = Y(r, u), d = Y(i, [-1]), [4, p0(d)];
          case 1:
            return p = g.sent(), f = oo(p, [1]), m = $s(h, f, a), n !== r && r.dispose(), t !== i && i.dispose(), f.dispose(), h.dispose(), d.dispose(), p.dispose(), [2, m];
        }
      });
    });
  }
  var n_ = t_;
  function r_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "notEqualStrict"), r = R(t, "b", "notEqualStrict");
    return Pe(e.shape, r.shape, "Error in notEqualStrict: "), no(e, r);
  }
  function i_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "lessStrict"), r = R(t, "b", "lessStrict");
    return Pe(e.shape, r.shape, "Error in lessStrict: "), Js(e, r);
  }
  function a_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "equalStrict"), r = R(t, "b", "equalStrict");
    return Pe(e.shape, r.shape, "Error in equalStrict: "), Ra(e, r);
  }
  function s_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "lessEqualStrict"), r = R(t, "b", "lessEqualStrict");
    return Pe(e.shape, r.shape, "Error in lessEqualStrict: "), Gr(e, r);
  }
  function o_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "greaterStrict"), r = R(t, "b", "greaterStrict");
    return Pe(e.shape, r.shape, "Error in greaterStrict: "), gr(e, r);
  }
  function c_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "greaterEqualStrict"), r = R(t, "b", "greaterEqualStrict");
    return Pe(e.shape, r.shape, "Error in greaterEqualStrict: "), Vr(e, r);
  }
  var f0 = U({equalStrict_: a_}), m0 = U({greaterEqualStrict_: c_}), g0 = U({greaterStrict_: o_}), y0 = U({lessEqualStrict_: s_}), v0 = U({lessStrict_: i_}), w0 = U({notEqualStrict_: r_});
  function l_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "addStrict"), r = R(t, "b", "addStrict");
    return Pe(e.shape, r.shape, "Error in addStrict: "), ge(e, r);
  }
  function u_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "subStrict"), r = R(t, "b", "subStrict");
    return Pe(e.shape, r.shape, "Error in subStrict: "), be(e, r);
  }
  function h_(n, t) {
    return Nt("strict variants of ops have been deprecated and will be removed in future"), Pe(n.shape, t.shape, "Error in powStrict: "), $n(n, t);
  }
  function d_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "mul"), r = R(t, "b", "mul");
    return Pe(e.shape, r.shape, "Error in multiplyStrict: "), Z(e, r);
  }
  function p_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "div"), r = R(t, "b", "div");
    return Pe(e.shape, r.shape, "Error in divideStrict: "), Ne(e, r);
  }
  function f_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "modStrict"), r = R(t, "b", "modStrict");
    return Pe(e.shape, r.shape, "Error in modStrict: "), eh(e, r);
  }
  function m_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "minimumStrict"), r = R(t, "b", "minimumStrict");
    return Pe(e.shape, r.shape, "Error in minimumStrict: "), to(e, r);
  }
  function g_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "maximumStrict"), r = R(t, "b", "maximumStrict");
    return Pe(e.shape, r.shape, "Error in maximumStrict: "), ki(e, r);
  }
  function y_(n, t) {
    Nt("strict variants of ops have been deprecated and will be removed in future");
    var e = R(n, "a", "squaredDifferenceStrict"), r = R(t, "b", "squaredDifferenceStrict");
    return Pe(e.shape, r.shape, "Error in squaredDifferenceStrict: "), so(e, r);
  }
  var b0 = U({addStrict_: l_}), x0 = U({divStrict_: p_}), L0 = U({maximumStrict_: g_}), S0 = U({minimumStrict_: m_}), I0 = U({modStrict_: f_}), A0 = U({mulStrict_: d_}), T0 = U({powStrict_: h_}), N0 = U({squaredDifferenceStrict_: y_}), _0 = U({subStrict_: u_});
  function v_(n, t, e, r) {
    t === void 0 && (t = "euclidean"), e === void 0 && (e = null), r === void 0 && (r = false), n = R(n, "x", "norm");
    var i = C0(n, t, e), a = i.shape;
    if (r) {
      var s = rt(e, n.shape);
      a = an(i.shape, s);
    }
    return Y(i, a);
  }
  function C0(n, t, e) {
    if (e === void 0 && (e = null), n.rank === 0)
      return jt(n);
    if (n.rank !== 1 && e === null)
      return C0(Y(n, [-1]), t, e);
    if (n.rank === 1 || typeof e == "number" || Array.isArray(e) && e.length === 1) {
      if (t === 1)
        return _e(jt(n), e);
      if (t === Infinity)
        return Yr(jt(n), e);
      if (t === -Infinity)
        return eo(jt(n), e);
      if (t === "euclidean" || t === 2)
        return Ht(_e($n(jt(n), Le(2, "int32")), e));
      throw new Error("Error in norm: invalid ord value: " + t);
    }
    if (Array.isArray(e) && e.length === 2) {
      if (t === 1)
        return Yr(_e(jt(n), e[0]), e[1] - 1);
      if (t === Infinity)
        return Yr(_e(jt(n), e[1]), e[0]);
      if (t === -Infinity)
        return eo(_e(jt(n), e[1]), e[0]);
      if (t === "fro" || t === "euclidean")
        return Ht(_e($e(n), e));
      throw new Error("Error in norm: invalid ord value: " + t);
    }
    throw new Error("Error in norm: invalid axis: " + e);
  }
  var lo = U({norm_: v_});
  function w_(n, t, e, r, i) {
    i === void 0 && (i = true);
    var a = R(n, "v", "movingAverage"), s = R(t, "x", "movingAverage"), o = R(e, "decay", "movingAverage");
    Am(a, s), E(fn(a.shape, s.shape), function() {
      return "Shape mismatch in v and x";
    });
    var c = Le(1), l = be(c, o), u = Z(be(s, a), l);
    if (i) {
      E(r != null, function() {
        return "When using zeroDebias: true, step is required.";
      });
      var h = R(r, "step", "movingAverage");
      u = Ne(u, be(c, $n(o, h)));
    }
    return ge(a, u);
  }
  var b_ = U({movingAverage_: w_});
  function x_(n, t, e) {
    var r = R(n, "indices", "scatterND", "int32"), i = R(t, "updates", "scatterND");
    Du(i, r, e);
    var a = function(c) {
      return c.scatterND(r, i, e);
    }, s = {indices: r, updates: i}, o = {shape: e};
    return z.runKernelFunc(a, s, null, fm, o);
  }
  var L_ = U({scatterND_: x_});
  function S_(n, t, e, r) {
    if (n.dtype !== "int32")
      throw new Error("tf.sparseToDense() expects the indices to be int32 type," + (" but the dtype was " + n.dtype + "."));
    if (n.rank > 2)
      throw new Error("sparseIndices should be a scalar, vector, or matrix," + (" but got shape " + n.shape + "."));
    var i = n.rank > 0 ? n.shape[0] : 1, a = n.rank > 1 ? n.shape[1] : 1;
    if (e.length !== a)
      throw new Error("outputShape has incorrect number of elements:," + (" " + e.length + ", should be: " + a + "."));
    var s = t.size;
    if (!(t.rank === 0 || t.rank === 1 && s === i))
      throw new Error("sparseValues has incorrect shape " + (t.shape + ", should be [] or [" + i + "]"));
    if (t.dtype !== r.dtype)
      throw new Error("sparseValues.dtype must match defaultValues.dtype");
  }
  function I_(n, t, e, r) {
    r === void 0 && (r = 0);
    var i = R(n, "sparseIndices", "sparseToDense", "int32"), a = R(t, "sparseValues", "sparseToDense"), s = R(r, "defaultValue", "sparseToDense", a.dtype);
    S_(i, a, e, s);
    var o = {sparseIndices: i, sparseValues: a, defaultValue: s}, c = {outputShape: e};
    return z.runKernelFunc(function(l) {
      return l.sparseToDense(i, a, e, s);
    }, o, null, gm, c);
  }
  var A_ = U({sparseToDense_: I_});
  function T_(n, t) {
    var e = R(t, "indices", "gatherND", "int32"), r = R(n, "x", "gatherND"), i = function(s) {
      return s.gatherND(r, e);
    }, a = {params: r, indices: e};
    return z.runKernelFunc(i, a, null, Gf);
  }
  var N_ = U({gatherND_: T_});
  function __(n, t) {
    if (t == null)
      return n.shape.slice();
    if (fn(n.shape, t))
      return t;
    if (n.shape.length === t.length) {
      for (var e = [], r = 0; r < n.shape.length; r++)
        t[r] == null && n.shape[r] != null ? e.push(n.shape[r]) : e.push(t[r]);
      return e;
    }
    return t;
  }
  function C_(n, t, e, r) {
    var i = R(n, "x", "dropout");
    if (E(i.dtype === "float32", function() {
      return "x has to be a floating point tensor since it's going to be " + ("scaled, but got a " + i.dtype + " tensor instead.");
    }), E(t >= 0 && t < 1, function() {
      return "rate must be a float in the range [0, 1), but got " + t + ".";
    }), t === 0)
      return n instanceof K ? i.clone() : i;
    var a = __(i, e), s = 1 - t, o = Ne(js(ge(e0(a, 0, 1, "float32", r), s)), s);
    return Z(i, o);
  }
  var R_ = U({dropout_: C_});
  function R0(n) {
    return Math.floor(Math.pow(2, Math.ceil(Math.log(n) / Math.log(2))));
  }
  function dh(n, t, e) {
    for (var r = 1 - n % 2, i = new Float32Array(n), a = 0; a < n; ++a) {
      var s = 2 * Math.PI * a / (n + r - 1);
      i[a] = t - e * Math.cos(s);
    }
    return Ui(i, "float32");
  }
  function O_(n, t, e) {
    return e === void 0 && (e = 1), pe(this, void 0, void 0, function() {
      var r, i, a, s, o, c, l, u, h, d, p, f, m, g, g;
      return fe(this, function(y) {
        switch (y.label) {
          case 0:
            return r = R(n, "predictions", "inTopK"), i = R(t, "targets", "inTopK"), E(r.rank > 1, function() {
              return "inTopK() expects the predictions to be of rank 2 or higher, " + ("but got " + r.rank);
            }), E(r.rank - 1 === i.rank, function() {
              return "predictions rank should be 1 larger than targets rank, but got predictions rank " + (r.rank + " and targets rank " + i.rank);
            }), Pe(r.shape.slice(0, r.shape.length - 1), i.shape, "predictions's shape should be align with the targets' shape, except the last dimension."), a = r.shape[r.shape.length - 1], E(e > 0 && e <= a, function() {
              return "'k' passed to inTopK() must be > 0 && <= the predictions last " + ("dimension (" + a + "), but got " + e);
            }), [4, r.data()];
          case 1:
            return s = y.sent(), [4, i.data()];
          case 2:
            for (o = y.sent(), c = [s.length / a, a], l = c[0], u = c[1], h = Ns("bool", l), d = 0; d < l; d++) {
              for (p = d * u, f = s.subarray(p, p + u), m = [], g = 0; g < f.length; g++)
                m.push({value: f[g], index: g});
              for (m.sort(function(w, b) {
                return b.value - w.value;
              }), h[d] = 0, g = 0; g < e; g++)
                if (m[g].index === o[d]) {
                  h[d] = 1;
                  break;
                }
            }
            return n !== r && r.dispose(), t !== i && i.dispose(), [2, hr(h, i.shape, "bool")];
        }
      });
    });
  }
  var E_ = O_;
  function D_(n, t, e, r, i, a, s) {
    a === void 0 && (a = "NHWC");
    var o = n;
    n.rank === 3 && (o = Y(n, [1, n.shape[0], n.shape[1], n.shape[2]]));
    var c = t;
    c.rank === 3 && (c = Y(t, [1, t.shape[0], t.shape[1], t.shape[2]])), E(o.rank === 4, function() {
      return "Error in conv2dDerFilter: input must be rank 4, but got shape " + (o.shape + ".");
    }), E(c.rank === 4, function() {
      return "Error in conv2dDerFilter: dy must be rank 4, but got shape " + (c.shape + ".");
    }), E(e.length === 4, function() {
      return "Error in conv2dDerFilter: filterShape must be length 4, but got " + (e + ".");
    });
    var l = a === "NHWC" ? o.shape[3] : o.shape[1], u = a === "NHWC" ? c.shape[3] : c.shape[1];
    E(l === e[2], function() {
      return "Error in conv2dDerFilter: depth of input " + l + ") must " + ("match input depth in filter (" + e[2] + ".");
    }), E(u === e[3], function() {
      return "Error in conv2dDerFilter: depth of dy (" + u + ") must " + ("match output depth for filter (" + e[3] + ").");
    }), s != null && E(ot(i), function() {
      return "Error in conv2dDerFilter: pad must be an integer when using, " + ("dimRoundingMode " + s + " but got pad " + i + ".");
    });
    var h = function(f) {
      var m = 1, g = Aa(a), y = gn(o.shape, e, r, m, i, s, false, g);
      return f.conv2dDerFilter(o, c, y);
    }, d = {x: o, dy: c}, p = {strides: r, pad: i, dataFormat: a, dimRoundingMode: s, filterShape: e};
    return z.runKernelFunc(h, d, null, Cf, p);
  }
  var ph = U({conv2DBackpropFilter_: D_});
  function uo(n, t, e) {
    if (e == null || e === "linear")
      return n;
    if (e === "relu")
      return Z(n, zi(t));
    throw new Error("Cannot compute gradient for fused activation " + e + ".");
  }
  function ho(n, t) {
    var e = t, r = xt(n.shape, t.shape);
    return r.length > 0 && (e = _e(e, r)), Y(e, n.shape);
  }
  function po(n, t, e) {
    if (t === "linear")
      return n;
    if (t === "relu")
      return Da(n);
    if (t === "elu")
      return Yu(n);
    if (t === "relu6")
      return sh(n);
    if (t === "prelu")
      return nh(n, e);
    throw new Error("Unknown fused activation " + t + ".");
  }
  var fo = function(n, t) {
    var e = n > 0;
    return !e || t === "linear";
  };
  function k_(n) {
    var t = n.x, e = n.filter, r = n.strides, i = n.pad, a = n.dataFormat, s = a === void 0 ? "NHWC" : a, o = n.dilations, c = o === void 0 ? [1, 1] : o, l = n.dimRoundingMode, u = n.bias, h = n.activation, d = h === void 0 ? "linear" : h, p = n.preluActivationWeights;
    if (d = d || "linear", fo(z.state.gradientDepth, d) === false) {
      var f = Ei(t, e, r, i, s, c, l);
      return u != null && (f = ge(f, u)), po(f, d, p);
    }
    var m = R(t, "x", "conv2d"), g = R(e, "filter", "conv2d"), y = m, w = false;
    m.rank === 3 && (w = true, y = Y(m, [1, m.shape[0], m.shape[1], m.shape[2]])), E(y.rank === 4, function() {
      return "Error in fused conv2d: input must be rank 4, but got rank " + (y.rank + ".");
    }), E(g.rank === 4, function() {
      return "Error in fused conv2d: filter must be rank 4, but got rank " + (g.rank + ".");
    }), l != null && E(ot(i), function() {
      return "Error in fused conv2d: pad must be an integer when using, " + ("dimRoundingMode " + l + " but got pad " + i + ".");
    }), E(y.shape[3] === g.shape[2], function() {
      return "Error in conv2d: depth of input (" + y.shape[3] + ") must match " + ("input depth for filter " + g.shape[2] + ".");
    }), E(Mt(r, c), function() {
      return "Error in conv2D: Either strides or dilations must be 1. " + ("Got strides " + r + " and dilations '" + c + "'");
    }), E(s === "NHWC", function() {
      return "Error in conv2d: got dataFormat of " + s + " but only NHWC is currently supported.";
    });
    var b = gn(y.shape, g.shape, r, c, i, l), L;
    u != null && (L = R(u, "bias", "fused conv2d"), L = ct(L, m)[0], it(b.outShape, L.shape));
    var x;
    p != null && (x = R(p, "prelu weights", "fused conv2d"));
    var N = function(k, B) {
      var V = B, P = V[0], G = V[1], j = V[2], q = V[3], H = uo(k, j, d);
      E(mr(c), function() {
        return "Error in gradient of fused conv2D: dilation rates greater than 1 " + ("are not yet supported in gradients. Got dilations '" + c + "'");
      });
      var J = Vu(G.shape, H, P, r, i), $ = ph(G, H, P.shape, r, i), ee = [J, $];
      if (q != null) {
        var te = ho(q, H);
        ee.push(te);
      }
      return ee;
    }, I = function(k) {
      var B = k.fusedConv2d({input: y, filter: g, convInfo: b, bias: L, activation: d, preluActivationWeights: x});
      return B;
    }, C = {x: y, filter: g, bias: L, preluActivationWeights: x}, O = {strides: r, pad: i, dataFormat: s, dilations: c, dimRoundingMode: l, activation: d};
    if (u == null) {
      var D = kn(function(k, B, V) {
        var P = z.runKernelFunc(I, C, null, ou, O);
        return V([B, k, P]), w && (P = Y(P, [P.shape[1], P.shape[2], P.shape[3]])), {value: P, gradFunc: N};
      });
      return D(y, g);
    } else {
      var F = kn(function(k, B, V, P) {
        var G = z.runKernelFunc(I, C, null, ou, O);
        return P([B, k, G, V]), w && (G = Y(G, [G.shape[1], G.shape[2], G.shape[3]])), {value: G, gradFunc: N};
      });
      return F(y, g, L);
    }
  }
  var F_ = U({fusedConv2d_: k_});
  function W_(n, t, e, r, i, a, s) {
    a === void 0 && (a = [1, 1]);
    var o = n;
    n.rank === 3 && (o = Y(n, [1, n.shape[0], n.shape[1], n.shape[2]]));
    var c = t;
    c.rank === 3 && (c = Y(t, [1, t.shape[0], t.shape[1], t.shape[2]]));
    var l = function(d) {
      var p = gn(n.shape, e, r, a, i, s, true);
      return d.depthwiseConv2DDerFilter(o, c, p);
    }, u = {x: o, dy: c}, h = {strides: r, pad: i, dimRoundingMode: s, dilations: a, filterShape: e};
    return z.runKernelFunc(l, u, null, kf, h);
  }
  var O0 = U({depthwiseConv2dNativeBackpropFilter_: W_});
  function U_(n, t, e, r, i, a, s) {
    a === void 0 && (a = [1, 1]);
    var o = t, c = false;
    t.rank === 3 && (c = true, o = Y(t, [1, t.shape[0], t.shape[1], t.shape[2]]));
    var l = function(p) {
      var f = gn(n, e.shape, r, a, i, s, true);
      return p.depthwiseConv2DDerInput(o, e, f);
    }, u = {dy: o, filter: e}, h = {strides: r, pad: i, dimRoundingMode: s, dilations: a, inputShape: n}, d = z.runKernelFunc(l, u, null, Ff, h);
    return c ? Y(d, [d.shape[1], d.shape[2], d.shape[3]]) : d;
  }
  var E0 = U({depthwiseConv2dNativeBackpropInput_: U_});
  function B_(n) {
    var t = n.x, e = n.filter, r = n.strides, i = n.pad, a = n.dataFormat, s = a === void 0 ? "NHWC" : a, o = n.dilations, c = o === void 0 ? [1, 1] : o, l = n.dimRoundingMode, u = n.bias, h = n.activation, d = h === void 0 ? "linear" : h, p = n.preluActivationWeights;
    if (fo(z.state.gradientDepth, d) === false) {
      var f = Ca(t, e, r, i, s, c, l);
      return u != null && (f = ge(f, u)), po(f, d, p);
    }
    var m = R(t, "x", "depthwiseConv2d"), g = R(e, "filter", "depthwiseConv2d"), y = m, w = false;
    m.rank === 3 && (w = true, y = Y(m, [1, m.shape[0], m.shape[1], m.shape[2]])), E(y.rank === 4, function() {
      return "Error in fused depthwiseConv2d: input must be rank 4, but got " + ("rank " + y.rank + ".");
    }), E(g.rank === 4, function() {
      return "Error in fused depthwiseConv2d: filter must be rank 4, " + ("but got rank " + g.rank + ".");
    }), E(y.shape[3] === g.shape[2], function() {
      return "Error in fused depthwiseConv2d: number of input channels " + ("(" + y.shape[3] + ") must match the inChannels dimension in ") + ("filter " + g.shape[2] + ".");
    }), c == null && (c = [1, 1]), E(Mt(r, c), function() {
      return "Error in fused depthwiseConv2d: Either strides or dilations must " + ("be 1. Got strides " + r + " and dilations '" + c + "'");
    }), l != null && E(ot(i), function() {
      return "Error in fused depthwiseConv2d: pad must be an integer when " + ("using dimRoundingMode " + l + " but got pad " + i + ".");
    });
    var b = gn(y.shape, g.shape, r, c, i, l, true), L;
    u != null && (L = R(u, "bias", "fused conv2d"), L = ct(L, m)[0], it(b.outShape, L.shape));
    var x;
    p != null && (x = R(p, "prelu weights", "fused depthwiseConv2d"));
    var N = function(k, B) {
      E(mr(c), function() {
        return "Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations " + ("'" + c + "'");
      });
      var V = B[0], P = B[1], G = B[2], j = B[3], q = uo(k, G, d), H = E0(P.shape, q, V, r, i, c, l), J = O0(P, q, V.shape, r, i, c, l);
      if (j != null) {
        var $ = ho(L, q);
        return [H, J, $];
      }
      return [H, J];
    }, I = function(k) {
      var B = k.fusedDepthwiseConv2D({input: y, filter: g, convInfo: b, bias: L, activation: d, preluActivationWeights: x});
      return B;
    }, C = {x: y, filter: g, bias: L, preluActivationWeights: x}, O = {strides: r, pad: i, dataFormat: s, dilations: c, dimRoundingMode: l, activation: d};
    if (u == null) {
      var D = kn(function(k, B, V) {
        var P = z.runKernelFunc(I, C, null, cu, O);
        return V([B, k, P]), w && (P = Y(P, [P.shape[1], P.shape[2], P.shape[3]])), {value: P, gradFunc: N};
      });
      return D(y, g);
    } else {
      var F = kn(function(k, B, V, P) {
        var G = z.runKernelFunc(I, C, null, cu, O);
        return P([B, k, G, V]), w && (G = Y(G, [G.shape[1], G.shape[2], G.shape[3]])), {value: G, gradFunc: N};
      });
      return F(y, g, L);
    }
  }
  var z_ = U({fusedDepthwiseConv2d_: B_});
  function P_(n) {
    var t, e = n.a, r = n.b, i = n.transposeA, a = i === void 0 ? false : i, s = n.transposeB, o = s === void 0 ? false : s, c = n.bias, l = n.activation, u = l === void 0 ? "linear" : l, h = n.preluActivationWeights;
    if (fo(z.state.gradientDepth, u) === false) {
      var d = Ue(e, r, a, o);
      return c != null && (d = ge(d, c)), po(d, u, h);
    }
    var p = R(e, "a", "fused matMul"), f = R(r, "b", "fused matMul");
    t = ct(p, f), p = t[0], f = t[1];
    var m = a ? p.shape[p.rank - 2] : p.shape[p.rank - 1], g = o ? f.shape[f.rank - 1] : f.shape[f.rank - 2], y = a ? p.shape[p.rank - 1] : p.shape[p.rank - 2], w = o ? f.shape[f.rank - 2] : f.shape[f.rank - 1], b = p.shape.slice(0, -2), L = f.shape.slice(0, -2), x = pt(b), N = pt(L);
    E(p.rank >= 2 && f.rank >= 2 && p.rank === f.rank, function() {
      return "Error in fused matMul: inputs must have the same rank of at least " + ("2, got ranks " + p.rank + " and " + f.rank + ".");
    }), E(fn(b, L), function() {
      return "Error in fused matMul: outer dimensions (" + b + ") and (" + (L + ") of Tensors with shapes " + p.shape + " and ") + (f.shape + " must match.");
    }), E(m === g, function() {
      return "Error in fused matMul: inner shapes (" + m + ") and (" + (g + ") of Tensors with shapes " + p.shape + " and ") + (f.shape + " and transposeA=" + a) + (" and transposeB=" + o + " must match.");
    });
    var I = p.shape.slice(0, -2).concat([y, w]), C = a ? Y(p, [x, m, y]) : Y(p, [x, y, m]), O = o ? Y(f, [N, w, g]) : Y(f, [N, g, w]), D;
    c != null && (D = R(c, "bias", "fused matMul"), D = ct(D, p)[0], it(I, D.shape));
    var F;
    h != null && (F = R(h, "prelu weights", "fused matMul"));
    var k = function(q, H) {
      var J = H[0], $ = H[1], ee = H[2], te = H[3], ne = uo(Y(q, ee.shape), ee, u), re, ie;
      if (!a && !o ? (re = Ue(ne, $, false, true), ie = Ue(J, ne, true, false)) : !a && o ? (re = Ue(ne, $, false, false), ie = Ue(ne, J, true, false)) : a && !o ? (re = Ue($, ne, false, true), ie = Ue(J, ne, false, false)) : (re = Ue($, ne, true, true), ie = Ue(ne, J, true, true)), c != null) {
        var oe = ho(te, ne);
        return [re, ie, oe];
      } else
        return [re, ie];
    }, B = function(q) {
      var H = q.fusedBatchMatMul({a: C, b: O, transposeA: a, transposeB: o, bias: D, activation: u, preluActivationWeights: F});
      return H;
    }, V = {a: C, b: O, bias: D, preluActivationWeights: F}, P = {transposeA: a, transposeB: o, activation: u};
    if (c == null) {
      var G = kn(function(q, H, J) {
        var $ = z.runKernelFunc(B, V, null, su, P);
        return J([q, H, $]), {value: Y($, I), gradFunc: k};
      });
      return G(C, O);
    } else {
      var j = kn(function(q, H, J, $) {
        var ee = z.runKernelFunc(B, V, null, su, P);
        return $([q, H, ee, J]), {value: Y(ee, I), gradFunc: k};
      });
      return j(C, O, D);
    }
  }
  var M_ = U({fusedMatMul_: P_});
  var H_ = {__proto__: null, conv2d: F_, depthwiseConv2d: z_, matMul: M_};
  function V_(n) {
    return dh(n, 0.54, 0.46);
  }
  var G_ = U({hammingWindow_: V_});
  function q_(n) {
    return dh(n, 0.5, 0.5);
  }
  var D0 = U({hannWindow_: q_});
  function Y_(n, t, e, r, i) {
    r === void 0 && (r = false), i === void 0 && (i = 0);
    for (var a = 0, s = []; a + t <= n.size; )
      s.push(Me(n, a, t)), a += e;
    if (r)
      for (; a < n.size; ) {
        var o = a + t - n.size, c = Et([Me(n, a, t - o), Ku([o], i)]);
        s.push(c), a += e;
      }
    return s.length === 0 ? Fa([], [0, t]) : Y(Et(s), [s.length, t]);
  }
  var k0 = U({frame_: Y_});
  function K_(n, t, e, r, i) {
    i === void 0 && (i = D0), r == null && (r = R0(t));
    for (var a = k0(n, t, e), s = Z(a, i(t)), o = [], c = 0; c < a.shape[0]; c++)
      o.push(ao(Me(s, [c, 0], [1, t]), r));
    return Et(o);
  }
  var j_ = U({stft_: K_});
  function $_(n, t, e, r, i, a) {
    var s = R(n, "image", "cropAndResize"), o = R(t, "boxes", "cropAndResize", "float32"), c = R(e, "boxInd", "cropAndResize", "int32");
    i = i || "bilinear", a = a || 0;
    var l = o.shape[0];
    E(s.rank === 4, function() {
      return "Error in cropAndResize: image must be rank 4," + ("but got rank " + s.rank + ".");
    }), E(o.rank === 2 && o.shape[1] === 4, function() {
      return "Error in cropAndResize: boxes must be have size [" + l + ",4] " + ("but had shape " + o.shape + ".");
    }), E(c.rank === 1 && c.shape[0] === l, function() {
      return "Error in cropAndResize: boxInd must be have size [" + l + "] " + ("but had shape " + o.shape + ".");
    }), E(r.length === 2, function() {
      return "Error in cropAndResize: cropSize must be of length 2, but got " + ("length " + r.length + ".");
    }), E(r[0] >= 1 && r[1] >= 1, function() {
      return "cropSize must be atleast [1,1], but was " + r;
    }), E(i === "bilinear" || i === "nearest", function() {
      return "method must be bilinear or nearest, but was " + i;
    });
    var u = function(f) {
      return f.cropAndResize(s, o, c, r, i, a);
    }, h = {image: s, boxes: o, boxInd: c}, d = {method: i, extrapolationValue: a, cropSize: r}, p = z.runKernelFunc(u, h, null, Ef, d);
    return p;
  }
  var X_ = U({cropAndResize_: $_});
  function J_(n) {
    var t = R(n, "image", "flipLeftRight", "float32");
    E(t.rank === 4, function() {
      return "Error in flipLeftRight: image must be rank 4," + ("but got rank " + t.rank + ".");
    });
    var e = {image: t}, r = z.runKernel(Vf, e, {});
    return r;
  }
  var Z_ = U({flipLeftRight_: J_});
  function Q_(n, t, e, r) {
    e === void 0 && (e = 0), r === void 0 && (r = 0.5);
    var i = R(n, "image", "rotateWithOffset", "float32");
    E(i.rank === 4, function() {
      return "Error in rotateWithOffset: image must be rank 4," + ("but got rank " + i.rank + ".");
    });
    var a = {image: i}, s = {radians: t, fillValue: e, center: r}, o = z.runKernel(bm, a, s);
    return o;
  }
  var eC = U({rotateWithOffset_: Q_});
  function Pi(n, t, e, r, i, a) {
    r == null && (r = 0.5), i == null && (i = Number.NEGATIVE_INFINITY), a == null && (a = 0);
    var s = n.shape[0];
    return e = Math.min(e, s), E(0 <= r && r <= 1, function() {
      return "iouThreshold must be in [0, 1], but was '" + r + "'";
    }), E(n.rank === 2, function() {
      return "boxes must be a 2D tensor, but was of rank '" + n.rank + "'";
    }), E(n.shape[1] === 4, function() {
      return "boxes must have 4 columns, but 2nd dimension was " + n.shape[1];
    }), E(t.rank === 1, function() {
      return "scores must be a 1D tensor";
    }), E(t.shape[0] === s, function() {
      return "scores has incompatible shape with boxes. Expected " + s + ", " + ("but was " + t.shape[0]);
    }), E(0 <= a && a <= 1, function() {
      return "softNmsSigma must be in [0, 1], but was '" + a + "'";
    }), {maxOutputSize: e, iouThreshold: r, scoreThreshold: i, softNmsSigma: a};
  }
  function tC(n, t, e, r, i) {
    r === void 0 && (r = 0.5), i === void 0 && (i = Number.NEGATIVE_INFINITY);
    var a = R(n, "boxes", "nonMaxSuppression"), s = R(t, "scores", "nonMaxSuppression"), o = Pi(a, s, e, r, i);
    e = o.maxOutputSize, r = o.iouThreshold, i = o.scoreThreshold;
    var c = {maxOutputSize: e, iouThreshold: r, scoreThreshold: i};
    return z.runKernelFunc(function(l) {
      return l.nonMaxSuppression(a, s, e, r, i);
    }, {boxes: a, scores: s}, null, sm, c);
  }
  var nC = U({nonMaxSuppression_: tC});
  function iC(n, t, e) {
    var r = rC(n, t, e), i = r < 0 ? -(r + 1) : r;
    n.splice(i, 0, t);
  }
  function rC(n, t, e) {
    return sC(n, t, e || aC);
  }
  function aC(n, t) {
    return n > t ? 1 : n < t ? -1 : 0;
  }
  function sC(n, t, e) {
    for (var r = 0, i = n.length, a = 0, s = false; r < i; ) {
      a = r + (i - r >>> 1);
      var o = e(t, n[a]);
      o > 0 ? r = a + 1 : (i = a, s = !o);
    }
    return s ? r : -r - 1;
  }
  function F0(n, t, e, r, i) {
    return fh(n, t, e, r, i, 0).selectedIndices;
  }
  function W0(n, t, e, r, i, a) {
    return fh(n, t, e, r, i, 0, false, a, true);
  }
  function U0(n, t, e, r, i, a) {
    return fh(n, t, e, r, i, a, true);
  }
  function fh(n, t, e, r, i, a, s, o, c) {
    s === void 0 && (s = false), o === void 0 && (o = false), c === void 0 && (c = false);
    for (var l = [], u = 0; u < t.length; u++)
      t[u] > i && l.push({score: t[u], boxIndex: u, suppressBeginIndex: 0});
    l.sort(B0);
    for (var h = a > 0 ? -0.5 / a : 0, d = [], p = []; d.length < e && l.length > 0; ) {
      var f = l.pop(), m = f.score, g = f.boxIndex, y = f.suppressBeginIndex;
      if (m < i)
        break;
      for (var w = false, b = d.length - 1; b >= y; --b) {
        var L = oC(n, g, d[b]);
        if (L >= r) {
          w = true;
          break;
        }
        if (f.score = f.score * cC(r, h, L), f.score <= i)
          break;
      }
      f.suppressBeginIndex = d.length, w || (f.score === m ? (d.push(g), p.push(f.score)) : f.score > i && iC(l, f, B0));
    }
    var x = d.length, N = e - x;
    o && N > 0 && (d.push.apply(d, new Array(N).fill(0)), p.push.apply(p, new Array(N).fill(0)));
    var I = {selectedIndices: Ui(d, "int32")};
    return s && (I.selectedScores = Ui(p, "float32")), c && (I.validOutputs = Le(x, "int32")), I;
  }
  function oC(n, t, e) {
    var r = n.subarray(t * 4, t * 4 + 4), i = n.subarray(e * 4, e * 4 + 4), a = Math.min(r[0], r[2]), s = Math.min(r[1], r[3]), o = Math.max(r[0], r[2]), c = Math.max(r[1], r[3]), l = Math.min(i[0], i[2]), u = Math.min(i[1], i[3]), h = Math.max(i[0], i[2]), d = Math.max(i[1], i[3]), p = (o - a) * (c - s), f = (h - l) * (d - u);
    if (p <= 0 || f <= 0)
      return 0;
    var m = Math.max(a, l), g = Math.max(s, u), y = Math.min(o, h), w = Math.min(c, d), b = Math.max(y - m, 0) * Math.max(w - g, 0);
    return b / (p + f - b);
  }
  function cC(n, t, e) {
    var r = Math.exp(t * e * e);
    return e <= n ? r : 0;
  }
  function B0(n, t) {
    return n.score - t.score || n.score === t.score && t.boxIndex - n.boxIndex;
  }
  function lC(n, t, e, r, i) {
    return r === void 0 && (r = 0.5), i === void 0 && (i = Number.NEGATIVE_INFINITY), pe(this, void 0, void 0, function() {
      var a, s, o, c, l, u, h;
      return fe(this, function(d) {
        switch (d.label) {
          case 0:
            return a = R(n, "boxes", "nonMaxSuppressionAsync"), s = R(t, "scores", "nonMaxSuppressionAsync"), o = Pi(a, s, e, r, i), e = o.maxOutputSize, r = o.iouThreshold, i = o.scoreThreshold, [4, Promise.all([a.data(), s.data()])];
          case 1:
            return c = d.sent(), l = c[0], u = c[1], h = F0(l, u, e, r, i), a !== n && a.dispose(), s !== t && s.dispose(), [2, h];
        }
      });
    });
  }
  var uC = lC;
  function hC(n, t, e, r, i, a) {
    r === void 0 && (r = 0.5), i === void 0 && (i = Number.NEGATIVE_INFINITY), a === void 0 && (a = 0);
    var s = R(n, "boxes", "nonMaxSuppression"), o = R(t, "scores", "nonMaxSuppression"), c = Pi(s, o, e, r, i, a);
    e = c.maxOutputSize, r = c.iouThreshold, i = c.scoreThreshold, a = c.softNmsSigma;
    var l = {boxes: s, scores: o}, u = {maxOutputSize: e, iouThreshold: r, scoreThreshold: i, softNmsSigma: a}, h = z.runKernel(cm, l, u);
    return {selectedIndices: h[0], selectedScores: h[1]};
  }
  var dC = U({nonMaxSuppressionWithScore_: hC});
  function pC(n, t, e, r, i, a) {
    return r === void 0 && (r = 0.5), i === void 0 && (i = Number.NEGATIVE_INFINITY), a === void 0 && (a = 0), pe(this, void 0, void 0, function() {
      var s, o, c, l, u, h, d;
      return fe(this, function(p) {
        switch (p.label) {
          case 0:
            return s = R(n, "boxes", "nonMaxSuppressionAsync"), o = R(t, "scores", "nonMaxSuppressionAsync"), c = Pi(s, o, e, r, i, a), e = c.maxOutputSize, r = c.iouThreshold, i = c.scoreThreshold, a = c.softNmsSigma, [4, Promise.all([s.data(), o.data()])];
          case 1:
            return l = p.sent(), u = l[0], h = l[1], d = U0(u, h, e, r, i, a), s !== n && s.dispose(), o !== t && o.dispose(), [2, d];
        }
      });
    });
  }
  var fC = pC;
  function mC(n, t, e, r, i, a) {
    r === void 0 && (r = 0.5), i === void 0 && (i = Number.NEGATIVE_INFINITY), a === void 0 && (a = false);
    var s = R(n, "boxes", "nonMaxSuppression"), o = R(t, "scores", "nonMaxSuppression"), c = Pi(s, o, e, r, i, null), l = c.maxOutputSize, u = c.iouThreshold, h = c.scoreThreshold, d = {boxes: s, scores: o}, p = {maxOutputSize: l, iouThreshold: u, scoreThreshold: h, padToMaxOutputSize: a}, f = z.runKernel(om, d, p);
    return {selectedIndices: f[0], validOutputs: f[1]};
  }
  var gC = U({nonMaxSuppressionPadded_: mC});
  function yC(n, t, e, r, i, a) {
    return r === void 0 && (r = 0.5), i === void 0 && (i = Number.NEGATIVE_INFINITY), a === void 0 && (a = false), pe(this, void 0, void 0, function() {
      var s, o, c, l, u, h, d, p, f, m;
      return fe(this, function(g) {
        switch (g.label) {
          case 0:
            return s = R(n, "boxes", "nonMaxSuppressionAsync"), o = R(t, "scores", "nonMaxSuppressionAsync"), c = Pi(s, o, e, r, i, null), l = c.maxOutputSize, u = c.iouThreshold, h = c.scoreThreshold, [4, Promise.all([s.data(), o.data()])];
          case 1:
            return d = g.sent(), p = d[0], f = d[1], m = W0(p, f, l, u, h, a), s !== n && s.dispose(), o !== t && o.dispose(), [2, m];
        }
      });
    });
  }
  var vC = yC;
  function wC(n, t, e) {
    e === void 0 && (e = false);
    var r = R(n, "images", "resizeBilinear");
    E(r.rank === 3 || r.rank === 4, function() {
      return "Error in resizeBilinear: x must be rank 3 or 4, but got " + ("rank " + r.rank + ".");
    }), E(t.length === 2, function() {
      return "Error in resizeBilinear: new shape must 2D, but got shape " + (t + ".");
    });
    var i = r, a = false;
    r.rank === 3 && (a = true, i = Y(r, [1, r.shape[0], r.shape[1], r.shape[2]]));
    var s = t[0], o = t[1], c = function(d, p) {
      return p([i]), d.resizeBilinear(i, s, o, e);
    }, l = {images: i}, u = {alignCorners: e, size: t}, h = z.runKernelFunc(c, l, null, Ol, u);
    return a ? Y(h, [h.shape[1], h.shape[2], h.shape[3]]) : h;
  }
  var z0 = U({resizeBilinear_: wC});
  function bC(n, t, e) {
    e === void 0 && (e = false);
    var r = R(n, "images", "resizeNearestNeighbor");
    E(r.rank === 3 || r.rank === 4, function() {
      return "Error in resizeNearestNeighbor: x must be rank 3 or 4, but got " + ("rank " + r.rank + ".");
    }), E(t.length === 2, function() {
      return "Error in resizeNearestNeighbor: new shape must 2D, but got shape " + (t + ".");
    }), E(r.dtype === "float32" || r.dtype === "int32", function() {
      return "`images` must have `int32` or `float32` as dtype";
    });
    var i = r, a = false;
    r.rank === 3 && (a = true, i = Y(r, [1, r.shape[0], r.shape[1], r.shape[2]]));
    var s = t[0], o = t[1], c = {images: i}, l = {alignCorners: e, size: t}, u = function(d, p) {
      return p([i]), d.resizeNearestNeighbor(i, s, o, e);
    }, h = z.runKernelFunc(u, c, null, Rl, l);
    return a ? Y(h, [h.shape[1], h.shape[2], h.shape[3]]) : h;
  }
  var P0 = U({resizeNearestNeighbor_: bC});
  function xC(n, t, e) {
    E(t % 1 === 0, function() {
      return "bandPart(): numLower must be an integer, got " + t + ".";
    }), E(e % 1 === 0, function() {
      return "bandPart(): numUpper must be an integer, got " + e + ".";
    });
    var r = R(n, "a", "bandPart");
    E(r.rank >= 2, function() {
      return "bandPart(): Rank must be at least 2, got " + r.rank + ".";
    });
    var i = r.shape, a = r.shape.slice(-2), s = a[0], o = a[1];
    if (!(t <= s))
      throw new Error("bandPart(): numLower (" + t + ")" + (" must not be greater than the number of rows (" + s + ")."));
    if (!(e <= o))
      throw new Error("bandPart(): numUpper (" + e + ")" + (" must not be greater than the number of columns (" + o + ")."));
    t < 0 && (t = s), e < 0 && (e = o);
    var c = Y(ah(0, s, 1, "int32"), [-1, 1]), l = ah(0, o, 1, "int32"), u = be(c, l), h = Kr(Gr(u, Le(+t, "int32")), Vr(u, Le(-e, "int32"))), d = jn([s, o], r.dtype);
    return Y(Jr(co(Y(r, [-1, s, o])).map(function(p) {
      return yn(h, p, d);
    })), i);
  }
  var LC = U({bandPart_: xC});
  function SC(n) {
    var t;
    if (Array.isArray(n)) {
      t = false, E(n != null && n.length > 0, function() {
        return "Gram-Schmidt process: input must not be null, undefined, or empty";
      });
      for (var e = n[0].shape[0], r = function(c) {
        E(n[c].shape[0] === e, function() {
          return "Gram-Schmidt: Non-unique lengths found in the input vectors: " + ("(" + n[c].shape[0] + " vs. " + e + ")");
        });
      }, i = 1; i < n.length; ++i)
        r(i);
    } else
      t = true, n = Bi(n, n.shape[0], 0).map(function(c) {
        return oo(c, [0]);
      });
    E(n.length <= n[0].shape[0], function() {
      return "Gram-Schmidt: Number of vectors (" + n.length + ") exceeds " + ("number of dimensions (" + n[0].shape[0] + ").");
    });
    for (var a = [], s = n, o = function(c) {
      a.push(z.tidy(function() {
        var l = s[c];
        if (c > 0)
          for (var u = 0; u < c; ++u) {
            var h = Z(_e(Z(a[u], l)), a[u]);
            l = be(l, h);
          }
        return Ne(l, lo(l, "euclidean"));
      }));
    }, i = 0; i < n.length; ++i)
      o(i);
    return t ? Jr(a, 0) : a;
  }
  var IC = U({gramSchmidt_: SC});
  function AC(n, t) {
    if (t === void 0 && (t = false), E(n.rank >= 2, function() {
      return "qr() requires input tensor to have a rank >= 2, but got rank " + n.rank;
    }), n.rank === 2)
      return M0(n, t);
    var e = n.shape.slice(0, n.shape.length - 2).reduce(function(c, l) {
      return c * l;
    }), r = co(Y(n, [e, n.shape[n.shape.length - 2], n.shape[n.shape.length - 1]]), 0), i = [], a = [];
    r.forEach(function(c) {
      var l = M0(c, t), u = l[0], h = l[1];
      i.push(u), a.push(h);
    });
    var s = Y(Jr(i, 0), n.shape), o = Y(Jr(a, 0), n.shape);
    return [s, o];
  }
  function M0(n, t) {
    return t === void 0 && (t = false), z.tidy(function() {
      E(n.shape.length === 2, function() {
        return "qr2d() requires a 2D Tensor, but got a " + n.shape.length + "D Tensor.";
      });
      for (var e = n.shape[0], r = n.shape[1], i = Pg(e), a = Pr(n), s = Fa([[1]], [1, 1]), o = Pr(s), c = e >= r ? r : e, l = function(h) {
        var d, p = a, f = o, m = i;
        d = z.tidy(function() {
          var g = Me(a, [h, h], [e - h, 1]), y = lo(g), w = Me(a, [h, h], [1, 1]), b = yn(gr(w, 0), Fa([[-1]]), Fa([[1]])), L = be(w, Z(b, y)), x = Ne(g, L);
          x.shape[0] === 1 ? o = Pr(s) : o = Et([s, Me(x, [1, 0], [x.shape[0] - 1, x.shape[1]])], 0);
          var N = Lt(Ne(Ue(b, L), y)), I = Me(a, [h, 0], [e - h, r]), C = Z(N, o), O = Tt(o);
          if (h === 0)
            a = be(I, Ue(C, Ue(O, I)));
          else {
            var D = be(I, Ue(C, Ue(O, I)));
            a = Et([Me(a, [0, 0], [h, r]), D], 0);
          }
          var F = Tt(C), k = Me(i, [0, h], [e, i.shape[1] - h]);
          if (h === 0)
            i = be(k, Ue(Ue(k, o), F));
          else {
            var B = be(k, Ue(Ue(k, o), F));
            i = Et([Me(i, [0, 0], [e, h]), B], 1);
          }
          return [o, a, i];
        }), o = d[0], a = d[1], i = d[2], Pt([p, f, m]);
      }, u = 0; u < c; ++u)
        l(u);
      return !t && e > r && (i = Me(i, [0, 0], [e, r]), a = Me(a, [0, 0], [r, r])), [i, a];
    });
  }
  var TC = U({qr_: AC});
  (function(n) {
    n[n.NONE = 0] = "NONE", n[n.MEAN = 1] = "MEAN", n[n.SUM = 2] = "SUM", n[n.SUM_BY_NONZERO_WEIGHTS = 3] = "SUM_BY_NONZERO_WEIGHTS";
  })(A.Reduction || (A.Reduction = {}));
  function NC(n, t, e) {
    e === void 0 && (e = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var r = R(n, "losses", "computeWeightedLoss"), i = null;
    t != null && (i = R(t, "weights", "computeWeightedLoss"));
    var a = i == null ? r : Z(r, i);
    if (e === A.Reduction.NONE)
      return a;
    if (e === A.Reduction.SUM)
      return _e(a);
    if (e === A.Reduction.MEAN) {
      if (i == null)
        return Oa(a);
      var s = r.size / i.size, o = Ne(_e(a), _e(i));
      return s > 1 ? Ne(o, Le(s)) : o;
    }
    if (e === A.Reduction.SUM_BY_NONZERO_WEIGHTS) {
      if (i == null)
        return Ne(_e(a), Le(r.size));
      var c = Z(i, Fi(r.shape)), l = he(_e(no(c, Le(0))), "float32");
      return Ne(_e(a), l);
    }
    throw Error("Unknown reduction: " + e);
  }
  var Jn = U({computeWeightedLoss_: NC});
  function _C(n, t, e, r) {
    r === void 0 && (r = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var i = R(n, "labels", "absoluteDifference"), a = R(t, "predictions", "absoluteDifference"), s = null;
    e != null && (s = R(e, "weights", "absoluteDifference")), Pe(i.shape, a.shape, "Error in absoluteDifference: ");
    var o = jt(be(i, a));
    return Jn(o, s, r);
  }
  var CC = U({absoluteDifference_: _C});
  function RC(n, t, e, r, i) {
    i === void 0 && (i = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var a = R(n, "labels", "cosineDistance"), s = R(t, "predictions", "cosineDistance"), o = null;
    r != null && (o = R(r, "weights", "cosineDistance")), Pe(a.shape, s.shape, "Error in cosineDistance: ");
    var c = Le(1), l = be(c, _e(Z(a, s), e, true));
    return Jn(l, o, i);
  }
  var OC = U({cosineDistance_: RC});
  function EC(n, t, e, r) {
    r === void 0 && (r = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var i = R(n, "labels", "hingeLoss"), a = R(t, "predictions", "hingeLoss"), s = null;
    e != null && (s = R(e, "weights", "hingeLoss")), Pe(i.shape, a.shape, "Error in hingeLoss: ");
    var o = Le(1);
    i = be(Z(Le(2), i), o);
    var c = Da(be(o, Z(i, a)));
    return Jn(c, s, r);
  }
  var DC = U({hingeLoss_: EC});
  function kC(n, t, e, r, i) {
    r === void 0 && (r = 1), i === void 0 && (i = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var a = R(n, "labels", "huberLoss"), s = R(t, "predictions", "huberLoss"), o = null;
    e != null && (o = R(e, "weights", "huberLoss")), Pe(a.shape, s.shape, "Error in huberLoss: ");
    var c = Le(r), l = jt(be(s, a)), u = to(l, c), h = be(l, u), d = ge(Z(Le(0.5), $e(u)), Z(c, h));
    return Jn(d, o, i);
  }
  var FC = U({huberLoss_: kC});
  function WC(n, t, e, r, i) {
    r === void 0 && (r = 1e-7), i === void 0 && (i = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var a = R(n, "labels", "logLoss"), s = R(t, "predictions", "logLoss"), o = null;
    e != null && (o = R(e, "weights", "logLoss")), Pe(a.shape, s.shape, "Error in logLoss: ");
    var c = Le(1), l = Le(r), u = Lt(Z(a, qr(ge(s, l)))), h = Z(be(c, a), qr(ge(be(c, s), l))), d = be(u, h);
    return Jn(d, o, i);
  }
  var UC = U({logLoss_: WC});
  function BC(n, t, e, r) {
    r === void 0 && (r = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var i = R(n, "labels", "meanSquaredError"), a = R(t, "predictions", "meanSquaredError"), s = null;
    e != null && (s = R(e, "weights", "meanSquaredError")), Pe(i.shape, a.shape, "Error in meanSquaredError: ");
    var o = so(i, a);
    return Jn(o, s, r);
  }
  var zC = U({meanSquaredError_: BC});
  function PC(n, t) {
    var e = R(n, "labels", "sigmoidCrossEntropyWithLogits"), r = R(t, "logits", "sigmoidCrossEntropyWithLogits");
    Pe(e.shape, r.shape, "Error in sigmoidCrossEntropyWithLogits: ");
    var i = Da(r), a = Z(r, e), s = $u(vn(Lt(jt(r))));
    return ge(be(i, a), s);
  }
  function MC(n, t, e, r, i) {
    r === void 0 && (r = 0), i === void 0 && (i = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var a = R(n, "multiClassLabels", "sigmoidCrossEntropy"), s = R(t, "logits", "sigmoidCrossEntropy"), o = null;
    if (e != null && (o = R(e, "weights", "sigmoidCrossEntropy")), Pe(a.shape, s.shape, "Error in sigmoidCrossEntropy: "), r > 0) {
      var c = Le(r), l = Le(1), u = Le(0.5);
      a = ge(Z(a, be(l, c)), Z(u, c));
    }
    var h = PC(a, s);
    return Jn(h, o, i);
  }
  var HC = U({sigmoidCrossEntropy_: MC});
  function VC(n, t, e) {
    if (e === void 0 && (e = -1), e === -1 && (e = t.rank - 1), e !== t.rank - 1)
      throw Error("Softmax cross entropy along a non-last dimension is not yet " + ("supported. Labels / logits was rank " + t.rank + " ") + ("and dim was " + e));
    var r = kn(function(i, a, s) {
      var o = true, c = Ju(a, [e], o), l = be(he(a, "float32"), c);
      s([i, l]);
      var u = Lt(Z(l, i)), h = _e(u, [e]), d = function(p, f) {
        var m = f[0], g = f[1], y = an(p.shape, [e]);
        return [Z(Y(p, y), be(he(m, "float32"), vn(g))), Z(Y(p, y), be(vn(g), he(m, "float32")))];
      };
      return {value: h, gradFunc: d};
    });
    return r(n, t);
  }
  function GC(n, t, e, r, i) {
    r === void 0 && (r = 0), i === void 0 && (i = A.Reduction.SUM_BY_NONZERO_WEIGHTS);
    var a = R(n, "onehotLabels", "softmaxCrossEntropy"), s = R(t, "logits", "softmaxCrossEntropy"), o = null;
    if (e != null && (o = R(e, "weights", "softmaxCrossEntropy")), Pe(a.shape, s.shape, "Error in softmaxCrossEntropy: "), r > 0) {
      var c = Le(r), l = Le(1), u = Le(a.shape[1]);
      a = ge(Z(a, be(l, c)), Ne(c, u));
    }
    var h = VC(a, s);
    return Jn(h, o, i);
  }
  var qC = U({softmaxCrossEntropy_: GC});
  var YC = {fft: io, ifft: ka, rfft: ao, irfft: uh}, KC = {hammingWindow: G_, hannWindow: D0, frame: k0, stft: j_}, jC = {flipLeftRight: Z_, resizeNearestNeighbor: P0, resizeBilinear: z0, rotateWithOffset: eC, cropAndResize: X_, nonMaxSuppression: nC, nonMaxSuppressionAsync: uC, nonMaxSuppressionWithScore: dC, nonMaxSuppressionWithScoreAsync: fC, nonMaxSuppressionPadded: gC, nonMaxSuppressionPaddedAsync: vC}, $C = {bandPart: LC, gramSchmidt: IC, qr: TC}, XC = {absoluteDifference: CC, computeWeightedLoss: Jn, cosineDistance: OC, hingeLoss: DC, huberLoss: FC, logLoss: UC, meanSquaredError: zC, sigmoidCrossEntropy: HC, softmaxCrossEntropy: qC};
  var yr = function(n) {
    qn(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.minimize = function(e, r, i) {
      r === void 0 && (r = false);
      var a = this.computeGradients(e, i), s = a.value, o = a.grads;
      if (i != null) {
        var c = i.map(function(l) {
          return {name: l.name, tensor: o[l.name]};
        });
        this.applyGradients(c);
      } else
        this.applyGradients(o);
      return Pt(o), r ? s : (s.dispose(), null);
    }, Object.defineProperty(t.prototype, "iterations", {get: function() {
      return this.iterations_ == null && (this.iterations_ = 0), this.iterations_;
    }, enumerable: true, configurable: true}), t.prototype.incrementIterations = function() {
      this.iterations_ = this.iterations + 1;
    }, t.prototype.computeGradients = function(e, r) {
      return Kg(e, r);
    }, t.prototype.dispose = function() {
      this.iterations_ != null && Pt(this.iterations_);
    }, t.prototype.saveIterations = function() {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(e) {
          return this.iterations_ == null && (this.iterations_ = 0), [2, {name: "iter", tensor: Le(this.iterations_, "int32")}];
        });
      });
    }, t.prototype.getWeights = function() {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(e) {
          throw new Error("getWeights() is not implemented for this optimizer yet.");
        });
      });
    }, t.prototype.setWeights = function(e) {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(r) {
          throw new Error("setWeights() is not implemented for this optimizer class " + ("" + this.getClassName()));
        });
      });
    }, t.prototype.extractIterations = function(e) {
      return pe(this, void 0, void 0, function() {
        var r;
        return fe(this, function(i) {
          switch (i.label) {
            case 0:
              return r = this, [4, e[0].tensor.data()];
            case 1:
              return r.iterations_ = i.sent()[0], [2, e.slice(1)];
          }
        });
      });
    }, t;
  }(ug);
  Object.defineProperty(yr, Symbol.hasInstance, {value: function(n) {
    return n.minimize != null && n.computeGradients != null && n.applyGradients != null;
  }});
  var mh = function(n) {
    qn(t, n);
    function t(e, r, i) {
      i === void 0 && (i = null);
      var a = n.call(this) || this;
      return a.learningRate = e, a.rho = r, a.epsilon = i, a.accumulatedGrads = [], a.accumulatedUpdates = [], i == null && (a.epsilon = z.backend.epsilon()), a;
    }
    return t.prototype.applyGradients = function(e) {
      var r = this, i = Array.isArray(e) ? e.map(function(a) {
        return a.name;
      }) : Object.keys(e);
      i.forEach(function(a, s) {
        var o = z.registeredVariables[a], c = false;
        r.accumulatedGrads[s] == null && (r.accumulatedGrads[s] = {originalName: a + "/accum_grad", variable: bt(function() {
          return ke(o).variable(c);
        })}), r.accumulatedUpdates[s] == null && (r.accumulatedUpdates[s] = {originalName: a + "/accum_var", variable: bt(function() {
          return ke(o).variable(c);
        })});
        var l = Array.isArray(e) ? e[s].tensor : e[a];
        if (l == null)
          return;
        var u = r.accumulatedGrads[s].variable, h = r.accumulatedUpdates[s].variable;
        bt(function() {
          var d = ge(Z(u, r.rho), Z($e(l), 1 - r.rho)), p = Z(Ne(Ht(ge(h, r.epsilon)), Ht(ge(u, r.epsilon))), l), f = ge(Z(h, r.rho), Z($e(p), 1 - r.rho));
          u.assign(d), h.assign(f);
          var m = ge(Z(p, -r.learningRate), o);
          o.assign(m);
        });
      }), this.incrementIterations();
    }, t.prototype.dispose = function() {
      this.accumulatedUpdates != null && (Pt(this.accumulatedGrads.map(function(e) {
        return e.variable;
      })), Pt(this.accumulatedUpdates.map(function(e) {
        return e.variable;
      })));
    }, t.prototype.getWeights = function() {
      return pe(this, void 0, void 0, function() {
        var e;
        return fe(this, function(r) {
          switch (r.label) {
            case 0:
              return e = this.accumulatedGrads.concat(this.accumulatedUpdates), [4, this.saveIterations()];
            case 1:
              return [2, [r.sent()].concat(e.map(function(i) {
                return {name: i.originalName, tensor: i.variable};
              }))];
          }
        });
      });
    }, t.prototype.setWeights = function(e) {
      return pe(this, void 0, void 0, function() {
        var r, i;
        return fe(this, function(a) {
          switch (a.label) {
            case 0:
              return [4, this.extractIterations(e)];
            case 1:
              return e = a.sent(), r = e.length / 2, i = false, this.accumulatedGrads = e.slice(0, r).map(function(s) {
                return {originalName: s.name, variable: s.tensor.variable(i)};
              }), this.accumulatedUpdates = e.slice(r, r * 2).map(function(s) {
                return {originalName: s.name, variable: s.tensor.variable(i)};
              }), [2];
          }
        });
      });
    }, t.prototype.getConfig = function() {
      return {learningRate: this.learningRate, rho: this.rho, epsilon: this.epsilon};
    }, t.fromConfig = function(e, r) {
      return new e(r.learningRate, r.rho, r.epsilon);
    }, t.className = "Adadelta", t;
  }(yr);
  fr(mh);
  var gh = function(n) {
    qn(t, n);
    function t(e, r) {
      r === void 0 && (r = 0.1);
      var i = n.call(this) || this;
      return i.learningRate = e, i.initialAccumulatorValue = r, i.accumulatedGrads = [], i;
    }
    return t.prototype.applyGradients = function(e) {
      var r = this, i = Array.isArray(e) ? e.map(function(a) {
        return a.name;
      }) : Object.keys(e);
      i.forEach(function(a, s) {
        var o = z.registeredVariables[a];
        if (r.accumulatedGrads[s] == null) {
          var c = false;
          r.accumulatedGrads[s] = {originalName: a + "/accumulator", variable: bt(function() {
            return Ku(o.shape, r.initialAccumulatorValue).variable(c);
          })};
        }
        var l = Array.isArray(e) ? e[s].tensor : e[a];
        if (l == null)
          return;
        var u = r.accumulatedGrads[s].variable;
        bt(function() {
          var h = ge(u, $e(l));
          u.assign(h);
          var d = ge(Z(Ne(l, Ht(ge(h, z.backend.epsilon()))), -r.learningRate), o);
          o.assign(d);
        });
      }), this.incrementIterations();
    }, t.prototype.dispose = function() {
      this.accumulatedGrads != null && Pt(this.accumulatedGrads.map(function(e) {
        return e.variable;
      }));
    }, t.prototype.getWeights = function() {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.saveIterations()];
            case 1:
              return [2, [e.sent()].concat(this.accumulatedGrads.map(function(r) {
                return {name: r.originalName, tensor: r.variable};
              }))];
          }
        });
      });
    }, t.prototype.setWeights = function(e) {
      return pe(this, void 0, void 0, function() {
        var r;
        return fe(this, function(i) {
          switch (i.label) {
            case 0:
              return [4, this.extractIterations(e)];
            case 1:
              return e = i.sent(), r = false, this.accumulatedGrads = e.map(function(a) {
                return {originalName: a.name, variable: a.tensor.variable(r)};
              }), [2];
          }
        });
      });
    }, t.prototype.getConfig = function() {
      return {learningRate: this.learningRate, initialAccumulatorValue: this.initialAccumulatorValue};
    }, t.fromConfig = function(e, r) {
      return new e(r.learningRate, r.initialAccumulatorValue);
    }, t.className = "Adagrad", t;
  }(yr);
  fr(gh);
  var yh = function(n) {
    qn(t, n);
    function t(e, r, i, a) {
      a === void 0 && (a = null);
      var s = n.call(this) || this;
      return s.learningRate = e, s.beta1 = r, s.beta2 = i, s.epsilon = a, s.accumulatedFirstMoment = [], s.accumulatedSecondMoment = [], bt(function() {
        s.accBeta1 = Le(r).variable(), s.accBeta2 = Le(i).variable();
      }), a == null && (s.epsilon = z.backend.epsilon()), s;
    }
    return t.prototype.applyGradients = function(e) {
      var r = this, i = Array.isArray(e) ? e.map(function(a) {
        return a.name;
      }) : Object.keys(e);
      bt(function() {
        var a = be(1, r.accBeta1), s = be(1, r.accBeta2);
        i.forEach(function(o, c) {
          var l = z.registeredVariables[o], u = false;
          r.accumulatedFirstMoment[c] == null && (r.accumulatedFirstMoment[c] = {originalName: o + "/m", variable: bt(function() {
            return ke(l).variable(u);
          })}), r.accumulatedSecondMoment[c] == null && (r.accumulatedSecondMoment[c] = {originalName: o + "/v", variable: bt(function() {
            return ke(l).variable(u);
          })});
          var h = Array.isArray(e) ? e[c].tensor : e[o];
          if (h == null)
            return;
          var d = r.accumulatedFirstMoment[c].variable, p = r.accumulatedSecondMoment[c].variable, f = ge(Z(d, r.beta1), Z(h, 1 - r.beta1)), m = ge(Z(p, r.beta2), Z($e(h), 1 - r.beta2)), g = Ne(f, a), y = Ne(m, s);
          d.assign(f), p.assign(m);
          var w = ge(Z(Ne(g, ge(Ht(y), r.epsilon)), -r.learningRate), l);
          l.assign(w);
        }), r.accBeta1.assign(Z(r.accBeta1, r.beta1)), r.accBeta2.assign(Z(r.accBeta2, r.beta2));
      }), this.incrementIterations();
    }, t.prototype.dispose = function() {
      this.accBeta1.dispose(), this.accBeta2.dispose(), this.accumulatedFirstMoment != null && Pt(this.accumulatedFirstMoment.map(function(e) {
        return e.variable;
      })), this.accumulatedSecondMoment != null && Pt(this.accumulatedSecondMoment.map(function(e) {
        return e.variable;
      }));
    }, t.prototype.getWeights = function() {
      return pe(this, void 0, void 0, function() {
        var e;
        return fe(this, function(r) {
          switch (r.label) {
            case 0:
              return e = this.accumulatedFirstMoment.concat(this.accumulatedSecondMoment), [4, this.saveIterations()];
            case 1:
              return [2, [r.sent()].concat(e.map(function(i) {
                return {name: i.originalName, tensor: i.variable};
              }))];
          }
        });
      });
    }, t.prototype.setWeights = function(e) {
      return pe(this, void 0, void 0, function() {
        var r, i, a = this;
        return fe(this, function(s) {
          switch (s.label) {
            case 0:
              return [4, this.extractIterations(e)];
            case 1:
              return e = s.sent(), bt(function() {
                a.accBeta1.assign($n(a.beta1, a.iterations_ + 1)), a.accBeta2.assign($n(a.beta2, a.iterations_ + 1));
              }), r = e.length / 2, i = false, this.accumulatedFirstMoment = e.slice(0, r).map(function(o) {
                return {originalName: o.name, variable: o.tensor.variable(i)};
              }), this.accumulatedSecondMoment = e.slice(r, r * 2).map(function(o) {
                return {originalName: o.name, variable: o.tensor.variable(i)};
              }), [2];
          }
        });
      });
    }, t.prototype.getConfig = function() {
      return {learningRate: this.learningRate, beta1: this.beta1, beta2: this.beta2, epsilon: this.epsilon};
    }, t.fromConfig = function(e, r) {
      return new e(r.learningRate, r.beta1, r.beta2, r.epsilon);
    }, t.className = "Adam", t;
  }(yr);
  fr(yh);
  var vh = function(n) {
    qn(t, n);
    function t(e, r, i, a, s) {
      a === void 0 && (a = null), s === void 0 && (s = 0);
      var o = n.call(this) || this;
      return o.learningRate = e, o.beta1 = r, o.beta2 = i, o.epsilon = a, o.decay = s, o.accumulatedFirstMoment = [], o.accumulatedWeightedInfNorm = [], bt(function() {
        o.iteration = Le(0).variable(), o.accBeta1 = Le(r).variable();
      }), a == null && (o.epsilon = z.backend.epsilon()), o;
    }
    return t.prototype.applyGradients = function(e) {
      var r = this, i = Array.isArray(e) ? e.map(function(a) {
        return a.name;
      }) : Object.keys(e);
      bt(function() {
        var a = be(1, r.accBeta1), s = Ne(-r.learningRate, ge(Z(r.iteration, r.decay), 1));
        i.forEach(function(o, c) {
          var l = z.registeredVariables[o], u = false;
          r.accumulatedFirstMoment[c] == null && (r.accumulatedFirstMoment[c] = {originalName: o + "/m", variable: ke(l).variable(u)}), r.accumulatedWeightedInfNorm[c] == null && (r.accumulatedWeightedInfNorm[c] = {originalName: o + "/v", variable: ke(l).variable(u)});
          var h = Array.isArray(e) ? e[c].tensor : e[o];
          if (h == null)
            return;
          var d = r.accumulatedFirstMoment[c].variable, p = r.accumulatedWeightedInfNorm[c].variable, f = ge(Z(d, r.beta1), Z(h, 1 - r.beta1)), m = Z(p, r.beta2), g = jt(h), y = ki(m, g);
          d.assign(f), p.assign(y);
          var w = ge(Z(Ne(s, a), Ne(f, ge(y, r.epsilon))), l);
          l.assign(w);
        }), r.iteration.assign(ge(r.iteration, 1)), r.accBeta1.assign(Z(r.accBeta1, r.beta1));
      }), this.incrementIterations();
    }, t.prototype.dispose = function() {
      this.accBeta1.dispose(), this.iteration.dispose(), this.accumulatedFirstMoment != null && Pt(this.accumulatedFirstMoment.map(function(e) {
        return e.variable;
      })), this.accumulatedWeightedInfNorm != null && Pt(this.accumulatedWeightedInfNorm.map(function(e) {
        return e.variable;
      }));
    }, t.prototype.getWeights = function() {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(e) {
          throw new Error("getWeights() is not implemented for Adamax yet.");
        });
      });
    }, t.prototype.setWeights = function(e) {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(r) {
          throw new Error("setWeights() is not implemented for Adamax yet.");
        });
      });
    }, t.prototype.getConfig = function() {
      return {learningRate: this.learningRate, beta1: this.beta1, beta2: this.beta2, epsilon: this.epsilon, decay: this.decay};
    }, t.fromConfig = function(e, r) {
      return new e(r.learningRate, r.beta1, r.beta2, r.epsilon, r.decay);
    }, t.className = "Adamax", t;
  }(yr);
  fr(vh);
  var mo = function(n) {
    qn(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.learningRate = e, r.setLearningRate(e), r;
    }
    return t.prototype.applyGradients = function(e) {
      var r = this, i = Array.isArray(e) ? e.map(function(a) {
        return a.name;
      }) : Object.keys(e);
      i.forEach(function(a, s) {
        var o = Array.isArray(e) ? e[s].tensor : e[a];
        if (o == null)
          return;
        var c = z.registeredVariables[a];
        bt(function() {
          var l = ge(Z(r.c, o), c);
          c.assign(l);
        });
      }), this.incrementIterations();
    }, t.prototype.setLearningRate = function(e) {
      this.learningRate = e, this.c != null && this.c.dispose(), this.c = pg(Le(-e));
    }, t.prototype.dispose = function() {
      this.c.dispose();
    }, t.prototype.getWeights = function() {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.saveIterations()];
            case 1:
              return [2, [e.sent()]];
          }
        });
      });
    }, t.prototype.setWeights = function(e) {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(r) {
          switch (r.label) {
            case 0:
              return [4, this.extractIterations(e)];
            case 1:
              if (e = r.sent(), e.length !== 0)
                throw new Error("SGD optimizer does not have settable weights.");
              return [2];
          }
        });
      });
    }, t.prototype.getConfig = function() {
      return {learningRate: this.learningRate};
    }, t.fromConfig = function(e, r) {
      return new e(r.learningRate);
    }, t.className = "SGD", t;
  }(yr);
  fr(mo);
  var wh = function(n) {
    qn(t, n);
    function t(e, r, i) {
      i === void 0 && (i = false);
      var a = n.call(this, e) || this;
      return a.learningRate = e, a.momentum = r, a.useNesterov = i, a.accumulations = [], a.m = Le(a.momentum), a;
    }
    return t.prototype.applyGradients = function(e) {
      var r = this, i = Array.isArray(e) ? e.map(function(a) {
        return a.name;
      }) : Object.keys(e);
      i.forEach(function(a, s) {
        var o = z.registeredVariables[a];
        if (r.accumulations[s] == null) {
          var c = false;
          r.accumulations[s] = {originalName: a + "/momentum", variable: bt(function() {
            return ke(o).variable(c);
          })};
        }
        var l = r.accumulations[s].variable, u = Array.isArray(e) ? e[s].tensor : e[a];
        if (u == null)
          return;
        bt(function() {
          var h, d = ge(Z(r.m, l), u);
          r.useNesterov ? h = ge(Z(r.c, ge(u, Z(d, r.m))), o) : h = ge(Z(r.c, d), o), l.assign(d), o.assign(h);
        });
      }), this.incrementIterations();
    }, t.prototype.dispose = function() {
      this.m.dispose(), this.accumulations != null && Pt(this.accumulations.map(function(e) {
        return e.variable;
      }));
    }, t.prototype.setMomentum = function(e) {
      this.momentum = e;
    }, t.prototype.getWeights = function() {
      return pe(this, void 0, void 0, function() {
        return fe(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.saveIterations()];
            case 1:
              return [2, [e.sent()].concat(this.accumulations.map(function(r) {
                return {name: r.originalName, tensor: r.variable};
              }))];
          }
        });
      });
    }, t.prototype.setWeights = function(e) {
      return pe(this, void 0, void 0, function() {
        var r;
        return fe(this, function(i) {
          switch (i.label) {
            case 0:
              return [4, this.extractIterations(e)];
            case 1:
              return e = i.sent(), r = false, this.accumulations = e.map(function(a) {
                return {originalName: a.name, variable: a.tensor.variable(r)};
              }), [2];
          }
        });
      });
    }, t.prototype.getConfig = function() {
      return {learningRate: this.learningRate, momentum: this.momentum, useNesterov: this.useNesterov};
    }, t.fromConfig = function(e, r) {
      return new e(r.learningRate, r.momentum, r.useNesterov);
    }, t.className = "Momentum", t;
  }(mo);
  fr(wh);
  var bh = function(n) {
    qn(t, n);
    function t(e, r, i, a, s) {
      r === void 0 && (r = 0.9), i === void 0 && (i = 0), a === void 0 && (a = null), s === void 0 && (s = false);
      var o = n.call(this) || this;
      if (o.learningRate = e, o.decay = r, o.momentum = i, o.epsilon = a, o.accumulatedMeanSquares = [], o.accumulatedMoments = [], o.accumulatedMeanGrads = [], o.centered = s, a == null && (o.epsilon = z.backend.epsilon()), e == null)
        throw new Error("learningRate for RMSPropOptimizer must be defined.");
      return o;
    }
    return t.prototype.applyGradients = function(e) {
      var r = this, i = Array.isArray(e) ? e.map(function(a) {
        return a.name;
      }) : Object.keys(e);
      i.forEach(function(a, s) {
        var o = z.registeredVariables[a], c = false;
        r.accumulatedMeanSquares[s] == null && (r.accumulatedMeanSquares[s] = {originalName: a + "/rms", variable: bt(function() {
          return ke(o).variable(c);
        })}), r.accumulatedMoments[s] == null && (r.accumulatedMoments[s] = {originalName: a + "/momentum", variable: bt(function() {
          return ke(o).variable(c);
        })}), r.accumulatedMeanGrads[s] == null && r.centered && (r.accumulatedMeanGrads[s] = {originalName: a + "/mg", variable: bt(function() {
          return ke(o).variable(c);
        })});
        var l = Array.isArray(e) ? e[s].tensor : e[a];
        if (l == null)
          return;
        var u = r.accumulatedMeanSquares[s].variable, h = r.accumulatedMoments[s].variable;
        bt(function() {
          var d = ge(Z(u, r.decay), Z($e(l), 1 - r.decay));
          if (r.centered) {
            var p = r.accumulatedMeanGrads[s].variable, f = ge(Z(p, r.decay), Z(l, 1 - r.decay)), m = Ne(Z(l, r.learningRate), Ht(be(d, ge($e(f), r.epsilon)))), g = ge(Z(h, r.momentum), m);
            u.assign(d), p.assign(f), h.assign(g);
            var y = be(o, g);
            o.assign(y);
          } else {
            var w = ge(Z(u, r.decay), Z($e(l), 1 - r.decay)), g = ge(Z(h, r.momentum), Ne(Z(l, r.learningRate), Ht(ge(w, r.epsilon))));
            u.assign(w), h.assign(g);
            var y = be(o, g);
            o.assign(y);
          }
        });
      }), this.incrementIterations();
    }, t.prototype.dispose = function() {
      this.accumulatedMeanSquares != null && Pt(this.accumulatedMeanSquares.map(function(e) {
        return e.variable;
      })), this.accumulatedMeanGrads != null && this.centered && Pt(this.accumulatedMeanGrads.map(function(e) {
        return e.variable;
      })), this.accumulatedMoments != null && Pt(this.accumulatedMoments.map(function(e) {
        return e.variable;
      }));
    }, t.prototype.getWeights = function() {
      return pe(this, void 0, void 0, function() {
        var e;
        return fe(this, function(r) {
          switch (r.label) {
            case 0:
              return e = this.accumulatedMeanSquares.concat(this.accumulatedMoments), this.centered && e.push.apply(e, this.accumulatedMeanGrads), [4, this.saveIterations()];
            case 1:
              return [2, [r.sent()].concat(e.map(function(i) {
                return {name: i.originalName, tensor: i.variable};
              }))];
          }
        });
      });
    }, t.prototype.setWeights = function(e) {
      return pe(this, void 0, void 0, function() {
        var r, i;
        return fe(this, function(a) {
          switch (a.label) {
            case 0:
              return [4, this.extractIterations(e)];
            case 1:
              return e = a.sent(), r = this.centered ? e.length / 3 : e.length / 2, i = false, this.accumulatedMeanSquares = e.slice(0, r).map(function(s) {
                return {originalName: s.name, variable: s.tensor.variable(i)};
              }), this.accumulatedMoments = e.slice(r, r * 2).map(function(s) {
                return {originalName: s.name, variable: s.tensor.variable(i)};
              }), this.centered && (this.accumulatedMeanGrads = e.slice(r * 2, r * 3).map(function(s) {
                return {originalName: s.name, variable: s.tensor.variable(i)};
              })), [2];
          }
        });
      });
    }, t.prototype.getConfig = function() {
      return {learningRate: this.learningRate, decay: this.decay, momentum: this.momentum, epsilon: this.epsilon, centered: this.centered};
    }, t.fromConfig = function(e, r) {
      return new e(r.learningRate, r.decay, r.momentum, r.epsilon, r.centered);
    }, t.className = "RMSProp", t;
  }(yr);
  fr(bh);
  var Zr = function() {
    function n() {
    }
    return n.sgd = function(t) {
      return new mo(t);
    }, n.momentum = function(t, e, r) {
      return r === void 0 && (r = false), new wh(t, e, r);
    }, n.rmsprop = function(t, e, r, i, a) {
      return e === void 0 && (e = 0.9), r === void 0 && (r = 0), i === void 0 && (i = null), a === void 0 && (a = false), new bh(t, e, r, i, a);
    }, n.adam = function(t, e, r, i) {
      return t === void 0 && (t = 1e-3), e === void 0 && (e = 0.9), r === void 0 && (r = 0.999), i === void 0 && (i = null), new yh(t, e, r, i);
    }, n.adadelta = function(t, e, r) {
      return t === void 0 && (t = 1e-3), e === void 0 && (e = 0.95), r === void 0 && (r = null), new mh(t, e, r);
    }, n.adamax = function(t, e, r, i, a) {
      return t === void 0 && (t = 2e-3), e === void 0 && (e = 0.9), r === void 0 && (r = 0.999), i === void 0 && (i = null), a === void 0 && (a = 0), new vh(t, e, r, i, a);
    }, n.adagrad = function(t, e) {
      return e === void 0 && (e = 0.1), new gh(t, e);
    }, n;
  }();
  var JC = {sgd: Zr.sgd, momentum: Zr.momentum, adadelta: Zr.adadelta, adagrad: Zr.adagrad, rmsprop: Zr.rmsprop, adamax: Zr.adamax, adam: Zr.adam};
  var ZC = function() {
    return typeof requestAnimationFrame != "undefined" ? requestAnimationFrame : typeof setImmediate != "undefined" ? setImmediate : function(n) {
      return n();
    };
  }();
  function QC() {
    return new Promise(function(n) {
      return ZC(function() {
        return n();
      });
    });
  }
  function eR(n, t, e) {
    var r = e * (typeof n == "number" ? n : n[0]), i = t * (typeof n == "number" ? n : n[1]);
    return [r, i];
  }
  function tR(n, t, e, r) {
    r === void 0 && (r = true);
    var i = [];
    if (r)
      i = i.concat(t.slice(0)), i.push(n[0] / e), i = i.concat(n.slice(1));
    else {
      i = i.concat(n[0]);
      for (var a = t.length, s = 0; s < a; ++s)
        i = i.concat([n[s + 1] / t[s], t[s]]);
      i = i.concat(n.slice(a + 1));
    }
    return i;
  }
  function nR(n, t, e) {
    e === void 0 && (e = true);
    var r = [];
    if (e) {
      r.push(t);
      for (var i = t + 1; i < n; ++i)
        i <= 2 * t ? (r.push(i), r.push(i - (t + 1))) : r.push(i);
    } else {
      for (var a = [], s = [], i = 1; i < n; ++i)
        i >= t * 2 + 1 || i % 2 === 1 ? s.push(i) : a.push(i);
      r.push.apply(r, a), r.push(0), r.push.apply(r, s);
    }
    return r;
  }
  function rR(n, t, e, r) {
    r === void 0 && (r = true);
    var i = [];
    r ? i.push(n[0] / e) : i.push(n[0] * e);
    for (var a = 1; a < n.length; ++a)
      a <= t.length ? r ? i.push(t[a - 1] * n[a]) : i.push(n[a] / t[a - 1]) : i.push(n[a]);
    return i;
  }
  function iR(n, t) {
    for (var e = [0], r = 0; r < t; ++r)
      e.push(n[r][0]);
    return e;
  }
  function aR(n, t, e) {
    for (var r = n.slice(0, 1), i = 0; i < e; ++i)
      r.push(n[i + 1] - t[i][0] - t[i][1]);
    return r;
  }
  var H0 = 1.7580993408473768, V0 = 1.0507009873554805;
  var sR = 0.3275911, oR = 0.254829592, cR = -0.284496736, lR = 1.421413741, uR = -1.453152027, hR = 1.061405429;
  function dR() {
    for (var n = [], t = 0; t < arguments.length; t++)
      n[t] = arguments[t];
    Ge().getBool("IS_TEST") || console.warn.apply(console, n);
  }
  function pR() {
    for (var n = [], t = 0; t < arguments.length; t++)
      n[t] = arguments[t];
    Ge().getBool("IS_TEST") || console.log.apply(console, n);
  }
  function fR(n, t) {
    if (n.length !== t.length)
      throw new Error("Cannot merge real and imag arrays of different lengths. real:" + (n.length + ", imag: " + t.length + "."));
    for (var e = new Float32Array(n.length * 2), r = 0; r < e.length; r += 2)
      e[r] = n[r / 2], e[r + 1] = t[r / 2];
    return e;
  }
  function mR(n) {
    for (var t = new Float32Array(n.length / 2), e = new Float32Array(n.length / 2), r = 0; r < n.length; r += 2)
      t[r / 2] = n[r], e[r / 2] = n[r + 1];
    return {real: t, imag: e};
  }
  function gR(n) {
    for (var t = Math.ceil(n.length / 4), e = new Float32Array(t), r = new Float32Array(t), i = 0; i < n.length; i += 4)
      e[Math.floor(i / 4)] = n[i], r[Math.floor(i / 4)] = n[i + 1];
    return {real: e, imag: r};
  }
  function yR(n) {
    for (var t = Math.floor(n.length / 4), e = new Float32Array(t), r = new Float32Array(t), i = 2; i < n.length; i += 4)
      e[Math.floor(i / 4)] = n[i], r[Math.floor(i / 4)] = n[i + 1];
    return {real: e, imag: r};
  }
  function vR(n, t) {
    var e = n[t * 2], r = n[t * 2 + 1];
    return {real: e, imag: r};
  }
  function wR(n, t, e, r) {
    n[r * 2] = t, n[r * 2 + 1] = e;
  }
  function bR(n, t) {
    for (var e = new Float32Array(n / 2), r = new Float32Array(n / 2), i = 0; i < Math.ceil(n / 2); i++) {
      var a = (t ? 2 : -2) * Math.PI * (i / n);
      e[i] = Math.cos(a), r[i] = Math.sin(a);
    }
    return {real: e, imag: r};
  }
  function xR(n, t, e) {
    var r = (e ? 2 : -2) * Math.PI * (n / t), i = Math.cos(r), a = Math.sin(r);
    return {real: i, imag: a};
  }
  function LR(n, t, e) {
    if (t === "complex64") {
      if (n.dtype === "complex64")
        return n.clone();
      var r = jn(n.shape), i = he(n, "float32"), a = e.complex(i, r);
      return r.dispose(), i.dispose(), a;
    }
    if (!ff(n.dtype, t))
      return z.makeTensorFromDataId(n.dataId, n.shape, t);
    if (n.dtype === "complex64") {
      var s = e.real(n), a = he(s, t);
      return s.dispose(), a;
    }
    if (t === "int32")
      return e.int(n);
    if (t === "bool") {
      var o = Le(0, n.dtype), a = e.notEqual(n, o);
      return o.dispose(), a;
    } else
      throw new Error("Error in Cast: failed to cast " + n.dtype + " to " + t);
  }
  function SR(n, t) {
    return z.makeTensorFromDataId(n.dataId, t, n.dtype);
  }
  function IR(n, t, e) {
    var r = (t - n) / (e - 1), i = Li(e, "float32");
    i[0] = n;
    for (var a = 1; a < i.length; a++)
      i[a] = i[a - 1] + r;
    return Ui(i, "float32");
  }
  var AR = {__proto__: null, slice_util: lg, segment_util: I5, castTensor: LR, reshapeTensor: SR, linspaceImpl: IR, upcastType: Ws, axesAreInnerMostDims: zu, combineLocations: gg, computeOutAndReduceShapes: yg, expandShapeToKeepDim: an, assertAxesAreInnerMostDims: eA, getAxesPermutation: mn, getUndoAxesPermutation: Ms, getInnerMostAxes: Dn, getBroadcastDims: o5, getReductionAxes: xt, assertAndGetBroadcastShape: it, assertParamsConsistent: Ng, computeOutShape: _g, computeDilation2DInfo: uA, computePool2DInfo: Ri, computePool3DInfo: Na, computeConv2DInfo: gn, computeConv3DInfo: Ta, computeDefaultPad: Mu, tupleValuesAreOne: mr, eitherStridesOrDilationsAreOne: Mt, convertConv2DDataFormat: Aa, getFusedDyActivation: uo, getFusedBiasGradient: ho, applyActivation: po, shouldFuse: fo, PARALLELIZE_THRESHOLD: ju, computeOptimalWindowSize: x5, getImageCenter: eR, getReshaped: tR, getPermuted: nR, getReshapedPermuted: rR, getSliceBeginCoords: iR, getSliceSize: aR, prepareAndValidate: Xm, validateUpdateShape: Eu, validateInput: Du, calculateShapes: Jm, SELU_SCALEALPHA: H0, SELU_SCALE: V0, ERF_P: sR, ERF_A1: oR, ERF_A2: cR, ERF_A3: lR, ERF_A4: uR, ERF_A5: hR, warn: dR, log: pR, mergeRealAndImagArrays: fR, splitRealAndImagArrays: mR, complexWithEvenIndex: gR, complexWithOddIndex: yR, getComplexWithIndex: vR, assignToTypedArray: wR, exponents: bR, exponent: xR, prepareSplitSize: o0};
  function TR(n, t, e) {
    var r = new Array(n.rank).fill(0), i = n.shape.slice();
    return t.map(function(a) {
      var s = i.slice();
      s[e] = a;
      var o = Me(n, r, s);
      return r[e] += a, o;
    });
  }
  function NR(n, t) {
    for (var e = new Array(n.rank), r = 0; r < e.length; r++)
      e[r] = n.shape[r] * t[r];
    for (var i = En(e, n.dtype), r = 0; r < i.values.length; ++r) {
      for (var a = i.indexToLoc(r), s = new Array(n.rank), o = 0; o < s.length; o++)
        s[o] = a[o] % n.shape[o];
      var c = n.locToIndex(s);
      i.values[r] = n.values[c];
    }
    return i.toTensor();
  }
  function _R(n, t, e, r, i) {
    for (var a = t[t.length - 1], s = [n.length / a, a], o = s[0], c = s[1], l = Ns(e, o * r), u = Ns("int32", o * r), h = 0; h < o; h++) {
      for (var d = h * c, p = n.subarray(d, d + c), f = [], m = 0; m < p.length; m++)
        f.push({value: p[m], index: m});
      f.sort(function(L, x) {
        return x.value - L.value;
      });
      for (var g = h * r, y = l.subarray(g, g + r), w = u.subarray(g, g + r), m = 0; m < r; m++)
        y[m] = f[m].value, w[m] = f[m].index;
    }
    var b = t.slice();
    return b[b.length - 1] = r, [hr(l, b, e), hr(u, b, "int32")];
  }
  var CR = {__proto__: null, nonMaxSuppressionV3Impl: F0, nonMaxSuppressionV4Impl: W0, nonMaxSuppressionV5Impl: U0, split: TR, tile: NR, topkImpl: _R, whereImpl: d0};
  var RR = {kernelName: xc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(n, zi(he(e, "float32"), -1));
    }};
  }};
  var OR = {kernelName: Lc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      var r = $e(he(e, "float32")), i = Ht(be(Le(1), r));
      return Lt(Ne(n, i));
    }};
  }};
  var ER = {kernelName: Sc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      var r = Ht(be($e(he(e, "float32")), 1));
      return Ne(n, r);
    }};
  }};
  var DR = {kernelName: Rs, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = it(e.shape, r.shape), a = function() {
      var o = n, c = xt(e.shape, i);
      return c.length > 0 && (o = _e(o, c)), Y(o, e.shape);
    }, s = function() {
      var o = n, c = xt(r.shape, i);
      return c.length > 0 && (o = _e(o, c)), Y(o, r.shape);
    };
    return {a, b: s};
  }};
  var kR = {kernelName: Ic, saveAllInputs: true, gradFunc: function(n, t) {
    var e = {};
    return t.forEach(function(r, i) {
      e[i] = function() {
        return n.clone();
      };
    }), e;
  }};
  var FR = {kernelName: Ac, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return ke(e);
    }};
  }};
  var WR = {kernelName: Tc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return ke(e);
    }};
  }};
  var UR = {kernelName: Nc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Ne(n, Ht(be(Le(1), $e(he(e, "float32")))));
    }};
  }};
  var BR = {kernelName: _c, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      var r = Ht(ge(Le(1), $e(he(e, "float32"))));
      return Ne(n, r);
    }};
  }};
  var zR = {kernelName: Oc, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = it(e.shape, r.shape), a = function() {
      var o = ge($e(e), $e(r)), c = Z(n, Ne(r, o)), l = xt(e.shape, i);
      return l.length > 0 && (c = _e(c, l)), Y(c, e.shape);
    }, s = function() {
      var o = ge($e(e), $e(r)), c = Lt(Z(n, Ne(e, o))), l = xt(r.shape, i);
      return l.length > 0 && (c = _e(c, l)), Y(c, r.shape);
    };
    return {a, b: s};
  }};
  var PR = {kernelName: Cc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Ne(n, ge($e(he(e, "float32")), 1));
    }};
  }};
  var MR = {kernelName: Rc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Ne(n, be(Le(1), $e(he(e, "float32"))));
    }};
  }};
  function HR(n, t, e, r, i, a, s) {
    i === void 0 && (i = [1, 1, 1]);
    var o = R(n, "dy", "avgPool3dBackprop"), c = R(t, "input", "avgPool3dBackprop"), l = o, u = c, h = false;
    c.rank === 4 && (h = true, l = Y(o, [1, o.shape[0], o.shape[1], o.shape[2], o.shape[3]]), u = Y(c, [1, c.shape[0], c.shape[1], c.shape[2], c.shape[3]])), E(l.rank === 5, function() {
      return "Error in avgPool3dBackprop: dy must be rank 5 but got rank " + (l.rank + ".");
    }), E(u.rank === 5, function() {
      return "Error in avgPool3dBackprop: input must be rank 5 but got rank " + (u.rank + ".");
    }), E(Mt(r, i), function() {
      return "Error in avgPool3dBackprop: Either strides or dilations " + ("must be 1. Got strides " + r + " and dilations '" + i + "'");
    }), s != null && E(ot(a), function() {
      return "Error in maxPool3dBackprop: pad must be an integer when " + ("using, dimRoundingMode " + s + " but got pad " + a + ".");
    });
    var d = function(g) {
      var y = Na(u.shape, e, r, i, a, s);
      return g.avgPool3dBackprop(l, u, y);
    }, p = {dy: l, input: u}, f = {filterSize: e, strides: r, dilations: i, pad: a, dimRoundingMode: s}, m = z.runKernelFunc(d, p, null, Nf, f);
    return h ? Y(m, [m.shape[1], m.shape[2], m.shape[3], m.shape[4]]) : m;
  }
  var VR = U({avgPool3dBackprop_: HR});
  var GR = {kernelName: Dc, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    var r = t[0], i = e, a = i.filterSize, s = i.strides, o = i.dilations, c = i.pad, l = i.dimRoundingMode, u = o == null ? [1, 1, 1] : o;
    return {x: function() {
      return VR(n, r, a, s, u, c, l);
    }};
  }};
  function qR(n, t, e, r, i) {
    var a = R(n, "dy", "avgPoolBackprop"), s = R(t, "input", "avgPoolBackprop");
    E(s.rank === a.rank, function() {
      return "Rank of input (" + s.rank + ") does not match rank of dy (" + a.rank + ")";
    });
    var o = s, c = a, l = false;
    s.rank === 3 && (l = true, o = Y(s, [1, s.shape[0], s.shape[1], s.shape[2]]), c = Y(a, [1, a.shape[0], a.shape[1], a.shape[2]])), E(c.rank === 4, function() {
      return "Error in avgPoolBackprop: dy must be rank 4 but got rank " + (c.rank + ".");
    }), E(o.rank === 4, function() {
      return "Error in avgPoolBackprop: input must be rank 4 but got rank " + (o.rank + ".");
    });
    var u = function(f) {
      var m = Ri(o.shape, e, r, 1, i);
      return f.avgPoolBackprop(c, o, m);
    }, h = {dy: c, input: o}, d = {filterSize: e, strides: r, pad: i}, p = z.runKernelFunc(u, h, null, Tf, d);
    return l ? Y(p, [p.shape[1], p.shape[2], p.shape[3]]) : p;
  }
  var YR = U({avgPoolBackprop_: qR});
  var KR = {kernelName: Ec, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    var r = t[0], i = e, a = i.filterSize, s = i.strides, o = i.pad;
    return {x: function() {
      return YR(n, r, a, s, o);
    }};
  }};
  var jR = {kernelName: kc, inputsToSave: ["a", "b"], gradFunc: function(n, t, e) {
    var r = t[0], i = t[1], a = e, s = a.transposeA, o = a.transposeB;
    return !s && !o ? {a: function() {
      return Ue(n, i, false, true);
    }, b: function() {
      return Ue(r, n, true, false);
    }} : !s && o ? {a: function() {
      return Ue(n, i, false, false);
    }, b: function() {
      return Ue(n, r, true, false);
    }} : s && !o ? {a: function() {
      return Ue(i, n, false, true);
    }, b: function() {
      return Ue(r, n, false, false);
    }} : {a: function() {
      return Ue(i, n, true, true);
    }, b: function() {
      return Ue(n, r, true, true);
    }};
  }};
  var $R = {kernelName: Fc, gradFunc: function(n, t, e) {
    var r = e, i = r.blockShape, a = r.crops;
    return {x: function() {
      return ro(n, i, a);
    }};
  }};
  var XR = {kernelName: Wc, gradFunc: function(n, t, e) {
    for (var r = e, i = r.inputShape, a = r.shape, s = Array.from(a), o = i.length - 1; o >= 0; o--)
      if (i[o] === a[o])
        s[o] = 1;
      else if (i[o] !== 1)
        throw new Error("broadcastTo(): [" + i + "] cannot be broadcast to [" + a + "].");
    for (var c = [], o = 0; o < s.length; o++)
      s[o] > 1 && c.push(o);
    return {x: function() {
      return _e(n, c, true);
    }};
  }};
  var JR = {kernelName: Os, gradFunc: function(n) {
    return {x: function() {
      return n.clone();
    }};
  }};
  var ZR = {kernelName: Uc, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var QR = {kernelName: Bc, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    var r = t[0], i = e, a = i.clipValueMin, s = i.clipValueMax;
    return {x: function() {
      return yn(Kr(Vr(r, a), Gr(r, s)), n, ke(n));
    }};
  }};
  var e3 = {kernelName: zc, saveAllInputs: true, gradFunc: function(n, t, e) {
    var r = t.map(function(c) {
      return c.shape;
    }), i = e.axis, a = rt(i, t[0].shape)[0], s = r.map(function(c) {
      return c[a];
    }), o = Bi(n, s, a);
    return o.map(function(c) {
      return function() {
        return c;
      };
    });
  }};
  var t3 = {kernelName: Pc, inputsToSave: ["x", "filter"], gradFunc: function(n, t, e) {
    var r = t, i = r[0], a = r[1], s = e, o = s.dilations, c = s.strides, l = s.pad, u = s.dataFormat;
    return E(mr(o), function() {
      return "Error in gradient of conv2D: dilation rates greater than 1 " + ("are not yet supported in gradients. Got dilations '" + o + "'");
    }), {x: function() {
      return Vu(i.shape, n, a, c, l, u);
    }, filter: function() {
      return ph(i, n, a.shape, c, l, u);
    }};
  }};
  var n3 = {kernelName: Mc, inputsToSave: ["dy", "filter"], gradFunc: function(n, t, e) {
    var r = t, i = r[0], a = r[1], s = e, o = s.strides, c = s.pad, l = s.dataFormat, u = s.dimRoundingMode;
    return {dy: function() {
      return Ei(n, a, o, c, l, 1, u);
    }, filter: function() {
      return ph(n, i, a.shape, o, c, l, u);
    }};
  }};
  function r3(n, t, e, r, i) {
    var a = n;
    n.rank === 4 && (a = Y(n, [1, n.shape[0], n.shape[1], n.shape[2], n.shape[3]]));
    var s = t;
    s.rank === 4 && (s = Y(t, [1, t.shape[0], t.shape[1], t.shape[2], t.shape[3]])), E(a.rank === 5, function() {
      return "Error in conv3dDerFilter: input must be rank 5, but got shape " + (a.shape + ".");
    }), E(s.rank === 5, function() {
      return "Error in conv3dDerFilter: dy must be rank 5, but got shape " + (s.shape + ".");
    }), E(e.length === 5, function() {
      return "Error in conv3dDerFilter: filterShape must be length 5, but got " + (e + ".");
    }), E(a.shape[4] === e[3], function() {
      return "Error in conv3dDerFilter: depth of input " + a.shape[4] + ") must " + ("match input depth in filter (" + e[3] + ".");
    }), E(s.shape[4] === e[4], function() {
      return "Error in conv3dDerFilter: depth of dy (" + s.shape[4] + ") must " + ("match output depth for filter (" + e[4] + ").");
    });
    var o = function(u) {
      var h = 1, d = Ta(a.shape, e, r, h, i);
      return u.conv3dDerFilter(a, s, d);
    }, c = {x: a, dy: s}, l = {strides: r, pad: i, filterShape: e};
    return z.runKernelFunc(o, c, null, Rf, l);
  }
  var i3 = U({conv3DBackpropFilter_: r3});
  var a3 = {kernelName: Hc, inputsToSave: ["x", "filter"], gradFunc: function(n, t, e) {
    var r = e, i = r.dilations, a = r.strides, s = r.pad;
    E(mr(i), function() {
      return "Error in gradient of conv3D: dilation rates greater than 1 are " + ("not yet supported in gradients. Got dilations '" + i + "'");
    });
    var o = t[0], c = t[1];
    return {x: function() {
      return Dg(o.shape, n, c, a, s);
    }, filter: function() {
      return i3(o, n, c.shape, a, s);
    }};
  }};
  var s3 = {kernelName: Vc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(Lt(ch(he(e, "float32"))), n);
    }};
  }};
  var o3 = {kernelName: Gc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(lh(he(e, "float32")), n);
    }};
  }};
  var c3 = {kernelName: qc, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    var r = t[0], i = e, a = i.axis, s = i.exclusive, o = i.reverse;
    return {x: function() {
      var c = mn([a], r.rank), l = qu(n, a, s, !o);
      return c != null && (l = Tt(l, c)), l;
    }};
  }};
  var l3 = {kernelName: Yc, inputsToSave: ["x", "filter"], gradFunc: function(n, t, e) {
    var r = e, i = r.dilations, a = r.strides, s = r.pad, o = r.dimRoundingMode, c = i == null ? [1, 1] : i;
    E(mr(c), function() {
      return "Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations " + ("'" + c + "'");
    });
    var l = t, u = l[0], h = l[1];
    return E(u.rank === 4, function() {
      return "Error in gradient of depthwiseConv2dNative: input must be " + ("rank 4, but got rank " + u.rank + ".");
    }), E(h.rank === 4, function() {
      return "Error in gradient of depthwiseConv2dNative: filter must be " + ("rank 4, but got rank " + h.rank + ".");
    }), E(u.shape[3] === h.shape[2], function() {
      return "Error in gradient of depthwiseConv2d: number of input " + ("channels (" + u.shape[3] + ") must match the inChannels dimension ") + ("in filter " + h.shape[2] + ".");
    }), E(Mt(a, c), function() {
      return "Error in gradient of depthwiseConv2d: Either strides or " + ("dilations must be  1. Got strides " + a + " and dilations ") + ("'" + c + "'.");
    }), o != null && E(ot(s), function() {
      return "Error in depthwiseConv2d: pad must be an integer when using, " + ("dimRoundingMode " + o + " but got pad " + s + ".");
    }), {x: function() {
      return E0(u.shape, n, h, a, s, i, o);
    }, filter: function() {
      return O0(u, n, h.shape, a, s, i, o);
    }};
  }};
  var u3 = {kernelName: Kc, inputsToSave: ["x", "filter"], gradFunc: function(n, t, e) {
    var r = t, i = r[0], a = r[1], s = {x: i, filter: a, dy: n}, o = {x: i, filter: a, dy: n};
    return {x: function() {
      return z.runKernel(Uf, s, e);
    }, filter: function() {
      return z.runKernel(Bf, o, e);
    }};
  }};
  var h3 = {kernelName: jc, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = it(e.shape, r.shape), a = function() {
      var o = Ne(n, he(r, "float32")), c = xt(e.shape, i);
      return c.length > 0 ? Y(_e(o, c), e.shape) : o;
    }, s = function() {
      var o = Z(n, he(e, "float32")), c = xt(r.shape, i);
      c.length > 0 && (o = Y(_e(o, c), r.shape));
      var l = $e(r);
      return Lt(Ne(o, he(l, "float32")));
    };
    return {a, b: s};
  }};
  var d3 = {kernelName: $c, outputsToSave: [true], gradFunc: function(n, t) {
    var e = t[0], r = function(a) {
      return a.eluDer(n, e);
    }, i = {dy: n, y: e};
    return {x: function() {
      return z.runKernelFunc(r, i, null, zf);
    }};
  }};
  var p3 = {kernelName: Xc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0], r = Z(vn(Lt($e(e))), 2 / Math.sqrt(Math.PI));
    return {x: function() {
      return Z(n, r);
    }};
  }};
  var f3 = {kernelName: Jc, outputsToSave: [true], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(n, e);
    }};
  }};
  var m3 = {kernelName: Zc, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(n, vn(e));
    }};
  }};
  var g3 = {kernelName: Qc, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var y3 = {kernelName: el, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = it(e.shape, r.shape), a = function() {
      var o = Ne(n, he(r, "float32")), c = xt(e.shape, i);
      return c.length > 0 ? Y(_e(o, c), e.shape) : o;
    }, s = function() {
      var o = Z(n, he(e, "float32")), c = xt(r.shape, i);
      c.length > 0 && (o = Y(_e(o, c), r.shape));
      var l = $e(r);
      return Lt(Ne(o, he(l, "float32")));
    };
    return {a, b: s};
  }};
  var v3 = {kernelName: tl, inputsToSave: ["x", "mean", "variance", "scale"], gradFunc: function(n, t, e) {
    var r = e.varianceEpsilon, i = t[0], a = t[1], s = t[2], o = t[3], c = o == null ? Le(1) : o, l = xt(a.shape, i.shape), u = [];
    if (a.rank === 1) {
      for (var h = 0; h < i.shape.length - 1; ++h)
        u.push(i.shape[h]);
      u.push(1);
    }
    var d = be(i, a), p = Z(n, c), f = oh(ge(s, Le(r))), m = Z(Z(Z(f, f), f), Le(-0.5)), g = function() {
      return a.rank === 1 ? Y(Z(Z(n, Di(Y(f, [1, 1, 1, a.shape[0]]), u)), c), i.shape) : Y(Z(Z(n, f), c), i.shape);
    }, y = function() {
      var x = Z(Z(f, Le(-1)), p);
      return a.rank === 1 && (x = _e(x, l)), Y(x, a.shape);
    }, w = function() {
      var x = Z(Z(m, d), p);
      return a.rank === 1 && (x = _e(x, l)), Y(x, a.shape);
    }, b = function() {
      var x = Z(d, f), N = Z(n, x);
      return a.rank === 1 && (N = _e(N, l)), Y(N, a.shape);
    }, L = function() {
      var x = n;
      return a.rank === 1 && (x = _e(x, l)), Y(x, a.shape);
    };
    return {x: g, mean: y, variance: w, scale: b, offset: L};
  }};
  var w3 = {kernelName: nl, inputsToSave: ["x", "indices"], gradFunc: function(n, t, e) {
    var r = t[0], i = t[1], a = e.axis, s = rt(a, r.shape)[0], o = function() {
      var c = r.shape, l = i.size, u = c.slice(0, s), h = u.length, d = c.slice(a, c.length).slice(1), p = d.length, f = G0(0, h), m = G0(h + 1, h + 1 + p), g = q0([u, [l], d]), y = Y(n, g), w = Y(i, [l]), b = q0([[h], f, m]), L = Tt(y, b), x = hh(L, w, r.shape[s]), N = Ms(b);
      return x = Tt(x, N), x;
    };
    return {x: o, indices: function() {
      return i;
    }};
  }};
  function G0(n, t) {
    for (var e = [], r = n; r < t; ++r)
      e.push(r);
    return e;
  }
  function q0(n) {
    for (var t = [], e = 0; e < n.length; ++e)
      for (var r = 0; r < n[e].length; ++r)
        t.push(n[e][r]);
    return t;
  }
  var b3 = {kernelName: rl, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1];
    return {a: function() {
      return ke(e);
    }, b: function() {
      return ke(r);
    }};
  }};
  var x3 = {kernelName: il, gradFunc: function(n) {
    return {x: function() {
      return he(n, "float32");
    }};
  }};
  var L3 = {kernelName: al, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var S3 = {kernelName: sl, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var I3 = {kernelName: ol, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var A3 = {kernelName: ll, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Ne(n, ge(e, 1));
    }};
  }};
  var T3 = {kernelName: cl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Ne(n, he(e, "float32"));
    }};
  }};
  var N3 = {kernelName: ul, inputsToSave: [], outputsToSave: [true], gradFunc: function(n, t, e) {
    var r = t[0], i = e.axis;
    return {logits: function() {
      var a = true, s = vn(r);
      return be(n, Z(_e(n, i, a), s));
    }};
  }};
  function _3(n, t, e, r, i, a, s) {
    r === void 0 && (r = 5), i === void 0 && (i = 1), a === void 0 && (a = 1), s === void 0 && (s = 0.5);
    var o = function(u) {
      return u.LRNGrad(e, n, t, r, i, a, s);
    }, c = {x: n, y: t, dy: e}, l = {depthRadius: r, bias: i, alpha: a, beta: s};
    return z.runKernelFunc(o, c, null, em, l);
  }
  var C3 = U({localResponseNormalizationBackprop_: _3});
  var R3 = {kernelName: hl, inputsToSave: ["x"], outputsToSave: [true], gradFunc: function(n, t, e) {
    var r = t, i = r[0], a = r[1], s = e, o = s.depthRadius, c = s.bias, l = s.alpha, u = s.beta;
    return {x: function() {
      return C3(i, a, n, o, c, l, u);
    }};
  }};
  function Y0(n, t, e, r) {
    return t.rank < e.rank && (t = Y(t, an(t.shape, r))), n.rank < e.rank && (n = Y(n, an(n.shape, r))), {x: function() {
      var i = Z(n, he(Ra(e, t), n.dtype));
      return i;
    }};
  }
  var K0 = {kernelName: dl, inputsToSave: ["x"], outputsToSave: [true], gradFunc: function(n, t, e) {
    var r = e, i = r.reductionIndices, a = t[0], s = t[1], o = rt(i, a.shape), c = Y0(n, s, a, o);
    return {x: function() {
      return c.x();
    }};
  }};
  var O3 = {kernelName: pl, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = function() {
      return Z(n, he(Vr(e, r), "float32"));
    }, a = function() {
      return Z(n, he(Js(e, r), "float32"));
    };
    return {a: i, b: a};
  }};
  function E3(n, t, e, r, i, a, s, o) {
    a === void 0 && (a = [1, 1, 1]);
    var c = R(n, "dy", "maxPool3dBackprop"), l = R(t, "input", "maxPool3dBackprop"), u = R(e, "output", "maxPool3dBackprop"), h = c, d = l, p = u, f = false;
    l.rank === 4 && (f = true, h = Y(c, [1, c.shape[0], c.shape[1], c.shape[2], c.shape[3]]), d = Y(l, [1, l.shape[0], l.shape[1], l.shape[2], l.shape[3]]), p = Y(u, [1, u.shape[0], u.shape[1], u.shape[2], u.shape[3]])), E(h.rank === 5, function() {
      return "Error in maxPool3dBackprop: dy must be rank 5 but got rank " + (h.rank + ".");
    }), E(d.rank === 5, function() {
      return "Error in maxPool3dBackprop: input must be rank 5 but got rank " + (d.rank + ".");
    }), E(p.rank === 5, function() {
      return "Error in maxPool3dBackprop: output must be rank 5 but got rank " + (p.rank + ".");
    }), E(Mt(i, a), function() {
      return "Error in maxPool3dBackprop: Either strides or dilations " + ("must be 1. Got strides " + i + " and dilations '" + a + "'");
    }), o != null && E(ot(s), function() {
      return "Error in maxPool3dBackprop: pad must be an integer when " + ("using, dimRoundingMode " + o + " but got pad " + s + ".");
    });
    var m = function(b) {
      var L = Na(d.shape, r, i, a, s, o);
      return b.maxPool3dBackprop(h, d, p, L);
    }, g = {dy: h, input: d, output: p}, y = {filterSize: r, strides: i, dilations: a, pad: s, dimRoundingMode: o}, w = z.runKernelFunc(m, g, null, nm, y);
    return f ? Y(w, [w.shape[1], w.shape[2], w.shape[3], w.shape[4]]) : w;
  }
  var D3 = U({maxPool3dBackprop_: E3});
  var k3 = {kernelName: ml, inputsToSave: ["x"], outputsToSave: [true], gradFunc: function(n, t, e) {
    var r = t, i = r[0], a = r[1], s = e, o = s.filterSize, c = s.strides, l = s.dilations, u = s.pad, h = s.dimRoundingMode, d = l == null ? [1, 1, 1] : l;
    return {x: function() {
      return D3(n, i, a, o, c, d, u, h);
    }};
  }};
  function F3(n, t, e, r, i, a, s) {
    var o = R(n, "dy", "maxPoolBackprop"), c = R(t, "input", "maxPoolBackprop"), l = R(e, "output", "maxPoolBackprop");
    E(c.rank === o.rank, function() {
      return "Rank of input (" + c.rank + ") does not match rank of dy " + ("(" + o.rank + ")");
    }), E(o.rank === 4, function() {
      return "Error in maxPoolBackprop: dy must be rank 4 but got rank " + (o.rank + ".");
    }), E(c.rank === 4, function() {
      return "Error in maxPoolBackprop: input must be rank 4 but got rank " + (c.rank + ".");
    }), s != null && E(ot(a), function() {
      return "Error in maxPoolBackprop: pad must be an integer when using, " + ("dimRoundingMode " + s + " but got pad " + a + ".");
    });
    var u = function(p) {
      var f = Ri(c.shape, r, i, 1, a, s);
      return p.maxPoolBackprop(o, c, l, f);
    }, h = {dy: o, input: c, output: l}, d = {filterSize: r, strides: i, pad: a, dimRoundingMode: s};
    return z.runKernelFunc(u, h, null, tm, d);
  }
  var W3 = U({maxPoolBackprop_: F3});
  var U3 = {kernelName: fl, inputsToSave: ["x"], outputsToSave: [true], gradFunc: function(n, t, e) {
    var r = t, i = r[0], a = r[1], s = e, o = s.filterSize, c = s.strides, l = s.pad;
    return {x: function() {
      return W3(n, i, a, o, c, l);
    }};
  }};
  var B3 = {kernelName: gl, inputsToSave: ["x"], outputsToSave: [true], gradFunc: function(n, t, e) {
    var r = e, i = r.axis, a = t[0], s = t[1], o = rt(i, a.shape), c = Y0(n, s, a, o);
    return {x: function() {
      return c.x();
    }};
  }};
  var z3 = {kernelName: yl, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = function() {
      return Z(n, he(Gr(e, r), "float32"));
    }, a = function() {
      return Z(n, he(gr(e, r), "float32"));
    };
    return {a: i, b: a};
  }};
  var P3 = {kernelName: vl, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    var r = t[0], i = e.paddings, a = i.map(function(s) {
      return s[0];
    });
    return {x: function() {
      return Me(n, a, r.shape);
    }};
  }};
  var M3 = {kernelName: wl, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = it(e.shape, r.shape), a = function() {
      var o = xt(e.shape, i);
      return o.length > 0 ? Y(_e(n, o), e.shape) : n;
    }, s = function() {
      var o = Z(n, Lt(js(Ne(e, r)))), c = xt(r.shape, i);
      return c.length > 0 ? Y(_e(o, c), r.shape) : o;
    };
    return {a, b: s};
  }};
  var H3 = {kernelName: bl, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = it(e.shape, r.shape), a = function() {
      var o = Z(n, he(r, "float32")), c = xt(e.shape, i);
      return c.length > 0 ? Y(_e(o, c), e.shape) : o;
    }, s = function() {
      var o = Z(n, he(e, "float32")), c = xt(r.shape, i);
      return c.length > 0 ? Y(_e(o, c), r.shape) : o;
    };
    return {a, b: s};
  }};
  var V3 = {kernelName: xl, gradFunc: function(n) {
    return {x: function() {
      return Lt(n);
    }};
  }};
  var G3 = {kernelName: Sl, inputsToSave: ["indices"], gradFunc: function(n, t) {
    var e = t[0];
    return {indices: function() {
      return jn(e.shape, "float32");
    }};
  }};
  var q3 = {kernelName: Ll, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var j0 = {kernelName: Il, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    var r = t[0], i = e.paddings, a = i.map(function(s) {
      return s[0];
    });
    return {x: function() {
      return Me(n, a, r.shape);
    }};
  }};
  var Y3 = {kernelName: Al, inputsToSave: ["a", "b"], outputsToSave: [true], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = t[2], a = e, s = r, o = it(a.shape, s.shape), c = function() {
      var u = he(s, "float32"), h = Z(n, Z(u, $n(a, be(u, Le(1))))), d = xt(a.shape, o);
      return d.length > 0 && (h = _e(h, d)), Y(h, a.shape);
    }, l = function() {
      var u = gr(a, 0), h = yn(u, qr(a), ke(a)), d = Z(n, Z(i, h)), p = xt(s.shape, o);
      return p.length > 0 && (d = _e(d, p)), Y(d, s.shape);
    };
    return {a: c, b: l};
  }};
  var K3 = {kernelName: Tl, inputsToSave: ["x", "alpha"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = gr(e, 0);
    return {x: function() {
      return yn(i, n, Z(n, r));
    }, alpha: function() {
      var a = yn(i, ke(n), Z(n, e)), s = xt(r.shape, n.shape);
      return s.length > 0 && (a = _e(a, s)), Y(a, r.shape);
    }};
  }};
  var j3 = {kernelName: Nl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Ne(n, Lt($e(e)));
    }};
  }};
  var $3 = {kernelName: El, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0], r = Z(Gr(e, 6), zi(e));
    return {x: function() {
      return Z(n, he(r, "float32"));
    }};
  }};
  var X3 = {kernelName: _l, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(n, he(zi(e), "float32"));
    }};
  }};
  var J3 = {kernelName: Cl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Y(n, e.shape);
    }};
  }};
  var Z3 = {kernelName: Ol, inputsToSave: ["images"], gradFunc: function(n, t, e) {
    var r = t[0], i = function(o) {
      var c = e.alignCorners;
      return o.resizeBilinearBackprop(n, r, c);
    }, a = {images: r}, s = function() {
      return z.runKernelFunc(i, a, null, pm, e);
    };
    return {images: s};
  }};
  var Q3 = {kernelName: Rl, inputsToSave: ["images"], gradFunc: function(n, t, e) {
    var r = t[0], i = function(o) {
      var c = e.alignCorners;
      return o.resizeNearestNeighborBackprop(n, r, c);
    }, a = {images: r}, s = function() {
      return z.runKernelFunc(i, a, null, dm, e);
    };
    return {images: s};
  }};
  var eO = {kernelName: Dl, gradFunc: function(n, t, e) {
    var r = e.dims, i = rt(r, n.shape);
    return {x: function() {
      return Xn(n, i);
    }};
  }};
  var tO = {kernelName: kl, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var nO = {kernelName: Fl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Lt(Ne(n, Z($n(e, 1.5), 2)));
    }};
  }};
  var rO = {kernelName: Wl, inputsToSave: ["condition"], gradFunc: function(n, t) {
    var e = t[0];
    return {condition: function() {
      return he(ke(e), "float32");
    }, t: function() {
      return Z(n, he(e, n.dtype));
    }, e: function() {
      return Z(n, he(Qs(e), n.dtype));
    }};
  }};
  var iO = {kernelName: Ul, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      var r = gr(e, Le(0)), i = Le(H0), a = Le(V0), s = Z(n, a), o = Z(Z(n, i), vn(he(e, "float32")));
      return yn(r, s, o);
    }};
  }};
  var aO = {kernelName: Hl, outputsToSave: [true], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(n, Z(e, be(Le(1), e)));
    }};
  }};
  var sO = {kernelName: Ml, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var oO = {kernelName: zl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(Ks(he(e, "float32")), n);
    }};
  }};
  var cO = {kernelName: Pl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(Gu(he(e, "float32")), n);
    }};
  }};
  var lO = {kernelName: Bl, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    for (var r = t[0], i = e, a = i.begin, s = i.size, o = r.shape, c = ku(r, a, s), l = c[0], u = c[1], h = [], d = 0; d < n.rank; d++)
      h.push([l[d], o[d] - l[d] - u[d]]);
    return {x: function() {
      return jr(n, h);
    }};
  }};
  var uO = {kernelName: jl, outputsToSave: [true], gradFunc: function(n, t, e) {
    var r = t[0], i = e.dim, a = true, s = Z(n, r);
    return {logits: function() {
      return be(s, Z(_e(s, [i], a), r));
    }};
  }};
  var hO = {kernelName: Vl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(n, Hr(e));
    }};
  }};
  var $0 = {kernelName: Yl, gradFunc: function(n, t, e) {
    var r = e, i = r.blockShape, a = r.paddings;
    return {x: function() {
      return Gs(n, i, a);
    }};
  }};
  var X0 = {kernelName: Kl, gradFunc: function(n, t, e) {
    var r = e.axis;
    return {x: function() {
      return Et(n, r);
    }};
  }};
  var dO = {kernelName: Gl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Ne(n, Z(Ht(he(e, "float32")), 2));
    }};
  }};
  var pO = {kernelName: mm, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(n, Z(he(e, "float32"), 2));
    }};
  }};
  var fO = {kernelName: $l, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = Le(2), a = function() {
      return Z(n, Z(i, be(e, r)));
    }, s = function() {
      return Z(n, Z(i, be(r, e)));
    };
    return {a, b: s};
  }};
  var mO = {kernelName: iu, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var gO = {kernelName: Xl, inputsToSave: ["a", "b"], gradFunc: function(n, t) {
    var e = t[0], r = t[1], i = it(e.shape, r.shape), a = function() {
      var o = n, c = xt(e.shape, i);
      return c.length > 0 && (o = _e(o, c)), Y(o, e.shape);
    }, s = function() {
      var o = n, c = xt(r.shape, i);
      return c.length > 0 && (o = _e(o, c)), Y(Lt(o), r.shape);
    };
    return {a, b: s};
  }};
  var yO = {kernelName: ql, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    var r = t[0], i = r.shape.slice(), a = e.axis, s = rt(a, r.shape);
    s.forEach(function(l) {
      i[l] = 1;
    });
    var o = Y(n, i), c = Z(o, Fi(r.shape, "float32"));
    return {x: function() {
      return c;
    }};
  }};
  var vO = {kernelName: Jl, inputsToSave: ["x"], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Ne(n, $e(Ks(e)));
    }};
  }};
  var wO = {kernelName: Zl, outputsToSave: [true], gradFunc: function(n, t) {
    var e = t[0];
    return {x: function() {
      return Z(be(Le(1), $e(e)), n);
    }};
  }};
  var bO = {kernelName: Ql, inputsToSave: ["x"], gradFunc: function(n, t, e) {
    var r = t[0], i = e.reps, a = function() {
      var s = ke(r);
      if (r.rank === 1)
        for (var o = 0; o < i[0]; ++o)
          s = ge(s, Me(n, [o * r.shape[0]], [r.shape[0]]));
      else if (r.rank === 2)
        for (var o = 0; o < i[0]; ++o)
          for (var c = 0; c < i[1]; ++c)
            s = ge(s, Me(n, [o * r.shape[0], c * r.shape[1]], [r.shape[0], r.shape[1]]));
      else if (r.rank === 3)
        for (var o = 0; o < i[0]; ++o)
          for (var c = 0; c < i[1]; ++c)
            for (var l = 0; l < i[2]; ++l)
              s = ge(s, Me(n, [o * r.shape[0], c * r.shape[1], l * r.shape[2]], [r.shape[0], r.shape[1], r.shape[2]]));
      else if (r.rank === 4)
        for (var o = 0; o < i[0]; ++o)
          for (var c = 0; c < i[1]; ++c)
            for (var l = 0; l < i[2]; ++l)
              for (var u = 0; u < i[3]; ++u)
                s = ge(s, Me(n, [o * r.shape[0], c * r.shape[1], l * r.shape[2], u * r.shape[3]], [r.shape[0], r.shape[1], r.shape[2], r.shape[3]]));
      else
        throw new Error("Gradient for tile operation is not implemented for rank-" + (r.rank + " tensors yet."));
      return s;
    };
    return {x: a};
  }};
  var xO = {kernelName: eu, gradFunc: function(n, t, e) {
    var r = e, i = r.perm, a = Ms(i);
    return {x: function() {
      return Tt(n, a);
    }};
  }};
  var LO = {kernelName: tu, gradFunc: function(n, t, e) {
    var r = e, i = r.axis;
    return {value: function() {
      return Jr(n, i);
    }};
  }};
  var IO = {kernelName: nu, inputsToSave: ["segmentIds"], gradFunc: function(n, t) {
    var e = t[0], r = function() {
      return SO(n, e);
    };
    return {x: r};
  }};
  function SO(n, t) {
    for (var e = ki(t, ke(t)), r = $s(n, e), i = Vr(t, Le(0, "int32")), a = r.rank - i.rank, s = 0; s < a; ++s)
      i = wn(i, s + 1);
    i = Kr(i, Fi(r.shape, "bool"));
    var o = ke(r);
    return yn(i, r, o);
  }
  var AO = {kernelName: ru, gradFunc: function(n) {
    return {x: function() {
      return ke(n);
    }};
  }};
  var TO = [RR, OR, ER, DR, kR, FR, WR, UR, BR, zR, PR, MR, GR, KR, jR, $R, XR, JR, ZR, QR, e3, n3, t3, a3, s3, o3, c3, l3, u3, h3, d3, p3, f3, m3, y3, g3, v3, w3, b3, x3, L3, S3, I3, A3, T3, N3, R3, K0, K0, O3, k3, U3, B3, z3, P3, M3, H3, V3, G3, q3, j0, j0, Y3, K3, j3, $3, X3, J3, Z3, Q3, eO, tO, nO, rO, iO, aO, sO, oO, cO, lO, uO, hO, $0, $0, X0, X0, dO, fO, pO, mO, gO, yO, vO, wO, bO, xO, LO, IO, AO];
  for (var xh = 0, J0 = TO; xh < J0.length; xh++) {
    var NO = J0[xh];
    Lm(NO);
  }
  K.prototype.abs = function() {
    return this.throwIfDisposed(), jt(this);
  };
  K.prototype.acos = function() {
    return this.throwIfDisposed(), fg(this);
  };
  K.prototype.acosh = function() {
    return this.throwIfDisposed(), mg(this);
  };
  K.prototype.addStrict = function(n) {
    return this.throwIfDisposed(), b0(this, n);
  };
  K.prototype.add = function(n) {
    return this.throwIfDisposed(), ge(this, n);
  };
  K.prototype.all = function(n, t) {
    return this.throwIfDisposed(), vg(this, n, t);
  };
  K.prototype.any = function(n, t) {
    return this.throwIfDisposed(), wg(this, n, t);
  };
  K.prototype.argMax = function(n) {
    return this.throwIfDisposed(), bg(this, n);
  };
  K.prototype.argMin = function(n) {
    return this.throwIfDisposed(), xg(this, n);
  };
  K.prototype.asScalar = function() {
    return this.throwIfDisposed(), E(this.size === 1, function() {
      return "The array must have only 1 element.";
    }), Y(this, []);
  };
  K.prototype.asType = function(n) {
    return this.throwIfDisposed(), he(this, n);
  };
  K.prototype.as1D = function() {
    return this.throwIfDisposed(), Y(this, [this.size]);
  };
  K.prototype.as2D = function(n, t) {
    return this.throwIfDisposed(), Y(this, [n, t]);
  };
  K.prototype.as3D = function(n, t, e) {
    return this.throwIfDisposed(), Y(this, [n, t, e]);
  };
  K.prototype.as4D = function(n, t, e, r) {
    return this.throwIfDisposed(), Y(this, [n, t, e, r]);
  };
  K.prototype.as5D = function(n, t, e, r, i) {
    return this.throwIfDisposed(), Y(this, [n, t, e, r, i]);
  };
  K.prototype.asin = function() {
    return this.throwIfDisposed(), Lg(this);
  };
  K.prototype.asinh = function() {
    return this.throwIfDisposed(), Sg(this);
  };
  K.prototype.atan = function() {
    return this.throwIfDisposed(), Ig(this);
  };
  K.prototype.atan2 = function(n) {
    return this.throwIfDisposed(), Ag(this, n);
  };
  K.prototype.atanh = function() {
    return this.throwIfDisposed(), Tg(this);
  };
  K.prototype.avgPool = function(n, t, e, r) {
    return this.throwIfDisposed(), Hu(this, n, t, e, r);
  };
  K.prototype.batchToSpaceND = function(n, t) {
    return this.throwIfDisposed(), Gs(this, n, t);
  };
  K.prototype.batchNorm = function(n, t, e, r, i) {
    return this.throwIfDisposed(), _a(this, n, t, e, r, i);
  };
  K.prototype.broadcastTo = function(n) {
    return this.throwIfDisposed(), Ys(this, n);
  };
  K.prototype.cast = function(n) {
    return this.throwIfDisposed(), he(this, n);
  };
  K.prototype.ceil = function() {
    return this.throwIfDisposed(), Cg(this);
  };
  K.prototype.clipByValue = function(n, t) {
    return this.throwIfDisposed(), Rg(this, n, t);
  };
  K.prototype.concat = function(n, t) {
    return this.throwIfDisposed(), n instanceof K && (n = [n]), Et([this].concat(n), t);
  };
  K.prototype.conv1d = function(n, t, e, r, i, a) {
    return this.throwIfDisposed(), Og(this, n, t, e, r, i, a);
  };
  K.prototype.conv2dTranspose = function(n, t, e, r, i) {
    return this.throwIfDisposed(), Eg(this, n, t, e, r, i);
  };
  K.prototype.conv2d = function(n, t, e, r, i, a) {
    return this.throwIfDisposed(), Ei(this, n, t, e, r, i, a);
  };
  K.prototype.cos = function() {
    return this.throwIfDisposed(), Ks(this);
  };
  K.prototype.cosh = function() {
    return this.throwIfDisposed(), Gu(this);
  };
  K.prototype.cumsum = function(n, t, e) {
    return this.throwIfDisposed(), qu(this, n, t, e);
  };
  K.prototype.depthToSpace = function(n, t) {
    return this.throwIfDisposed(), kg(this, n, t);
  };
  K.prototype.depthwiseConv2D = function(n, t, e, r, i, a) {
    return Nt("depthwiseConv2D is deprecated, use depthwiseConv2d instead"), this.throwIfDisposed(), Ca(this, n, t, e, r, i, a);
  };
  K.prototype.depthwiseConv2d = function(n, t, e, r, i, a) {
    return this.throwIfDisposed(), Ca(this, n, t, e, r, i, a);
  };
  K.prototype.dilation2d = function(n, t, e, r, i) {
    return this.throwIfDisposed(), Fg(this, n, t, e, r, i);
  };
  K.prototype.divNoNan = function(n) {
    return this.throwIfDisposed(), Wg(this, n);
  };
  K.prototype.divStrict = function(n) {
    return this.throwIfDisposed(), x0(this, n);
  };
  K.prototype.div = function(n) {
    return this.throwIfDisposed(), Ne(this, n);
  };
  K.prototype.dot = function(n) {
    return this.throwIfDisposed(), Ug(this, n);
  };
  K.prototype.elu = function() {
    return this.throwIfDisposed(), Yu(this);
  };
  K.prototype.equalStrict = function(n) {
    return this.throwIfDisposed(), f0(this, n);
  };
  K.prototype.equal = function(n) {
    return this.throwIfDisposed(), Ra(this, n);
  };
  K.prototype.erf = function() {
    return this.throwIfDisposed(), Bg(this);
  };
  K.prototype.exp = function() {
    return this.throwIfDisposed(), vn(this);
  };
  K.prototype.expandDims = function(n) {
    return this.throwIfDisposed(), wn(this, n);
  };
  K.prototype.expm1 = function() {
    return this.throwIfDisposed(), zg(this);
  };
  K.prototype.fft = function() {
    return this.throwIfDisposed(), io(this);
  };
  K.prototype.flatten = function() {
    return this.throwIfDisposed(), Y(this, [this.size]);
  };
  K.prototype.floor = function() {
    return this.throwIfDisposed(), js(this);
  };
  K.prototype.floorDiv = function(n) {
    return this.throwIfDisposed(), Bu(this, n);
  };
  K.prototype.gather = function(n, t) {
    return this.throwIfDisposed(), $s(this, n, t);
  };
  K.prototype.greaterEqualStrict = function(n) {
    return this.throwIfDisposed(), m0(this, n);
  };
  K.prototype.greaterEqual = function(n) {
    return this.throwIfDisposed(), Vr(this, n);
  };
  K.prototype.greaterStrict = function(n) {
    return this.throwIfDisposed(), g0(this, n);
  };
  K.prototype.greater = function(n) {
    return this.throwIfDisposed(), gr(this, n);
  };
  K.prototype.ifft = function() {
    return this.throwIfDisposed(), ka(this);
  };
  K.prototype.irfft = function() {
    return this.throwIfDisposed(), uh(this);
  };
  K.prototype.isFinite = function() {
    return this.throwIfDisposed(), Hg(this);
  };
  K.prototype.isInf = function() {
    return this.throwIfDisposed(), Vg(this);
  };
  K.prototype.isNaN = function() {
    return this.throwIfDisposed(), Gg(this);
  };
  K.prototype.leakyRelu = function(n) {
    return this.throwIfDisposed(), qg(this, n);
  };
  K.prototype.lessEqualStrict = function(n) {
    return this.throwIfDisposed(), y0(this, n);
  };
  K.prototype.lessEqual = function(n) {
    return this.throwIfDisposed(), Gr(this, n);
  };
  K.prototype.lessStrict = function(n) {
    return this.throwIfDisposed(), v0(this, n);
  };
  K.prototype.less = function(n) {
    return this.throwIfDisposed(), Js(this, n);
  };
  K.prototype.localResponseNormalization = function(n, t, e, r) {
    return this.throwIfDisposed(), Yg(this, n, t, e, r);
  };
  K.prototype.logSigmoid = function() {
    return this.throwIfDisposed(), jg(this);
  };
  K.prototype.logSoftmax = function(n) {
    return this.throwIfDisposed(), $g(this, n);
  };
  K.prototype.logSumExp = function(n, t) {
    return this.throwIfDisposed(), Ju(this, n, t);
  };
  K.prototype.log = function() {
    return this.throwIfDisposed(), qr(this);
  };
  K.prototype.log1p = function() {
    return this.throwIfDisposed(), $u(this);
  };
  K.prototype.logicalAnd = function(n) {
    return this.throwIfDisposed(), Kr(this, n);
  };
  K.prototype.logicalNot = function() {
    return this.throwIfDisposed(), Qs(this);
  };
  K.prototype.logicalOr = function(n) {
    return this.throwIfDisposed(), Zu(this, n);
  };
  K.prototype.logicalXor = function(n) {
    return this.throwIfDisposed(), Xg(this, n);
  };
  K.prototype.matMul = function(n, t, e) {
    return this.throwIfDisposed(), Ue(this, n, t, e);
  };
  K.prototype.maxPool = function(n, t, e, r) {
    return this.throwIfDisposed(), Qu(this, n, t, e, r);
  };
  K.prototype.max = function(n, t) {
    return this.throwIfDisposed(), Yr(this, n, t);
  };
  K.prototype.maximumStrict = function(n) {
    return this.throwIfDisposed(), L0(this, n);
  };
  K.prototype.maximum = function(n) {
    return this.throwIfDisposed(), ki(this, n);
  };
  K.prototype.mean = function(n, t) {
    return this.throwIfDisposed(), Oa(this, n, t);
  };
  K.prototype.min = function(n, t) {
    return this.throwIfDisposed(), eo(this, n, t);
  };
  K.prototype.minimumStrict = function(n) {
    return this.throwIfDisposed(), S0(this, n);
  };
  K.prototype.minimum = function(n) {
    return this.throwIfDisposed(), to(this, n);
  };
  K.prototype.mirrorPad = function(n, t) {
    return this.throwIfDisposed(), Jg(this, n, t);
  };
  K.prototype.modStrict = function(n) {
    return this.throwIfDisposed(), I0(this, n);
  };
  K.prototype.mod = function(n) {
    return this.throwIfDisposed(), eh(this, n);
  };
  K.prototype.mulStrict = function(n) {
    return this.throwIfDisposed(), A0(this, n);
  };
  K.prototype.mul = function(n) {
    return this.throwIfDisposed(), Z(this, n);
  };
  K.prototype.neg = function() {
    return this.throwIfDisposed(), Lt(this);
  };
  K.prototype.norm = function(n, t, e) {
    return this.throwIfDisposed(), lo(this, n, t, e);
  };
  K.prototype.notEqualStrict = function(n) {
    return this.throwIfDisposed(), w0(this, n);
  };
  K.prototype.notEqual = function(n) {
    return this.throwIfDisposed(), no(this, n);
  };
  K.prototype.oneHot = function(n, t, e) {
    return t === void 0 && (t = 1), e === void 0 && (e = 0), this.throwIfDisposed(), zs(this, n, t, e);
  };
  K.prototype.onesLike = function() {
    return this.throwIfDisposed(), th(this);
  };
  K.prototype.pad = function(n, t) {
    return this.throwIfDisposed(), jr(this, n, t);
  };
  K.prototype.pool = function(n, t, e, r, i) {
    return this.throwIfDisposed(), Zg(this, n, t, e, r, i);
  };
  K.prototype.powStrict = function(n) {
    return this.throwIfDisposed(), T0(this, n);
  };
  K.prototype.pow = function(n) {
    return this.throwIfDisposed(), $n(this, n);
  };
  K.prototype.prelu = function(n) {
    return this.throwIfDisposed(), nh(this, n);
  };
  K.prototype.prod = function(n, t) {
    return this.throwIfDisposed(), Qg(this, n, t);
  };
  K.prototype.reciprocal = function() {
    return this.throwIfDisposed(), t0(this);
  };
  K.prototype.relu = function() {
    return this.throwIfDisposed(), Da(this);
  };
  K.prototype.relu6 = function() {
    return this.throwIfDisposed(), sh(this);
  };
  K.prototype.reshapeAs = function(n) {
    return this.throwIfDisposed(), Y(this, n.shape);
  };
  K.prototype.reshape = function(n) {
    return this.throwIfDisposed(), Y(this, n);
  };
  K.prototype.resizeBilinear = function(n, t) {
    return this.throwIfDisposed(), z0(this, n, t);
  };
  K.prototype.resizeNearestNeighbor = function(n, t) {
    return this.throwIfDisposed(), P0(this, n, t);
  };
  K.prototype.reverse = function(n) {
    return this.throwIfDisposed(), Xn(this, n);
  };
  K.prototype.rfft = function() {
    return this.throwIfDisposed(), ao(this);
  };
  K.prototype.round = function() {
    return this.throwIfDisposed(), n0(this);
  };
  K.prototype.rsqrt = function() {
    return this.throwIfDisposed(), oh(this);
  };
  K.prototype.selu = function() {
    return this.throwIfDisposed(), r0(this);
  };
  K.prototype.separableConv2d = function(n, t, e, r, i, a) {
    return this.throwIfDisposed(), i0(this, n, t, e, r, i, a);
  };
  K.prototype.sigmoid = function() {
    return this.throwIfDisposed(), Hr(this);
  };
  K.prototype.sign = function() {
    return this.throwIfDisposed(), a0(this);
  };
  K.prototype.sin = function() {
    return this.throwIfDisposed(), ch(this);
  };
  K.prototype.sinh = function() {
    return this.throwIfDisposed(), lh(this);
  };
  K.prototype.slice = function(n, t) {
    return this.throwIfDisposed(), Me(this, n, t);
  };
  K.prototype.softmax = function(n) {
    return this.throwIfDisposed(), s0(this, n);
  };
  K.prototype.softplus = function() {
    return this.throwIfDisposed(), Xu(this);
  };
  K.prototype.spaceToBatchND = function(n, t) {
    return this.throwIfDisposed(), ro(this, n, t);
  };
  K.prototype.split = function(n, t) {
    return this.throwIfDisposed(), Bi(this, n, t);
  };
  K.prototype.sqrt = function() {
    return this.throwIfDisposed(), Ht(this);
  };
  K.prototype.square = function() {
    return this.throwIfDisposed(), $e(this);
  };
  K.prototype.squaredDifference = function(n) {
    return this.throwIfDisposed(), so(this, n);
  };
  K.prototype.squaredDifferenceStrict = function(n) {
    return this.throwIfDisposed(), N0(this, n);
  };
  K.prototype.squeeze = function(n) {
    return this.throwIfDisposed(), oo(this, n);
  };
  K.prototype.stack = function(n, t) {
    this.throwIfDisposed();
    var e = n instanceof K ? [this, n] : [this].concat(n);
    return Jr(e, t);
  };
  K.prototype.step = function(n) {
    return this.throwIfDisposed(), zi(this, n);
  };
  K.prototype.stridedSlice = function(n, t, e, r, i, a, s, o) {
    return this.throwIfDisposed(), c0(this, n, t, e, r, i, a, s, o);
  };
  K.prototype.subStrict = function(n) {
    return this.throwIfDisposed(), _0(this, n);
  };
  K.prototype.sub = function(n) {
    return this.throwIfDisposed(), be(this, n);
  };
  K.prototype.sum = function(n, t) {
    return this.throwIfDisposed(), _e(this, n, t);
  };
  K.prototype.tan = function() {
    return this.throwIfDisposed(), l0(this);
  };
  K.prototype.tanh = function() {
    return this.throwIfDisposed(), Vs(this);
  };
  K.prototype.tile = function(n) {
    return this.throwIfDisposed(), Di(this, n);
  };
  K.prototype.toBool = function() {
    return this.throwIfDisposed(), he(this, "bool");
  };
  K.prototype.toFloat = function() {
    return this.throwIfDisposed(), he(this, "float32");
  };
  K.prototype.toInt = function() {
    return this.throwIfDisposed(), he(this, "int32");
  };
  K.prototype.topk = function(n, t) {
    return this.throwIfDisposed(), u0(this, n, t);
  };
  K.prototype.transpose = function(n) {
    return this.throwIfDisposed(), Tt(this, n);
  };
  K.prototype.unique = function(n) {
    return this.throwIfDisposed(), h0(this, n);
  };
  K.prototype.unsortedSegmentSum = function(n, t) {
    return this.throwIfDisposed(), hh(this, n, t);
  };
  K.prototype.unstack = function(n) {
    return this.throwIfDisposed(), co(this, n);
  };
  K.prototype.where = function(n, t) {
    return this.throwIfDisposed(), yn(n, this, t);
  };
  K.prototype.zerosLike = function() {
    return this.throwIfDisposed(), ke(this);
  };
  A.Abs = xc;
  A.Acos = Lc;
  A.Acosh = Sc;
  A.AdadeltaOptimizer = mh;
  A.AdagradOptimizer = gh;
  A.AdamOptimizer = yh;
  A.AdamaxOptimizer = vh;
  A.Add = Rs;
  A.AddN = Ic;
  A.All = If;
  A.Any = Af;
  A.ArgMax = Ac;
  A.ArgMin = Tc;
  A.Asin = Nc;
  A.Asinh = _c;
  A.Atan = Cc;
  A.Atan2 = Oc;
  A.Atanh = Rc;
  A.AvgPool = Ec;
  A.AvgPool3D = Dc;
  A.AvgPool3DBackprop = Nf;
  A.AvgPoolBackprop = Tf;
  A.BatchMatMul = kc;
  A.BatchToSpaceND = Fc;
  A.BroadcastTo = Wc;
  A.Cast = Os;
  A.Ceil = Uc;
  A.ClipByValue = Bc;
  A.Complex = _f;
  A.Concat = zc;
  A.Conv2D = Pc;
  A.Conv2DBackpropFilter = Cf;
  A.Conv2DBackpropInput = Mc;
  A.Conv3D = Hc;
  A.Conv3DBackpropFilterV2 = Rf;
  A.Conv3DBackpropInputV2 = Of;
  A.Cos = Vc;
  A.Cosh = Gc;
  A.CropAndResize = Ef;
  A.Cumsum = qc;
  A.DataStorage = mL;
  A.DepthToSpace = Df;
  A.DepthwiseConv2dNative = Yc;
  A.DepthwiseConv2dNativeBackpropFilter = kf;
  A.DepthwiseConv2dNativeBackpropInput = Ff;
  A.Diag = Wf;
  A.Dilation2D = Kc;
  A.Dilation2DBackpropFilter = Bf;
  A.Dilation2DBackpropInput = Uf;
  A.Div = jc;
  A.Elu = $c;
  A.EluGrad = zf;
  A.Environment = xf;
  A.Equal = Pf;
  A.Erf = Xc;
  A.Exp = Jc;
  A.Expm1 = Zc;
  A.FFT = Mf;
  A.Fill = Hf;
  A.FlipLeftRight = Vf;
  A.Floor = Qc;
  A.FloorDiv = el;
  A.FromPixels = au;
  A.FusedBatchNorm = tl;
  A.FusedConv2D = ou;
  A.FusedDepthwiseConv2D = cu;
  A.GatherNd = Gf;
  A.GatherV2 = nl;
  A.Greater = qf;
  A.GreaterEqual = rl;
  A.IFFT = Yf;
  A.Identity = il;
  A.Imag = Kf;
  A.IsFinite = al;
  A.IsInf = sl;
  A.IsNan = ol;
  A.KernelBackend = of;
  A.LRN = hl;
  A.LRNBackprop = em;
  A.Less = jf;
  A.LessEqual = $f;
  A.LinSpace = Xf;
  A.Log = cl;
  A.Log1p = ll;
  A.LogSoftmax = ul;
  A.LogicalAnd = Jf;
  A.LogicalNot = Zf;
  A.LogicalOr = Qf;
  A.Max = dl;
  A.MaxPool = fl;
  A.MaxPool3D = ml;
  A.MaxPool3DBackprop = nm;
  A.MaxPoolBackprop = tm;
  A.MaxPoolWithArgmax = rm;
  A.Maximum = pl;
  A.Mean = im;
  A.Min = gl;
  A.Minimum = yl;
  A.MirrorPad = vl;
  A.Mod = wl;
  A.MomentumOptimizer = wh;
  A.Multiply = bl;
  A.Negate = xl;
  A.NonMaxSuppressionV3 = sm;
  A.NonMaxSuppressionV4 = om;
  A.NonMaxSuppressionV5 = cm;
  A.NotEqual = am;
  A.OP_SCOPE_SUFFIX = Em;
  A.OneHot = Sl;
  A.OnesLike = Ll;
  A.Optimizer = yr;
  A.PadV2 = Il;
  A.Pool = DL;
  A.Pow = Al;
  A.Prelu = Tl;
  A.Prod = lm;
  A.RMSPropOptimizer = bh;
  A.Range = um;
  A.Real = hm;
  A.Reciprocal = Nl;
  A.Relu = _l;
  A.Relu6 = El;
  A.Reshape = Cl;
  A.ResizeBilinear = Ol;
  A.ResizeBilinearGrad = pm;
  A.ResizeNearestNeighbor = Rl;
  A.ResizeNearestNeighborGrad = dm;
  A.Reverse = Dl;
  A.RotateWithOffset = bm;
  A.Round = kl;
  A.Rsqrt = Fl;
  A.SGDOptimizer = mo;
  A.ScatterNd = fm;
  A.SelectV2 = Wl;
  A.Selu = Ul;
  A.Sigmoid = Hl;
  A.Sign = Ml;
  A.Sin = zl;
  A.Sinh = Pl;
  A.Slice = Bl;
  A.Softmax = jl;
  A.Softplus = Vl;
  A.SpaceToBatchND = Yl;
  A.SparseToDense = gm;
  A.SplitV = Kl;
  A.Sqrt = Gl;
  A.Square = mm;
  A.SquaredDifference = $l;
  A.Step = iu;
  A.StridedSlice = ym;
  A.Sub = Xl;
  A.Sum = ql;
  A.Tan = Jl;
  A.Tanh = Zl;
  A.Tensor = K;
  A.TensorBuffer = Fs;
  A.Tile = Ql;
  A.TopK = vm;
  A.Transpose = eu;
  A.Unique = wm;
  A.Unpack = tu;
  A.UnsortedSegmentSum = nu;
  A.Variable = La;
  A.ZerosLike = ru;
  A._FusedMatMul = su;
  A.abs = jt;
  A.acos = fg;
  A.acosh = mg;
  A.add = ge;
  A.addN = QI;
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      var r = n.call(this) || this;
      return r.defaultMinValue = 0, r.defaultMaxValue = 1, r.defaultRate = 1, r.defaultAxis = 0, r.minValue = e.minValue != null ? e.minValue : r.defaultMinValue, r.maxValue = e.maxValue != null ? e.maxValue : r.defaultMaxValue, r.rate = e.rate != null ? e.rate : r.defaultRate, r.axis = e.axis != null ? e.axis : r.defaultAxis, r;
    }
    return t.prototype.apply = function(e) {
      var r = this;
      return v.tidy(function() {
        var i = Nh(e, r.axis), a = v.add(v.mul(r.rate, v.clipByValue(i, r.minValue, r.maxValue)), v.mul(1 - r.rate, i));
        return v.mul(e, v.div(a, v.add(St(), i)));
      });
    }, t.prototype.getConfig = function() {
      return {minValue: this.minValue, maxValue: this.maxValue, rate: this.rate, axis: this.axis};
    }, t.className = "MinMaxNorm", t;
  }(Ua);
  v.serialization.registerClass(iy);
  var ay = {maxNorm: "MaxNorm", minMaxNorm: "MinMaxNorm", nonNeg: "NonNeg", unitNorm: "UnitNorm"};
  function It(n) {
    return Ih(n);
  }
  function sy(n, t) {
    return t === void 0 && (t = {}), Wa(n, v.serialization.SerializationMap.getMap().classNameMap, t, "constraint");
  }
  function At(n) {
    if (n == null)
      return null;
    if (typeof n == "string") {
      var t = n in ay ? ay[n] : n, e = {className: t, config: {}};
      return sy(e);
    } else
      return n instanceof Ua ? n : sy(n);
  }
  function DO(n) {
    return new ty(n);
  }
  function kO(n) {
    return new ny(n);
  }
  function FO() {
    return new ry();
  }
  function WO(n) {
    return new iy(n);
  }
  var UO = {__proto__: null, maxNorm: DO, unitNorm: kO, nonNeg: FO, minMaxNorm: WO};
  var BO = ["channelsFirst", "channelsLast"], zO = ["valid", "same", "causal"], PO = ["max", "avg"], MO = ["sum", "mul", "concat", "ave"];
  var Hi = new Map();
  function gt(n) {
    Mi(BO, "DataFormat", n);
  }
  function sn(n) {
    Mi(zO, "PaddingMode", n);
  }
  function oy(n) {
    Mi(PO, "PoolMode", n);
  }
  var Ba = [], cy = "/";
  function ni(n, t) {
    Ba.push(n);
    try {
      var e = t();
      return Ba.pop(), e;
    } catch (r) {
      throw Ba.pop(), r;
    }
  }
  function HO() {
    return Ba.length === 0 ? "" : Ba.join(cy) + cy;
  }
  function uy(n) {
    if (!ly(n))
      throw new Error("Not a valid tensor name: '" + n + "'");
    return HO() + n;
  }
  function hy(n) {
    if (!ly(n))
      throw new Error("Not a valid tensor name: '" + n + "'");
    Hi.has(n) || Hi.set(n, 0);
    var t = Hi.get(n);
    if (Hi.set(n, Hi.get(n) + 1), t > 0) {
      var e = n + "_" + t;
      return Hi.set(e, 1), e;
    } else
      return n;
  }
  var VO = new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);
  function ly(n) {
    return !!n.match(VO);
  }
  function GO(n) {
    return n === parseInt(n.toString(), 10);
  }
  function br(n, t, e) {
    t == null && (t = 0), e == null && (e = n.length);
    for (var r = 1, i = t; i < e; ++i)
      r *= n[i];
    return r;
  }
  function dy(n) {
    return n = Array.isArray(n) ? new Float32Array(n) : n, v.tensor1d(n);
  }
  function Vi(n) {
    return v.min(dy(n)).dataSync()[0];
  }
  function xr(n) {
    return v.max(dy(n)).dataSync()[0];
  }
  function xn(n, t) {
    if (t < n)
      throw new M("end (" + t + ") < begin (" + n + ") is forbidden.");
    for (var e = [], r = n; r < t; ++r)
      e.push(r);
    return e;
  }
  function za(n, t) {
    return n.asType(t);
  }
  function Pa(n, t) {
    t === void 0 && (t = -1);
    var e = n.shape.slice();
    return t < 0 && (t = e.length + t + 1), e.splice(t, 0, 1), n.reshape(e);
  }
  function qO(n, t) {
    return v.tidy(function() {
      if (n.shape.length !== 2)
        throw new M("repeat() expects a rank-2 tensor, but received a " + ("rank-" + n.shape.length + " tensor."));
      var e = Pa(n, 1);
      return _h(e, [1, t, 1]);
    });
  }
  function YO(n) {
    var t = [br(n.shape)];
    return n.reshape(t);
  }
  function KO(n) {
    if (n.rank <= 1)
      throw new M("batchFlatten requires a minimum rank of 2. Got rank: " + n.rank + ".");
    var t = [n.shape[0], br(n.shape, 1)];
    return n.reshape(t);
  }
  function ri(n, t, e) {
    return v.tidy(function() {
      switch (n.rank) {
        case 1:
          return v.slice1d(n, t, e);
        case 2:
          return v.slice2d(n, [t, 0], [e, n.shape[1]]);
        case 3:
          return v.slice3d(n, [t, 0, 0], [e, n.shape[1], n.shape[2]]);
        case 4:
          return v.slice4d(n, [t, 0, 0, 0], [e, n.shape[1], n.shape[2], n.shape[3]]);
        case 5:
          return v.slice(n, [t, 0, 0, 0, 0], [e, n.shape[1], n.shape[2], n.shape[3], n.shape[4]]);
        case 6:
          return v.slice(n, [t, 0, 0, 0, 0, 0], [e, n.shape[1], n.shape[2], n.shape[3], n.shape[4], n.shape[5]]);
        default:
          throw new M("sliceAlongFirstAxis() received an unsupported tensor rank: " + ("" + n.rank));
      }
    });
  }
  function Ch(n, t, e) {
    return v.tidy(function() {
      switch (n.rank) {
        case 1:
          return v.slice1d(n, t, e);
        case 2:
          return v.slice2d(n, [0, t], [n.shape[0], e]);
        case 3:
          return v.slice3d(n, [0, 0, t], [n.shape[0], n.shape[1], e]);
        case 4:
          return v.slice4d(n, [0, 0, 0, t], [n.shape[0], n.shape[1], n.shape[2], e]);
        default:
          throw new M("sliceAlongLastAxis() received an unsupported tensor rank: " + ("" + n.rank));
      }
    });
  }
  function yo(n, t, e, r) {
    return v.tidy(function() {
      switch (n.rank) {
        case 1:
          return v.slice1d(n, t, e);
        case 2:
          switch (r) {
            case 1:
              return ri(n, t, e);
            case 2:
              return Ch(n, t, e);
            default:
              throw new M("The axis is not within the rank of the tensor " + ("" + r));
          }
        case 3:
          switch (r) {
            case 1:
              return ri(n, t, e);
            case 2:
              return v.slice3d(n, [0, t, 0], [n.shape[0], e, n.shape[2]]);
            case 3:
              return Ch(n, t, e);
            default:
              throw new M("The axis is not within the rank of the tensor " + ("" + r));
          }
        case 4:
          switch (r) {
            case 1:
              return ri(n, t, e);
            case 2:
              return v.slice4d(n, [0, t, 0, 0], [n.shape[0], e, n.shape[2], n.shape[3]]);
            case 3:
              return v.slice4d(n, [0, 0, t, 0], [n.shape[0], n.shape[1], e, n.shape[3]]);
            case 4:
              return Ch(n, t, e);
            default:
              throw new M("The axis is not within the rank of the tensor " + ("" + r));
          }
        default:
          throw new M("sliceAlongLastAxis() received an unsupported tensor rank: " + ("" + n.rank));
      }
    });
  }
  function Rh(n, t) {
    t === void 0 && (t = -1);
    var e;
    return t < 0 && (e = n[0].rank, e !== 0 ? t = e : t = 0), t === n[0].rank && (t = -1), v.concat(n, t);
  }
  function py(n, t) {
    switch (n.rank) {
      case 1:
        return v.concat1d([n, t]);
      case 2:
        return v.concat2d([n, t], 0);
      case 3:
        return v.concat3d([n, t], 0);
      case 4:
        return v.concat4d([n, t], 0);
      default:
        throw new M("concatAlongFirstAxis() received an unsupported " + ("tensor rank: " + n.rank));
    }
  }
  function _h(n, t) {
    if (Array.isArray(t) || (t = [t]), n.rank !== t.length)
      throw new M("The length of input n (" + t.length + ") does not match " + ("the number of dimensions in input x (" + n.rank + ")"));
    return v.tile(n, t);
  }
  function vo(n, t, e, r, i) {
    return t === void 0 && (t = 0), e === void 0 && (e = 1), v.randomNormal(n, t, e, r, i);
  }
  function Un(n, t, e, r) {
    if (n.rank < 2 || t.rank < 2)
      throw new Re("dot requires both inputs to be rank >= 2" + (" but got x shape = " + n.shape + " and y shape = " + t.shape));
    if (t.rank >= 3) {
      var i = n.shape.slice(-1)[0], a = t.shape.slice(-2)[0];
      if (i !== a)
        throw new Re("If rank y >= 3, then the second last dim" + (" of y must equal the last dim of x but got x shape = " + n.shape + " and ") + (" y shape = " + t.shape));
    }
    if (n.rank === 2 && t.rank === 2) {
      var s = false, o = false;
      return v.fused.matMul({a: n, b: t, transposeA: s, transposeB: o, bias: r ? Oh(n.rank, r, bn()) : null, activation: e});
    } else {
      var c = n.shape.slice(), l = c.pop();
      n = n.reshape([-1, l]);
      var u = t.shape.slice(), h = u.pop(), a = u.pop(), d = u.concat([h]), p = Array.from({length: t.rank}, function(w, b) {
        return b === 0 ? t.rank - 2 : b <= t.rank - 2 ? b - 1 : b;
      });
      t = t.transpose(p).reshape([a, -1]);
      var f = c.concat(d), s = false, o = false;
      return v.fused.matMul({a: n, b: t, transposeA: s, transposeB: o, bias: r ? Oh(n.rank, r, bn()) : null, activation: e}).reshape(f);
    }
  }
  function fy(n, t, e) {
    return v.tidy(function() {
      return Array.isArray(t) ? t = v.tensor1d(t, "int32") : t = t.toInt(), v.gather(n, t, e);
    });
  }
  function Ma(n) {
    return v.mul(n, n);
  }
  function Oh(n, t, e) {
    var r = t.shape;
    if (t.rank !== 1 && t.rank !== n)
      throw new M("Unexpected bias dimensions: " + t.rank + ("; expected it to be 1 or " + n));
    if (n === 5) {
      if (e === "channelsFirst")
        return r.length === 1 ? t.reshape([1, r[0], 1, 1, 1]) : t.reshape([1, r[3], r[0], r[1], r[2]]);
      if (e === "channelsLast")
        return r.length === 1 ? t.reshape([1, 1, 1, 1, r[0]]) : t.reshape([1].concat(r));
    } else if (n === 4) {
      if (e === "channelsFirst")
        return r.length === 1 ? t.reshape([1, r[0], 1, 1]) : t.reshape([1, r[2], r[0], r[1]]);
      if (e === "channelsLast")
        return r.length === 1 ? t.reshape([1, 1, 1, r[0]]) : t.reshape([1].concat(r));
    } else if (n === 3) {
      if (e === "channelsFirst")
        return r.length === 1 ? t.reshape([1, r[0], 1]) : t.reshape([1, r[1], r[0]]);
      if (e === "channelsLast")
        return r.length === 1 ? t.reshape([1, 1, r[0]]) : t.reshape([1].concat(r));
    } else if (n < 3)
      return t;
    throw new M("Unsupported input rank by biasAdd: " + t.rank);
  }
  function Bn(n, t, e) {
    return v.tidy(function() {
      return e == null && (e = bn()), gt(e), n.add(Oh(n.rank, t, e));
    });
  }
  function jO(n, t) {
    if (t === void 0 && (t = 1), t !== 1)
      throw new Re("Support for alpha values other than 1 (" + t + ") is not implemented yet.");
    return v.elu(n);
  }
  function $O(n) {
    return v.tidy(function() {
      return v.div(n, v.abs(n).add(1));
    });
  }
  function my(n, t, e, r) {
    return v.tidy(function() {
      return v.dropout(n, t, e, r);
    });
  }
  function XO(n) {
    return v.tidy(function() {
      var t = v.add(0.5, v.mul(0.2, n));
      return v.clipByValue(t, 0, 1);
    });
  }
  function Ha(n, t, e) {
    return e === void 0 && (e = false), e ? n() : t();
  }
  var JO = ["fanIn", "fanOut", "fanAvg"], ZO = ["normal", "uniform", "truncatedNormal"];
  function QO(n) {
    Mi(JO, "FanMode", n);
  }
  function eE(n) {
    Mi(ZO, "Distribution", n);
  }
  var dn = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.fromConfigUsesCustomObjects = function() {
      return false;
    }, t.prototype.getConfig = function() {
      return {};
    }, t;
  }(v.serialization.Serializable), gy = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e, r) {
      return v.zeros(e, r);
    }, t.className = "Zeros", t;
  }(dn);
  v.serialization.registerClass(gy);
  var Eh = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e, r) {
      return v.ones(e, r);
    }, t.className = "Ones", t;
  }(dn);
  v.serialization.registerClass(Eh);
  var yy = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this) || this;
      if (typeof e != "object")
        throw new M("Expected argument of type ConstantConfig but got " + e);
      if (e.value === void 0)
        throw new M("config must have value set but got " + e);
      return r.value = e.value, r;
    }
    return t.prototype.apply = function(e, r) {
      var i = this;
      return v.tidy(function() {
        return v.mul(v.scalar(i.value), v.ones(e, r));
      });
    }, t.prototype.getConfig = function() {
      return {value: this.value};
    }, t.className = "Constant", t;
  }(dn);
  v.serialization.registerClass(yy);
  var vy = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.DEFAULT_MINVAL = -0.05, r.DEFAULT_MAXVAL = 0.05, r.minval = e.minval || r.DEFAULT_MINVAL, r.maxval = e.maxval || r.DEFAULT_MAXVAL, r.seed = e.seed, r;
    }
    return t.prototype.apply = function(e, r) {
      return v.randomUniform(e, this.minval, this.maxval, r);
    }, t.prototype.getConfig = function() {
      return {minval: this.minval, maxval: this.maxval, seed: this.seed};
    }, t.className = "RandomUniform", t;
  }(dn);
  v.serialization.registerClass(vy);
  var wy = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.DEFAULT_MEAN = 0, r.DEFAULT_STDDEV = 0.05, r.mean = e.mean || r.DEFAULT_MEAN, r.stddev = e.stddev || r.DEFAULT_STDDEV, r.seed = e.seed, r;
    }
    return t.prototype.apply = function(e, r) {
      if (r = r || "float32", r !== "float32" && r !== "int32")
        throw new Re("randomNormal does not support dType " + r + ".");
      return vo(e, this.mean, this.stddev, r, this.seed);
    }, t.prototype.getConfig = function() {
      return {mean: this.mean, stddev: this.stddev, seed: this.seed};
    }, t.className = "RandomNormal", t;
  }(dn);
  v.serialization.registerClass(wy);
  var by = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.DEFAULT_MEAN = 0, r.DEFAULT_STDDEV = 0.05, r.mean = e.mean || r.DEFAULT_MEAN, r.stddev = e.stddev || r.DEFAULT_STDDEV, r.seed = e.seed, r;
    }
    return t.prototype.apply = function(e, r) {
      if (r = r || "float32", r !== "float32" && r !== "int32")
        throw new Re("truncatedNormal does not support dType " + r + ".");
      return v.truncatedNormal(e, this.mean, this.stddev, r, this.seed);
    }, t.prototype.getConfig = function() {
      return {mean: this.mean, stddev: this.stddev, seed: this.seed};
    }, t.className = "TruncatedNormal", t;
  }(dn);
  v.serialization.registerClass(by);
  var xy = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.gain = e.gain != null ? e.gain : 1, r;
    }
    return t.prototype.apply = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (e.length !== 2 || e[0] !== e[1])
          throw new M("Identity matrix initializer can only be used for 2D square matrices.");
        return v.mul(i.gain, v.eye(e[0]));
      });
    }, t.prototype.getConfig = function() {
      return {gain: this.gain};
    }, t.className = "Identity", t;
  }(dn);
  v.serialization.registerClass(xy);
  function tE(n, t) {
    t === void 0 && (t = "channelsLast");
    var e, r;
    if (gt(t), n.length === 2)
      e = n[0], r = n[1];
    else if ([3, 4, 5].indexOf(n.length) !== -1) {
      if (t === "channelsFirst") {
        var i = br(n, 2);
        e = n[1] * i, r = n[0] * i;
      } else if (t === "channelsLast") {
        var i = br(n, 0, n.length - 2);
        e = n[n.length - 2] * i, r = n[n.length - 1] * i;
      }
    } else {
      var a = br(n);
      e = Math.sqrt(a), r = Math.sqrt(a);
    }
    return [e, r];
  }
  var Xt = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this) || this;
      if (e.scale < 0)
        throw new M("scale must be a positive float. Got: " + e.scale);
      return r.scale = e.scale == null ? 1 : e.scale, r.mode = e.mode == null ? "fanIn" : e.mode, QO(r.mode), r.distribution = e.distribution == null ? "normal" : e.distribution, eE(r.distribution), r.seed = e.seed, r;
    }
    return t.prototype.apply = function(e, r) {
      var i = tE(e), a = i[0], s = i[1], o = this.scale;
      if (this.mode === "fanIn" ? o /= Math.max(1, a) : this.mode === "fanOut" ? o /= Math.max(1, s) : o /= Math.max(1, (a + s) / 2), this.distribution === "normal") {
        var c = Math.sqrt(o);
        if (r = r || "float32", r !== "float32" && r !== "int32")
          throw new Re(this.getClassName() + " does not support dType " + r + ".");
        return v.truncatedNormal(e, 0, c, r, this.seed);
      } else {
        var l = Math.sqrt(3 * o);
        return v.randomUniform(e, -l, l, r);
      }
    }, t.prototype.getConfig = function() {
      return {scale: this.scale, mode: this.mode, distribution: this.distribution, seed: this.seed};
    }, t.className = "VarianceScaling", t;
  }(dn);
  v.serialization.registerClass(Xt);
  var Dh = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, {scale: 1, mode: "fanAvg", distribution: "uniform", seed: e == null ? null : e.seed}) || this;
    }
    return t.prototype.getClassName = function() {
      return Xt.className;
    }, t.className = "GlorotUniform", t;
  }(Xt);
  v.serialization.registerClass(Dh);
  var kh = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, {scale: 1, mode: "fanAvg", distribution: "normal", seed: e == null ? null : e.seed}) || this;
    }
    return t.prototype.getClassName = function() {
      return Xt.className;
    }, t.className = "GlorotNormal", t;
  }(Xt);
  v.serialization.registerClass(kh);
  var Fh = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, {scale: 2, mode: "fanIn", distribution: "normal", seed: e == null ? null : e.seed}) || this;
    }
    return t.prototype.getClassName = function() {
      return Xt.className;
    }, t.className = "HeNormal", t;
  }(Xt);
  v.serialization.registerClass(Fh);
  var Wh = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, {scale: 2, mode: "fanIn", distribution: "uniform", seed: e == null ? null : e.seed}) || this;
    }
    return t.prototype.getClassName = function() {
      return Xt.className;
    }, t.className = "HeUniform", t;
  }(Xt);
  v.serialization.registerClass(Wh);
  var Uh = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, {scale: 1, mode: "fanIn", distribution: "normal", seed: e == null ? null : e.seed}) || this;
    }
    return t.prototype.getClassName = function() {
      return Xt.className;
    }, t.className = "LeCunNormal", t;
  }(Xt);
  v.serialization.registerClass(Uh);
  var Bh = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, {scale: 1, mode: "fanIn", distribution: "uniform", seed: e == null ? null : e.seed}) || this;
    }
    return t.prototype.getClassName = function() {
      return Xt.className;
    }, t.className = "LeCunNormal", t;
  }(Xt);
  v.serialization.registerClass(Bh);
  var Ly = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this) || this;
      if (r.DEFAULT_GAIN = 1, r.gain = e.gain == null ? r.DEFAULT_GAIN : e.gain, r.seed = e.seed, r.seed != null)
        throw new Re("Random seed is not implemented for Orthogonal Initializer yet.");
      return r;
    }
    return t.prototype.apply = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (e.length < 2)
          throw new Re("Shape must be at least 2D.");
        e[0] * e[1] > 2e3 && console.warn("Orthogonal initializer is being called on a matrix with more " + ("than 2000 (" + e[0] * e[1] + ") elements: ") + "Slowness may result.");
        var a = e[0] > e[1] ? [e[1], e[0]] : e, s = vo(a, 0, 1, "float32"), o = v.linalg.gramSchmidt(s);
        return e[0] > e[1] && (o = o.transpose()), v.mul(i.gain, o);
      });
    }, t.prototype.getConfig = function() {
      return {gain: this.gain, seed: this.seed};
    }, t.className = "Orthogonal", t;
  }(dn);
  v.serialization.registerClass(Ly);
  var Sy = {constant: "Constant", glorotNormal: "GlorotNormal", glorotUniform: "GlorotUniform", heNormal: "HeNormal", heUniform: "HeUniform", identity: "Identity", leCunNormal: "LeCunNormal", leCunUniform: "LeCunUniform", ones: "Ones", orthogonal: "Orthogonal", randomNormal: "RandomNormal", randomUniform: "RandomUniform", truncatedNormal: "TruncatedNormal", varianceScaling: "VarianceScaling", zeros: "Zeros"};
  function Iy(n, t) {
    return t === void 0 && (t = {}), Wa(n, v.serialization.SerializationMap.getMap().classNameMap, t, "initializer");
  }
  function lt(n) {
    return Ih(n);
  }
  function at(n) {
    if (typeof n == "string") {
      var t = n in Sy ? Sy[n] : n;
      if (t === "GlorotNormal")
        return new kh();
      if (t === "GlorotUniform")
        return new Dh();
      if (t === "HeNormal")
        return new Fh();
      if (t === "HeUniform")
        return new Wh();
      if (t === "LeCunNormal")
        return new Uh();
      if (t === "LeCunUniform")
        return new Bh();
      var e = {};
      return e.className = t, e.config = {}, Iy(e);
    } else
      return n instanceof dn ? n : Iy(n);
  }
  function nE() {
    return new gy();
  }
  function rE() {
    return new Eh();
  }
  function iE(n) {
    return new yy(n);
  }
  function aE(n) {
    return new vy(n);
  }
  function sE(n) {
    return new wy(n);
  }
  function oE(n) {
    return new by(n);
  }
  function cE(n) {
    return new xy(n);
  }
  function lE(n) {
    return new Xt(n);
  }
  function uE(n) {
    return new Dh(n);
  }
  function hE(n) {
    return new kh(n);
  }
  function dE(n) {
    return new Fh(n);
  }
  function pE(n) {
    return new Wh(n);
  }
  function fE(n) {
    return new Uh(n);
  }
  function mE(n) {
    return new Bh(n);
  }
  function gE(n) {
    return new Ly(n);
  }
  var yE = {__proto__: null, zeros: nE, ones: rE, constant: iE, randomUniform: aE, randomNormal: sE, truncatedNormal: oE, identity: cE, varianceScaling: lE, glorotUniform: uE, glorotNormal: hE, heNormal: dE, heUniform: pE, leCunNormal: fE, leCunUniform: mE, orthogonal: gE};
  var vE = 0;
  function Ay() {
    return vE++;
  }
  var wo = {};
  function bo(n) {
    return n === void 0 && (n = ""), n in wo || (wo[n] = 0), wo[n] += 1, n + wo[n].toString();
  }
  function zh(n) {
    return Array.isArray(n) && Array.isArray(n[0]);
  }
  function xo(n) {
    return n.length === 0 ? [] : Array.isArray(n[0]) ? n : [n];
  }
  function Oe(n) {
    var t;
    if (Array.isArray(n)) {
      if (n.length !== 1)
        throw new M("Expected Tensor length to be 1; got " + n.length);
      t = n[0];
    } else
      t = n;
    return t;
  }
  function Xe(n) {
    if (Array.isArray(n) && Array.isArray(n[0])) {
      if (n.length === 1)
        return n = n, n[0];
      throw new M("Expected exactly 1 Shape; got " + n.length);
    } else
      return n;
  }
  function Lo(n) {
    for (var t = 0, e = 0, r = n; e < r.length; e++) {
      var i = r[e];
      i.shape.length === 0 ? t += 1 : t += i.shape.reduce(function(a, s) {
        return a * s;
      });
    }
    return t;
  }
  var Ty = "Variable", Ny = function() {
    function n(t, e, r, i, a) {
      e === void 0 && (e = "float32"), r === void 0 && (r = Ty), i === void 0 && (i = true), a === void 0 && (a = null), this.dtype = e == null ? "float32" : e, this.shape = t.shape, this.id = Ay(), r = r == null ? Ty : r, this.originalName = uy(r), this.name = hy(this.originalName), this.trainable_ = i, this.constraint = a, this.val = v.variable(t, this.trainable_, this.name, this.dtype);
    }
    return n.prototype.read = function() {
      return this.assertNotDisposed(), this.val;
    }, n.prototype.write = function(t) {
      return this.assertNotDisposed(), wE(this.val, t), this.val.id !== t.id && (this.val.assign(t), this.constraint != null && this.val.assign(this.constraint.apply(this.val))), this;
    }, n.prototype.dispose = function() {
      this.assertNotDisposed(), this.val.dispose();
    }, n.prototype.assertNotDisposed = function() {
      if (this.val.isDisposed)
        throw new Error("LayersVariable " + this.name + " is already disposed.");
    }, Object.defineProperty(n.prototype, "trainable", {get: function() {
      return this.trainable_;
    }, set: function(t) {
      this.trainable_ = t, this.val.trainable = t;
    }, enumerable: true, configurable: true}), n;
  }();
  function wE(n, t) {
    if (n.shape.toString() !== t.shape.toString())
      throw new Error("Shape mismatch: " + JSON.stringify(n.shape) + " vs. " + JSON.stringify(t.shape));
  }
  function Ph(n) {
    return n.map(function(t) {
      return t.read();
    });
  }
  function Mh(n) {
    n.forEach(function(t) {
      var e = t[0];
      e.write(t[1]);
    });
  }
  var Ct = function() {
    function n(t) {
      this.dtype = t.dtype, this.shape = t.shape, t.shape != null ? this.ndim = t.shape.length : this.ndim = t.ndim, this.maxNDim = t.maxNDim, this.minNDim = t.minNDim, this.axes = t.axes || {};
    }
    return n;
  }(), Ln = function() {
    function n(t, e, r, i, a, s, o) {
      this.dtype = t, this.shape = e, this.sourceLayer = r, this.inputs = i, this.callArgs = a, this.outputTensorIndex = o, this.id = Ay(), s != null && (this.originalName = uy(s), this.name = hy(this.originalName)), this.rank = e.length;
    }
    return n;
  }(), bE = 0, So = function() {
    function n(t, e) {
      this.callArgs = e, this.id = bE++, this.outboundLayer = t.outboundLayer, this.inboundLayers = t.inboundLayers, this.nodeIndices = t.nodeIndices, this.tensorIndices = t.tensorIndices, this.inputTensors = t.inputTensors, this.outputTensors = t.outputTensors, this.inputMasks = t.inputMasks, this.outputMasks = t.outputMasks, this.inputShapes = t.inputShapes, this.outputShapes = t.outputShapes;
      for (var r = 0, i = t.inboundLayers; r < i.length; r++) {
        var a = i[r];
        a != null && a.outboundNodes.push(this);
      }
      t.outboundLayer.inboundNodes.push(this);
    }
    return n.prototype.getConfig = function() {
      for (var t = [], e = 0, r = this.inboundLayers; e < r.length; e++) {
        var i = r[e];
        i != null ? t.push(i.name) : t.push(null);
      }
      return {outboundLayer: this.outboundLayer ? this.outboundLayer.name : null, inboundLayers: t, nodeIndices: this.nodeIndices, tensorIndices: this.tensorIndices};
    }, n;
  }(), xE = 0, Fe = function(n) {
    Q(t, n);
    function t(e) {
      e === void 0 && (e = {});
      var r = n.call(this) || this;
      r._callHook = null, r._addedWeightNames = [], r._stateful = false, r.id = xE++, r.activityRegularizer = null, r.inputSpec = null, r.supportsMasking = false, r._trainableWeights = [], r._nonTrainableWeights = [], r._losses = [], r._updates = [], r._built = false, r.inboundNodes = [], r.outboundNodes = [];
      var i = e.name;
      if (!i) {
        var a = r.getClassName();
        i = Zn(a) + "_" + bo(a);
      }
      if (r.name = i, r.trainable_ = e.trainable == null ? true : e.trainable, e.inputShape != null || e.batchInputShape != null) {
        var s = void 0;
        if (e.batchInputShape != null)
          s = e.batchInputShape;
        else if (e.inputShape != null) {
          var o = null;
          e.batchSize != null && (o = e.batchSize), s = [o].concat(e.inputShape);
        }
        r.batchInputShape = s;
        var c = e.dtype;
        c == null && (c = e.inputDType), c == null && (c = "float32"), r.dtype = c;
      }
      return e.weights != null ? r.initialWeights = e.weights : r.initialWeights = null, r._refCount = null, r.fastWeightInitDuringBuild = false, r;
    }
    return t.nodeKey = function(e, r) {
      return e.name + "_ib-" + r.toString();
    }, t.prototype.getNodeAtIndex = function(e, r) {
      if (this.inboundNodes.length === 0)
        throw new Fn("The layer has never been called " + ("and thus has no defined " + r + "."));
      if (this.inboundNodes.length <= e)
        throw new M("Asked to get " + r + " at node " + e + ", " + ("but the layer has only " + this.inboundNodes.length + " inbound nodes."));
      return this.inboundNodes[e];
    }, t.prototype.getInputAt = function(e) {
      return Vt(this.getNodeAtIndex(e, "input").inputTensors);
    }, t.prototype.getOutputAt = function(e) {
      return Vt(this.getNodeAtIndex(e, "output").outputTensors);
    }, Object.defineProperty(t.prototype, "input", {get: function() {
      if (this.inboundNodes.length > 1)
        throw new vr("Layer " + this.name + ' has multiple inbound nodes, hence the notion of "layer input" is ill-defined. Use `getInputAt(nodeIndex)` instead.');
      if (this.inboundNodes.length === 0)
        throw new vr("Layer " + this.name + " is not connected, no input to return.");
      return Vt(this.getNodeAtIndex(0, "input").inputTensors);
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "output", {get: function() {
      if (this.inboundNodes.length === 0)
        throw new vr("Layer " + this.name + " has no inbound nodes.");
      if (this.inboundNodes.length > 1)
        throw new vr("Layer " + this.name + ' has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use `getOutputAt(nodeIndex)` instead.');
      return Vt(this.getNodeAtIndex(0, "output").outputTensors);
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "losses", {get: function() {
      return this._losses;
    }, enumerable: true, configurable: true}), t.prototype.calculateLosses = function() {
      return this.losses.map(function(e) {
        return e();
      });
    }, Object.defineProperty(t.prototype, "updates", {get: function() {
      return this._updates;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "built", {get: function() {
      return this._built;
    }, set: function(e) {
      this._built = e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "trainable", {get: function() {
      return this.trainable_;
    }, set: function(e) {
      this._trainableWeights.forEach(function(r) {
        return r.trainable = e;
      }), this.trainable_ = e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "trainableWeights", {get: function() {
      return this.trainable_ ? this._trainableWeights.filter(function(e) {
        return e.trainable;
      }) : [];
    }, set: function(e) {
      this._trainableWeights = e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "nonTrainableWeights", {get: function() {
      return this.trainable ? this._trainableWeights.filter(function(e) {
        return !e.trainable;
      }).concat(this._nonTrainableWeights) : this._trainableWeights.concat(this._nonTrainableWeights);
    }, set: function(e) {
      this._nonTrainableWeights = e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "weights", {get: function() {
      return this.trainableWeights.concat(this.nonTrainableWeights);
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "stateful", {get: function() {
      return this._stateful;
    }, enumerable: true, configurable: true}), t.prototype.resetStates = function() {
      if (!this.stateful)
        throw new Error("Cannot call the resetStates() method of a non-stateful Layer object.");
    }, t.prototype.assertInputCompatibility = function(e) {
      if (e = nt(e), this.inputSpec == null || this.inputSpec.length === 0)
        return;
      var r = nt(this.inputSpec);
      if (e.length !== r.length)
        throw new M("Layer " + this.name + " expects " + r.length + " inputs, " + ("but it received " + e.length + " input tensors. ") + ("Input received: " + e));
      for (var i = 0; i < e.length; i++) {
        var a = e[i], s = r[i];
        if (s == null)
          continue;
        var o = a.rank;
        if (s.ndim != null && o !== s.ndim)
          throw new M("Input " + i + " is incompatible with layer " + this.name + ": " + ("expected ndim=" + s.ndim + ", found ndim=" + o));
        if (s.maxNDim != null && o > s.maxNDim)
          throw new M("Input " + i + " is incompatible with layer " + this.name + (": expected max_ndim=" + s.maxNDim + ", found ndim=" + o));
        if (s.minNDim != null && o < s.minNDim)
          throw new M("Input " + i + " is incompatible with layer " + this.name + (": expected min_ndim=" + s.minNDim + ", found ndim=" + o + "."));
        if (s.dtype != null && a.dtype !== s.dtype)
          throw new M("Input " + i + " is incompatible with layer " + this.name + " " + (": expected dtype=" + s.dtype + ", found dtype=" + a.dtype + "."));
        if (s.axes) {
          var c = a.shape;
          for (var l in s.axes) {
            var u = Number(l), h = s.axes[l], d = u >= 0 ? c[u] : c[c.length + u];
            if (h != null && [h, null].indexOf(d) === -1)
              throw new M("Input " + i + " is incompatible with layer " + (this.name + ": expected axis " + u + " of input shape to ") + ("have value " + h + " but got shape " + c + "."));
          }
        }
        if (s.shape != null)
          for (var p = 0; p < s.shape.length; ++p) {
            var f = s.shape[p], m = a.shape[p];
            if (f != null && m != null && f !== m)
              throw new M("Input " + i + " is incompatible with layer " + (this.name + ": expected shape=" + s.shape + ", ") + ("found shape=" + a.shape + "."));
          }
      }
    }, t.prototype.call = function(e, r) {
      return e;
    }, t.prototype.invokeCallHook = function(e, r) {
      this._callHook != null && this._callHook(e, r);
    }, t.prototype.setCallHook = function(e) {
      this._callHook = e;
    }, t.prototype.clearCallHook = function() {
      this._callHook = null;
    }, t.prototype.apply = function(e, r) {
      var i = this;
      r = r || {}, this.assertNotDisposed();
      for (var a = nt(e), s = true, o = 0, c = a; o < c.length; o++) {
        var l = c[o];
        if (!(l instanceof Ln)) {
          s = false;
          break;
        }
      }
      for (var u = true, h = 0, d = a; h < d.length; h++) {
        var l = d[h];
        if (l instanceof Ln) {
          u = false;
          break;
        }
      }
      if (s === u)
        throw new M("Arguments to apply() must be all SymbolicTensors or all Tensors");
      return ni(this.name, function() {
        if (!i.built) {
          i.assertInputCompatibility(e);
          for (var p = [], f = 0, m = nt(e); f < m.length; f++) {
            var g = m[f];
            p.push(g.shape);
          }
          i.build(Vt(p)), i.built = true, i.initialWeights && i.setWeights(i.initialWeights), i._refCount === null && u && (i._refCount = 1);
        }
        if (i.assertInputCompatibility(e), u) {
          for (var y = i.call(e, r), w = nt(y), b = [], L = 0, x = w; L < x.length; L++) {
            var N = x[L];
            a.indexOf(N) !== -1 && (N = N.clone()), b.push(N);
          }
          if (y = Vt(b), i.activityRegularizer != null)
            throw new Re("Layer invocation in the presence of activity regularizer(s) is not supported yet.");
          return y;
        } else {
          var I = LE(e), C = i.computeOutputShape(I), y = void 0, O = SE(e);
          if (i.warnOnIncompatibleInputShape(Array.isArray(e) ? I[0] : I), C != null && C.length > 0 && Array.isArray(C[0]) ? y = C.map(function(F, k) {
            return new Ln(O, F, i, nt(e), r, i.name, k);
          }) : y = new Ln(O, C, i, nt(e), r, i.name), i.addInboundNode(e, y, null, null, I, C, r), i._refCount++, i.activityRegularizer != null)
            throw new Re("Layer invocation in the presence of activity regularizer(s) is not supported yet.");
          return y;
        }
      });
    }, t.prototype.warnOnIncompatibleInputShape = function(e) {
      if (this.batchInputShape == null)
        return;
      if (e.length !== this.batchInputShape.length)
        console.warn("The rank of the input tensor provided (shape: " + (JSON.stringify(e) + ") does not match that of the ") + ("batchInputShape (" + JSON.stringify(this.batchInputShape) + ") ") + ("of the layer " + this.name));
      else {
        var r = false;
        this.batchInputShape.forEach(function(i, a) {
          i != null && e[a] != null && e[a] !== i && (r = true);
        }), r && console.warn("The shape of the input tensor " + ("(" + JSON.stringify(e) + ") does not ") + ("match the expectation of layer " + this.name + ": ") + ("" + JSON.stringify(this.batchInputShape)));
      }
    }, Object.defineProperty(t.prototype, "outputShape", {get: function() {
      if (this.inboundNodes == null || this.inboundNodes.length === 0)
        throw new vr("The layer " + this.name + " has never been called and thus has no defined output shape.");
      for (var e = [], r = 0, i = this.inboundNodes; r < i.length; r++) {
        var a = i[r], s = JSON.stringify(a.outputShapes);
        e.indexOf(s) === -1 && e.push(s);
      }
      if (e.length === 1) {
        var o = this.inboundNodes[0].outputShapes;
        return Array.isArray(o) && Array.isArray(o[0]) && o.length === 1 ? o[0] : o;
      } else
        throw new vr("The layer " + this.name + ' has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.');
    }, enumerable: true, configurable: true}), t.prototype.countParams = function() {
      if (!this.built)
        throw new Fn("You tried to call countParams() on " + this.name + ", but the layer is not built yet. Build it first by calling build(batchInputShape).");
      return Lo(this.weights);
    }, t.prototype.build = function(e) {
      this.built = true;
    }, t.prototype.getWeights = function(e) {
      return e === void 0 && (e = false), Ph(e ? this.trainableWeights : this.weights);
    }, t.prototype.setWeights = function(e) {
      var r = this;
      v.tidy(function() {
        var i = r.weights;
        if (i.length !== e.length)
          throw new M('You called setWeights(weights) on layer "' + r.name + '" ' + ("with a weight list of length " + e.length + ", ") + ("but the layer was expecting " + i.length + " weights. ") + ("Provided weights: " + e + "..."));
        if (i.length === 0)
          return;
        for (var a = [], s = Ph(i), o = 0; o < s.length; ++o) {
          var c = s[o], l = i[o], u = e[o];
          if (!v.util.arraysEqual(c.shape, u.shape))
            throw new M("Layer weight shape " + c.shape + " " + ("not compatible with provided weight shape " + u.shape));
          a.push([l, u]);
        }
        Mh(a);
      });
    }, t.prototype.addWeight = function(e, r, i, a, s, o, c) {
      if (this._addedWeightNames.indexOf(e) !== -1)
        throw new M("Duplicate weight name " + e + " for layer " + this.name);
      this._addedWeightNames.push(e), i == null && (i = "float32"), this.fastWeightInitDuringBuild && (a = at("zeros"));
      var l = a.apply(r, i), u = new Ny(l, i, e, o, c);
      return l.dispose(), s != null && this.addLoss(function() {
        return s.apply(u.read());
      }), o == null && (o = true), o ? this._trainableWeights.push(u) : this._nonTrainableWeights.push(u), u;
    }, t.prototype.setFastWeightInitDuringBuild = function(e) {
      this.fastWeightInitDuringBuild = e;
    }, t.prototype.addLoss = function(e) {
      var r;
      if (e == null || Array.isArray(e) && e.length === 0)
        return;
      e = nt(e), this._losses !== void 0 && this._losses !== null && (r = this.losses).push.apply(r, e);
    }, t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.computeMask = function(e, r) {
      var i = this;
      if (!this.supportsMasking) {
        if (r != null)
          if (Array.isArray(r))
            r.forEach(function(a) {
              if (a != null)
                throw new TypeError("Layer " + i.name + " does not support masking, but was passed an inputMask.");
            });
          else
            throw new TypeError("Layer " + this.name + " does not support masking, but was passed an inputMask.");
        return null;
      }
      return r;
    }, t.prototype.addInboundNode = function(e, r, i, a, s, o, c) {
      c === void 0 && (c = null);
      var l = nt(e);
      r = nt(r), i = nt(i), a = nt(a), s = xo(s), o = xo(o);
      for (var u = [], h = [], d = [], p = 0, f = l; p < f.length; p++) {
        var m = f[p];
        u.push(m.sourceLayer), h.push(m.nodeIndex), d.push(m.tensorIndex);
      }
      new So({outboundLayer: this, inboundLayers: u, nodeIndices: h, tensorIndices: d, inputTensors: l, outputTensors: r, inputMasks: i, outputMasks: a, inputShapes: s, outputShapes: o}, c);
      for (var g = 0; g < r.length; g++)
        r[g].sourceLayer = this, r[g].nodeIndex = this.inboundNodes.length - 1, r[g].tensorIndex = g;
    }, t.prototype.getConfig = function() {
      var e = {name: this.name, trainable: this.trainable};
      return this.batchInputShape != null && (e.batchInputShape = this.batchInputShape), this.dtype != null && (e.dtype = this.dtype), e;
    }, t.prototype.disposeWeights = function() {
      return this.weights.forEach(function(e) {
        return e.dispose();
      }), this.weights.length;
    }, t.prototype.assertNotDisposed = function() {
      if (this._refCount === 0)
        throw new Error("Layer '" + this.name + "' is already disposed.");
    }, t.prototype.dispose = function() {
      if (!this.built)
        throw new Error("Cannot dispose Layer " + this.name + " because it has not been built yet.");
      if (this._refCount === null)
        throw new Error("Cannot dispose Layer " + this.name + " because it has not been used yet.");
      this.assertNotDisposed();
      var e = 0;
      return --this._refCount === 0 && (e = this.disposeWeights()), {refCountAfterDispose: this._refCount, numDisposedVariables: e};
    }, t;
  }(v.serialization.Serializable);
  function LE(n) {
    n = nt(n);
    for (var t = [], e = 0, r = n; e < r.length; e++) {
      var i = r[e];
      t.push(i.shape);
    }
    return Vt(t);
  }
  function SE(n) {
    return "float32";
  }
  function _y(n, t, e) {
    if ((t == null || e != null && e > 0) && (t = n.sourceLayer, e = n.nodeIndex), t.inboundNodes.length === 0)
      return [n];
    var r = t.inboundNodes[e];
    if (r.inboundLayers.length === 0)
      return r.inputTensors;
    for (var i = [], a = 0; a < r.inboundLayers.length; a++)
      for (var s = r.inputTensors[a], o = r.inboundLayers[a], c = r.nodeIndices[a], l = _y(s, o, c), u = 0, h = l; u < h.length; u++) {
        var d = h[u];
        i.indexOf(d) === -1 && i.push(d);
      }
    return i;
  }
  var Va = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, {dtype: e.dtype, name: e.name != null ? e.name : bo("input").toString()}) || this;
      if (e.batchSize == null && (e.batchSize = null), e.sparse == null && (e.sparse = false), r.trainable = false, r.built = true, r.sparse = e.sparse, e.inputShape != null && e.batchInputShape != null)
        throw new M("Only provide the inputShape OR batchInputShape argument to inputLayer, not both at the same time.");
      var i = e.batchInputShape;
      if (i == null) {
        if (e.inputShape == null)
          throw new M("An InputLayer should be passed either a `batchInputShape` or an `inputShape`.");
        i = [e.batchSize].concat(e.inputShape);
      } else if (e.batchSize != null)
        throw new M("Cannot specify batchSize if batchInputShape is specified when creating an InputLayer.");
      var a = e.dtype || "float32";
      r.batchInputShape = i, r.dtype = a, r.inputSpec = [{shape: i}];
      var s = new Ln(r.dtype, r.batchInputShape, r, [], {}, r.name);
      return s.nodeIndex = 0, s.tensorIndex = 0, new So({outboundLayer: r, inboundLayers: [], nodeIndices: [], tensorIndices: [], inputTensors: [s], outputTensors: [s], inputMasks: [null], outputMasks: [null], inputShapes: [i], outputShapes: [i]}), r;
    }
    return t.prototype.apply = function(e, r) {
      throw new M("Cannot pass any input to an " + ("InputLayer's apply() method. InputLayer name: " + this.name));
    }, t.prototype.dispose = function() {
      return {refCountAfterDispose: this._refCount, numDisposedVariables: 0};
    }, t.prototype.getConfig = function() {
      return {batchInputShape: this.batchInputShape, dtype: this.dtype, sparse: this.sparse, name: this.name};
    }, t.className = "InputLayer", t;
  }(Fe);
  v.serialization.registerClass(Va);
  function Cy(n) {
    if (n.batchShape == null && n.shape == null)
      throw new Error("Please provide to Input either a `shape` or a `batchShape` argument. Note that `shape` does not include the batch dimension.");
    if (n.batchShape != null && n.shape != null)
      throw new M("Please provide either a `shape` or `batchShape` argument to Input, but not both.");
    var t = n.batchShape;
    n.shape != null && t == null && (t = [null].concat(n.shape));
    var e = n.dtype;
    e == null && (e = "float32");
    var r = new Va({batchInputShape: t, name: n.name, dtype: e, sparse: n.sparse}), i = r.inboundNodes[0].outputTensors;
    return i[0];
  }
  function Lr(n) {
    return Ae(this, void 0, void 0, function() {
      var t, e, r, i, a, s, o, c;
      return xe(this, function(l) {
        switch (l.label) {
          case 0:
            if (n == null)
              return [2];
            t = [], e = [], r = [];
            for (i in n)
              a = n[i], typeof a != "number" && (s = a, t.push(s.data()), e.push(i), r.push(s));
            return t.length > 0 ? [4, Promise.all(t)] : [3, 2];
          case 1:
            for (o = l.sent(), c = 0; c < o.length; ++c)
              n[e[c]] = o[c][0];
            v.dispose(r), l.label = 2;
          case 2:
            return [2];
        }
      });
    });
  }
  function Ry(n) {
    if (n == null)
      return;
    for (var t in n) {
      var e = n[t];
      typeof e != "number" && e.dispose();
    }
  }
  var Oy;
  (function(n) {
    n[n.SILENT = 0] = "SILENT", n[n.VERBOSE = 1] = "VERBOSE";
  })(Oy || (Oy = {}));
  var IE = 125, Gi = function() {
    function n() {
      this.validationData = null;
    }
    return n.prototype.setParams = function(t) {
      this.params = t;
    }, n.prototype.onEpochBegin = function(t, e) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(r) {
          return [2];
        });
      });
    }, n.prototype.onEpochEnd = function(t, e) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(r) {
          return [2];
        });
      });
    }, n.prototype.onBatchBegin = function(t, e) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(r) {
          return [2];
        });
      });
    }, n.prototype.onBatchEnd = function(t, e) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(r) {
          return [2];
        });
      });
    }, n.prototype.onTrainBegin = function(t) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(e) {
          return [2];
        });
      });
    }, n.prototype.onTrainEnd = function(t) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(e) {
          return [2];
        });
      });
    }, n.prototype.setModel = function(t) {
    }, n;
  }(), Ey = function() {
    function n(t, e) {
      e === void 0 && (e = 10), t == null && (t = []), this.callbacks = t, this.queueLength = e;
    }
    return n.prototype.append = function(t) {
      this.callbacks.push(t);
    }, n.prototype.setParams = function(t) {
      for (var e = 0, r = this.callbacks; e < r.length; e++) {
        var i = r[e];
        i.setParams(t);
      }
    }, n.prototype.setModel = function(t) {
      for (var e = 0, r = this.callbacks; e < r.length; e++) {
        var i = r[e];
        i.setModel(t);
      }
    }, n.prototype.onEpochBegin = function(t, e) {
      return Ae(this, void 0, void 0, function() {
        var r, i, a;
        return xe(this, function(s) {
          switch (s.label) {
            case 0:
              e == null && (e = {}), r = 0, i = this.callbacks, s.label = 1;
            case 1:
              return r < i.length ? (a = i[r], [4, a.onEpochBegin(t, e)]) : [3, 4];
            case 2:
              s.sent(), s.label = 3;
            case 3:
              return r++, [3, 1];
            case 4:
              return [2];
          }
        });
      });
    }, n.prototype.onEpochEnd = function(t, e) {
      return Ae(this, void 0, void 0, function() {
        var r, i, a;
        return xe(this, function(s) {
          switch (s.label) {
            case 0:
              e == null && (e = {}), r = 0, i = this.callbacks, s.label = 1;
            case 1:
              return r < i.length ? (a = i[r], [4, a.onEpochEnd(t, e)]) : [3, 4];
            case 2:
              s.sent(), s.label = 3;
            case 3:
              return r++, [3, 1];
            case 4:
              return [2];
          }
        });
      });
    }, n.prototype.onBatchBegin = function(t, e) {
      return Ae(this, void 0, void 0, function() {
        var r, i, a;
        return xe(this, function(s) {
          switch (s.label) {
            case 0:
              e == null && (e = {}), r = 0, i = this.callbacks, s.label = 1;
            case 1:
              return r < i.length ? (a = i[r], [4, a.onBatchBegin(t, e)]) : [3, 4];
            case 2:
              s.sent(), s.label = 3;
            case 3:
              return r++, [3, 1];
            case 4:
              return [2];
          }
        });
      });
    }, n.prototype.onBatchEnd = function(t, e) {
      return Ae(this, void 0, void 0, function() {
        var r, i, a;
        return xe(this, function(s) {
          switch (s.label) {
            case 0:
              e == null && (e = {}), r = 0, i = this.callbacks, s.label = 1;
            case 1:
              return r < i.length ? (a = i[r], [4, a.onBatchEnd(t, e)]) : [3, 4];
            case 2:
              s.sent(), s.label = 3;
            case 3:
              return r++, [3, 1];
            case 4:
              return [2];
          }
        });
      });
    }, n.prototype.onTrainBegin = function(t) {
      return Ae(this, void 0, void 0, function() {
        var e, r, i;
        return xe(this, function(a) {
          switch (a.label) {
            case 0:
              t == null && (t = {}), e = 0, r = this.callbacks, a.label = 1;
            case 1:
              return e < r.length ? (i = r[e], [4, i.onTrainBegin(t)]) : [3, 4];
            case 2:
              a.sent(), a.label = 3;
            case 3:
              return e++, [3, 1];
            case 4:
              return [2];
          }
        });
      });
    }, n.prototype.onTrainEnd = function(t) {
      return Ae(this, void 0, void 0, function() {
        var e, r, i;
        return xe(this, function(a) {
          switch (a.label) {
            case 0:
              t == null && (t = {}), e = 0, r = this.callbacks, a.label = 1;
            case 1:
              return e < r.length ? (i = r[e], [4, i.onTrainEnd(t)]) : [3, 4];
            case 2:
              a.sent(), a.label = 3;
            case 3:
              return e++, [3, 1];
            case 4:
              return [2];
          }
        });
      });
    }, n;
  }(), AE = function(n) {
    Q(t, n);
    function t() {
      return n.call(this) || this;
    }
    return t.prototype.onEpochBegin = function(e) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(r) {
          return this.seen = 0, this.totals = {}, [2];
        });
      });
    }, t.prototype.onBatchEnd = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        var i, a, s, o, c = this;
        return xe(this, function(l) {
          r == null && (r = {}), i = r.size == null ? 0 : r.size, this.seen += i, a = function(u) {
            var h = r[u];
            if (typeof h == "number")
              s.totals.hasOwnProperty(u) || (s.totals[u] = 0), s.totals[u] = s.totals[u] + h * i;
            else {
              var d = void 0;
              u in s.totals ? d = s.totals[u] : s.totals[u] = 0;
              var p = v.tidy(function() {
                return v.add(c.totals[u], v.mul(h, i));
              });
              s.totals[u] = p, d != null && d.dispose();
            }
          }, s = this;
          for (o in r)
            a(o);
          return [2];
        });
      });
    }, t.prototype.onEpochEnd = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        var i, a, s, o, c, l = this;
        return xe(this, function(u) {
          if (r != null)
            for (i = function(h) {
              if (a.totals[h] == null)
                return "continue";
              typeof a.totals[h] == "number" ? r[h] = a.totals[h] / a.seen : v.tidy(function() {
                var d = v.mul(v.div(1, l.seen), l.totals[h]);
                r[h] = d, l.totals[h].dispose(), v.keep(r[h]);
              });
            }, a = this, s = 0, o = this.params.metrics; s < o.length; s++)
              c = o[s], i(c);
          return [2];
        });
      });
    }, t;
  }(Gi), Dy = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.onTrainBegin = function(e) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(r) {
          return this.epoch = [], this.history = {}, [2];
        });
      });
    }, t.prototype.onEpochEnd = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        var i;
        return xe(this, function(a) {
          r == null && (r = {}), this.epoch.push(e);
          for (i in r)
            this.history[i] == null && (this.history[i] = []), this.history[i].push(r[i]);
          return [2];
        });
      });
    }, t.prototype.syncData = function() {
      return Ae(this, void 0, void 0, function() {
        var e, r, i, a, s, o, c, l, u, h;
        return xe(this, function(d) {
          switch (d.label) {
            case 0:
              e = [], r = [], i = [];
              for (a in this.history)
                for (s = this.history[a], o = 0; o < s.length; ++o)
                  typeof s[o] != "number" && (c = s[o], e.push(c.data()), r.push(a), i.push(o));
              return [4, Promise.all(e)];
            case 1:
              for (l = d.sent(), u = 0; u < l.length; ++u)
                h = this.history[r[u]][i[u]], h.dispose(), this.history[r[u]][i[u]] = l[u][0];
              return [2];
          }
        });
      });
    }, t;
  }(Gi), ky = function(n) {
    Q(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      if (i.currentEpoch = 0, i.yieldEvery = r || "auto", i.yieldEvery === "auto" && (i.yieldEvery = IE), i.yieldEvery === "never" && e.onYield != null)
        throw new Error("yieldEvery is `never` but you provided an `onYield` callback. Either change `yieldEvery` or remove the callback");
      return v.util.isNumber(i.yieldEvery) && (i.maybeWait = EO(i.maybeWait.bind(i), i.yieldEvery)), i.trainBegin = e.onTrainBegin, i.trainEnd = e.onTrainEnd, i.epochBegin = e.onEpochBegin, i.epochEnd = e.onEpochEnd, i.batchBegin = e.onBatchBegin, i.batchEnd = e.onBatchEnd, i.yield = e.onYield, i;
    }
    return t.prototype.maybeWait = function(e, r, i) {
      return Ae(this, void 0, void 0, function() {
        var a;
        return xe(this, function(s) {
          switch (s.label) {
            case 0:
              return a = [], this.yield != null ? [4, Lr(i)] : [3, 2];
            case 1:
              s.sent(), a.push(this.yield(e, r, i)), s.label = 2;
            case 2:
              return a.push(v.nextFrame()), [4, Promise.all(a)];
            case 3:
              return s.sent(), [2];
          }
        });
      });
    }, t.prototype.onEpochBegin = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(i) {
          switch (i.label) {
            case 0:
              return this.currentEpoch = e, this.epochBegin != null ? [4, Lr(r)] : [3, 3];
            case 1:
              return i.sent(), [4, this.epochBegin(e, r)];
            case 2:
              i.sent(), i.label = 3;
            case 3:
              return [2];
          }
        });
      });
    }, t.prototype.onEpochEnd = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        var i;
        return xe(this, function(a) {
          switch (a.label) {
            case 0:
              return i = [], this.epochEnd != null ? [4, Lr(r)] : [3, 2];
            case 1:
              a.sent(), i.push(this.epochEnd(e, r)), a.label = 2;
            case 2:
              return this.yieldEvery === "epoch" && i.push(v.nextFrame()), [4, Promise.all(i)];
            case 3:
              return a.sent(), [2];
          }
        });
      });
    }, t.prototype.onBatchBegin = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(i) {
          switch (i.label) {
            case 0:
              return this.batchBegin != null ? [4, Lr(r)] : [3, 3];
            case 1:
              return i.sent(), [4, this.batchBegin(e, r)];
            case 2:
              i.sent(), i.label = 3;
            case 3:
              return [2];
          }
        });
      });
    }, t.prototype.onBatchEnd = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        var i;
        return xe(this, function(a) {
          switch (a.label) {
            case 0:
              return i = [], this.batchEnd != null ? [4, Lr(r)] : [3, 2];
            case 1:
              a.sent(), i.push(this.batchEnd(e, r)), a.label = 2;
            case 2:
              return this.yieldEvery === "batch" ? i.push(v.nextFrame()) : v.util.isNumber(this.yieldEvery) && i.push(this.maybeWait(this.currentEpoch, e, r)), [4, Promise.all(i)];
            case 3:
              return a.sent(), [2];
          }
        });
      });
    }, t.prototype.onTrainBegin = function(e) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(r) {
          switch (r.label) {
            case 0:
              return this.trainBegin != null ? [4, Lr(e)] : [3, 3];
            case 1:
              return r.sent(), [4, this.trainBegin(e)];
            case 2:
              r.sent(), r.label = 3;
            case 3:
              return [2];
          }
        });
      });
    }, t.prototype.onTrainEnd = function(e) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(r) {
          switch (r.label) {
            case 0:
              return this.trainEnd != null ? [4, Lr(e)] : [3, 3];
            case 1:
              return r.sent(), [4, this.trainEnd(e)];
            case 2:
              r.sent(), r.label = 3;
            case 3:
              return [2];
          }
        });
      });
    }, t;
  }(Gi);
  function Fy(n, t) {
    if (n == null && (n = {}), n instanceof Gi)
      return [n];
    if (Array.isArray(n) && n[0] instanceof Gi)
      return n;
    var e = nt(n);
    return e.map(function(r) {
      return new ky(r, t);
    });
  }
  var Wy = function() {
    function n() {
    }
    return n.registerCallbackConstructor = function(t, e) {
      v.util.assert(t >= 0 && Number.isInteger(t), function() {
        return "Verbosity level is expected to be an integer >= 0, " + ("but got " + t);
      }), n.checkForDuplicate(e), n.constructors[t] == null && (n.constructors[t] = []), n.constructors[t].push(e);
    }, n.checkForDuplicate = function(t) {
      for (var e in n.constructors) {
        var r = n.constructors[+e];
        r.forEach(function(i) {
          if (i === t)
            throw new M("Duplicate callback constructor.");
        });
      }
    }, n.clear = function() {
      n.constructors = {};
    }, n.createCallbacks = function(t) {
      var e = [];
      for (var r in n.constructors) {
        var i = +r;
        t >= i && e.push.apply(e, n.constructors[i]);
      }
      return e.map(function(a) {
        return new a();
      });
    }, n.constructors = {}, n;
  }();
  function Uy(n, t, e, r, i, a, s, o, c) {
    var l = new Dy(), u = [new AE()].concat(Wy.createCallbacks(t));
    n != null && u.push.apply(u, n), u.push(l);
    var h = new Ey(u);
    return h.setParams({epochs: e, initialEpoch: r, samples: i, steps: a, batchSize: s, verbose: t, doValidation: o, metrics: c}), {callbackList: h, history: l};
  }
  function Sn(n, t, e) {
    return t === void 0 && (t = {}), e === void 0 && (e = false), Wa(n, v.serialization.SerializationMap.getMap().classNameMap, t, "layer", e);
  }
  function Io(n, t) {
    return v.tidy(function() {
      n.dtype !== "float32" && (n = n.asType("float32"));
      var e = v.sum(Ma(n), t, true), r = v.fill(e.shape, St()), i = v.sqrt(v.maximum(e, r));
      return v.div(n, i);
    });
  }
  function ii(n, t) {
    return v.tidy(function() {
      return v.mean(Ma(v.sub(t, n)), -1);
    });
  }
  function Ao(n, t) {
    return v.tidy(function() {
      return v.mean(v.abs(v.sub(t, n)), -1);
    });
  }
  function qi(n, t) {
    return v.tidy(function() {
      var e = v.sub(n, t), r = v.clipByValue(v.abs(n), St(), Number.MAX_VALUE), i = v.abs(v.div(e, r));
      return v.mul(100, v.mean(i, -1));
    });
  }
  function TE(n, t) {
    return v.tidy(function() {
      var e = v.clipByValue(t, St(), Number.MAX_VALUE), r = v.log(v.add(1, e)), i = v.clipByValue(n, St(), Number.MAX_VALUE), a = v.log(v.add(1, i));
      return v.mean(Ma(v.sub(r, a)), -1);
    });
  }
  function NE(n, t) {
    return v.tidy(function() {
      var e = v.maximum(0, v.sub(1, v.mul(n, t)));
      return v.mean(Ma(e), -1);
    });
  }
  function _E(n, t) {
    return v.tidy(function() {
      var e = v.maximum(0, v.sub(1, v.mul(n, t)));
      return v.mean(e, -1);
    });
  }
  function CE(n, t) {
    return v.tidy(function() {
      var e = v.sum(v.mul(n, t), -1), r = v.max(v.mul(v.sub(1, n), t), -1);
      return v.maximum(0, v.add(1, v.sub(r, e)));
    });
  }
  function RE(n, t) {
    return v.tidy(function() {
      var e = Math.log(2), r = v.sub(t, n), i = v.sub(v.add(r, v.softplus(v.mul(-2, r))), e);
      return v.mean(i, -1);
    });
  }
  function Ga(n, t, e) {
    return e === void 0 && (e = false), v.tidy(function() {
      if (e)
        t = v.softmax(t);
      else {
        var r = v.sum(t, t.shape.length - 1, true);
        t = v.div(t, r);
      }
      return t = v.clipByValue(t, St(), 1 - St()), v.neg(v.sum(v.mul(n.toFloat(), v.log(t)), t.shape.length - 1));
    });
  }
  function To(n, t, e) {
    return e === void 0 && (e = false), v.tidy(function() {
      var r = v.floor(YO(n)).toInt();
      t = v.clipByValue(t, St(), 1 - St());
      var i = t.shape, a = v.oneHot(r, i[i.length - 1]).reshape(i);
      return Ga(a, t, e);
    });
  }
  function OE(n, t) {
    if (!v.util.arraysEqual(n.shape, t.shape))
      throw new M("logits and labels must have the same shape, but got shapes " + (JSON.stringify(n.shape) + " and " + JSON.stringify(t.shape)));
    return v.tidy(function() {
      var e = t.relu(), r = t.abs().neg();
      return e.sub(t.mul(n)).add(r.exp().log1p());
    });
  }
  function No(n, t) {
    return v.tidy(function() {
      var e;
      return e = v.clipByValue(t, St(), 1 - St()), e = v.log(v.div(e, v.sub(1, e))), v.mean(OE(n, e), -1);
    });
  }
  function EE(n, t) {
    return v.tidy(function() {
      var e = v.clipByValue(n, St(), 1), r = v.clipByValue(t, St(), 1);
      return v.sum(v.mul(n, v.log(v.div(e, r))), -1);
    });
  }
  function DE(n, t) {
    return v.tidy(function() {
      var e = v.log(v.add(St(), t));
      return v.mean(v.sub(t, v.mul(n, e)), -1);
    });
  }
  function Hh(n, t) {
    return v.tidy(function() {
      var e = Io(n, -1), r = Io(t, -1), i = v.mul(e, r);
      return v.neg(v.sum(i, -1));
    });
  }
  var _o = {meanSquaredError: ii, meanAbsoluteError: Ao, meanAbsolutePercentageError: qi, meanSquaredLogarithmicError: TE, squaredHinge: NE, hinge: _E, categoricalHinge: CE, logcosh: RE, categoricalCrossentropy: Ga, sparseCategoricalCrossentropy: To, binaryCrossentropy: No, kullbackLeiblerDivergence: EE, poisson: DE, cosineProximity: Hh};
  function Vh(n) {
    if (typeof n == "string") {
      if (n in _o)
        return _o[n];
      var t = "Unknown loss " + n;
      throw n.toLowerCase().includes("softmaxcrossentropy") && (t = "Unknown loss " + n + '. Use "categoricalCrossentropy" as the string name for tf.losses.softmaxCrossEntropy'), new M(t);
    } else
      return n;
  }
  function Gh(n, t) {
    return v.tidy(function() {
      var e = v.mul(0.5, v.onesLike(t)), r = za(v.greater(t, e), n.dtype);
      return v.mean(v.equal(n, r), -1);
    });
  }
  function qh(n, t) {
    return v.tidy(function() {
      return za(v.equal(v.argMax(n, -1), v.argMax(t, -1)), "float32");
    });
  }
  function By(n, t) {
    return v.tidy(function() {
      return v.logicalAnd(n.equal(1), t.equal(1)).sum().cast("float32");
    });
  }
  function kE(n, t) {
    return v.tidy(function() {
      return v.logicalAnd(n.equal(1), t.equal(0)).sum().cast("float32");
    });
  }
  function FE(n, t) {
    return v.tidy(function() {
      return v.logicalAnd(n.equal(0), t.equal(1)).sum().cast("float32");
    });
  }
  function zy(n, t) {
    return v.tidy(function() {
      var e = By(n, t), r = FE(n, t), i = e.add(r);
      return v.where(v.greater(i, 0), e.div(i), 0).cast("float32");
    });
  }
  function WE(n, t) {
    return v.tidy(function() {
      var e = By(n, t), r = kE(n, t), i = e.add(r);
      return v.where(v.greater(i, 0), e.div(i), 0).cast("float32");
    });
  }
  function Py(n, t) {
    return No(n, t);
  }
  function My(n, t) {
    return n.rank === t.rank && (n = n.squeeze([n.rank - 1])), t = t.argMax(-1), t.dtype !== n.dtype && (t = t.asType(n.dtype)), v.equal(n, t).asType("float32");
  }
  var UE = ii, BE = ii, zE = Ao, PE = Ao, ME = qi, HE = qi, Yh = Ga, VE = Hh, Hy = To, Co = {binaryAccuracy: Gh, categoricalAccuracy: qh, precision: zy, categoricalCrossentropy: Yh, sparseCategoricalCrossentropy: Hy, mse: UE, MSE: BE, mae: zE, MAE: PE, mape: ME, MAPE: HE, cosine: VE};
  function GE(n) {
    if (typeof n == "string" && n in Co)
      return Co[n];
    if (typeof n != "string" && n != null)
      return n;
    throw new M("Unknown metric " + n);
  }
  function Ro(n) {
    if (Wn(n !== null, "Unknown LossOrMetricFn " + n), typeof n == "string")
      return n;
    for (var t = void 0, e = 0, r = Object.keys(_o); e < r.length; e++) {
      var i = r[e];
      if (_o[i] === n) {
        t = i;
        break;
      }
    }
    if (t !== void 0)
      return t;
    for (var a = 0, s = Object.keys(Co); a < s.length; a++) {
      var i = s[a];
      if (Co[i] === n) {
        t = i;
        break;
      }
    }
    return t !== void 0 ? t : n.name;
  }
  function qE(n) {
    var t = {Adagrad: function() {
      return v.train.adagrad(0.01);
    }, Adadelta: function() {
      return v.train.adadelta(1, 0.95, St());
    }, Adam: function() {
      return v.train.adam(1e-3, 0.9, 0.999, St());
    }, Adamax: function() {
      return v.train.adamax(2e-3, 0.9, 0.999, St(), 0);
    }, RMSProp: function() {
      return v.train.rmsprop(1e-3, 0.9, 0, St());
    }, SGD: function() {
      return v.train.sgd(0.01);
    }};
    if (t.adagrad = t.Adagrad, t.adadelta = t.Adadelta, t.adam = t.Adam, t.adamax = t.Adamax, t.rmsprop = t.RMSProp, t.sgd = t.SGD, n in t)
      return t[n]();
    throw new M("Unknown Optimizer " + n);
  }
  var Vy = 1 * 1024 * 1024;
  function Gy(n, t, e) {
    if (e === void 0 && (e = false), n == null || typeof n != "object" || Object.getPrototypeOf(n) !== Object.prototype || !Kh(n))
      throw new Error("User-defined metadata is expected to be a JSON object, but is not.");
    if (e) {
      var r = JSON.stringify(n);
      r.length > Vy && console.warn('User-defined metadata of model "' + t + '" is too large in ' + ("size (length=" + r.length + " when serialized). It is not ") + "recommended to store such large objects in user-defined metadata. Please make sure its serialized length is <= " + (Vy + "."));
    }
  }
  function Kh(n) {
    if (n === null)
      return true;
    if (typeof n == "object")
      if (Object.getPrototypeOf(n) === Object.prototype) {
        for (var t = Object.keys(n), e = 0, r = t; e < r.length; e++) {
          var i = r[e];
          if (typeof i != "string")
            return false;
          if (!Kh(n[i]))
            return false;
        }
        return true;
      } else if (Array.isArray(n)) {
        for (var a = 0, s = n; a < s.length; a++) {
          var o = s[a];
          if (!Kh(o))
            return false;
        }
        return true;
      } else
        return false;
    else {
      var c = typeof n;
      return c === "string" || c === "number" || c === "boolean";
    }
  }
  function XE(n, t, e, r) {
    r === void 0 && (r = console.log);
    var i = KE(n), a = ["Layer (type)", "Output shape", "Param #"];
    i ? (t = t || 65, e = e || [0.45, 0.85, 1]) : (t = t || 98, e = e || [0.33, 0.55, 0.67, 1]), e[e.length - 1] <= 1 && (e = e.map(function(d) {
      return Math.floor(t * d);
    }));
    var s;
    if (!i) {
      a.push("Receives inputs"), s = [];
      for (var o in n.nodesByDepth)
        s.push.apply(s, n.nodesByDepth[o]);
    }
    r("_".repeat(t)), Oo(a, e, r), r("=".repeat(t));
    for (var c = n.layers, l = 0; l < c.length; ++l)
      i ? jE(c[l], e, r) : $E(c[l], e, s, r), r((l === c.length - 1 ? "=" : "_").repeat(t));
    n.checkTrainableWeightsConsistency();
    var u = YE(n), h = Lo(n.nonTrainableWeights);
    r("Total params: " + (u + h)), r("Trainable params: " + u), r("Non-trainable params: " + h), r("_".repeat(t));
  }
  function YE(n) {
    var t;
    return n.collectedTrainableWeights != null ? t = Lo(n.collectedTrainableWeights) : t = Lo(n.trainableWeights), t;
  }
  function KE(n) {
    var t = true, e = [], r = [];
    for (var i in n.nodesByDepth)
      e.push(n.nodesByDepth[i]);
    for (var a = 0, s = e; a < s.length; a++) {
      var o = s[a];
      if (o.length > 1 || o.length === 1 && o[0].inboundLayers.length > 1) {
        t = false;
        break;
      }
      r.push.apply(r, o);
    }
    if (t)
      for (var c = 0, l = n.layers; c < l.length; c++) {
        for (var u = l[c], h = false, d = 0, p = u.inboundNodes; d < p.length; d++) {
          var f = p[d];
          if (r.indexOf(f) !== -1)
            if (h) {
              t = false;
              break;
            } else
              h = true;
        }
        if (!t)
          break;
      }
    return t;
  }
  function Oo(n, t, e) {
    e === void 0 && (e = console.log);
    for (var r = "", i = 0; i < n.length; ++i)
      i > 0 && (r = r.slice(0, r.length - 1) + " "), r += n[i], r = r.slice(0, t[i]), r += " ".repeat(t[i] - r.length);
    e(r);
  }
  function jE(n, t, e) {
    var r;
    try {
      r = JSON.stringify(n.outputShape);
    } catch (o) {
      r = "multiple";
    }
    var i = n.name, a = n.getClassName(), s = [i + " (" + a + ")", r, n.countParams().toString()];
    Oo(s, t, e);
  }
  function $E(n, t, e, r) {
    var i;
    try {
      i = JSON.stringify(n.outputShape);
    } catch (y) {
      i = "multiple";
    }
    for (var a = [], s = 0, o = n.inboundNodes; s < o.length; s++) {
      var c = o[s];
      if (e != null && e.length > 0 && e.indexOf(c) === -1)
        continue;
      for (var l = 0; l < c.inboundLayers.length; ++l) {
        var u = c.inboundLayers[l].name, h = c.nodeIndices[l], d = c.tensorIndices[l];
        a.push(u + "[" + h + "][" + d + "]");
      }
    }
    var p = n.name, f = n.getClassName(), m = a.length === 0 ? "" : a[0], g = [p + " (" + f + ")", i, n.countParams().toString(), m];
    Oo(g, t, r);
    for (var l = 1; l < a.length; ++l)
      Oo(["", "", "", a[l]], t, r);
  }
  function qy(n, t, e) {
    return (n === "inboundNodes" || n === "outputLayers" || n === "inputLayers") && t === 0 && typeof e == "string";
  }
  function qa(n, t) {
    if (n === null)
      return null;
    if (typeof n == "string")
      return ti(n);
    if (typeof n == "number" || typeof n == "boolean")
      return n;
    if (n instanceof Array) {
      for (var e = [], r = n.length, i = 0; i < r; ++i) {
        var a = n[i];
        qy(t, i, a) ? e.push(a) : e.push(qa(a, t));
      }
      return e;
    } else {
      for (var s = {}, o = 0, c = Object.keys(n); o < c.length; o++) {
        var l = c[o], u = n[l];
        if (l === "name" && typeof u == "string")
          s[l] = u;
        else {
          var h = ti(l);
          s[h] = qa(u, h);
        }
      }
      return s;
    }
  }
  function jh(n, t) {
    if (n == null)
      return null;
    if (typeof n == "string")
      return Zn(n);
    if (typeof n == "number" || typeof n == "boolean")
      return n;
    if (n instanceof Array) {
      for (var e = [], r = n.length, i = 0; i < r; ++i) {
        var a = n[i];
        qy(t, i, a) ? e.push(a) : e.push(jh(a, t));
      }
      return e;
    } else {
      for (var s = {}, o = 0, c = Object.keys(n); o < c.length; o++) {
        var l = c[o], u = n[l], h = Zn(l);
        (l === "name" || l === "className") && typeof u == "string" ? s[h] = u : s[h] = jh(u, l);
      }
      return s;
    }
  }
  var $h = "2.7.0";
  function JE(n, t) {
    if (n.dtype == null || n.dtype === t.dtype)
      return t;
    try {
      return v.cast(t, n.dtype);
    } catch (e) {
      throw new M("The dtype of the feed (" + t.dtype + ") can not be cast to the dtype " + ("of the key '" + n.name + "' (" + n.dtype + ")."));
    }
  }
  var Yi = function() {
    function n(t) {
      if (this.id2Value = {}, this.id2Mask = {}, this.name2Id = {}, t instanceof n)
        for (var e in t.id2Value)
          this.id2Value[e] = t.id2Value[e], e in t.id2Mask && (this.id2Mask[e] = t.id2Mask[e]);
      else {
        if (t == null)
          return;
        for (var r = 0, i = t; r < i.length; r++) {
          var a = i[r];
          this.add(a.key, a.value);
        }
      }
    }
    return n.prototype.add = function(t, e, r) {
      if (this.id2Value[t.id] == null)
        this.id2Value[t.id] = JE(t, e), this.name2Id[t.name] = t.id, r != null && (this.id2Mask[t.id] = r);
      else
        throw new M("Duplicate key: name=" + t.name + ", id=" + t.id);
      return this;
    }, n.prototype.addFeed = function(t) {
      this.add(t.key, t.value);
    }, n.prototype.hasKey = function(t) {
      return this.id2Value[t.id] != null;
    }, n.prototype.names = function() {
      return Object.keys(this.name2Id);
    }, n.prototype.getValue = function(t) {
      if (t instanceof Ln) {
        if (this.id2Value[t.id] == null)
          throw new M("Nonexistent key: " + t.name);
        return this.id2Value[t.id];
      } else {
        var e = this.name2Id[t];
        if (e == null)
          throw new M("Feed dict has no SymbolicTensor name: " + t);
        return this.id2Value[e];
      }
    }, n.prototype.getMask = function(t) {
      if (t instanceof Ln) {
        if (this.id2Value[t.id] == null)
          throw new M("Nonexistent key: " + t.name);
        return this.id2Mask[t.id];
      } else {
        var e = this.name2Id[t];
        if (e == null)
          throw new M("Feed dict has no SymbolicTensor name: " + t);
        return this.id2Mask[e];
      }
    }, n.prototype.disposeMasks = function() {
      this.id2Mask != null && v.dispose(this.id2Mask);
    }, n;
  }(), Xh = {}, Yy = {};
  function Ya(n, t, e, r) {
    for (var i = e == null ? false : e.training, a = Array.isArray(n), s = a ? n : [n], o = s.map(function($) {
      return $.name;
    }), c = [], l = t.names(), u = 0, h = o; u < h.length; u++) {
      var d = h[u];
      l.indexOf(d) !== -1 ? c.push(t.getValue(d)) : c.push(null);
    }
    r != null && (r.maxNumTensors = -Infinity, r.minNumTensors = Infinity);
    var p = o.join(",") + "|" + t.names().join(","), f, m;
    if (Xh[p] == null) {
      var g = ZE(s, t);
      f = g.sorted, m = g.recipientCounts, Xh[p] = f, Yy[p] = m;
    }
    f = Xh[p], m = {}, i || Object.assign(m, Yy[p]);
    for (var y = new Yi(t), w = 0; w < f.length; ++w) {
      if (r != null) {
        var b = v.memory().numTensors;
        b > r.maxNumTensors && (r.maxNumTensors = b), b < r.minNumTensors && (r.minNumTensors = b);
      }
      var L = f[w], x = L.sourceLayer;
      if (x instanceof Va)
        continue;
      for (var N = [], I = [], C = [], O = false, D = 0, F = L.inputs; D < F.length; D++) {
        var k = F[D], B = y.getValue(k), V = y.getMask(k);
        N.push(B), I.push(V), V != null && (O = true), i || (m[k.name]--, m[k.name] === 0 && !t.hasKey(k) && o.indexOf(k.name) === -1 && !B.isDisposed && k.sourceLayer.stateful !== true && C.push(B));
      }
      O && (e = e || {}, e.mask = I[0]);
      var P = nt(x.apply(N, e)), G = null;
      x.supportsMasking && (G = x.computeMask(N, I));
      for (var j = QE(L), q = Array.isArray(j) ? j : [j], H = 0; H < q.length; ++H) {
        y.hasKey(q[H]) || y.add(q[H], P[H], Array.isArray(G) ? G[0] : G);
        var J = o.indexOf(q[H].name);
        J !== -1 && (c[J] = P[H]);
      }
      i || v.dispose(C);
    }
    return y.disposeMasks(), a ? c : c[0];
  }
  function ZE(n, t) {
    v.util.assert(n != null && n.length > 0, function() {
      return "Expected at least one fetch, got none";
    });
    var e = [], r = {};
    if (n.length === 1) {
      var i = Ky(n[0], t);
      e = i.sorted, r = i.recipientMap;
    } else
      for (var a = new Set(), s = 0, o = n; s < o.length; s++) {
        for (var c = o[s], l = Ky(c, t), u = l.sorted, h = l.recipientMap, d = 0, p = u; d < p.length; d++) {
          var f = p[d];
          a.has(f.name) || (e.push(f), a.add(f.name));
        }
        var m = function(y) {
          r[y] == null && (r[y] = new Set()), h[y].forEach(function(w) {
            return r[y].add(w);
          });
        };
        for (var g in h)
          m(g);
      }
    return {sorted: e, recipientCounts: e7(r)};
  }
  function e7(n) {
    var t = {};
    for (var e in n)
      t[e] = n[e].size;
    return t;
  }
  function Ky(n, t) {
    for (var e = new Set(), r = [], i = {}, a = 0, s = t.names(); a < s.length; a++) {
      var o = s[a];
      e.add(o);
    }
    var c = [], l = [];
    for (c.push(n); c.length > 0; ) {
      var u = c[c.length - 1];
      if (e.has(u.name)) {
        c.pop();
        continue;
      }
      var h = l[l.length - 1] === c.length - 1;
      if (u.inputs.length === 0 || h)
        c.pop(), r.push(u), e.add(u.name), h && l.pop();
      else {
        l.push(c.length - 1);
        for (var d = 0, p = u.inputs; d < p.length; d++) {
          var f = p[d];
          if (i[f.name] == null && (i[f.name] = new Set()), i[f.name].add(u.name), e.has(f.name))
            continue;
          c.push(f);
        }
      }
    }
    return {sorted: r, recipientMap: i};
  }
  function QE(n) {
    var t;
    if (n.sourceLayer.inboundNodes.length === 1)
      t = n.sourceLayer.output;
    else {
      for (var e = null, r = 0; r < n.sourceLayer.inboundNodes.length; ++r)
        for (var i = 0, a = n.sourceLayer.inboundNodes[r].outputTensors; i < a.length; i++) {
          var s = a[i];
          if (s.id === n.id) {
            e = r;
            break;
          }
        }
      t = n.sourceLayer.getOutputAt(e);
    }
    return t;
  }
  var t7 = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, {}) || this;
      if (r.containerNodes = new Set(), r.name = e.name, r.name == null) {
        var i = r.getClassName().toLowerCase();
        r.name = bo(i);
      }
      if (r.supportsMasking = false, r.trainable_ = true, Array.isArray(e.inputs) ? r.inputs = e.inputs.slice() : r.inputs = [e.inputs], Array.isArray(e.outputs) ? r.outputs = e.outputs.slice() : r.outputs = [e.outputs], wr(r.inputs).length !== r.inputs.length)
        throw new M("The list of inputs passed to the model is redundant. All inputs should only appear once. Found: " + ("" + r.inputs.map(function(Te) {
          return Te.name;
        })));
      wr(r.outputs).length !== r.outputs.length && console.warn("The list of outputs passed to the model is redundant. All outputs should only appear once. Found: " + ("" + r.outputs.map(function(Te) {
        return Te.name;
      }))), r.inputLayers = [], r.inputLayersNodeIndices = [], r.inputLayersTensorIndices = [], r.outputLayers = [], r.outputLayersNodeIndices = [], r.outputLayersTensorIndices = [], r.layers = [], r.internalContainerRefs = [];
      for (var a = 0, s = r.outputs; a < s.length; a++) {
        var o = s[a], c = o.sourceLayer, l = o.nodeIndex, u = o.tensorIndex;
        r.outputLayers.push(c), r.outputLayersNodeIndices.push(l), r.outputLayersTensorIndices.push(u);
      }
      for (var h = 0, d = r.inputs; h < d.length; h++) {
        var o = d[h], c = o.sourceLayer, l = o.nodeIndex, u = o.tensorIndex;
        Wn(l === 0, "input layer has >1 nodes"), Wn(u === 0, "input layer has >1 tensors"), r.inputLayers.push(c), r.inputLayersNodeIndices.push(l), r.inputLayersTensorIndices.push(u);
      }
      r.inputNames = [], r.outputNames = [], r.feedInputShapes = [], r.feedInputNames = [], r.feedOutputNames = [];
      for (var p = 0; p < r.inputLayers.length; p++) {
        var c = r.inputLayers[p];
        if (!(c instanceof Va))
          throw new TypeError("Input layers to a LayersModel must be InputLayer objects. " + ("Received inputs: " + e.inputs + ". ") + ("Input " + p + " (0-based) originates ") + ("from layer type " + c.getClassName() + "."));
        r.inputNames.push(c.name), r.feedInputShapes.push(c.batchInputShape), r.feedInputNames.push(c.name);
      }
      for (var f = 0, m = r.outputLayers; f < m.length; f++) {
        var c = m[f];
        r.outputNames.push(c.name);
      }
      r.internalInputShapes = r.inputs.map(function(Te) {
        return Te.shape;
      }), r.internalOutputShapes = r.outputs.map(function(Te) {
        return Te.shape;
      });
      for (var g = {}, y = {}, w = {}, b = {}, L = {}, x = [], N = function(Te, dt, mt, Ve, Kt, Gn) {
        (Ve == null || Kt == null || Gn == null) && (Ve = Te.sourceLayer, Kt = Te.nodeIndex, Gn = Te.tensorIndex);
        var kt = Ve.inboundNodes[Kt];
        if (mt.indexOf(kt) !== -1)
          throw new Fn("The tensor " + Te.name + ' at layer "' + Ve.name + '" is part of a cycle.');
        if (dt.indexOf(kt) !== -1)
          return;
        r.containerNodes.add(t.nodeKey(Ve, Kt)), Ve.id in L || (L[Ve.id] = Object.keys(L).length), mt.indexOf(kt) === -1 && mt.push(kt);
        for (var ma = kt.inboundLayers.length, sr = 0; sr < ma; sr++) {
          var wi = kt.inputTensors[sr], fc = kt.inboundLayers[sr], mc = kt.nodeIndices[sr], hL = kt.tensorIndices[sr];
          N(wi, dt, mt, fc, mc, hL);
        }
        for (dt.push(kt); mt.indexOf(kt) >= 0; )
          mt.splice(mt.indexOf(kt), 1);
        x.push(kt);
      }, I = [], C = [], O = 0, D = r.outputs; O < D.length; O++) {
        var o = D[O];
        N(o, I, C);
      }
      for (var F = x.slice().reverse(), k = 0, B = F; k < B.length; k++) {
        var V = B[k];
        y[V.id] = V, V.id in g || (g[V.id] = 0);
        var P = g[V.id], G = w[V.outboundLayer.id] == null ? 0 : w[V.outboundLayer.id];
        P = Math.max(P, G), w[V.outboundLayer.id] = P, b[V.outboundLayer.id] = V.outboundLayer, g[V.id] = P;
        for (var p = 0; p < V.inboundLayers.length; p++) {
          var j = V.inboundLayers[p], l = V.nodeIndices[p], q = j.inboundNodes[l], H = g[q.id] == null ? 0 : g[q.id];
          g[q.id] = Math.max(P + 1, H), y[q.id] = q;
        }
      }
      var J = {};
      for (var $ in g) {
        var P = g[$];
        P in J || (J[P] = []), J[P].push(y[$]);
      }
      var ee = {};
      for (var te in w) {
        var P = w[te];
        P in ee || (ee[P] = []), ee[P].push(b[te]);
      }
      var ne = Object.keys(ee).map(function(Te) {
        return parseInt(Te, 10);
      }).sort(go);
      r.layers = [];
      for (var re = 0, ie = ne; re < ie.length; re++) {
        var P = ie[re], oe = ee[P];
        oe.sort(function(dt, mt) {
          var Ve = L[dt.id], Kt = L[mt.id];
          return Ve < Kt ? -1 : Ve > Kt ? 1 : 0;
        });
        for (var se = 0, me = oe; se < me.length; se++) {
          var c = me[se];
          c instanceof t && r.internalContainerRefs.push(c), r.layers.push(c);
        }
      }
      r.layersByDepth = ee, ne = Object.keys(J).map(function(Te) {
        return parseInt(Te, 10);
      }).sort(go);
      for (var ye = r.inputs.slice(), ve = [], Ee = 0, Be = ne; Ee < Be.length; Ee++)
        for (var P = Be[Ee], We = 0, Ke = J[P]; We < Ke.length; We++) {
          var V = Ke[We], c = V.outboundLayer;
          if (c != null) {
            for (var ze = 0, Ie = V.inputTensors; ze < Ie.length; ze++) {
              var o = Ie[ze];
              if (ye.indexOf(o) === -1)
                throw new Fn("Graph disconnected: cannot obtain value for tensor " + o + (' at layer "' + c.name + '". ') + "The following previous layers were accessed without " + ("issue: " + ve));
            }
            for (var ue = 0, Qe = V.outputTensors; ue < Qe.length; ue++) {
              var o = Qe[ue];
              ye.push(o);
            }
            ve.push(c.name);
          }
        }
      r.nodesByDepth = J;
      for (var ft = r.layers.map(function(Te) {
        return Te.name;
      }), He = function(Te) {
        var dt = ft.filter(function(mt) {
          return mt === Te;
        }).length;
        if (dt !== 1)
          throw new Fn('The name "' + Te + '" is used ' + dt + " times in the model. All layer names should be unique. Layer names: " + JSON.stringify(ft));
      }, Ot = 0, ht = ft; Ot < ht.length; Ot++) {
        var wt = ht[Ot];
        He(wt);
      }
      return r.outboundNodes = [], r.inboundNodes = [], new So({outboundLayer: r, inboundLayers: [], nodeIndices: [], tensorIndices: [], inputTensors: r.inputs, outputTensors: r.outputs, inputMasks: r.inputs.map(function(Te) {
        return null;
      }), outputMasks: r.outputs.map(function(Te) {
        return null;
      }), inputShapes: r.inputs.map(function(Te) {
        return Te.shape;
      }), outputShapes: r.outputs.map(function(Te) {
        return Te.shape;
      })}), r.built = true, r._refCount = 1, r;
    }
    return t.prototype.assertNotDisposed = function() {
      if (this._refCount === 0)
        throw new Error("Container '" + this.name + "' is already disposed.");
    }, t.prototype.dispose = function() {
      this.assertNotDisposed();
      var e = {refCountAfterDispose: null, numDisposedVariables: 0};
      if (--this._refCount === 0) {
        for (var r = 0, i = this.layers; r < i.length; r++) {
          var a = i[r];
          e.numDisposedVariables += a.dispose().numDisposedVariables;
        }
        for (var s = 0, o = this.internalContainerRefs; s < o.length; s++) {
          var c = o[s];
          e.numDisposedVariables += c.dispose().numDisposedVariables;
        }
      }
      return e.refCountAfterDispose = this._refCount, e;
    }, Object.defineProperty(t.prototype, "trainable", {get: function() {
      return this.trainable_;
    }, set: function(e) {
      this.layers.forEach(function(r) {
        r._trainableWeights.forEach(function(i) {
          return i.trainable = e;
        });
      }), this.trainable_ = e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "trainableWeights", {get: function() {
      if (this._trainableWeights.length > 0)
        throw new M("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.");
      if (!this.trainable)
        return [];
      for (var e = [], r = 0, i = this.layers; r < i.length; r++) {
        var a = i[r];
        e = e.concat(a.trainableWeights);
      }
      return e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "nonTrainableWeights", {get: function() {
      for (var e = [], r = 0, i = this.layers; r < i.length; r++) {
        var a = i[r];
        e.push.apply(e, a.nonTrainableWeights);
      }
      if (!this.trainable) {
        for (var s = [], o = 0, c = this.layers; o < c.length; o++) {
          var a = c[o];
          s.push.apply(s, a.trainableWeights);
        }
        return s.concat(e);
      }
      return e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "weights", {get: function() {
      return this.trainableWeights.concat(this.nonTrainableWeights);
    }, enumerable: true, configurable: true}), t.prototype.loadWeights = function(e, r) {
      r === void 0 && (r = true);
      for (var i = {}, a = 0, s = 0, o = this.layers; s < o.length; s++)
        for (var c = o[s], l = 0, u = c.weights; l < u.length; l++) {
          var h = u[l];
          if (i[h.originalName] != null)
            throw new M("Duplicate weight name: " + h.originalName);
          i[h.originalName] = h, a++;
        }
      var d = [];
      for (var p in e) {
        var f = p;
        if (i[p] == null) {
          var m = p.split("/"), g = m.slice(0, -2).concat([m[m.length - 1]]);
          f = g.join("/");
        }
        if (i[f] != null)
          d.push([i[f], e[p]]);
        else if (r)
          throw new M("Provided weight data has no target variable: " + p);
        delete i[f];
      }
      if (r) {
        var y = [];
        for (var w in i)
          y.push(w);
        if (y.length > 0)
          throw new M(y.length + " of " + a + " weights are not set: " + ("" + y));
      }
      Mh(d);
    }, t.prototype.updatedConfig = function() {
      var e = this.getConfig(), r = {};
      return r.className = this.getClassName(), r.config = e, r.kerasVersion = "tfjs-layers " + $h, r.backend = "TensorFlow.js", r;
    }, t.prototype.toJSON = function(e, r) {
      r === void 0 && (r = true);
      var i = jh(this.updatedConfig());
      return r ? JSON.stringify(i) : i;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        e = nt(e);
        for (var a = new Yi(), s = 0; s < i.inputs.length; ++s)
          a.add(i.inputs[s], e[s]);
        return Ya(i.outputs, a, r);
      });
    }, t.prototype.computeMask = function(e, r) {
      var i = this;
      return v.tidy(function() {
        e = nt(e);
        var a;
        return r == null ? a = ei(null, e.length) : a = nt(r), i.runInternalGraph(e, a)[1];
      });
    }, t.prototype.computeOutputShape = function(e) {
      var r = xo(e);
      if (r.length !== this.inputLayers.length)
        throw new M("Invalid inputShape argument " + e + ": " + ("model has " + this.inputLayers.length + " tensor inputs."));
      for (var i = {}, a = 0; a < r.length; a++) {
        var s = this.inputLayers[a], o = r[a], c = s.name + "_0_0";
        i[c] = o;
      }
      var l = Object.keys(this.nodesByDepth).map(function(B) {
        return parseInt(B, 10);
      }).sort(go);
      if (l.length > 1)
        for (var u = 0, h = l; u < h.length; u++)
          for (var d = h[u], p = this.nodesByDepth[d], f = 0, m = p; f < m.length; f++) {
            var g = m[f], s = g.outboundLayer;
            if (this.inputLayers.map(function(V) {
              return V.id;
            }).indexOf(s.id) !== -1)
              continue;
            for (var y = [], w = 0; w < g.inboundLayers.length; w++) {
              var b = g.inboundLayers[w], L = g.nodeIndices[w], x = g.tensorIndices[w], c = b.name + "_" + L + "_" + x, N = i[c];
              y.push(N);
            }
            for (var I = s.computeOutputShape(Vt(y)), C = xo(I), O = s.inboundNodes.indexOf(g), w = 0; w < C.length; w++) {
              var c = s.name + "_" + O + "_" + w;
              i[c] = C[w];
            }
          }
      for (var D = [], F = [], a = 0; a < this.outputLayers.length; a++) {
        var s = this.outputLayers[a], O = this.outputLayersNodeIndices[a], x = this.outputLayersTensorIndices[a], c = s.name + "_" + O + "_" + x;
        F.push(c);
      }
      for (var a = 0; a < F.length; a++) {
        var k = F[a];
        Wn(k in i), D.push(i[k]);
      }
      return Vt(D);
    }, t.prototype.runInternalGraph = function(e, r) {
      r == null && (r = ei(null, e.length));
      for (var i = {}, a = 0; a < this.inputs.length; ++a) {
        var s = this.inputs[a], o = e[a], c = r[a];
        i[s.id] = [o, c];
      }
      for (var l = Object.keys(this.nodesByDepth).map(function(ee) {
        return parseInt(ee, 10);
      }).sort(go), u = 0, h = l; u < h.length; u++)
        for (var d = h[u], p = this.nodesByDepth[d], f = 0, m = p; f < m.length; f++) {
          for (var g = m[f], y = g.outboundLayer, w = g.inputTensors, b = g.outputTensors, L = new Array(), x = 0, N = w; x < N.length; x++) {
            var s = N[x];
            s.id in i && L.push(i[s.id]);
          }
          if (L.length === w.length) {
            var I = {}, C = void 0, O = void 0, D = void 0, F = void 0;
            if (g.callArgs != null && (I = g.callArgs), L.length === 1) {
              var k = L[0], B = k[0], V = k[1];
              I.mask == null && (I.mask = V), D = nt(y.call(B, I)), F = nt(y.computeMask(B, V)), C = [B], O = [V];
            } else
              C = L.map(function(ee) {
                return ee[0];
              }), O = L.map(function(ee) {
                return ee[1];
              }), I.mask == null && (I.mask = O), D = nt(y.call(C, I)), F = nt(y.computeMask(C, O));
            if (y.activityRegularizer)
              throw new Re("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");
            for (var a = 0; a < b.length; ++a) {
              var s = b[a], o = D[a], c = F[a];
              i[s.id] = [o, c];
            }
          }
        }
      for (var P = [], G = [], j = [], q = 0, H = this.outputs; q < H.length; q++) {
        var s = H[q];
        Wn(s.id in i, "Could not compute output " + s.name + " : " + s.id);
        var J = i[s.id], $ = J[0], c = J[1];
        j.push($.shape), P.push($), G.push(c);
      }
      return [P, G, j];
    }, t.prototype.buildNodeConversionMap = function(e) {
      for (var r = {}, i, a = 0, s = this.layers; a < s.length; a++) {
        var o = s[a];
        i = o instanceof t ? 1 : 0;
        for (var c = 0; c < o.inboundNodes.length; c++) {
          var l = t.nodeKey(o, c);
          this.containerNodes.has(l) && (r[l] = i, i += 1);
        }
      }
      return r;
    }, t.prototype.getLayer = function(e, r) {
      if (r != null) {
        if (this.layers.length <= r)
          throw new M("Was asked to retrieve layer at index " + r + ", but model only " + ("has " + this.layers.length + " layer(s)."));
        return this.layers[r];
      } else if (e == null)
        throw new M("Provide either a layer name or layer index");
      for (var i = 0, a = this.layers; i < a.length; i++) {
        var s = a[i];
        if (s.name === e)
          return s;
      }
      throw new M("No such layer: " + e);
    }, t.prototype.calculateLosses = function() {
      var e = this;
      return v.tidy(function() {
        for (var r = [], i = 0, a = e.layers; i < a.length; i++)
          for (var s = a[i], o = 0; o < s.inboundNodes.length; ++o) {
            var c = t.nodeKey(s, o);
            e.containerNodes.has(c) && r.push.apply(r, s.calculateLosses());
          }
        return r;
      });
    }, t.prototype.getConfig = function() {
      for (var e = {name: this.name}, r = this.buildNodeConversionMap(this.layers), i = [], a = 0, s = this.layers; a < s.length; a++) {
        for (var o = s[a], c = o.getClassName(), l = o.getConfig(), u = [], h = 0; h < o.inboundNodes.length; h++) {
          var d = o.inboundNodes[h], p = t.nodeKey(o, h), f = {};
          if (this.containerNodes.has(p)) {
            if (d.callArgs)
              try {
                JSON.stringify(d.callArgs), f = d.callArgs;
              } catch (O) {
                console.warn("Layer " + o.name + " was passed non-serializable keyword arguments: " + (d.callArgs + ". They will not be included ") + "in the serialized model (and thus will be missing at deserialization time)."), f = {};
              }
            if (d.inboundLayers.length > 0) {
              for (var m = [], g = 0; g < d.inboundLayers.length; g++) {
                var y = d.inboundLayers[g], w = d.nodeIndices[g], b = d.tensorIndices[g], L = t.nodeKey(y, w), x = r[L];
                x == null && (x = 0), m.push([y.name, x, b, f]);
              }
              u.push(m);
            }
          }
        }
        var N = {};
        N.name = o.name, N.className = c, N.config = l, N.inboundNodes = u, i.push(N);
      }
      e.layers = i;
      for (var I = [], g = 0; g < this.inputLayers.length; g++) {
        var o = this.inputLayers[g], w = this.inputLayersNodeIndices[g], p = t.nodeKey(o, w);
        if (!this.containerNodes.has(p))
          continue;
        var x = r[p];
        x == null && (x = 0);
        var b = this.inputLayersTensorIndices[g];
        I.push([o.name, x, b]);
      }
      e.inputLayers = I;
      for (var C = [], g = 0; g < this.outputLayers.length; g++) {
        var o = this.outputLayers[g], w = this.outputLayersNodeIndices[g], p = t.nodeKey(o, w);
        if (!this.containerNodes.has(p))
          continue;
        var x = r[p];
        x == null && (x = 0);
        var b = this.outputLayersTensorIndices[g];
        C.push([o.name, x, b]);
      }
      return e.outputLayers = C, e;
    }, t.fromConfig = function(e, r, i, a) {
      a === void 0 && (a = false);
      var s = {}, o = {};
      function c(H, J) {
        H.name in o ? o[H.name].push(J) : o[H.name] = [J];
      }
      function l(H, J) {
        for (var $ = [], ee, te = 0, ne = J; te < ne.length; te++) {
          var re = ne[te], ie = re[0], oe = re[1], se = re[2];
          if (ee = re[3] == null ? {} : re[3], !(ie in s)) {
            c(H, J);
            return;
          }
          var me = s[ie];
          if (me.inboundNodes.length <= oe) {
            c(H, J);
            return;
          }
          var ye = me.inboundNodes[oe];
          $.push(ye.outputTensors[se]);
        }
        $.length > 0 && H.apply(Vt($), ee);
      }
      function u(H) {
        var J = H.name, $ = Sn(H, r.customObjects != null ? r.customObjects : {});
        $.setFastWeightInitDuringBuild(a), s[J] = $;
        var ee = H.inboundNodes;
        ee.forEach(function(te) {
          if (!(te instanceof Array))
            throw new M("Corrupted configuration, expected array for nodeData: " + te);
          c($, te);
        });
      }
      for (var h = r.name, d = r.layers, p = 0, f = d; p < f.length; p++) {
        var m = f[p];
        u(m);
      }
      for (; !OO(o); )
        for (var g = 0, y = d; g < y.length; g++) {
          var m = y[g], w = s[m.name];
          if (w.name in o) {
            var b = o[w.name];
            delete o[w.name];
            for (var L = 0, x = b; L < x.length; L++) {
              var N = x[L];
              l(w, N);
            }
          }
        }
      for (var I = [], C = [], O = r.inputLayers, D = 0, F = O; D < F.length; D++) {
        var m = F[D], k = m[0], B = m[1], V = m[2];
        Wn(k in s);
        var w = s[k], P = w.inboundNodes[B].outputTensors;
        I.push(P[V]);
      }
      for (var G = r.outputLayers, j = 0, q = G; j < q.length; j++) {
        var m = q[j], k = m[0], B = m[1], V = m[2];
        Wn(k in s);
        var w = s[k], P = w.inboundNodes[B].outputTensors;
        C.push(P[V]);
      }
      return new e({inputs: I, outputs: C, name: h});
    }, Object.defineProperty(t.prototype, "stateful", {get: function() {
      if (this._stateful)
        throw new M("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");
      for (var e = 0, r = this.layers; e < r.length; e++) {
        var i = r[e];
        if (i.stateful)
          return true;
      }
      return false;
    }, enumerable: true, configurable: true}), t.prototype.resetStates = function() {
      var e = this;
      v.tidy(function() {
        e.layers.forEach(function(r) {
          r.stateful && r.resetStates();
        });
      });
    }, t;
  }(Fe);
  function n7(n, t, e) {
    var r = t.length;
    if (n == null || Array.isArray(n) && n.length === 0)
      return t.map(function(a) {
        return null;
      });
    if (r === 1)
      return Array.isArray(n) && n.length === 1 ? n : typeof n == "object" && t[0] in n ? [n[t[0]]] : [n];
    if (Array.isArray(n)) {
      if (n.length !== r)
        throw new Error("Provided " + e + " is an array of " + n.length + " " + ("element(s), but the model has " + r + " outputs. ") + "Make sure a set of weights is provided for each model output.");
      return n;
    } else if (typeof n == "object" && Object.keys(n).length > 0 && typeof n[Object.keys(n)[0]] == "object") {
      var i = [];
      return t.forEach(function(a) {
        a in n ? i.push(n[a]) : i.push(null);
      }), i;
    } else
      throw new Error("The model has multiple (" + r + ") outputs, " + ("so " + e + " must be either an array with ") + (r + " elements or an object with " + t + " keys. ") + ("Provided " + e + " not understood: " + JSON.stringify(n)));
  }
  function jy(n, t) {
    return n7(n, t, "classWeight");
  }
  function $y(n, t, e, r) {
    return Ae(this, void 0, void 0, function() {
      var i, a, s, o, c;
      return xe(this, function(l) {
        switch (l.label) {
          case 0:
            if (t != null || r != null)
              throw new Error("Support sampleWeight is not implemented yet");
            return e != null ? (i = v.tidy(function() {
              if (n.shape.length === 1)
                return n.clone();
              if (n.shape.length === 2)
                if (n.shape[1] > 1) {
                  var u = 1;
                  return n.argMax(u);
                } else {
                  if (n.shape[1] === 1)
                    return n.reshape([n.shape[0]]);
                  throw new Error("Encountered unexpected last-dimension size (" + n.shape[1] + ") during handling of class weights. The size is expected to be >= 1.");
                }
              else
                throw new Error("Unexpected rank of target (y) tensor (" + n.rank + ") during handling of class weights. The rank is expected to be 1 or 2.");
            }), o = (s = Array).from, [4, i.data()]) : [3, 2];
          case 1:
            return a = o.apply(s, [l.sent()]), v.dispose(i), c = [], a.forEach(function(u) {
              if (e[u] == null)
                throw new Error("classWeight must contain all classes in the training data. " + ("The class " + u + " exists in the data but not in ") + "classWeight");
              c.push(e[u]);
            }), [2, v.tensor1d(c, "float32")];
          case 2:
            return [2, null];
        }
      });
    });
  }
  function r7(n, t) {
    return v.mul(n, t);
  }
  var i7 = 32;
  function Jy(n, t) {
    var e, r, i = t;
    e = i.xs, r = i.ys, v.util.assert(e != null && r != null, function() {
      return "A Dataset iterator for fitDataset() is expected to generate objects of the form `{xs: xVal, ys: yVal}`, where the two values may be `tf.Tensor`, an array of Tensors, or a map of string to Tensor.  The provided Dataset instead generates " + ("" + t);
    });
    var a = Xy("input", n.inputNames, e), s = Xy("output", n.outputNames, r), o = a[0].shape[0];
    v.util.assert(a.length === n.inputs.length, function() {
      return "LayersModel has " + n.inputs.length + " inputs, but the dataset " + ("provides " + a.length + " inputs.  (Expected input keys: ") + (JSON.stringify(n.inputNames) + ")");
    }), v.util.assert(s.length === n.outputs.length, function() {
      return "LayersModel has " + n.outputs.length + " outputs, but the dataset " + ("provides " + s.length + " outputs.  (Expected output keys: ") + (JSON.stringify(n.outputNames) + ")");
    });
    for (var c = function(d) {
      v.util.assert(a[d].shape[0] === o, function() {
        return "Batch size mismatch: input " + (n.inputNames[d] + " has " + a[d].shape[0] + "; ") + ("expected  " + o + " based on input " + n.inputNames[0] + ".");
      });
    }, l = 0; l < a.length; l++)
      c(l);
    for (var u = function(d) {
      v.util.assert(s[d].shape[0] === o, function() {
        return "Batch size mismatch: output " + (n.outputNames[d] + " has " + s[d].shape[0] + "; ") + ("expected  " + o + " based on input " + n.inputNames[0] + ".");
      });
    }, h = 0; h < s.length; h++)
      u(h);
    return {xs: a, ys: s};
  }
  function Xy(n, t, e) {
    if (e instanceof v.Tensor)
      return [e];
    if (Array.isArray(e))
      return v.util.assert(e.length === t.length, function() {
        return "Received an array of " + e.length + " Tensors, but expected " + t.length + " to match the " + n + " keys " + t + ".";
      }), e;
    for (var r = [], i = 0, a = t; i < a.length; i++) {
      var s = a[i];
      if (e[s] == null)
        throw new M("The feature data generated by the dataset lacks the required " + (n + " key '" + s + "'."));
      r.push(e[s]);
    }
    return r;
  }
  function a7(n) {
    if (n.length === 3)
      throw new Re("Validation with sample weights is not implemented yet.");
    return {xs: n[0], ys: n[1]};
  }
  function o7(n, t, e) {
    return Ae(this, void 0, void 0, function() {
      var r, i, a, s, o, c, l, u, h, d, p, f, m, g, y, w, b, L, x, N, I, C, O, D, F, k, B, V, P, G, k, j, q, H, J, k;
      return xe(this, function($) {
        switch ($.label) {
          case 0:
            if (r = e.batchesPerEpoch != null, v.util.assert(n.optimizer != null, function() {
              return "You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig).";
            }), v.util.assert(e != null, function() {
              return "For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call.";
            }), v.util.assert(e.epochs != null && e.epochs > 0 && Number.isInteger(e.epochs), function() {
              return "For fitDataset(), config.epochs is expected to be a positive " + ("integer, but got " + e.epochs);
            }), v.util.assert(!r || e.batchesPerEpoch > 0 && Number.isInteger(e.batchesPerEpoch), function() {
              return "For fitDataset(), config.batchesPerEpoch is expected to be a " + ("positive integer if specified, but got " + e.batchesPerEpoch);
            }), v.util.assert(e.validationSplit == null, function() {
              return "`validationSplit` is not supported by `fitDataset()`. Use validationData instead.";
            }), n.isTraining)
              throw new Error("Cannot start training because another fit() call is ongoing.");
            n.isTraining = true, $.label = 1;
          case 1:
            return $.trys.push([1, , 26, 27]), i = e.validationData != null, a = void 0, s = void 0, i && (Zy(e.validationData) ? v.util.assert(e.validationBatches == null || e.validationBatches > 0 && Number.isInteger(e.validationBatches), function() {
              return "For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, " + ("but got " + e.validationBatches);
            }) : (o = a7(e.validationData), a = o.xs, s = o.ys)), c = n.makeTrainFunction(), l = n.getDedupedMetricsNames(), u = void 0, i ? u = l.slice().concat(l.map(function(ee) {
              return "val_" + ee;
            })) : u = l.slice(), h = Fy(e.callbacks, e.yieldEvery), d = e.verbose == null ? 1 : e.verbose, p = Uy(h, d, e.epochs, null, null, s7(t, e), null, i, u), f = p.callbackList, m = p.history, f.setModel(n), n.history = m, [4, f.onTrainBegin()];
          case 2:
            return $.sent(), n.stopTraining_ = false, g = e.initialEpoch == null ? 0 : e.initialEpoch, [4, t.iterator()];
          case 3:
            y = $.sent(), $.label = 4;
          case 4:
            return g < e.epochs ? (w = {}, [4, f.onEpochBegin(g)]) : [3, 23];
          case 5:
            return $.sent(), b = 0, L = 0, r ? [3, 7] : [4, t.iterator()];
          case 6:
            y = $.sent(), $.label = 7;
          case 7:
            return (r ? b < e.batchesPerEpoch : true) ? [4, y.next()] : [3, 21];
          case 8:
            return x = $.sent(), r && x.done ? (console.warn("You provided `batchesPerEpoch` as " + (e.batchesPerEpoch + ", ") + "but your dataset iterator ran out of data after " + (b + " batches; ") + "interrupting training. Make sure that your dataset can generate at least `batchesPerEpoch * epochs` batches (in this case, " + (e.batchesPerEpoch * e.epochs + " batches). ") + "You may need to use the repeat() function when building your dataset."), [3, 21]) : x.value != null ? (N = Jy(n, x.value), I = N.xs, C = N.ys, O = {}, O.batch = L, O.size = I[0].shape[0], [4, f.onBatchBegin(L, O)]) : [3, 15];
          case 9:
            if ($.sent(), D = [], !(e.classWeight != null))
              return [3, 13];
            F = jy(e.classWeight, n.outputNames), k = 0, $.label = 10;
          case 10:
            return k < F.length ? (V = (B = D).push, [4, $y(C[k], null, F[k])]) : [3, 13];
          case 11:
            V.apply(B, [$.sent()]), $.label = 12;
          case 12:
            return ++k, [3, 10];
          case 13:
            for (P = I.concat(C).concat(D), G = c(P), v.dispose(P), k = 0; k < l.length; ++k)
              j = l[k], q = G[k], O[j] = q, v.keep(q);
            return [4, f.onBatchEnd(L, O)];
          case 14:
            $.sent(), Ry(O), L++, b++, $.label = 15;
          case 15:
            return (r ? b >= e.batchesPerEpoch : x.done) ? i ? (H = void 0, Zy(e.validationData) ? (J = nt, [4, n.evaluateDataset(e.validationData, {batches: e.validationBatches})]) : [3, 17]) : [3, 19] : [3, 20];
          case 16:
            return H = J.apply(void 0, [$.sent()]), [3, 18];
          case 17:
            H = nt(n.evaluate(a, s, {batchSize: e.validationBatchSize == null ? i7 : e.validationBatchSize, verbose: 0})), $.label = 18;
          case 18:
            for (k = 0; k < n.metricsNames.length; ++k)
              w["val_" + n.metricsNames[k]] = H[k];
            $.label = 19;
          case 19:
            return [3, 21];
          case 20:
            return n.stopTraining_ ? [3, 21] : [3, 7];
          case 21:
            return [4, f.onEpochEnd(g, w)];
          case 22:
            return $.sent(), g++, n.stopTraining_ ? [3, 23] : [3, 4];
          case 23:
            return [4, f.onTrainEnd()];
          case 24:
            return $.sent(), [4, n.history.syncData()];
          case 25:
            return $.sent(), [2, n.history];
          case 26:
            return n.isTraining = false, [7];
          case 27:
            return [2];
        }
      });
    });
  }
  function s7(n, t) {
    var e = null;
    return t.batchesPerEpoch != null ? e = t.batchesPerEpoch : Number.isFinite(n.size) && (e = n.size), e;
  }
  function Zy(n) {
    return typeof n.iterator == "function";
  }
  function c7(n) {
    return typeof n.next == "function";
  }
  function l7(n, t, e) {
    return Ae(this, void 0, void 0, function() {
      var r, i, a, s, o, c, l, u, h, d, p;
      return xe(this, function(f) {
        switch (f.label) {
          case 0:
            if (e = e || {}, r = e.batches != null, i = n.testFunction, a = [], e.verbose > 0)
              throw new Re("Verbose mode is not implemented yet.");
            return v.util.assert(!r || e.batches > 0 && Number.isInteger(e.batches), function() {
              return "Test loop expects `batches` to be a positive integer, but " + ("received " + JSON.stringify(e.batches));
            }), c7(t) ? (o = t, [3, 3]) : [3, 1];
          case 1:
            return [4, t.iterator()];
          case 2:
            o = f.sent(), f.label = 3;
          case 3:
            s = o, c = 0, l = 0, u = function() {
              var m;
              return xe(this, function(g) {
                switch (g.label) {
                  case 0:
                    return [4, s.next()];
                  case 1:
                    return m = g.sent(), a = v.tidy(function() {
                      if (m.value) {
                        var y = Jy(n, m.value), w = y.xs, b = y.ys, L = w.concat(b), x = v.tidy(function() {
                          return i(L);
                        });
                        if (v.dispose(L), l === 0)
                          for (var N = 0; N < x.length; ++N)
                            a.push(v.scalar(0));
                        for (var I = L[0].shape[0], C = function(O) {
                          var D = x[O], F = a[O];
                          a[O] = v.tidy(function() {
                            return v.add(a[O], v.mul(I, D));
                          }), l > 0 && v.dispose(F);
                        }, N = 0; N < x.length; ++N)
                          C(N);
                        v.dispose(x), c += I, ++l;
                      }
                      return a;
                    }), m.done ? (r && console.warn("Your dataset iterator ran out of data during evaluateDataset(). Interrupting evalution. Make sure that your dataset can generate at least `batches` " + ("batches (in this case, " + e.batches + " batches). ") + "You may need to use the repeat() function when building your dataset."), [2, "break"]) : [2];
                }
              });
            }, f.label = 4;
          case 4:
            return (r ? l < e.batches : true) ? [5, u()] : [3, 6];
          case 5:
            return h = f.sent(), h === "break" ? [3, 6] : [3, 4];
          case 6:
            for (d = 0; d < a.length; ++d)
              p = a[d], a[d] = v.div(a[d], c), v.dispose(p);
            return [2, Vt(a)];
        }
      });
    });
  }
  function Jh(n) {
    v.util.assert(n > 0 && Number.isInteger(n), function() {
      return "batchSize is required to be a positive integer, but got " + n;
    });
  }
  function Ka(n, t, e) {
    return n == null ? [null] : Array.isArray(n) ? n.map(function(r) {
      return ri(r, t, e - t);
    }) : ri(n, t, e - t);
  }
  function Zh(n, t) {
    return v.tidy(function() {
      return n == null ? null : Array.isArray(n) ? n.map(function(e) {
        return Zh(e, t);
      }) : fy(n, t.dtype === "int32" ? t : t.toInt());
    });
  }
  function Qh(n, t) {
    for (var e = [], r = 0, i = null; r < n; )
      i = r + t, i >= n && (i = n), e.push([r, i]), r = i;
    return e;
  }
  function u7(n, t, e, r, i, a, s, o, c, l, u, h, d, p, f) {
    return Ae(this, void 0, void 0, function() {
      var m, g, y, w, b, L, x, N, I;
      return xe(this, function(C) {
        switch (C.label) {
          case 0:
            if (i == null && (i = 32), a == null && (a = 1), u == null && (u = true), d == null && (d = 0), m = false, c != null && l != null && (m = true), f != null && (m = true, p == null))
              throw new M("Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.");
            return g = n.checkNumSamples(e, i, p, "steps_per_epoch"), g != null && (y = xn(0, g)), s == null && (s = 1), w = Uy(o, s, a, d, g, p, i, m, h), b = w.callbackList, L = w.history, b.setModel(n), n.history = L, [4, b.onTrainBegin()];
          case 1:
            C.sent(), n.stopTraining_ = false, x = function(O) {
              var D, F, k, B, V, P;
              return xe(this, function(G) {
                switch (G.label) {
                  case 0:
                    return [4, b.onEpochBegin(O)];
                  case 1:
                    if (G.sent(), D = {}, !(p != null))
                      return [3, 2];
                    throw new Re("stepsPerEpoch mode is not implemented yet.");
                  case 2:
                    if (u === "batch")
                      throw new Re("batch shuffling is not implemneted yet");
                    u && v.util.shuffle(y), F = v.tensor1d(y), k = Qh(g, i), B = function(j) {
                      var q;
                      return xe(this, function(H) {
                        switch (H.label) {
                          case 0:
                            return q = {}, [4, b.onBatchBegin(j, q)];
                          case 1:
                            return H.sent(), v.tidy(function() {
                              var J = k[j][0], $ = k[j][1], ee = ri(F, J, $ - J);
                              q.batch = j, q.size = $ - J;
                              for (var te = Zh(e, ee), ne = t(te), re = 0; re < r.length; ++re) {
                                var ie = r[re], oe = ne[re];
                                q[ie] = oe, v.keep(oe);
                              }
                              if (j === k.length - 1 && m)
                                for (var se = n.testLoop(c, l, i), re = 0; re < r.length; ++re) {
                                  var ie = r[re], oe = se[re];
                                  v.keep(oe), D["val_" + ie] = oe;
                                }
                            }), [4, b.onBatchEnd(j, q)];
                          case 2:
                            return H.sent(), Ry(q), n.stopTraining_ ? [2, "break"] : [2];
                        }
                      });
                    }, V = 0, G.label = 3;
                  case 3:
                    return V < k.length ? [5, B(V)] : [3, 6];
                  case 4:
                    if (P = G.sent(), P === "break")
                      return [3, 6];
                    G.label = 5;
                  case 5:
                    return ++V, [3, 3];
                  case 6:
                    F.dispose(), G.label = 7;
                  case 7:
                    return [4, b.onEpochEnd(O, D)];
                  case 8:
                    return G.sent(), n.stopTraining_ ? [2, "break"] : [2];
                }
              });
            }, N = d, C.label = 2;
          case 2:
            return N < a ? [5, x(N)] : [3, 5];
          case 3:
            if (I = C.sent(), I === "break")
              return [3, 5];
            C.label = 4;
          case 4:
            return ++N, [3, 2];
          case 5:
            return [4, b.onTrainEnd()];
          case 6:
            return C.sent(), [4, n.history.syncData()];
          case 7:
            return C.sent(), [2, n.history];
        }
      });
    });
  }
  function h7(n, t, e, r) {
    return r === void 0 && (r = {}), Ae(this, void 0, void 0, function() {
      var i, a, s, o, c, l, u, h, d, p, f, m, g, y, w, b, L, x, N, I, C, O, D;
      return xe(this, function(F) {
        switch (F.label) {
          case 0:
            if (n.isTraining)
              throw new Error("Cannot start training because another fit() call is ongoing.");
            n.isTraining = true, F.label = 1;
          case 1:
            return F.trys.push([1, , 7, 8]), h = r.batchSize == null ? 32 : r.batchSize, Jh(h), d = false, [4, n.standardizeUserData(t, e, r.sampleWeight, r.classWeight, d, h)];
          case 2:
            if (p = F.sent(), i = p[0], a = p[1], u = p[2], f = false, m = void 0, !(r.validationData != null && r.validationData.length > 0))
              return [3, 4];
            if (f = true, r.validationData.length === 2)
              s = r.validationData[0], o = r.validationData[1];
            else
              throw r.validationData.length === 3 ? new Re("validationData including sample weights is not supported yet.") : new M("When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; " + (r.validationData + " is invalid."));
            return g = true, [4, n.standardizeUserData(s, o, null, null, g, h)];
          case 3:
            return y = F.sent(), c = y[0], l = y[1], m = c.concat(l), [3, 5];
          case 4:
            r.validationSplit != null && r.validationSplit > 0 && r.validationSplit < 1 ? (f = true, w = Math.floor(i[0].shape[0] * (1 - r.validationSplit)), b = i[0].shape[0], c = Ka(i, w, b), i = Ka(i, 0, w), l = Ka(a, w, b), a = Ka(a, 0, w), m = c.concat(l)) : r.validationSteps != null && (f = true), F.label = 5;
          case 5:
            return L = i.concat(a).concat(u), n.checkTrainableWeightsConsistency(), x = n.makeTrainFunction(), N = n.getDedupedMetricsNames(), I = void 0, C = void 0, f ? (n.makeTestFunction(), I = n.testFunction, C = N.slice().concat(N.map(function(k) {
              return "val_" + k;
            }))) : (I = null, m = [], C = N.slice()), O = Fy(r.callbacks, r.yieldEvery), [4, u7(n, x, L, N, h, r.epochs, r.verbose, O, I, m, r.shuffle, C, r.initialEpoch, null, null)];
          case 6:
            return D = F.sent(), [2, D];
          case 7:
            return n.isTraining = false, ai(i, t), ai(a, e), ai(c, s), ai(l, o), u != null && v.dispose(u), [7];
          case 8:
            return [2];
        }
      });
    });
  }
  function Qy(n) {
    var t = [];
    n instanceof v.Tensor && (n = [n]);
    for (var e = 0; e < n.length; ++e) {
      var r = n[e];
      if (r.rank === 1)
        t.push(Pa(r, 1));
      else {
        if (r.rank === 0)
          throw new Error("Expected tensor to be at least 1D, but received a 0D tensor (scalar).");
        t.push(r);
      }
    }
    return t;
  }
  function ai(n, t) {
    if (n == null)
      return;
    var e = [];
    if (t instanceof v.Tensor)
      e.push(t.id);
    else if (Array.isArray(t))
      t.forEach(function(c) {
        return e.push(c.id);
      });
    else if (t != null)
      for (var r in t) {
        var i = t[r];
        e.push(i.id);
      }
    var a = [];
    if (n instanceof v.Tensor)
      e.indexOf(n.id) === -1 && a.push(n);
    else if (Array.isArray(n))
      n.forEach(function(c) {
        e.indexOf(c.id) === -1 && a.push(c);
      });
    else if (n != null)
      for (var s in n) {
        var o = n[s];
        e.indexOf(o.id) === -1 && a.push(o);
      }
    a.forEach(function(c) {
      c.isDisposed || c.dispose();
    });
  }
  function d7(n) {
    return n instanceof v.Tensor;
  }
  function ed(n) {
    return Array.isArray(n);
  }
  function ev(n) {
    return !d7(n) && !ed(n);
  }
  function tv(n, t, e, r, i) {
    if (r === void 0 && (r = true), i === void 0 && (i = ""), t == null || t.length === 0) {
      if (n != null) {
        var a = false;
        if (ed(n) && n.length > 0)
          a = true;
        else if (ev(n)) {
          for (var s in n)
            if (n.hasOwnProperty(s)) {
              a = true;
              break;
            }
        } else
          a = true;
        if (a)
          throw new M("Error when checking model " + i + " expected no data, " + ("but got " + n));
      }
      return [];
    }
    if (n == null)
      return t.map(function(g) {
        return null;
      });
    var o;
    if (ev(n)) {
      n = n, o = [];
      for (var c = 0, l = t; c < l.length; c++) {
        var u = l[c];
        if (n[u] == null)
          throw new M('No data provided for "' + u + '". Need data for each key in: ' + ("" + t));
        o.push(n[u]);
      }
    } else if (ed(n)) {
      if (n = n, n.length !== t.length)
        throw new M("Error when checking model " + i + ": the Array of Tensors that you are passing to your model is not the size the " + ("model expected. Expected to see " + t.length + " Tensor(s), but ") + ("instead got the following list of Tensor(s): " + n));
      o = n;
    } else {
      if (n = n, t.length > 1)
        throw new M("The model " + i + " expects " + t.length + " Tensor(s), " + ("but only received one Tensor. Found: Tensor with shape " + n.shape));
      o = [n];
    }
    if (o = Qy(o), e != null)
      for (var h = 0; h < t.length; ++h) {
        if (e[h] == null)
          continue;
        var d = o[h];
        if (d.shape.length !== e[h].length)
          throw new M("Error when checking " + i + ": expected " + t[h] + " " + ("to have " + e[h].length + " dimension(s). but got array with ") + ("shape " + d.shape));
        for (var p = 0; p < e[h].length; ++p) {
          if (p === 0 && !r)
            continue;
          var f = d.shape[p], m = e[h][p];
          if (m != null && m >= 0 && f !== m)
            throw new M("Error when checking " + i + ": expected " + t[h] + " " + ("to have shape [" + e[h] + "], but got array with shape ") + ("[" + d.shape + "]."));
        }
      }
    return o;
  }
  function p7(n, t, e) {
    var r = wr(n.map(function(a) {
      return a.shape[0];
    }));
    r.sort();
    var i = wr(t.map(function(a) {
      return a.shape[0];
    }));
    if (i.sort(), r.length > 1)
      throw new M("All input Tensors (x) should have the same number of samples. Got array shapes: " + ("" + JSON.stringify(n.map(function(a) {
        return a.shape;
      }))));
    if (i.length > 1)
      throw new M("All target Tensors (y) should have the same number of samples. Got array shapes: " + ("" + JSON.stringify(t.map(function(a) {
        return a.shape;
      }))));
    if (r.length > 0 && i.length > 0 && !v.util.arraysEqual(r, i))
      throw new M("Input Tensors should have the same number of samples as target " + ("Tensors. Found " + r[0] + " input sample(s) and " + i[0] + " target ") + "sample(s).");
  }
  function f7(n, t, e) {
    for (var r = [ii, No, Ga], i = 0; i < n.length; ++i) {
      var a = n[i], s = t[i], o = e[i];
      if (s == null)
        continue;
      if (s === Ga && a.shape[a.shape.length - 1] === 1)
        throw new M("You are passing a target array of shape " + a.shape + " while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].");
      if (r.indexOf(s) !== -1)
        for (var c = a.shape.slice(1), l = o.slice(1), u = 0; u < c.length; ++u) {
          var h = c[u], d = l[u];
          if (d != null && h !== d)
            throw new M("A target Tensor with shape " + a.shape + " was passed for an " + ("output of shape " + o + ", while using a loss function that ") + "expects targets to have the same shape as the output.");
        }
    }
  }
  function nv(n, t, e, r, i) {
    r === void 0 && (r = true), i === void 0 && (i = "");
    var a;
    if (Array.isArray(n)) {
      if (n.length !== t.length)
        throw new M("Error when checking model " + i + ": the Array of Tensors that you are passing to your model is not the size the " + ("the model expected. Expected to see " + t.length + " Tensor(s),") + (" but instead got " + n.length + " Tensors(s)."));
      a = n;
    } else {
      if (t.length > 1)
        throw new M("The model expects " + t.length + " " + i + " Tensors, but only received one Tensor. Found: array with shape " + (JSON.stringify(n.shape) + "."));
      a = [n];
    }
    if (e != null)
      for (var s = 0; s < t.length; ++s) {
        if (e[s] == null)
          continue;
        var o = a[s];
        if (o.shape.length !== e[s].length)
          throw new M("Error when checking " + i + ": expected " + t[s] + " " + ("to have " + e[s].length + " dimension(s), but got array with ") + ("shape " + JSON.stringify(o.shape)));
        for (var c = 0; c < e[s].length; ++c) {
          if (c === 0 && !r)
            continue;
          var l = o.shape[c], u = e[s][c];
          if (u != null && u !== l)
            throw new M("Error when checking " + i + ": expected " + (t[s] + " to have shape " + JSON.stringify(e[s]) + " but ") + ("got array with shape " + JSON.stringify(o.shape) + "."));
        }
      }
  }
  function m7(n, t) {
    if (n == null || Array.isArray(n) && n.length === 0)
      return t.map(function(c) {
        return [];
      });
    var e;
    if (typeof n == "string" || typeof n == "function")
      e = [n];
    else if (Array.isArray(n) || typeof n == "object")
      e = n;
    else
      throw new TypeError("Type of metrics argument not understood. Expected an string," + ("function, Array, or Object, found: " + n));
    if (Array.isArray(e))
      return t.map(function(c) {
        return e;
      });
    for (var r = [], i = 0, a = t; i < a.length; i++) {
      var s = a[i], o = e.hasOwnProperty(s) ? e[s] : [];
      Array.isArray(o) || (o = [o]), r.push(o);
    }
    return r;
  }
  var g7 = "layers-model", Sr = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.isTraining = false, r;
    }
    return t.prototype.summary = function(e, r, i) {
      if (i === void 0 && (i = console.log), !this.built)
        throw new M("This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).");
      XE(this, e, r, i);
    }, t.prototype.compile = function(e) {
      var r = this;
      if (e.loss == null && (e.loss = []), this.loss = e.loss, typeof e.optimizer == "string")
        this.optimizer_ = qE(e.optimizer), this.isOptimizerOwned = true;
      else {
        if (!(e.optimizer instanceof v.Optimizer))
          throw new M("User-defined optimizer must be an instance of tf.Optimizer.");
        this.optimizer_ = e.optimizer, this.isOptimizerOwned = false;
      }
      var i = [];
      if (!Array.isArray(e.loss) && typeof e.loss != "string" && typeof e.loss != "function") {
        e.loss = e.loss;
        for (var a in e.loss)
          if (this.outputNames.indexOf(a) === -1)
            throw new M('Unknown entry in loss dictionary: "' + a + '". ' + ("Only expected the following keys: " + this.outputNames));
        for (var s = 0, o = this.outputNames; s < o.length; s++) {
          var c = o[s];
          e.loss[c] == null && console.warn('Output "' + c + '" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data ' + ("to be passed to " + c + " during training")), i.push(Vh(e.loss[c]));
        }
      } else if (Array.isArray(e.loss)) {
        if (e.loss.length !== this.outputs.length)
          throw new M("When passing an Array as loss, it should have one entry per " + ("model output. The model has " + this.outputs.length + " output(s), ") + ("but you passed loss=" + e.loss + "."));
        var l = e.loss;
        i = l.map(function(y) {
          return Vh(y);
        });
      } else {
        var u = Vh(e.loss);
        this.outputs.forEach(function(y) {
          i.push(u);
        });
      }
      this.lossFunctions = i, this.feedOutputNames = [], this.feedOutputShapes = [], this.feedLossFns = [];
      for (var h = 0; h < this.outputs.length; ++h) {
        var d = this.internalOutputShapes[h], p = this.outputNames[h];
        this.feedOutputNames.push(p), this.feedOutputShapes.push(d), this.feedLossFns.push(this.lossFunctions[h]);
      }
      var f = [];
      this.metrics = e.metrics, this.metricsNames = ["loss"], this.metricsTensors = [], ni("loss", function() {
        for (var y = 0; y < r.outputs.length; ++y) {
          if (f.indexOf(y) !== -1)
            continue;
          var w = r.lossFunctions[y];
          r.outputs.length > 1 && (r.metricsTensors.push([w, y]), r.metricsNames.push(r.outputNames[y] + "_loss"));
        }
      });
      var m = m7(e.metrics, this.outputNames), g = function(y, w, b) {
        r.outputNames.length > 1 && (w = r.outputNames[y] + "_" + w), r.metricsNames.push(w), r.metricsTensors.push([b, y]);
      };
      ni("metric", function() {
        for (var y = function(b) {
          if (f.indexOf(b) !== -1)
            return "continue";
          var L = m[b], x = function(N) {
            for (var I = "", C, O, D, F = function(P) {
              if (typeof P == "string" && ["accuracy", "acc", "crossentropy", "ce"].indexOf(P) !== -1) {
                var G = r.internalOutputShapes[b];
                G[G.length - 1] === 1 || r.lossFunctions[b] === No ? ["accuracy", "acc"].indexOf(P) !== -1 ? O = Gh : ["crossentropy", "ce"].indexOf(P) !== -1 && (O = Py) : r.lossFunctions[b] === To ? ["accuracy", "acc"].indexOf(P) !== -1 ? O = My : ["crossentropy", "ce"].indexOf(P) !== -1 && (O = Hy) : ["accuracy", "acc"].indexOf(P) !== -1 ? O = qh : ["crossentropy", "ce"].indexOf(P) !== -1 && (O = Yh);
                var j = void 0;
                ["accuracy", "acc"].indexOf(P) !== -1 ? j = "acc" : ["crossentropy", "ce"].indexOf(P) !== -1 && (j = "ce"), D = O, C = I + j;
              } else {
                var q = GE(P);
                D = q, C = I + Ro(P);
              }
              var H;
              ni(C, function() {
                H = D;
              }), g(b, C, H);
            }, k = 0, B = N; k < B.length; k++) {
              var V = B[k];
              F(V);
            }
          };
          x(L);
        }, w = 0; w < r.outputs.length; ++w)
          y(w);
      }), this.collectedTrainableWeights = this.trainableWeights;
    }, t.prototype.checkTrainableWeightsConsistency = function() {
      if (this.collectedTrainableWeights == null)
        return;
      this.trainableWeights.length !== this.collectedTrainableWeights.length && console.warn("Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?");
    }, t.prototype.evaluate = function(e, r, i) {
      i === void 0 && (i = {});
      var a = i.batchSize == null ? 32 : i.batchSize;
      Jh(a);
      var s = true, o = this.standardizeUserDataXY(e, r, s, a);
      try {
        var c = o[0].concat(o[1]);
        this.makeTestFunction();
        var l = this.testFunction, u = this.testLoop(l, c, a, i.verbose, i.steps);
        return Vt(u);
      } finally {
        ai(o[0], e), ai(o[1], r);
      }
    }, t.prototype.evaluateDataset = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(i) {
          return this.makeTestFunction(), [2, l7(this, e, r)];
        });
      });
    }, t.prototype.checkNumSamples = function(e, r, i, a) {
      a === void 0 && (a = "steps");
      var s;
      if (i != null) {
        if (s = null, r != null)
          throw new M("If " + a + " is set, batchSize must be null or undefined." + ("Got batchSize = " + r));
      } else if (e != null)
        Array.isArray(e) ? s = e[0].shape[0] : s = e.shape[0];
      else
        throw new M("Either the input data should have a defined shape, or " + (a + " shoud be specified."));
      return s;
    }, t.prototype.execute = function(e, r) {
      if (Array.isArray(r) && r.length === 0)
        throw new M("`outputs` is an empty Array, which is not allowed.");
      var i = Array.isArray(r), a = i ? r : [r], s = this.retrieveSymbolicTensors(a), o = new Yi();
      if (e instanceof v.Tensor && (e = [e]), Array.isArray(e)) {
        if (e.length !== this.inputs.length)
          throw new M("The number of inputs provided (" + e.length + ") does not match the number of inputs of this model " + ("(" + this.inputs.length + ")."));
        for (var c = 0; c < this.inputs.length; ++c)
          o.add(this.inputs[c], e[c]);
      } else
        for (var l = 0, u = this.inputs; l < u.length; l++) {
          var h = u[l], d = e[h.name];
          if (d == null)
            throw new M("No value is provided for the model's input " + h.name);
          o.add(h, d);
        }
      var p = Ya(s, o);
      return i ? p : p[0];
    }, t.prototype.retrieveSymbolicTensors = function(e) {
      for (var r = ei(null, e.length), i = e.length, a = 0, s = this.layers; a < s.length; a++) {
        for (var o = s[a], c = Array.isArray(o.output) ? o.output : [o.output], l = c.map(function(p) {
          return p.name;
        }), u = 0; u < e.length; ++u) {
          var h = l.indexOf(e[u]);
          if (h !== -1 && (r[u] = c[h], i--), i === 0)
            break;
        }
        if (i === 0)
          break;
      }
      if (i > 0) {
        var d = [];
        throw r.forEach(function(p, f) {
          p == null && d.push(e[f]);
        }), new M("Cannot find SymbolicTensors for output name(s): " + ("" + JSON.stringify(d)));
      }
      return r;
    }, t.prototype.predictLoop = function(e, r, i) {
      var a = this;
      return r === void 0 && (r = 32), i === void 0 && (i = false), v.tidy(function() {
        var s = a.checkNumSamples(e);
        if (i)
          throw new Re("Verbose predictLoop() is not implemented yet.");
        for (var o = Qh(s, r), c = a.outputs.map(function(h) {
          return [];
        }), l = function(h) {
          var d = v.tidy(function() {
            var p = o[h][0], f = o[h][1], m = Ka(e, p, f), g = [];
            if (Array.isArray(m))
              for (var y = 0; y < m.length; ++y)
                g.push({key: a.inputs[y], value: m[y]});
            else
              g.push({key: a.inputs[0], value: m});
            var w = new Yi(g);
            return Ya(a.outputs, w);
          });
          d.forEach(function(p, f) {
            return c[f].push(p);
          });
        }, u = 0; u < o.length; ++u)
          l(u);
        return Vt(c.map(function(h) {
          return v.concat(h, 0);
        }));
      });
    }, t.prototype.predict = function(e, r) {
      r === void 0 && (r = {});
      var i = Qy(e);
      nv(i, this.inputNames, this.feedInputShapes, false);
      try {
        var a = r.batchSize == null ? 32 : r.batchSize;
        return Jh(a), this.predictLoop(i, a);
      } finally {
        ai(i, e);
      }
    }, t.prototype.predictOnBatch = function(e) {
      nv(e, this.inputNames, this.feedInputShapes, true);
      var r = (Array.isArray(e) ? e[0] : e).shape[0];
      return this.predictLoop(e, r);
    }, t.prototype.standardizeUserDataXY = function(e, r, i, a) {
      if (this.optimizer_ == null)
        throw new Fn("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");
      for (var s = [], o = 0; o < this.feedOutputShapes.length; ++o) {
        var c = this.feedOutputShapes[o], l = this.feedLossFns[o];
        l === To ? s.push(c.slice(0, c.length - 1).concat([1])) : s.push(c);
      }
      if (e = tv(e, this.feedInputNames, this.feedInputShapes, false, "input"), r = tv(r, this.feedOutputNames, s, false, "target"), p7(e, r), f7(r, this.feedLossFns, this.feedOutputShapes), this.stateful && a != null && a > 0 && e[0].shape[0] % a !== 0)
        throw new M("In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size " + (a + ". Found: " + e[0].shape[0] + " sample(s)."));
      return [e, r];
    }, t.prototype.standardizeUserData = function(e, r, i, a, s, o) {
      return s === void 0 && (s = true), Ae(this, void 0, void 0, function() {
        var c, l, u, h, d, p, f, m;
        return xe(this, function(g) {
          switch (g.label) {
            case 0:
              if (c = this.standardizeUserDataXY(e, r, s, o), l = c[0], u = c[1], i != null)
                throw new Error("sample weight is not supported yet.");
              if (h = null, !(a != null))
                return [3, 4];
              d = jy(a, this.outputNames), h = [], p = 0, g.label = 1;
            case 1:
              return p < d.length ? (m = (f = h).push, [4, $y(u[p], null, d[p])]) : [3, 4];
            case 2:
              m.apply(f, [g.sent()]), g.label = 3;
            case 3:
              return ++p, [3, 1];
            case 4:
              return [2, [l, u, h]];
          }
        });
      });
    }, t.prototype.testLoop = function(e, r, i, a, s) {
      var o = this;
      return a === void 0 && (a = 0), v.tidy(function() {
        var c = o.checkNumSamples(r, i, s, "steps"), l = [];
        if (a > 0)
          throw new Re("Verbose mode is not implemented yet.");
        if (s != null)
          throw new Re("steps mode in testLoop() is not implemented yet");
        for (var u = Qh(c, i), h = v.tensor1d(xn(0, c)), d = 0; d < u.length; ++d) {
          var p = u[d][0], f = u[d][1], m = ri(h, p, f - p), g = Zh(r, m), y = e(g);
          if (d === 0)
            for (var w = 0; w < y.length; ++w)
              l.push(v.scalar(0));
          for (var w = 0; w < y.length; ++w) {
            var b = y[w];
            l[w] = v.add(l[w], v.mul(f - p, b));
          }
        }
        for (var w = 0; w < l.length; ++w)
          l[w] = v.div(l[w], c);
        return l;
      });
    }, t.prototype.getDedupedMetricsNames = function() {
      for (var e = this.metricsNames, r = [], i = 0; i < e.length; ++i) {
        var a = e[i], s = a;
        if (Z0(e, a) > 1) {
          var o = Z0(e.slice(0, i), a);
          s += "_" + o;
        }
        r.push(s);
      }
      return r;
    }, t.prototype.makeTrainFunction = function() {
      var e = this;
      return function(r) {
        var i = [], a = r.slice(0, e.inputs.length), s = r.slice(e.inputs.length, e.inputs.length + e.outputs.length), o = r.slice(e.inputs.length + e.outputs.length, e.inputs.length + e.outputs.length * 2), c = [], l = function() {
          for (var p = [], f = 0; f < e.inputs.length; ++f)
            p.push({key: e.inputs[f], value: a[f]});
          for (var m = new Yi(p), g = Ya(e.outputs, m, {training: true}), y, f = 0; f < e.lossFunctions.length; ++f) {
            var w = e.lossFunctions[f], b = w(s[f], g[f]);
            o[f] != null && (b = r7(b, o[f]));
            var L = v.mean(b);
            i.push(L), f === 0 ? y = b : y = v.add(y, b);
          }
          for (var f = 0; f < e.metricsTensors.length; ++f) {
            var x = void 0;
            if (e.outputs.length > 1 && f < e.outputs.length)
              x = i[f];
            else {
              var N = e.metricsTensors[f][0], I = e.metricsTensors[f][1];
              x = v.mean(N(s[I], g[I]));
            }
            v.keep(x), c.push(x);
          }
          return y = v.mean(y), e.calculateLosses().forEach(function(C) {
            y = v.add(y, C);
          }), y;
        }, u = e.collectedTrainableWeights.map(function(p) {
          return p.read();
        }), h = true, d = e.optimizer_.minimize(l, h, u);
        return [d].concat(c);
      };
    }, t.prototype.makeTestFunction = function() {
      var e = this;
      this.testFunction = function(r) {
        return v.tidy(function() {
          for (var i = [], a, s = r.slice(0, e.inputs.length), o = r.slice(e.inputs.length, e.inputs.length + e.outputs.length), c = [], l = 0; l < e.inputs.length; ++l)
            c.push({key: e.inputs[l], value: s[l]});
          for (var u = new Yi(c), h = Ya(e.outputs, u), l = 0; l < e.lossFunctions.length; ++l) {
            var d = e.lossFunctions[l], p = v.mean(d(o[l], h[l]));
            l === 0 ? a = p : a = v.add(a, p), i.push(a);
          }
          for (var l = 0; l < e.metricsTensors.length; ++l) {
            var f = e.metricsTensors[l][0], m = e.metricsTensors[l][1], g = v.mean(f(o[m], h[m]));
            i.push(g);
          }
          return i;
        });
      };
    }, t.prototype.fit = function(e, r, i) {
      return i === void 0 && (i = {}), Ae(this, void 0, void 0, function() {
        return xe(this, function(a) {
          return [2, h7(this, e, r, i)];
        });
      });
    }, t.prototype.fitDataset = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(i) {
          return [2, o7(this, e, r)];
        });
      });
    }, t.prototype.trainOnBatch = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        var i, a, s, o, c, l, u, h, d, p;
        return xe(this, function(f) {
          switch (f.label) {
            case 0:
              return [4, this.standardizeUserData(e, r)];
            case 1:
              i = f.sent(), a = i[0], s = i[1], o = this.makeTrainFunction(), c = o(a.concat(s)), l = [], u = 0, h = c, f.label = 2;
            case 2:
              return u < h.length ? (d = h[u], [4, d.data()]) : [3, 5];
            case 3:
              p = f.sent(), l.push(p[0]), f.label = 4;
            case 4:
              return u++, [3, 2];
            case 5:
              return v.dispose(c), [2, Vt(l)];
          }
        });
      });
    }, t.prototype.getNamedWeights = function(e) {
      for (var r = [], i = e != null && e.trainableOnly, a = i ? this.trainableWeights : this.weights, s = this.getWeights(i), o = 0; o < a.length; ++o) {
        if (i && !a[o].trainable)
          continue;
        r.push({name: a[o].originalName, tensor: s[o]});
      }
      return r;
    }, Object.defineProperty(t.prototype, "stopTraining", {get: function() {
      return this.stopTraining_;
    }, set: function(e) {
      this.stopTraining_ = e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "optimizer", {get: function() {
      return this.optimizer_;
    }, set: function(e) {
      this.optimizer_ !== e && (this.optimizer_ = e, this.isOptimizerOwned = false);
    }, enumerable: true, configurable: true}), t.prototype.dispose = function() {
      var e = n.prototype.dispose.call(this);
      if (e.refCountAfterDispose === 0 && this.optimizer != null && this.isOptimizerOwned) {
        var r = v.memory().numTensors;
        this.optimizer_.dispose(), e.numDisposedVariables += r - v.memory().numTensors;
      }
      return e;
    }, t.prototype.getLossIdentifiers = function() {
      var e;
      if (typeof this.loss == "string")
        e = Zn(this.loss);
      else if (Array.isArray(this.loss)) {
        for (var r = 0, i = this.loss; r < i.length; r++) {
          var a = i[r];
          if (typeof a != "string")
            throw new Error("Serialization of non-string loss is not supported.");
        }
        e = this.loss.map(function(h) {
          return Zn(h);
        });
      } else {
        var s = Object.keys(this.loss);
        e = {};
        for (var o = this.loss, c = 0, l = s; c < l.length; c++) {
          var u = l[c];
          if (typeof o[u] == "string")
            e[u] = Zn(o[u]);
          else
            throw new Error("Serialization of non-string loss is not supported.");
        }
      }
      return e;
    }, t.prototype.getMetricIdentifiers = function() {
      if (typeof this.metrics == "string" || typeof this.metrics == "function")
        return [Zn(Ro(this.metrics))];
      if (Array.isArray(this.metrics))
        return this.metrics.map(function(i) {
          return Zn(Ro(i));
        });
      var e = {};
      for (var r in this.metrics)
        e[r] = Zn(Ro(this.metrics[r]));
      return e;
    }, t.prototype.getTrainingConfig = function() {
      return {loss: this.getLossIdentifiers(), metrics: this.getMetricIdentifiers(), optimizer_config: {class_name: this.optimizer.getClassName(), config: this.optimizer.getConfig()}};
    }, t.prototype.loadTrainingConfig = function(e) {
      if (e.weighted_metrics != null)
        throw new Error("Loading weight_metrics is not supported yet.");
      if (e.loss_weights != null)
        throw new Error("Loading loss_weights is not supported yet.");
      if (e.sample_weight_mode != null)
        throw new Error("Loading sample_weight_mode is not supported yet.");
      var r = qa(e.optimizer_config), i = Sn(r), a;
      if (typeof e.loss == "string")
        a = ti(e.loss);
      else if (Array.isArray(e.loss))
        a = e.loss.map(function(c) {
          return ti(c);
        });
      else if (e.loss != null) {
        a = {};
        for (var s in e.loss)
          a[s] = ti(e.loss[s]);
      }
      var o;
      if (Array.isArray(e.metrics))
        o = e.metrics.map(function(c) {
          return ti(c);
        });
      else if (e.metrics != null) {
        o = {};
        for (var s in e.metrics)
          o[s] = ti(e.metrics[s]);
      }
      this.compile({loss: a, metrics: o, optimizer: i});
    }, t.prototype.save = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        var i, a, s, o, c, l, u, h, d, p, f, m, g, y, w;
        return xe(this, function(b) {
          switch (b.label) {
            case 0:
              if (typeof e == "string") {
                if (i = v.io.getSaveHandlers(e), i.length === 0)
                  throw new M("Cannot find any save handlers for URL '" + e + "'");
                if (i.length > 1)
                  throw new M("Found more than one (" + i.length + ") save handlers for " + ("URL '" + e + "'"));
                e = i[0];
              }
              if (e.save == null)
                throw new M("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");
              return [4, v.io.encodeWeights(this.getNamedWeights(r))];
            case 1:
              return a = b.sent(), s = false, o = null, c = this.toJSON(o, s), l = {modelTopology: c, format: g7, generatedBy: "TensorFlow.js tfjs-layers v" + $h, convertedBy: null}, u = r == null ? false : r.includeOptimizer, u && this.optimizer != null ? (l.trainingConfig = this.getTrainingConfig(), h = "optimizer", g = (m = v.io).encodeWeights, [4, this.optimizer.getWeights()]) : [3, 4];
            case 2:
              return [4, g.apply(m, [b.sent(), h])];
            case 3:
              d = b.sent(), p = d.data, f = d.specs, (w = a.specs).push.apply(w, f), a.data = v.io.concatenateArrayBuffers([a.data, p]), b.label = 4;
            case 4:
              return this.userDefinedMetadata != null && (y = true, Gy(this.userDefinedMetadata, this.name, y), l.userDefinedMetadata = this.userDefinedMetadata), l.weightData = a.data, l.weightSpecs = a.specs, [2, e.save(l)];
          }
        });
      });
    }, t.prototype.setUserDefinedMetadata = function(e) {
      Gy(e, this.name), this.userDefinedMetadata = e;
    }, t.prototype.getUserDefinedMetadata = function() {
      return this.userDefinedMetadata;
    }, t.className = "Model", t;
  }(t7);
  v.serialization.registerClass(Sr);
  var y7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.className = "Functional", t;
  }(Sr);
  v.serialization.registerClass(y7);
  function v7(n, t) {
    return Ae(this, void 0, void 0, function() {
      var e, r, i, a, s, o, c, l;
      return xe(this, function(u) {
        switch (u.label) {
          case 0:
            return "modelTopology" in n || (n = {modelTopology: n}), n = n, e = n.modelTopology, e.model_config != null && (e = e.model_config), r = qa(e), i = Sn(r, t), n.weightsManifest != null ? [4, v.io.loadWeights(n.weightsManifest, n.pathPrefix, i.weights.map(function(h) {
              return h.originalName;
            }))] : [3, 2];
          case 1:
            for (a = u.sent(), s = {}, o = 0, c = i.weights; o < c.length; o++)
              l = c[o], s[l.originalName] = a[l.originalName];
            i.loadWeights(s), v.dispose(a), u.label = 2;
          case 2:
            return [2, i];
        }
      });
    });
  }
  function b7(n, t) {
    return Ae(this, void 0, void 0, function() {
      var e;
      return xe(this, function(r) {
        if (t == null && (t = {}), typeof n == "string") {
          if (e = v.io.getLoadHandlers(n, t), e.length === 0)
            e.push(v.io.browserHTTPRequest(n, t));
          else if (e.length > 1)
            throw new M("Found more than one (" + e.length + ") load handlers for " + ("URL '" + n + "'"));
          n = e[0];
        }
        return [2, w7(n, void 0, t)];
      });
    });
  }
  function w7(n, t, e) {
    return Ae(this, void 0, void 0, function() {
      var r, i, a, s, o, c, l, u, h;
      return xe(this, function(d) {
        switch (d.label) {
          case 0:
            if (e == null && (e = {}), n.load == null)
              throw new M("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");
            return [4, n.load()];
          case 1:
            if (r = d.sent(), i = r.modelTopology, i.model_config != null && (i = i.model_config), a = e.strict == null ? true : e.strict, s = r.weightData != null && r.weightSpecs != null && a, o = Sn(qa(i), t, s), c = r.trainingConfig, c != null && o.loadTrainingConfig(c), r.userDefinedMetadata != null && o.setUserDefinedMetadata(r.userDefinedMetadata), !(r.weightData != null))
              return [3, 4];
            if (r.weightSpecs == null)
              throw new M("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");
            return l = x7(r.weightData, r.weightSpecs), u = l.modelWeights, h = l.optimizerWeights, o.loadWeights(u, a), o.optimizer != null && h.length > 0 ? [4, o.optimizer.setWeights(h)] : [3, 3];
          case 2:
            d.sent(), d.label = 3;
          case 3:
            v.dispose(u), v.dispose(h.map(function(p) {
              return p.tensor;
            })), d.label = 4;
          case 4:
            return [2, o];
        }
      });
    });
  }
  function x7(n, t) {
    var e = v.io.decodeWeights(n, t), r = {}, i = [];
    return t.forEach(function(a) {
      a.group === "optimizer" ? i.push({name: a.name, tensor: e[a.name]}) : r[a.name] = e[a.name];
    }), {modelWeights: r, optimizerWeights: i};
  }
  var td = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, {inputs: [], outputs: []}) || this;
      if (e = e || {}, r.trainable = true, r.built = false, r.name = e.name != null ? e.name : bo("sequential_"), e.layers != null)
        for (var i = 0, a = e.layers; i < a.length; i++) {
          var s = a[i];
          r.add(s);
        }
      return r;
    }
    return t.prototype.checkShape = function(e) {
      var r = e.inboundNodes[0].outputTensors[0].shape;
      if (r.some(function(i) {
        return i < 0;
      }))
        throw new M("Negative dimension size caused by adding layer " + (e.name + " with input shape [") + (e.inboundNodes[0].inputTensors[0].shape + "]"));
    }, t.prototype.add = function(e) {
      var r = e instanceof t || e instanceof Sr, i;
      if (r) {
        if (i = e, i.outputs.length !== 1)
          throw new M("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");
        if (i.inputs.length !== 1)
          throw new M("All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.");
      }
      if (this.outputs.length === 0) {
        if (e.inboundNodes.length === 0) {
          if (e.batchInputShape == null)
            throw new M("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");
          var a = Cy({batchShape: e.batchInputShape, dtype: e.dtype, name: e.name + "_input"});
          e.apply(a);
        }
        if (r)
          this.outputs = i.outputs, this.inputs = i.inputs;
        else {
          if (e.inboundNodes.length !== 1)
            throw new M("A layer added to a Sequential model must not already be " + ("connected somewhere else. LayersModel received layer " + e.name + " ") + ("which has " + e.inboundNodes.length + " pre-existing inbound ") + "connections.");
          if (e.inboundNodes[0].outputTensors.length !== 1)
            throw new M("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");
          this.checkShape(e), this.outputs = [e.inboundNodes[0].outputTensors[0]], this.inputs = _y(this.outputs[0]);
        }
        this.inboundNodes = [], new So({outboundLayer: this, inboundLayers: [], nodeIndices: [], tensorIndices: [], inputTensors: this.inputs, outputTensors: this.outputs, inputMasks: ei(null, this.inputs.length), outputMasks: [null], inputShapes: this.inputs.map(function(o) {
          return o.shape;
        }), outputShapes: this.outputs[0].shape});
      } else {
        var s = e.apply(this.outputs[0]);
        if (Array.isArray(s))
          throw new TypeError("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");
        this.checkShape(e), this.outputs = [s], this.inboundNodes[0].outputTensors = this.outputs, this.inboundNodes[0].outputShapes = [this.outputs[0].shape];
      }
      this.layers.push(e), this.built = false;
    }, t.prototype.pop = function() {
      if (this.layers.length === 0)
        throw new TypeError("There are no layers in the model.");
      if (this.layers.pop(), this.layers.length === 0)
        this.outputs = [], this.inboundNodes = [], this.outboundNodes = [];
      else {
        var e = this.layers.length - 1;
        this.layers[e].outboundNodes = [], this.outputs = [this.layers[e].output], this.inboundNodes[0].outputTensors = this.outputs, this.inboundNodes[0].outputShapes = [this.outputs[0].shape];
      }
    }, t.prototype.call = function(e, r) {
      return this.model == null && this.build(), this.model.call(e, r);
    }, t.prototype.build = function(e) {
      if (Xe(e), this.inputs.length === 0 || this.outputs.length === 0)
        throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");
      this.model = new Sr({inputs: this.inputs, outputs: this.outputs[0], name: this.name + "_model"}), this.model.trainable = this.trainable, this.supportsMasking = this.model.supportsMasking, this.inputLayers = this.model.inputLayers, this.inputLayersNodeIndices = this.model.inputLayersNodeIndices, this.inputLayersTensorIndices = this.model.inputLayersTensorIndices, this.outputLayers = this.model.outputLayers, this.outputLayersNodeIndices = this.model.outputLayersNodeIndices, this.outputLayersTensorIndices = this.model.outputLayersTensorIndices, this.nodesByDepth = this.model.nodesByDepth, this.containerNodes = this.model.containerNodes, this.outputNames = this.model.outputNames, this.inputNames = this.model.inputNames, this.built = true;
    }, t.prototype.countParams = function() {
      return this.built || this.build(), n.prototype.countParams.call(this);
    }, t.prototype.summary = function(e, r, i) {
      i === void 0 && (i = console.log), this.built || this.build(), n.prototype.summary.call(this, e, r, i);
    }, t.prototype.setWeights = function(e) {
      this.model == null && this.build(), this.model.setWeights(e);
    }, t.prototype.evaluate = function(e, r, i) {
      if (i === void 0 && (i = {}), !this.built)
        throw new Fn("The model needs to be compiled before being used.");
      return this.model.evaluate(e, r, i);
    }, t.prototype.evaluateDataset = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(i) {
          if (!this.built)
            throw new Fn("The model needs to be compiled before being used.");
          return [2, this.model.evaluateDataset(e, r)];
        });
      });
    }, t.prototype.predict = function(e, r) {
      return r === void 0 && (r = {}), this.model == null && this.build(), this.model.predict(e, r);
    }, t.prototype.predictOnBatch = function(e) {
      return this.model == null && this.build(), this.model.predictOnBatch(e);
    }, t.prototype.compile = function(e) {
      this.build(), this.model.compile(e), this.optimizer_ = this.model.optimizer, this.isOptimizerOwned = this.model.isOptimizerOwned, this.loss = this.model.loss, this.metrics = this.model.metrics, this.metricsTensors = this.model.metricsTensors, this.metricsNames = this.model.metricsNames;
    }, Object.defineProperty(t.prototype, "optimizer", {get: function() {
      return this.model == null ? void 0 : this.model.optimizer;
    }, set: function(e) {
      this.model.optimizer = e;
    }, enumerable: true, configurable: true}), t.prototype.fit = function(e, r, i) {
      return i === void 0 && (i = {}), Ae(this, void 0, void 0, function() {
        return xe(this, function(a) {
          if (!this.built)
            throw new Fn("The model needs to be compiled before being used.");
          return [2, this.model.fit(e, r, i)];
        });
      });
    }, t.prototype.fitDataset = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(i) {
          if (!this.built)
            throw new Fn("The model needs to be compiled before being used.");
          return [2, this.model.fitDataset(e, r)];
        });
      });
    }, t.prototype.trainOnBatch = function(e, r) {
      return Ae(this, void 0, void 0, function() {
        return xe(this, function(i) {
          return [2, this.model.trainOnBatch(e, r)];
        });
      });
    }, t.fromConfig = function(e, r, i, a) {
      a === void 0 && (a = false);
      var s, o = {};
      if (r instanceof Array) {
        if (!(r[0].className != null) || r[0].className === "Merge")
          throw new M("Legacy serialization format not supported yet.");
        s = r;
      } else
        v.util.assert(r.layers != null, function() {
          return "When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field.";
        }), s = r.layers, delete r.layers, o = r;
      var c = new e(o);
      if (!(c instanceof t))
        throw new Re("Sequential.fromConfig called on non-Sequential input: " + c);
      for (var l = 0, u = s; l < u.length; l++) {
        var h = u[l], d = void 0, p = Sn(h, d, a);
        a && p.setFastWeightInitDuringBuild(true), c.add(p);
      }
      return c;
    }, Object.defineProperty(t.prototype, "stopTraining", {get: function() {
      if (this.model == null)
        throw new M("Cannot get the stopTraining property of a sequential model before it is compiled.");
      return this.model.stopTraining;
    }, set: function(e) {
      if (this.model == null)
        throw new M("Cannot set the stopTraining property of a sequential model before it is compiled.");
      this.model.stopTraining = e;
    }, enumerable: true, configurable: true}), t.prototype.getConfig = function() {
      for (var e = [], r = 0, i = this.layers; r < i.length; r++) {
        var a = i[r], s = {};
        s.className = a.getClassName(), s.config = a.getConfig(), e.push(s);
      }
      return {name: this.name, layers: e};
    }, t.className = "Sequential", t;
  }(Sr);
  v.serialization.registerClass(td);
  function L7(n) {
    return new Sr(n);
  }
  function S7(n) {
    return new td(n);
  }
  function I7(n, t) {
    return t == null && (t = {}), b7(n, t);
  }
  function rv(n) {
    return Cy(n);
  }
  function A7(n, t) {
    Wy.registerCallbackConstructor(n, t);
  }
  var Jt = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.getConfig = function() {
      return {};
    }, t;
  }(v.serialization.Serializable), T7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e, r) {
      return r === void 0 && (r = 1), jO(e, r);
    }, t.className = "elu", t;
  }(Jt);
  v.serialization.registerClass(T7);
  var N7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return v.selu(e);
    }, t.className = "selu", t;
  }(Jt);
  v.serialization.registerClass(N7);
  var _7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return v.relu(e);
    }, t.className = "relu", t;
  }(Jt);
  v.serialization.registerClass(_7);
  var C7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return v.tidy(function() {
        return v.minimum(6, v.relu(e));
      });
    }, t.className = "relu6", t;
  }(Jt);
  v.serialization.registerClass(C7);
  var R7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return e;
    }, t.className = "linear", t;
  }(Jt);
  v.serialization.registerClass(R7);
  var O7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return v.sigmoid(e);
    }, t.className = "sigmoid", t;
  }(Jt);
  v.serialization.registerClass(O7);
  var E7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return XO(e);
    }, t.className = "hardSigmoid", t;
  }(Jt);
  v.serialization.registerClass(E7);
  var D7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return v.softplus(e);
    }, t.className = "softplus", t;
  }(Jt);
  v.serialization.registerClass(D7);
  var k7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return $O(e);
    }, t.className = "softsign", t;
  }(Jt);
  v.serialization.registerClass(k7);
  var F7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e) {
      return v.tanh(e);
    }, t.className = "tanh", t;
  }(Jt);
  v.serialization.registerClass(F7);
  var iv = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e, r) {
      return r === void 0 && (r = -1), v.softmax(e, r);
    }, t.className = "softmax", t;
  }(Jt);
  v.serialization.registerClass(iv);
  var W7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e, r) {
      return r === void 0 && (r = -1), v.logSoftmax(e, r);
    }, t.className = "logSoftmax", t;
  }(Jt);
  v.serialization.registerClass(W7);
  var U7 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.apply = function(e, r) {
      return r === void 0 && (r = 1), v.tidy(function() {
        return v.sigmoid(e.mul(r)).mul(e);
      });
    }, t.className = "swish", t;
  }(Jt);
  v.serialization.registerClass(U7);
  function Ir(n) {
    return n.getClassName();
  }
  function nd(n, t) {
    return t === void 0 && (t = {}), Wa(n, v.serialization.SerializationMap.getMap().classNameMap, t, "activation");
  }
  function Ar(n) {
    if (n == null) {
      var t = {};
      return t.className = "linear", t.config = {}, nd(t);
    }
    if (typeof n == "string") {
      var t = {};
      return t.className = n, t.config = {}, nd(t);
    } else
      return n instanceof Jt ? n : nd(n);
  }
  function rd(n) {
    if (n != null && typeof n != "object")
      throw new Error("Argument to L1L2 regularizer's constructor is expected to be an " + ("object, but received: " + n));
  }
  var av = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t;
  }(v.serialization.Serializable), Eo = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return rd(e), r.l1 = e == null || e.l1 == null ? 0.01 : e.l1, r.l2 = e == null || e.l2 == null ? 0.01 : e.l2, r.hasL1 = r.l1 !== 0, r.hasL2 = r.l2 !== 0, r;
    }
    return t.prototype.apply = function(e) {
      var r = this;
      return v.tidy(function() {
        var i = v.zeros([1]);
        return r.hasL1 && (i = v.add(i, v.sum(v.mul(r.l1, v.abs(e))))), r.hasL2 && (i = v.add(i, v.sum(v.mul(r.l2, Ma(e))))), i.asScalar();
      });
    }, t.prototype.getConfig = function() {
      return {l1: this.l1, l2: this.l2};
    }, t.fromConfig = function(e, r) {
      return new e({l1: r.l1, l2: r.l2});
    }, t.className = "L1L2", t;
  }(av);
  v.serialization.registerClass(Eo);
  function B7(n) {
    return rd(n), new Eo({l1: n != null ? n.l1 : null, l2: 0});
  }
  function z7(n) {
    return rd(n), new Eo({l2: n != null ? n.l2 : null, l1: 0});
  }
  var sv = {l1l2: "L1L2"};
  function Je(n) {
    return Ih(n);
  }
  function ov(n, t) {
    return t === void 0 && (t = {}), Wa(n, v.serialization.SerializationMap.getMap().classNameMap, t, "regularizer");
  }
  function st(n) {
    if (n == null)
      return null;
    if (typeof n == "string") {
      var t = n in sv ? sv[n] : n, e = {className: t, config: {}};
      return ov(e);
    } else
      return n instanceof av ? n : ov(n);
  }
  var cv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e == null ? {} : e) || this;
      return r.supportsMasking = true, e != null && (r.maxValue = e.maxValue), r;
    }
    return t.prototype.call = function(e, r) {
      e = Oe(e);
      var i = v.relu(e);
      return this.maxValue != null && (i = v.clipByValue(i, 0, this.maxValue)), i;
    }, t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = {maxValue: this.maxValue}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "ReLU", t;
  }(Fe);
  v.serialization.registerClass(cv);
  var lv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e == null ? {} : e) || this;
      return r.DEFAULT_ALPHA = 0.3, e == null && (e = {}), r.alpha = e.alpha == null ? r.DEFAULT_ALPHA : e.alpha, r;
    }
    return t.prototype.call = function(e, r) {
      var i = Oe(e);
      return v.leakyRelu(i, this.alpha);
    }, t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = {alpha: this.alpha}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "LeakyReLU", t;
  }(Fe);
  v.serialization.registerClass(lv);
  var uv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e == null ? {} : e) || this;
      if (r.DEFAULT_ALPHA_INITIALIZER = "zeros", e == null && (e = {}), r.supportsMasking = true, r.alphaInitializer = at(e.alphaInitializer || r.DEFAULT_ALPHA_INITIALIZER), r.alphaRegularizer = st(e.alphaRegularizer), r.alphaConstraint = At(e.alphaConstraint), e.sharedAxes == null)
        r.sharedAxes = null;
      else if (Array.isArray(e.sharedAxes))
        r.sharedAxes = e.sharedAxes;
      else if (typeof e.sharedAxes == "number")
        r.sharedAxes = [e.sharedAxes];
      else
        throw new M("Expected sharedAxes to be a number or an array of numbers, " + ("but got " + e.sharedAxes));
      return r;
    }
    return t.prototype.build = function(e) {
      e = Xe(e);
      var r = e.slice(1);
      if (this.sharedAxes != null)
        for (var i = 0, a = this.sharedAxes; i < a.length; i++) {
          var s = a[i];
          r[s - 1] = 1;
        }
      this.alpha = this.addWeight("alpha", r, "float32", this.alphaInitializer, this.alphaRegularizer, true, this.alphaConstraint);
      var o = {};
      if (this.sharedAxes != null)
        for (var s = 1; s < e.length; ++s)
          o[s] = e[s];
      this.inputSpec = [new Ct({ndim: e.length, axes: o})], this.built = true;
    }, t.prototype.call = function(e, r) {
      return e = Oe(e), v.prelu(e, this.alpha.read());
    }, t.prototype.getConfig = function() {
      var e = {alphaInitializer: lt(this.alphaInitializer), alphaRegularizer: Je(this.alphaRegularizer), alphaConstraint: It(this.alphaConstraint), sharedAxes: this.sharedAxes}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "PReLU", t;
  }(Fe);
  v.serialization.registerClass(uv);
  var hv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e == null ? {} : e) || this;
      if (r.DEFAULT_ALPHA = 1, e == null && (e = {}), e.alpha != null && e.alpha !== r.DEFAULT_ALPHA)
        throw new Re("Non-default alpha value (" + e.alpha + ") is not supported by the ELU layer yet.");
      return r.alpha = e.alpha == null ? r.DEFAULT_ALPHA : e.alpha, r;
    }
    return t.prototype.call = function(e, r) {
      var i = Oe(e);
      return v.elu(i);
    }, t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = {alpha: this.alpha}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "ELU", t;
  }(Fe);
  v.serialization.registerClass(hv);
  var dv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e == null ? {} : e) || this;
      return r.DEFAULT_THETA = 1, e == null && (e = {}), r.theta = e.theta == null ? r.DEFAULT_THETA : e.theta, r;
    }
    return t.prototype.call = function(e, r) {
      var i = Oe(e);
      return i.mul(za(i.greater(this.theta), "float32"));
    }, t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = {theta: this.theta}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "ThresholdedReLU", t;
  }(Fe);
  v.serialization.registerClass(dv);
  var pv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e == null ? {} : e) || this;
      return r.DEFAULT_AXIS = 1, e == null && (e = {}), r.softmax = new iv().apply, r.axis = e.axis == null ? r.DEFAULT_AXIS : e.axis, r;
    }
    return t.prototype.call = function(e, r) {
      var i = Oe(e);
      return this.softmax(i, this.axis);
    }, t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = {axis: this.axis}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Softmax", t;
  }(Fe);
  v.serialization.registerClass(pv);
  function Ki(n, t, e) {
    if (typeof n == "number")
      return ei(n, t);
    if (n.length !== t)
      throw new M("The " + e + " argument must be an integer or tuple of " + t + " integers." + (" Received: " + n.length + " elements."));
    for (var r = 0; r < t; ++r) {
      var i = n[r];
      if (!GO(i))
        throw new M("The " + e + " argument must be an integer or tuple of " + t + (" integers. Received: " + JSON.stringify(n) + " including a") + (" non-integer number " + i));
    }
    return n;
  }
  function In(n, t, e, r, i) {
    if (i === void 0 && (i = 1), n == null)
      return n;
    var a = t + (t - 1) * (i - 1), s;
    return e === "same" ? s = n : s = n - a + 1, Math.floor((s + r - 1) / r);
  }
  function Do(n, t, e, r) {
    if (n == null)
      return null;
    if (r === "valid")
      n = n * t + xr([e - t, 0]);
    else if (r === "same")
      n = n * t;
    else
      throw new M("Unsupport padding mode: " + r + ".");
    return n;
  }
  function id(n, t) {
    return v.tidy(function() {
      return gt(t), t === "channelsFirst" ? v.transpose(n, [0, 2, 3, 1]) : n;
    });
  }
  function fv(n, t) {
    return v.tidy(function() {
      return gt(t), t === "channelsFirst" ? v.transpose(n, [0, 2, 3, 4, 1]) : n;
    });
  }
  function P7(n, t, e, r, i, a, s) {
    return r === void 0 && (r = 1), i === void 0 && (i = "valid"), s === void 0 && (s = 1), v.tidy(function() {
      if (a == null && (a = bn()), gt(a), n.shape.length !== 3)
        throw new M("The input of a conv1dWithBias operation should be 3, but is " + (n.shape.length + " instead."));
      if (t.shape.length !== 3)
        throw new M("The kernel for a conv1dWithBias operation should be 3, but is " + (t.shape.length + " instead"));
      if (e != null && e.shape.length !== 1)
        throw new M("The bias for a conv1dWithBias operation should be 1, but is " + (t.shape.length + " instead"));
      if (a === "channelsFirst" && (n = v.transpose(n, [0, 2, 1])), i === "causal")
        throw new Re("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");
      var o = v.conv1d(n, t, r, i === "same" ? "same" : "valid", "NWC", s);
      return e != null && (o = Bn(o, e)), o;
    });
  }
  function mv(n, t, e, r, i, a, s, o) {
    return r === void 0 && (r = [1, 1]), i === void 0 && (i = "valid"), o === void 0 && (o = null), v.tidy(function() {
      if (a == null && (a = bn()), gt(a), n.rank !== 3 && n.rank !== 4)
        throw new M("conv2dWithBiasActivation expects input to be of rank 3 or 4, " + ("but received " + n.rank + "."));
      if (t.rank !== 3 && t.rank !== 4)
        throw new M("conv2dWithBiasActivation expects kernel to be of rank 3 or 4, " + ("but received " + n.rank + "."));
      var c = id(n, a);
      if (i === "causal")
        throw new Re("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");
      return c = v.fused.conv2d({x: c, filter: t, strides: r, pad: i === "same" ? "same" : "valid", dilations: s, dataFormat: "NHWC", bias: e, activation: o}), a === "channelsFirst" && (c = v.transpose(c, [0, 3, 1, 2])), c;
    });
  }
  function M7(n, t, e, r, i, a, s) {
    return r === void 0 && (r = [1, 1, 1]), i === void 0 && (i = "valid"), v.tidy(function() {
      if (a == null && (a = bn()), gt(a), n.rank !== 4 && n.rank !== 5)
        throw new M("conv3dWithBias expects input to be of rank 4 or 5, but received " + (n.rank + "."));
      if (t.rank !== 4 && t.rank !== 5)
        throw new M("conv3dWithBias expects kernel to be of rank 4 or 5, but received " + (n.rank + "."));
      var o = fv(n, a);
      if (i === "causal")
        throw new Re("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");
      return o = v.conv3d(o, t, r, i === "same" ? "same" : "valid", "NDHWC", s), e != null && (o = Bn(o, e)), a === "channelsFirst" && (o = v.transpose(o, [0, 4, 1, 2, 3])), o;
    });
  }
  var gv = function(n) {
    Q(t, n);
    function t(e, r) {
      var i = n.call(this, r) || this;
      if (i.bias = null, i.DEFAULT_KERNEL_INITIALIZER = "glorotNormal", i.DEFAULT_BIAS_INITIALIZER = "zeros", t.verifyArgs(r), i.rank = e, _t(i.rank, "rank"), i.rank !== 1 && i.rank !== 2 && i.rank !== 3)
        throw new Re("Convolution layer for rank other than 1, 2, or 3 (" + i.rank + ") is not implemented yet.");
      if (i.kernelSize = Ki(r.kernelSize, e, "kernelSize"), i.strides = Ki(r.strides == null ? 1 : r.strides, e, "strides"), i.padding = r.padding == null ? "valid" : r.padding, sn(i.padding), i.dataFormat = r.dataFormat == null ? "channelsLast" : r.dataFormat, gt(i.dataFormat), i.activation = Ar(r.activation), i.useBias = r.useBias == null ? true : r.useBias, i.biasInitializer = at(r.biasInitializer || i.DEFAULT_BIAS_INITIALIZER), i.biasConstraint = At(r.biasConstraint), i.biasRegularizer = st(r.biasRegularizer), i.activityRegularizer = st(r.activityRegularizer), i.dilationRate = Ki(r.dilationRate == null ? 1 : r.dilationRate, e, "dilationRate"), i.rank === 1 && Array.isArray(i.dilationRate) && i.dilationRate.length !== 1)
        throw new M("dilationRate must be a number or an array of a single number for 1D convolution, but received " + ("" + JSON.stringify(i.dilationRate)));
      if (i.rank === 2) {
        if (typeof i.dilationRate == "number")
          i.dilationRate = [i.dilationRate, i.dilationRate];
        else if (i.dilationRate.length !== 2)
          throw new M("dilationRate must be a number or array of two numbers for 2D " + ("convolution, but received " + JSON.stringify(i.dilationRate)));
      } else if (i.rank === 3) {
        if (typeof i.dilationRate == "number")
          i.dilationRate = [i.dilationRate, i.dilationRate, i.dilationRate];
        else if (i.dilationRate.length !== 3)
          throw new M("dilationRate must be a number or array of three numbers for 3D " + ("convolution, but received " + JSON.stringify(i.dilationRate)));
      }
      return i;
    }
    return t.verifyArgs = function(e) {
      if (Wn("kernelSize" in e, "required key 'kernelSize' not in config"), typeof e.kernelSize != "number" && !Th(e.kernelSize, "number", 1, 3))
        throw new M("BaseConv expects config.kernelSize to be number or number[] with " + ("length 1, 2, or 3, but received " + JSON.stringify(e.kernelSize) + "."));
    }, t.prototype.getConfig = function() {
      var e = {kernelSize: this.kernelSize, strides: this.strides, padding: this.padding, dataFormat: this.dataFormat, dilationRate: this.dilationRate, activation: Ir(this.activation), useBias: this.useBias, biasInitializer: lt(this.biasInitializer), biasRegularizer: Je(this.biasRegularizer), activityRegularizer: Je(this.activityRegularizer), biasConstraint: It(this.biasConstraint)}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t;
  }(Fe), ko = function(n) {
    Q(t, n);
    function t(e, r) {
      var i = n.call(this, e, r) || this;
      return i.kernel = null, t.verifyArgs(r), i.filters = r.filters, _t(i.filters, "filters"), i.kernelInitializer = at(r.kernelInitializer || i.DEFAULT_KERNEL_INITIALIZER), i.kernelConstraint = At(r.kernelConstraint), i.kernelRegularizer = st(r.kernelRegularizer), i;
    }
    return t.prototype.build = function(e) {
      var r;
      e = Xe(e);
      var i = this.dataFormat === "channelsFirst" ? 1 : e.length - 1;
      if (e[i] == null)
        throw new M("The channel dimension of the input should be defined. " + ("Found " + e[i]));
      var a = e[i], s = this.kernelSize.concat([a, this.filters]);
      this.kernel = this.addWeight("kernel", s, null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint), this.useBias && (this.bias = this.addWeight("bias", [this.filters], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint)), this.inputSpec = [{ndim: this.rank + 2, axes: (r = {}, r[i] = a, r)}], this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        e = Oe(e);
        var a, s = i.bias == null ? null : i.bias.read(), o = ey(i.activation.getClassName());
        if (o != null && i.rank === 2)
          a = mv(e, i.kernel.read(), s, i.strides, i.padding, i.dataFormat, i.dilationRate, o);
        else {
          if (i.rank === 1)
            a = P7(e, i.kernel.read(), s, i.strides[0], i.padding, i.dataFormat, i.dilationRate[0]);
          else if (i.rank === 2)
            a = mv(e, i.kernel.read(), s, i.strides, i.padding, i.dataFormat, i.dilationRate);
          else if (i.rank === 3)
            a = M7(e, i.kernel.read(), s, i.strides, i.padding, i.dataFormat, i.dilationRate);
          else
            throw new Re("convolutions greater than 3D are not implemented yet.");
          i.activation != null && (a = i.activation.apply(a));
        }
        return a;
      });
    }, t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      for (var r = [], i = this.dataFormat === "channelsLast" ? e.slice(1, e.length - 1) : e.slice(2), a = 0; a < i.length; ++a) {
        var s = In(i[a], this.kernelSize[a], this.padding, this.strides[a], typeof this.dilationRate == "number" ? this.dilationRate : this.dilationRate[a]);
        r.push(s);
      }
      var o = [e[0]];
      return this.dataFormat === "channelsLast" ? (o = o.concat(r), o.push(this.filters)) : (o.push(this.filters), o = o.concat(r)), o;
    }, t.prototype.getConfig = function() {
      var e = {filters: this.filters, kernelInitializer: lt(this.kernelInitializer), kernelRegularizer: Je(this.kernelRegularizer), kernelConstraint: It(this.kernelConstraint)}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.verifyArgs = function(e) {
      if (!("filters" in e) || typeof e.filters != "number" || e.filters < 1)
        throw new M("Convolution layer expected config.filters to be a 'number' > 0 " + ("but got " + JSON.stringify(e.filters)));
    }, t;
  }(gv), ad = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, 2, e) || this;
      return t.verifyArgs(e), r;
    }
    return t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this);
      return delete e.rank, e;
    }, t.verifyArgs = function(e) {
      if (typeof e.kernelSize != "number" && !Th(e.kernelSize, "number", 1, 2))
        throw new M("Conv2D expects config.kernelSize to be number or number[] with " + ("length 1 or 2, but received " + JSON.stringify(e.kernelSize) + "."));
    }, t.className = "Conv2D", t;
  }(ko);
  v.serialization.registerClass(ad);
  var yv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, 3, e) || this;
      return t.verifyArgs(e), r;
    }
    return t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this);
      return delete e.rank, e;
    }, t.verifyArgs = function(e) {
      if (typeof e.kernelSize != "number" && !(Array.isArray(e.kernelSize) && (e.kernelSize.length === 1 || e.kernelSize.length === 3)))
        throw new M("Conv3D expects config.kernelSize to be number or" + (" [number, number, number], but received " + JSON.stringify(e.kernelSize) + "."));
    }, t.className = "Conv3D", t;
  }(ko);
  v.serialization.registerClass(yv);
  var vv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      if (r.inputSpec = [new Ct({ndim: 4})], r.padding !== "same" && r.padding !== "valid")
        throw new M("Conv2DTranspose currently supports only padding modes 'same' " + ("and 'valid', but received padding mode " + r.padding));
      return r;
    }
    return t.prototype.build = function(e) {
      var r;
      if (e = Xe(e), e.length !== 4)
        throw new M("Input should have rank 4; Received input shape: " + JSON.stringify(e));
      var i = this.dataFormat === "channelsFirst" ? 1 : e.length - 1;
      if (e[i] == null)
        throw new M("The channel dimension of the inputs should be defined. Found `None`.");
      var a = e[i], s = this.kernelSize.concat([this.filters, a]);
      this.kernel = this.addWeight("kernel", s, "float32", this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint), this.useBias && (this.bias = this.addWeight("bias", [this.filters], "float32", this.biasInitializer, this.biasRegularizer, true, this.biasConstraint)), this.inputSpec = [new Ct({ndim: 4, axes: (r = {}, r[i] = a, r)})], this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        var a = Oe(e);
        if (a.shape.length !== 4)
          throw new M("Conv2DTranspose.call() expects input tensor to be rank-4, but " + ("received a tensor of rank-" + a.shape.length));
        var s = a.shape, o = s[0], c, l;
        i.dataFormat === "channelsFirst" ? (c = 2, l = 3) : (c = 1, l = 2);
        var u = s[c], h = s[l], d = i.kernelSize[0], p = i.kernelSize[1], f = i.strides[0], m = i.strides[1], g = Do(u, f, d, i.padding), y = Do(h, m, p, i.padding), w = [o, g, y, i.filters];
        i.dataFormat !== "channelsLast" && (a = v.transpose(a, [0, 2, 3, 1]));
        var b = v.conv2dTranspose(a, i.kernel.read(), w, i.strides, i.padding);
        return i.dataFormat !== "channelsLast" && (b = v.transpose(b, [0, 3, 1, 2])), i.bias != null && (b = Bn(b, i.bias.read(), i.dataFormat)), i.activation != null && (b = i.activation.apply(b)), b;
      });
    }, t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r = e.slice(), i, a, s;
      this.dataFormat === "channelsFirst" ? (i = 1, a = 2, s = 3) : (i = 3, a = 1, s = 2);
      var o = this.kernelSize[0], c = this.kernelSize[1], l = this.strides[0], u = this.strides[1];
      return r[i] = this.filters, r[a] = Do(r[a], l, o, this.padding), r[s] = Do(r[s], u, c, this.padding), r;
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this);
      return delete e.dilationRate, e;
    }, t.className = "Conv2DTranspose", t;
  }(ad);
  v.serialization.registerClass(vv);
  var H7 = function(n) {
    Q(t, n);
    function t(e, r) {
      var i = n.call(this, e, r) || this;
      if (i.DEFAULT_DEPTHWISE_INITIALIZER = "glorotUniform", i.DEFAULT_POINTWISE_INITIALIZER = "glorotUniform", i.depthwiseKernel = null, i.pointwiseKernel = null, r.filters == null)
        throw new M("The `filters` configuration field is required by SeparableConv, but is unspecified.");
      if (r.kernelInitializer != null || r.kernelRegularizer != null || r.kernelConstraint != null)
        throw new M("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");
      if (r.padding != null && r.padding !== "same" && r.padding !== "valid")
        throw new M("SeparableConv" + i.rank + "D supports only padding modes: " + ("'same' and 'valid', but received " + JSON.stringify(r.padding)));
      return i.depthMultiplier = r.depthMultiplier == null ? 1 : r.depthMultiplier, i.depthwiseInitializer = at(r.depthwiseInitializer || i.DEFAULT_DEPTHWISE_INITIALIZER), i.depthwiseRegularizer = st(r.depthwiseRegularizer), i.depthwiseConstraint = At(r.depthwiseConstraint), i.pointwiseInitializer = at(r.depthwiseInitializer || i.DEFAULT_POINTWISE_INITIALIZER), i.pointwiseRegularizer = st(r.pointwiseRegularizer), i.pointwiseConstraint = At(r.pointwiseConstraint), i;
    }
    return t.prototype.build = function(e) {
      var r;
      if (e = Xe(e), e.length < this.rank + 2)
        throw new M("Inputs to SeparableConv" + this.rank + "D should have rank " + (this.rank + 2 + ", but received input shape: ") + ("" + JSON.stringify(e)));
      var i = this.dataFormat === "channelsFirst" ? 1 : e.length - 1;
      if (e[i] == null || e[i] < 0)
        throw new M("The channel dimension of the inputs should be defined, " + ("but found " + JSON.stringify(e[i])));
      for (var a = e[i], s = this.kernelSize.concat([a, this.depthMultiplier]), o = [], c = 0; c < this.rank; ++c)
        o.push(1);
      o.push(a * this.depthMultiplier, this.filters);
      var l = true;
      this.depthwiseKernel = this.addWeight("depthwise_kernel", s, "float32", this.depthwiseInitializer, this.depthwiseRegularizer, l, this.depthwiseConstraint), this.pointwiseKernel = this.addWeight("pointwise_kernel", o, "float32", this.pointwiseInitializer, this.pointwiseRegularizer, l, this.pointwiseConstraint), this.useBias ? this.bias = this.addWeight("bias", [this.filters], "float32", this.biasInitializer, this.biasRegularizer, l, this.biasConstraint) : this.bias = null, this.inputSpec = [new Ct({ndim: this.rank + 2, axes: (r = {}, r[i] = a, r)})], this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        e = Oe(e);
        var a;
        if (i.rank === 1)
          throw new Re("1D separable convolution is not implemented yet.");
        return i.rank === 2 && (i.dataFormat === "channelsFirst" && (e = v.transpose(e, [0, 2, 3, 1])), a = v.separableConv2d(e, i.depthwiseKernel.read(), i.pointwiseKernel.read(), i.strides, i.padding, i.dilationRate, "NHWC")), i.useBias && (a = Bn(a, i.bias.read(), i.dataFormat)), i.activation != null && (a = i.activation.apply(a)), i.dataFormat === "channelsFirst" && (a = v.transpose(a, [0, 3, 1, 2])), a;
      });
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this);
      return delete e.rank, delete e.kernelInitializer, delete e.kernelRegularizer, delete e.kernelConstraint, e.depthwiseInitializer = lt(this.depthwiseInitializer), e.pointwiseInitializer = lt(this.pointwiseInitializer), e.depthwiseRegularizer = Je(this.depthwiseRegularizer), e.pointwiseRegularizer = Je(this.pointwiseRegularizer), e.depthwiseConstraint = It(this.depthwiseConstraint), e.pointwiseConstraint = It(this.pointwiseConstraint), e;
    }, t.className = "SeparableConv", t;
  }(ko), wv = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, 2, e) || this;
    }
    return t.className = "SeparableConv2D", t;
  }(H7);
  v.serialization.registerClass(wv);
  var bv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, 1, e) || this;
      return t.verifyArgs(e), r.inputSpec = [{ndim: 3}], r;
    }
    return t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this);
      return delete e.rank, delete e.dataFormat, e;
    }, t.verifyArgs = function(e) {
      if (typeof e.kernelSize != "number" && !Th(e.kernelSize, "number", 1, 1))
        throw new M("Conv1D expects config.kernelSize to be number or number[] with " + ("length 1, but received " + JSON.stringify(e.kernelSize) + "."));
    }, t.className = "Conv1D", t;
  }(ko);
  v.serialization.registerClass(bv);
  var xv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return typeof e.cropping == "number" ? r.cropping = [[e.cropping, e.cropping], [e.cropping, e.cropping]] : typeof e.cropping[0] == "number" ? r.cropping = [[e.cropping[0], e.cropping[0]], [e.cropping[1], e.cropping[1]]] : r.cropping = e.cropping, r.dataFormat = e.dataFormat === void 0 ? "channelsLast" : e.dataFormat, r.inputSpec = [{ndim: 4}], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      return this.dataFormat === "channelsFirst" ? [e[0], e[1], e[2] - this.cropping[0][0] - this.cropping[0][1], e[3] - this.cropping[1][0] - this.cropping[1][1]] : [e[0], e[1] - this.cropping[0][0] - this.cropping[0][1], e[2] - this.cropping[1][0] - this.cropping[1][1], e[3]];
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (e = Oe(e), i.dataFormat === "channelsLast") {
          var a = yo(e, i.cropping[0][0], e.shape[1] - i.cropping[0][0] - i.cropping[0][1], 2);
          return yo(a, i.cropping[1][0], e.shape[2] - i.cropping[1][1] - i.cropping[1][0], 3);
        } else {
          var a = yo(e, i.cropping[0][0], e.shape[2] - i.cropping[0][0] - i.cropping[0][1], 3);
          return yo(a, i.cropping[1][0], e.shape[3] - i.cropping[1][1] - i.cropping[1][0], 4);
        }
      });
    }, t.prototype.getConfig = function() {
      var e = {cropping: this.cropping, dataFormat: this.dataFormat}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Cropping2D", t;
  }(Fe);
  v.serialization.registerClass(xv);
  var Lv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.DEFAULT_SIZE = [2, 2], r.inputSpec = [{ndim: 4}], r.size = e.size == null ? r.DEFAULT_SIZE : e.size, r.dataFormat = e.dataFormat == null ? "channelsLast" : e.dataFormat, r;
    }
    return t.prototype.computeOutputShape = function(e) {
      if (this.dataFormat === "channelsFirst") {
        var r = e[2] == null ? null : this.size[0] * e[2], i = e[3] == null ? null : this.size[1] * e[3];
        return [e[0], e[1], r, i];
      } else {
        var r = e[1] == null ? null : this.size[0] * e[1], i = e[2] == null ? null : this.size[1] * e[2];
        return [e[0], r, i, e[3]];
      }
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        var a = Oe(e), s = a.shape;
        if (i.dataFormat === "channelsFirst") {
          a = v.transpose(a, [0, 2, 3, 1]);
          var o = i.size[0] * s[2], c = i.size[1] * s[3], l = a.resizeNearestNeighbor([o, c]);
          return v.transpose(l, [0, 3, 1, 2]);
        } else {
          var o = i.size[0] * s[1], c = i.size[1] * s[2];
          return a.resizeNearestNeighbor([o, c]);
        }
      });
    }, t.prototype.getConfig = function() {
      var e = {size: this.size, dataFormat: this.dataFormat}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "UpSampling2D", t;
  }(Fe);
  v.serialization.registerClass(Lv);
  function V7(n, t, e, r, i, a) {
    return e === void 0 && (e = [1, 1]), r === void 0 && (r = "valid"), v.tidy(function() {
      i == null && (i = bn()), gt(i);
      var s = id(n, i);
      if (n.rank !== 4)
        throw new M("Input for depthwiseConv2d is required to be 4-D, but is instead " + (n.rank + "-D"));
      if (t.rank !== 4)
        throw new M("depthwiseKernel is required to be 4-D, but is instead " + (t.rank + "-D"));
      return s = v.depthwiseConv2d(s, t, e, r === "same" ? "same" : "valid", "NHWC", a), i === "channelsFirst" && (s = v.transpose(s, [0, 3, 1, 2])), s;
    });
  }
  var Sv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, 2, e) || this;
      return r.depthwiseKernel = null, r.depthMultiplier = e.depthMultiplier == null ? 1 : e.depthMultiplier, r.depthwiseInitializer = at(e.depthwiseInitializer || r.DEFAULT_KERNEL_INITIALIZER), r.depthwiseConstraint = At(e.depthwiseConstraint), r.depthwiseRegularizer = st(e.depthwiseRegularizer), r;
    }
    return t.prototype.build = function(e) {
      if (e = Xe(e), e.length < 4)
        throw new M("Inputs to DepthwiseConv2D should have rank 4. " + ("Received input shape: " + JSON.stringify(e) + "."));
      var r = this.dataFormat === "channelsFirst" ? 1 : 3;
      if (e[r] == null || e[r] < 0)
        throw new M("The channel dimension of the inputs to DepthwiseConv2D should " + ("be defined, but is not (" + e[r] + ")."));
      var i = e[r], a = [this.kernelSize[0], this.kernelSize[1], i, this.depthMultiplier];
      this.depthwiseKernel = this.addWeight("depthwise_kernel", a, null, this.depthwiseInitializer, this.depthwiseRegularizer, true, this.depthwiseConstraint), this.useBias ? this.bias = this.addWeight("bias", [i * this.depthMultiplier], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint) : this.bias = null, this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        e = Oe(e);
        var a = V7(e, i.depthwiseKernel.read(), i.strides, i.padding, i.dataFormat, null);
        return i.useBias && (a = Bn(a, i.bias.read(), i.dataFormat)), i.activation != null && (a = i.activation.apply(a)), a;
      });
    }, t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r = this.dataFormat === "channelsFirst" ? e[2] : e[1], i = this.dataFormat === "channelsFirst" ? e[3] : e[2], a = this.dataFormat === "channelsFirst" ? e[1] * this.depthMultiplier : e[3] * this.depthMultiplier, s = In(r, this.kernelSize[0], this.padding, this.strides[0]), o = In(i, this.kernelSize[1], this.padding, this.strides[1]);
      return this.dataFormat === "channelsFirst" ? [e[0], a, s, o] : [e[0], s, o, a];
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this);
      return e.depthMultiplier = this.depthMultiplier, e.depthwiseInitializer = lt(this.depthwiseInitializer), e.depthwiseRegularizer = Je(this.depthwiseRegularizer), e.depthwiseConstraint = It(this.depthwiseRegularizer), e;
    }, t.className = "DepthwiseConv2D", t;
  }(gv);
  v.serialization.registerClass(Sv);
  function Iv(n, t, e, r) {
    if (Array.isArray(n)) {
      if (t != null || e != null)
        throw new M("When inputs is an array, neither initialState or constants should be provided");
      r != null && (e = n.slice(n.length - r, n.length), n = n.slice(0, n.length - r)), n.length > 1 && (t = n.slice(1, n.length)), n = n[0];
    }
    function i(a) {
      return a == null || Array.isArray(a) ? a : [a];
    }
    return t = i(t), e = i(e), {inputs: n, initialState: t, constants: e};
  }
  function Av(n, t, e, r, i, a, s, o) {
    return r === void 0 && (r = false), s === void 0 && (s = false), o === void 0 && (o = false), v.tidy(function() {
      var c = t.shape.length;
      if (c < 3)
        throw new M("Input should be at least 3D, but is " + c + "D.");
      var l = [1, 0].concat(xn(2, c));
      if (t = v.transpose(t, l), a != null)
        throw new Re("The rnn() functoin of the deeplearn.js backend does not support constants yet.");
      s && console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."), i != null && (i = i.asType("bool").asType("float32"), i.rank === c - 1 && (i = v.expandDims(i, -1)), i = v.transpose(i, l)), r && (t = v.reverse(t, 0), i != null && (i = v.reverse(i, 0)));
      var u = [], h, d = e, p = t.shape[0], f = v.unstack(t), m;
      i != null && (m = v.unstack(i));
      for (var g = function(L) {
        var x = f[L], N = v.tidy(function() {
          return n(x, d);
        });
        if (i == null)
          h = N[0], d = N[1];
        else {
          var I = v.tidy(function() {
            var C = m[L], O = v.onesLike(C).sub(C), D = N[0].mul(C).add(d[0].mul(O)), F = d.map(function(k, B) {
              return N[1][B].mul(C).add(k.mul(O));
            });
            return {output: D, newStates: F};
          });
          h = I.output, d = I.newStates;
        }
        o && u.push(h);
      }, y = 0; y < p; ++y)
        g(y);
      var w;
      if (o) {
        var b = 1;
        w = v.stack(u, b);
      }
      return [h, w, d];
    });
  }
  var Tr = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this, i;
      if (e.cell == null)
        throw new M("cell property is missing for the constructor of RNN.");
      if (Array.isArray(e.cell) ? i = new sd({cells: e.cell}) : i = e.cell, i.stateSize == null)
        throw new M("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");
      return r.cell = i, r.returnSequences = e.returnSequences == null ? false : e.returnSequences, r.returnState = e.returnState == null ? false : e.returnState, r.goBackwards = e.goBackwards == null ? false : e.goBackwards, r._stateful = e.stateful == null ? false : e.stateful, r.unroll = e.unroll == null ? false : e.unroll, r.supportsMasking = true, r.inputSpec = [new Ct({ndim: 3})], r.stateSpec = null, r.states_ = null, r.numConstants = null, r.keptStates = [], r;
    }
    return t.prototype.getStates = function() {
      if (this.states_ == null) {
        var e = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;
        return xn(0, e).map(function(r) {
          return null;
        });
      } else
        return this.states_;
    }, t.prototype.setStates = function(e) {
      this.states_ = e;
    }, t.prototype.computeOutputShape = function(e) {
      zh(e) && (e = e[0]), e = e;
      var r = this.cell.stateSize;
      Array.isArray(r) || (r = [r]);
      var i = r[0], a;
      if (this.returnSequences ? a = [e[0], e[1], i] : a = [e[0], i], this.returnState) {
        for (var s = [], o = 0, c = r; o < c.length; o++) {
          var l = c[o];
          s.push([e[0], l]);
        }
        return [a].concat(s);
      } else
        return a;
    }, t.prototype.computeMask = function(e, r) {
      var i = this;
      return v.tidy(function() {
        Array.isArray(r) && (r = r[0]);
        var a = i.returnSequences ? r : null;
        if (i.returnState) {
          var s = i.states.map(function(o) {
            return null;
          });
          return [a].concat(s);
        } else
          return a;
      });
    }, Object.defineProperty(t.prototype, "states", {get: function() {
      if (this.states_ == null) {
        for (var e = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1, r = [], i = 0; i < e; ++i)
          r.push(null);
        return r;
      } else
        return this.states_;
    }, set: function(e) {
      this.states_ = e;
    }, enumerable: true, configurable: true}), t.prototype.build = function(e) {
      if (this.numConstants != null)
        throw new Re("Constants support is not implemented in RNN yet.");
      zh(e) && (e = e[0]), e = e;
      var r = this.stateful ? e[0] : null, i = e.slice(2);
      this.inputSpec[0] = new Ct({shape: [r, null].concat(i)});
      var a = [e[0]].concat(e.slice(2));
      this.cell.build(a);
      var s;
      if (Array.isArray(this.cell.stateSize) ? s = this.cell.stateSize : s = [this.cell.stateSize], this.stateSpec != null) {
        if (!v.util.arraysEqual(this.stateSpec.map(function(o) {
          return o.shape[o.shape.length - 1];
        }), s))
          throw new M("An initialState was passed that is not compatible with " + ("cell.stateSize. Received stateSpec=" + this.stateSpec + "; ") + ("However cell.stateSize is " + this.cell.stateSize));
      } else
        this.stateSpec = s.map(function(o) {
          return new Ct({shape: [null, o]});
        });
      this.stateful && this.resetStates();
    }, t.prototype.resetStates = function(e, r) {
      var i = this;
      r === void 0 && (r = false), v.tidy(function() {
        if (!i.stateful)
          throw new vr("Cannot call resetStates() on an RNN Layer that is not stateful.");
        var a = i.inputSpec[0].shape[0];
        if (a == null)
          throw new M("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");
        if (i.states_ == null)
          Array.isArray(i.cell.stateSize) ? i.states_ = i.cell.stateSize.map(function(u) {
            return v.zeros([a, u]);
          }) : i.states_ = [v.zeros([a, i.cell.stateSize])];
        else if (e == null)
          v.dispose(i.states_), i.keptStates != null && (v.dispose(i.keptStates), i.keptStates = []), Array.isArray(i.cell.stateSize) ? i.states_ = i.cell.stateSize.map(function(u) {
            return v.zeros([a, u]);
          }) : i.states_[0] = v.zeros([a, i.cell.stateSize]);
        else {
          if (Array.isArray(e) || (e = [e]), e.length !== i.states_.length)
            throw new M("Layer " + i.name + " expects " + i.states_.length + " state(s), " + ("but it received " + e.length + " state value(s). Input ") + ("received: " + e));
          r === true ? i.keptStates.push(i.states_.slice()) : v.dispose(i.states_);
          for (var s = 0; s < i.states_.length; ++s) {
            var o = e[s], c = Array.isArray(i.cell.stateSize) ? i.cell.stateSize[s] : i.cell.stateSize, l = [a, c];
            if (!v.util.arraysEqual(o.shape, l))
              throw new M("State " + s + " is incompatible with layer " + i.name + ": " + ("expected shape=" + l + ", received shape=" + o.shape));
            i.states_[s] = o;
          }
        }
        i.states_ = i.states_.map(function(u) {
          return v.keep(u.clone());
        });
      });
    }, t.prototype.apply = function(e, r) {
      var i = r == null ? null : r.initialState, a = r == null ? null : r.constants;
      r == null && (r = {});
      var s = Iv(e, i, a, this.numConstants);
      e = s.inputs, i = s.initialState, a = s.constants;
      var o = [], c = [];
      if (i != null) {
        r.initialState = i, o = o.concat(i), this.stateSpec = [];
        for (var l = 0, u = i; l < u.length; l++) {
          var h = u[l];
          this.stateSpec.push(new Ct({shape: h.shape}));
        }
        c = c.concat(this.stateSpec);
      }
      a != null && (r.constants = a, o = o.concat(a), this.numConstants = a.length);
      var d = o[0] instanceof Ln;
      if (d) {
        var p = [e].concat(o), f = this.inputSpec.concat(c), m = this.inputSpec;
        this.inputSpec = f;
        var g = n.prototype.apply.call(this, p, r);
        return this.inputSpec = m, g;
      } else
        return n.prototype.apply.call(this, e, r);
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        var a = r == null ? null : r.mask, s = r == null ? null : r.training, o = r == null ? null : r.initialState;
        e = Oe(e), o == null && (i.stateful ? o = i.states_ : o = i.getInitialState(e));
        var c = Array.isArray(i.cell.stateSize) ? i.cell.stateSize.length : 1;
        if (o.length !== c)
          throw new M("RNN Layer has " + c + " state(s) but was passed " + (o.length + " initial state(s)."));
        i.unroll && console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");
        var l = {training: s}, u = function(g, y) {
          var w = i.cell.call([g].concat(y), l);
          return [w[0], w.slice(1)];
        }, h = Av(u, e, o, i.goBackwards, a, null, i.unroll, i.returnSequences), d = h[0], p = h[1], f = h[2];
        i.stateful && i.resetStates(f, s);
        var m = i.returnSequences ? p : d;
        return i.returnState ? [m].concat(f) : m;
      });
    }, t.prototype.getInitialState = function(e) {
      var r = this;
      return v.tidy(function() {
        var i = v.zeros(e.shape);
        return i = v.sum(i, [1, 2]), i = Pa(i), Array.isArray(r.cell.stateSize) ? r.cell.stateSize.map(function(a) {
          return a > 1 ? _h(i, [1, a]) : i;
        }) : r.cell.stateSize > 1 ? [_h(i, [1, r.cell.stateSize])] : [i];
      });
    }, Object.defineProperty(t.prototype, "trainableWeights", {get: function() {
      return this.trainable ? this.cell.trainableWeights : [];
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "nonTrainableWeights", {get: function() {
      return this.trainable ? this.cell.nonTrainableWeights : this.cell.weights;
    }, enumerable: true, configurable: true}), t.prototype.setFastWeightInitDuringBuild = function(e) {
      n.prototype.setFastWeightInitDuringBuild.call(this, e), this.cell != null && this.cell.setFastWeightInitDuringBuild(e);
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = {returnSequences: this.returnSequences, returnState: this.returnState, goBackwards: this.goBackwards, stateful: this.stateful, unroll: this.unroll};
      this.numConstants != null && (r.numConstants = this.numConstants);
      var i = this.cell.getConfig();
      return this.getClassName() === t.className && (r.cell = {className: this.cell.getClassName(), config: i}), $t({}, i, e, r);
    }, t.fromConfig = function(e, r, i) {
      i === void 0 && (i = {});
      var a = r.cell, s = Sn(a, i);
      return new e(Object.assign(r, {cell: s}));
    }, t.className = "RNN", t;
  }(Fe);
  v.serialization.registerClass(Tr);
  var ji = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t;
  }(Fe), od = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.DEFAULT_ACTIVATION = "tanh", r.DEFAULT_KERNEL_INITIALIZER = "glorotNormal", r.DEFAULT_RECURRENT_INITIALIZER = "orthogonal", r.DEFAULT_BIAS_INITIALIZER = "zeros", r.units = e.units, _t(r.units, "units"), r.activation = Ar(e.activation == null ? r.DEFAULT_ACTIVATION : e.activation), r.useBias = e.useBias == null ? true : e.useBias, r.kernelInitializer = at(e.kernelInitializer || r.DEFAULT_KERNEL_INITIALIZER), r.recurrentInitializer = at(e.recurrentInitializer || r.DEFAULT_RECURRENT_INITIALIZER), r.biasInitializer = at(e.biasInitializer || r.DEFAULT_BIAS_INITIALIZER), r.kernelRegularizer = st(e.kernelRegularizer), r.recurrentRegularizer = st(e.recurrentRegularizer), r.biasRegularizer = st(e.biasRegularizer), r.kernelConstraint = At(e.kernelConstraint), r.recurrentConstraint = At(e.recurrentConstraint), r.biasConstraint = At(e.biasConstraint), r.dropout = Vi([1, xr([0, e.dropout == null ? 0 : e.dropout])]), r.recurrentDropout = Vi([1, xr([0, e.recurrentDropout == null ? 0 : e.recurrentDropout])]), r.stateSize = r.units, r.dropoutMask = null, r.recurrentDropoutMask = null, r;
    }
    return t.prototype.build = function(e) {
      e = Xe(e), this.kernel = this.addWeight("kernel", [e[e.length - 1], this.units], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint), this.recurrentKernel = this.addWeight("recurrent_kernel", [this.units, this.units], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint), this.useBias ? this.bias = this.addWeight("bias", [this.units], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint) : this.bias = null, this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (e = e, e.length !== 2)
          throw new M("SimpleRNNCell expects 2 input Tensors, got " + e.length + ".");
        var a = e[1];
        e = e[0];
        var s = r.training == null ? false : r.training;
        0 < i.dropout && i.dropout < 1 && i.dropoutMask == null && (i.dropoutMask = Nr({ones: function() {
          return v.onesLike(e);
        }, rate: i.dropout, training: s})), 0 < i.recurrentDropout && i.recurrentDropout < 1 && i.recurrentDropoutMask == null && (i.recurrentDropoutMask = Nr({ones: function() {
          return v.onesLike(a);
        }, rate: i.recurrentDropout, training: s}));
        var o, c = i.dropoutMask, l = i.recurrentDropoutMask;
        c != null ? o = Un(v.mul(e, c), i.kernel.read()) : o = Un(e, i.kernel.read()), i.bias != null && (o = Bn(o, i.bias.read())), l != null && (a = v.mul(a, l));
        var u = v.add(o, Un(a, i.recurrentKernel.read()));
        return i.activation != null && (u = i.activation.apply(u)), [u, u];
      });
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = {units: this.units, activation: Ir(this.activation), useBias: this.useBias, kernelInitializer: lt(this.kernelInitializer), recurrentInitializer: lt(this.recurrentInitializer), biasInitializer: lt(this.biasInitializer), kernelRegularizer: Je(this.kernelRegularizer), recurrentRegularizer: Je(this.recurrentRegularizer), biasRegularizer: Je(this.biasRegularizer), activityRegularizer: Je(this.activityRegularizer), kernelConstraint: It(this.kernelConstraint), recurrentConstraint: It(this.recurrentConstraint), biasConstraint: It(this.biasConstraint), dropout: this.dropout, recurrentDropout: this.recurrentDropout};
      return $t({}, e, r);
    }, t.className = "SimpleRNNCell", t;
  }(ji);
  v.serialization.registerClass(od);
  var Tv = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      return e.cell = new od(e), r = n.call(this, e) || this, r;
    }
    return t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.cell.dropoutMask != null && (v.dispose(i.cell.dropoutMask), i.cell.dropoutMask = null), i.cell.recurrentDropoutMask != null && (v.dispose(i.cell.recurrentDropoutMask), i.cell.recurrentDropoutMask = null);
        var a = r == null ? null : r.mask, s = r == null ? null : r.training, o = r == null ? null : r.initialState;
        return n.prototype.call.call(i, e, {mask: a, training: s, initialState: o});
      });
    }, t.fromConfig = function(e, r) {
      return new e(r);
    }, t.className = "SimpleRNN", t;
  }(Tr);
  v.serialization.registerClass(Tv);
  var cd = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      if (r.DEFAULT_ACTIVATION = "tanh", r.DEFAULT_RECURRENT_ACTIVATION = "hardSigmoid", r.DEFAULT_KERNEL_INITIALIZER = "glorotNormal", r.DEFAULT_RECURRENT_INITIALIZER = "orthogonal", r.DEFAULT_BIAS_INITIALIZER = "zeros", e.resetAfter)
        throw new M("GRUCell does not support reset_after parameter set to true.");
      return r.units = e.units, _t(r.units, "units"), r.activation = Ar(e.activation === void 0 ? r.DEFAULT_ACTIVATION : e.activation), r.recurrentActivation = Ar(e.recurrentActivation === void 0 ? r.DEFAULT_RECURRENT_ACTIVATION : e.recurrentActivation), r.useBias = e.useBias == null ? true : e.useBias, r.kernelInitializer = at(e.kernelInitializer || r.DEFAULT_KERNEL_INITIALIZER), r.recurrentInitializer = at(e.recurrentInitializer || r.DEFAULT_RECURRENT_INITIALIZER), r.biasInitializer = at(e.biasInitializer || r.DEFAULT_BIAS_INITIALIZER), r.kernelRegularizer = st(e.kernelRegularizer), r.recurrentRegularizer = st(e.recurrentRegularizer), r.biasRegularizer = st(e.biasRegularizer), r.kernelConstraint = At(e.kernelConstraint), r.recurrentConstraint = At(e.recurrentConstraint), r.biasConstraint = At(e.biasConstraint), r.dropout = Vi([1, xr([0, e.dropout == null ? 0 : e.dropout])]), r.recurrentDropout = Vi([1, xr([0, e.recurrentDropout == null ? 0 : e.recurrentDropout])]), r.implementation = e.implementation, r.stateSize = r.units, r.dropoutMask = null, r.recurrentDropoutMask = null, r;
    }
    return t.prototype.build = function(e) {
      e = Xe(e);
      var r = e[e.length - 1];
      this.kernel = this.addWeight("kernel", [r, this.units * 3], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint), this.recurrentKernel = this.addWeight("recurrent_kernel", [this.units, this.units * 3], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint), this.useBias ? this.bias = this.addWeight("bias", [this.units * 3], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint) : this.bias = null, this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (e = e, e.length !== 2)
          throw new M("GRUCell expects 2 input Tensors (inputs, h, c), got " + (e.length + "."));
        var a = r.training == null ? false : r.training, s = e[1];
        e = e[0], 0 < i.dropout && i.dropout < 1 && i.dropoutMask == null && (i.dropoutMask = Nr({ones: function() {
          return v.onesLike(e);
        }, rate: i.dropout, training: a, count: 3})), 0 < i.recurrentDropout && i.recurrentDropout < 1 && i.recurrentDropoutMask == null && (i.recurrentDropoutMask = Nr({ones: function() {
          return v.onesLike(s);
        }, rate: i.recurrentDropout, training: a, count: 3}));
        var o = i.dropoutMask, c = i.recurrentDropoutMask, l, u, h;
        0 < i.dropout && i.dropout < 1 && (e = v.mul(e, o[0]));
        var d = Un(e, i.kernel.read());
        i.useBias && (d = Bn(d, i.bias.read())), 0 < i.recurrentDropout && i.recurrentDropout < 1 && (s = v.mul(s, c[0]));
        var p = i.recurrentKernel.read(), f = v.split(p, [2 * i.units, i.units], p.rank - 1), m = f[0], g = f[1], y = Un(s, m), w = v.split(d, 3, d.rank - 1), b = w[0], L = w[1], x = w[2], N = v.split(y, 2, y.rank - 1), I = N[0], C = N[1];
        l = i.recurrentActivation.apply(v.add(b, I)), u = i.recurrentActivation.apply(v.add(L, C));
        var O = Un(v.mul(u, s), g);
        h = i.activation.apply(v.add(x, O));
        var D = v.add(v.mul(l, s), v.mul(v.add(1, v.neg(l)), h));
        return [D, D];
      });
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = {units: this.units, activation: Ir(this.activation), recurrentActivation: Ir(this.recurrentActivation), useBias: this.useBias, kernelInitializer: lt(this.kernelInitializer), recurrentInitializer: lt(this.recurrentInitializer), biasInitializer: lt(this.biasInitializer), kernelRegularizer: Je(this.kernelRegularizer), recurrentRegularizer: Je(this.recurrentRegularizer), biasRegularizer: Je(this.biasRegularizer), activityRegularizer: Je(this.activityRegularizer), kernelConstraint: It(this.kernelConstraint), recurrentConstraint: It(this.recurrentConstraint), biasConstraint: It(this.biasConstraint), dropout: this.dropout, recurrentDropout: this.recurrentDropout, implementation: this.implementation, resetAfter: false};
      return $t({}, e, r);
    }, t.className = "GRUCell", t;
  }(ji);
  v.serialization.registerClass(cd);
  var Nv = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      return e.implementation === 0 && console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."), e.cell = new cd(e), r = n.call(this, e) || this, r;
    }
    return t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.cell.dropoutMask != null && (v.dispose(i.cell.dropoutMask), i.cell.dropoutMask = null), i.cell.recurrentDropoutMask != null && (v.dispose(i.cell.recurrentDropoutMask), i.cell.recurrentDropoutMask = null);
        var a = r == null ? null : r.mask, s = r == null ? null : r.training, o = r == null ? null : r.initialState;
        return n.prototype.call.call(i, e, {mask: a, training: s, initialState: o});
      });
    }, t.fromConfig = function(e, r) {
      return r.implmentation === 0 && (r.implementation = 1), new e(r);
    }, t.className = "GRU", t;
  }(Tr);
  v.serialization.registerClass(Nv);
  var Fo = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.DEFAULT_ACTIVATION = "tanh", r.DEFAULT_RECURRENT_ACTIVATION = "hardSigmoid", r.DEFAULT_KERNEL_INITIALIZER = "glorotNormal", r.DEFAULT_RECURRENT_INITIALIZER = "orthogonal", r.DEFAULT_BIAS_INITIALIZER = "zeros", r.units = e.units, _t(r.units, "units"), r.activation = Ar(e.activation === void 0 ? r.DEFAULT_ACTIVATION : e.activation), r.recurrentActivation = Ar(e.recurrentActivation === void 0 ? r.DEFAULT_RECURRENT_ACTIVATION : e.recurrentActivation), r.useBias = e.useBias == null ? true : e.useBias, r.kernelInitializer = at(e.kernelInitializer || r.DEFAULT_KERNEL_INITIALIZER), r.recurrentInitializer = at(e.recurrentInitializer || r.DEFAULT_RECURRENT_INITIALIZER), r.biasInitializer = at(e.biasInitializer || r.DEFAULT_BIAS_INITIALIZER), r.unitForgetBias = e.unitForgetBias, r.kernelRegularizer = st(e.kernelRegularizer), r.recurrentRegularizer = st(e.recurrentRegularizer), r.biasRegularizer = st(e.biasRegularizer), r.kernelConstraint = At(e.kernelConstraint), r.recurrentConstraint = At(e.recurrentConstraint), r.biasConstraint = At(e.biasConstraint), r.dropout = Vi([1, xr([0, e.dropout == null ? 0 : e.dropout])]), r.recurrentDropout = Vi([1, xr([0, e.recurrentDropout == null ? 0 : e.recurrentDropout])]), r.implementation = e.implementation, r.stateSize = [r.units, r.units], r.dropoutMask = null, r.recurrentDropoutMask = null, r;
    }
    return t.prototype.build = function(e) {
      var r;
      e = Xe(e);
      var i = e[e.length - 1];
      this.kernel = this.addWeight("kernel", [i, this.units * 4], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint), this.recurrentKernel = this.addWeight("recurrent_kernel", [this.units, this.units * 4], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);
      var a;
      if (this.useBias) {
        if (this.unitForgetBias) {
          var s = this.biasInitializer, o = this.units;
          a = new (r = function(c) {
            Q(l, c);
            function l() {
              return c !== null && c.apply(this, arguments) || this;
            }
            return l.prototype.apply = function(u, h) {
              var d = s.apply([o]), p = new Eh().apply([o]), f = s.apply([o * 2]);
              return py(py(d, p), f);
            }, l;
          }(dn), r.className = "CustomInit", r)();
        } else
          a = this.biasInitializer;
        this.bias = this.addWeight("bias", [this.units * 4], null, a, this.biasRegularizer, true, this.biasConstraint);
      } else
        this.bias = null;
      this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        var a = r.training == null ? false : r.training;
        if (e = e, e.length !== 3)
          throw new M("LSTMCell expects 3 input Tensors (inputs, h, c), got " + (e.length + "."));
        var s = e[1], o = e[2];
        e = e[0], 0 < i.dropout && i.dropout < 1 && i.dropoutMask == null && (i.dropoutMask = Nr({ones: function() {
          return v.onesLike(e);
        }, rate: i.dropout, training: a, count: 4})), 0 < i.recurrentDropout && i.recurrentDropout < 1 && i.recurrentDropoutMask == null && (i.recurrentDropoutMask = Nr({ones: function() {
          return v.onesLike(s);
        }, rate: i.recurrentDropout, training: a, count: 4}));
        var c = i.dropoutMask, l = i.recurrentDropoutMask, u, h, d, p;
        0 < i.dropout && i.dropout < 1 && (e = v.mul(e, c[0]));
        var f = Un(e, i.kernel.read());
        0 < i.recurrentDropout && i.recurrentDropout < 1 && (s = v.mul(s, l[0])), f = v.add(f, Un(s, i.recurrentKernel.read())), i.useBias && (f = Bn(f, i.bias.read()));
        var m = v.split(f, 4, f.rank - 1), g = m[0], y = m[1], w = m[2], b = m[3];
        u = i.recurrentActivation.apply(g), h = i.recurrentActivation.apply(y), d = v.add(v.mul(h, o), v.mul(u, i.activation.apply(w))), p = i.recurrentActivation.apply(b);
        var L = v.mul(p, i.activation.apply(d));
        return [L, L, d];
      });
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = {units: this.units, activation: Ir(this.activation), recurrentActivation: Ir(this.recurrentActivation), useBias: this.useBias, kernelInitializer: lt(this.kernelInitializer), recurrentInitializer: lt(this.recurrentInitializer), biasInitializer: lt(this.biasInitializer), unitForgetBias: this.unitForgetBias, kernelRegularizer: Je(this.kernelRegularizer), recurrentRegularizer: Je(this.recurrentRegularizer), biasRegularizer: Je(this.biasRegularizer), activityRegularizer: Je(this.activityRegularizer), kernelConstraint: It(this.kernelConstraint), recurrentConstraint: It(this.recurrentConstraint), biasConstraint: It(this.biasConstraint), dropout: this.dropout, recurrentDropout: this.recurrentDropout, implementation: this.implementation};
      return $t({}, e, r);
    }, t.className = "LSTMCell", t;
  }(ji);
  v.serialization.registerClass(Fo);
  var _v = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      return e.implementation === 0 && console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."), e.cell = new Fo(e), r = n.call(this, e) || this, r;
    }
    return t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.cell.dropoutMask != null && (v.dispose(i.cell.dropoutMask), i.cell.dropoutMask = null), i.cell.recurrentDropoutMask != null && (v.dispose(i.cell.recurrentDropoutMask), i.cell.recurrentDropoutMask = null);
        var a = r == null ? null : r.mask, s = r == null ? null : r.training, o = r == null ? null : r.initialState;
        return n.prototype.call.call(i, e, {mask: a, training: s, initialState: o});
      });
    }, t.fromConfig = function(e, r) {
      return r.implmentation === 0 && (r.implementation = 1), new e(r);
    }, t.className = "LSTM", t;
  }(Tr);
  v.serialization.registerClass(_v);
  var sd = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.cells = e.cells, r;
    }
    return Object.defineProperty(t.prototype, "stateSize", {get: function() {
      for (var e = [], r = 0, i = this.cells.slice().reverse(); r < i.length; r++) {
        var a = i[r];
        Array.isArray(a.stateSize) ? e.push.apply(e, a.stateSize) : e.push(a.stateSize);
      }
      return e;
    }, enumerable: true, configurable: true}), t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        e = e;
        for (var a = e.slice(1), s = [], o = 0, c = i.cells.slice().reverse(); o < c.length; o++) {
          var l = c[o];
          Array.isArray(l.stateSize) ? s.push(a.splice(0, l.stateSize.length)) : s.push(a.splice(0, 1));
        }
        s.reverse();
        for (var u = [], h, d = 0; d < i.cells.length; ++d) {
          var l = i.cells[d];
          a = s[d], d === 0 ? h = [e[0]].concat(a) : h = [h[0]].concat(a), h = l.call(h, r), u.push(h.slice(1));
        }
        a = [];
        for (var p = 0, f = u.slice().reverse(); p < f.length; p++) {
          var m = f[p];
          a.push.apply(a, m);
        }
        return [h[0]].concat(a);
      });
    }, t.prototype.build = function(e) {
      zh(e) && (e = e[0]), e = e;
      var r;
      this.cells.forEach(function(i, a) {
        ni("RNNCell_" + a, function() {
          i.build(e), Array.isArray(i.stateSize) ? r = i.stateSize[0] : r = i.stateSize, e = [e[0], r];
        });
      }), this.built = true;
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = function(s) {
        return {className: s.getClassName(), config: s.getConfig()};
      }, i = this.cells.map(r), a = {cells: i};
      return $t({}, e, a);
    }, t.fromConfig = function(e, r, i) {
      i === void 0 && (i = {});
      for (var a = [], s = 0, o = r.cells; s < o.length; s++) {
        var c = o[s];
        a.push(Sn(c, i));
      }
      return new e({cells: a});
    }, Object.defineProperty(t.prototype, "trainableWeights", {get: function() {
      if (!this.trainable)
        return [];
      for (var e = [], r = 0, i = this.cells; r < i.length; r++) {
        var a = i[r];
        e.push.apply(e, a.trainableWeights);
      }
      return e;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "nonTrainableWeights", {get: function() {
      for (var e = [], r = 0, i = this.cells; r < i.length; r++) {
        var a = i[r];
        e.push.apply(e, a.nonTrainableWeights);
      }
      if (!this.trainable) {
        for (var s = [], o = 0, c = this.cells; o < c.length; o++) {
          var a = c[o];
          s.push.apply(s, a.trainableWeights);
        }
        return s.concat(e);
      }
      return e;
    }, enumerable: true, configurable: true}), t.prototype.getWeights = function() {
      for (var e = [], r = 0, i = this.cells; r < i.length; r++) {
        var a = i[r];
        e.push.apply(e, a.weights);
      }
      return Ph(e);
    }, t.prototype.setWeights = function(e) {
      for (var r = [], i = 0, a = this.cells; i < a.length; i++)
        for (var s = a[i], o = s.weights.length, c = e.splice(o), l = 0; l < s.weights.length; ++l)
          r.push([s.weights[l], c[l]]);
      Mh(r);
    }, t.className = "StackedRNNCells", t;
  }(ji);
  v.serialization.registerClass(sd);
  function Nr(n) {
    var t = n.ones, e = n.rate, r = n.training, i = r === void 0 ? false : r, a = n.count, s = a === void 0 ? 1 : a, o = function() {
      return my(t(), e);
    }, c = function() {
      return Ha(o, t, i);
    };
    if (!s || s <= 1)
      return v.keep(c().clone());
    var l = Array(s).fill(void 0).map(c);
    return l.map(function(u) {
      return v.keep(u.clone());
    });
  }
  var bG = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t;
  }(ji), G7 = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      if (e.unroll)
        throw new Re("Unrolling is not possible with convolutional RNNs.");
      if (Array.isArray(e.cell))
        throw new Re("It is not possible at the moment to stack convolutional cells.");
      return r = n.call(this, e) || this, r.inputSpec = [new Ct({ndim: 5})], r;
    }
    return t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (i.cell.dropoutMask != null && (v.dispose(i.cell.dropoutMask), i.cell.dropoutMask = null), i.cell.recurrentDropoutMask != null && (v.dispose(i.cell.recurrentDropoutMask), i.cell.recurrentDropoutMask = null), r && r.constants)
          throw new M("ConvRNN2D cell does not support constants");
        var a = r == null ? null : r.mask, s = r == null ? null : r.training, o = r == null ? null : r.initialState;
        return n.prototype.call.call(i, e, {mask: a, training: s, initialState: o});
      });
    }, t.prototype.computeOutputShape = function(e) {
      var r = this.computeSingleOutputShape(e);
      return this.returnSequences || (r = [r[0]].concat(r.slice(2))), this.returnState && (r = [r].concat(Array(2).fill([e[0]].concat(r.slice(-3))))), r;
    }, t.prototype.getInitialState = function(e) {
      var r = this;
      return v.tidy(function() {
        var i = r.cell.stateSize, a = e.shape, s = r.computeSingleOutputShape(a), o = [s[0]].concat(s.slice(2)), c = v.zeros(o);
        return Array.isArray(i) ? Array(i.length).fill(c) : [c];
      });
    }, t.prototype.resetStates = function(e, r) {
      var i = this;
      r === void 0 && (r = false), v.tidy(function() {
        if (!i.stateful)
          throw new vr("Cannot call resetStates() on an RNN Layer that is not stateful.");
        var a = i.inputSpec[0].shape, s = i.computeSingleOutputShape(a), o = [s[0]].concat(s.slice(2)), c = a[0];
        if (c == null)
          throw new M("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");
        if (i.getStates() == null)
          Array.isArray(i.cell.stateSize) ? i.states_ = i.cell.stateSize.map(function() {
            return v.zeros(o);
          }) : i.states_ = [v.zeros(o)];
        else if (e == null)
          v.dispose(i.states_), i.keptStates != null && (v.dispose(i.keptStates), i.keptStates = []), Array.isArray(i.cell.stateSize) ? i.states_ = i.cell.stateSize.map(function() {
            return v.zeros(o);
          }) : i.states_[0] = v.zeros(o);
        else {
          if (Array.isArray(e) || (e = [e]), e.length !== i.states_.length)
            throw new M("Layer " + i.name + " expects " + i.states_.length + " state(s), " + ("but it received " + e.length + " state value(s). Input ") + ("received: " + e));
          r ? i.keptStates.push(i.states_.slice()) : v.dispose(i.states_);
          for (var l = 0; l < i.states_.length; ++l) {
            var u = e[l], h = o;
            if (!v.util.arraysEqual(u.shape, h))
              throw new M("State " + l + " is incompatible with layer " + i.name + ": " + ("expected shape=" + h + ", received shape=" + u.shape));
            i.states_[l] = u;
          }
        }
        i.states_ = i.states_.map(function(d) {
          return v.keep(d.clone());
        });
      });
    }, t.prototype.computeSingleOutputShape = function(e) {
      var r = this.cell, i = r.dataFormat, a = r.filters, s = r.kernelSize, o = r.padding, c = r.strides, l = r.dilationRate, u = i === "channelsFirst", h = e[u ? 3 : 2], d = e[u ? 4 : 3], p = In(h, s[0], o, c[0], l[0]), f = In(d, s[1], o, c[1], l[1]), m = e.slice(0, 2).concat(u ? [a, p, f] : [p, f, a]);
      return m;
    }, t.className = "ConvRNN2D", t;
  }(Tr), ld = function(n) {
    Q(t, n);
    function t(e) {
      var r = this, i = e.filters, a = e.kernelSize, s = e.strides, o = e.padding, c = e.dataFormat, l = e.dilationRate;
      return r = n.call(this, $t({}, e, {units: i})) || this, r.filters = i, _t(r.filters, "filters"), r.kernelSize = Ki(a, 2, "kernelSize"), r.kernelSize.forEach(function(u) {
        return _t(u, "kernelSize");
      }), r.strides = Ki(s || 1, 2, "strides"), r.strides.forEach(function(u) {
        return _t(u, "strides");
      }), r.padding = o || "valid", sn(r.padding), r.dataFormat = c || "channelsLast", gt(r.dataFormat), r.dilationRate = Ki(l || 1, 2, "dilationRate"), r.dilationRate.forEach(function(u) {
        return _t(u, "dilationRate");
      }), r;
    }
    return t.prototype.build = function(e) {
      var r;
      e = Xe(e);
      var i = this.dataFormat === "channelsFirst" ? 1 : e.length - 1;
      if (e[i] == null)
        throw new M("The channel dimension of the input should be defined. " + ("Found " + e[i]));
      var a = e[i], s = 4, o = this.kernelSize.concat([a, this.filters * s]);
      this.kernel = this.addWeight("kernel", o, null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);
      var c = this.kernelSize.concat([this.filters, this.filters * s]);
      if (this.recurrentKernel = this.addWeight("recurrent_kernel", c, null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint), this.useBias) {
        var l = void 0;
        if (this.unitForgetBias) {
          var u = this.biasInitializer, h = this.filters;
          l = new (r = function(d) {
            Q(p, d);
            function p() {
              return d !== null && d.apply(this, arguments) || this;
            }
            return p.prototype.apply = function(f, m) {
              var g = u.apply([h]), y = v.ones([h]), w = u.apply([h * 2]);
              return Rh([g, y, w]);
            }, p;
          }(dn), r.className = "CustomInit", r)();
        } else
          l = this.biasInitializer;
        this.bias = this.addWeight("bias", [this.filters * s], null, l, this.biasRegularizer, true, this.biasConstraint);
      }
      this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (e.length !== 3)
          throw new M("ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got " + (e.length + "."));
        var a = r.training || false, s = e[0], o = e[1], c = e[2], l = 4;
        0 < i.dropout && i.dropout < 1 && i.dropoutMask == null && (i.dropoutMask = Nr({ones: function() {
          return v.onesLike(s);
        }, rate: i.dropout, training: a, count: l}));
        var u = i.dropoutMask, h = function(re, ie, oe) {
          return !ie || !ie[oe] ? re : v.mul(ie[oe], re);
        }, d = h(s, u, 0), p = h(s, u, 1), f = h(s, u, 2), m = h(s, u, 3);
        0 < i.recurrentDropout && i.recurrentDropout < 1 && i.recurrentDropoutMask == null && (i.recurrentDropoutMask = Nr({ones: function() {
          return v.onesLike(o);
        }, rate: i.recurrentDropout, training: a, count: l}));
        var g = i.recurrentDropoutMask, y = h(o, g, 0), w = h(o, g, 1), b = h(o, g, 2), L = h(o, g, 3), x = 3, N = v.split(i.kernel.read(), l, x), I = N[0], C = N[1], O = N[2], D = N[3], F = i.useBias ? v.split(i.bias.read(), l) : [null, null, null, null], k = F[0], B = F[1], V = F[2], P = F[3];
        d = i.inputConv(d, I, k, i.padding), p = i.inputConv(p, C, B, i.padding), f = i.inputConv(f, O, V, i.padding), m = i.inputConv(m, D, P, i.padding);
        var G = v.split(i.recurrentKernel.read(), l, x), j = G[0], q = G[1], H = G[2], J = G[3];
        y = i.recurrentConv(y, j), w = i.recurrentConv(w, q), b = i.recurrentConv(b, H), L = i.recurrentConv(L, J);
        var $ = i.recurrentActivation.apply(v.add(d, y)), ee = i.recurrentActivation.apply(v.add(p, w)), te = v.add(v.mul(ee, c), v.mul($, i.activation.apply(v.add(f, b)))), ne = v.mul(i.recurrentActivation.apply(v.add(m, L)), i.activation.apply(te));
        return [ne, ne, te];
      });
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = e.units, i = _O(e, ["units"]), a = {filters: this.filters, kernelSize: this.kernelSize, padding: this.padding, dataFormat: this.dataFormat, dilationRate: this.dilationRate, strides: this.strides};
      return $t({}, i, a);
    }, t.prototype.inputConv = function(e, r, i, a) {
      var s = v.conv2d(e, r, this.strides, a || "valid", this.dataFormat === "channelsFirst" ? "NCHW" : "NHWC", this.dilationRate);
      return i ? Bn(s, i, this.dataFormat) : s;
    }, t.prototype.recurrentConv = function(e, r) {
      var i = 1;
      return v.conv2d(e, r, i, "same", this.dataFormat === "channelsFirst" ? "NCHW" : "NHWC");
    }, t.className = "ConvLSTM2DCell", t;
  }(Fo);
  v.serialization.registerClass(ld);
  var Cv = function(n) {
    Q(t, n);
    function t(e) {
      var r = this, i = new ld(e);
      return r = n.call(this, $t({}, e, {cell: i})) || this, r;
    }
    return t.fromConfig = function(e, r) {
      return new e(r);
    }, t.className = "ConvLSTM2D", t;
  }(G7);
  v.serialization.registerClass(Cv);
  var ud = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.rate = Math.max(Math.min(e.rate, 1), 0), r.noiseShape = e.noiseShape, r.seed = e.seed, r.supportsMasking = true, r;
    }
    return t.prototype.getNoiseShape = function(e) {
      if (this.noiseShape == null)
        return this.noiseShape;
      for (var r = e.shape, i = [], a = 0; a < this.noiseShape.length; ++a)
        i.push(this.noiseShape[a] == null ? r[a] : this.noiseShape[a]);
      return i;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e);
        if (0 < i.rate && i.rate < 1) {
          var s = r.training == null ? false : r.training, o = i.getNoiseShape(a), c = Ha(function() {
            return my(a, i.rate, o, i.seed);
          }, function() {
            return a;
          }, s);
          return c;
        }
        return e;
      });
    }, t.prototype.getConfig = function() {
      var e = {rate: this.rate, noiseShape: this.noiseShape, seed: this.seed}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.prototype.dispose = function() {
      return n.prototype.dispose.call(this);
    }, t.className = "Dropout", t;
  }(Fe);
  v.serialization.registerClass(ud);
  var Rv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.inputSpec = [{ndim: 3}], r;
    }
    return t.prototype.getNoiseShape = function(e) {
      var r = e.shape;
      return [r[0], 1, r[2]];
    }, t.className = "SpatialDropout1D", t;
  }(ud);
  v.serialization.registerClass(Rv);
  var Ov = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      if (r.activation = null, r.useBias = true, r.kernel = null, r.bias = null, r.DEFAULT_KERNEL_INITIALIZER = "glorotNormal", r.DEFAULT_BIAS_INITIALIZER = "zeros", e.batchInputShape == null && e.inputShape == null && e.inputDim != null) {
        var i = null;
        e.batchSize != null && (i = e.batchSize), r.batchInputShape = [i, e.inputDim];
      }
      return r.units = e.units, _t(r.units, "units"), r.activation = Ar(e.activation), e.useBias != null && (r.useBias = e.useBias), r.kernelInitializer = at(e.kernelInitializer || r.DEFAULT_KERNEL_INITIALIZER), r.biasInitializer = at(e.biasInitializer || r.DEFAULT_BIAS_INITIALIZER), r.kernelConstraint = At(e.kernelConstraint), r.biasConstraint = At(e.biasConstraint), r.kernelRegularizer = st(e.kernelRegularizer), r.biasRegularizer = st(e.biasRegularizer), r.activityRegularizer = st(e.activityRegularizer), r.supportsMasking = true, r.inputSpec = [{minNDim: 2}], r;
    }
    return t.prototype.build = function(e) {
      var r;
      e = Xe(e);
      var i = e[e.length - 1];
      this.kernel == null && (this.kernel = this.addWeight("kernel", [i, this.units], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint), this.useBias && (this.bias = this.addWeight("bias", [this.units], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint))), this.inputSpec = [{minNDim: 2, axes: (r = {}, r[-1] = i, r)}], this.built = true;
    }, t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r = e.slice();
      return r[r.length - 1] = this.units, r;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e), s = ey(i.activation.getClassName()), o;
        return s != null ? o = Un(a, i.kernel.read(), s, i.bias ? i.bias.read() : null) : (o = Un(a, i.kernel.read()), i.bias != null && (o = Bn(o, i.bias.read())), i.activation != null && (o = i.activation.apply(o))), o;
      });
    }, t.prototype.getConfig = function() {
      var e = {units: this.units, activation: Ir(this.activation), useBias: this.useBias, kernelInitializer: lt(this.kernelInitializer), biasInitializer: lt(this.biasInitializer), kernelRegularizer: Je(this.kernelRegularizer), biasRegularizer: Je(this.biasRegularizer), activityRegularizer: Je(this.activityRegularizer), kernelConstraint: It(this.kernelConstraint), biasConstraint: It(this.biasConstraint)}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Dense", t;
  }(Fe);
  v.serialization.registerClass(Ov);
  var Ev = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      return e = e || {}, r = n.call(this, e) || this, r.inputSpec = [{minNDim: 3}], r.dataFormat = e.dataFormat, r;
    }
    return t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      for (var r = 0, i = e.slice(1); r < i.length; r++) {
        var a = i[r];
        if (a == null)
          throw new M('The shape of the input to "Flatten" is not fully defined ' + ("(got " + e.slice(1) + "). Make sure to pass a complete ") + '"input_shape" or "batch_input_shape" argument to the first layer in your model.');
      }
      return [e[0], br(e, 1)];
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e);
        if (i.dataFormat === "channelsFirst" && a.rank > 1) {
          for (var s = [0], o = 2; o < a.rank; ++o)
            s.push(o);
          s.push(1), a = a.transpose(s);
        }
        return KO(a);
      });
    }, t.prototype.getConfig = function() {
      var e = {};
      this.dataFormat != null && (e.dataFormat = this.dataFormat);
      var r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Flatten", t;
  }(Fe);
  v.serialization.registerClass(Ev);
  var Dv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.supportsMasking = true, r.activation = Ar(e.activation), r;
    }
    return t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e);
        return i.activation.apply(a);
      });
    }, t.prototype.getConfig = function() {
      var e = {activation: Ir(this.activation)}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Activation", t;
  }(Fe);
  v.serialization.registerClass(Dv);
  var kv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.n = e.n, r.inputSpec = [{ndim: 2}], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      return [e[0], this.n, e[1]];
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        return e = Oe(e), qO(e, i.n);
      });
    }, t.prototype.getConfig = function() {
      var e = {n: this.n}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "RepeatVector", t;
  }(Fe);
  v.serialization.registerClass(kv);
  var Fv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      r.targetShape = e.targetShape;
      for (var i = 0; i < r.targetShape.length; ++i)
        r.isUnknown(r.targetShape[i]) && (r.targetShape[i] = null);
      return r;
    }
    return t.prototype.isUnknown = function(e) {
      return e < 0 || e == null;
    }, t.prototype.fixUnknownDimension = function(e, r) {
      for (var i = "Total size of new array must be unchanged.", a = r.slice(), s = 1, o = null, c = 0; c < a.length; ++c) {
        var l = a[c];
        if (this.isUnknown(l))
          if (o === null)
            o = c;
          else
            throw new M("Can only specifiy one unknown dimension.");
        else
          s *= l;
      }
      var u = br(e);
      if (o !== null) {
        if (s === 0 || u % s !== 0)
          throw new M(i);
        a[o] = u / s;
      } else if (u !== s)
        throw new M(i);
      return a;
    }, t.prototype.computeOutputShape = function(e) {
      for (var r = false, i = 0; i < e.length; ++i)
        if (this.isUnknown(e[i])) {
          r = true;
          break;
        }
      return r ? e.slice(0, 1).concat(this.targetShape) : e.slice(0, 1).concat(this.fixUnknownDimension(e.slice(1), this.targetShape));
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e), s = a.shape, o = s.slice(0, 1).concat(i.fixUnknownDimension(s.slice(1), i.targetShape));
        return a.reshape(o);
      });
    }, t.prototype.getConfig = function() {
      var e = {targetShape: this.targetShape}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Reshape", t;
  }(Fe);
  v.serialization.registerClass(Fv);
  var Wv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      if (e.dims == null)
        throw new Error("Required configuration field `dims` is missing during Permute constructor call.");
      if (!Array.isArray(e.dims))
        throw new Error("Permute constructor requires `dims` to be an Array, but received " + (e.dims + " instead."));
      var i = xn(1, e.dims.length + 1);
      if (!v.util.arraysEqual(e.dims.slice().sort(), i))
        throw new Error("Invalid permutation `dims`: " + JSON.stringify(e.dims) + " `dims` must contain consecutive integers starting from 1.");
      return r.dims = e.dims, r.dimsIncludingBatch = [0].concat(r.dims), r.inputSpec = [new Ct({ndim: r.dims.length + 1})], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r = e.slice();
      return this.dims.forEach(function(i, a) {
        r[a + 1] = e[i];
      }), r;
    }, t.prototype.call = function(e, r) {
      return v.transpose(Oe(e), this.dimsIncludingBatch);
    }, t.prototype.getConfig = function() {
      var e = {dims: this.dims}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Permute", t;
  }(Fe);
  v.serialization.registerClass(Wv);
  var Uv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e == null ? {} : e) || this;
      return r.supportsMasking = true, e != null ? r.maskValue = e.maskValue == null ? 0 : e.maskValue : r.maskValue = 0, r;
    }
    return t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = {maskValue: this.maskValue};
      return Object.assign(r, e), r;
    }, t.prototype.computeMask = function(e, r) {
      var i = Oe(e), a = -1;
      return v.any(v.notEqual(i, this.maskValue), a);
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e), s = -1, o = true, c = v.any(v.notEqual(a, i.maskValue), s, o), l = a.mul(c.asType(a.dtype));
        return l;
      });
    }, t.className = "Masking", t;
  }(Fe);
  v.serialization.registerClass(Uv);
  var Bv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      if (r.embeddings = null, r.DEFAULT_EMBEDDINGS_INITIALIZER = "randomUniform", e.batchInputShape == null && e.inputShape == null) {
        var i = null;
        e.batchSize != null && (i = e.batchSize), e.inputLength == null ? r.batchInputShape = [i, null] : r.batchInputShape = [i].concat(nt(e.inputLength));
      }
      return r.inputDim = e.inputDim, _t(r.inputDim, "inputDim"), r.outputDim = e.outputDim, _t(r.outputDim, "outputDim"), r.embeddingsInitializer = at(e.embeddingsInitializer || r.DEFAULT_EMBEDDINGS_INITIALIZER), r.embeddingsRegularizer = st(e.embeddingsRegularizer), r.activityRegularizer = st(e.activityRegularizer), r.embeddingsConstraint = At(e.embeddingsConstraint), r.maskZero = e.maskZero, r.supportsMasking = e.maskZero, r.inputLength = e.inputLength, r;
    }
    return t.prototype.build = function(e) {
      this.embeddings = this.addWeight("embeddings", [this.inputDim, this.outputDim], this.dtype, this.embeddingsInitializer, this.embeddingsRegularizer, true, this.embeddingsConstraint), this.built = true;
    }, t.prototype.warnOnIncompatibleInputShape = function(e) {
    }, t.prototype.computeMask = function(e, r) {
      var i = this;
      return v.tidy(function() {
        return i.maskZero ? (e = Oe(e), v.notEqual(e, v.zerosLike(e))) : null;
      });
    }, t.prototype.computeOutputShape = function(e) {
      if (e = Xe(e), this.inputLength == null)
        return e.concat([this.outputDim]);
      var r = nt(this.inputLength);
      if (r.length !== e.length - 1)
        throw new M('"inputLength" is ' + this.inputLength + ", but received " + ("input shape has shape " + e));
      for (var i = 0, a = 0; a < r.length; ++a) {
        var s = r[a], o = e[a + 1];
        if (s != null && o != null && s !== o)
          throw new M('"inputLength" is ' + this.inputLength + ", but received " + ("input shape has shape " + e));
        s == null && (r[i] = o), i++;
      }
      return [e[0]].concat(r, [this.outputDim]);
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e);
        a.dtype !== "int32" && (a = za(a, "int32"));
        var s = fy(i.embeddings.read(), a.as1D());
        return s.reshape(Xe(i.computeOutputShape(a.shape)));
      });
    }, t.prototype.getConfig = function() {
      var e = {inputDim: this.inputDim, outputDim: this.outputDim, embeddingsInitializer: lt(this.embeddingsInitializer), embeddingsRegularizer: Je(this.embeddingsRegularizer), activityRegularizer: Je(this.activityRegularizer), embeddingsConstraint: It(this.embeddingsConstraint), maskZero: this.maskZero, inputLength: this.inputLength}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Embedding", t;
  }(Fe);
  v.serialization.registerClass(Bv);
  var si = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e || {}) || this;
      return r.supportsMasking = true, r;
    }
    return t.prototype.mergeFunction = function(e) {
      throw new Re();
    }, t.prototype.computeElementwiseOpOutputShape = function(e, r) {
      if (e == null || r == null)
        return null;
      if (e.length < r.length)
        return this.computeElementwiseOpOutputShape(r, e);
      if (r.length === 0)
        return e;
      for (var i = e.slice(0, e.length - r.length), a = 0; a < r.length; ++a) {
        var s = e[e.length - r.length + a], o = r[a];
        if (s == null || o == null || s < 0 || o < 0)
          i.push(null);
        else if (s === 1)
          i.push(o);
        else if (o === 1)
          i.push(s);
        else {
          if (s !== o)
            throw new M("Operands could not be broadcast together with shapes " + JSON.stringify(e) + " " + JSON.stringify(r));
          i.push(s);
        }
      }
      return i;
    }, t.prototype.build = function(e) {
      if (Array.isArray(e) && !Array.isArray(e[0]) && (e = [Xe(e)]), e = e, e.length < 2)
        throw new M("A merge layer should be called on an Array of at least 2 inputs." + (" Got " + e.length + " input(s)."));
      for (var r = [], i = 0, a = e; i < a.length; i++) {
        var s = a[i];
        s != null && s[0] !== null && r.push(s[0]);
      }
      if (r = wr(r), r.length > 1)
        throw new M("Can not merge tensors with different batch sizes. " + ("Got tensors with shapes: " + JSON.stringify(e) + "."));
      for (var o = e[0] == null ? null : e[0].slice(1), c = 1; c < e.length; ++c) {
        var s = e[c] == null ? null : e[c].slice(1);
        o = this.computeElementwiseOpOutputShape(o, s);
      }
      var l = e.map(function(u) {
        return u.length;
      });
      e.indexOf(null) === -1 && wr(l).length === 1 ? this.reshapeRequired = false : this.reshapeRequired = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (e = e, i.reshapeRequired) {
          var a = [], s = e.map(function(O) {
            return O.rank;
          });
          if (s.indexOf(null) === -1) {
            for (var o = xr(s), c = 0, l = e; c < l.length; c++) {
              for (var u = l[c], h = u.rank, d = 0; d < o - h; ++d)
                u = Pa(u, 1);
              a.push(u);
            }
            return i.mergeFunction(a);
          } else {
            for (var p = false, f = 0, m = e; f < m.length; f++) {
              var u = m[f], h = u.rank;
              if (h == null) {
                var g = u.shape, y = g[0], w = g.slice(1).concat([y]), b = u.reshape([y].concat(br(g.slice(1))));
                b = v.transpose(b, [1, 0]), b = b.reshape(w), a.push(b), p = true;
              } else if (h > 1) {
                var L = xn(1, h).concat([0]);
                a.push(v.transpose(u, L)), p = true;
              } else
                a.push(u);
            }
            var x = i.mergeFunction(a), N = x.rank;
            if (p) {
              if (N == null) {
                var I = x.shape, C = I.length, y = I[C - 1], w = [y].concat(I.slice(0, I.length - 1));
                x = v.transpose(x.reshape([-1, y]), [1, 0]).reshape(w);
              } else if (N > 1) {
                var L = [N - 1].concat(xn(0, N - 1));
                x = v.transpose(x, L);
              }
            }
            return x;
          }
        } else
          return i.mergeFunction(e);
      });
    }, t.prototype.computeOutputShape = function(e) {
      e = e;
      var r;
      e[0] == null ? r = null : r = e[0].slice(1);
      for (var i = 1; i < e.length; ++i) {
        var a = e[i] == null ? null : e[i].slice(1);
        r = this.computeElementwiseOpOutputShape(r, a);
      }
      for (var s = [], o = 0, c = e; o < c.length; o++) {
        var a = c[o];
        a != null && a[0] !== null && s.push(a[0]);
      }
      return s = wr(s), s.length === 1 ? r = s.concat(r) : r = [null].concat(r), r;
    }, t.prototype.computeMask = function(e, r) {
      return v.tidy(function() {
        if (r == null)
          return null;
        if (!Array.isArray(r))
          throw new M("`mask` should be an Array");
        if (!Array.isArray(e))
          throw new M("`inputs` should be an Array");
        if (r.length !== e.length)
          throw new M("The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths " + ("(" + e.length + " vs " + r.length + ")"));
        if (r.every(function(s) {
          return s == null;
        }))
          return null;
        r = r.map(function(s) {
          return s == null ? s : v.expandDims(s, 0);
        });
        for (var i = r[0], a = 1; a < r.length - 1; ++a)
          i = v.logicalAnd(i, r[a]);
        return i;
      });
    }, t;
  }(Fe), zv = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.mergeFunction = function(e) {
      return v.tidy(function() {
        for (var r = e[0].clone(), i = 1; i < e.length; ++i)
          r = v.add(r, e[i]);
        return r;
      });
    }, t.className = "Add", t;
  }(si);
  v.serialization.registerClass(zv);
  var Pv = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.mergeFunction = function(e) {
      return v.tidy(function() {
        for (var r = e[0].clone(), i = 1; i < e.length; ++i)
          r = v.mul(r, e[i]);
        return r;
      });
    }, t.className = "Multiply", t;
  }(si);
  v.serialization.registerClass(Pv);
  var Mv = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.mergeFunction = function(e) {
      return v.tidy(function() {
        for (var r = e[0].clone(), i = 1; i < e.length; ++i)
          r = v.add(r, e[i]);
        return v.mul(1 / e.length, r);
      });
    }, t.className = "Average", t;
  }(si);
  v.serialization.registerClass(Mv);
  var Hv = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.mergeFunction = function(e) {
      return v.tidy(function() {
        for (var r = e[0], i = 1; i < e.length; ++i)
          r = v.maximum(r, e[i]);
        return r;
      });
    }, t.className = "Maximum", t;
  }(si);
  v.serialization.registerClass(Hv);
  var Vv = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.mergeFunction = function(e) {
      return v.tidy(function() {
        for (var r = e[0], i = 1; i < e.length; ++i)
          r = v.minimum(r, e[i]);
        return r;
      });
    }, t.className = "Minimum", t;
  }(si);
  v.serialization.registerClass(Vv);
  var Gv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.DEFAULT_AXIS = -1, e == null && (e = {}), r.axis = e.axis == null ? r.DEFAULT_AXIS : e.axis, r.supportsMasking = true, r.reshapeRequired = false, r;
    }
    return t.prototype.build = function(e) {
      if (!(Array.isArray(e) && Array.isArray(e[0])) || e.length === 1)
        throw new M("A `Concatenate` layer should be called on a list of at least 2 inputs");
      e = e;
      for (var r = true, i = 0, a = e; i < a.length; i++) {
        var s = a[i];
        if (s != null) {
          r = false;
          break;
        }
      }
      if (r)
        return;
      for (var o = [], c = 0; c < e.length; ++c) {
        var l = e[c].slice();
        l.splice(this.axis, 1);
        for (var u = false, h = 0, d = o; h < d.length; h++) {
          var s = d[h];
          if (v.util.arraysEqual(s, l)) {
            u = true;
            break;
          }
        }
        u || o.push(l);
      }
      if (o.length > 1)
        throw new M("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: " + JSON.stringify(e));
    }, t.prototype.mergeFunction = function(e) {
      var r = this;
      return v.tidy(function() {
        return Rh(e, r.axis);
      });
    }, t.prototype.computeOutputShape = function(e) {
      if (!(Array.isArray(e) && Array.isArray(e[0])))
        throw new M("A `Concatenate` layer should be called on a list of inputs.");
      for (var r = e, i = r[0].slice(), a = this.axis < 0 ? i.length + this.axis : this.axis, s = 0, o = r.slice(1); s < o.length; s++) {
        var c = o[s];
        if (i[a] == null || c[a] == null) {
          i[a] = null;
          break;
        }
        i[a] += c[a];
      }
      return i;
    }, t.prototype.computeMask = function(e, r) {
      var i = this;
      if (r == null)
        return null;
      if (!Array.isArray(r))
        throw new M("`mask` should be an array for Concatenate");
      if (!Array.isArray(e))
        throw new M("`inputs` should be an array for Concatenate");
      if (r.length !== e.length)
        throw new M("Mismatch in the length of mask (" + r.length + ") " + ("and the legnth of inputs (" + e.length + ")"));
      return v.tidy(function() {
        var a = true;
        if (r.forEach(function(l) {
          if (l != null) {
            a = false;
            return;
          }
        }), a)
          return null;
        for (var s = [], o = 0; o < e.length; ++o)
          r[o] == null ? s.push(v.onesLike(e[o]).asType("bool")) : r[o].rank < e[o].rank ? s.push(v.expandDims(r[o], -1)) : s.push(r[o]);
        var c = v.concat(s, i.axis);
        return v.all(c, -1, false);
      });
    }, t.prototype.getConfig = function() {
      var e = {axis: this.axis}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Concatenate", t;
  }(si);
  v.serialization.registerClass(Gv);
  function ja(n, t) {
    for (; n < 0; )
      n += t;
    return n;
  }
  function q7(n, t, e) {
    if (n.shape.length > 3 || t.shape.length > 3)
      throw new Re("batchDot is not implemented for tensors of 4D or higher rank yet");
    if (v.util.assert(n.shape.length >= 2, function() {
      return "batchDot requires the rank of x to be >= 2, " + ("but got " + n.shape.length);
    }), v.util.assert(n.shape.length >= 2, function() {
      return "batchDot requires the rank of y to be >= 2, " + ("but got " + t.shape.length);
    }), typeof e == "number" && (e = [e, e]), n.dtype === "complex64" || t.dtype === "complex64")
      throw new Re("batchDot is not implemented for complex64-type Tensors yet.");
    var r = n.shape.length, i = t.shape.length;
    e == null && (e = [r - 1, i - 2]);
    var a = e;
    return v.tidy(function() {
      var s;
      if (r > i) {
        s = r - i;
        for (var o = [], c = 0; c < s; ++c)
          o.push(1);
        t = t.reshape(t.shape.concat(o));
      } else if (i > r) {
        s = i - r;
        for (var o = [], c = 0; c < s; ++c)
          o.push(1);
        n = n.reshape(n.shape.concat(o));
      } else
        s = 0;
      var l;
      if (n.shape.length === 2 && t.shape.length === 2)
        a[0] === a[1] ? l = n.mul(t).sum(a[0]) : l = n.transpose([1, 0]).mul(t).sum(a[1]);
      else {
        var u = a[0] !== n.shape.length - 1, h = a[1] === t.shape.length - 1;
        l = n.matMul(t, u, h);
      }
      if (s > 0) {
        var d = void 0;
        r > i ? d = r + i - 3 : d = r - 1;
        for (var p = [], c = d; c < d + s; ++c)
          p.push(c);
        l = l.squeeze(p);
      }
      return l.shape.length === 1 && (l = l.expandDims(1)), l;
    });
  }
  var qv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.axes = e.axes, r.normalize = e.normalize == null ? false : e.normalize, r.supportsMasking = true, r.reshapeRequired = false, r;
    }
    return t.prototype.build = function(e) {
      v.util.assert(Array.isArray(e) && e.length === 2 && Array.isArray(e[0]) && Array.isArray(e[1]), function() {
        return "A `Dot` layer should be called on a list of exactly 2 inputs.";
      });
      var r = e[0], i = e[1];
      if (r.length > 3 || i.length > 3)
        throw new Re("Dot layer does not support tensors of 4D or higher rank yet.");
      var a = this.interpretAxes(r, i);
      if (r[a[0]] !== i[a[1]])
        throw new M("Dimension incompatibility: " + (r[a[0]] + " !== " + i[a[1]]));
    }, t.prototype.mergeFunction = function(e) {
      if (e.length !== 2)
        throw new M("A `Dot` layer must be called on exactly 2 inputs, " + ("but received " + e.length + " input(s)."));
      var r = e[0], i = e[1], a;
      return Array.isArray(this.axes) ? a = this.axes.map(function(s, o) {
        return ja(s, e[o].shape.length);
      }) : a = [ja(this.axes, r.shape.length), ja(this.axes, i.shape.length)], this.normalize && (r = Io(r, a[0]), i = Io(i, a[1])), q7(r, i, a);
    }, t.prototype.interpretAxes = function(e, r) {
      var i;
      return Array.isArray(this.axes) ? i = this.axes : i = [ja(this.axes, e.length), ja(this.axes, r.length)], i;
    }, t.prototype.computeOutputShape = function(e) {
      v.util.assert(Array.isArray(e) && e.length === 2 && Array.isArray(e[0]) && Array.isArray(e[1]), function() {
        return "A `Dot` layer should be called on a list of exactly 2 inputs.";
      });
      var r = e[0].slice(), i = e[1].slice();
      if (r.length > 3 || i.length > 3)
        throw new Re("Dot layer does not support tensors of 4D or higher rank yet.");
      var a = this.interpretAxes(r, i);
      r.splice(a[0], 1), i.splice(a[1], 1), i.splice(0, 1);
      var s = r.concat(i);
      return s.length === 1 && s.push(1), s;
    }, t.prototype.computeMask = function(e, r) {
      return null;
    }, t.prototype.getConfig = function() {
      var e = {axes: this.axes, normalize: this.normalize}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "Dot", t;
  }(si);
  v.serialization.registerClass(qv);
  var Yv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.supportsMasking = true, r.stddev = e.stddev, r;
    }
    return t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = {stddev: this.stddev};
      return Object.assign(r, e), r;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e), s = function() {
          return vo(a.shape, 0, i.stddev).add(a);
        }, o = Ha(s, function() {
          return a;
        }, r.training || false);
        return o;
      });
    }, t.className = "GaussianNoise", t;
  }(Fe);
  v.serialization.registerClass(Yv);
  var Kv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.supportsMasking = true, r.rate = e.rate, r;
    }
    return t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = {rate: this.rate};
      return Object.assign(r, e), r;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r);
        var a = Oe(e);
        if (i.rate > 0 && i.rate < 1) {
          var s = function() {
            var o = Math.sqrt(i.rate / (1 - i.rate));
            return a.mul(vo(a.shape, 1, o));
          };
          return Ha(s, function() {
            return a;
          }, r.training || false);
        }
        return a;
      });
    }, t.className = "GaussianDropout", t;
  }(Fe);
  v.serialization.registerClass(Kv);
  var jv = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.supportsMasking = true, r.rate = e.rate, r.noiseShape = e.noiseShape, r;
    }
    return t.prototype._getNoiseShape = function(e) {
      return this.noiseShape || Oe(e).shape;
    }, t.prototype.computeOutputShape = function(e) {
      return e;
    }, t.prototype.getConfig = function() {
      var e = n.prototype.getConfig.call(this), r = {rate: this.rate};
      return Object.assign(r, e), r;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        if (i.rate < 1 && i.rate > 0) {
          var a = i._getNoiseShape(e), s = function() {
            var o = Oe(e), c = 1.6732632423543772, l = 1.0507009873554805, u = -c * l, h = v.greaterEqual(v.randomUniform(a), i.rate);
            h = za(h, "float32");
            var d = Math.pow((1 - i.rate) * (1 + i.rate * Math.pow(u, 2)), -0.5), p = -d * u * i.rate, f = o.mul(h).add(h.add(-1).mul(u));
            return f.mul(d).add(p);
          };
          return Ha(s, function() {
            return Oe(e);
          }, r.training || false);
        }
        return e;
      });
    }, t.className = "AlphaDropout", t;
  }(Fe);
  v.serialization.registerClass(jv);
  function $a(n, t, e, r, i, a) {
    a === void 0 && (a = 1e-3);
    var s;
    if (n.rank === 2)
      s = v.batchNorm2d(n, t, e, r, i, a);
    else if (n.rank === 3)
      s = v.batchNorm3d(n, t, e, r, i, a);
    else if (n.rank === 4)
      s = v.batchNorm4d(n, t, e, r, i, a);
    else
      throw new Re("batchNormalization is not implemented for array of rank " + n.rank + " yet");
    return s;
  }
  function Y7(n, t, e, r, i) {
    return i === void 0 && (i = 1e-3), v.tidy(function() {
      var a = v.moments(n, r), s = a.mean, o = a.variance, c = $a(n, s, o, e, t, i);
      return [c, s, o];
    });
  }
  function K7(n, t, e, r, i) {
    return i === void 0 && (i = 1e-3), v.tidy(function() {
      for (var a = v.moments(n, r), s = a.mean, o = a.variance, c = [], l = 0, u = xn(0, n.rank); l < u.length; l++) {
        var h = u[l];
        r.indexOf(h) !== -1 ? c.push(1) : c.push(n.shape[h]);
      }
      var d = s.reshape(c), p = o.reshape(c), f = t == null ? null : t.reshape(c), m = e == null ? null : e.reshape(c), g = $a(n, d, p, m, f, i);
      return [g, s, o];
    });
  }
  function j7(n, t, e, r, i) {
    return i === void 0 && (i = 1e-3), v.util.arraysEqual(r.slice().sort(), xn(0, n.rank - 1)) ? Y7(n, t, e, r, i) : K7(n, t, e, r, i);
  }
  var $v = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      return e == null && (e = {}), r = n.call(this, e) || this, r.supportsMasking = true, r.axis = e.axis == null ? -1 : e.axis, r.momentum = e.momentum == null ? 0.99 : e.momentum, r.epsilon = e.epsilon == null ? 1e-3 : e.epsilon, r.center = e.center == null ? true : e.center, r.scale = e.scale == null ? true : e.scale, r.betaInitializer = at(e.betaInitializer || "zeros"), r.gammaInitializer = at(e.gammaInitializer || "ones"), r.movingMeanInitializer = at(e.movingMeanInitializer || "zeros"), r.movingVarianceInitializer = at(e.movingVarianceInitializer || "ones"), r.betaConstraint = At(e.betaConstraint), r.gammaConstraint = At(e.gammaConstraint), r.betaRegularizer = st(e.betaRegularizer), r.gammaRegularizer = st(e.gammaRegularizer), r;
    }
    return t.prototype.build = function(e) {
      var r;
      e = Xe(e);
      var i = this.axis >= 0 ? this.axis : this.axis + e.length, a = e[i];
      if (a == null)
        throw new M("Axis " + i + " of input tensor should have a defined dimension but the layer received an input with shape " + (JSON.stringify(e) + "."));
      this.inputSpec = [new Ct({ndim: e.length, axes: (r = {}, r[i] = a, r)})];
      var s = [a];
      this.scale && (this.gamma = this.addWeight("gamma", s, null, this.gammaInitializer, this.gammaRegularizer, true, this.gammaConstraint)), this.center && (this.beta = this.addWeight("beta", s, null, this.betaInitializer, this.betaRegularizer, true, this.betaConstraint)), this.movingMean = this.addWeight("moving_mean", s, null, this.movingMeanInitializer, null, false), this.movingVariance = this.addWeight("moving_variance", s, null, this.movingVarianceInitializer, null, false), this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        var a = r.training == null ? false : r.training, s = Oe(e), o = s.shape, c = o.length, l = xn(0, c), u = i.axis >= 0 ? i.axis : i.axis + c;
        l.splice(u, 1);
        var h = ei(1, c);
        h[u] = o[u];
        var d = l.slice();
        d.sort();
        var p = !v.util.arraysEqual(d, xn(0, c).slice(0, c - 1)), f = function() {
          if (p) {
            var x = i.movingMean.read().reshape(h), N = i.movingVariance.read().reshape(h), I = i.center ? i.beta.read().reshape(h) : null, C = i.scale ? i.gamma.read().reshape(h) : null;
            return $a(s, x, N, I, C, i.epsilon);
          } else
            return $a(s, i.movingMean.read(), i.movingVariance.read(), i.beta == null ? null : i.beta.read(), i.gamma == null ? null : i.gamma.read(), i.epsilon);
        };
        if (!a)
          return f();
        var m = j7(s, i.gamma.read(), i.beta.read(), l, i.epsilon), g = m[0], y = m[1], w = m[2], b = function(x, N, I) {
          v.tidy(function() {
            var C = 1 - I, O = x.read(), D = O.sub(N).mul(C);
            x.write(O.sub(D));
          });
        }, L = function() {
          b(i.movingMean, y, i.momentum), b(i.movingVariance, w, i.momentum);
        };
        return L(), g;
      });
    }, t.prototype.getConfig = function() {
      var e = {axis: this.axis, momentum: this.momentum, epsilon: this.epsilon, center: this.center, scale: this.scale, betaInitializer: lt(this.betaInitializer), gammaInitializer: lt(this.gammaInitializer), movingMeanInitializer: lt(this.movingMeanInitializer), movingVarianceInitializer: lt(this.movingVarianceInitializer), betaRegularizer: Je(this.betaRegularizer), gammaRegularizer: Je(this.gammaRegularizer), betaConstraint: It(this.betaConstraint), gammaConstraint: It(this.gammaConstraint)}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "BatchNormalization", t;
  }(Fe);
  v.serialization.registerClass($v);
  var Xv = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      if (e == null && (e = {}), r = n.call(this, e) || this, r.axis = e.axis == null ? -1 : e.axis, typeof r.axis == "number") {
        if (!Number.isInteger(r.axis))
          throw new Error("Expected axis to be an integer, but received " + r.axis);
      } else if (Array.isArray(r.axis))
        for (var i = 0, a = r.axis; i < a.length; i++) {
          var s = a[i];
          if (!Number.isInteger(s))
            throw new Error("Expected axis to be an array of integers, " + ("but received " + JSON.stringify(r.axis)));
        }
      else
        throw new Error("Expected axis to be an integer or an array of integers, " + ("but received " + JSON.stringify(r.axis)));
      return r.epsilon = e.epsilon == null ? 1e-3 : e.epsilon, r.center = e.center == null ? true : e.center, r.scale = e.scale == null ? true : e.scale, r.betaInitializer = at(e.betaInitializer || "zeros"), r.gammaInitializer = at(e.gammaInitializer || "ones"), r.betaRegularizer = st(e.betaRegularizer), r.gammaRegularizer = st(e.gammaRegularizer), r.supportsMasking = true, r;
    }
    return t.prototype.build = function(e) {
      e = Xe(e);
      var r = e.length;
      typeof this.axis == "number" && (this.axis = [this.axis]);
      for (var i = 0; i < this.axis.length; ++i)
        this.axis[i] < 0 && (this.axis[i] += r);
      for (var a = 0, s = this.axis; a < s.length; a++) {
        var o = s[a];
        if (o < 0 || o >= r)
          throw new Error("Invalid axis: " + o);
      }
      if (this.axis.length !== wr(this.axis).length)
        throw new Error("Found duplicate axes in: " + this.axis);
      var c = this.axis.map(function(u) {
        return e[u];
      }), l = true;
      this.scale ? this.gamma = this.addWeight("gamma", c, "float32", this.gammaInitializer, this.gammaRegularizer, l) : this.gamma = null, this.center ? this.beta = this.addWeight("beta", c, "float32", this.betaInitializer, this.betaRegularizer, l) : this.beta = null, this.built = true;
    }, t.prototype.call = function(e, r) {
      var i = this, a = Oe(e), s = a.shape, o = s.length;
      return v.tidy(function() {
        for (var c = true, l = v.moments(a, i.axis, c), u = l.mean, h = l.variance, d = ei(1, o), p = 0, f = i.axis; p < f.length; p++) {
          var m = f[p];
          d[m] = s[m];
        }
        for (var g = function(N) {
          return N != null && N.shape.length !== o && i.axis !== [o - 1] ? N.reshape(d) : N;
        }, y = g(i.gamma.read()), w = g(i.beta.read()), b = [], L = [], x = 0; x < o; ++x)
          i.axis.indexOf(x) !== -1 ? (b.push(s[x]), L.push(1)) : (b.push(1), L.push(s[x]));
        return u = u.tile(b), h = h.tile(b), y = y.tile(L), w = w.tile(L), $a(a, u, h, w, y, i.epsilon);
      });
    }, t.prototype.getConfig = function() {
      var e = {axis: this.axis, epsilon: this.epsilon, center: this.center, scale: this.scale, betaInitializer: lt(this.betaInitializer), gammaInitializer: lt(this.gammaInitializer), betaRegularizer: Je(this.betaRegularizer), gammaRegularizer: Je(this.gammaRegularizer)}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "LayerNormalization", t;
  }(Fe);
  v.serialization.registerClass(Xv);
  function $7(n, t, e) {
    return v.tidy(function() {
      if (n.rank !== 4)
        throw new M("temporalPadding expects input tensor to be 4-D, but received a " + (n.rank + "-D tensor."));
      if (t == null && (t = [[1, 1], [1, 1]]), t.length !== 2 || t[0].length !== 2 || t[1].length !== 2)
        throw new M("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");
      if (e == null && (e = bn()), e !== "channelsLast" && e !== "channelsFirst")
        throw new M("Unknown data format: " + e + ". Supported data formats are 'channelsLast' and 'channelsFirst.");
      var r;
      return e === "channelsFirst" ? r = [[0, 0], [0, 0], t[0], t[1]] : r = [[0, 0], t[0], t[1], [0, 0]], v.pad(n, r);
    });
  }
  var Jv = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      if (e == null && (e = {}), r = n.call(this, e) || this, r.dataFormat = e.dataFormat == null ? bn() : e.dataFormat, e.padding == null)
        r.padding = [[1, 1], [1, 1]];
      else if (typeof e.padding == "number")
        r.padding = [[e.padding, e.padding], [e.padding, e.padding]];
      else {
        if (e.padding = e.padding, e.padding.length !== 2)
          throw new M("ZeroPadding2D expects padding to be a length-2 array, but " + ("received a length-" + e.padding.length + " array."));
        var i = void 0, a = void 0;
        if (typeof e.padding[0] == "number")
          i = [e.padding[0], e.padding[0]], a = [e.padding[1], e.padding[1]];
        else {
          if (e.padding = e.padding, e.padding[0].length !== 2)
            throw new M("ZeroPadding2D expects height padding to be a length-2 array, " + ("but received a length-" + e.padding[0].length + " array."));
          if (i = e.padding[0], e.padding[1].length !== 2)
            throw new M("ZeroPadding2D expects width padding to be a length-2 array, " + ("but received a length-" + e.padding[1].length + " array."));
          a = e.padding[1];
        }
        r.padding = [i, a];
      }
      return r.inputSpec = [new Ct({ndim: 4})], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r, i;
      return this.dataFormat === "channelsFirst" ? (e[2] != null && e[2] >= 0 ? r = e[2] + this.padding[0][0] + this.padding[0][1] : r = null, e[3] != null && e[3] >= 0 ? i = e[3] + this.padding[1][0] + this.padding[1][1] : i = null, [e[0], e[1], r, i]) : (e[1] != null && e[1] >= 0 ? r = e[1] + this.padding[0][0] + this.padding[0][1] : r = null, e[2] != null && e[2] >= 0 ? i = e[2] + this.padding[1][0] + this.padding[1][1] : i = null, [e[0], r, i, e[3]]);
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        return $7(Oe(e), i.padding, i.dataFormat);
      });
    }, t.prototype.getConfig = function() {
      var e = {padding: this.padding, dataFormat: this.dataFormat}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.className = "ZeroPadding2D", t;
  }(Fe);
  v.serialization.registerClass(Jv);
  function Wo(n, t, e, r, i, a) {
    return v.tidy(function() {
      gt(i), oy(a), sn(r), e == null && (e = [1, 1]), r == null && (r = "valid"), i == null && (i = bn()), a == null && (a = "max"), n = id(n, i);
      var s, o = r === "same" ? "same" : "valid";
      return a === "max" ? s = v.maxPool(n, t, e, o) : s = v.avgPool(n, t, e, o), i === "channelsFirst" && (s = v.transpose(s, [0, 3, 1, 2])), s;
    });
  }
  function Zv(n, t, e, r, i, a) {
    return v.tidy(function() {
      gt(i), oy(a), sn(r), e == null && (e = [1, 1, 1]), r == null && (r = "valid"), i == null && (i = bn()), a == null && (a = "max"), n = fv(n, i);
      var s, o = r === "same" ? "same" : "valid";
      return a === "max" ? s = v.maxPool3d(n, t, e, o) : s = v.avgPool3d(n, t, e, o), i === "channelsFirst" && (s = v.transpose(s, [0, 4, 1, 2, 3])), s;
    });
  }
  var Qv = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      if (e.poolSize == null && (e.poolSize = 2), r = n.call(this, e) || this, typeof e.poolSize == "number")
        r.poolSize = [e.poolSize];
      else if (Array.isArray(e.poolSize) && e.poolSize.length === 1 && typeof e.poolSize[0] == "number")
        r.poolSize = e.poolSize;
      else
        throw new M("poolSize for 1D convolutional layer must be a number or an Array of a single number, but received " + ("" + JSON.stringify(e.poolSize)));
      if (_t(r.poolSize, "poolSize"), e.strides == null)
        r.strides = r.poolSize;
      else if (typeof e.strides == "number")
        r.strides = [e.strides];
      else if (Array.isArray(e.strides) && e.strides.length === 1 && typeof e.strides[0] == "number")
        r.strides = e.strides;
      else
        throw new M("strides for 1D convolutional layer must be a number or an Array of a single number, but received " + ("" + JSON.stringify(e.strides)));
      return _t(r.strides, "strides"), r.padding = e.padding == null ? "valid" : e.padding, sn(r.padding), r.inputSpec = [new Ct({ndim: 3})], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r = In(e[1], this.poolSize[0], this.padding, this.strides[0]);
      return [e[0], r, e[2]];
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        i.invokeCallHook(e, r), e = Pa(Oe(e), 2);
        var a = i.poolingFunction(Oe(e), [i.poolSize[0], 1], [i.strides[0], 1], i.padding, "channelsLast");
        return v.squeeze(a, [2]);
      });
    }, t.prototype.getConfig = function() {
      var e = {poolSize: this.poolSize, padding: this.padding, strides: this.strides}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t;
  }(Fe), e1 = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.poolingFunction = function(e, r, i, a, s) {
      return gt(s), sn(a), Wo(e, r, i, a, s, "max");
    }, t.className = "MaxPooling1D", t;
  }(Qv);
  v.serialization.registerClass(e1);
  var t1 = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.poolingFunction = function(e, r, i, a, s) {
      return gt(s), sn(a), Wo(e, r, i, a, s, "avg");
    }, t.className = "AveragePooling1D", t;
  }(Qv);
  v.serialization.registerClass(t1);
  var n1 = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      if (e.poolSize == null && (e.poolSize = [2, 2]), r = n.call(this, e) || this, r.poolSize = Array.isArray(e.poolSize) ? e.poolSize : [e.poolSize, e.poolSize], e.strides == null)
        r.strides = r.poolSize;
      else if (Array.isArray(e.strides)) {
        if (e.strides.length !== 2)
          throw new M("If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length " + (e.strides.length + "."));
        r.strides = e.strides;
      } else
        r.strides = [e.strides, e.strides];
      return _t(r.poolSize, "poolSize"), _t(r.strides, "strides"), r.padding = e.padding == null ? "valid" : e.padding, r.dataFormat = e.dataFormat == null ? "channelsLast" : e.dataFormat, gt(r.dataFormat), sn(r.padding), r.inputSpec = [new Ct({ndim: 4})], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r = this.dataFormat === "channelsFirst" ? e[2] : e[1], i = this.dataFormat === "channelsFirst" ? e[3] : e[2];
      return r = In(r, this.poolSize[0], this.padding, this.strides[0]), i = In(i, this.poolSize[1], this.padding, this.strides[1]), this.dataFormat === "channelsFirst" ? [e[0], e[1], r, i] : [e[0], r, i, e[3]];
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        return i.invokeCallHook(e, r), i.poolingFunction(Oe(e), i.poolSize, i.strides, i.padding, i.dataFormat);
      });
    }, t.prototype.getConfig = function() {
      var e = {poolSize: this.poolSize, padding: this.padding, strides: this.strides, dataFormat: this.dataFormat}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t;
  }(Fe), r1 = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.poolingFunction = function(e, r, i, a, s) {
      return gt(s), sn(a), Wo(e, r, i, a, s, "max");
    }, t.className = "MaxPooling2D", t;
  }(n1);
  v.serialization.registerClass(r1);
  var i1 = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.poolingFunction = function(e, r, i, a, s) {
      return gt(s), sn(a), Wo(e, r, i, a, s, "avg");
    }, t.className = "AveragePooling2D", t;
  }(n1);
  v.serialization.registerClass(i1);
  var a1 = function(n) {
    Q(t, n);
    function t(e) {
      var r = this;
      if (e.poolSize == null && (e.poolSize = [2, 2, 2]), r = n.call(this, e) || this, r.poolSize = Array.isArray(e.poolSize) ? e.poolSize : [e.poolSize, e.poolSize, e.poolSize], e.strides == null)
        r.strides = r.poolSize;
      else if (Array.isArray(e.strides)) {
        if (e.strides.length !== 3)
          throw new M("If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length " + (e.strides.length + "."));
        r.strides = e.strides;
      } else
        r.strides = [e.strides, e.strides, e.strides];
      return _t(r.poolSize, "poolSize"), _t(r.strides, "strides"), r.padding = e.padding == null ? "valid" : e.padding, r.dataFormat = e.dataFormat == null ? "channelsLast" : e.dataFormat, gt(r.dataFormat), sn(r.padding), r.inputSpec = [new Ct({ndim: 5})], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r = this.dataFormat === "channelsFirst" ? e[2] : e[1], i = this.dataFormat === "channelsFirst" ? e[3] : e[2], a = this.dataFormat === "channelsFirst" ? e[4] : e[3];
      return r = In(r, this.poolSize[0], this.padding, this.strides[0]), i = In(i, this.poolSize[1], this.padding, this.strides[1]), a = In(a, this.poolSize[2], this.padding, this.strides[2]), this.dataFormat === "channelsFirst" ? [e[0], e[1], r, i, a] : [e[0], r, i, a, e[4]];
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        return i.invokeCallHook(e, r), i.poolingFunction(Oe(e), i.poolSize, i.strides, i.padding, i.dataFormat);
      });
    }, t.prototype.getConfig = function() {
      var e = {poolSize: this.poolSize, padding: this.padding, strides: this.strides, dataFormat: this.dataFormat}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t;
  }(Fe), s1 = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.poolingFunction = function(e, r, i, a, s) {
      return gt(s), sn(a), Zv(e, r, i, a, s, "max");
    }, t.className = "MaxPooling3D", t;
  }(a1);
  v.serialization.registerClass(s1);
  var o1 = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e) || this;
    }
    return t.prototype.poolingFunction = function(e, r, i, a, s) {
      return gt(s), sn(a), Zv(e, r, i, a, s, "avg");
    }, t.className = "AveragePooling3D", t;
  }(a1);
  v.serialization.registerClass(o1);
  var c1 = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.inputSpec = [new Ct({ndim: 3})], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      return [e[0], e[2]];
    }, t.prototype.call = function(e, r) {
      throw new Re();
    }, t;
  }(Fe), l1 = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e || {}) || this;
    }
    return t.prototype.call = function(e, r) {
      return v.tidy(function() {
        var i = Oe(e);
        return v.mean(i, 1);
      });
    }, t.className = "GlobalAveragePooling1D", t;
  }(c1);
  v.serialization.registerClass(l1);
  var u1 = function(n) {
    Q(t, n);
    function t(e) {
      return n.call(this, e || {}) || this;
    }
    return t.prototype.call = function(e, r) {
      return v.tidy(function() {
        var i = Oe(e);
        return v.max(i, 1);
      });
    }, t.className = "GlobalMaxPooling1D", t;
  }(c1);
  v.serialization.registerClass(u1);
  var h1 = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.dataFormat = e.dataFormat == null ? "channelsLast" : e.dataFormat, gt(r.dataFormat), r.inputSpec = [new Ct({ndim: 4})], r;
    }
    return t.prototype.computeOutputShape = function(e) {
      return e = e, this.dataFormat === "channelsLast" ? [e[0], e[3]] : [e[0], e[1]];
    }, t.prototype.call = function(e, r) {
      throw new Re();
    }, t.prototype.getConfig = function() {
      var e = {dataFormat: this.dataFormat}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t;
  }(Fe), d1 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        var a = Oe(e);
        return i.dataFormat === "channelsLast" ? v.mean(a, [1, 2]) : v.mean(a, [2, 3]);
      });
    }, t.className = "GlobalAveragePooling2D", t;
  }(h1);
  v.serialization.registerClass(d1);
  var p1 = function(n) {
    Q(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        var a = Oe(e);
        return i.dataFormat === "channelsLast" ? v.max(a, [1, 2]) : v.max(a, [2, 3]);
      });
    }, t.className = "GlobalMaxPooling2D", t;
  }(h1);
  v.serialization.registerClass(p1);
  var f1 = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.layer = e.layer, r;
    }
    return t.prototype.build = function(e) {
      this.built = true;
    }, Object.defineProperty(t.prototype, "trainable", {get: function() {
      return this.layer != null ? this.layer.trainable : false;
    }, set: function(e) {
      this.layer != null && (this.layer.trainable = e);
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "trainableWeights", {get: function() {
      return this.layer.trainableWeights;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "nonTrainableWeights", {get: function() {
      return this.layer.nonTrainableWeights;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "updates", {get: function() {
      return this.layer._updates;
    }, enumerable: true, configurable: true}), Object.defineProperty(t.prototype, "losses", {get: function() {
      return this.layer.losses;
    }, enumerable: true, configurable: true}), t.prototype.getWeights = function() {
      return this.layer.getWeights();
    }, t.prototype.setWeights = function(e) {
      this.layer.setWeights(e);
    }, t.prototype.getConfig = function() {
      var e = {layer: {className: this.layer.getClassName(), config: this.layer.getConfig()}}, r = n.prototype.getConfig.call(this);
      return Object.assign(e, r), e;
    }, t.prototype.setFastWeightInitDuringBuild = function(e) {
      n.prototype.setFastWeightInitDuringBuild.call(this, e), this.layer != null && this.layer.setFastWeightInitDuringBuild(e);
    }, t.fromConfig = function(e, r, i) {
      i === void 0 && (i = {});
      var a = r.layer, s = Sn(a, i);
      delete r.layer;
      var o = {layer: s};
      return Object.assign(o, r), new e(o);
    }, t;
  }(Fe), m1 = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this;
      return r.supportsMasking = true, r;
    }
    return t.prototype.build = function(e) {
      if (e = Xe(e), e.length < 3)
        throw new M("TimeDistributed layer expects an input shape >= 3D, but received " + ("input shape " + JSON.stringify(e)));
      this.inputSpec = [{shape: e}];
      var r = [e[0]].concat(e.slice(2));
      this.layer.built || (this.layer.build(r), this.layer.built = true), n.prototype.build.call(this, e);
    }, t.prototype.computeOutputShape = function(e) {
      e = Xe(e);
      var r = [e[0]].concat(e.slice(2)), i = this.layer.computeOutputShape(r), a = e[1];
      return [i[0], a].concat(i.slice(1));
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        e = Oe(e);
        var a = function(c, l) {
          var u = Oe(i.layer.call(c, r));
          return [u, []];
        }, s = Av(a, e, [], false, null, null, false, true), o = s[1];
        return o;
      });
    }, t.className = "TimeDistributed", t;
  }(f1);
  v.serialization.registerClass(m1);
  function X7(n) {
    Mi(MO, "BidirectionalMergeMode", n);
  }
  var J7 = "concat", g1 = function(n) {
    Q(t, n);
    function t(e) {
      var r = n.call(this, e) || this, i = e.layer.getConfig(), a = {};
      a.className = e.layer.getClassName(), a.config = i, r.forwardLayer = Sn(a), i.goBackwards = !(i.goBackwards === true);
      var s = {};
      if (s.className = e.layer.getClassName(), s.config = i, r.backwardLayer = Sn(s), r.forwardLayer.name = "forward_" + r.forwardLayer.name, r.backwardLayer.name = "backward_" + r.backwardLayer.name, r.mergeMode = e.mergeMode === void 0 ? J7 : e.mergeMode, X7(r.mergeMode), e.weights)
        throw new Re("weights support is not implemented for Bidirectional layer yet.");
      return r._stateful = e.layer.stateful, r.returnSequences = e.layer.returnSequences, r.returnState = e.layer.returnState, r.supportsMasking = true, r._trainable = true, r.inputSpec = e.layer.inputSpec, r.numConstants = null, r;
    }
    return Object.defineProperty(t.prototype, "trainable", {get: function() {
      return this._trainable;
    }, set: function(e) {
      this._trainable = e, this.forwardLayer != null && (this.forwardLayer.trainable = e), this.backwardLayer != null && (this.backwardLayer.trainable = e);
    }, enumerable: true, configurable: true}), t.prototype.getWeights = function() {
      return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights());
    }, t.prototype.setWeights = function(e) {
      var r = e.length, i = Math.floor(r / 2);
      this.forwardLayer.setWeights(e.slice(0, i)), this.backwardLayer.setWeights(e.slice(i));
    }, t.prototype.computeOutputShape = function(e) {
      var r = this.forwardLayer.computeOutputShape(e);
      Array.isArray(r) && Array.isArray(r[0]) || (r = [r]), r = r;
      var i, a, s;
      return this.returnState && (s = r.slice(1)), i = r[0], i = i, this.mergeMode === "concat" ? (i[i.length - 1] *= 2, a = [i]) : this.mergeMode == null ? a = [i, i.slice()] : a = [i], this.returnState ? this.mergeMode == null ? a.concat(s).concat(s.slice()) : [i].concat(s).concat(s.slice()) : Vt(a);
    }, t.prototype.apply = function(e, r) {
      var i = r == null ? null : r.initialState, a = r == null ? null : r.constants;
      r == null && (r = {});
      var s = Iv(e, i, a, this.numConstants);
      if (e = s.inputs, i = s.initialState, a = s.constants, Array.isArray(e) && (i = e.slice(1), e = e[0]), (i == null || i.length === 0) && a == null)
        return n.prototype.apply.call(this, e, r);
      var o = [], c = [];
      if (i != null) {
        var l = i.length;
        if (l % 2 > 0)
          throw new M("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");
        r.initialState = i, o.push.apply(o, i);
        var u = i.map(function(b) {
          return new Ct({shape: b.shape});
        });
        this.forwardLayer.stateSpec = u.slice(0, l / 2), this.backwardLayer.stateSpec = u.slice(l / 2), c.push.apply(c, u);
      }
      if (a != null)
        throw new Re("Support for constants in Bidirectional layers is not implemented yet.");
      for (var h = o[0] instanceof Ln, d = 0, p = o; d < p.length; d++) {
        var f = p[d];
        if (f instanceof Ln !== h)
          throw new M("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");
      }
      if (h) {
        var m = [e].concat(o), g = this.inputSpec.concat(c), y = this.inputSpec;
        this.inputSpec = g;
        var w = n.prototype.apply.call(this, m, r);
        return this.inputSpec = y, w;
      } else
        return n.prototype.apply.call(this, e, r);
    }, t.prototype.call = function(e, r) {
      var i = this;
      return v.tidy(function() {
        var a = r.initialState, s, o;
        if (a == null)
          s = i.forwardLayer.call(e, r), o = i.backwardLayer.call(e, r);
        else {
          var c = a.slice(0, a.length / 2), l = a.slice(a.length / 2);
          s = i.forwardLayer.call(e, Object.assign(r, {initialState: c})), o = i.backwardLayer.call(e, Object.assign(r, {initialState: l}));
        }
        var u;
        i.returnState && (Array.isArray(s) && (u = s.slice(1).concat(o.slice(1))), s = s[0], o = o[0]), i.returnSequences && (o = v.reverse(o, 1));
        var h;
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    return n.kept ? n : W.clone(n);
  }
  var kD = [{tfOpName: "Add", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "AddV2", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "AddN", category: "arithmetic", inputs: [{start: 0, end: 0, name: "tensors", type: "tensors"}]}, {tfOpName: "BiasAdd", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Sub", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "RealDiv", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Div", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "DivNoNan", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "FloorDiv", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Mul", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Maximum", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}]}, {tfOpName: "Minimum", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}]}, {tfOpName: "Pow", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "SquaredDifference", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Mod", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "FloorMod", category: "arithmetic", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}], FD = {__proto__: null, json: kD};
  var WD = [{tfOpName: "Abs", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Acos", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Asin", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Atan", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Atan2", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "y", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Ceil", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "ClipByValue", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "clip_value_min", name: "clipValueMin", type: "number"}, {tfName: "clip_value_max", name: "clipValueMax", type: "number"}]}, {tfOpName: "Complex", category: "basic_math", inputs: [{start: 0, name: "real", type: "tensor"}, {start: 1, name: "imag", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "ComplexAbs", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Cos", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Cosh", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Elu", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Exp", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Floor", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Log", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Imag", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "Tout", name: "outputType", type: "dtype", notSupported: true}]}, {tfOpName: "Neg", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Real", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "Tout", name: "outputType", type: "dtype", notSupported: true}]}, {tfOpName: "Prelu", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "alpha", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Relu", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Relu6", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "clipValueMin", name: "clipValueMin", type: "number", defaultValue: 0}, {tfName: "clipValueMax", name: "clipValueMax", type: "number", defaultValue: 6}]}, {tfOpName: "Selu", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Sigmoid", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Sin", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Sinh", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Sqrt", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Rsqrt", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Square", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Tan", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Tanh", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Sign", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Round", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Expm1", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Log1p", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Reciprocal", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Softplus", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Asinh", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Acosh", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Atanh", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Erf", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Prod", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axes", type: "number[]"}], attrs: [{tfName: "keep_dims", name: "keepDims", type: "bool", notSupported: true}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "LeakyRelu", category: "basic_math", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "alpha", name: "alpha", type: "number", defaultValue: 0.2}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}], UD = {__proto__: null, json: WD}, BD = [{tfOpName: "LoopCond", category: "control", inputs: [{start: 0, name: "pred", type: "tensor"}]}, {tfOpName: "Switch", category: "control", inputs: [{start: 0, name: "data", type: "tensor"}, {start: 1, name: "pred", type: "tensor"}]}, {tfOpName: "Merge", category: "control", inputs: [{start: 0, end: 0, name: "tensors", type: "tensors"}]}, {tfOpName: "Enter", category: "control", inputs: [{start: 0, name: "tensor", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "frame_name", name: "frameName", type: "string"}, {tfName: "is_constant", name: "isConstant", type: "bool"}]}, {tfOpName: "Exit", category: "control", inputs: [{start: 0, name: "tensor", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "NextIteration", category: "control", inputs: [{start: 0, name: "tensor", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "TensorArrayV3", category: "control", inputs: [{start: 0, name: "size", type: "number"}], attrs: [{tfName: "dtype", name: "dtype", type: "dtype"}, {tfName: "element_shape", name: "elementShape", type: "shape"}, {tfName: "dynamic_size", name: "dynamicSize", type: "bool"}, {tfName: "clear_after_read", name: "clearAfterRead", type: "bool"}, {tfName: "identical_element_shapes", name: "identicalElementShapes", type: "bool"}, {tfName: "tensor_array_name", name: "name", type: "string"}]}, {tfOpName: "TensorArrayWriteV3", category: "control", inputs: [{start: 0, name: "tensorArrayId", type: "tensor"}, {start: 1, name: "index", type: "number"}, {start: 2, name: "tensor", type: "tensor"}, {start: 3, name: "flowIn", type: "number"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "TensorArrayReadV3", category: "control", inputs: [{start: 0, name: "tensorArrayId", type: "tensor"}, {start: 1, name: "index", type: "number"}, {start: 2, name: "flowIn", type: "number"}], attrs: [{tfName: "dtype", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "TensorArrayGatherV3", category: "control", inputs: [{start: 0, name: "tensorArrayId", type: "tensor"}, {start: 1, name: "indices", type: "number[]"}, {start: 2, name: "flowIn", type: "number"}], attrs: [{tfName: "dtype", name: "dtype", type: "dtype"}, {tfName: "element_shape", name: "elementShape", type: "shape"}]}, {tfOpName: "TensorArrayScatterV3", category: "control", inputs: [{start: 0, name: "tensorArrayId", type: "tensor"}, {start: 1, name: "indices", type: "number[]"}, {start: 2, name: "tensor", type: "tensor"}, {start: 3, name: "flowIn", type: "number"}], attrs: [{tfName: "T", name: "dtype", type: "dtype"}]}, {tfOpName: "TensorArrayConcatV3", category: "control", inputs: [{start: 0, name: "tensorArrayId", type: "tensor"}, {start: 1, name: "flowIn", type: "number"}], attrs: [{tfName: "dtype", name: "dtype", type: "dtype"}, {tfName: "element_shape_except0", name: "elementShapeExcept0", type: "shape", notSupported: true}]}, {tfOpName: "TensorArraySplitV3", category: "control", inputs: [{start: 0, name: "tensorArrayId", type: "tensor"}, {start: 1, name: "tensor", type: "tensor"}, {start: 2, name: "lengths", type: "number[]"}, {start: 3, name: "flowIn", type: "number"}], attrs: [{tfName: "T", name: "dtype", type: "dtype"}]}, {tfOpName: "TensorArraySizeV3", category: "control", inputs: [{start: 0, name: "tensorArrayId", type: "tensor"}, {start: 1, name: "flowIn", type: "number"}]}, {tfOpName: "TensorArrayCloseV3", category: "control", inputs: [{start: 0, name: "tensorArrayId", type: "tensor"}]}, {tfOpName: "StatelessIf", category: "control", inputs: [{start: 0, name: "cond", type: "tensor"}, {start: 1, end: 0, name: "args", type: "tensors"}], attrs: [{tfName: "then_branch", name: "thenBranch", type: "func"}, {tfName: "else_branch", name: "elseBranch", type: "func"}]}, {tfOpName: "If", category: "control", inputs: [{start: 0, name: "cond", type: "tensor"}, {start: 1, end: 0, name: "args", type: "tensors"}], attrs: [{tfName: "then_branch", name: "thenBranch", type: "func"}, {tfName: "else_branch", name: "elseBranch", type: "func"}]}, {tfOpName: "StatelessWhile", category: "control", inputs: [{start: 0, end: 0, name: "args", type: "tensors"}], attrs: [{tfName: "cond", name: "cond", type: "func"}, {tfName: "body", name: "body", type: "func"}]}, {tfOpName: "While", category: "control", inputs: [{start: 0, end: 0, name: "args", type: "tensors"}], attrs: [{tfName: "cond", name: "cond", type: "func"}, {tfName: "body", name: "body", type: "func"}]}, {tfOpName: "TensorListScatter", category: "control", inputs: [{start: 0, name: "tensor", type: "tensor"}, {start: 1, name: "indices", type: "number[]"}, {start: 2, name: "elementShape", type: "shape"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListScatterV2", category: "control", inputs: [{start: 0, name: "tensor", type: "tensor"}, {start: 1, name: "indices", type: "number[]"}, {start: 2, name: "elementShape", type: "shape"}, {start: 3, name: "numElements", type: "number"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListGather", category: "control", inputs: [{start: 0, name: "tensorListId", type: "tensor"}, {start: 1, name: "indices", type: "number[]"}, {start: 2, name: "elementShape", type: "shape"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListGetItem", category: "control", inputs: [{start: 0, name: "tensorListId", type: "tensor"}, {start: 1, name: "index", type: "number"}, {start: 2, name: "elementShape", type: "shape"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListSetItem", category: "control", inputs: [{start: 0, name: "tensorListId", type: "tensor"}, {start: 1, name: "index", type: "number"}, {start: 2, name: "tensor", type: "tensor"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListReserve", category: "control", inputs: [{start: 0, name: "elementShape", type: "shape"}, {start: 1, name: "numElements", type: "number"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListFromTensor", category: "control", inputs: [{start: 0, name: "tensor", type: "tensor"}, {start: 1, name: "elementShape", type: "shape"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListStack", category: "control", inputs: [{start: 0, name: "tensorListId", type: "tensor"}, {start: 1, name: "elementShape", type: "shape"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}, {tfName: "num_elements", name: "numElements", type: "dtype"}]}, {tfOpName: "TensorListSplit", category: "control", inputs: [{start: 0, name: "tensor", type: "tensor"}, {start: 1, name: "elementShape", type: "shape"}, {start: 2, name: "lengths", type: "number[]"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListConcat", category: "control", inputs: [{start: 0, name: "tensorListId", type: "tensor"}], attrs: [{tfName: "element_shape", name: "elementShape", type: "shape"}, {tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListPopBack", category: "control", inputs: [{start: 0, name: "tensorListId", type: "tensor"}, {start: 1, name: "elementShape", type: "shape"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}, {tfOpName: "TensorListPushBack", category: "control", inputs: [{start: 0, name: "tensorListId", type: "tensor"}, {start: 1, name: "tensor", type: "tensor"}], attrs: [{tfName: "element_dtype", name: "elementDType", type: "dtype"}]}], zD = {__proto__: null, json: BD};
  var PD = [{tfOpName: "AvgPool", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", notSupported: true}, {tfName: "ksize", name: "kernelSize", type: "number[]"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "MaxPool", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", notSupported: true}, {tfName: "ksize", name: "kernelSize", type: "number[]"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "MaxPoolWithArgmax", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "ksize", name: "kernelSize", type: "number[]"}, {tfName: "include_batch_in_index", name: "includeBatchInIndex", type: "bool"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "AvgPool3D", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", notSupported: true}, {tfName: "ksize", name: "kernelSize", type: "number[]"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "MaxPool3D", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", notSupported: true}, {tfName: "ksize", name: "kernelSize", type: "number[]"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Conv1D", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}], attrs: [{tfName: "stride", name: "stride", type: "number"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", defaultValue: "NWC"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "dilation", name: "dilation", type: "number", defaultValue: 1}]}, {tfOpName: "Conv2D", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "useCudnnOnGpu", name: "useCudnnOnGpu", type: "bool"}, {tfName: "data_format", name: "dataFormat", type: "string", defaultValue: "NHWC"}, {tfName: "explicit_paddings", name: "explicitPaddings", type: "number[]", defaultValue: []}, {tfName: "dilations", name: "dilations", type: "number[]"}]}, {tfOpName: "_FusedConv2D", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}, {start: 2, end: 0, name: "args", type: "tensors"}], attrs: [{tfName: "num_args", name: "numArgs", type: "number"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "explicit_paddings", name: "explicitPaddings", type: "number[]", defaultValue: []}, {tfName: "use_cudnn_on_gpu", name: "useCudnnOnGpu", type: "bool", defaultValue: true}, {tfName: "data_format", name: "dataFormat", type: "string", defaultValue: "NHWC"}, {tfName: "dilations", name: "dilations", type: "number[]", defaultValue: [1, 1, 1, 1]}, {tfName: "fused_ops", name: "fusedOps", type: "string[]", defaultValue: []}, {tfName: "epsilon", name: "epsilon", type: "number", defaultValue: 1e-4}]}, {tfOpName: "Conv2DBackpropInput", category: "convolution", inputs: [{start: 2, name: "x", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}, {start: 0, name: "outputShape", type: "number[]"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", notSupported: true}, {tfName: "explicit_paddings", name: "explicitPaddings", type: "number[]", defaultValue: []}]}, {tfOpName: "DepthwiseConv2d", category: "convolution", inputs: [{start: 0, name: "input", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", defaultValue: "NHWC"}, {tfName: "explicit_paddings", name: "explicitPaddings", type: "number[]", defaultValue: []}, {tfName: "dilations", name: "dilations", type: "number[]"}]}, {tfOpName: "DepthwiseConv2dNative", category: "convolution", inputs: [{start: 0, name: "input", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", defaultValue: "NHWC"}, {tfName: "explicit_paddings", name: "explicitPaddings", type: "number[]", defaultValue: []}, {tfName: "dilations", name: "dilations", type: "number[]"}]}, {tfOpName: "FusedDepthwiseConv2dNative", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}, {start: 2, end: 0, name: "args", type: "tensors"}], attrs: [{tfName: "num_args", name: "numArgs", type: "number"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", defaultValue: "NHWC"}, {tfName: "dilations", name: "dilations", type: "number[]", defaultValue: [1, 1, 1, 1]}, {tfName: "fused_ops", name: "fusedOps", type: "string[]", defaultValue: []}]}, {tfOpName: "Conv3D", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}, {tfName: "data_format", name: "dataFormat", type: "string", defaultValue: "NHWC"}, {tfName: "dilations", name: "dilations", type: "number[]"}]}, {tfOpName: "Dilation2D", category: "convolution", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "filter", type: "tensor"}], attrs: [{tfName: "strides", name: "strides", type: "number[]"}, {tfName: "rates", name: "dilations", type: "number[]"}, {tfName: "padding", name: "pad", type: "string"}]}], MD = {__proto__: null, json: PD};
  var HD = [{tfOpName: "Fill", category: "creation", inputs: [{start: 0, name: "shape", type: "number[]"}, {start: 1, name: "value", type: "number"}], attrs: [{tfName: "T", name: "dtype", type: "dtype"}]}, {tfOpName: "LinSpace", category: "creation", inputs: [{start: 0, name: "start", type: "number"}, {start: 1, name: "stop", type: "number"}, {start: 2, name: "num", type: "number"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "OneHot", category: "creation", inputs: [{start: 0, name: "indices", type: "tensor"}, {start: 1, name: "depth", type: "number"}, {start: 2, name: "onValue", type: "number", defaultValue: 1}, {start: 3, name: "offValue", type: "number", defaultValue: 0}], attrs: [{tfName: "axis", name: "axis", type: "number", notSupported: true}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Ones", category: "creation", inputs: [{start: 0, name: "shape", type: "number[]"}], attrs: [{tfName: "T", name: "dtype", type: "dtype"}]}, {tfOpName: "OnesLike", category: "creation", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "dtype", name: "dtype", type: "dtype"}]}, {tfOpName: "RandomUniform", category: "creation", inputs: [{start: 0, name: "shape", type: "number[]"}], attrs: [{tfName: "minval", name: "minval", type: "number", defaultValue: 0}, {tfName: "maxval", name: "maxval", type: "number", defaultValue: 1}, {tfName: "dtype", name: "dtype", type: "dtype"}, {tfName: "seed", name: "seed", type: "number", defaultValue: 0}, {tfName: "seed2", name: "seed2", type: "number", defaultValue: 0, notSupported: true}, {tfName: "T", name: "T", type: "number", notSupported: true}]}, {tfOpName: "Range", category: "creation", inputs: [{start: 0, name: "start", type: "number"}, {start: 1, name: "stop", type: "number"}, {start: 2, name: "step", type: "number", defaultValue: 0}], attrs: [{tfName: "Tidx", name: "dtype", type: "dtype"}]}, {tfOpName: "TruncatedNormal", category: "creation", inputs: [{start: 0, name: "shape", type: "number[]"}], attrs: [{tfName: "means", name: "mean", type: "number", defaultValue: 0}, {tfName: "stddev", name: "stdDev", type: "number", defaultValue: 1}, {tfName: "seed", name: "seed", type: "number"}, {tfName: "seed2", name: "seed2", type: "number", defaultValue: 0, notSupported: true}, {tfName: "dtype", name: "dtype", type: "dtype"}, {tfName: "T", name: "T", type: "number", notSupported: true}]}, {tfOpName: "Zeros", category: "creation", inputs: [{start: 0, name: "shape", type: "number[]"}], attrs: [{tfName: "T", name: "dtype", type: "dtype"}]}, {tfOpName: "ZerosLike", category: "creation", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype"}]}, {tfOpName: "Multinomial", category: "creation", inputs: [{start: 0, name: "logits", type: "tensor"}, {start: 1, name: "numSamples", type: "number"}], attrs: [{tfName: "seed", name: "seed", type: "number"}, {tfName: "seed2", name: "seed2", type: "number"}, {tfName: "T", name: "dtype", type: "dtype"}, {tfName: "output_dtype", name: "output_dtype", type: "dtype"}]}], VD = {__proto__: null, json: HD};
  var GD = [{tfOpName: "NonMaxSuppressionV2", category: "dynamic", inputs: [{start: 0, name: "boxes", type: "tensor"}, {start: 1, name: "scores", type: "tensor"}, {start: 2, name: "maxOutputSize", type: "number"}, {start: 3, name: "iouThreshold", type: "number"}]}, {tfOpName: "NonMaxSuppressionV3", category: "dynamic", inputs: [{start: 0, name: "boxes", type: "tensor"}, {start: 1, name: "scores", type: "tensor"}, {start: 2, name: "maxOutputSize", type: "number"}, {start: 3, name: "iouThreshold", type: "number"}, {start: 4, name: "scoreThreshold", type: "number"}]}, {tfOpName: "NonMaxSuppressionV4", category: "dynamic", inputs: [{start: 0, name: "boxes", type: "tensor"}, {start: 1, name: "scores", type: "tensor"}, {start: 2, name: "maxOutputSize", type: "number"}, {start: 3, name: "iouThreshold", type: "number"}, {start: 4, name: "scoreThreshold", type: "number"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}, {tfName: "T_threshold", name: "threshold", type: "dtype", notSupported: true}, {tfName: "pad_to_max_output_size", name: "padToMaxOutputSize", type: "bool"}]}, {tfOpName: "NonMaxSuppressionV5", category: "dynamic", inputs: [{start: 0, name: "boxes", type: "tensor"}, {start: 1, name: "scores", type: "tensor"}, {start: 2, name: "maxOutputSize", type: "number"}, {start: 3, name: "iouThreshold", type: "number"}, {start: 4, name: "scoreThreshold", type: "number"}, {start: 5, name: "softNmsSigma", type: "number"}]}, {tfOpName: "Where", category: "dynamic", inputs: [{start: 0, name: "condition", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "ListDiff", category: "dynamic", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "y", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}], qD = {__proto__: null, json: GD};
  var YD = [{tfOpName: "TopKV2", category: "evaluation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "k", type: "number"}], attrs: [{tfName: "sorted", name: "sorted", type: "bool"}]}, {tfOpName: "Unique", category: "evaluation", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "UniqueV2", category: "evaluation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number"}]}], KD = {__proto__: null, json: YD};
  var jD = [{tfOpName: "PlaceholderWithDefault", category: "graph", inputs: [{start: 0, name: "default", type: "tensor"}], attrs: [{tfName: "shape", name: "shape", type: "shape"}, {tfName: "dtype", name: "dtype", type: "dtype"}]}, {tfOpName: "Placeholder", category: "graph", attrs: [{tfName: "shape", name: "shape", type: "shape"}, {tfName: "dtype", name: "dtype", type: "dtype"}]}, {tfOpName: "Const", category: "graph"}, {tfOpName: "Identity", category: "graph", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "IdentityN", category: "graph", inputs: [{start: 0, end: 0, name: "x", type: "tensors"}]}, {tfOpName: "Snapshot", category: "graph", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "Rank", category: "graph", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "Size", category: "graph", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "Shape", category: "graph", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "ShapeN", category: "graph", inputs: [{start: 0, end: 0, name: "x", type: "tensors"}]}, {tfOpName: "Print", category: "graph", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "data", type: "tensors"}], attrs: [{tfName: "message", name: "message", type: "string"}, {tfName: "first_n", name: "firstN", type: "number", notSupported: true}, {tfName: "summarize", name: "summarize", type: "number", defaultValue: 3}]}, {tfOpName: "NoOp", category: "graph", inputs: []}, {tfOpName: "StopGradient", category: "graph", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "FakeQuantWithMinMaxVars", category: "graph", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "min", name: "min", type: "number"}, {tfName: "max", name: "max", type: "number"}]}], $D = {__proto__: null, json: jD}, XD = [{tfOpName: "HashTable", category: "hash_table", inputs: [], attrs: [{tfName: "shared_name", name: "sharedName", type: "string"}, {tfName: "use_node_name_sharing", name: "useNodeNameSharing", type: "bool"}, {tfName: "key_dtype", name: "keyDType", type: "dtype"}, {tfName: "value_dtype", name: "valueDType", type: "dtype"}]}, {tfOpName: "HashTableV2", category: "hash_table", inputs: [], attrs: [{tfName: "shared_name", name: "sharedName", type: "string"}, {tfName: "use_node_name_sharing", name: "useNodeNameSharing", type: "bool"}, {tfName: "key_dtype", name: "keyDType", type: "dtype"}, {tfName: "value_dtype", name: "valueDType", type: "dtype"}]}, {tfOpName: "LookupTableImport", category: "hash_table", inputs: [{start: 0, name: "tableHandle", type: "tensor"}, {start: 1, name: "keys", type: "tensor"}, {start: 2, name: "values", type: "tensor"}], attrs: [{tfName: "Tin", name: "tIn", type: "dtype", notSupported: true}, {tfName: "Tout", name: "tOut", type: "dtype", notSupported: true}]}, {tfOpName: "LookupTableImportV2", category: "hash_table", inputs: [{start: 0, name: "tableHandle", type: "tensor"}, {start: 1, name: "keys", type: "tensor"}, {start: 2, name: "values", type: "tensor"}], attrs: [{tfName: "Tin", name: "tIn", type: "dtype", notSupported: true}, {tfName: "Tout", name: "tOut", type: "dtype", notSupported: true}]}, {tfOpName: "LookupTableFind", category: "hash_table", inputs: [{start: 0, name: "tableHandle", type: "tensor"}, {start: 1, name: "keys", type: "tensor"}, {start: 2, name: "defaultValue", type: "tensor"}], attrs: [{tfName: "Tin", name: "tIn", type: "dtype", notSupported: true}, {tfName: "Tout", name: "tOut", type: "dtype", notSupported: true}]}, {tfOpName: "LookupTableFindV2", category: "hash_table", inputs: [{start: 0, name: "tableHandle", type: "tensor"}, {start: 1, name: "keys", type: "tensor"}, {start: 2, name: "defaultValue", type: "tensor"}], attrs: [{tfName: "Tin", name: "tIn", type: "dtype", notSupported: true}, {tfName: "Tout", name: "tOut", type: "dtype", notSupported: true}]}], JD = {__proto__: null, json: XD};
  var ZD = [{tfOpName: "ResizeBilinear", category: "image", inputs: [{start: 0, name: "images", type: "tensor"}, {start: 1, name: "size", type: "number[]"}], attrs: [{tfName: "align_corners", name: "alignCorners", type: "bool"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "ResizeNearestNeighbor", category: "image", inputs: [{start: 0, name: "images", type: "tensor"}, {start: 1, name: "size", type: "number[]"}], attrs: [{tfName: "align_corners", name: "alignCorners", type: "bool"}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "CropAndResize", category: "image", inputs: [{start: 0, name: "image", type: "tensor"}, {start: 1, name: "boxes", type: "tensor"}, {start: 2, name: "boxInd", type: "tensor"}, {start: 3, name: "cropSize", type: "number[]"}], attrs: [{tfName: "method", name: "method", type: "string"}, {tfName: "extrapolation_value", name: "extrapolationValue", type: "number"}]}], QD = {__proto__: null, json: ZD};
  var ek = [{tfOpName: "Equal", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "NotEqual", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Greater", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "GreaterEqual", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Less", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "LessEqual", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "LogicalAnd", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "LogicalNot", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "LogicalOr", category: "logical", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Select", category: "logical", inputs: [{start: 0, name: "condition", type: "tensor"}, {start: 1, name: "a", type: "tensor"}, {start: 2, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "SelectV2", category: "logical", inputs: [{start: 0, name: "condition", type: "tensor"}, {start: 1, name: "a", type: "tensor"}, {start: 2, name: "b", type: "tensor"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}], tk = {__proto__: null, json: ek};
  var nk = [{tfOpName: "_FusedMatMul", category: "matrices", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}, {start: 2, end: 0, name: "args", type: "tensors"}], attrs: [{tfName: "num_args", name: "numArgs", type: "number"}, {tfName: "fused_ops", name: "fusedOps", type: "string[]", defaultValue: []}, {tfName: "epsilon", name: "epsilon", type: "number", defaultValue: 1e-4}, {tfName: "transpose_a", name: "transposeA", type: "bool", defaultValue: false}, {tfName: "transpose_b", name: "transposeB", type: "bool", defaultValue: false}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "MatMul", category: "matrices", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "transpose_a", name: "transposeA", type: "bool", defaultValue: false}, {tfName: "transpose_b", name: "transposeB", type: "bool", defaultValue: false}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "BatchMatMul", category: "matrices", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "adj_x", name: "transposeA", type: "bool", defaultValue: false}, {tfName: "adj_y", name: "transposeB", type: "bool", defaultValue: false}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "BatchMatMulV2", category: "matrices", inputs: [{start: 0, name: "a", type: "tensor"}, {start: 1, name: "b", type: "tensor"}], attrs: [{tfName: "adj_x", name: "transposeA", type: "bool", defaultValue: false}, {tfName: "adj_y", name: "transposeB", type: "bool", defaultValue: false}, {tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}, {tfOpName: "Transpose", category: "matrices", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "perm", type: "number[]"}], attrs: [{tfName: "T", name: "dtype", type: "dtype", notSupported: true}]}], rk = {__proto__: null, json: nk};
  var ik = [{tfOpName: "FusedBatchNorm", category: "normalization", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "scale", type: "tensor"}, {start: 2, name: "offset", type: "tensor"}, {start: 3, name: "mean", type: "tensor"}, {start: 4, name: "variance", type: "tensor"}], attrs: [{tfName: "epsilon", name: "epsilon", type: "number", defaultValue: 1e-3}, {tfName: "data_format", name: "dataFormat", type: "string", notSupported: true}]}, {tfOpName: "FusedBatchNormV2", category: "normalization", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "scale", type: "tensor"}, {start: 2, name: "offset", type: "tensor"}, {start: 3, name: "mean", type: "tensor"}, {start: 4, name: "variance", type: "tensor"}], attrs: [{tfName: "epsilon", name: "epsilon", type: "number", defaultValue: 1e-3}, {tfName: "data_format", name: "dataFormat", type: "string", notSupported: true}]}, {tfOpName: "FusedBatchNormV3", category: "normalization", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "scale", type: "tensor"}, {start: 2, name: "offset", type: "tensor"}, {start: 3, name: "mean", type: "tensor"}, {start: 4, name: "variance", type: "tensor"}], attrs: [{tfName: "epsilon", name: "epsilon", type: "number", defaultValue: 1e-3}, {tfName: "data_format", name: "dataFormat", type: "string", notSupported: true}]}, {tfOpName: "LRN", category: "normalization", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "depth_radius", name: "radius", type: "number", defaultValue: 5}, {tfName: "bias", name: "bias", type: "number", defaultValue: 1}, {tfName: "alpha", name: "alpha", type: "number", defaultValue: 1}, {tfName: "beta", name: "beta", type: "number", defaultValue: 0.5}]}, {tfOpName: "Softmax", category: "normalization", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "LogSoftmax", category: "normalization", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "SparseToDense", category: "normalization", inputs: [{start: 0, name: "sparseIndices", type: "tensor"}, {start: 1, name: "outputShape", type: "number[]"}, {start: 2, name: "sparseValues", type: "tensor"}, {start: 3, name: "defaultValue", type: "tensor"}], attrs: [{tfName: "validate_indices", name: "validateIndices", type: "bool", defaultValue: true, notSupported: true}]}], ak = {__proto__: null, json: ik};
  var sk = [{tfOpName: "Max", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number[]"}], attrs: [{tfName: "keep_dims", name: "keepDims", type: "bool"}]}, {tfOpName: "Mean", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number[]"}], attrs: [{tfName: "keep_dims", name: "keepDims", type: "bool"}]}, {tfOpName: "Min", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number[]"}], attrs: [{tfName: "keep_dims", name: "keepDims", type: "bool"}]}, {tfOpName: "Sum", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number[]"}], attrs: [{tfName: "keep_dims", name: "keepDims", type: "bool"}]}, {tfOpName: "All", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number[]"}], attrs: [{tfName: "keep_dims", name: "keepDims", type: "bool"}]}, {tfOpName: "Any", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number[]"}], attrs: [{tfName: "keep_dims", name: "keepDims", type: "bool"}]}, {tfOpName: "ArgMax", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number"}]}, {tfOpName: "ArgMin", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number"}]}, {tfOpName: "Prod", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number[]"}], attrs: [{tfName: "keep_dims", name: "keepDims", type: "bool"}]}, {tfOpName: "Cumsum", category: "reduction", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number"}], attrs: [{tfName: "exclusive", name: "exclusive", type: "bool"}, {tfName: "reverse", name: "reverse", type: "bool"}]}], ok = {__proto__: null, json: sk};
  var ck = [{tfOpName: "ConcatV2", category: "slice_join", inputs: [{start: 0, end: -1, name: "tensors", type: "tensors"}, {start: -1, name: "axis", type: "number"}], attrs: [{tfName: "N", name: "n", type: "number", defaultValue: 2}]}, {tfOpName: "Concat", category: "slice_join", inputs: [{start: 1, end: 0, name: "tensors", type: "tensors"}, {start: 0, name: "axis", type: "number"}], attrs: [{tfName: "N", name: "n", type: "number", defaultValue: 2}]}, {tfOpName: "GatherV2", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "indices", type: "tensor"}, {start: 2, name: "axis", type: "number", defaultValue: 0}]}, {tfOpName: "Gather", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "indices", type: "tensor"}], attrs: [{tfName: "axis", name: "axis", type: "number", defaultValue: 0}, {tfName: "validate_indices", name: "validateIndices", type: "bool", notSupported: true}]}, {tfOpName: "Reverse", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "dims", type: "bool", notSupported: true}]}, {tfOpName: "ReverseV2", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number[]"}]}, {tfOpName: "Slice", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "begin", type: "number[]"}, {start: 2, name: "size", type: "number[]"}]}, {tfOpName: "StridedSlice", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "begin", type: "number[]"}, {start: 2, name: "end", type: "number[]"}, {start: 3, name: "strides", type: "number[]"}], attrs: [{tfName: "begin_mask", name: "beginMask", type: "number", defaultValue: 0}, {tfName: "end_mask", name: "endMask", type: "number", defaultValue: 0}, {tfName: "new_axis_mask", name: "newAxisMask", type: "number", defaultValue: 0}, {tfName: "ellipsis_mask", name: "ellipsisMask", type: "number", defaultValue: 0}, {tfName: "shrink_axis_mask", name: "shrinkAxisMask", type: "number", defaultValue: 0}]}, {tfOpName: "Pack", category: "slice_join", inputs: [{start: 0, end: 0, name: "tensors", type: "tensors"}], attrs: [{tfName: "axis", name: "axis", type: "number", defaultValue: 0}]}, {tfOpName: "Unpack", category: "slice_join", inputs: [{start: 0, name: "tensor", type: "tensor"}], attrs: [{tfName: "axis", name: "axis", type: "number", defaultValue: 0}, {tfName: "num", name: "num", type: "number", defaultValue: 0, notSupported: true}]}, {tfOpName: "Tile", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "reps", type: "number[]"}]}, {tfOpName: "Split", category: "slice_join", inputs: [{start: 0, name: "axis", type: "number", defaultValue: 0}, {start: 1, name: "x", type: "tensor"}], attrs: [{tfName: "num_split", name: "numOrSizeSplits", type: "number", defaultValue: 1}]}, {tfOpName: "SplitV", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "numOrSizeSplits", type: "number[]"}, {start: 2, name: "axis", type: "number", defaultValue: 0}]}, {tfOpName: "ScatterNd", category: "slice_join", inputs: [{start: 0, name: "indices", type: "tensor"}, {start: 1, name: "values", type: "tensor"}, {start: 2, name: "shape", type: "number[]"}]}, {tfOpName: "GatherNd", category: "slice_join", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "indices", type: "tensor"}]}, {tfOpName: "SparseToDense", category: "slice_join", inputs: [{start: 0, name: "sparseIndices", type: "tensor"}, {start: 1, name: "outputShape", type: "number[]"}, {start: 2, name: "sparseValues", type: "tensor"}, {start: 3, name: "defaultValue", type: "tensor"}], attrs: [{tfName: "validate_indices", name: "validateIndices", type: "bool", defaultValue: false, notSupported: true}]}], lk = {__proto__: null, json: ck};
  var uk = [{tfOpName: "FFT", category: "spectral", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "IFFT", category: "spectral", inputs: [{start: 0, name: "x", type: "tensor"}]}, {tfOpName: "RFFT", category: "spectral", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "fft_length", type: "number", notSupported: true}]}, {tfOpName: "IRFFT", category: "spectral", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "fft_length", type: "number", notSupported: true}]}], hk = {__proto__: null, json: uk};
  var dk = [{tfOpName: "Cast", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "SrcT", name: "sdtype", type: "dtype", notSupported: true}, {tfName: "DstT", name: "dtype", type: "dtype"}]}, {tfOpName: "ExpandDims", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "axis", type: "number"}]}, {tfOpName: "MirrorPad", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "padding", type: "number[]"}], attrs: [{tfName: "mode", name: "mode", type: "string"}]}, {tfOpName: "Pad", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "padding", type: "number[]"}], attrs: [{tfName: "constant_value", name: "constantValue", type: "number", defaultValue: 0}]}, {tfOpName: "PadV2", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "padding", type: "number[]"}, {start: 2, name: "constantValue", type: "number", defaultValue: 0}]}, {tfOpName: "Reshape", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "shape", type: "number[]"}]}, {tfOpName: "Squeeze", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "axis", tfDeprecatedName: "squeeze_dims", name: "axis", type: "number[]"}]}, {tfOpName: "SpaceToBatchND", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "blockShape", type: "number[]"}, {start: 2, name: "paddings", type: "number[]"}]}, {tfOpName: "BatchToSpaceND", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "blockShape", type: "number[]"}, {start: 2, name: "crops", type: "number[]"}]}, {tfOpName: "DepthToSpace", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}], attrs: [{tfName: "block_size", name: "blockSize", type: "number"}, {tfName: "data_format", name: "dataFormat", type: "string"}]}, {tfOpName: "BroadcastTo", category: "transformation", inputs: [{start: 0, name: "x", type: "tensor"}, {start: 1, name: "shape", type: "number[]"}], attrs: []}], pk = {__proto__: null, json: dk};
  var C1 = function() {
    function n() {
      var t = [FD, UD, zD, MD, VD, qD, KD, tk, QD, $D, rk, ak, ok, lk, hk, pk, JD], e = [].concat.apply([], _r(t.map(function(r) {
        return r.json;
      })));
      this.opMappers = e.reduce(function(r, i) {
        return r[i.tfOpName] = i, r;
      }, {});
    }
    return Object.defineProperty(n, "Instance", {get: function() {
      return this._instance || (this._instance = new this());
    }, enumerable: true, configurable: true}), n.prototype.transformGraph = function(t, e) {
      var r = this;
      e === void 0 && (e = {});
      var i = t.node, a = [], s = [], o = [], c = i.reduce(function(g, y) {
        return g[y.name] = r.mapNode(y), y.op.startsWith("Placeholder") ? a.push(g[y.name]) : y.op === "Const" ? s.push(g[y.name]) : (y.input == null || y.input.length === 0) && o.push(g[y.name]), g;
      }, {}), l = [], u = [], h = {}, d = {};
      e != null && (h = this.mapSignatureEntries(e.inputs), d = this.mapSignatureEntries(e.outputs));
      var p = Object.keys(c);
      p.forEach(function(g) {
        var y = c[g];
        y.inputNames.forEach(function(w) {
          var b = yt(Qn(w), 1), L = b[0];
          y.inputs.push(c[L]), c[L].children.push(y);
        });
      }), Object.keys(d).length === 0 ? p.forEach(function(g) {
        var y = c[g];
        y.children.length === 0 && u.push(y);
      }) : Object.keys(d).forEach(function(g) {
        var y = yt(Qn(g), 1), w = y[0], b = c[w];
        b != null && (b.signatureKey = d[g], u.push(b));
      }), Object.keys(h).length > 0 ? Object.keys(h).forEach(function(g) {
        var y = yt(Qn(g), 1), w = y[0], b = c[w];
        b && (b.signatureKey = h[g], l.push(b));
      }) : l = a;
      var f = {};
      t.library != null && t.library.function != null && (f = t.library.function.reduce(function(g, y) {
        return g[y.signature.name] = r.mapFunction(y), g;
      }, {}));
      var m = {nodes: c, inputs: l, outputs: u, weights: s, placeholders: a, signature: e, functions: f};
      return o.length > 0 && (m.initNodes = o), m;
    }, n.prototype.mapSignatureEntries = function(t) {
      return Object.keys(t || {}).reduce(function(e, r) {
        return e[t[r].name] = r, e;
      }, {});
    }, n.prototype.mapNode = function(t) {
      var e = N1(t.op) || this.opMappers[t.op] || {};
      t.attr == null && (t.attr = {});
      var r = {name: t.name, op: t.op, category: e.category, inputNames: (t.input || []).map(function(i) {
        return i.startsWith("^") ? i.substr(1) : i;
      }), inputs: [], children: [], inputParams: {}, attrParams: {}, rawAttrs: t.attr};
      return e.inputs != null && (r.inputParams = e.inputs.reduce(function(i, a) {
        return i[a.name] = {type: a.type, inputIndexStart: a.start, inputIndexEnd: a.end}, i;
      }, {})), e.attrs != null && (r.attrParams = e.attrs.reduce(function(i, a) {
        var s = a.type, o = void 0;
        switch (a.type) {
          case "string":
            o = md(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = md(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "string[]":
            o = Sd(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = Sd(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "number":
            o = yd(t.attr, a.tfName, a.defaultValue || 0), o === void 0 && !!a.tfDeprecatedName && (o = yd(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "number[]":
            o = Ld(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = Ld(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "bool":
            o = gd(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = gd(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "bool[]":
            o = Ad(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = Ad(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "shape":
            o = xd(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = xd(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "shape[]":
            o = Id(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = Id(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "dtype":
            o = wd(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = wd(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "dtype[]":
            o = bd(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = bd(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "func":
            o = _1(t.attr, a.tfName, a.defaultValue), o === void 0 && !!a.tfDeprecatedName && (o = _1(t.attr, a.tfDeprecatedName, a.defaultValue));
            break;
          case "tensor":
          case "tensors":
            break;
          default:
            throw new Error("Unsupported param type: " + a.type + " for op: " + t.op);
        }
        return i[a.name] = {value: o, type: s}, i;
      }, {})), r;
    }, n.prototype.mapFunction = function(t) {
      var e = this, r = t.nodeDef, i = [], a = [], s = {};
      r != null && (s = r.reduce(function(d, p) {
        return d[p.name] = e.mapNode(p), p.op === "Const" && a.push(d[p.name]), d;
      }, {}));
      var o = [], c = [];
      t.signature.inputArg.forEach(function(d) {
        var p = yt(Qn(d.name), 1), f = p[0], m = {name: f, op: "Placeholder", inputs: [], inputNames: [], category: "graph", inputParams: {}, attrParams: {dtype: {value: vd(d.type), type: "dtype"}}, children: []};
        m.signatureKey = d.name, o.push(m), s[f] = m;
      });
      var l = Object.keys(s);
      l.forEach(function(d) {
        var p = s[d];
        p.inputNames.forEach(function(f) {
          var m = yt(Qn(f), 1), g = m[0];
          p.inputs.push(s[g]), s[g].children.push(p);
        });
      });
      var u = t.ret;
      t.signature.outputArg.forEach(function(d) {
        var p = yt(Qn(u[d.name]), 2), f = p[0], m = p[1], g = s[f];
        g != null && (g.defaultOutput = m, c.push(g));
      });
      var h = this.mapArgsToSignature(t);
      return {nodes: s, inputs: o, outputs: c, weights: a, placeholders: i, signature: h};
    }, n.prototype.mapArgsToSignature = function(t) {
      var e = this;
      return {methodName: t.signature.name, inputs: t.signature.inputArg.reduce(function(r, i) {
        return r[i.name] = e.mapArgToTensorInfo(i), r;
      }, {}), outputs: t.signature.outputArg.reduce(function(r, i) {
        return r[i.name] = e.mapArgToTensorInfo(i, t.ret), r;
      }, {})};
    }, n.prototype.mapArgToTensorInfo = function(t, e) {
      var r = t.name;
      return e != null && (r = e[r]), {name: r, dtype: t.type};
    }, n;
  }();
  function fk(n) {
    var t = W.env().global;
    if (typeof t.atob != "undefined")
      return t.atob(n);
    if (typeof Buffer != "undefined")
      return new Buffer(n, "base64").toString();
    throw new Error("Unable to decode base64 in this environment. Missing built-in atob() or Buffer()");
  }
  function R1(n, t) {
    var e = Array.isArray(n) ? String.fromCharCode.apply(null, n) : fk(n);
    return t ? e : e.toLowerCase();
  }
  function md(n, t, e, r) {
    r === void 0 && (r = false);
    var i = n[t];
    return i != null ? R1(i.s, r) : e;
  }
  function gd(n, t, e) {
    var r = n[t];
    return r ? r.b : e;
  }
  function yd(n, t, e) {
    var r = n[t] || {}, i = r.i != null ? r.i : r.f != null ? r.f : e;
    return typeof i == "number" ? i : parseInt(i, 10);
  }
  function vd(n) {
    typeof n == "string" && (n = An[n]);
    switch (n) {
      case An.DT_FLOAT:
        return "float32";
      case An.DT_INT32:
      case An.DT_INT64:
      case An.DT_INT8:
      case An.DT_UINT8:
        return "int32";
      case An.DT_BOOL:
        return "bool";
      case An.DT_DOUBLE:
        return "float32";
      case An.DT_STRING:
        return "string";
      default:
        return null;
    }
  }
  function _1(n, t, e) {
    var r = n[t];
    return r && r.func ? r.func.name : e;
  }
  function wd(n, t, e) {
    var r = n[t];
    return r && r.type ? vd(r.type) : e;
  }
  function bd(n, t, e) {
    var r = n[t];
    return r && r.list && r.list.type ? r.list.type.map(function(i) {
      return vd(i);
    }) : e;
  }
  function O1(n) {
    return n.unknownRank ? void 0 : n.dim != null ? n.dim.map(function(t) {
      return typeof t.size == "number" ? t.size : parseInt(t.size, 10);
    }) : [];
  }
  function xd(n, t, e) {
    var r = n[t];
    return r && r.shape ? O1(r.shape) : e;
  }
  function Ld(n, t, e) {
    var r = n[t];
    return r ? ((r.list.f && r.list.f.length ? r.list.f : r.list.i) || []).map(function(i) {
      return typeof i == "number" ? i : parseInt(i, 10);
    }) : e;
  }
  function Sd(n, t, e, r) {
    r === void 0 && (r = false);
    var i = n[t];
    return i && i.list && i.list.s ? i.list.s.map(function(a) {
      return R1(a, r);
    }) : e;
  }
  function Id(n, t, e) {
    var r = n[t];
    return r && r.list && r.list.shape ? r.list.shape.map(function(i) {
      return O1(i);
    }) : e;
  }
  function Ad(n, t, e) {
    var r = n[t];
    return r && r.list && r.list.b ? r.list.b : e;
  }
  var mk = function() {
    function n(t, e, r) {
      var i = this;
      this.node = t, this.tensorMap = e, this.context = r, this.inputs = [], this.attrs = {}, this.inputs = t.inputNames.map(function(a) {
        return i.getInput(a);
      }), t.rawAttrs != null && (this.attrs = Object.keys(t.rawAttrs).reduce(function(a, s) {
        return a[s] = i.getAttr(s), a;
      }, {}));
    }
    return n.prototype.getInput = function(t) {
      return Gt(t, this.tensorMap, this.context);
    }, n.prototype.getAttr = function(t, e) {
      var r = this.node.rawAttrs[t];
      if (r.tensor != null)
        return Gt(t, this.tensorMap, this.context);
      if (r.i != null || r.f != null)
        return yd(this.node.rawAttrs, t, e);
      if (r.s != null)
        return md(this.node.rawAttrs, t, e);
      if (r.b != null)
        return gd(this.node.rawAttrs, t, e);
      if (r.shape != null)
        return xd(this.node.rawAttrs, t, e);
      if (r.type != null)
        return wd(this.node.rawAttrs, t, e);
      if (r.list != null) {
        if (r.list.i != null || r.list.f != null)
          return Ld(this.node.rawAttrs, t, e);
        if (r.list.s != null)
          return Sd(this.node.rawAttrs, t, e);
        if (r.list.shape != null)
          return Id(this.node.rawAttrs, t, e);
        if (r.list.b != null)
          return Ad(this.node.rawAttrs, t, e);
        if (r.list.type != null)
          return bd(this.node.rawAttrs, t, e);
      }
      return e;
    }, n;
  }();
  var gk = function(n, t, e) {
    switch (n.op) {
      case "BiasAdd":
      case "AddV2":
      case "Add":
        return [W.add(T("a", n, t, e), T("b", n, t, e))];
      case "AddN":
        return [W.addN(T("tensors", n, t, e))];
      case "FloorMod":
      case "Mod":
        return [W.mod(T("a", n, t, e), T("b", n, t, e))];
      case "Mul":
        return [W.mul(T("a", n, t, e), T("b", n, t, e))];
      case "RealDiv":
      case "Div":
        return [W.div(T("a", n, t, e), T("b", n, t, e))];
      case "DivNoNan":
        return [W.divNoNan(T("a", n, t, e), T("b", n, t, e))];
      case "FloorDiv":
        return [W.floorDiv(T("a", n, t, e), T("b", n, t, e))];
      case "Sub":
        return [W.sub(T("a", n, t, e), T("b", n, t, e))];
      case "Minimum":
        return [W.minimum(T("a", n, t, e), T("b", n, t, e))];
      case "Maximum":
        return [W.maximum(T("a", n, t, e), T("b", n, t, e))];
      case "Pow":
        return [W.pow(T("a", n, t, e), T("b", n, t, e))];
      case "SquaredDifference":
        return [W.squaredDifference(T("a", n, t, e), T("b", n, t, e))];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var yk = function(n, t, e) {
    switch (n.op) {
      case "Abs":
      case "ComplexAbs":
        return [W.abs(T("x", n, t, e))];
      case "Acos":
        return [W.acos(T("x", n, t, e))];
      case "Acosh":
        return [W.acosh(T("x", n, t, e))];
      case "Asin":
        return [W.asin(T("x", n, t, e))];
      case "Asinh":
        return [W.asinh(T("x", n, t, e))];
      case "Atan":
        return [W.atan(T("x", n, t, e))];
      case "Atan2":
        return [W.atan2(T("x", n, t, e), T("y", n, t, e))];
      case "Atanh":
        return [W.atanh(T("x", n, t, e))];
      case "Ceil":
        return [W.ceil(T("x", n, t, e))];
      case "Complex":
        return [W.complex(T("real", n, t, e), T("imag", n, t, e))];
      case "Cos":
        return [W.cos(T("x", n, t, e))];
      case "Cosh":
        return [W.cosh(T("x", n, t, e))];
      case "Elu":
        return [W.elu(T("x", n, t, e))];
      case "Erf":
        return [W.erf(T("x", n, t, e))];
      case "Exp":
        return [W.exp(T("x", n, t, e))];
      case "Expm1":
        return [W.expm1(T("x", n, t, e))];
      case "Floor":
        return [W.floor(T("x", n, t, e))];
      case "Log":
        return [W.log(T("x", n, t, e))];
      case "Log1p":
        return [W.log1p(T("x", n, t, e))];
      case "Imag":
        return [W.imag(T("x", n, t, e))];
      case "Neg":
        return [W.neg(T("x", n, t, e))];
      case "Reciprocal":
        return [W.reciprocal(T("x", n, t, e))];
      case "Real":
        return [W.real(T("x", n, t, e))];
      case "Relu":
        return [W.relu(T("x", n, t, e))];
      case "Round":
        return [W.round(T("x", n, t, e))];
      case "Selu":
        return [W.selu(T("x", n, t, e))];
      case "Sigmoid":
        return [W.sigmoid(T("x", n, t, e))];
      case "Sin":
        return [W.sin(T("x", n, t, e))];
      case "Sign":
        return [W.sign(T("x", n, t, e))];
      case "Sinh":
        return [W.sinh(T("x", n, t, e))];
      case "Softplus":
        return [W.softplus(T("x", n, t, e))];
      case "Sqrt":
        return [W.sqrt(T("x", n, t, e))];
      case "Square":
        return [W.square(T("x", n, t, e))];
      case "Tanh":
        return [W.tanh(T("x", n, t, e))];
      case "Tan":
        return [W.tan(T("x", n, t, e))];
      case "Relu6":
      case "ClipByValue":
        return [W.clipByValue(T("x", n, t, e), T("clipValueMin", n, t, e), T("clipValueMax", n, t, e))];
      case "Rsqrt":
        return [W.rsqrt(Gt(n.inputNames[0], t, e))];
      case "Prod":
        return [W.prod(T("x", n, t, e), T("axes", n, t, e))];
      case "LeakyRelu":
        return [W.leakyRelu(T("x", n, t, e), T("alpha", n, t, e))];
      case "Prelu":
        return [W.prelu(T("x", n, t, e), T("alpha", n, t, e))];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  function pn(n, t, e) {
    e === void 0 && (e = ""), W.util.assert(vk(n, t), function() {
      return e + (" Shapes " + n + " and " + t + " must match");
    });
  }
  function vk(n, t) {
    if (n.length !== t.length)
      return false;
    for (var e = 0; e < n.length; e++)
      if (n[e] !== -1 && t[e] !== -1 && n[e] !== t[e])
        return false;
    return true;
  }
  var wk = function() {
    function n(t, e, r, i, a, s, o) {
      this.name = t, this.dtype = e, this.maxSize = r, this.elementShape = i, this.identicalElementShapes = a, this.dynamicSize = s, this.clearAfterRead = o, this.tensors = [], this.closed_ = false, this.idTensor = W.scalar(0), W.keep(this.idTensor);
    }
    return Object.defineProperty(n.prototype, "id", {get: function() {
      return this.idTensor.id;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "closed", {get: function() {
      return this.closed_;
    }, enumerable: true, configurable: true}), n.prototype.clearAndClose = function(t) {
      this.tensors.forEach(function(e) {
        (t == null || !t.has(e.tensor.id)) && e.tensor.dispose();
      }), this.tensors = [], this.closed_ = true, this.idTensor.dispose();
    }, n.prototype.size = function() {
      return this.tensors.length;
    }, n.prototype.read = function(t) {
      if (this.closed_)
        throw new Error("TensorArray " + this.name + " has already been closed.");
      if (t < 0 || t >= this.size())
        throw new Error("Tried to read from index " + t + ", but array size is: " + this.size());
      var e = this.tensors[t];
      if (e.cleared)
        throw new Error("TensorArray " + this.name + ": Could not read index " + t + " twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).");
      return this.clearAfterRead && (e.cleared = true), e.read = true, e.tensor;
    }, n.prototype.readMany = function(t) {
      var e = this;
      return t.map(function(r) {
        return e.read(r);
      });
    }, n.prototype.write = function(t, e) {
      if (this.closed_)
        throw new Error("TensorArray " + this.name + " has already been closed.");
      if (t < 0 || !this.dynamicSize && t >= this.maxSize)
        throw new Error("Tried to write to index " + t + ", but array is not resizeable and size is: " + this.maxSize);
      var r = this.tensors[t] || {};
      if (e.dtype !== this.dtype)
        throw new Error("TensorArray " + this.name + ": Could not write to TensorArray index " + t + `,
          because the value dtype is ` + e.dtype + ", but TensorArray dtype is " + this.dtype + ".");
      if (this.size() === 0 && (this.elementShape == null || this.elementShape.length === 0) && (this.elementShape = e.shape), pn(this.elementShape, e.shape, "TensorArray " + this.name + ": Could not write to TensorArray index " + t + "."), r.read)
        throw new Error("TensorArray " + this.name + ": Could not write to TensorArray index " + t + ", because it has already been read.");
      if (r.written)
        throw new Error("TensorArray " + this.name + ": Could not write to TensorArray index " + t + ", because it has already been written.");
      r.tensor = e, W.keep(e), r.written = true, this.tensors[t] = r;
    }, n.prototype.writeMany = function(t, e) {
      var r = this;
      if (t.length !== e.length)
        throw new Error("TensorArray " + this.name + ": could not write multiple tensors," + ("because the index size: " + t.length + " is not the same as tensors size: " + e.length + "."));
      t.forEach(function(i, a) {
        return r.write(i, e[a]);
      });
    }, n.prototype.gather = function(t, e) {
      if (!!e && e !== this.dtype)
        throw new Error("TensorArray dtype is " + this.dtype + " but gather requested dtype " + e);
      if (t)
        t = t.slice(0, this.size());
      else {
        t = [];
        for (var r = 0; r < this.size(); r++)
          t.push(r);
      }
      if (t.length === 0)
        return W.tensor([], [0].concat(this.elementShape));
      var i = this.readMany(t);
      return pn(this.elementShape, i[0].shape, "TensorArray shape mismatch: "), W.stack(i, 0);
    }, n.prototype.concat = function(t) {
      if (!!t && t !== this.dtype)
        throw new Error("TensorArray dtype is " + this.dtype + " but concat requested dtype " + t);
      if (this.size() === 0)
        return W.tensor([], [0].concat(this.elementShape));
      for (var e = [], r = 0; r < this.size(); r++)
        e.push(r);
      var i = this.readMany(e);
      return pn(this.elementShape, i[0].shape, "TensorArray shape mismatch: tensor array shape (" + this.elementShape + ") vs first tensor shape (" + i[0].shape + ")"), W.concat(i, 0);
    }, n.prototype.scatter = function(t, e) {
      if (e.dtype !== this.dtype)
        throw new Error("TensorArray dtype is " + this.dtype + " but tensor has dtype " + e.dtype);
      if (t.length !== e.shape[0])
        throw new Error("Expected len(indices) == tensor.shape[0], but saw: " + t.length + " vs. " + e.shape[0]);
      var r = Math.max.apply(Math, _r(t));
      if (!this.dynamicSize && r >= this.maxSize)
        throw new Error("Max index must be < array size (" + r + "  vs. " + this.maxSize + ")");
      this.writeMany(t, W.unstack(e, 0));
    }, n.prototype.split = function(t, e) {
      var r = this;
      if (e.dtype !== this.dtype)
        throw new Error("TensorArray dtype is " + this.dtype + " but tensor has dtype " + e.dtype);
      var i = 0, a = t.map(function(u) {
        return i += u, i;
      });
      if (i !== e.shape[0])
        throw new Error(`Expected sum of lengths to be equal to
          tensor.shape[0], but sum of lengths is
        ` + i + ", and tensor's shape is: " + e.shape);
      if (!this.dynamicSize && t.length !== this.maxSize)
        throw new Error("TensorArray's size is not equal to the size of lengths (" + this.maxSize + " vs. " + t.length + "), and the TensorArray is not marked as dynamically resizeable");
      var s = i === 0 ? 0 : e.size / i, o = [];
      W.tidy(function() {
        e = W.reshape(e, [1, i, s]);
        for (var u = 0; u < t.length; ++u) {
          var h = u === 0 ? 0 : a[u - 1], d = [0, h, 0], p = [1, t[u], s];
          o[u] = W.reshape(W.slice(e, d, p), r.elementShape);
        }
        return o;
      });
      for (var c = [], l = 0; l < t.length; l++)
        c[l] = l;
      this.writeMany(c, o);
    }, n;
  }();
  var Po = function() {
    function n(t, e, r, i) {
      i === void 0 && (i = -1), this.tensors = t, this.elementShape = e, this.elementDtype = r, t != null && t.forEach(function(a) {
        if (r !== a.dtype)
          throw new Error("Invalid data types; op elements " + r + ", but list elements " + a.dtype);
        pn(e, a.shape, "TensorList shape mismatch: "), W.keep(a);
      }), this.idTensor = W.scalar(0), this.maxNumElements = i, W.keep(this.idTensor);
    }
    return Object.defineProperty(n.prototype, "id", {get: function() {
      return this.idTensor.id;
    }, enumerable: true, configurable: true}), n.prototype.copy = function() {
      return new n(_r(this.tensors), this.elementShape, this.elementDtype);
    }, n.prototype.clearAndClose = function(t) {
      this.tensors.forEach(function(e) {
        (t == null || !t.has(e.id)) && e.dispose();
      }), this.tensors.length = 0, this.idTensor.dispose();
    }, n.prototype.size = function() {
      return this.tensors.length;
    }, n.prototype.stack = function(t, e, r) {
      var i = this;
      if (r === void 0 && (r = -1), e !== this.elementDtype)
        throw new Error("Invalid data types; op elements " + e + ", but list elements " + this.elementDtype);
      if (r !== -1 && this.tensors.length !== r)
        throw new Error("Operation expected a list with " + r + " elements but got a list with " + this.tensors.length + " elements.");
      return pn(t, this.elementShape, "TensorList shape mismatch: "), W.tidy(function() {
        var a = i.tensors.map(function(s) {
          return W.reshape(s, t);
        });
        return W.stack(a, 0);
      });
    }, n.prototype.popBack = function(t, e) {
      if (e !== this.elementDtype)
        throw new Error("Invalid data types; op elements " + e + ", but list elements " + this.elementDtype);
      if (this.size() === 0)
        throw new Error("Trying to pop from an empty list.");
      var r = this.tensors.pop();
      return pn(r.shape, t, "TensorList shape mismatch: "), W.reshape(r, t);
    }, n.prototype.pushBack = function(t) {
      if (t.dtype !== this.elementDtype)
        throw new Error("Invalid data types; op elements " + t.dtype + ", but list elements " + this.elementDtype);
      if (pn(t.shape, this.elementShape, "TensorList shape mismatch: "), this.maxNumElements === this.size())
        throw new Error("Trying to push element into a full list.");
      W.keep(t), this.tensors.push(t);
    }, n.prototype.resize = function(t) {
      if (t < 0)
        throw new Error("TensorListResize expects size to be non-negative. Got: " + t);
      if (this.maxNumElements !== -1 && t > this.maxNumElements)
        throw new Error("TensorListResize input size " + t + " is greater maxNumElement " + this.maxNumElements + ".");
      this.tensors.length = t;
    }, n.prototype.getItem = function(t, e, r) {
      if (r !== this.elementDtype)
        throw new Error("Invalid data types; op elements " + r + ", but list elements " + this.elementDtype);
      if (t < 0 || t > this.tensors.length)
        throw new Error("Trying to access element " + t + " in a list with " + this.tensors.length + " elements.");
      if (this.tensors[t] == null)
        throw new Error("element at index " + t + " is null.");
      return pn(this.tensors[t].shape, e, "TensorList shape mismatch: "), this.tensors[t];
    }, n.prototype.setItem = function(t, e) {
      if (e.dtype !== this.elementDtype)
        throw new Error("Invalid data types; op elements " + e.dtype + ", but list elements " + this.elementDtype);
      if (t < 0 || this.maxNumElements !== -1 && t >= this.maxNumElements)
        throw new Error("Trying to set element " + t + " in a list with max " + this.maxNumElements + " elements.");
      pn(this.elementShape, e.shape, "TensorList shape mismatch: "), W.keep(e), this.tensors[t] = e;
    }, n.prototype.gather = function(t, e, r) {
      var i = this;
      if (e !== this.elementDtype)
        throw new Error("Invalid data types; op elements " + e + ", but list elements " + this.elementDtype);
      return pn(this.elementShape, r, "TensorList shape mismatch: "), t = t.slice(0, this.size()), t.length === 0 ? W.tensor([], [0].concat(this.elementShape)) : W.tidy(function() {
        var a = t.map(function(s) {
          return W.reshape(i.tensors[s], r);
        });
        return W.stack(a, 0);
      });
    }, n.prototype.concat = function(t, e) {
      var r = this;
      if (!!t && t !== this.elementDtype)
        throw new Error("TensorList dtype is " + this.elementDtype + " but concat requested dtype " + t);
      return pn(this.elementShape, e, "TensorList shape mismatch: "), this.size() === 0 ? W.tensor([], [0].concat(this.elementShape)) : W.tidy(function() {
        var i = r.tensors.map(function(a) {
          return W.reshape(a, e);
        });
        return W.concat(i, 0);
      });
    }, n;
  }();
  function bk(n, t, e) {
    var r = n.dtype;
    if (n.shape.length < 1)
      throw new Error("Tensor must be at least a vector, but saw shape: " + n.shape);
    if (n.dtype !== e)
      throw new Error("Invalid data types; op elements " + n.dtype + ", but list elements " + e);
    var i = n.shape.slice(1);
    pn(i, t, "TensorList shape mismatch: ");
    var a = W.unstack(n);
    return new Po(a, t, r);
  }
  function xk(n, t, e) {
    return new Po([], n, t, e);
  }
  function Lk(n, t, e, r) {
    if (t.length !== n.shape[0])
      throw new Error("Expected len(indices) == tensor.shape[0], but saw: " + t.length + " vs. " + n.shape[0]);
    var i = Math.max.apply(Math, _r(t));
    if (r != null && r !== -1 && i >= r)
      throw new Error("Max index must be < array size (" + i + "  vs. " + r + ")");
    var a = new Po([], e, n.dtype, r), s = W.unstack(n, 0);
    return t.forEach(function(o, c) {
      a.setItem(o, s[c]);
    }), a;
  }
  function Sk(n, t, e) {
    var r = 0, i = t.map(function(l) {
      return r += l, r;
    });
    if (r !== n.shape[0])
      throw new Error(`Expected sum of lengths to be equal to
          tensor.shape[0], but sum of lengths is
        ` + r + ", and tensor's shape is: " + n.shape);
    for (var a = r === 0 ? 0 : n.size / r, s = W.tidy(function() {
      var l = [];
      n = W.reshape(n, [1, r, a]);
      for (var u = 0; u < t.length; ++u) {
        var h = u === 0 ? 0 : i[u - 1], d = [0, h, 0], p = [1, t[u], a];
        l[u] = W.reshape(W.slice(n, d, p), e);
      }
      return n.dispose(), l;
    }), o = new Po([], e, n.dtype, t.length), c = 0; c < s.length; c++)
      o.setItem(c, s[c]);
    return o;
  }
  var Ik = void 0, Ak = function(n, t, e) {
    return on(Ik, void 0, void 0, function() {
      var r, i, a, s, o, c, l, u, o, h, d, c, p, f, m, m, g, y, g, w, g, g, g, b, L, x, N, I, C, O, D, F, k, B, V, P, G, j, q, H, J, $, ee, te, ne, re, ie, oe, se, me, ye, ve, Ee, Be, We, Ke, ze, Ie, k, B, ue, Ie, G, x, Qe, ue, te, ne, x, ft, ue, x, He, ft, ue, q, H, x, He, ue, Ie, x, He, ft, ue, Ot, x, He, ue, ie, ue, se, x, Ie, B, ue, Ie, x, Qe, ue, ye, x, ve, ue;
      return Zt(this, function(ht) {
        switch (ht.label) {
          case 0:
            r = n.op;
            switch (r) {
              case "If":
                return [3, 1];
              case "StatelessIf":
                return [3, 1];
              case "While":
                return [3, 3];
              case "StatelessWhile":
                return [3, 3];
              case "LoopCond":
                return [3, 9];
              case "Switch":
                return [3, 10];
              case "Merge":
                return [3, 12];
              case "Enter":
                return [3, 13];
              case "Exit":
                return [3, 14];
              case "NextIteration":
                return [3, 15];
              case "TensorArrayV3":
                return [3, 16];
              case "TensorArrayWriteV3":
                return [3, 17];
              case "TensorArrayReadV3":
                return [3, 18];
              case "TensorArrayGatherV3":
                return [3, 19];
              case "TensorArrayScatterV3":
                return [3, 20];
              case "TensorArrayConcatV3":
                return [3, 21];
              case "TensorArraySplitV3":
                return [3, 22];
              case "TensorArraySizeV3":
                return [3, 23];
              case "TensorArrayCloseV3":
                return [3, 24];
              case "TensorListSetItem":
                return [3, 25];
              case "TensorListGetItem":
                return [3, 26];
              case "TensorListScatterV2":
                return [3, 27];
              case "TensorListScatter":
                return [3, 27];
              case "TensorListReserve":
                return [3, 28];
              case "TensorListGather":
                return [3, 29];
              case "TensorListStack":
                return [3, 30];
              case "TensorListFromTensor":
                return [3, 31];
              case "TensorListConcat":
                return [3, 32];
              case "TensorListPushBack":
                return [3, 33];
              case "TensorListPopBack":
                return [3, 34];
              case "TensorListSplit":
                return [3, 35];
            }
            return [3, 36];
          case 1:
            return i = T("thenBranch", n, t, e), a = T("elseBranch", n, t, e), s = T("cond", n, t, e), o = T("args", n, t, e), [4, s.data()];
          case 2:
            return c = ht.sent(), c[0] ? [2, e.functionMap[i].executeFunctionAsync(o, e.tensorArrayMap, e.tensorListMap)] : [2, e.functionMap[a].executeFunctionAsync(o, e.tensorArrayMap, e.tensorListMap)];
          case 3:
            return l = T("body", n, t, e), u = T("cond", n, t, e), o = T("args", n, t, e), [4, e.functionMap[u].executeFunctionAsync(o, e.tensorArrayMap, e.tensorListMap)];
          case 4:
            return h = ht.sent(), d = o.map(function(wt) {
              return wt.id;
            }), [4, h[0].data()];
          case 5:
            c = ht.sent(), h.forEach(function(wt) {
              !wt.kept && d.indexOf(wt.id) === -1 && wt.dispose();
            }), p = o, f = function() {
              var wt, Te, dt;
              return Zt(this, function(mt) {
                switch (mt.label) {
                  case 0:
                    return wt = p, [4, e.functionMap[l].executeFunctionAsync(p, e.tensorArrayMap, e.tensorListMap)];
                  case 1:
                    return p = mt.sent(), Te = p.map(function(Ve) {
                      return Ve.id;
                    }), wt.forEach(function(Ve) {
                      !Ve.kept && d.indexOf(Ve.id) === -1 && Te.indexOf(Ve.id) === -1 && Ve.dispose();
                    }), [4, e.functionMap[u].executeFunctionAsync(p, e.tensorArrayMap, e.tensorListMap)];
                  case 2:
                    return dt = mt.sent(), [4, dt[0].data()];
                  case 3:
                    return c = mt.sent(), dt.forEach(function(Ve) {
                      !Ve.kept && d.indexOf(Ve.id) === -1 && Te.indexOf(Ve.id) === -1 && Ve.dispose();
                    }), [2];
                }
              });
            }, ht.label = 6;
          case 6:
            return c[0] ? [5, f()] : [3, 8];
          case 7:
            return ht.sent(), [3, 6];
          case 8:
            return [2, p];
          case 9:
            return m = T("pred", n, t, e), [2, [er(m)]];
          case 10:
            return m = T("pred", n, t, e), g = T("data", n, t, e), g.kept || (g = er(g)), [4, m.data()];
          case 11:
            return [2, ht.sent()[0] ? [void 0, g] : [g, void 0]];
          case 12:
            return y = n.inputNames.find(function(wt) {
              return Gt(wt, t, e) !== void 0;
            }), y ? (g = Gt(y, t, e), [2, [er(g)]]) : [2, void 0];
          case 13:
            return w = T("frameName", n, t, e), g = T("tensor", n, t, e), e.enterFrame(w), [2, [er(g)]];
          case 14:
            return g = T("tensor", n, t, e), e.exitFrame(), [2, [er(g)]];
          case 15:
            return g = T("tensor", n, t, e), e.nextIteration(), [2, [er(g)]];
          case 16:
            return b = T("size", n, t, e), L = T("dtype", n, t, e), x = T("elementShape", n, t, e), N = T("dynamicSize", n, t, e), I = T("clearAfterRead", n, t, e), C = T("identicalElementShapes", n, t, e), O = T("name", n, t, e), D = new wk(O, L, b, x, C, N, I), e.addTensorArray(D), [2, [D.idTensor, W.scalar(1)]];
          case 17:
            return F = T("tensorArrayId", n, t, e), k = T("index", n, t, e), B = T("tensor", n, t, e), V = e.getTensorArray(F.id), V.write(k, B), [2, [V.idTensor]];
          case 18:
            return P = T("tensorArrayId", n, t, e), G = T("index", n, t, e), j = e.getTensorArray(P.id), [2, [j.read(G)]];
          case 19:
            return q = T("tensorArrayId", n, t, e), H = T("indices", n, t, e), J = T("dtype", n, t, e), $ = e.getTensorArray(q.id), [2, [$.gather(H, J)]];
          case 20:
            return ee = T("tensorArrayId", n, t, e), te = T("indices", n, t, e), ne = T("tensor", n, t, e), re = e.getTensorArray(ee.id), re.scatter(te, ne), [2, [re.idTensor]];
          case 21:
            return ie = T("tensorArrayId", n, t, e), oe = e.getTensorArray(ie.id), se = T("dtype", n, t, e), [2, [oe.concat(se)]];
          case 22:
            return me = T("tensorArrayId", n, t, e), ye = T("tensor", n, t, e), ve = T("lengths", n, t, e), Ee = e.getTensorArray(me.id), Ee.split(ve, ye), [2, [Ee.idTensor]];
          case 23:
            return Be = T("tensorArrayId", n, t, e), We = e.getTensorArray(Be.id), [2, [W.scalar(We.size(), "int32")]];
          case 24:
            return Ke = T("tensorArrayId", n, t, e), ze = e.getTensorArray(Ke.id), ze.clearAndClose(), [2, [ze.idTensor]];
          case 25:
            return Ie = T("tensorListId", n, t, e), k = T("index", n, t, e), B = T("tensor", n, t, e), ue = e.getTensorList(Ie.id), ue.setItem(k, B), [2, [ue.idTensor]];
          case 26:
            return Ie = T("tensorListId", n, t, e), G = T("index", n, t, e), x = T("elementShape", n, t, e), Qe = T("elementDType", n, t, e), ue = e.getTensorList(Ie.id), [2, [ue.getItem(G, x, Qe)]];
          case 27:
            return te = T("indices", n, t, e), ne = T("tensor", n, t, e), x = T("elementShape", n, t, e), ft = T("numElements", n, t, e), ue = Lk(ne, te, x, ft), e.addTensorList(ue), [2, [ue.idTensor]];
          case 28:
            return x = T("elementShape", n, t, e), He = T("elementDType", n, t, e), ft = T("numElements", n, t, e), ue = xk(x, He, ft), e.addTensorList(ue), [2, [ue.idTensor]];
          case 29:
            return q = T("tensorListId", n, t, e), H = T("indices", n, t, e), x = T("elementShape", n, t, e), He = T("elementDType", n, t, e), ue = e.getTensorList(q.id), [2, [ue.gather(H, He, x)]];
          case 30:
            return Ie = T("tensorListId", n, t, e), x = T("elementShape", n, t, e), He = T("elementDType", n, t, e), ft = T("numElements", n, t, e), ue = e.getTensorList(Ie.id), [2, [ue.stack(x, He, ft)]];
          case 31:
            return Ot = T("tensor", n, t, e), x = T("elementShape", n, t, e), He = T("elementDType", n, t, e), ue = bk(Ot, x, He), e.addTensorList(ue), [2, [ue.idTensor]];
          case 32:
            return ie = T("tensorListId", n, t, e), ue = e.getTensorList(ie.id), se = T("dtype", n, t, e), x = T("elementShape", n, t, e), [2, [ue.concat(se, x)]];
          case 33:
            return Ie = T("tensorListId", n, t, e), B = T("tensor", n, t, e), ue = e.getTensorList(Ie.id), ue.pushBack(B), [2, [ue.idTensor]];
          case 34:
            return Ie = T("tensorListId", n, t, e), x = T("elementShape", n, t, e), Qe = T("elementDType", n, t, e), ue = e.getTensorList(Ie.id), [2, [ue.popBack(x, Qe)]];
          case 35:
            return ye = T("tensor", n, t, e), x = T("elementShape", n, t, e), ve = T("lengths", n, t, e), ue = Sk(ye, ve, x), e.addTensorList(ue), [2, [ue.idTensor]];
          case 36:
            throw TypeError("Node type " + n.op + " is not implemented");
        }
      });
    });
  };
  function E1(n, t, e) {
    var r = yt(T("fusedOps", n, t, e), 2), i = r[0], a = r[1], s = i === "biasadd", o = a === "prelu", c = i === "fusedbatchnorm", l = T("numArgs", n, t, e);
    if (s) {
      if (o && l !== 2)
        throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");
      if (!o && l !== 1)
        throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.");
    }
    if (c)
      throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported.");
    var u = T("strides", n, t, e), h = zo(n, t, e), d = T("dataFormat", n, t, e).toUpperCase(), p = T("dilations", n, t, e), f = yt(T("args", n, t, e), 2), m = f[0], g = f[1];
    return {stride: u, pad: h, dataFormat: d, dilations: p, biasArg: m, preluArg: g, activationFunc: a};
  }
  var Tk = function(n, t, e) {
    switch (n.op) {
      case "Conv1D": {
        var r = T("stride", n, t, e), i = T("pad", n, t, e), a = T("dataFormat", n, t, e).toUpperCase(), s = T("dilation", n, t, e);
        return [W.conv1d(T("x", n, t, e), T("filter", n, t, e), r, i, a, s)];
      }
      case "Conv2D": {
        var r = T("strides", n, t, e), i = zo(n, t, e), a = T("dataFormat", n, t, e).toUpperCase(), o = T("dilations", n, t, e);
        return [W.conv2d(T("x", n, t, e), T("filter", n, t, e), [r[1], r[2]], i, a, [o[1], o[2]])];
      }
      case "_FusedConv2D": {
        var c = E1(n, t, e), r = c.stride, i = c.pad, a = c.dataFormat, o = c.dilations, l = c.biasArg, u = c.preluArg, h = c.activationFunc;
        return [W.fused.conv2d({x: T("x", n, t, e), filter: T("filter", n, t, e), strides: [r[1], r[2]], pad: i, dataFormat: a, dilations: [o[1], o[2]], bias: l, activation: h, preluActivationWeights: u})];
      }
      case "FusedDepthwiseConv2dNative": {
        var d = E1(n, t, e), r = d.stride, i = d.pad, a = d.dataFormat, o = d.dilations, l = d.biasArg, u = d.preluArg, h = d.activationFunc;
        return [W.fused.depthwiseConv2d({x: T("x", n, t, e), filter: T("filter", n, t, e), strides: [r[1], r[2]], pad: i, dataFormat: a, dilations: [o[1], o[2]], bias: l, activation: h, preluActivationWeights: u})];
      }
      case "Conv2DBackpropInput":
      case "Conv2dTranspose": {
        var p = T("outputShape", n, t, e), r = T("strides", n, t, e), i = zo(n, t, e);
        return [W.conv2dTranspose(T("x", n, t, e), T("filter", n, t, e), p, [r[1], r[2]], i)];
      }
      case "DepthwiseConv2dNative":
      case "DepthwiseConv2d": {
        var r = T("strides", n, t, e), i = zo(n, t, e), o = T("dilations", n, t, e), a = T("dataFormat", n, t, e).toUpperCase();
        return [W.depthwiseConv2d(T("input", n, t, e), T("filter", n, t, e), [r[1], r[2]], i, a, [o[1], o[2]])];
      }
      case "Conv3D": {
        var r = T("strides", n, t, e), i = T("pad", n, t, e), a = T("dataFormat", n, t, e).toUpperCase(), o = T("dilations", n, t, e);
        return [W.conv3d(T("x", n, t, e), T("filter", n, t, e), [r[1], r[2], r[3]], i, a, [o[1], o[2], o[3]])];
      }
      case "AvgPool": {
        var r = T("strides", n, t, e), i = T("pad", n, t, e), f = T("kernelSize", n, t, e);
        return [W.avgPool(T("x", n, t, e), [f[1], f[2]], [r[1], r[2]], i)];
      }
      case "MaxPool": {
        var r = T("strides", n, t, e), i = T("pad", n, t, e), f = T("kernelSize", n, t, e);
        return [W.maxPool(T("x", n, t, e), [f[1], f[2]], [r[1], r[2]], i)];
      }
      case "MaxPoolWithArgmax": {
        var r = T("strides", n, t, e), i = T("pad", n, t, e), f = T("kernelSize", n, t, e), m = T("includeBatchInIndex", n, t, e), g = W.maxPoolWithArgmax(T("x", n, t, e), [f[1], f[2]], [r[1], r[2]], i, m), y = g.result, w = g.indexes;
        return [y, w];
      }
      case "AvgPool3D": {
        var r = T("strides", n, t, e), i = T("pad", n, t, e), f = T("kernelSize", n, t, e);
        return [W.avgPool3d(T("x", n, t, e), [f[1], f[2], f[3]], [r[1], r[2], r[3]], i)];
      }
      case "MaxPool3D": {
        var r = T("strides", n, t, e), i = T("pad", n, t, e), f = T("kernelSize", n, t, e);
        return [W.maxPool3d(T("x", n, t, e), [f[1], f[2], f[3]], [r[1], r[2], r[3]], i)];
      }
      case "Dilation2D": {
        var b = T("strides", n, t, e), i = T("pad", n, t, e), o = T("dilations", n, t, e), L = b[1], x = b[2], N = o[1], I = o[2];
        return [W.dilation2d(T("x", n, t, e), T("filter", n, t, e), [L, x], i, [N, I], "NHWC")];
      }
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var Nk = function(n, t, e) {
    switch (n.op) {
      case "Fill": {
        var r = T("shape", n, t, e), i = T("dtype", n, t, e), a = T("value", n, t, e);
        return [W.fill(r, a, i)];
      }
      case "LinSpace": {
        var s = T("start", n, t, e), o = T("stop", n, t, e), c = T("num", n, t, e);
        return [W.linspace(s, o, c)];
      }
      case "Multinomial": {
        var l = T("logits", n, t, e), u = T("numSamples", n, t, e), h = T("seed", n, t, e);
        return [W.multinomial(l, u, h)];
      }
      case "OneHot": {
        var d = T("indices", n, t, e), p = T("depth", n, t, e), f = T("onValue", n, t, e), m = T("offValue", n, t, e);
        return [W.oneHot(d, p, f, m)];
      }
      case "Ones":
        return [W.ones(T("shape", n, t, e), T("dtype", n, t, e))];
      case "OnesLike":
        return [W.onesLike(T("x", n, t, e))];
      case "RandomUniform":
        return [W.randomUniform(T("shape", n, t, e), T("minval", n, t, e), T("maxval", n, t, e), T("dtype", n, t, e))];
      case "Range": {
        var s = T("start", n, t, e), g = T("stop", n, t, e), y = T("step", n, t, e);
        return [W.range(s, g, y, T("dtype", n, t, e))];
      }
      case "TruncatedNormal": {
        var r = T("shape", n, t, e), w = T("mean", n, t, e), b = T("stdDev", n, t, e), h = T("seed", n, t, e);
        return [W.truncatedNormal(r, w, b, T("dtype", n, t, e), h)];
      }
      case "Zeros":
        return [W.zeros(T("shape", n, t, e), T("dtype", n, t, e))];
      case "ZerosLike":
        return [W.zerosLike(T("x", n, t, e))];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var _k = void 0;
  function Td(n, t, e) {
    var r = T("boxes", n, t, e), i = T("scores", n, t, e), a = T("maxOutputSize", n, t, e), s = T("iouThreshold", n, t, e), o = T("scoreThreshold", n, t, e), c = T("softNmsSigma", n, t, e);
    return {boxes: r, scores: i, maxOutputSize: a, iouThreshold: s, scoreThreshold: o, softNmsSigma: c};
  }
  var Ck = function(n, t, e) {
    return on(_k, void 0, void 0, function() {
      var r, i, a, s, o, c, l, u, h, d, a, s, o, c, l, p, h, f, a, s, o, c, l, m, h;
      return Zt(this, function(g) {
        switch (g.label) {
          case 0:
            r = n.op;
            switch (r) {
              case "NonMaxSuppressionV5":
                return [3, 1];
              case "NonMaxSuppressionV4":
                return [3, 3];
              case "NonMaxSuppressionV3":
                return [3, 5];
              case "NonMaxSuppressionV2":
                return [3, 5];
              case "Where":
                return [3, 7];
              case "ListDiff":
                return [3, 9];
            }
            return [3, 10];
          case 1:
            return i = Td(n, t, e), a = i.boxes, s = i.scores, o = i.maxOutputSize, c = i.iouThreshold, l = i.scoreThreshold, u = i.softNmsSigma, [4, W.image.nonMaxSuppressionWithScoreAsync(a, s, o, c, l, u)];
          case 2:
            return h = g.sent(), [2, [h.selectedIndices, h.selectedScores]];
          case 3:
            return d = Td(n, t, e), a = d.boxes, s = d.scores, o = d.maxOutputSize, c = d.iouThreshold, l = d.scoreThreshold, p = T("padToMaxOutputSize", n, t, e), [4, W.image.nonMaxSuppressionPaddedAsync(a, s, o, c, l, p)];
          case 4:
            return h = g.sent(), [2, [h.selectedIndices, h.validOutputs]];
          case 5:
            return f = Td(n, t, e), a = f.boxes, s = f.scores, o = f.maxOutputSize, c = f.iouThreshold, l = f.scoreThreshold, [4, W.image.nonMaxSuppressionAsync(a, s, o, c, l)];
          case 6:
            return [2, [g.sent()]];
          case 7:
            return m = W.cast(T("condition", n, t, e), "bool"), [4, W.whereAsync(m)];
          case 8:
            return h = [g.sent()], m.dispose(), [2, h];
          case 9:
            return [2, W.setdiff1dAsync(T("x", n, t, e), T("y", n, t, e))];
          case 10:
            throw TypeError("Node type " + n.op + " is not implemented");
        }
      });
    });
  };
  var Rk = function(n, t, e) {
    switch (n.op) {
      case "TopKV2": {
        var r = T("x", n, t, e), i = T("k", n, t, e), a = T("sorted", n, t, e), s = W.topk(r, i, a);
        return [s.values, s.indices];
      }
      case "Unique": {
        var r = T("x", n, t, e), s = W.unique(r);
        return [s.values, s.indices];
      }
      case "UniqueV2": {
        var r = T("x", n, t, e), o = T("axis", n, t, e), s = W.unique(r, o);
        return [s.values, s.indices];
      }
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var Ok = function(n, t, e) {
    switch (n.op) {
      case "Const":
        return t[n.name];
      case "PlaceholderWithDefault":
        var r = T("default", n, t, e);
        return [Gt(n.name, t, e) || r];
      case "Placeholder":
        return [Gt(n.name, t, e)];
      case "Identity":
      case "StopGradient":
      case "FakeQuantWithMinMaxVars": {
        var i = T("x", n, t, e);
        return [er(i)];
      }
      case "IdentityN":
        return T("x", n, t, e).map(function(h) {
          return er(h);
        });
      case "Snapshot":
        var a = T("x", n, t, e);
        return [er(a)];
      case "Shape":
        return [W.tensor1d(T("x", n, t, e).shape, "int32")];
      case "ShapeN":
        return T("x", n, t, e).map(function(h) {
          return W.tensor1d(h.shape);
        });
      case "Size":
        return [W.scalar(T("x", n, t, e).size, "int32")];
      case "Rank":
        return [W.scalar(T("x", n, t, e).rank, "int32")];
      case "NoOp":
        return [W.scalar(1)];
      case "Print":
        var s = T("x", n, t, e), o = T("data", n, t, e), c = T("message", n, t, e), l = T("summarize", n, t, e);
        console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."), console.log(c);
        for (var u = 0; u < o.length; u++)
          console.log(Array.prototype.slice.call(o[u].dataSync()).slice(0, l));
        return [s];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  }, Ek = function() {
    function n(t, e) {
      this.keyDType = t, this.valueDType = e, this.handle = W.scalar(0), this.tensorMap = new Map(), W.keep(this.handle);
    }
    return Object.defineProperty(n.prototype, "id", {get: function() {
      return this.handle.id;
    }, enumerable: true, configurable: true}), n.prototype.clearAndClose = function() {
      this.tensorMap.forEach(function(t) {
        return t.dispose();
      }), this.tensorMap.clear(), this.handle.dispose();
    }, n.prototype.size = function() {
      return this.tensorMap.size;
    }, n.prototype.import = function(t, e) {
      return on(this, void 0, void 0, function() {
        var r, i = this;
        return Zt(this, function(a) {
          switch (a.label) {
            case 0:
              return this.checkKeyAndValueTensor(t, e), [4, t.data()];
            case 1:
              return r = a.sent(), this.tensorMap.forEach(function(s) {
                return s.dispose();
              }), this.tensorMap.clear(), [2, W.tidy(function() {
                var s = W.unstack(e), o = r.length, c = s.length;
                W.util.assert(o === c, function() {
                  return "The number of elements doesn't match, keys has " + (o + " elements, the values has " + c + " ") + "elements.";
                });
                for (var l = 0; l < o; l++) {
                  var u = r[l], h = s[l];
                  W.keep(h), i.tensorMap.set(u, h);
                }
                return i.handle;
              })];
          }
        });
      });
    }, n.prototype.find = function(t, e) {
      return on(this, void 0, void 0, function() {
        var r, i = this;
        return Zt(this, function(a) {
          switch (a.label) {
            case 0:
              return this.checkKeyAndValueTensor(t, e), [4, t.data()];
            case 1:
              return r = a.sent(), [2, W.tidy(function() {
                for (var s = [], o = 0; o < r.length; o++) {
                  var c = r[o], l = i.findWithDefault(c, e);
                  s.push(l);
                }
                return W.stack(s);
              })];
          }
        });
      });
    }, n.prototype.findWithDefault = function(t, e) {
      var r = this.tensorMap.get(t);
      return r != null ? r : e;
    }, n.prototype.checkKeyAndValueTensor = function(t, e) {
      if (t.dtype !== this.keyDType)
        throw new Error("Expect key dtype " + this.keyDType + ", but got " + ("" + t.dtype));
      if (e.dtype !== this.valueDType)
        throw new Error("Expect value dtype " + this.valueDType + ", but got " + ("" + e.dtype));
    }, n;
  }();
  var Dk = void 0, kk = function(n, t, e, r) {
    return on(Dk, void 0, void 0, function() {
      var i, a, s, o, c, l, u, o, c, l, h, o;
      return Zt(this, function(d) {
        switch (d.label) {
          case 0:
            i = n.op;
            switch (i) {
              case "HashTable":
                return [3, 1];
              case "HashTableV2":
                return [3, 1];
              case "LookupTableImport":
                return [3, 2];
              case "LookupTableImportV2":
                return [3, 2];
              case "LookupTableFind":
                return [3, 4];
              case "LookupTableFindV2":
                return [3, 4];
            }
            return [3, 6];
          case 1:
            return a = T("keyDType", n, t, e), s = T("valueDType", n, t, e), o = new Ek(a, s), r.addHashTable(n.name, o), [2, [o.handle]];
          case 2:
            return c = T("tableHandle", n, t, e, r), l = T("keys", n, t, e), u = T("values", n, t, e), o = r.getHashTableById(c.id), [4, o.import(l, u)];
          case 3:
            return [2, [d.sent()]];
          case 4:
            return c = T("tableHandle", n, t, e, r), l = T("keys", n, t, e), h = T("defaultValue", n, t, e), o = r.getHashTableById(c.id), [4, o.find(l, h)];
          case 5:
            return [2, [d.sent()]];
          case 6:
            throw TypeError("Node type " + n.op + " is not implemented");
        }
      });
    });
  };
  var Fk = function(n, t, e) {
    switch (n.op) {
      case "ResizeBilinear": {
        var r = T("images", n, t, e), i = T("size", n, t, e), a = T("alignCorners", n, t, e);
        return [W.image.resizeBilinear(r, [i[0], i[1]], a)];
      }
      case "ResizeNearestNeighbor": {
        var r = T("images", n, t, e), i = T("size", n, t, e), a = T("alignCorners", n, t, e);
        return [W.image.resizeNearestNeighbor(r, [i[0], i[1]], a)];
      }
      case "CropAndResize": {
        var s = T("image", n, t, e), o = T("boxes", n, t, e), c = T("boxInd", n, t, e), l = T("cropSize", n, t, e), u = T("method", n, t, e), h = T("extrapolationValue", n, t, e);
        return [W.image.cropAndResize(s, o, c, l, u, h)];
      }
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var Wk = function(n, t, e) {
    switch (n.op) {
      case "Equal":
        return [W.equal(T("a", n, t, e), T("b", n, t, e))];
      case "NotEqual":
        return [W.notEqual(T("a", n, t, e), T("b", n, t, e))];
      case "Greater":
        return [W.greater(T("a", n, t, e), T("b", n, t, e))];
      case "GreaterEqual":
        return [W.greaterEqual(T("a", n, t, e), T("b", n, t, e))];
      case "Less":
        return [W.less(T("a", n, t, e), T("b", n, t, e))];
      case "LessEqual":
        return [W.lessEqual(T("a", n, t, e), T("b", n, t, e))];
      case "LogicalAnd":
        return [W.logicalAnd(T("a", n, t, e), T("b", n, t, e))];
      case "LogicalNot":
        return [W.logicalNot(T("a", n, t, e))];
      case "LogicalOr":
        return [W.logicalOr(T("a", n, t, e), T("b", n, t, e))];
      case "Select":
      case "SelectV2":
        return [W.where(T("condition", n, t, e), T("a", n, t, e), T("b", n, t, e))];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var Uk = function(n, t, e) {
    switch (n.op) {
      case "BatchMatMul":
      case "BatchMatMulV2":
      case "MatMul":
        return [W.matMul(T("a", n, t, e), T("b", n, t, e), T("transposeA", n, t, e), T("transposeB", n, t, e))];
      case "Transpose":
        return [W.transpose(T("x", n, t, e), T("perm", n, t, e))];
      case "_FusedMatMul":
        var r = yt(T("fusedOps", n, t, e), 2), i = r[0], a = r[1], s = i === "biasadd", o = a === "prelu", c = T("numArgs", n, t, e);
        if (s) {
          if (o && c !== 2)
            throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");
          if (!o && c !== 1)
            throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.");
        }
        var l = yt(T("args", n, t, e), 2), u = l[0], h = l[1];
        return [W.fused.matMul({a: T("a", n, t, e), b: T("b", n, t, e), transposeA: T("transposeA", n, t, e), transposeB: T("transposeB", n, t, e), bias: u, activation: a, preluActivationWeights: h})];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var Bk = function(n, t, e) {
    switch (n.op) {
      case "FusedBatchNorm":
      case "FusedBatchNormV2":
        return [W.batchNorm(T("x", n, t, e), T("mean", n, t, e), T("variance", n, t, e), T("offset", n, t, e), T("scale", n, t, e), T("epsilon", n, t, e))];
      case "FusedBatchNormV3":
        return [W.batchNorm(T("x", n, t, e), T("mean", n, t, e), T("variance", n, t, e), T("offset", n, t, e), T("scale", n, t, e), T("epsilon", n, t, e))];
      case "LRN":
        return [W.localResponseNormalization(T("x", n, t, e), T("radius", n, t, e), T("bias", n, t, e), T("alpha", n, t, e), T("beta", n, t, e))];
      case "Softmax":
        return [W.softmax(T("x", n, t, e))];
      case "LogSoftmax":
        return [W.logSoftmax(T("x", n, t, e))];
      case "SparseToDense":
        return [W.sparseToDense(T("sparseIndices", n, t, e), T("outputShape", n, t, e), T("sparseValues", n, t, e), T("defaultValue", n, t, e))];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var zk = function(n, t, e) {
    switch (n.op) {
      case "Max": {
        var r = T("axis", n, t, e), i = T("keepDims", n, t, e);
        return [W.max(T("x", n, t, e), r, i)];
      }
      case "Mean": {
        var r = T("axis", n, t, e), i = T("keepDims", n, t, e);
        return [W.mean(T("x", n, t, e), r, i)];
      }
      case "Min": {
        var r = T("axis", n, t, e), i = T("keepDims", n, t, e);
        return [W.min(T("x", n, t, e), r, i)];
      }
      case "Sum": {
        var r = T("axis", n, t, e), i = T("keepDims", n, t, e);
        return [W.sum(T("x", n, t, e), r, i)];
      }
      case "All": {
        var r = T("axis", n, t, e), i = T("keepDims", n, t, e);
        return [W.all(T("x", n, t, e), r, i)];
      }
      case "Any": {
        var r = T("axis", n, t, e), i = T("keepDims", n, t, e);
        return [W.any(T("x", n, t, e), r, i)];
      }
      case "ArgMax": {
        var r = T("axis", n, t, e);
        return [W.argMax(T("x", n, t, e), r)];
      }
      case "ArgMin": {
        var r = T("axis", n, t, e);
        return [W.argMin(T("x", n, t, e), r)];
      }
      case "Prod": {
        var r = T("axis", n, t, e), i = T("keepDims", n, t, e);
        return [W.prod(T("x", n, t, e), r, i)];
      }
      case "Cumsum": {
        var r = T("axis", n, t, e), a = T("exclusive", n, t, e), s = T("reverse", n, t, e);
        return [W.cumsum(T("x", n, t, e), r, a, s)];
      }
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var Pk = function(n, t, e) {
    switch (n.op) {
      case "ConcatV2":
      case "Concat": {
        var r = T("n", n, t, e), i = T("axis", n, t, e), a = T("tensors", n, t, e);
        return a = a.slice(0, r), [W.concat(a, i)];
      }
      case "GatherV2":
      case "Gather": {
        var i = T("axis", n, t, e), s = T("x", n, t, e), o = T("indices", n, t, e);
        return [W.gather(s, W.cast(o, "int32"), i)];
      }
      case "ReverseV2":
      case "Reverse": {
        var i = T("axis", n, t, e), s = T("x", n, t, e);
        return [W.reverse(s, i)];
      }
      case "Slice": {
        var c = T("begin", n, t, e), l = T("size", n, t, e);
        return [W.slice(T("x", n, t, e), c, l)];
      }
      case "StridedSlice": {
        var c = T("begin", n, t, e), u = T("end", n, t, e), h = T("strides", n, t, e), d = T("beginMask", n, t, e), p = T("endMask", n, t, e), f = T("ellipsisMask", n, t, e), m = T("newAxisMask", n, t, e), g = T("shrinkAxisMask", n, t, e), y = T("x", n, t, e);
        return [W.stridedSlice(y, c, u, h, d, p, f, m, g)];
      }
      case "Pack":
        return W.tidy(function() {
          var O = T("axis", n, t, e), D = T("tensors", n, t, e), F = D[0].shape, k = W.squeeze(D[0]).shape, B = D.map(function(V) {
            var P = W.util.arraysEqual(V.shape, F);
            if (!P && !W.util.arraysEqual(W.squeeze(V).shape, k))
              throw new Error("the input tensors shape does not match");
            return P ? V : W.reshape(V, F);
          });
          return [W.stack(B, O)];
        });
      case "Unpack": {
        var i = T("axis", n, t, e), y = T("tensor", n, t, e);
        return W.unstack(y, i);
      }
      case "Tile": {
        var w = T("reps", n, t, e);
        return [W.tile(T("x", n, t, e), w)];
      }
      case "Split":
      case "SplitV": {
        var i = T("axis", n, t, e), b = T("numOrSizeSplits", n, t, e), y = T("x", n, t, e);
        return W.split(y, b, i);
      }
      case "ScatterNd": {
        var o = T("indices", n, t, e), L = T("values", n, t, e), x = T("shape", n, t, e);
        return [W.scatterND(o, L, x)];
      }
      case "GatherNd": {
        var N = T("x", n, t, e), o = T("indices", n, t, e);
        return [W.gatherND(N, o)];
      }
      case "SparseToDense": {
        var o = T("sparseIndices", n, t, e), x = T("outputShape", n, t, e), I = T("sparseValues", n, t, e), C = T("defaultValue", n, t, e);
        return [W.sparseToDense(o, I, x, I.dtype === C.dtype ? C : W.cast(C, I.dtype))];
      }
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var Mk = function(n, t, e) {
    switch (n.op) {
      case "FFT":
        return [W.fft(T("x", n, t, e))];
      case "IFFT":
        return [W.ifft(T("x", n, t, e))];
      case "RFFT":
        return [W.rfft(T("x", n, t, e))];
      case "IRFFT":
        return [W.irfft(T("x", n, t, e))];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  var Hk = function(n, t, e) {
    switch (n.op) {
      case "Cast":
        return [W.cast(T("x", n, t, e), T("dtype", n, t, e))];
      case "ExpandDims": {
        var r = T("axis", n, t, e);
        return [W.expandDims(T("x", n, t, e), r)];
      }
      case "Squeeze": {
        var r = T("axis", n, t, e);
        return [W.squeeze(T("x", n, t, e), r)];
      }
      case "Reshape":
        return [W.reshape(T("x", n, t, e), T("shape", n, t, e))];
      case "MirrorPad":
        return [W.mirrorPad(T("x", n, t, e), T("padding", n, t, e), T("mode", n, t, e))];
      case "PadV2":
      case "Pad":
        return [W.pad(T("x", n, t, e), T("padding", n, t, e), T("constantValue", n, t, e))];
      case "SpaceToBatchND": {
        var i = T("blockShape", n, t, e), a = T("paddings", n, t, e);
        return [W.spaceToBatchND(T("x", n, t, e), i, a)];
      }
      case "BatchToSpaceND": {
        var i = T("blockShape", n, t, e), s = T("crops", n, t, e);
        return [W.batchToSpaceND(T("x", n, t, e), i, s)];
      }
      case "DepthToSpace": {
        var o = T("blockSize", n, t, e), c = T("dataFormat", n, t, e).toUpperCase();
        return [W.depthToSpace(T("x", n, t, e), o, c)];
      }
      case "BroadcastTo":
        return [W.broadcastTo(T("x", n, t, e), T("shape", n, t, e))];
      default:
        throw TypeError("Node type " + n.op + " is not implemented");
    }
  };
  function D1(n, t, e, r) {
    var i = function(a, s, o) {
      switch (a.category) {
        case "arithmetic":
          return W.tidy(function() {
            return gk(a, s, o);
          });
        case "basic_math":
          return W.tidy(function() {
            return yk(a, s, o);
          });
        case "control":
          return Ak(a, s, o);
        case "convolution":
          return W.tidy(function() {
            return Tk(a, s, o);
          });
        case "creation":
          return W.tidy(function() {
            return Nk(a, s, o);
          });
        case "dynamic":
          return Ck(a, s, o);
        case "evaluation":
          return W.tidy(function() {
            return Rk(a, s, o);
          });
        case "image":
          return W.tidy(function() {
            return Fk(a, s, o);
          });
        case "graph":
          return W.tidy(function() {
            return Ok(a, s, o);
          });
        case "logical":
          return W.tidy(function() {
            return Wk(a, s, o);
          });
        case "matrices":
          return W.tidy(function() {
            return Uk(a, s, o);
          });
        case "normalization":
          return W.tidy(function() {
            return Bk(a, s, o);
          });
        case "reduction":
          return W.tidy(function() {
            return zk(a, s, o);
          });
        case "slice_join":
          return W.tidy(function() {
            return Pk(a, s, o);
          });
        case "spectral":
          return W.tidy(function() {
            return Mk(a, s, o);
          });
        case "transformation":
          return W.tidy(function() {
            return Hk(a, s, o);
          });
        case "hash_table":
          return kk(a, s, o, r);
        case "custom":
          var c = N1(a.op);
          if (c && c.customExecutor)
            return c.customExecutor(new mk(a, s, o));
          throw TypeError("Custom op " + a.op + " is not registered.");
        default:
          throw TypeError("Unknown op '" + a.op + "'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()");
      }
    }(n, t, e);
    return W.util.isPromise(i) ? i.then(function(a) {
      return [].concat(a);
    }) : [].concat(i);
  }
  var k1 = function() {
    function n(t, e, r, i) {
      t === void 0 && (t = {}), e === void 0 && (e = {}), r === void 0 && (r = {}), i === void 0 && (i = {}), this.weightMap = t, this.tensorArrayMap = e, this.tensorListMap = r, this.functionMap = i, this.rootContext = {id: 0, frameName: "", iterationId: 0}, this.contexts = [this.rootContext], this.lastId = 0, this.generateCurrentContextIds();
    }
    return n.prototype.newFrame = function(t, e) {
      return {id: t, frameName: e, iterationId: 0};
    }, Object.defineProperty(n.prototype, "currentContext", {get: function() {
      return this.contexts;
    }, set: function(t) {
      this.contexts !== t && (this.contexts = t, this.generateCurrentContextIds());
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "currentContextId", {get: function() {
      return this._currentContextIds[0];
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "currentContextIds", {get: function() {
      return this._currentContextIds;
    }, enumerable: true, configurable: true}), n.prototype.generateCurrentContextIds = function() {
      for (var t = [], e = 0; e < this.contexts.length - 1; e++) {
        var r = this.contexts.slice(0, this.contexts.length - e);
        t.push(this.contextIdforContexts(r));
      }
      t.push(""), this._currentContextIds = t;
    }, n.prototype.contextIdforContexts = function(t) {
      return t ? t.map(function(e) {
        return e.id === 0 && e.iterationId === 0 ? "" : e.frameName + "-" + e.iterationId;
      }).join("/") : "";
    }, n.prototype.enterFrame = function(t) {
      this.contexts && (this.lastId++, this.contexts = this.contexts.slice(), this.contexts.push(this.newFrame(this.lastId, t)), this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)));
    }, n.prototype.exitFrame = function() {
      if (this.contexts && this.contexts.length > 1)
        this.contexts = this.contexts.slice(), this.contexts.splice(-1), this.currentContextIds.shift();
      else
        throw new Error("Cannot exit frame, the context is empty");
    }, n.prototype.nextIteration = function() {
      if (this.contexts && this.contexts.length > 0) {
        this.contexts = this.contexts.slice(), this.lastId++;
        var t = Object.assign({}, this.contexts[this.contexts.length - 1]);
        t.iterationId += 1, t.id = this.lastId, this.contexts.splice(-1, 1, t), this._currentContextIds.splice(0, 1, this.contextIdforContexts(this.contexts));
      } else
        throw new Error("Cannot increase frame iteration, the context is empty");
    }, n.prototype.getWeight = function(t) {
      return this.weightMap[t];
    }, n.prototype.addTensorArray = function(t) {
      this.tensorArrayMap[t.id] = t;
    }, n.prototype.getTensorArray = function(t) {
      return this.tensorArrayMap[t];
    }, n.prototype.addTensorList = function(t) {
      this.tensorListMap[t.id] = t;
    }, n.prototype.getTensorList = function(t) {
      return this.tensorListMap[t];
    }, n.prototype.dispose = function(t) {
      for (var e in this.tensorArrayMap)
        this.tensorArrayMap[e].clearAndClose(t);
      for (var e in this.tensorListMap)
        this.tensorListMap[e].clearAndClose(t);
    }, n;
  }();
  function W1(n, t, e, r) {
    var i = new Set(), a = [], s = null, o = null, c = new Set(), l = Object.keys(n).map(function(p) {
      return Qt(p)[0];
    }), u = [];
    r != null && (u = r.map(function(p) {
      return Qt(p.name)[0];
    }));
    for (var h = _r(t); h.length > 0; ) {
      var d = h.pop();
      if ((F1(d) || Vk(d) || Gk(d)) && (s == null && (s = d, o = s.children.map(function(p) {
        return p.name;
      }).filter(function(p) {
        return i.has(p);
      }))), i.add(d.name), e[d.name] != null)
        continue;
      if (l.indexOf(d.name) !== -1)
        continue;
      if (u.indexOf(d.name) !== -1)
        continue;
      if (d.inputs.length === 0) {
        a.push(d.name);
        continue;
      }
      d.inputs.forEach(function(p) {
        if (c.has(p.name))
          return;
        c.add(p.name), h.push(p);
      });
    }
    return {inputs: n, outputs: t, usedNodes: i, missingInputs: a, dynamicNode: s, syncInputs: o};
  }
  function qk(n, t, e) {
    var r = e.usedNodes, i = e.inputs, a = [], s = Object.keys(i).map(function(h) {
      return Qt(h)[0];
    }).map(function(h) {
      return n.nodes[h];
    }), o = n.initNodes;
    s.forEach(function(h) {
      r.has(h.name) && a.push(h);
    }), n.weights.forEach(function(h) {
      r.has(h.name) && a.push(h);
    }), o != null && o.forEach(function(h) {
      r.has(h.name) && a.push(h);
    });
    for (var c = new Set(), l = []; a.length > 0; ) {
      var u = a.pop();
      c.add(u.name), t[u.name] || l.push(u), u.children.forEach(function(h) {
        !c.has(h.name) && r.has(h.name) && h.inputs.every(function(d) {
          return c.has(d.name);
        }) && a.push(h);
      });
    }
    return l;
  }
  var Yk = ["Switch", "Merge", "Enter", "Exit", "NextIteration", "StatelessIf", "StatelessWhile", "if", "While"], Kk = ["NonMaxSuppressionV2", "NonMaxSuppressionV3", "NonMaxSuppressionV5", "Where"], jk = ["HashTable", "HashTableV2", "LookupTableImport", "LookupTableImportV2", "LookupTableFind", "LookupTableFindV2"];
  function F1(n) {
    return Yk.indexOf(n.op) >= 0;
  }
  function Vk(n) {
    return Kk.indexOf(n.op) >= 0;
  }
  function Gk(n) {
    return jk.indexOf(n.op) >= 0;
  }
  var U1 = function() {
    function n(t, e) {
      var r = this;
      this.graph = t, this.parent = e, this.compiledMap = new Map(), this._weightMap = {}, this.SEPERATOR = ",", this._functions = {}, this._functionExecutorMap = {}, this._outputs = t.outputs, this._inputs = t.inputs, this._initNodes = t.initNodes, this._signature = t.signature, this._functions = t.functions, t.functions != null && Object.keys(t.functions).forEach(function(i) {
        r._functionExecutorMap[i] = new n(t.functions[i], r);
      });
    }
    return Object.defineProperty(n.prototype, "weightIds", {get: function() {
      return this.parent ? this.parent.weightIds : this._weightIds;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "functionExecutorMap", {get: function() {
      return this.parent ? this.parent.functionExecutorMap : this._functionExecutorMap;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "weightMap", {get: function() {
      return this.parent ? this.parent.weightMap : this._weightMap;
    }, set: function(t) {
      var e = Object.keys(t).map(function(r) {
        return t[r].map(function(i) {
          return i.id;
        });
      });
      this._weightIds = [].concat.apply([], _r(e)), this._weightMap = t;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "resourceManager", {set: function(t) {
      this._resourceManager = t;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "inputs", {get: function() {
      return this._inputs.map(function(t) {
        return {name: t.name, shape: t.attrParams.shape ? t.attrParams.shape.value : void 0, dtype: t.attrParams.dtype ? t.attrParams.dtype.value : void 0};
      });
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "outputs", {get: function() {
      return this._outputs.map(function(t) {
        return {name: t.name, shape: t.attrParams.shape ? t.attrParams.shape.value : void 0, dtype: t.attrParams.dtype ? t.attrParams.dtype.value : void 0};
      });
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "inputNodes", {get: function() {
      return this._inputs.map(function(t) {
        return t.signatureKey || t.name;
      });
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "outputNodes", {get: function() {
      return this._outputs.map(function(t) {
        var e = t.signatureKey || t.name;
        return t.defaultOutput ? e + ":" + t.defaultOutput : e;
      });
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "functions", {get: function() {
      var t = this;
      return Object.keys(this._functions).reduce(function(e, r) {
        return e[r] = t._functions[r].signature, e;
      }, {});
    }, enumerable: true, configurable: true}), n.prototype.getCompilationKey = function(t, e) {
      var r = t.map(function(a) {
        return a.name;
      }).sort(), i = e.map(function(a) {
        return a.name;
      }).sort();
      return r.join(this.SEPERATOR) + "--" + i.join(this.SEPERATOR);
    }, n.prototype.compile = function(t, e) {
      var r = W1(t, e, this.weightMap, this._initNodes), i = r.missingInputs, a = r.dynamicNode, s = r.syncInputs;
      if (a != null)
        throw new Error("This execution contains the node '" + a.name + "', which has " + ("the dynamic op '" + a.op + "'. Please use ") + "model.executeAsync() instead. Alternatively, to avoid the " + ("dynamic ops, specify the inputs [" + s + "]"));
      if (i.length > 0) {
        var o = e.map(function(l) {
          return l.name;
        }), c = Object.keys(t);
        throw new Error("Cannot compute the outputs [" + o + "] from the provided inputs " + ("[" + c + "]. Missing the following inputs: [" + i + "]"));
      }
      return qk(this.graph, this.weightMap, r);
    }, n.prototype.execute = function(t, e) {
      var r = this;
      t = this.mapInputs(t);
      var i = Object.keys(t).sort();
      this.checkInputs(t), this.checkInputShapeAndType(t), e = this.mapOutputs(e), this.checkOutputs(e);
      var a = i.map(function(d) {
        return r.graph.nodes[Qt(d)[0]];
      }), s = e.map(function(d) {
        return Qt(d)[0];
      }), o = s.map(function(d) {
        return r.graph.nodes[d];
      });
      o.length === 0 && (o = this._outputs);
      var c = this.getCompilationKey(a, o), l = this.compiledMap.get(c);
      l == null && (l = this.compile(t, o), this.compiledMap.set(c, l));
      var u = {}, h = {};
      return W.tidy(function() {
        var d = new k1(r.weightMap, u, h, r.functionExecutorMap), p = A1({}, r.weightMap);
        Object.keys(t).forEach(function(b) {
          var L = yt(Qt(b), 2), x = L[0], N = L[1], I = [];
          I[N] = t[b], p[x] = I;
        });
        for (var f = r.getFrozenTensorIds(p), m = {}, g = 0; g < l.length; g++) {
          var y = l[g];
          if (!p[y.name]) {
            var w = D1(y, p, d, r._resourceManager);
            if (W.util.isPromise(w))
              throw new Error("The execution of the op '" + y.op + "' returned a promise. Please use model.executeAsync() instead.");
            p[y.name] = w, r.checkTensorForDisposal(y.name, y, p, d, f, s, m);
          }
        }
        return r.parent == null && d.dispose(f), e.map(function(b) {
          return Gt(b, p, d);
        });
      });
    }, n.prototype.getFrozenTensorIds = function(t) {
      var e = [].concat.apply([], Object.keys(t).map(function(r) {
        return t[r];
      }).map(function(r) {
        return r.map(function(i) {
          return i.id;
        });
      }));
      return new Set(e);
    }, n.prototype.checkTensorForDisposal = function(t, e, r, i, a, s, o) {
      if (e.category === "control" || s.indexOf(t) !== -1)
        return;
      r[t].forEach(function(c) {
        c != null && (o[c.id] = (o[c.id] || 0) + e.children.length);
      }), e.inputs.forEach(function(c) {
        if (c.category !== "control") {
          var l = DD(c.name, r, i);
          l != null && l.forEach(function(u) {
            if (u && !a.has(u.id)) {
              var h = o[u.id];
              h === 1 ? (u.dispose(), delete o[u.id]) : h != null && o[u.id]--;
            }
          });
        }
      });
    }, n.prototype.executeAsync = function(t, e) {
      return on(this, void 0, void 0, function() {
        return Zt(this, function(r) {
          return [2, this._executeAsync(t, e)];
        });
      });
    }, n.prototype._executeAsync = function(t, e, r, i, a) {
      return r === void 0 && (r = false), i === void 0 && (i = {}), a === void 0 && (a = {}), on(this, void 0, void 0, function() {
        var s, o, c, l, u, h;
        return Zt(this, function(d) {
          switch (d.label) {
            case 0:
              return r || (t = this.mapInputs(t), this.checkInputs(t), this.checkInputShapeAndType(t), e = this.mapOutputs(e), this.checkOutputs(e)), s = new k1(this.weightMap, i, a, this.functionExecutorMap), [4, this.executeWithControlFlow(t, s, e, r)];
            case 1:
              return o = d.sent(), c = e.map(function(p) {
                return Gt(p, o, s);
              }), l = c.map(function(p) {
                return p.id;
              }), u = Object.keys(t).map(function(p) {
                return t[p].id;
              }), h = new Set(_r(l, u, this.weightIds)), Object.keys(o).forEach(function(p) {
                var f = o[p];
                f.forEach(function(m) {
                  m && !m.isDisposed && !h.has(m.id) && m.dispose();
                });
              }), this.parent == null && s.dispose(h), [2, c];
          }
        });
      });
    }, n.prototype.executeFunctionAsync = function(t, e, r) {
      return on(this, void 0, void 0, function() {
        var i, a = this;
        return Zt(this, function(s) {
          return i = t.reduce(function(o, c, l) {
            return o[a.inputs[l].name] = c, o;
          }, {}), [2, this._executeAsync(i, this.outputNodes, true, e, r)];
        });
      });
    }, n.prototype.executeWithControlFlow = function(t, e, r, i) {
      return on(this, void 0, void 0, function() {
        var a, s, o, c, l, u, h, d, p, f, m, g, y, w, b, L, x, N = this;
        return Zt(this, function(I) {
          switch (I.label) {
            case 0:
              a = Object.keys(t), s = a.map(function(C) {
                return N.graph.nodes[Qt(C)[0]];
              }), o = r.map(function(C) {
                return Qt(C)[0];
              }), c = o.map(function(C) {
                return N.graph.nodes[C];
              }), c.length === 0 && (c = this._outputs), l = W1(t, c, this.weightMap, this._initNodes), u = l.usedNodes, h = l.missingInputs, d = l.dynamicNode, p = l.syncInputs, f = _r(s, this.graph.weights, this._initNodes || []).map(function(C) {
                return {node: C, contexts: e.currentContext};
              }), m = A1({}, this.weightMap), Object.keys(t).forEach(function(C) {
                var O = yt(Qt(C), 2), D = O[0], F = O[1], k = [];
                k[F] = t[C], m[D] = k;
              }), g = {}, y = this.getFrozenTensorIds(m), w = {}, I.label = 1;
            case 1:
              return f.length > 0 ? (b = this.processStack(s, f, e, m, w, y, o, g, u), [4, Promise.all(b)]) : [3, 3];
            case 2:
              return I.sent(), [3, 1];
            case 3:
              if (d == null && !i && console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead."), L = c.filter(function(C) {
                return !F1(C) && !Gt(C.name, m, e);
              }).map(function(C) {
                return C.name;
              }), L.length > 0)
                throw x = "", d != null && (x = "Alternatively, to avoid the dynamic ops, use model.execute() " + ("and specify the inputs [" + p + "]")), new Error("Cannot compute the outputs [" + L + "] from the provided " + ("inputs [" + a + "]. Consider providing the following inputs: ") + ("[" + h + "]. " + x));
              return [2, m];
          }
        });
      });
    }, n.prototype.processStack = function(t, e, r, i, a, s, o, c, l) {
      for (var u = this, h = [], d = function() {
        var f, m, g = e.pop();
        r.currentContext = g.contexts;
        var y = "";
        if (g.node.op === "Enter" && T("isConstant", g.node, i, r) && (f = yt(Qn(g.node.name, r), 1), y = f[0]), i[g.node.name] == null) {
          var w = D1(g.node, i, r, p._resourceManager);
          y || (m = yt(Qn(g.node.name, r), 1), y = m[0]);
          var b = r.currentContext;
          W.util.isPromise(w) ? h.push(w.then(function(L) {
            return i[y] = L, r.currentContext = b, u.checkTensorForDisposal(y, g.node, i, r, s, o, c), u.processChildNodes(g.node, e, r, i, a, l), L;
          })) : (i[y] = w, p.checkTensorForDisposal(y, g.node, i, r, s, o, c), p.processChildNodes(g.node, e, r, i, a, l));
        } else
          p.processChildNodes(g.node, e, r, i, a, l);
      }, p = this; e.length > 0; )
        d();
      return h;
    }, n.prototype.processChildNodes = function(t, e, r, i, a, s) {
      t.children.forEach(function(o) {
        var c = yt(Qn(o.name, r), 1), l = c[0];
        if (a[l] || !s.has(o.name))
          return;
        o.op === "Merge" ? o.inputNames.some(function(u) {
          return !!Gt(u, i, r);
        }) && (a[l] = true, e.push({contexts: r.currentContext, node: o})) : o.inputNames.every(function(u) {
          return !!Gt(u, i, r);
        }) && (a[l] = true, e.push({contexts: r.currentContext, node: o}));
      });
    }, n.prototype.dispose = function() {
      var t = this;
      Object.keys(this.weightMap).forEach(function(e) {
        return t.weightMap[e].forEach(function(r) {
          return r.dispose();
        });
      });
    }, n.prototype.checkInputShapeAndType = function(t) {
      var e = this;
      Object.keys(t).forEach(function(r) {
        var i = t[r], a = yt(Qt(r), 1), s = a[0], o = e.graph.nodes[s];
        if (o.attrParams.shape && o.attrParams.shape.value) {
          var c = o.attrParams.shape.value, l = c.length === i.shape.length && i.shape.every(function(u, h) {
            return c[h] === -1 || c[h] === u;
          });
          W.util.assert(l, function() {
            return "The shape of dict['" + o.name + "'] provided in " + ("model.execute(dict) must be [" + c + "], but was ") + ("[" + i.shape + "]");
          });
        }
        o.attrParams.dtype && o.attrParams.dtype.value && W.util.assert(i.dtype === o.attrParams.dtype.value, function() {
          return "The dtype of dict['" + o.name + "'] provided in model.execute(dict) must be " + (o.attrParams.dtype.value + ", but was " + i.dtype);
        });
      });
    }, n.prototype.mapInputs = function(t) {
      var e = {};
      for (var r in t)
        if (this._signature != null && this._signature.inputs != null && this._signature.inputs[r] != null) {
          var i = this._signature.inputs[r];
          e[i.name] = t[r];
        } else
          e[r] = t[r];
      return e;
    }, n.prototype.checkInputs = function(t) {
      var e = this, r = Object.keys(t).filter(function(i) {
        var a = yt(Qt(i), 1), s = a[0];
        return e.graph.nodes[s] == null;
      });
      if (r.length > 0)
        throw new Error("The dict provided in model.execute(dict) has " + ("keys: [" + r + "] that are not part of graph"));
    }, n.prototype.mapOutputs = function(t) {
      var e = this;
      return t.map(function(r) {
        if (e._signature != null && e._signature.outputs != null && e._signature.outputs[r] != null) {
          var i = e._signature.outputs[r];
          return i.name;
        }
        return r;
      }, {});
    }, n.prototype.checkOutputs = function(t) {
      var e = this;
      t.forEach(function(r) {
        var i = yt(Qt(r), 1), a = i[0];
        if (!e.graph.nodes[a])
          throw new Error("The output '" + r + "' is not found in the graph");
      });
    }, n;
  }(), $k = function() {
    function n(t, e) {
      t === void 0 && (t = {}), e === void 0 && (e = {}), this.hashTableNameToHandle = t, this.hashTableMap = e;
    }
    return n.prototype.addHashTable = function(t, e) {
      this.hashTableNameToHandle[t] = e.handle, this.hashTableMap[e.id] = e;
    }, n.prototype.getHashTableHandleByName = function(t) {
      return this.hashTableNameToHandle[t];
    }, n.prototype.getHashTableById = function(t) {
      return this.hashTableMap[t];
    }, n.prototype.dispose = function() {
      for (var t in this.hashTableMap)
        this.hashTableMap[t].clearAndClose(), delete this.hashTableMap[t];
      for (var e in this.hashTableNameToHandle)
        this.hashTableNameToHandle[e].dispose(), delete this.hashTableNameToHandle[e];
    }, n;
  }();
  var Xk = "?tfjs-format=file", Jk = "model.json", B1 = function() {
    function n(t, e) {
      e === void 0 && (e = {}), this.modelUrl = t, this.loadOptions = e, this.version = "n/a", e == null && (this.loadOptions = {}), this.resourceManager = new $k();
    }
    return Object.defineProperty(n.prototype, "modelVersion", {get: function() {
      return this.version;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "inputNodes", {get: function() {
      return this.executor.inputNodes;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "outputNodes", {get: function() {
      return this.executor.outputNodes;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "inputs", {get: function() {
      return this.executor.inputs;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "outputs", {get: function() {
      return this.executor.outputs;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "weights", {get: function() {
      return this.executor.weightMap;
    }, enumerable: true, configurable: true}), n.prototype.findIOHandler = function() {
      var t = this.modelUrl;
      if (t.load != null)
        this.handler = t;
      else if (this.loadOptions.requestInit != null)
        this.handler = W.io.browserHTTPRequest(t, this.loadOptions);
      else {
        var e = W.io.getLoadHandlers(t, this.loadOptions);
        if (e.length === 0)
          e.push(W.io.browserHTTPRequest(t, this.loadOptions));
        else if (e.length > 1)
          throw new Error("Found more than one (" + e.length + ") load handlers for " + ("URL '" + [t] + "'"));
        this.handler = e[0];
      }
    }, n.prototype.load = function() {
      return on(this, void 0, void 0, function() {
        var t;
        return Zt(this, function(e) {
          switch (e.label) {
            case 0:
              if (this.findIOHandler(), this.handler.load == null)
                throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");
              return [4, this.handler.load()];
            case 1:
              return t = e.sent(), [2, this.loadSync(t)];
          }
        });
      });
    }, n.prototype.loadSync = function(t) {
      this.artifacts = t;
      var e = this.artifacts.modelTopology, r = {};
      this.artifacts.userDefinedMetadata != null && (r = this.artifacts.userDefinedMetadata.signature), this.version = e.versions.producer + "." + e.versions.minConsumer;
      var i = W.io.decodeWeights(this.artifacts.weightData, this.artifacts.weightSpecs);
      if (this.executor = new U1(C1.Instance.transformGraph(e, r)), this.executor.weightMap = this.convertTensorMapToTensorsMap(i), this.executor.resourceManager = this.resourceManager, t.modelInitializer != null) {
        var a = C1.Instance.transformGraph(t.modelInitializer);
        this.initializer = new U1(a), this.initializer.weightMap = this.executor.weightMap, this.initializer.resourceManager = this.resourceManager, this.initializer.executeAsync({}, []);
      }
      return true;
    }, n.prototype.save = function(t, e) {
      return on(this, void 0, void 0, function() {
        var r;
        return Zt(this, function(i) {
          if (typeof t == "string") {
            if (r = W.io.getSaveHandlers(t), r.length === 0)
              throw new Error("Cannot find any save handlers for URL '" + t + "'");
            if (r.length > 1)
              throw new Error("Found more than one (" + r.length + ") save handlers for " + ("URL '" + t + "'"));
            t = r[0];
          }
          if (t.save == null)
            throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");
          return [2, t.save(this.artifacts)];
        });
      });
    }, n.prototype.predict = function(t, e) {
      return this.execute(t, this.outputNodes);
    }, n.prototype.normalizeInputs = function(t) {
      if (!(t instanceof W.Tensor) && !Array.isArray(t))
        return t;
      if (t = Array.isArray(t) ? t : [t], t.length !== this.inputNodes.length)
        throw new Error("Input tensor count mismatch," + ("the graph model has " + this.inputNodes.length + " placeholders, ") + ("while there are " + t.length + " input tensors."));
      return this.inputNodes.reduce(function(e, r, i) {
        return e[r] = t[i], e;
      }, {});
    }, n.prototype.normalizeOutputs = function(t) {
      return t = t || this.outputNodes, Array.isArray(t) ? t : [t];
    }, n.prototype.execute = function(t, e) {
      t = this.normalizeInputs(t), e = this.normalizeOutputs(e);
      var r = this.executor.execute(t, e);
      return r.length > 1 ? r : r[0];
    }, n.prototype.executeAsync = function(t, e) {
      return on(this, void 0, void 0, function() {
        var r;
        return Zt(this, function(i) {
          switch (i.label) {
            case 0:
              return t = this.normalizeInputs(t), e = this.normalizeOutputs(e), [4, this.executor.executeAsync(t, e)];
            case 1:
              return r = i.sent(), [2, r.length > 1 ? r : r[0]];
          }
        });
      });
    }, n.prototype.convertTensorMapToTensorsMap = function(t) {
      return Object.keys(t).reduce(function(e, r) {
        return e[r] = [t[r]], e;
      }, {});
    }, n.prototype.dispose = function() {
      this.executor.dispose(), this.initializer && this.initializer.dispose(), this.resourceManager.dispose();
    }, n;
  }();
  function Zk(n, t) {
    return t === void 0 && (t = {}), on(this, void 0, void 0, function() {
      var e;
      return Zt(this, function(r) {
        switch (r.label) {
          case 0:
            if (n == null)
              throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");
            return t == null && (t = {}), t.fromTFHub && (n.load == null && (n.endsWith("/") || (n = n + "/"), n = "" + n + Jk + Xk)), e = new B1(n, t), [4, e.load()];
          case 1:
            return r.sent(), [2, e];
        }
      });
    });
  }
  var Qk = "2.7.0";
  oi.GraphModel = B1;
  oi.deregisterOp = ED;
  oi.loadGraphModel = Zk;
  oi.registerOp = OD;
  oi.version_converter = Qk;
});
var P1 = we(() => {
});
var sw = we((qt) => {
  "use strict";
  Object.defineProperty(qt, "__esModule", {value: true});
  var Ce = Qr();
  var Nd = function(n, t) {
    return Nd = Object.setPrototypeOf || {__proto__: []} instanceof Array && function(e, r) {
      e.__proto__ = r;
    } || function(e, r) {
      for (var i in r)
        r.hasOwnProperty(i) && (e[i] = r[i]);
    }, Nd(n, t);
  };
  function qe(n, t) {
    Nd(n, t);
    function e() {
      this.constructor = n;
    }
    n.prototype = t === null ? Object.create(t) : (e.prototype = t.prototype, new e());
  }
  function ce(n, t, e, r) {
    return new (e || (e = Promise))(function(i, a) {
      function s(l) {
        try {
          c(r.next(l));
        } catch (u) {
          a(u);
        }
      }
      function o(l) {
        try {
          c(r.throw(l));
        } catch (u) {
          a(u);
        }
      }
      function c(l) {
        l.done ? i(l.value) : new e(function(u) {
          u(l.value);
        }).then(s, o);
      }
      c((r = r.apply(n, t || [])).next());
    });
  }
  function le(n, t) {
    var e = {label: 0, sent: function() {
      if (a[0] & 1)
        throw a[1];
      return a[1];
    }, trys: [], ops: []}, r, i, a, s;
    return s = {next: o(0), throw: o(1), return: o(2)}, typeof Symbol == "function" && (s[Symbol.iterator] = function() {
      return this;
    }), s;
    function o(l) {
      return function(u) {
        return c([l, u]);
      };
    }
    function c(l) {
      if (r)
        throw new TypeError("Generator is already executing.");
      for (; e; )
        try {
          if (r = 1, i && (a = l[0] & 2 ? i.return : l[0] ? i.throw || ((a = i.return) && a.call(i), 0) : i.next) && !(a = a.call(i, l[1])).done)
            return a;
          (i = 0, a) && (l = [l[0] & 2, a.value]);
          switch (l[0]) {
            case 0:
            case 1:
              a = l;
              break;
            case 4:
              return e.label++, {value: l[1], done: false};
            case 5:
              e.label++, i = l[1], l = [0];
              continue;
            case 7:
              l = e.ops.pop(), e.trys.pop();
              continue;
            default:
              if (!(a = e.trys, a = a.length > 0 && a[a.length - 1]) && (l[0] === 6 || l[0] === 2)) {
                e = 0;
                continue;
              }
              if (l[0] === 3 && (!a || l[1] > a[0] && l[1] < a[3])) {
                e.label = l[1];
                break;
              }
              if (l[0] === 6 && e.label < a[1]) {
                e.label = a[1], a = l;
                break;
              }
              if (a && e.label < a[2]) {
                e.label = a[2], e.ops.push(l);
                break;
              }
              a[2] && e.ops.pop(), e.trys.pop();
              continue;
          }
          l = t.call(n, e);
        } catch (u) {
          l = [6, u], i = 0;
        } finally {
          r = a = 0;
        }
      if (l[0] & 5)
        throw l[1];
      return {value: l[0] ? l[1] : void 0, done: true};
    }
  }
  var $i = typeof globalThis != "undefined" ? globalThis : typeof window != "undefined" ? window : typeof global != "undefined" ? global : typeof self != "undefined" ? self : {};
  function ci(n, t) {
    return t = {exports: {}}, n(t, t.exports), t.exports;
  }
  var e6 = ci(function(n) {
    (function(t, e, r) {
      function i(c) {
        var l = this, u = o();
        l.next = function() {
          var h = 2091639 * l.s0 + l.c * 23283064365386963e-26;
          return l.s0 = l.s1, l.s1 = l.s2, l.s2 = h - (l.c = h | 0);
        }, l.c = 1, l.s0 = u(" "), l.s1 = u(" "), l.s2 = u(" "), l.s0 -= u(c), l.s0 < 0 && (l.s0 += 1), l.s1 -= u(c), l.s1 < 0 && (l.s1 += 1), l.s2 -= u(c), l.s2 < 0 && (l.s2 += 1), u = null;
      }
      function a(c, l) {
        return l.c = c.c, l.s0 = c.s0, l.s1 = c.s1, l.s2 = c.s2, l;
      }
      function s(c, l) {
        var u = new i(c), h = l && l.state, d = u.next;
        return d.int32 = function() {
          return u.next() * 4294967296 | 0;
        }, d.double = function() {
          return d() + (d() * 2097152 | 0) * 11102230246251565e-32;
        }, d.quick = d, h && (typeof h == "object" && a(h, u), d.state = function() {
          return a(u, {});
        }), d;
      }
      function o() {
        var c = 4022871197, l = function(u) {
          u = u.toString();
          for (var h = 0; h < u.length; h++) {
            c += u.charCodeAt(h);
            var d = 0.02519603282416938 * c;
            c = d >>> 0, d -= c, d *= c, c = d >>> 0, d -= c, c += d * 4294967296;
          }
          return (c >>> 0) * 23283064365386963e-26;
        };
        return l;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.alea = s;
    })($i, n, false);
  }), t6 = ci(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this, l = "";
        c.x = 0, c.y = 0, c.z = 0, c.w = 0, c.next = function() {
          var h = c.x ^ c.x << 11;
          return c.x = c.y, c.y = c.z, c.z = c.w, c.w ^= c.w >>> 19 ^ h ^ h >>> 8;
        }, o === (o | 0) ? c.x = o : l += o;
        for (var u = 0; u < l.length + 64; u++)
          c.x ^= l.charCodeAt(u) | 0, c.next();
      }
      function a(o, c) {
        return c.x = o.x, c.y = o.y, c.z = o.z, c.w = o.w, c;
      }
      function s(o, c) {
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (typeof u == "object" && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.xor128 = s;
    })($i, n, false);
  }), n6 = ci(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this, l = "";
        c.next = function() {
          var h = c.x ^ c.x >>> 2;
          return c.x = c.y, c.y = c.z, c.z = c.w, c.w = c.v, (c.d = c.d + 362437 | 0) + (c.v = c.v ^ c.v << 4 ^ (h ^ h << 1)) | 0;
        }, c.x = 0, c.y = 0, c.z = 0, c.w = 0, c.v = 0, o === (o | 0) ? c.x = o : l += o;
        for (var u = 0; u < l.length + 64; u++)
          c.x ^= l.charCodeAt(u) | 0, u == l.length && (c.d = c.x << 10 ^ c.x >>> 4), c.next();
      }
      function a(o, c) {
        return c.x = o.x, c.y = o.y, c.z = o.z, c.w = o.w, c.v = o.v, c.d = o.d, c;
      }
      function s(o, c) {
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (typeof u == "object" && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.xorwow = s;
    })($i, n, false);
  }), r6 = ci(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this;
        c.next = function() {
          var u = c.x, h = c.i, d, p;
          return d = u[h], d ^= d >>> 7, p = d ^ d << 24, d = u[h + 1 & 7], p ^= d ^ d >>> 10, d = u[h + 3 & 7], p ^= d ^ d >>> 3, d = u[h + 4 & 7], p ^= d ^ d << 7, d = u[h + 7 & 7], d = d ^ d << 13, p ^= d ^ d << 9, u[h] = p, c.i = h + 1 & 7, p;
        };
        function l(u, h) {
          var d, p, f = [];
          if (h === (h | 0))
            p = f[0] = h;
          else
            for (h = "" + h, d = 0; d < h.length; ++d)
              f[d & 7] = f[d & 7] << 15 ^ h.charCodeAt(d) + f[d + 1 & 7] << 13;
          for (; f.length < 8; )
            f.push(0);
          for (d = 0; d < 8 && f[d] === 0; ++d)
            ;
          for (d == 8 ? p = f[7] = -1 : p = f[d], u.x = f, u.i = 0, d = 256; d > 0; --d)
            u.next();
        }
        l(c, o);
      }
      function a(o, c) {
        return c.x = o.x.slice(), c.i = o.i, c;
      }
      function s(o, c) {
        o == null && (o = +new Date());
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (u.x && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.xorshift7 = s;
    })($i, n, false);
  }), i6 = ci(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this;
        c.next = function() {
          var u = c.w, h = c.X, d = c.i, p, f;
          return c.w = u = u + 1640531527 | 0, f = h[d + 34 & 127], p = h[d = d + 1 & 127], f ^= f << 13, p ^= p << 17, f ^= f >>> 15, p ^= p >>> 12, f = h[d] = f ^ p, c.i = d, f + (u ^ u >>> 16) | 0;
        };
        function l(u, h) {
          var d, p, f, m, g, y = [], w = 128;
          for (h === (h | 0) ? (p = h, h = null) : (h = h + "\0", p = 0, w = Math.max(w, h.length)), f = 0, m = -32; m < w; ++m)
            h && (p ^= h.charCodeAt((m + 32) % h.length)), m === 0 && (g = p), p ^= p << 10, p ^= p >>> 15, p ^= p << 4, p ^= p >>> 13, m >= 0 && (g = g + 1640531527 | 0, d = y[m & 127] ^= p + g, f = d == 0 ? f + 1 : 0);
          for (f >= 128 && (y[(h && h.length || 0) & 127] = -1), f = 127, m = 4 * 128; m > 0; --m)
            p = y[f + 34 & 127], d = y[f = f + 1 & 127], p ^= p << 13, d ^= d << 17, p ^= p >>> 15, d ^= d >>> 12, y[f] = p ^ d;
          u.w = g, u.X = y, u.i = f;
        }
        l(c, o);
      }
      function a(o, c) {
        return c.i = o.i, c.w = o.w, c.X = o.X.slice(), c;
      }
      function s(o, c) {
        o == null && (o = +new Date());
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (u.X && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.xor4096 = s;
    })($i, n, false);
  }), a6 = ci(function(n) {
    (function(t, e, r) {
      function i(o) {
        var c = this, l = "";
        c.next = function() {
          var h = c.b, d = c.c, p = c.d, f = c.a;
          return h = h << 25 ^ h >>> 7 ^ d, d = d - p | 0, p = p << 24 ^ p >>> 8 ^ f, f = f - h | 0, c.b = h = h << 20 ^ h >>> 12 ^ d, c.c = d = d - p | 0, c.d = p << 16 ^ d >>> 16 ^ f, c.a = f - h | 0;
        }, c.a = 0, c.b = 0, c.c = 2654435769 | 0, c.d = 1367130551, o === Math.floor(o) ? (c.a = o / 4294967296 | 0, c.b = o | 0) : l += o;
        for (var u = 0; u < l.length + 20; u++)
          c.b ^= l.charCodeAt(u) | 0, c.next();
      }
      function a(o, c) {
        return c.a = o.a, c.b = o.b, c.c = o.c, c.d = o.d, c;
      }
      function s(o, c) {
        var l = new i(o), u = c && c.state, h = function() {
          return (l.next() >>> 0) / 4294967296;
        };
        return h.double = function() {
          do
            var d = l.next() >>> 11, p = (l.next() >>> 0) / 4294967296, f = (d + p) / (1 << 21);
          while (f === 0);
          return f;
        }, h.int32 = l.next, h.quick = h, u && (typeof u == "object" && a(u, l), h.state = function() {
          return a(l, {});
        }), h;
      }
      e && e.exports ? e.exports = s : r && r.amd ? r(function() {
        return s;
      }) : this.tychei = s;
    })($i, n, false);
  }), li = ci(function(n) {
    (function(t, e) {
      var r = this, i = 256, a = 6, s = 52, o = "random", c = e.pow(i, a), l = e.pow(2, s), u = l * 2, h = i - 1, d;
      function p(L, x, N) {
        var I = [];
        x = x == true ? {entropy: true} : x || {};
        var C = y(g(x.entropy ? [L, b(t)] : L == null ? w() : L, 3), I), O = new f(I), D = function() {
          for (var F = O.g(a), k = c, B = 0; F < l; )
            F = (F + B) * i, k *= i, B = O.g(1);
          for (; F >= u; )
            F /= 2, k /= 2, B >>>= 1;
          return (F + B) / k;
        };
        return D.int32 = function() {
          return O.g(4) | 0;
        }, D.quick = function() {
          return O.g(4) / 4294967296;
        }, D.double = D, y(b(O.S), t), (x.pass || N || function(F, k, B, V) {
          return V && (V.S && m(V, O), F.state = function() {
            return m(O, {});
          }), B ? (e[o] = F, k) : F;
        })(D, C, "global" in x ? x.global : this == e, x.state);
      }
      e["seed" + o] = p;
      function f(L) {
        var x, N = L.length, I = this, C = 0, O = I.i = I.j = 0, D = I.S = [];
        for (N || (L = [N++]); C < i; )
          D[C] = C++;
        for (C = 0; C < i; C++)
          D[C] = D[O = h & O + L[C % N] + (x = D[C])], D[O] = x;
        (I.g = function(F) {
          for (var k, B = 0, V = I.i, P = I.j, G = I.S; F--; )
            k = G[V = h & V + 1], B = B * i + G[h & (G[V] = G[P = h & P + k]) + (G[P] = k)];
          return I.i = V, I.j = P, B;
        })(i);
      }
      function m(L, x) {
        return x.i = L.i, x.j = L.j, x.S = L.S.slice(), x;
      }
      function g(L, x) {
        var N = [], I = typeof L, C;
        if (x && I == "object")
          for (C in L)
            try {
              N.push(g(L[C], x - 1));
            } catch (O) {
            }
        return N.length ? N : I == "string" ? L : L + "\0";
      }
      function y(L, x) {
        for (var N = L + "", I, C = 0; C < N.length; )
          x[h & C] = h & (I ^= x[h & C] * 19) + N.charCodeAt(C++);
        return b(x);
      }
      function w() {
        try {
          var L;
          return d && (L = d.randomBytes) ? L = L(i) : (L = new Uint8Array(i), (r.crypto || r.msCrypto).getRandomValues(L)), b(L);
        } catch (I) {
          var x = r.navigator, N = x && x.plugins;
          return [+new Date(), r, N, r.screen, b(t)];
        }
      }
      function b(L) {
        return String.fromCharCode.apply(0, L);
      }
      if (y(e.random(), t), n.exports) {
        n.exports = p;
        try {
          d = Ts();
        } catch (L) {
        }
      }
    })([], Math);
  });
  li.alea = e6;
  li.xor128 = t6;
  li.xorwow = n6;
  li.xorshift7 = r6;
  li.xor4096 = i6;
  li.tychei = a6;
  var s6 = li, M1 = s6.alea;
  function o6(n, t) {
    return Mo(n, t);
  }
  function Mo(n, t, e, r) {
    if (e === void 0 && (e = new Map()), r === void 0 && (r = new Set()), n == null)
      return null;
    if (r.has(n))
      throw new Error("Circular references are not supported.");
    if (e.has(n))
      return e.get(n);
    var i = t(n);
    if (i.recurse && i.value !== null)
      throw new Error("A deep map function may not return both a value and recurse=true.");
    if (i.recurse)
      if (Xi(n)) {
        var a = Array.isArray(n) ? [] : {};
        r.add(n);
        for (var s in n) {
          var o = n[s], c = Mo(o, t, e, r);
          a[s] = c;
        }
        return r.delete(n), a;
      } else
        throw new Error("Can't recurse into non-iterable type: " + n);
    else
      return e.set(n, i.value), i.value;
  }
  function c6(n, t) {
    return t === void 0 && (t = V1), H1(n, t);
  }
  function H1(n, t, e) {
    e === void 0 && (e = new Set());
    var r = n[0];
    if (e.has(r))
      throw new Error("Circular references are not supported.");
    var i = t(n);
    if (i.recurse && i.value !== null)
      throw new Error("A deep zip function may not return both a value and recurse=true.");
    if (i.recurse)
      if (Xi(r)) {
        var a = Array.isArray(r) ? [] : {};
        e.add(r);
        var s = function(c) {
          var l = n.map(function(h) {
            return h[c];
          }), u = H1(l, t, e);
          a[c] = u;
        };
        for (var o in r)
          s(o);
        return e.delete(r), a;
      } else
        throw new Error("Can't recurse into non-iterable type: " + r);
    else
      return i.value;
  }
  function V1(n) {
    return n === null ? null : Xi(n[0]) ? {value: null, recurse: true} : {value: n, recurse: false};
  }
  function G1(n, t) {
    return ce(this, void 0, void 0, function() {
      var e, r, i, a, s, o, c;
      return le(this, function(l) {
        switch (l.label) {
          case 0:
            e = new Map(), Mo(n, t, e), r = 0, i = Array.from(e.keys()), l.label = 1;
          case 1:
            return r < i.length ? (a = i[r], s = e.get(a), Ce.util.isPromise(s) ? [4, s] : [3, 3]) : [3, 4];
          case 2:
            o = l.sent(), e.set(a, o), l.label = 3;
          case 3:
            return r++, [3, 1];
          case 4:
            return c = Mo(n, t, e), [2, c];
        }
      });
    });
  }
  function Xi(n) {
    return n != null && !ArrayBuffer.isView(n) && (Array.isArray(n) || typeof n == "object" && !(n instanceof Ce.Tensor));
  }
  function u6(n) {
    return n == null || l6(n) || Array.isArray(n) || typeof n == "object" && n instanceof Ce.Tensor || Ce.util.isTypedArray(n);
  }
  function l6(n) {
    return n === null || typeof n != "object" && typeof n != "function";
  }
  function d6(n) {
    return o6(n, h6);
  }
  function h6(n) {
    return n instanceof Ce.Tensor ? {value: n.clone(), recurse: false} : Xi(n) ? {value: null, recurse: true} : {value: n, recurse: false};
  }
  var q1 = function() {
    function n(t) {
      if (this.capacity = t, this.begin = 0, this.end = 0, t == null)
        throw new RangeError("Can't create a ring buffer of unknown capacity.");
      if (t < 1)
        throw new RangeError("Can't create ring buffer of capacity < 1.");
      this.data = new Array(t), this.doubledCapacity = 2 * t;
    }
    return n.prototype.wrap = function(t) {
      for (; t < 0; )
        t += this.doubledCapacity;
      return t % this.doubledCapacity;
    }, n.prototype.get = function(t) {
      if (t < 0)
        throw new RangeError("Can't get item at a negative index.");
      return this.data[t % this.capacity];
    }, n.prototype.set = function(t, e) {
      if (t < 0)
        throw new RangeError("Can't set item at a negative index.");
      this.data[t % this.capacity] = e;
    }, n.prototype.length = function() {
      var t = this.end - this.begin;
      return t < 0 && (t = this.doubledCapacity + t), t;
    }, n.prototype.isFull = function() {
      return this.length() === this.capacity;
    }, n.prototype.isEmpty = function() {
      return this.length() === 0;
    }, n.prototype.push = function(t) {
      if (this.isFull())
        throw new RangeError("Ring buffer is full.");
      this.set(this.end, t), this.end = this.wrap(this.end + 1);
    }, n.prototype.pushAll = function(t) {
      for (var e = 0, r = t; e < r.length; e++) {
        var i = r[e];
        this.push(i);
      }
    }, n.prototype.pop = function() {
      if (this.isEmpty())
        throw new RangeError("Ring buffer is empty.");
      this.end = this.wrap(this.end - 1);
      var t = this.get(this.end);
      return this.set(this.end, void 0), t;
    }, n.prototype.unshift = function(t) {
      if (this.isFull())
        throw new RangeError("Ring buffer is full.");
      this.begin = this.wrap(this.begin - 1), this.set(this.begin, t);
    }, n.prototype.shift = function() {
      if (this.isEmpty())
        throw new RangeError("Ring buffer is empty.");
      var t = this.get(this.begin);
      return this.set(this.begin, void 0), this.begin = this.wrap(this.begin + 1), t;
    }, n.prototype.shuffleExcise = function(t) {
      if (this.isEmpty())
        throw new RangeError("Ring buffer is empty.");
      var e = this.wrap(this.begin + t), r = this.get(e);
      return this.set(e, this.pop()), r;
    }, n;
  }();
  var p6 = function(n) {
    qe(t, n);
    function t() {
      return n.call(this, t.INITIAL_CAPACITY) || this;
    }
    return t.prototype.isFull = function() {
      return false;
    }, t.prototype.push = function(e) {
      n.prototype.isFull.call(this) && this.expand(), n.prototype.push.call(this, e);
    }, t.prototype.unshift = function(e) {
      n.prototype.isFull.call(this) && this.expand(), n.prototype.unshift.call(this, e);
    }, t.prototype.expand = function() {
      for (var e = this.capacity * 2, r = new Array(e), i = this.length(), a = 0; a < i; a++)
        r[a] = this.get(this.wrap(this.begin + a));
      this.data = r, this.capacity = e, this.doubledCapacity = 2 * this.capacity, this.begin = 0, this.end = i;
    }, t.INITIAL_CAPACITY = 32, t;
  }(q1);
  function Y1(n) {
    return new f6(n);
  }
  function _d(n) {
    return new m6(n);
  }
  function g6(n, t) {
    return new K1(n, t);
  }
  function v6(n, t) {
    return t === void 0 && (t = Cr.FAIL), new y6(n, t);
  }
  var Rt = function() {
    function n() {
    }
    return n.prototype.toArray = function() {
      return ce(this, void 0, void 0, function() {
        var t, e;
        return le(this, function(r) {
          switch (r.label) {
            case 0:
              return t = [], [4, this.next()];
            case 1:
              e = r.sent(), r.label = 2;
            case 2:
              return e.done ? [3, 4] : (t.push(e.value), [4, this.next()]);
            case 3:
              return e = r.sent(), [3, 2];
            case 4:
              return [2, t];
          }
        });
      });
    }, n.prototype.toArrayForTest = function() {
      return ce(this, void 0, void 0, function() {
        var t, e, r;
        return le(this, function(i) {
          switch (i.label) {
            case 0:
              return t = this.prefetch(100), e = [], [4, t.next()];
            case 1:
              r = i.sent(), i.label = 2;
            case 2:
              return r.done ? [3, 4] : (e.push(r.value), [4, t.next()]);
            case 3:
              return r = i.sent(), [3, 2];
            case 4:
              return [2, e];
          }
        });
      });
    }, n.prototype.resolveFully = function() {
      return ce(this, void 0, void 0, function() {
        var t;
        return le(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.next()];
            case 1:
              t = e.sent(), e.label = 2;
            case 2:
              return t.done ? [3, 4] : [4, this.next()];
            case 3:
              return t = e.sent(), [3, 2];
            case 4:
              return [2];
          }
        });
      });
    }, n.prototype.resolveWhile = function(t) {
      return ce(this, void 0, void 0, function() {
        var e, r;
        return le(this, function(i) {
          switch (i.label) {
            case 0:
              return [4, this.next()];
            case 1:
              e = i.sent(), r = t(e.value), i.label = 2;
            case 2:
              return !e.done && r ? [4, this.next()] : [3, 4];
            case 3:
              return e = i.sent(), r = t(e.value), [3, 2];
            case 4:
              return [2];
          }
        });
      });
    }, n.prototype.handleErrors = function(t) {
      return new A6(this, t);
    }, n.prototype.filter = function(t) {
      return new S6(this, t);
    }, n.prototype.map = function(t) {
      return new I6(this, t);
    }, n.prototype.mapAsync = function(t) {
      return new j1(this, t);
    }, n.prototype.serialMapAsync = function(t) {
      return new j1(this, t).serial();
    }, n.prototype.flatmap = function(t) {
      return new T6(this, t);
    }, n.prototype.forEachAsync = function(t) {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return [2, this.map(t).resolveFully()];
        });
      });
    }, n.prototype.serialForEach = function(t) {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return [2, this.serialMapAsync(t).resolveWhile(function(r) {
            return r === true;
          })];
        });
      });
    }, n.prototype.rowMajorBatch = function(t, e) {
      return e === void 0 && (e = true), new L6(this, t, e);
    }, n.prototype.columnMajorBatch = function(t, e, r) {
      e === void 0 && (e = true), r === void 0 && (r = V1);
      var i = this.rowMajorBatch(t, e);
      return i.map(function(a) {
        return c6(a, r);
      });
    }, n.prototype.concatenate = function(t, e) {
      return new K1(Y1([this, t]), e);
    }, n.prototype.take = function(t) {
      return t < 0 || t == null ? this : new x6(this, t);
    }, n.prototype.skip = function(t) {
      return t < 0 || t == null ? this : new b6(this, t);
    }, n.prototype.prefetch = function(t) {
      return new $1(this, t);
    }, n.prototype.shuffle = function(t, e) {
      return new N6(this, t, e);
    }, n.prototype.serial = function() {
      return new w6(this);
    }, n;
  }(), f6 = function(n) {
    qe(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.items = e, r.trav = 0, r;
    }
    return t.prototype.summary = function() {
      return "Array of " + this.items.length + " items";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e;
        return le(this, function(r) {
          return this.trav >= this.items.length ? [2, {value: null, done: true}] : (e = this.items[this.trav], this.trav++, [2, {value: d6(e), done: false}]);
        });
      });
    }, t;
  }(Rt), m6 = function(n) {
    qe(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.nextFn = e, r;
    }
    return t.prototype.summary = function() {
      return "Function call";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          try {
            return [2, this.nextFn()];
          } catch (r) {
            throw r.message = "Error thrown while iterating through a dataset: " + r.message, r;
          }
          return [2];
        });
      });
    }, t;
  }(Rt), w6 = function(n) {
    qe(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.upstream = e, r.lastRead = Promise.resolve({value: null, done: false}), r;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Serial";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e = this;
        return le(this, function(r) {
          return this.lastRead = this.lastRead.then(function() {
            return e.serialNext();
          }), [2, this.lastRead];
        });
      });
    }, t.prototype.serialNext = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return [2, this.upstream.next()];
        });
      });
    }, t;
  }(Rt), b6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.maxCount = r, i.count = 0, i.lastRead = Promise.resolve({value: null, done: false}), i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Skip";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e = this;
        return le(this, function(r) {
          return this.lastRead = this.lastRead.then(function() {
            return e.serialNext();
          }), [2, this.lastRead];
        });
      });
    }, t.prototype.serialNext = function() {
      return ce(this, void 0, void 0, function() {
        var e;
        return le(this, function(r) {
          switch (r.label) {
            case 0:
              return this.count++ < this.maxCount ? [4, this.upstream.next()] : [3, 2];
            case 1:
              return e = r.sent(), e.done ? [2, e] : (Ce.dispose(e.value), [3, 0]);
            case 2:
              return [2, this.upstream.next()];
          }
        });
      });
    }, t;
  }(Rt), x6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.maxCount = r, i.count = 0, i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Take";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return this.count++ >= this.maxCount ? [2, {value: null, done: true}] : [2, this.upstream.next()];
        });
      });
    }, t;
  }(Rt), L6 = function(n) {
    qe(t, n);
    function t(e, r, i) {
      i === void 0 && (i = true);
      var a = n.call(this) || this;
      return a.upstream = e, a.batchSize = r, a.enableSmallLastBatch = i, a.lastRead = Promise.resolve({value: null, done: false}), a;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> RowMajorBatch";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e = this;
        return le(this, function(r) {
          return this.lastRead = this.lastRead.then(function() {
            return e.serialNext();
          }), [2, this.lastRead];
        });
      });
    }, t.prototype.serialNext = function() {
      return ce(this, void 0, void 0, function() {
        var e, r;
        return le(this, function(i) {
          switch (i.label) {
            case 0:
              e = [], i.label = 1;
            case 1:
              return e.length < this.batchSize ? [4, this.upstream.next()] : [3, 3];
            case 2:
              return r = i.sent(), r.done ? this.enableSmallLastBatch && e.length > 0 ? [2, {value: e, done: false}] : [2, {value: null, done: true}] : (e.push(r.value), [3, 1]);
            case 3:
              return [2, {value: e, done: false}];
          }
        });
      });
    }, t;
  }(Rt), S6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.predicate = r, i.lastRead = Promise.resolve({value: null, done: false}), i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Filter";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e = this;
        return le(this, function(r) {
          return this.lastRead = this.lastRead.then(function() {
            return e.serialNext();
          }), [2, this.lastRead];
        });
      });
    }, t.prototype.serialNext = function() {
      return ce(this, void 0, void 0, function() {
        var e;
        return le(this, function(r) {
          switch (r.label) {
            case 0:
              return [4, this.upstream.next()];
            case 1:
              return e = r.sent(), e.done || this.predicate(e.value) ? [2, e] : (Ce.dispose(e.value), [3, 0]);
            case 2:
              return [2];
          }
        });
      });
    }, t;
  }(Rt), I6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.transform = r, i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Map";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a, s, o, c;
        return le(this, function(l) {
          switch (l.label) {
            case 0:
              return [4, this.upstream.next()];
            case 1:
              if (e = l.sent(), e.done)
                return [2, {value: null, done: true}];
              for (r = Ce.tensor_util.getTensorsInContainer(e.value), i = this.transform(e.value), a = Ce.tensor_util.getTensorsInContainer(i), s = 0, o = r; s < o.length; s++)
                c = o[s], Ce.tensor_util.isTensorInList(c, a) || c.dispose();
              return [2, {value: i, done: false}];
          }
        });
      });
    }, t;
  }(Rt), A6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.handler = r, i.count = 0, i.lastRead = Promise.resolve({value: null, done: false}), i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> handleErrors";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e = this;
        return le(this, function(r) {
          return this.lastRead = this.lastRead.then(function() {
            return e.serialNext();
          }), [2, this.lastRead];
        });
      });
    }, t.prototype.serialNext = function() {
      return ce(this, void 0, void 0, function() {
        var e;
        return le(this, function(r) {
          switch (r.label) {
            case 0:
              r.label = 1;
            case 1:
              return r.trys.push([1, 3, , 4]), [4, this.upstream.next()];
            case 2:
              return [2, r.sent()];
            case 3:
              return e = r.sent(), this.handler(e) ? [3, 4] : [2, {value: null, done: true}];
            case 4:
              return [3, 0];
            case 5:
              return [2];
          }
        });
      });
    }, t;
  }(Rt), j1 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.transform = r, i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> AsyncMap";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a, s, o, c;
        return le(this, function(l) {
          switch (l.label) {
            case 0:
              return [4, this.upstream.next()];
            case 1:
              return e = l.sent(), e.done ? [2, {value: null, done: true}] : (r = Ce.tensor_util.getTensorsInContainer(e.value), [4, this.transform(e.value)]);
            case 2:
              for (i = l.sent(), a = Ce.tensor_util.getTensorsInContainer(i), s = 0, o = r; s < o.length; s++)
                c = o[s], Ce.tensor_util.isTensorInList(c, a) || c.dispose();
              return [2, {value: i, done: false}];
          }
        });
      });
    }, t;
  }(Rt), Cd = function(n) {
    qe(t, n);
    function t() {
      var e = n.call(this) || this;
      return e.outputQueue = new p6(), e.lastRead = Promise.resolve({value: null, done: false}), e;
    }
    return t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e = this;
        return le(this, function(r) {
          return this.lastRead = this.lastRead.then(function() {
            return e.serialNext();
          }), [2, this.lastRead];
        });
      });
    }, t.prototype.serialNext = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          switch (e.label) {
            case 0:
              return this.outputQueue.length() === 0 ? [4, this.pump()] : [3, 2];
            case 1:
              return e.sent() ? [3, 0] : [2, {value: null, done: true}];
            case 2:
              return [2, {value: this.outputQueue.shift(), done: false}];
          }
        });
      });
    }, t;
  }(Rt), T6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.transform = r, i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Flatmap";
    }, t.prototype.pump = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a, s, o, c;
        return le(this, function(l) {
          switch (l.label) {
            case 0:
              return [4, this.upstream.next()];
            case 1:
              if (e = l.sent(), e.done)
                return [2, false];
              for (r = Ce.tensor_util.getTensorsInContainer(e.value), i = this.transform(e.value), a = Ce.tensor_util.getTensorsInContainer(i), this.outputQueue.pushAll(i), s = 0, o = r; s < o.length; s++)
                c = o[s], Ce.tensor_util.isTensorInList(c, a) || c.dispose();
              return [2, true];
          }
        });
      });
    }, t;
  }(Cd), K1 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.baseErrorHandler = r, i.lastRead = null, i.iterator = null, i.moreIterators = e, i;
    }
    return t.prototype.summary = function() {
      var e = "TODO: fill in upstream of chained summaries";
      return e + " -> Chained";
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return this.lastRead = this.readFromChain(this.lastRead), [2, this.lastRead];
        });
      });
    }, t.prototype.readFromChain = function(e) {
      return ce(this, void 0, void 0, function() {
        var r, i;
        return le(this, function(a) {
          switch (a.label) {
            case 0:
              return [4, e];
            case 1:
              return a.sent(), this.iterator == null ? [4, this.moreIterators.next()] : [3, 3];
            case 2:
              if (r = a.sent(), r.done)
                return [2, {value: null, done: true}];
              this.iterator = r.value, this.baseErrorHandler != null && (this.iterator = this.iterator.handleErrors(this.baseErrorHandler)), a.label = 3;
            case 3:
              return [4, this.iterator.next()];
            case 4:
              return i = a.sent(), i.done ? (this.iterator = null, [2, this.readFromChain(e)]) : [2, i];
          }
        });
      });
    }, t;
  }(Rt), Cr;
  (function(n) {
    n[n.FAIL = 0] = "FAIL", n[n.SHORTEST = 1] = "SHORTEST", n[n.LONGEST = 2] = "LONGEST";
  })(Cr || (Cr = {}));
  var y6 = function(n) {
    qe(t, n);
    function t(e, r) {
      r === void 0 && (r = Cr.FAIL);
      var i = n.call(this) || this;
      return i.iterators = e, i.mismatchMode = r, i.count = 0, i.currentPromise = null, i;
    }
    return t.prototype.summary = function() {
      var e = "TODO: fill in upstream of zip summaries";
      return "{" + e + "} -> Zip";
    }, t.prototype.nextState = function(e) {
      return ce(this, void 0, void 0, function() {
        function r(o) {
          if (o instanceof Rt) {
            var c = o.next();
            return {value: c.then(function(l) {
              return i++, l.done && a++, l.value;
            }), recurse: false};
          } else
            return {value: null, recurse: true};
        }
        var i, a, s;
        return le(this, function(o) {
          switch (o.label) {
            case 0:
              return [4, e];
            case 1:
              return o.sent(), i = 0, a = 0, [4, G1(this.iterators, r)];
            case 2:
              if (s = o.sent(), i === a)
                return [2, {value: null, done: true}];
              if (a > 0)
                switch (this.mismatchMode) {
                  case Cr.FAIL:
                    throw new Error("Zipped streams should have the same length. " + ("Mismatched at element " + this.count + "."));
                  case Cr.SHORTEST:
                    return [2, {value: null, done: true}];
                  case Cr.LONGEST:
                }
              return this.count++, [2, {value: s, done: false}];
          }
        });
      });
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return this.currentPromise = this.nextState(this.currentPromise), [2, this.currentPromise];
        });
      });
    }, t;
  }(Rt), $1 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.bufferSize = r, i.buffer = new q1(r), i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Prefetch";
    }, t.prototype.refill = function() {
      for (; !this.buffer.isFull(); ) {
        var e = this.upstream.next();
        this.buffer.push(e);
      }
    }, t.prototype.next = function() {
      return this.refill(), this.buffer.shift();
    }, t;
  }(Rt), N6 = function(n) {
    qe(t, n);
    function t(e, r, i) {
      var a = n.call(this, e, r) || this;
      return a.upstream = e, a.windowSize = r, a.upstreamExhausted = false, a.random = M1(i || Ce.util.now().toString()), a.lastRead = Promise.resolve({value: null, done: false}), a;
    }
    return t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e = this;
        return le(this, function(r) {
          return this.lastRead = this.lastRead.then(function() {
            return e.serialNext();
          }), [2, this.lastRead];
        });
      });
    }, t.prototype.randomInt = function(e) {
      return Math.floor(this.random() * e);
    }, t.prototype.chooseIndex = function() {
      return this.randomInt(this.buffer.length());
    }, t.prototype.serialNext = function() {
      return ce(this, void 0, void 0, function() {
        var e, r;
        return le(this, function(i) {
          switch (i.label) {
            case 0:
              this.upstreamExhausted || this.refill(), i.label = 1;
            case 1:
              return this.buffer.isEmpty() ? [3, 3] : (e = this.chooseIndex(), [4, this.buffer.shuffleExcise(e)]);
            case 2:
              if (r = i.sent(), r.done)
                this.upstreamExhausted = true;
              else
                return this.refill(), [2, r];
              return [3, 1];
            case 3:
              return [2, {value: null, done: true}];
          }
        });
      });
    }, t;
  }($1);
  var Xa = function() {
    function n() {
      this.size = null;
    }
    return n.prototype.batch = function(t, e) {
      var r = this;
      e === void 0 && (e = true);
      var i = this;
      Ce.util.assert(t > 0, function() {
        return `batchSize needs to be positive, but it is
      ` + t;
      });
      var a;
      return this.size === Infinity || this.size == null ? a = this.size : e ? a = Math.ceil(this.size / t) : a = Math.floor(this.size / t), en(function() {
        return ce(r, void 0, void 0, function() {
          return le(this, function(s) {
            switch (s.label) {
              case 0:
                return [4, i.iterator()];
              case 1:
                return [2, s.sent().columnMajorBatch(t, e, _6)];
            }
          });
        });
      }, a);
    }, n.prototype.concatenate = function(t) {
      var e = this, r = this, i;
      return this.size === Infinity || t.size === Infinity ? i = Infinity : this.size != null && t.size != null ? i = this.size + t.size : i = null, en(function() {
        return ce(e, void 0, void 0, function() {
          var a, s;
          return le(this, function(o) {
            switch (o.label) {
              case 0:
                return [4, r.iterator()];
              case 1:
                return s = (a = o.sent()).concatenate, [4, t.iterator()];
              case 2:
                return [2, s.apply(a, [o.sent()])];
            }
          });
        });
      }, i);
    }, n.prototype.filter = function(t) {
      var e = this, r = this, i;
      return this.size === Infinity ? i = Infinity : i = null, en(function() {
        return ce(e, void 0, void 0, function() {
          return le(this, function(a) {
            switch (a.label) {
              case 0:
                return [4, r.iterator()];
              case 1:
                return [2, a.sent().filter(function(s) {
                  return Ce.tidy(function() {
                    return t(s);
                  });
                })];
            }
          });
        });
      }, i);
    }, n.prototype.forEachAsync = function(t) {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.iterator()];
            case 1:
              return [2, e.sent().forEachAsync(t)];
          }
        });
      });
    }, n.prototype.map = function(t) {
      var e = this, r = this;
      return en(function() {
        return ce(e, void 0, void 0, function() {
          return le(this, function(i) {
            switch (i.label) {
              case 0:
                return [4, r.iterator()];
              case 1:
                return [2, i.sent().map(function(a) {
                  return Ce.tidy(function() {
                    return t(a);
                  });
                })];
            }
          });
        });
      }, this.size);
    }, n.prototype.mapAsync = function(t) {
      var e = this, r = this;
      return en(function() {
        return ce(e, void 0, void 0, function() {
          return le(this, function(i) {
            switch (i.label) {
              case 0:
                return [4, r.iterator()];
              case 1:
                return [2, i.sent().mapAsync(t)];
            }
          });
        });
      }, this.size);
    }, n.prototype.prefetch = function(t) {
      var e = this;
      if (t == null)
        throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");
      var r = this;
      return en(function() {
        return ce(e, void 0, void 0, function() {
          return le(this, function(i) {
            switch (i.label) {
              case 0:
                return [4, r.iterator()];
              case 1:
                return [2, i.sent().prefetch(t)];
            }
          });
        });
      }, this.size);
    }, n.prototype.repeat = function(t) {
      var e = this, r = this, i;
      return this.size != null && t > 0 ? i = this.size * t : t === 0 ? i = 0 : this.size != null && (t === void 0 || t < 0) ? i = Infinity : i = null, en(function() {
        return ce(e, void 0, void 0, function() {
          var a, s = this;
          return le(this, function(o) {
            return a = _d(function() {
              return ce(s, void 0, void 0, function() {
                var c;
                return le(this, function(l) {
                  switch (l.label) {
                    case 0:
                      return c = {}, [4, r.iterator()];
                    case 1:
                      return [2, (c.value = l.sent(), c.done = false, c)];
                  }
                });
              });
            }), [2, g6(a.take(t))];
          });
        });
      }, i);
    }, n.prototype.skip = function(t) {
      var e = this, r = this, i;
      return this.size != null && t >= 0 && this.size >= t ? i = this.size - t : this.size != null && (this.size < t || t === void 0 || t < 0) ? i = 0 : i = null, en(function() {
        return ce(e, void 0, void 0, function() {
          return le(this, function(a) {
            switch (a.label) {
              case 0:
                return [4, r.iterator()];
              case 1:
                return [2, a.sent().skip(t)];
            }
          });
        });
      }, i);
    }, n.prototype.shuffle = function(t, e, r) {
      var i = this;
      if (r === void 0 && (r = true), t == null || t < 0)
        throw this.size == null ? new RangeError("`Dataset.shuffle()` requires bufferSize to be specified.") : new RangeError("`Dataset.shuffle()` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for `tf.Tensor`s), consider setting " + ("bufferSize to the dataset size (" + this.size + " elements)"));
      var a = this, s = M1(e || Ce.util.now().toString());
      return en(function() {
        return ce(i, void 0, void 0, function() {
          var o;
          return le(this, function(c) {
            switch (c.label) {
              case 0:
                return o = s.int32(), r && (o += s.int32()), [4, a.iterator()];
              case 1:
                return [2, c.sent().shuffle(t, o.toString())];
            }
          });
        });
      }, this.size);
    }, n.prototype.take = function(t) {
      var e = this, r = this, i;
      return this.size != null && this.size > t ? i = t : this.size != null && this.size <= t ? i = this.size : i = null, en(function() {
        return ce(e, void 0, void 0, function() {
          return le(this, function(a) {
            switch (a.label) {
              case 0:
                return [4, r.iterator()];
              case 1:
                return [2, a.sent().take(t)];
            }
          });
        });
      }, i);
    }, n.prototype.toArray = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(t) {
          switch (t.label) {
            case 0:
              if (this.size === Infinity)
                throw new Error("Can not convert infinite data stream to array.");
              return [4, this.iterator()];
            case 1:
              return [2, t.sent().toArray()];
          }
        });
      });
    }, n.prototype.toArrayForTest = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(t) {
          switch (t.label) {
            case 0:
              if (this.size === Infinity)
                throw new Error("Can not convert infinite data stream to array.");
              return [4, this.iterator()];
            case 1:
              return [2, t.sent().toArrayForTest()];
          }
        });
      });
    }, n.MAX_BUFFER_SIZE = 1e4, n;
  }();
  function en(n, t) {
    return t === void 0 && (t = null), new (function(e) {
      qe(r, e);
      function r() {
        var i = e !== null && e.apply(this, arguments) || this;
        return i.size = t, i;
      }
      return r.prototype.iterator = function() {
        return ce(this, void 0, void 0, function() {
          return le(this, function(i) {
            return [2, n()];
          });
        });
      }, r;
    }(Xa))();
  }
  function C6(n) {
    var t = this;
    return en(function() {
      return ce(t, void 0, void 0, function() {
        return le(this, function(e) {
          return [2, Y1(n)];
        });
      });
    }, n.length);
  }
  function R6(n) {
    var t = this;
    if (!Xi(n))
      throw new Error("The argument to zip() must be an object or array.");
    var e;
    if (Array.isArray(n))
      for (var r = 0; r < n.length; r++)
        e = e == null ? n[r].size : Math.min(e, n[r].size);
    else if (n instanceof Object)
      for (var i in n)
        e = e == null ? n[i].size : Math.min(e, n[i].size);
    return en(function() {
      return ce(t, void 0, void 0, function() {
        var a;
        return le(this, function(s) {
          switch (s.label) {
            case 0:
              return [4, G1(n, function(o) {
                if (o instanceof Xa)
                  return {value: o.iterator(), recurse: false};
                if (Xi(o))
                  return {value: null, recurse: true};
                throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.");
              })];
            case 1:
              return a = s.sent(), [2, v6(a, Cr.SHORTEST)];
          }
        });
      });
    }, e);
  }
  function _6(n) {
    if (n === null)
      return null;
    var t = n[0];
    if (u6(t)) {
      var e = O6(n);
      return {value: e, recurse: false};
    }
    return {value: null, recurse: true};
  }
  function O6(n) {
    if (n.length === 0)
      throw new Error("Can't make a batch of zero elements.");
    return n[0] instanceof Ce.Tensor ? Ce.stack(n) : Ce.tensor(n);
  }
  var X1 = function(n) {
    qe(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.input = e, r;
    }
    return t.prototype.iterator = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i;
        return le(this, function(a) {
          switch (a.label) {
            case 0:
              return [4, this.input.iterator()];
            case 1:
              return e = a.sent(), r = e.decodeUTF8(), i = r.split(`
`).map(function(s) {
                return s.endsWith("\r") && (s = s.slice(0, -1)), s;
              }), [2, i];
          }
        });
      });
    }, t;
  }(Xa);
  var Ho = '"', Ja = Symbol("out"), J1 = Symbol("field"), Vo = Symbol("quote"), Rd = Symbol("quoteafterquote"), Z1 = Symbol("quoteinquote"), Q1 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.input = e, i.hasHeader = true, i.fullColumnNames = null, i.columnNamesValidated = false, i.columnConfigs = null, i.configuredColumnsOnly = false, i.delimiter = ",", i.delimWhitespace = false, i.base = new X1(e), r || (r = {}), i.hasHeader = !(r.hasHeader === false), i.fullColumnNames = r.columnNames, i.columnConfigs = r.columnConfigs, i.configuredColumnsOnly = r.configuredColumnsOnly, r.delimWhitespace ? (Ce.util.assert(r.delimiter == null, function() {
        return "Delimiter should not be provided when delimWhitespace is true.";
      }), i.delimWhitespace = true, i.delimiter = " ") : i.delimiter = r.delimiter ? r.delimiter : ",", i;
    }
    return t.prototype.columnNames = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          switch (e.label) {
            case 0:
              return this.columnNamesValidated ? [3, 2] : [4, this.setColumnNames()];
            case 1:
              e.sent(), e.label = 2;
            case 2:
              return [2, this.configuredColumnsOnly ? Object.keys(this.columnConfigs) : this.fullColumnNames];
          }
        });
      });
    }, t.prototype.setColumnNames = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a, s, o, c, l = this;
        return le(this, function(u) {
          switch (u.label) {
            case 0:
              return [4, this.maybeReadHeaderLine()];
            case 1:
              if (e = u.sent(), !this.fullColumnNames && !e)
                throw new Error("Column names must be provided if there is no header line.");
              if (this.fullColumnNames && e && Ce.util.assert(e.length === this.fullColumnNames.length, function() {
                return "The length of provided columnNames (" + l.fullColumnNames.length.toString() + ") does not match the length of the header line read from file (" + e.length.toString() + ").";
              }), this.fullColumnNames || (this.fullColumnNames = e), r = this.fullColumnNames.reduce(function(h, d) {
                return h[d] = h[d] + 1 || 1, h;
              }, {}), i = Object.keys(r).filter(function(h) {
                return r[h] > 1;
              }), Ce.util.assert(i.length === 0, function() {
                return "Duplicate column names found: " + i.toString();
              }), this.columnConfigs) {
                for (a = 0, s = Object.keys(this.columnConfigs); a < s.length; a++)
                  if (o = s[a], c = this.fullColumnNames.indexOf(o), c === -1)
                    throw new Error('The key "' + o + '" provided in columnConfigs does not match any of the column names (' + this.fullColumnNames.toString() + ").");
              }
              return this.columnNamesValidated = true, [2];
          }
        });
      });
    }, t.prototype.maybeReadHeaderLine = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a;
        return le(this, function(s) {
          switch (s.label) {
            case 0:
              return this.hasHeader ? [4, this.base.iterator()] : [3, 3];
            case 1:
              return e = s.sent(), [4, e.next()];
            case 2:
              if (r = s.sent(), r.done)
                throw new Error("No data was found for CSV parsing.");
              return i = r.value, a = this.parseRow(i, false), [2, a];
            case 3:
              return [2, null];
          }
        });
      });
    }, t.prototype.iterator = function() {
      return ce(this, void 0, void 0, function() {
        var e, r = this;
        return le(this, function(i) {
          switch (i.label) {
            case 0:
              return this.columnNamesValidated ? [3, 2] : [4, this.setColumnNames()];
            case 1:
              i.sent(), i.label = 2;
            case 2:
              return [4, this.base.iterator()];
            case 3:
              return e = i.sent(), this.hasHeader && (e = e.skip(1)), [2, e.map(function(a) {
                return r.makeDataElement(a);
              })];
          }
        });
      });
    }, t.prototype.makeDataElement = function(e) {
      for (var r = this.parseRow(e), i = {}, a = {}, s = 0; s < this.fullColumnNames.length; s++) {
        var o = this.fullColumnNames[s], c = this.columnConfigs ? this.columnConfigs[o] : null;
        if (this.configuredColumnsOnly && !c)
          continue;
        var l = r[s], u = null;
        if (l === "")
          if (c && c.default !== void 0)
            u = c.default;
          else {
            if (c && (c.required || c.isLabel))
              throw new Error("Required column " + o + " is empty in this line: " + e);
            u = void 0;
          }
        else {
          var h = Number(l);
          if (isNaN(h))
            c && c.dtype === "bool" ? u = this.getBoolean(l) : u = l;
          else if (!c || !c.dtype)
            u = h;
          else
            switch (c.dtype) {
              case "float32":
                u = h;
                break;
              case "int32":
                u = Math.floor(h);
                break;
              case "bool":
                u = this.getBoolean(l);
                break;
              default:
                u = h;
            }
        }
        c && c.isLabel ? a[o] = u : i[o] = u;
      }
      return Object.keys(a).length === 0 ? i : {xs: i, ys: a};
    }, t.prototype.getBoolean = function(e) {
      return e === "1" || e.toLowerCase() === "true" ? 1 : 0;
    }, t.prototype.parseRow = function(e, r) {
      r === void 0 && (r = true);
      for (var i = [], a = 0, s = e.length, o = Ja, c = 0; c < s; c++)
        switch (o) {
          case Ja:
            switch (e.charAt(c)) {
              case Ho:
                a = c + 1, o = Vo;
                break;
              case this.delimiter:
                if (a = c + 1, this.delimiter === " " && this.delimWhitespace)
                  break;
                i.push(""), o = Ja;
                break;
              default:
                o = J1, a = c;
                break;
            }
            break;
          case J1:
            switch (e.charAt(c)) {
              case this.delimiter:
                i.push(e.substring(a, c)), o = Ja, a = c + 1;
                break;
            }
            break;
          case Vo:
            switch (e.charAt(c)) {
              case Ho:
                o = Rd;
                break;
            }
            break;
          case Rd:
            switch (e.charAt(c)) {
              case this.delimiter:
                i.push(e.substring(a, c - 1)), o = Ja, a = c + 1;
                break;
              case Ho:
                o = Vo;
                break;
              default:
                o = Z1;
                break;
            }
            break;
          case Z1:
            switch (e.charAt(c)) {
              case Ho:
                o = Vo;
                break;
            }
            break;
        }
      if (o === Rd ? i.push(e.substring(a, s - 1)) : i.push(e.substring(a)), r && i.length !== this.fullColumnNames.length)
        throw new Error("Invalid row in csv file. Should have " + this.fullColumnNames.length + " elements in a row, but got " + i);
      return i;
    }, t;
  }(Xa);
  var E6 = function(n) {
    qe(t, n);
    function t(e) {
      var r = n.call(this) || this;
      r.microphoneConfig = e, r.isClosed = false, r.fftSize = e.fftSize || 1024;
      var i = Math.log2(r.fftSize);
      if (r.fftSize < 0 || i < 4 || i > 14 || !Number.isInteger(i))
        throw new Error("Invalid fftSize: it must be a power of 2 between " + ("2 to 4 and 2 to 14, but got " + r.fftSize));
      if (r.numFrames = e.numFramesPerSpectrogram || 43, r.sampleRateHz = e.sampleRateHz, r.columnTruncateLength = e.columnTruncateLength || r.fftSize, r.audioTrackConstraints = e.audioTrackConstraints, r.smoothingTimeConstant = e.smoothingTimeConstant || 0, r.includeSpectrogram = !(e.includeSpectrogram === false), r.includeWaveform = e.includeWaveform === true, !r.includeSpectrogram && !r.includeWaveform)
        throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.");
      return r;
    }
    return t.prototype.summary = function() {
      return "microphone";
    }, t.create = function(e) {
      return e === void 0 && (e = {}), ce(this, void 0, void 0, function() {
        var r;
        return le(this, function(i) {
          switch (i.label) {
            case 0:
              if (Ce.env().get("IS_NODE"))
                throw new Error("microphone API is only supported in browser environment.");
              return r = new t(e), [4, r.start()];
            case 1:
              return i.sent(), [2, r];
          }
        });
      });
    }, t.prototype.start = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a;
        return le(this, function(s) {
          switch (s.label) {
            case 0:
              return s.trys.push([0, 2, , 3]), e = this, [4, navigator.mediaDevices.getUserMedia({audio: this.audioTrackConstraints == null ? true : this.audioTrackConstraints, video: false})];
            case 1:
              return e.stream = s.sent(), [3, 3];
            case 2:
              throw r = s.sent(), new Error("Error thrown while initializing video stream: " + r.message);
            case 3:
              if (!this.stream)
                throw new Error("Could not obtain audio from microphone.");
              if (i = window.AudioContext || window.webkitAudioContext, this.audioContext = new i(), !this.sampleRateHz)
                this.sampleRateHz = this.audioContext.sampleRate;
              else if (this.audioContext.sampleRate !== this.sampleRateHz)
                throw new Error("Mismatch in sampling rate: " + ("Expected: " + this.sampleRateHz + "; ") + ("Actual: " + this.audioContext.sampleRate));
              return a = this.audioContext.createMediaStreamSource(this.stream), this.analyser = this.audioContext.createAnalyser(), this.analyser.fftSize = this.fftSize * 2, this.analyser.smoothingTimeConstant = this.smoothingTimeConstant, a.connect(this.analyser), this.freqData = new Float32Array(this.fftSize), this.timeData = new Float32Array(this.fftSize), [2];
          }
        });
      });
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a, s;
        return le(this, function(o) {
          switch (o.label) {
            case 0:
              return this.isClosed ? [2, {value: null, done: true}] : [4, this.getAudioData()];
            case 1:
              return i = o.sent(), this.includeSpectrogram && (a = this.flattenQueue(i.freqDataQueue), e = this.getTensorFromAudioDataArray(a, [this.numFrames, this.columnTruncateLength, 1])), this.includeWaveform && (s = this.flattenQueue(i.timeDataQueue), r = this.getTensorFromAudioDataArray(s, [this.numFrames * this.fftSize, 1])), [2, {value: {spectrogram: e, waveform: r}, done: false}];
          }
        });
      });
    }, t.prototype.capture = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.next()];
            case 1:
              return [2, e.sent().value];
          }
        });
      });
    }, t.prototype.getAudioData = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a = this;
        return le(this, function(s) {
          return e = [], r = [], i = 0, [2, new Promise(function(o) {
            var c = setInterval(function() {
              a.includeSpectrogram && (a.analyser.getFloatFrequencyData(a.freqData), a.freqData[0] === -Infinity && o({freqDataQueue: e, timeDataQueue: r}), e.push(a.freqData.slice(0, a.columnTruncateLength))), a.includeWaveform && (a.analyser.getFloatTimeDomainData(a.timeData), r.push(a.timeData.slice())), ++i === a.numFrames && (clearInterval(c), o({freqDataQueue: e, timeDataQueue: r}));
            }, a.fftSize / a.sampleRateHz * 1e3);
          })];
        });
      });
    }, t.prototype.stop = function() {
      this.isClosed || (this.isClosed = true, this.analyser.disconnect(), this.audioContext.close(), this.stream != null && this.stream.getTracks().length > 0 && this.stream.getTracks()[0].stop());
    }, t.prototype.toArray = function() {
      throw new Error("Can not convert infinite audio stream to array.");
    }, t.prototype.getSampleRate = function() {
      return this.sampleRateHz;
    }, t.prototype.flattenQueue = function(e) {
      var r = e[0].length, i = new Float32Array(e.length * r);
      return e.forEach(function(a, s) {
        return i.set(a, s * r);
      }), i;
    }, t.prototype.getTensorFromAudioDataArray = function(e, r) {
      var i = new Float32Array(Ce.util.sizeFromShape(r));
      return i.set(e, i.length - e.length), Ce.tensor(i, r);
    }, t;
  }(Rt);
  var D6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      if (i.webcamVideoElement = e, i.webcamConfig = r, i.isClosed = true, i.resize = false, i.needToResize())
        if (i.resize = true, i.cropSize = [i.webcamConfig.resizeHeight, i.webcamConfig.resizeWidth], i.cropBoxInd = Ce.tensor1d([0], "int32"), i.webcamConfig.centerCrop) {
          var a = i.webcamConfig.resizeWidth * 1 / i.webcamVideoElement.width, s = i.webcamConfig.resizeHeight * 1 / i.webcamVideoElement.height, o = (1 - a) / 2, c = (1 - s) / 2, l = o + a, u = s + c;
          i.cropBox = Ce.tensor2d([c, o, u, l], [1, 4]);
        } else
          i.cropBox = Ce.tensor2d([0, 0, 1, 1], [1, 4]);
      return i;
    }
    return t.prototype.summary = function() {
      return "webcam";
    }, t.create = function(e, r) {
      return r === void 0 && (r = {}), ce(this, void 0, void 0, function() {
        var i;
        return le(this, function(a) {
          switch (a.label) {
            case 0:
              if (Ce.env().get("IS_NODE"))
                throw new Error("tf.data.webcam is only supported in browser environment.");
              if (!e) {
                if (e = document.createElement("video"), !r.resizeWidth || !r.resizeHeight)
                  throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");
                e.width = r.resizeWidth, e.height = r.resizeHeight;
              }
              return i = new t(e, r), [4, i.start()];
            case 1:
              return a.sent(), [2, i];
          }
        });
      });
    }, t.prototype.start = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i = this;
        return le(this, function(a) {
          switch (a.label) {
            case 0:
              this.webcamConfig.facingMode && Ce.util.assert(this.webcamConfig.facingMode === "user" || this.webcamConfig.facingMode === "environment", function() {
                return "Invalid webcam facing mode: " + i.webcamConfig.facingMode + ". Please provide 'user' or 'environment'";
              }), a.label = 1;
            case 1:
              return a.trys.push([1, 3, , 4]), e = this, [4, navigator.mediaDevices.getUserMedia({video: {deviceId: this.webcamConfig.deviceId, facingMode: this.webcamConfig.facingMode ? this.webcamConfig.facingMode : "user", width: this.webcamVideoElement.width, height: this.webcamVideoElement.height}})];
            case 2:
              return e.stream = a.sent(), [3, 4];
            case 3:
              throw r = a.sent(), r.message = "Error thrown while initializing video stream: " + r.message, r;
            case 4:
              if (!this.stream)
                throw new Error("Could not obtain video from webcam.");
              try {
                this.webcamVideoElement.srcObject = this.stream;
              } catch (s) {
                console.log(s), this.webcamVideoElement.src = window.URL.createObjectURL(this.stream);
              }
              return this.webcamVideoElement.play(), this.isClosed = false, [2, new Promise(function(s) {
                i.webcamVideoElement.onloadedmetadata = function() {
                  s();
                };
              })];
          }
        });
      });
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e;
        return le(this, function(r) {
          if (this.isClosed)
            return [2, {value: null, done: true}];
          try {
            e = Ce.browser.fromPixels(this.webcamVideoElement);
          } catch (i) {
            throw new Error("Error thrown converting video to pixels: " + JSON.stringify(i));
          }
          if (this.resize)
            try {
              return [2, {value: this.cropAndResizeFrame(e), done: false}];
            } catch (i) {
              throw new Error("Error thrown cropping the video: " + i.message);
            } finally {
              e.dispose();
            }
          else
            return [2, {value: e, done: false}];
          return [2];
        });
      });
    }, t.prototype.needToResize = function() {
      return !!(this.webcamConfig.resizeWidth && this.webcamConfig.resizeHeight && (this.webcamVideoElement.width !== this.webcamConfig.resizeWidth || this.webcamVideoElement.height !== this.webcamConfig.resizeHeight));
    }, t.prototype.cropAndResizeFrame = function(e) {
      var r = this;
      return Ce.tidy(function() {
        var i = e.toFloat().expandDims(0), a;
        a = Ce.image.cropAndResize(i, r.cropBox, r.cropBoxInd, r.cropSize, "bilinear");
        var s = a.shape;
        return a.reshape(s.slice(1));
      });
    }, t.prototype.capture = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          switch (e.label) {
            case 0:
              return [4, this.next()];
            case 1:
              return [2, e.sent().value];
          }
        });
      });
    }, t.prototype.stop = function() {
      var e = this.stream.getTracks();
      e.forEach(function(r) {
        return r.stop();
      });
      try {
        this.webcamVideoElement.srcObject = null;
      } catch (r) {
        console.log(r), this.webcamVideoElement.src = null;
      }
      this.isClosed = true;
    }, t.prototype.toArray = function() {
      throw new Error("Can not convert infinite video stream to array.");
    }, t;
  }(Rt);
  var ew = function() {
    function n() {
    }
    return n;
  }();
  var tw = function(n) {
    qe(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.split = function(e) {
      return new k6(this, e);
    }, t;
  }(Rt), k6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.impl = new F6(e, r), i;
    }
    return t.prototype.summary = function() {
      return this.impl.summary();
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return [2, this.impl.next()];
        });
      });
    }, t;
  }(tw), F6 = function(n) {
    qe(t, n);
    function t(e, r) {
      var i = n.call(this) || this;
      return i.upstream = e, i.separator = r, i.carryover = "", i;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Split('" + this.separator + "')";
    }, t.prototype.pump = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i, a, s;
        return le(this, function(o) {
          switch (o.label) {
            case 0:
              return [4, this.upstream.next()];
            case 1:
              if (e = o.sent(), e.done)
                return this.carryover === "" ? [2, false] : (this.outputQueue.push(this.carryover), this.carryover = "", [2, true]);
              for (r = e.value.split(this.separator), r[0] = this.carryover + r[0], i = 0, a = r.slice(0, -1); i < a.length; i++)
                s = a[i], this.outputQueue.push(s);
              return this.carryover = r[r.length - 1], [2, true];
          }
        });
      });
    }, t;
  }(Cd);
  var U6 = function(n) {
    qe(t, n);
    function t() {
      return n !== null && n.apply(this, arguments) || this;
    }
    return t.prototype.decodeUTF8 = function() {
      return new W6(this);
    }, t;
  }(Rt), W6 = function(n) {
    qe(t, n);
    function t(e) {
      var r = n.call(this) || this;
      return r.upstream = e, r.impl = new B6(e), r;
    }
    return t.prototype.summary = function() {
      return this.impl.summary();
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return [2, this.impl.next()];
        });
      });
    }, t;
  }(tw), B6 = function(n) {
    qe(t, n);
    function t(e) {
      var r = n.call(this) || this;
      if (r.upstream = e, Ce.env().get("IS_BROWSER"))
        r.decoder = new TextDecoder("utf-8");
      else {
        var i = P1().StringDecoder;
        r.decoder = new i("utf8");
      }
      return r;
    }
    return t.prototype.summary = function() {
      return this.upstream.summary() + " -> Utf8";
    }, t.prototype.pump = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i;
        return le(this, function(a) {
          switch (a.label) {
            case 0:
              return [4, this.upstream.next()];
            case 1:
              return e = a.sent(), e.done ? [2, false] : (r = e.value, Ce.env().get("IS_BROWSER") ? i = this.decoder.decode(r, {stream: true}) : i = this.decoder.write(Buffer.from(r.buffer)), this.outputQueue.push(i), [2, true]);
          }
        });
      });
    }, t;
  }(Cd);
  var nw = function(n) {
    qe(t, n);
    function t(e, r) {
      r === void 0 && (r = {});
      var i = n.call(this) || this;
      return i.file = e, i.options = r, Ce.util.assert(e instanceof Uint8Array || (Ce.env().get("IS_BROWSER") ? e instanceof File || e instanceof Blob : false), function() {
        return "FileChunkIterator only supports File, Blob and Uint8Array right now.";
      }), i.offset = r.offset || 0, i.chunkSize = r.chunkSize || 1024 * 1024, i;
    }
    return t.prototype.summary = function() {
      return "FileChunks " + this.file;
    }, t.prototype.next = function() {
      return ce(this, void 0, void 0, function() {
        var e, r, i = this;
        return le(this, function(a) {
          switch (a.label) {
            case 0:
              return this.offset >= (this.file instanceof Uint8Array ? this.file.byteLength : this.file.size) ? [2, {value: null, done: true}] : (e = new Promise(function(s, o) {
                var c = i.offset + i.chunkSize;
                if (i.file instanceof Uint8Array)
                  s(new Uint8Array(i.file.slice(i.offset, c)));
                else {
                  var l = new FileReader();
                  l.onload = function(h) {
                    var d = l.result;
                    if (d instanceof ArrayBuffer && (d = new Uint8Array(d)), !(d instanceof Uint8Array))
                      return o(new TypeError("FileReader returned unknown type."));
                    s(d);
                  }, l.onabort = function(h) {
                    return o(new Error("Aborted"));
                  }, l.onerror = function(h) {
                    return o(new Error(h.type));
                  };
                  var u = i.file.slice(i.offset, c);
                  l.readAsArrayBuffer(u);
                }
                i.offset = c;
              }), r = {}, [4, e]);
            case 1:
              return [2, (r.value = a.sent(), r.done = false, r)];
          }
        });
      });
    }, t;
  }(U6);
  function P6(n, t) {
    return t === void 0 && (t = {}), ce(this, void 0, void 0, function() {
      var e, r, i, a, s;
      return le(this, function(o) {
        switch (o.label) {
          case 0:
            return typeof n == "string" ? e = n : (e = n.url, r = z6(n)), [4, Ce.util.fetch(e, r)];
          case 1:
            return i = o.sent(), i.ok ? (s = Uint8Array.bind, [4, i.arrayBuffer()]) : [3, 3];
          case 2:
            return a = new (s.apply(Uint8Array, [void 0, o.sent()]))(), [2, new nw(a, t)];
          case 3:
            throw new Error(i.statusText);
        }
      });
    });
  }
  var z6 = function(n) {
    var t = {method: n.method, headers: n.headers, body: n.body, mode: n.mode, credentials: n.credentials, cache: n.cache, redirect: n.redirect, referrer: n.referrer, integrity: n.integrity};
    return t;
  };
  function rw(n) {
    return typeof n == "string" && n.substr(0, 7) === "file://";
  }
  var iw = function(n) {
    qe(t, n);
    function t(e, r) {
      r === void 0 && (r = {});
      var i = n.call(this) || this;
      return i.input = e, i.options = r, i;
    }
    return t.prototype.iterator = function() {
      return ce(this, void 0, void 0, function() {
        var e;
        return le(this, function(r) {
          return rw(this.input) && Ce.env().get("IS_NODE") && (e = require("fs"), this.input = e.readFileSync(this.input.substr(7))), [2, new nw(this.input, this.options)];
        });
      });
    }, t;
  }(ew);
  var aw = function(n) {
    qe(t, n);
    function t(e, r) {
      r === void 0 && (r = {});
      var i = n.call(this) || this;
      return i.url = e, i.fileOptions = r, i;
    }
    return t.prototype.iterator = function() {
      return ce(this, void 0, void 0, function() {
        return le(this, function(e) {
          return rw(this.url) ? [2, new iw(this.url, this.fileOptions).iterator()] : [2, P6(this.url, this.fileOptions)];
        });
      });
    }, t;
  }(ew);
  function M6(n, t) {
    return t === void 0 && (t = {}), new Q1(new aw(n), t);
  }
  function H6(n) {
    var t = this, e = _d(n);
    return en(function() {
      return ce(t, void 0, void 0, function() {
        return le(this, function(r) {
          return [2, e];
        });
      });
    });
  }
  function V6(n) {
    var t = this;
    return en(function() {
      return ce(t, void 0, void 0, function() {
        var e;
        return le(this, function(r) {
          switch (r.label) {
            case 0:
              return [4, n()];
            case 1:
              return e = r.sent(), [2, _d(function() {
                return e.next();
              })];
          }
        });
      });
    });
  }
  function G6(n, t) {
    return ce(this, void 0, void 0, function() {
      return le(this, function(e) {
        return [2, D6.create(n, t)];
      });
    });
  }
  function q6(n) {
    return ce(this, void 0, void 0, function() {
      return le(this, function(t) {
        return [2, E6.create(n)];
      });
    });
  }
  var Y6 = "2.7.0";
  qt.CSVDataset = Q1;
  qt.Dataset = Xa;
  qt.FileDataSource = iw;
  qt.TextLineDataset = X1;
  qt.URLDataSource = aw;
  qt.array = C6;
  qt.csv = M6;
  qt.func = H6;
  qt.generator = V6;
  qt.microphone = q6;
  qt.version_data = Y6;
  qt.webcam = G6;
  qt.zip = R6;
});
var cw = we((ow, Od) => {
  (function(n, t, e) {
    function r(o) {
      var c = this, l = s();
      c.next = function() {
        var u = 2091639 * c.s0 + c.c * 23283064365386963e-26;
        return c.s0 = c.s1, c.s1 = c.s2, c.s2 = u - (c.c = u | 0);
      }, c.c = 1, c.s0 = l(" "), c.s1 = l(" "), c.s2 = l(" "), c.s0 -= l(o), c.s0 < 0 && (c.s0 += 1), c.s1 -= l(o), c.s1 < 0 && (c.s1 += 1), c.s2 -= l(o), c.s2 < 0 && (c.s2 += 1), l = null;
    }
    function i(o, c) {
      return c.c = o.c, c.s0 = o.s0, c.s1 = o.s1, c.s2 = o.s2, c;
    }
    function a(o, c) {
      var l = new r(o), u = c && c.state, h = l.next;
      return h.int32 = function() {
        return l.next() * 4294967296 | 0;
      }, h.double = function() {
        return h() + (h() * 2097152 | 0) * 11102230246251565e-32;
      }, h.quick = h, u && (typeof u == "object" && i(u, l), h.state = function() {
        return i(l, {});
      }), h;
    }
    function s() {
      var o = 4022871197, c = function(l) {
        l = l.toString();
        for (var u = 0; u < l.length; u++) {
          o += l.charCodeAt(u);
          var h = 0.02519603282416938 * o;
          o = h >>> 0, h -= o, h *= o, o = h >>> 0, h -= o, o += h * 4294967296;
        }
        return (o >>> 0) * 23283064365386963e-26;
      };
      return c;
    }
    t && t.exports ? t.exports = a : e && e.amd ? e(function() {
      return a;
    }) : this.alea = a;
  })(ow, typeof Od == "object" && Od, typeof define == "function" && define);
});
var uw = we((lw, Ed) => {
  (function(n, t, e) {
    function r(s) {
      var o = this, c = "";
      o.x = 0, o.y = 0, o.z = 0, o.w = 0, o.next = function() {
        var u = o.x ^ o.x << 11;
        return o.x = o.y, o.y = o.z, o.z = o.w, o.w ^= o.w >>> 19 ^ u ^ u >>> 8;
      }, s === (s | 0) ? o.x = s : c += s;
      for (var l = 0; l < c.length + 64; l++)
        o.x ^= c.charCodeAt(l) | 0, o.next();
    }
    function i(s, o) {
      return o.x = s.x, o.y = s.y, o.z = s.z, o.w = s.w, o;
    }
    function a(s, o) {
      var c = new r(s), l = o && o.state, u = function() {
        return (c.next() >>> 0) / 4294967296;
      };
      return u.double = function() {
        do
          var h = c.next() >>> 11, d = (c.next() >>> 0) / 4294967296, p = (h + d) / (1 << 21);
        while (p === 0);
        return p;
      }, u.int32 = c.next, u.quick = u, l && (typeof l == "object" && i(l, c), u.state = function() {
        return i(c, {});
      }), u;
    }
    t && t.exports ? t.exports = a : e && e.amd ? e(function() {
      return a;
    }) : this.xor128 = a;
  })(lw, typeof Ed == "object" && Ed, typeof define == "function" && define);
});
var dw = we((hw, Dd) => {
  (function(n, t, e) {
    function r(s) {
      var o = this, c = "";
      o.next = function() {
        var u = o.x ^ o.x >>> 2;
        return o.x = o.y, o.y = o.z, o.z = o.w, o.w = o.v, (o.d = o.d + 362437 | 0) + (o.v = o.v ^ o.v << 4 ^ (u ^ u << 1)) | 0;
      }, o.x = 0, o.y = 0, o.z = 0, o.w = 0, o.v = 0, s === (s | 0) ? o.x = s : c += s;
      for (var l = 0; l < c.length + 64; l++)
        o.x ^= c.charCodeAt(l) | 0, l == c.length && (o.d = o.x << 10 ^ o.x >>> 4), o.next();
    }
    function i(s, o) {
      return o.x = s.x, o.y = s.y, o.z = s.z, o.w = s.w, o.v = s.v, o.d = s.d, o;
    }
    function a(s, o) {
      var c = new r(s), l = o && o.state, u = function() {
        return (c.next() >>> 0) / 4294967296;
      };
      return u.double = function() {
        do
          var h = c.next() >>> 11, d = (c.next() >>> 0) / 4294967296, p = (h + d) / (1 << 21);
        while (p === 0);
        return p;
      }, u.int32 = c.next, u.quick = u, l && (typeof l == "object" && i(l, c), u.state = function() {
        return i(c, {});
      }), u;
    }
    t && t.exports ? t.exports = a : e && e.amd ? e(function() {
      return a;
    }) : this.xorwow = a;
  })(hw, typeof Dd == "object" && Dd, typeof define == "function" && define);
});
var fw = we((pw, kd) => {
  (function(n, t, e) {
    function r(s) {
      var o = this;
      o.next = function() {
        var l = o.x, u = o.i, h, d, p;
        return h = l[u], h ^= h >>> 7, d = h ^ h << 24, h = l[u + 1 & 7], d ^= h ^ h >>> 10, h = l[u + 3 & 7], d ^= h ^ h >>> 3, h = l[u + 4 & 7], d ^= h ^ h << 7, h = l[u + 7 & 7], h = h ^ h << 13, d ^= h ^ h << 9, l[u] = d, o.i = u + 1 & 7, d;
      };
      function c(l, u) {
        var h, d, p = [];
        if (u === (u | 0))
          d = p[0] = u;
        else
          for (u = "" + u, h = 0; h < u.length; ++h)
            p[h & 7] = p[h & 7] << 15 ^ u.charCodeAt(h) + p[h + 1 & 7] << 13;
        for (; p.length < 8; )
          p.push(0);
        for (h = 0; h < 8 && p[h] === 0; ++h)
          ;
        for (h == 8 ? d = p[7] = -1 : d = p[h], l.x = p, l.i = 0, h = 256; h > 0; --h)
          l.next();
      }
      c(o, s);
    }
    function i(s, o) {
      return o.x = s.x.slice(), o.i = s.i, o;
    }
    function a(s, o) {
      s == null && (s = +new Date());
      var c = new r(s), l = o && o.state, u = function() {
        return (c.next() >>> 0) / 4294967296;
      };
      return u.double = function() {
        do
          var h = c.next() >>> 11, d = (c.next() >>> 0) / 4294967296, p = (h + d) / (1 << 21);
        while (p === 0);
        return p;
      }, u.int32 = c.next, u.quick = u, l && (l.x && i(l, c), u.state = function() {
        return i(c, {});
      }), u;
    }
    t && t.exports ? t.exports = a : e && e.amd ? e(function() {
      return a;
    }) : this.xorshift7 = a;
  })(pw, typeof kd == "object" && kd, typeof define == "function" && define);
});
var gw = we((mw, Fd) => {
  (function(n, t, e) {
    function r(s) {
      var o = this;
      o.next = function() {
        var l = o.w, u = o.X, h = o.i, d, p;
        return o.w = l = l + 1640531527 | 0, p = u[h + 34 & 127], d = u[h = h + 1 & 127], p ^= p << 13, d ^= d << 17, p ^= p >>> 15, d ^= d >>> 12, p = u[h] = p ^ d, o.i = h, p + (l ^ l >>> 16) | 0;
      };
      function c(l, u) {
        var h, d, p, f, m, g = [], y = 128;
        for (u === (u | 0) ? (d = u, u = null) : (u = u + "\0", d = 0, y = Math.max(y, u.length)), p = 0, f = -32; f < y; ++f)
          u && (d ^= u.charCodeAt((f + 32) % u.length)), f === 0 && (m = d), d ^= d << 10, d ^= d >>> 15, d ^= d << 4, d ^= d >>> 13, f >= 0 && (m = m + 1640531527 | 0, h = g[f & 127] ^= d + m, p = h == 0 ? p + 1 : 0);
        for (p >= 128 && (g[(u && u.length || 0) & 127] = -1), p = 127, f = 4 * 128; f > 0; --f)
          d = g[p + 34 & 127], h = g[p = p + 1 & 127], d ^= d << 13, h ^= h << 17, d ^= d >>> 15, h ^= h >>> 12, g[p] = d ^ h;
        l.w = m, l.X = g, l.i = p;
      }
      c(o, s);
    }
    function i(s, o) {
      return o.i = s.i, o.w = s.w, o.X = s.X.slice(), o;
    }
    function a(s, o) {
      s == null && (s = +new Date());
      var c = new r(s), l = o && o.state, u = function() {
        return (c.next() >>> 0) / 4294967296;
      };
      return u.double = function() {
        do
          var h = c.next() >>> 11, d = (c.next() >>> 0) / 4294967296, p = (h + d) / (1 << 21);
        while (p === 0);
        return p;
      }, u.int32 = c.next, u.quick = u, l && (l.X && i(l, c), u.state = function() {
        return i(c, {});
      }), u;
    }
    t && t.exports ? t.exports = a : e && e.amd ? e(function() {
      return a;
    }) : this.xor4096 = a;
  })(mw, typeof Fd == "object" && Fd, typeof define == "function" && define);
});
var vw = we((yw, Wd) => {
  (function(n, t, e) {
    function r(s) {
      var o = this, c = "";
      o.next = function() {
        var u = o.b, h = o.c, d = o.d, p = o.a;
        return u = u << 25 ^ u >>> 7 ^ h, h = h - d | 0, d = d << 24 ^ d >>> 8 ^ p, p = p - u | 0, o.b = u = u << 20 ^ u >>> 12 ^ h, o.c = h = h - d | 0, o.d = d << 16 ^ h >>> 16 ^ p, o.a = p - u | 0;
      }, o.a = 0, o.b = 0, o.c = 2654435769 | 0, o.d = 1367130551, s === Math.floor(s) ? (o.a = s / 4294967296 | 0, o.b = s | 0) : c += s;
      for (var l = 0; l < c.length + 20; l++)
        o.b ^= c.charCodeAt(l) | 0, o.next();
    }
    function i(s, o) {
      return o.a = s.a, o.b = s.b, o.c = s.c, o.d = s.d, o;
    }
    function a(s, o) {
      var c = new r(s), l = o && o.state, u = function() {
        return (c.next() >>> 0) / 4294967296;
      };
      return u.double = function() {
        do
          var h = c.next() >>> 11, d = (c.next() >>> 0) / 4294967296, p = (h + d) / (1 << 21);
        while (p === 0);
        return p;
      }, u.int32 = c.next, u.quick = u, l && (typeof l == "object" && i(l, c), u.state = function() {
        return i(c, {});
      }), u;
    }
    t && t.exports ? t.exports = a : e && e.amd ? e(function() {
      return a;
    }) : this.tychei = a;
  })(yw, typeof Wd == "object" && Wd, typeof define == "function" && define);
});
var ww = we((TG, Go) => {
  (function(n, t) {
    var e = this, r = 256, i = 6, a = 52, s = "random", o = t.pow(r, i), c = t.pow(2, a), l = c * 2, u = r - 1, h;
    function d(b, L, x) {
      var N = [];
      L = L == true ? {entropy: true} : L || {};
      var I = g(m(L.entropy ? [b, w(n)] : b == null ? y() : b, 3), N), C = new p(N), O = function() {
        for (var D = C.g(i), F = o, k = 0; D < c; )
          D = (D + k) * r, F *= r, k = C.g(1);
        for (; D >= l; )
          D /= 2, F /= 2, k >>>= 1;
        return (D + k) / F;
      };
      return O.int32 = function() {
        return C.g(4) | 0;
      }, O.quick = function() {
        return C.g(4) / 4294967296;
      }, O.double = O, g(w(C.S), n), (L.pass || x || function(D, F, k, B) {
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============================
Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. Visit https://github.com/tensorflow/tfjs-node for more details.
============================`));
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      return this.data.get(e).values;
    }, t.prototype.bufferSync = function(e) {
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          i = r.map(function(a) {
            return S.util.decodeString(a);
          });
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          throw new Error("Failed to decode encoded string bytes into utf-8");
        }
      return S.buffer(e.shape, e.dtype, i);
    }, t.prototype.makeOutput = function(e, r, i) {
      var a = this.write(e, r, i);
      return S.engine().makeTensorFromDataId(a, r, i, this);
    }, t.prototype.disposeData = function(e) {
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        var r = this.data.get(e).complexTensorInfos;
        r != null && (this.disposeData(r.real.dataId), this.disposeData(r.imag.dataId)), this.data.delete(e);
      }
    }, t.prototype.disposeIntermediateTensorInfo = function(e) {
      var r = e.dataId;
      if (this.data.has(r)) {
        var i = this.data.get(r);
        i.refCount--, i.refCount < 1 && this.disposeData(r);
      }
    }, t.prototype.time = function(e) {
      return Lw(this, void 0, void 0, function() {
        var r, i;
        return Sw(this, function(a) {
          return r = S.util.now(), e(), i = S.util.now() - r, [2, {kernelMs: i}];
        });
      });
    }, t.prototype.memory = function() {
      return {unreliable: true, reasons: ["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."]};
    }, t.prototype.stridedSlice = function(e, r, i, a) {
      ae(e, "stridedSlice");
      var s = S.slice_util.computeOutShape(r, i, a);
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        return p === 0;
      }))
        return S.tensor([], s);
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        for (var u = o.indexToLoc(l), h = new Array(u.length), d = 0; d < h.length; d++)
          h[d] = u[d] * a[d] + r[d];
        o.set.apply(o, [c.get.apply(c, h)].concat(u));
      }
      return o.toTensor();
    }, t.prototype.diag = function(e) {
      for (var r = this.readSync(e.dataId), i = S.buffer([e.size, e.size], e.dtype), a = i.values, s = 0; s < r.length; s++)
        a[s * e.size + s] = r[s];
      return i.toTensor();
    }, t.prototype.unstack = function(e, r) {
      for (var i = e.shape[r], a = new Array(e.rank - 1), s = 0, o = 0; o < e.rank; o++)
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      l[r] = 1;
      for (var u = new Array(i), o = 0; o < u.length; o++)
        c[r] = o, u[o] = S.slice(e, c, l).reshape(a);
      return u;
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      ae(e, "reverse");
      for (var i = S.buffer(e.shape, e.dtype), a = this.bufferSync(e), s = function(c) {
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          return u[h] = e.shape[h] - 1 - u[h];
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        s(o);
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        a.push(u);
      }
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        for (var p = d * l, f = h[p], m = 0, g = 0; g < l; ++g) {
          var y = h[p + g];
          y < f && (f = y, m = g);
        }
        u[d] = m;
      }
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    }, t.prototype.argMax = function(e, r) {
      ae(e, "argMax");
      var i = [r];
      S.backend_util.assertAxesAreInnerMostDims("argMax", i, e.rank);
      for (var a = S.backend_util.computeOutAndReduceShapes(e.shape, i), s = a[0], o = a[1], c = S.zeros(s, "int32"), l = S.util.sizeFromShape(o), u = this.readSync(c.dataId), h = this.readSync(e.dataId), d = 0; d < u.length; ++d) {
        for (var p = d * l, f = h[p], m = 0, g = 0; g < l; ++g) {
          var y = h[p + g];
          y > f && (f = y, m = g);
        }
        u[d] = m;
      }
      return c;
    }, t.prototype.cumsum = function(e, r, i, a) {
      if (ae(e, "cumsum"), r !== e.rank - 1)
        throw new Error("backend.cumsum in CPU expects an inner-most axis=" + (e.rank - 1) + " " + ("but got axis=" + r));
      for (var s = S.upcastType(e.dtype, "int32"), o = S.zeros(e.shape, s), c = this.readSync(o.dataId), l = this.readSync(e.dataId), u = e.shape[e.rank - 1], h = a ? function(g, y) {
        return g + u - y - 1;
      } : function(g, y) {
        return g + y;
      }, d = 0; d < l.length; d += u)
        for (var p = 0; p < u; p++) {
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          if (p === 0)
            c[f] = i ? 0 : l[f];
          else {
            var m = h(d, p - 1);
            c[f] = i ? l[m] + c[m] : l[f] + c[m];
          }
        }
      return o;
    }, t.prototype.equal = function(e, r) {
      return ae([e, r], "equal"), this.broadcastedBinaryOp(e, r, "bool", function(i, a) {
        return i === a ? 1 : 0;
      });
    }, t.prototype.notEqual = function(e, r) {
      return ae([e, r], "notEqual"), this.broadcastedBinaryOp(e, r, "bool", function(i, a) {
        return i !== a ? 1 : 0;
      });
    }, t.prototype.less = function(e, r) {
      return ae([e, r], "less"), this.broadcastedBinaryOp(e, r, "bool", function(i, a) {
        return i < a ? 1 : 0;
      });
    }, t.prototype.lessEqual = function(e, r) {
      return ae([e, r], "lessEqual"), this.broadcastedBinaryOp(e, r, "bool", function(i, a) {
        return i <= a ? 1 : 0;
      });
    }, t.prototype.greater = function(e, r) {
      return ae([e, r], "greater"), this.broadcastedBinaryOp(e, r, "bool", function(i, a) {
        return i > a ? 1 : 0;
      });
    }, t.prototype.greaterEqual = function(e, r) {
      return ae([e, r], "greaterEqual"), this.broadcastedBinaryOp(e, r, "bool", function(i, a) {
        return i >= a ? 1 : 0;
      });
    }, t.prototype.logicalAnd = function(e, r) {
      return ae([e, r], "logicalAnd"), this.broadcastedBinaryOp(e, r, "bool", function(i, a) {
        return i && a;
      });
    }, t.prototype.logicalOr = function(e, r) {
      return ae([e, r], "logicalOr"), this.broadcastedBinaryOp(e, r, "bool", function(i, a) {
        return i || a;
      });
    }, t.prototype.select = function(e, r, i) {
      ae([e, r, i], "select");
      for (var a = this.readSync(e.dataId), s = this.readSync(r.dataId), o = this.readSync(i.dataId), c = S.zeros(r.shape, S.upcastType(r.dtype, i.dtype)), l = this.readSync(c.dataId), u = 0, h = e.rank === 0 || e.rank > 1 || r.rank === 1 ? 1 : S.util.sizeFromShape(r.shape.slice(1)), d = 0; d < a.length; d++)
        for (var p = 0; p < h; p++)
          a[d] === 1 ? l[u++] = s[d] : l[u++] = o[d];
      return c;
    }, t.prototype.where = function(e) {
      ae([e], "where");
      var r = this.readSync(e.dataId);
      return a8(e.shape, r);
    }, t.prototype.topk = function(e, r, i) {
      ae(e, "topk");
      var a = this.readSync(e.dataId);
      return i8(a, e.shape, e.dtype, r, i);
    }, t.prototype.min = function(e, r) {
      ae(e, "min"), S.backend_util.assertAxesAreInnerMostDims("min", r, e.rank);
      for (var i = S.backend_util.computeOutAndReduceShapes(e.shape, r), a = i[0], s = i[1], o = S.zeros(a, e.dtype), c = S.util.sizeFromShape(s), l = this.readSync(o.dataId), u = this.readSync(e.dataId), h = 0; h < l.length; ++h) {
        for (var d = h * c, p = u[d], f = 0; f < c; ++f) {
          var m = u[d + f];
          m < p && (p = m);
        }
        l[h] = p;
      }
      return o;
    }, t.prototype.minimum = function(e, r) {
      return ae([e, r], "minimum"), this.broadcastedBinaryOp(e, r, e.dtype, function(i, a) {
        return Math.min(i, a);
      });
    }, t.prototype.mod = function(e, r) {
      return ae([e, r], "mod"), this.broadcastedBinaryOp(e, r, e.dtype, function(i, a) {
        var s = i % a;
        return i < 0 && a < 0 || i >= 0 && a >= 0 ? s : (s + a) % a;
      });
    }, t.prototype.maximum = function(e, r) {
      return ae([e, r], "maximum"), this.broadcastedBinaryOp(e, r, e.dtype, function(i, a) {
        return Math.max(i, a);
      });
    }, t.prototype.all = function(e, r) {
      ae(e, "all"), S.backend_util.assertAxesAreInnerMostDims("all", r, e.rank);
      for (var i = S.backend_util.computeOutAndReduceShapes(e.shape, r), a = i[0], s = i[1], o = S.zeros(a, e.dtype), c = S.util.sizeFromShape(s), l = this.readSync(o.dataId), u = this.readSync(e.dataId), h = 0; h < l.length; ++h) {
        for (var d = h * c, p = u[d], f = 0; f < c; ++f) {
          var m = u[d + f];
          p = p && m;
        }
        l[h] = p;
      }
      return o;
    }, t.prototype.any = function(e, r) {
      ae(e, "any"), S.backend_util.assertAxesAreInnerMostDims("any", r, e.rank);
      for (var i = S.backend_util.computeOutAndReduceShapes(e.shape, r), a = i[0], s = i[1], o = S.zeros(a, e.dtype), c = S.util.sizeFromShape(s), l = this.readSync(o.dataId), u = this.readSync(e.dataId), h = 0; h < l.length; ++h) {
        for (var d = h * c, p = u[d], f = 0; f < c; ++f) {
          var m = u[d + f];
          p = p || m;
        }
        l[h] = p;
      }
      return o;
    }, t.prototype.squaredDifference = function(e, r) {
      return ae([e, r], "squaredDifference"), this.broadcastedBinaryOp(e, r, e.dtype, function(i, a) {
        var s = i - a;
        return s * s;
      });
    }, t.prototype.eluDer = function(e, r) {
      ae([e, r], "eluDer");
      for (var i = new Float32Array(r.size), a = this.readSync(r.dataId), s = this.readSync(e.dataId), o = 0; o < a.length; ++o) {
        var c = a[o];
        c >= 1 ? i[o] = s[o] : i[o] = s[o] * (c + 1);
      }
      return this.makeOutput(i, r.shape, "float32");
    }, t.prototype.atan2 = function(e, r) {
      return ae([e, r], "atan2"), this.broadcastedBinaryOp(e, r, e.dtype, function(i, a) {
        return Math.atan2(i, a);
      });
    }, t.prototype.tile = function(e, r) {
      return ae(e, "tile"), r8(this.bufferSync(e), r);
    }, t.prototype.gather = function(e, r, i) {
      ae([e, r], "gather");
      var a = e.shape.slice(), s = this.readSync(r.dataId);
      a[i] = s.length;
      for (var o = S.buffer(a, e.dtype), c = this.bufferSync(e), l = 0; l < o.size; ++l) {
        var u = o.indexToLoc(l), h = u.slice();
        h[i] = s[u[i]];
        var d = c.locToIndex(h);
        o.values[l] = c.values[d];
      }
      return o.toTensor();
    }, t.prototype.batchToSpaceND = function(e, r, i) {
      ae([e], "batchToSpaceND");
      var a = r.reduce(function(h, d) {
        return h * d;
      }), s = S.backend_util.getReshaped(e.shape, r, a), o = S.backend_util.getPermuted(s.length, r.length), c = S.backend_util.getReshapedPermuted(e.shape, r, a), l = S.backend_util.getSliceBeginCoords(i, r.length), u = S.backend_util.getSliceSize(c, i, r.length);
      return S.transpose(e.reshape(s), o).reshape(c).slice(l, u);
    }, t.prototype.pool3d = function(e, r, i) {
      ae(e, "pool3d");
      for (var a = r.strideDepth, s = r.strideHeight, o = r.strideWidth, c = r.dilationDepth, l = r.dilationHeight, u = r.dilationWidth, h = r.effectiveFilterDepth, d = r.effectiveFilterHeight, p = r.effectiveFilterWidth, f = r.padInfo.front, m = r.padInfo.top, g = r.padInfo.left, y = i === "max" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY, w = this.readSync(e.dataId), b = S.buffer(r.outShape, e.dtype), L = b.values, x = r.outShape[1] * r.outShape[2] * r.outShape[3] * r.outShape[4], N = r.outShape[2] * r.outShape[3] * r.outShape[4], I = r.outShape[3] * r.outShape[4], C = r.outShape[4], O = 0; O < r.batchSize; ++O)
        for (var D = O * x, F = O * e.strides[0], k = 0; k < r.inChannels; ++k)
          for (var B = 0; B < r.outDepth; ++B) {
            for (var V = B * a - f, P = V; P < 0; )
              P += c;
            for (var G = Math.min(r.inDepth, h + V), j = D + B * N, q = 0; q < r.outHeight; ++q) {
              for (var H = q * s - m, J = H; J < 0; )
                J += l;
              for (var $ = Math.min(r.inHeight, d + H), ee = j + q * I, te = 0; te < r.outWidth; ++te) {
                for (var ne = te * o - g, re = ne; re < 0; )
                  re += u;
                for (var ie = Math.min(r.inWidth, p + ne), oe = ee + te * C, se = y, me = 0, ye = 0, ve = P; ve < G; ve += c) {
                  for (var Ee = F + ve * e.strides[1], Be = J; Be < $; Be += l) {
                    for (var We = Ee + Be * e.strides[2], Ke = re; Ke < ie; Ke += u) {
                      var ze = We + Ke * e.strides[3], Ie = w[ze + k];
                      if (i === "max" && Ie > se ? se = Ie : i === "avg" && (me += Ie, ye++), isNaN(se))
                        break;
                    }
                    if (isNaN(se))
                      break;
                  }
                  if (isNaN(se))
                    break;
                }
                var ue = oe + k;
                L[ue] = i === "avg" ? me / ye : se;
              }
            }
          }
      return b.toTensor();
    }, t.prototype.avgPool3d = function(e, r) {
      return ae(e, "avgPool3d"), this.pool3d(e, r, "avg").toFloat();
    }, t.prototype.avgPool3dBackprop = function(e, r, i) {
      ae([e, r], "avgPool3dBackprop");
      for (var a = i.strideDepth, s = i.strideHeight, o = i.strideWidth, c = i.filterDepth, l = i.filterHeight, u = i.filterWidth, h = i.dilationDepth, d = i.dilationHeight, p = i.dilationWidth, f = i.effectiveFilterDepth, m = i.effectiveFilterHeight, g = i.effectiveFilterWidth, y = f - 1 - i.padInfo.front, w = g - 1 - i.padInfo.left, b = m - 1 - i.padInfo.top, L = S.buffer(r.shape, "float32"), x = 1 / (c * l * u), N = this.bufferSync(e), I = 0; I < i.batchSize; ++I)
        for (var C = 0; C < i.inChannels; ++C)
          for (var O = 0; O < i.inDepth; ++O)
            for (var D = 0; D < i.inHeight; ++D)
              for (var F = 0; F < i.inWidth; ++F) {
                for (var k = O - y, B = D - b, V = F - w, P = 0, G = 0; G < f; G += h) {
                  var j = (k + G) / a;
                  if (j < 0 || j >= i.outDepth || Math.floor(j) !== j)
                    continue;
                  for (var q = 0; q < m; q += d) {
                    var H = (B + q) / s;
                    if (H < 0 || H >= i.outHeight || Math.floor(H) !== H)
                      continue;
                    for (var J = 0; J < g; J += p) {
                      var $ = (V + J) / o;
                      if ($ < 0 || $ >= i.outWidth || Math.floor($) !== $)
                        continue;
                      var ee = N.get(I, j, H, $, C);
                      P += ee;
                    }
                  }
                }
                L.set(P * x, I, O, D, F, C);
              }
      return L.toTensor();
    }, t.prototype.maxPool3d = function(e, r) {
      return ae(e, "maxPool3d"), this.pool3d(e, r, "max").toFloat();
    }, t.prototype.maxPool3dPositions = function(e, r) {
      for (var i = S.buffer(r.outShape, "int32"), a = r.strideDepth, s = r.strideHeight, o = r.strideWidth, c = r.dilationDepth, l = r.dilationHeight, u = r.dilationWidth, h = r.effectiveFilterDepth, d = r.effectiveFilterHeight, p = r.effectiveFilterWidth, f = r.padInfo.front, m = r.padInfo.top, g = r.padInfo.left, y = this.bufferSync(e), w = 0; w < r.batchSize; ++w)
        for (var b = 0; b < r.inChannels; ++b)
          for (var L = 0; L < r.outDepth; ++L) {
            for (var x = L * a - f, N = x; N < 0; )
              N += c;
            for (var I = Math.min(r.inDepth, h + x), C = 0; C < r.outHeight; ++C) {
              for (var O = C * s - m, D = O; D < 0; )
                D += l;
              for (var F = Math.min(r.inHeight, d + O), k = 0; k < r.outWidth; ++k) {
                for (var B = k * o - g, V = B; V < 0; )
                  V += u;
                for (var P = Math.min(r.inWidth, p + B), G = Number.NEGATIVE_INFINITY, j = -1, q = N; q < I; q += c)
                  for (var H = q - x, J = D; J < F; J += l)
                    for (var $ = J - O, ee = V; ee < P; ee += u) {
                      var te = ee - B, ne = y.get(w, q, J, ee, b);
                      ne >= G && (G = ne, j = H * d * p + $ * d + te);
                    }
                i.set(j, w, L, C, k, b);
              }
            }
          }
      return i.toTensor();
    }, t.prototype.maxPool3dBackprop = function(e, r, i, a) {
      ae([r, i], "maxPool3dBackprop");
      for (var s = this.maxPool3dPositions(r, a), o = a.strideDepth, c = a.strideHeight, l = a.strideWidth, u = a.dilationDepth, h = a.dilationHeight, d = a.dilationWidth, p = a.effectiveFilterDepth, f = a.effectiveFilterHeight, m = a.effectiveFilterWidth, g = p - 1 - a.padInfo.front, y = m - 1 - a.padInfo.left, w = f - 1 - a.padInfo.top, b = S.buffer(r.shape, "float32"), L = this.bufferSync(s), x = this.bufferSync(e), N = 0; N < a.batchSize; ++N)
        for (var I = 0; I < a.inChannels; ++I)
          for (var C = 0; C < a.inDepth; ++C)
            for (var O = 0; O < a.inHeight; ++O)
              for (var D = 0; D < a.inWidth; ++D) {
                for (var F = C - g, k = O - w, B = D - y, V = 0, P = 0; P < p; P += u) {
                  var G = (F + P) / o;
                  if (G < 0 || G >= a.outDepth || Math.floor(G) !== G)
                    continue;
                  for (var j = 0; j < f; j += h) {
                    var q = (k + j) / c;
                    if (q < 0 || q >= a.outHeight || Math.floor(q) !== q)
                      continue;
                    for (var H = 0; H < m; H += d) {
                      var J = (B + H) / l;
                      if (J < 0 || J >= a.outWidth || Math.floor(J) !== J)
                        continue;
                      var $ = p * f * m - 1 - L.get(N, G, q, J, I), ee = P * f * m + j * m + H, te = $ === ee ? 1 : 0;
                      if (te === 0)
                        continue;
                      var ne = x.get(N, G, q, J, I);
                      V += ne * te;
                    }
                  }
                }
                b.set(V, N, C, O, D, I);
              }
      return b.toTensor();
    }, t.prototype.resizeBilinear = function(e, r, i, a) {
      ae(e, "resizeBilinear");
      for (var s = e.shape, o = s[0], c = s[1], l = s[2], u = s[3], h = this.readSync(e.dataId), d = new Float32Array(S.util.sizeFromShape([o, r, i, u])), p = [a && r > 1 ? c - 1 : c, a && i > 1 ? l - 1 : l], f = [a && r > 1 ? r - 1 : r, a && i > 1 ? i - 1 : i], m = 0, g = p[0] / f[0], y = p[1] / f[1], w = 0; w < o; w++)
        for (var b = 0; b < r; b++)
          for (var L = g * b, x = Math.floor(L), N = L - x, I = Math.min(c - 1, Math.ceil(L)), C = w * e.strides[0] + x * e.strides[1], O = w * e.strides[0] + I * e.strides[1], D = 0; D < i; D++)
            for (var F = y * D, k = Math.floor(F), B = F - k, V = Math.min(l - 1, Math.ceil(F)), P = C + k * e.strides[2], G = O + k * e.strides[2], j = C + V * e.strides[2], q = O + V * e.strides[2], H = 0; H < u; H++) {
              var J = h[P + H], $ = h[G + H], ee = h[j + H], te = h[q + H], ne = J + (ee - J) * B, re = $ + (te - $) * B, ie = ne + (re - ne) * N;
              d[m++] = ie;
            }
      return S.tensor(d, [o, r, i, u]);
    }, t.prototype.resizeBilinearBackprop = function(e, r, i) {
      ae([e, r], "resizeBilinearBackprop");
      for (var a = r.shape, s = a[0], o = a[1], c = a[2], l = a[3], u = e.shape, h = u[1], d = u[2], p = new Float32Array(s * o * c * l), f = [i && h > 1 ? o - 1 : o, i && d > 1 ? c - 1 : c], m = [i && h > 1 ? h - 1 : h, i && d > 1 ? d - 1 : d], g = f[0] / m[0], y = f[1] / m[1], w = this.readSync(e.dataId), b = 0, L = 0; L < s; L++)
        for (var x = L * r.strides[0], N = 0; N < h; N++)
          for (var I = N * g, C = Math.floor(I), O = Math.min(Math.ceil(I), o - 1), D = x + C * r.strides[1], F = x + O * r.strides[1], k = I - C, B = 1 - k, V = 0; V < d; V++)
            for (var P = V * y, G = Math.floor(P), j = Math.min(Math.ceil(P), c - 1), q = P - G, H = 1 - q, J = D + G * r.strides[2], $ = D + j * r.strides[2], ee = F + G * r.strides[2], te = F + j * r.strides[2], ne = B * H, re = B * q, ie = k * H, oe = k * q, se = 0; se < l; se++) {
              var me = w[b++];
              p[J + se] += me * ne, p[$ + se] += me * re, p[ee + se] += me * ie, p[te + se] += me * oe;
            }
      return S.tensor4d(p, [s, c, o, l], r.dtype);
    }, t.prototype.resizeNearestNeighbor = function(e, r, i, a) {
      ae(e, "resizeNearestNeighbor");
      for (var s = e.shape, o = s[0], c = s[1], l = s[2], u = s[3], h = this.readSync(e.dataId), d = new Float32Array(o * r * i * u), p = [a && r > 1 ? c - 1 : c, a && i > 1 ? l - 1 : l], f = [a && r > 1 ? r - 1 : r, a && i > 1 ? i - 1 : i], m = p[0] / f[0], g = p[1] / f[1], y = 0, w = 0; w < o; w++)
        for (var b = w * e.strides[0], L = 0; L < r; L++)
          for (var x = m * L, N = Math.min(c - 1, a ? Math.round(x) : Math.floor(x)), I = b + N * e.strides[1], C = 0; C < i; C++)
            for (var O = g * C, D = Math.min(l - 1, a ? Math.round(O) : Math.floor(O)), F = I + D * e.strides[2], k = 0; k < u; k++) {
              var B = h[F + k];
              d[y++] = B;
            }
      return S.tensor(d, [o, r, i, u], e.dtype);
    }, t.prototype.resizeNearestNeighborBackprop = function(e, r, i) {
      ae([e, r], "resizeNearestNeighborBackprop");
      for (var a = r.shape, s = a[0], o = a[1], c = a[2], l = a[3], u = e.shape, h = u[1], d = u[2], p = new Float32Array(s * o * c * l), f = this.readSync(e.dataId), m = [i && h > 1 ? o - 1 : o, i && d > 1 ? c - 1 : c], g = [i && h > 1 ? h - 1 : h, i && d > 1 ? d - 1 : d], y = m[0] / g[0], w = m[1] / g[1], b = 1 / y, L = 1 / w, x = Math.ceil(b) * 2 + 2, N = Math.ceil(L) * 2 + 2, I = 0; I < s; I++)
        for (var C = I * r.strides[0], O = 0; O < o; O++)
          for (var D = C + O * r.strides[1], F = Math.floor(O * b), k = Math.floor(F - x / 2), B = 0; B < c; B++)
            for (var V = D + B * r.strides[2], P = Math.floor(B * L), G = Math.floor(P - N / 2), j = 0; j < l; j++) {
              for (var q = 0, H = 0; H < x; H++) {
                var J = H + k;
                if (J < 0 || J >= h)
                  continue;
                var $ = C + J * e.strides[1], ee = J * y, te = Math.min(o - 1, i ? Math.round(ee) : Math.floor(ee));
                if (O !== te)
                  continue;
                for (var ne = 0; ne < N; ne++) {
                  var re = ne + G;
                  if (re < 0 || re >= d)
                    continue;
                  var ie = $ + re * e.strides[2], oe = re * w, se = Math.min(c - 1, i ? Math.round(oe) : Math.floor(oe));
                  B === se && (q += f[ie + j]);
                }
              }
              p[V + j] = q;
            }
      return S.tensor4d(p, r.shape, r.dtype);
    }, t.prototype.localResponseNormalization4D = function(e, r, i, a, s) {
      ae(e, "localResponseNormalization4D");
      var o = e.shape[3], c = o - 1, l = this.readSync(e.dataId), u = e.size, h = new Float32Array(u);
      function d(g) {
        for (var y = g % o, w = g - y + Math.max(0, y - r), b = g - y + Math.min(y + r, c), L = 0; w <= b; w++) {
          var x = l[w];
          L += x * x;
        }
        return L;
      }
      for (var p = 0; p < u; p++) {
        var f = d(p), m = l[p] * Math.pow(i + a * f, -s);
        h[p] = m;
      }
      return S.tensor4d(h, e.shape);
    }, t.prototype.LRNGrad = function(e, r, i, a, s, o, c) {
      ae(e, "LRNGrad");
      for (var l = e.shape[3], u = this.readSync(e.dataId), h = this.readSync(r.dataId), d = this.readSync(i.dataId), p = new Float32Array(e.size), f = e.size, m = 0; m < f; m++) {
        for (var g = m % l, y = m - g + Math.max(0, g - a), w = m - g + Math.min(l, g + a + 1), b = 0, L = y; L < w; L++)
          b += Math.pow(h[L], 2);
        b = o * b + s;
        for (var L = y; L < w; L++) {
          var x = -2 * o * c * h[L] * d[m] / b;
          m === L && (x += Math.pow(b, -c)), x *= u[m], p[L] += x;
        }
      }
      return S.tensor4d(p, e.shape);
    }, t.prototype.multinomial = function(e, r, i, a) {
      ae(e, "multinomial");
      for (var s = r ? e : S.softmax(e), o = s.shape[0], c = s.shape[1], l = S.zeros([o, i], "int32"), u = this.readSync(l.dataId), h = this.readSync(s.dataId), d = 0; d < o; ++d) {
        var p = d * c, f = new Float32Array(c - 1);
        f[0] = h[p];
        for (var m = 1; m < f.length; ++m)
          f[m] = f[m - 1] + h[p + m];
        for (var g = Q6.alea(a.toString()), y = d * i, w = 0; w < i; ++w) {
          var b = g();
          u[y + w] = f.length;
          for (var L = 0; L < f.length; L++)
            if (b < f[L]) {
              u[y + w] = L;
              break;
            }
        }
      }
      return l;
    }, t.prototype.oneHot = function(e, r, i, a) {
      ae(e, "oneHot");
      var s = new Float32Array(e.size * r);
      s.fill(a);
      for (var o = this.readSync(e.dataId), c = 0; c < e.size; ++c)
        o[c] >= 0 && o[c] < r && (s[c * r + o[c]] = i);
      return S.tensor2d(s, [e.size, r], "int32");
    }, t.prototype.nonMaxSuppression = function(e, r, i, a, s) {
      ae(e, "nonMaxSuppression");
      var o = this.readSync(e.dataId), c = this.readSync(r.dataId);
      return t8(o, c, i, a, s);
    }, t.prototype.depthToSpace = function(e, r, i) {
      S.util.assert(i === "NHWC", function() {
        return "Only NHWC dataFormat supported on CPU for depthToSpace. Got " + i;
      }), S.util.assert(r > 1, function() {
        return "blockSize should be > 1 for depthToSpace, but was: " + r;
      });
      for (var a = e.shape[0], s = e.shape[1], o = e.shape[2], c = e.shape[3], l = s * r, u = o * r, h = c / (r * r), d = this.readSync(e.dataId), p = new Float32Array(a * l * u * h), f = 0, m = 0; m < a; ++m)
        for (var g = 0; g < l; ++g)
          for (var y = Math.floor(g / r), w = g % r, b = 0; b < u; ++b)
            for (var L = Math.floor(b / r), x = b % r, N = (w * r + x) * h, I = 0; I < h; ++I) {
              var C = I + N, O = C + c * (L + o * (y + s * m));
              p[f++] = d[O];
            }
      return S.tensor4d(p, [a, l, u, h]);
    }, t.prototype.broadcastedBinaryOp = function(e, r, i, a) {
      var s = S.backend_util.assertAndGetBroadcastShape(e.shape, r.shape), o = S.buffer(s, i), c = this.readSync(e.dataId), l = this.readSync(r.dataId), u = S.backend_util.getBroadcastDims(e.shape, s), h = S.backend_util.getBroadcastDims(r.shape, s), d = o.values;
      if (u.length + h.length === 0)
        for (var p = 0; p < d.length; ++p)
          d[p] = a(c[p % c.length], l[p % l.length]);
      else
        for (var f = this.bufferSync(e), m = this.bufferSync(r), g = function(y) {
          var w = o.indexToLoc(y), b = w.slice(-e.rank);
          u.forEach(function(I) {
            return b[I] = 0;
          });
          var L = f.locToIndex(b), x = w.slice(-r.rank);
          h.forEach(function(I) {
            return x[I] = 0;
          });
          var N = m.locToIndex(x);
          d[y] = a(c[L], l[N]);
        }, p = 0; p < d.length; ++p)
          g(p);
      return o.toTensor();
    }, t.prototype.split = function(e, r, i) {
      return n8(e, r, i);
    }, t.prototype.dispose = function() {
    }, t.prototype.floatPrecision = function() {
      return 32;
    }, t.prototype.epsilon = function() {
      return n.prototype.epsilon.call(this);
    }, t.prototype.cropAndResize = function(e, r, i, a, s, o) {
      for (var c = e.shape, l = c[0], u = c[1], h = c[2], d = c[3], p = r.shape[0], f = a[0], m = a[1], g = S.buffer([p, f, m, d], "float32"), y = this.readSync(r.dataId), w = this.readSync(i.dataId), b = this.readSync(e.dataId), L = e.strides, x = g.strides, N = 0; N < p; N++) {
        var I = N * 4, C = y[I], O = y[I + 1], D = y[I + 2], F = y[I + 3], k = w[N];
        if (k >= l)
          continue;
        for (var B = f > 1 ? (D - C) * (u - 1) / (f - 1) : 0, V = m > 1 ? (F - O) * (h - 1) / (m - 1) : 0, P = 0; P < f; P++) {
          var G = f > 1 ? C * (u - 1) + P * B : 0.5 * (C + D) * (u - 1);
          if (G < 0 || G > u - 1) {
            for (var j = 0; j < m; j++)
              for (var q = 0; q < d; q++) {
                var H = q + j * x[2] + P * x[1] + N * x[0];
                g.values[H] = o;
              }
            continue;
          }
          if (s === "bilinear")
            for (var J = Math.floor(G), $ = Math.ceil(G), ee = G - J, j = 0; j < m; j++) {
              var te = m > 1 ? O * (h - 1) + j * V : 0.5 * (O + F) * (h - 1);
              if (te < 0 || te > h - 1) {
                for (var q = 0; q < d; q++) {
                  var H = q + j * x[2] + P * x[1] + N * x[0];
                  g.values[H] = o;
                }
                continue;
              }
              for (var ne = Math.floor(te), re = Math.ceil(te), ie = te - ne, q = 0; q < d; q++) {
                var H = q + ne * L[2] + J * L[1] + k * L[0], oe = b[H];
                H = q + re * L[2] + J * L[1] + k * L[0];
                var se = b[H];
                H = q + ne * L[2] + $ * L[1] + k * L[0];
                var me = b[H];
                H = q + re * L[2] + $ * L[1] + k * L[0];
                var ye = b[H], ve = oe + (se - oe) * ie, Ee = me + (ye - me) * ie;
                H = q + j * x[2] + P * x[1] + N * x[0], g.values[H] = ve + (Ee - ve) * ee;
              }
            }
          else
            for (var j = 0; j < m; ++j) {
              var te = m > 1 ? O * (h - 1) + j * V : 0.5 * (O + F) * (h - 1);
              if (te < 0 || te > h - 1) {
                for (var q = 0; q < d; q++) {
                  var H = q + j * x[2] + P * x[1] + N * x[0];
                  g.values[H] = o;
                }
                continue;
              }
              for (var Be = Math.round(te), We = Math.round(G), q = 0; q < d; q++) {
                var Ke = q + Be * L[2] + We * L[1] + k * L[0], ze = q + j * x[2] + P * x[1] + N * x[0];
                g.values[ze] = b[Ke];
              }
            }
        }
      }
      return g.toTensor();
    }, t.prototype.sparseToDense = function(e, r, i, a) {
      var s = S.backend_util.calculateShapes(r, e, i), o = s.sliceRank, c = s.numUpdates, l = s.sliceSize, u = s.strides, h = s.outputSize, d = false;
      return this.scatter(e, r, i, h, l, c, o, u, a, d);
    }, t.prototype.gatherND = function(e, r) {
      var i = r.shape, a = i[i.length - 1], s = S.backend_util.prepareAndValidate(e, r), o = s[0], c = s[1], l = s[2], u = s[3];
      if (c === 0)
        return S.tensor([], o, e.dtype);
      for (var h = new S.TensorBuffer([c, l], e.dtype), d = this.readSync(r.dataId), p = this.readSync(e.dataId), f = 0; f < c; f++) {
        for (var m = [], g = 0, y = 0; y < a; y++) {
          var w = d[f * a + y];
          g += w * u[y], m.push(w);
        }
        if (g < 0 || g >= e.size / l)
          throw new Error("Invalid indices: " + m + " does not index into " + e.shape);
        for (var b = 0; b < l; b++)
          h.values[f * l + b] = p[g * l + b];
      }
      return h.toTensor().reshape(o);
    }, t.prototype.scatterND = function(e, r, i) {
      var a = S.backend_util.calculateShapes(r, e, i), s = a.sliceRank, o = a.numUpdates, c = a.sliceSize, l = a.strides, u = a.outputSize, h = S.scalar(0), d = true;
      return this.scatter(e, r, i, u, c, o, s, l, h, d);
    }, t.prototype.onesLike = function(e) {
      if (e.dtype === "string")
        throw new Error("onesLike is not supported for string tensors");
      return S.fill(e.shape, 1, e.dtype);
    }, t.prototype.zerosLike = function(e) {
      var r = S.util.getArrayFromDType(e.dtype, S.util.sizeFromShape(e.shape));
      return this.makeOutput(r, e.shape, e.dtype);
    }, t.prototype.linspace = function(e, r, i) {
      return S.backend_util.linspaceImpl(e, r, i);
    }, t.prototype.scatter = function(e, r, i, a, s, o, c, l, u, h) {
      var d = [a / s, s], p = this.readSync(e.dataId), f = this.readSync(r.dataId);
      if (a === 0)
        return S.tensor([], i, r.dtype);
      var m = new S.TensorBuffer(d, r.dtype);
      m.values.fill(this.readSync(u.dataId)[0]);
      for (var g = 0; g < o; g++) {
        for (var y = [], w = 0, b = 0; b < c; b++) {
          var L = p[g * c + b];
          y.push(L), w += L * l[b];
        }
        if (w < 0 || w >= a / s)
          throw new Error("Invalid indices: " + y + " does not index into " + i);
        for (var x = 0; x < s; x++)
          h ? m.values[w * s + x] += f[g * s + x] : m.values[w * s + x] = r.rank === 0 ? f[0] : f[g * s + x];
      }
      return m.toTensor().reshape(i);
    }, t;
  }(S.KernelBackend);
  function Aw(n) {
    for (var t = new Float32Array(n.length), e = 0; e < n.length; ++e)
      t[e] = Math.abs(n[e]);
    return t;
  }
  var s8 = function(n) {
    var t = n.inputs.x, e = n.backend, r = new Float32Array(S.util.sizeFromShape(t.shape));
    if (t.dtype !== "complex64") {
      var i = e.data.get(t.dataId).values;
      r = Aw(i);
    } else
      for (var a = e.data.get(t.dataId), s = a.complexTensorInfos.real, o = a.complexTensorInfos.imag, c = e.data.get(s.dataId).values, l = e.data.get(o.dataId).values, u = 0; u < c.length; u++) {
        var h = c[u], d = l[u];
        r[u] = Math.hypot(h, d);
      }
    return e.makeOutput(r, t.shape, "float32");
  }, o8 = {kernelName: S.Abs, backendName: "cpu", kernelFunc: s8};
  function Rr(n) {
    return function(t, e, r, i, a) {
      var s = S.backend_util.assertAndGetBroadcastShape(t, e), o = s.length, c = S.util.computeStrides(s), l = S.util.sizeFromShape(s), u = S.util.getTypedArrayFromDType(a, l), h = t.length, d = e.length, p = S.util.computeStrides(t), f = S.util.computeStrides(e), m = S.backend_util.getBroadcastDims(t, s), g = S.backend_util.getBroadcastDims(e, s);
      if (m.length + g.length === 0)
        for (var y = 0; y < u.length; ++y)
          u[y] = n(r[y % r.length], i[y % i.length]);
      else
        for (var w = function(b) {
          var L = S.util.indexToLoc(b, o, c), x = L.slice(-h);
          m.forEach(function(O) {
            return x[O] = 0;
          });
          var N = S.util.locToIndex(x, h, p), I = L.slice(-d);
          g.forEach(function(O) {
            return I[O] = 0;
          });
          var C = S.util.locToIndex(I, d, f);
          u[b] = n(r[N], i[C]);
        }, y = 0; y < u.length; ++y)
          w(y);
      return [u, s];
    };
  }
  function Tn(n) {
    var t = n.inputs, e = n.backend, r = t.real, i = t.imag, a = e.data.get(r.dataId).values, s = e.data.get(i.dataId).values, o = e.makeTensorInfo(r.shape, "complex64"), c = e.data.get(o.dataId);
    return c.complexTensorInfos = {real: e.makeTensorInfo(r.shape, "float32", a), imag: e.makeTensorInfo(i.shape, "float32", s)}, o;
  }
  var c8 = {kernelName: S.Complex, backendName: "cpu", kernelFunc: Tn};
  function hi(n) {
    var t = n.inputs, e = n.backend, r = t.x;
    return e.incRef(r.dataId), {dataId: r.dataId, shape: r.shape, dtype: r.dtype};
  }
  var l8 = {kernelName: S.Identity, backendName: "cpu", kernelFunc: hi};
  function Qa(n) {
    var t = n.inputs, e = n.backend, r = t.input, i = e.data.get(r.dataId).complexTensorInfos.real, a = e.data.get(i.dataId).values;
    return e.makeTensorInfo(i.shape, i.dtype, a);
  }
  var u8 = {kernelName: S.Real, backendName: "cpu", kernelFunc: Qa};
  function es(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.dtype;
    if (a === "complex64") {
      if (i.dtype === "complex64")
        return hi({inputs: {x: i}, backend: e});
      var s = S.zeros(i.shape), o = es({inputs: {x: i}, backend: e, attrs: {dtype: "float32"}}), c = Tn({inputs: {real: o, imag: s}, backend: e});
      return s.dispose(), e.disposeIntermediateTensorInfo(o), c;
    }
    if (i.dtype === "complex64") {
      var l = Qa({inputs: {input: i}, backend: e}), c = es({inputs: {x: l}, backend: e, attrs: {dtype: a}});
      return e.disposeIntermediateTensorInfo(l), c;
    }
    if (!S.util.hasEncodingLoss(i.dtype, a)) {
      var c = hi({inputs: {x: i}, backend: e});
      return {dataId: c.dataId, shape: c.shape, dtype: a};
    }
    if (a === "int32") {
      var u = e.data.get(i.dataId).values, h = Int32Array.from(u);
      return e.makeTensorInfo(i.shape, "int32", h);
    }
    if (a === "bool") {
      var d = e.data.get(i.dataId).values, p = S.util.toTypedArray([0], i.dtype), f = Rr(function(y, w) {
        return y !== w ? 1 : 0;
      })(i.shape, [], d, p, "bool"), m = f[0], g = f[1];
      return e.makeTensorInfo(g, "bool", m);
    }
    throw new Error("Error in Cast: failed to cast " + i.dtype + " to " + a);
  }
  var h8 = {kernelName: S.Cast, backendName: "cpu", kernelFunc: es};
  function Ji(n, t, e, r) {
    return e == null ? function(i) {
      var a = i.inputs, s = i.backend, o = a, c = o.a, l = o.b, u = s;
      ae([c, l], n);
      var h = u.data.get(c.dataId).values, d = u.data.get(l.dataId).values, p = r || c.dtype, f = t(c.shape, l.shape, h, d, p), m = f[0], g = f[1];
      return u.makeTensorInfo(g, p, m);
    } : function(i) {
      var a = i.inputs, s = i.backend, o = a, c = o.a, l = o.b, u = s;
      if (c.dtype === "complex64" || l.dtype === "complex64") {
        var h = es({inputs: {x: c}, backend: u, attrs: {dtype: "complex64"}}), d = u.data.get(h.dataId), p = d.complexTensorInfos.real, f = d.complexTensorInfos.imag, m = u.data.get(p.dataId).values, g = u.data.get(f.dataId).values, y = es({inputs: {x: l}, backend: u, attrs: {dtype: "complex64"}}), w = u.data.get(y.dataId), b = w.complexTensorInfos.real, L = w.complexTensorInfos.imag, x = u.data.get(b.dataId).values, N = u.data.get(L.dataId).values, I = e(c.shape, l.shape, m, g, x, N), C = I[0], O = I[1], D = I[2], F = u.makeTensorInfo(D, "float32", C), k = u.makeTensorInfo(D, "float32", O), B = Tn({inputs: {real: F, imag: k}, backend: u});
        return u.disposeIntermediateTensorInfo(h), u.disposeIntermediateTensorInfo(y), u.disposeIntermediateTensorInfo(F), u.disposeIntermediateTensorInfo(k), B;
      } else {
        var V = u.data.get(c.dataId).values, P = u.data.get(l.dataId).values, G = r || c.dtype, j = t(c.shape, l.shape, V, P, G), q = j[0], D = j[1];
        return u.makeTensorInfo(D, G, q);
      }
    };
  }
  function Bd(n) {
    return function(t, e, r, i, a, s) {
      var o = S.backend_util.assertAndGetBroadcastShape(t, e), c = S.util.sizeFromShape(o), l = o.length, u = S.util.computeStrides(o), h = S.util.getTypedArrayFromDType("float32", c), d = S.util.getTypedArrayFromDType("float32", c), p = S.backend_util.getBroadcastDims(t, o), f = S.backend_util.getBroadcastDims(e, o), m = S.backend_util.mergeRealAndImagArrays(r, i), g = S.backend_util.mergeRealAndImagArrays(a, s), y = t.length, w = S.util.computeStrides(t), b = e.length, L = S.util.computeStrides(e);
      if (p.length + f.length === 0)
        for (var x = 0; x < h.length; x++) {
          var N = x % m.length, I = x % g.length, C = n(m[N * 2], m[N * 2 + 1], g[I * 2], g[I * 2 + 1]);
          h[x] = C.real, d[x] = C.imag;
        }
      else
        for (var O = function(D) {
          var F = S.util.indexToLoc(D, l, u), k = F.slice(-y);
          p.forEach(function(j) {
            return k[j] = 0;
          });
          var B = S.util.locToIndex(k, y, w), V = F.slice(-b);
          f.forEach(function(j) {
            return V[j] = 0;
          });
          var P = S.util.locToIndex(V, b, L), G = n(m[B * 2], m[B * 2 + 1], g[P * 2], g[P * 2 + 1]);
          h[D] = G.real, d[D] = G.imag;
        }, x = 0; x < h.length; x++)
          O(x);
      return [h, d, o];
    };
  }
  var Tw = Rr(function(n, t) {
    return n + t;
  }), d8 = Bd(function(n, t, e, r) {
    return {real: n + e, imag: t + r};
  }), ts = Ji(S.Add, Tw, d8), p8 = {kernelName: S.Add, backendName: "cpu", kernelFunc: ts};
  function Zi(n) {
    return function(t, e, r) {
      for (var i = S.util.getTypedArrayFromDType(e, t.length), a = 0; a < t.length; ++a)
        i[a] = n(t[a], r);
      return i;
    };
  }
  function je(n, t, e) {
    return function(r) {
      var i = r.inputs, a = r.attrs, s = r.backend, o = i.x;
      if (ae(o, n), o.dtype === "string" || e === "string")
        throw new Error("unaryKernelFunc does not support string input/output");
      for (var c = s, l = c.data.get(o.dataId).values, u = S.util.sizeFromShape(o.shape), h = e || o.dtype, d = S.util.getArrayFromDType(h, u), p = 0; p < u; ++p)
        d[p] = t(l[p], a);
      return c.makeTensorInfo(o.shape, h, d);
    };
  }
  function Qi(n, t, e) {
    return function(r) {
      var i = r.inputs, a = r.attrs, s = r.backend, o = i.x;
      if (ae(o, n), o.dtype === "string" || e === "string")
        throw new Error("unaryKernelFunc does not support string input/output");
      var c = s, l = c.data.get(o.dataId).values, u = e || o.dtype, h = t(l, u, a);
      return c.makeTensorInfo(o.shape, u, h);
    };
  }
  var Nw = Zi(function(n) {
    return Math.ceil(n);
  }), f8 = Qi(S.Ceil, Nw), m8 = {kernelName: S.Ceil, backendName: "cpu", kernelFunc: f8};
  var _w = Zi(function(n) {
    return Math.exp(n);
  }), g8 = Qi(S.Exp, _w), y8 = {kernelName: S.Exp, backendName: "cpu", kernelFunc: g8};
  var Cw = Zi(function(n) {
    return Math.expm1(n);
  }), v8 = Qi(S.Expm1, Cw), w8 = {kernelName: S.Expm1, backendName: "cpu", kernelFunc: v8};
  var Rw = Zi(function(n) {
    return Math.floor(n);
  }), b8 = Qi(S.Floor, Rw), x8 = {kernelName: S.Floor, backendName: "cpu", kernelFunc: b8};
  var Ow = Zi(function(n) {
    return Math.log(n);
  }), L8 = Qi(S.Log, Ow), S8 = {kernelName: S.Log, backendName: "cpu", kernelFunc: L8};
  function Ew(n, t, e, r) {
    for (var i = S.util.getTypedArrayFromDType(r, S.util.sizeFromShape(e)), a = 0; a < i.length; ++a) {
      for (var s = a * t, o = n[s], c = 0; c < t; ++c) {
        var l = n[s + c];
        l > o && (o = l);
      }
      i[a] = o;
    }
    return i;
  }
  var Dw = Rr(function(n, t) {
    return n * t;
  }), I8 = Bd(function(n, t, e, r) {
    return {real: n * e - t * r, imag: n * r + t * e};
  }), kw = Ji(S.Multiply, Dw, I8), A8 = {kernelName: S.Multiply, backendName: "cpu", kernelFunc: kw};
  var Fw = Rr(function(n, t) {
    return n !== t ? 1 : 0;
  }), T8 = Ji(S.NotEqual, Fw, null, "bool"), N8 = {kernelName: S.NotEqual, backendName: "cpu", kernelFunc: T8};
  var Ww = Zi(function(n) {
    return 1 / Math.sqrt(n);
  }), _8 = Qi(S.Rsqrt, Ww), C8 = {kernelName: S.Rsqrt, backendName: "cpu", kernelFunc: _8};
  function Uw(n, t, e, r, i) {
    var a = S.slice_util.isSliceContinous(r, t, e), s = S.util.sizeFromShape(e), o = S.util.computeStrides(r);
    if (a) {
      var c = S.slice_util.computeFlatOffset(t, o);
      return n.subarray(c, c + s);
    }
    for (var l = S.util.getTypedArrayFromDType(i, s), u = 0; u < s; ++u) {
      var h = e.length, d = S.util.computeStrides(e), p = S.util.indexToLoc(u, h, d), f = p.map(function(g, y) {
        return g + t[y];
      }), m = S.util.locToIndex(f, r.length, o);
      l[u] = n[m];
    }
    return l;
  }
  function zd(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.begin, s = r.size;
    ae(i, "slice");
    var o = S.slice_util.parseSliceParams(i, a, s), c = o[0], l = o[1];
    S.slice_util.assertParamsValid(i, c, l);
    var u = e.data.get(i.dataId).values, h = Uw(u, c, l, i.shape, i.dtype);
    return e.makeTensorInfo(l, i.dtype, h);
  }
  var R8 = {kernelName: S.Slice, backendName: "cpu", kernelFunc: zd};
  var Bw = Rr(function(n, t) {
    var e = n - t;
    return e * e;
  }), O8 = Ji(S.SquaredDifference, Bw), E8 = {kernelName: S.SquaredDifference, backendName: "cpu", kernelFunc: O8};
  var zw = Rr(function(n, t) {
    return n - t;
  }), D8 = Bd(function(n, t, e, r) {
    return {real: n - e, imag: t - r};
  }), Pw = Ji(S.Sub, zw, D8), k8 = {kernelName: S.Sub, backendName: "cpu", kernelFunc: Pw};
  function Pd(n, t, e, r, i) {
    for (var a = t.length, s = S.util.sizeFromShape(t), o = S.util.computeStrides(t), c = S.util.computeStrides(i), l = S.util.getTypedArrayFromDType(e, S.util.sizeFromShape(i)), u = 0; u < s; ++u) {
      for (var h = S.util.indexToLoc(u, a, o), d = new Array(h.length), p = 0; p < d.length; p++)
        d[p] = h[r[p]];
      var f = S.util.locToIndex(d, a, c);
      l[f] = n[u];
    }
    return l;
  }
  function Mw(n, t, e, r) {
    for (var i = S.util.parseAxisParam(t, e)[0], a = [1, e[0], 1], s = 0; s < i; s++)
      a[0] *= e[s];
    a[1] = e[i];
    for (var s = i + 1; s < e.length; s++)
      a[2] *= e[s];
    for (var o = {}, c = new Int32Array(e[i]), l = new S.TensorBuffer(a, r, n), u = [], h = a[0] === 1 && a[2] === 1, s = 0; s < e[i]; s++) {
      var d = void 0;
      if (h)
        d = n[s].toString();
      else {
        for (var p = [], f = 0; f < a[0]; f++)
          for (var m = 0; m < a[2]; m++)
            p.push(l.get(f, s, m));
        d = p.join(",");
      }
      if (o[d] !== void 0)
        c[s] = o[d];
      else {
        var g = Object.keys(o).length;
        o[d] = g, c[s] = g, u.push(s);
      }
    }
    var y = a.slice();
    y[1] = Object.keys(o).length;
    var w = new S.TensorBuffer(y, r);
    u.forEach(function(L, x) {
      for (var N = 0; N < a[0]; N++)
        for (var I = 0; I < a[2]; I++)
          w.set(l.get(N, L, I), N, x, I);
    });
    var b = e.slice();
    return b[i] = y[1], {outputValues: w.values, outputShape: b, indices: c};
  }
  var F8 = {__proto__: null, simpleAbsImpl: Aw, addImpl: Tw, ceilImpl: Nw, expImpl: _w, expm1Impl: Cw, floorImpl: Rw, logImpl: Ow, maxImpl: Ew, multiplyImpl: Dw, notEqualImpl: Fw, rsqrtImpl: Ww, sliceImpl: Uw, squaredDifferenceImpl: Bw, subImpl: zw, transposeImpl: Pd, uniqueImpl: Mw};
  var W8 = "2.7.0";
  S.registerBackend("cpu", function() {
    return new Iw();
  }, 1);
  var Hw = je(S.Elu, function(n) {
    return n >= 0 ? n : Math.exp(n) - 1;
  }), U8 = {kernelName: S.Elu, backendName: "cpu", kernelFunc: Hw};
  var B8 = Rr(function(n, t) {
    return n < 0 ? t * n : n;
  });
  function Vw(n) {
    var t = n.inputs, e = n.backend, r = t.x, i = t.alpha;
    ae([r, i], "prelu");
    var a = e.data.get(r.dataId).values, s = e.data.get(i.dataId).values, o = B8(r.shape, i.shape, a, s, r.dtype), c = o[0], l = o[1];
    return e.makeTensorInfo(l, r.dtype, c);
  }
  var z8 = {kernelName: S.Prelu, backendName: "cpu", kernelFunc: Vw};
  var Gw = je(S.Relu, function(n) {
    return Math.max(0, n);
  }), P8 = {kernelName: S.Relu, backendName: "cpu", kernelFunc: Gw};
  var qw = je(S.Relu6, function(n) {
    return Math.min(Math.max(0, n), 6);
  }), M8 = {kernelName: S.Relu6, backendName: "cpu", kernelFunc: qw};
  function Md(n, t, e, r) {
    if (e === "linear")
      return hi({inputs: {x: t}, backend: n});
    if (e === "relu")
      return Gw({inputs: {x: t}, backend: n});
    if (e === "elu")
      return Hw({inputs: {x: t}, backend: n});
    if (e === "relu6")
      return qw({inputs: {x: t}, backend: n});
    if (e === "prelu")
      return Vw({inputs: {x: t, alpha: r}, backend: n});
    throw new Error("Activation " + e + " has not been implemented for the CPU backend.");
  }
  function zn(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.shape, s = S.util.sizeFromShape(i.shape), o = S.util.inferFromImplicitShape(a, s), c = S.util.sizeFromShape(o);
    S.util.assert(s === c, function() {
      return "The new shape (" + o + ") has " + c + " elements and the old " + ("shape (" + i.shape + ") has " + s + " elements. The new shape and old ") + "shape must have the same number of elements.";
    }), e.incRef(i.dataId);
    var l = e.data.get(i.dataId);
    if (l.complexTensorInfos != null) {
      var u = l.complexTensorInfos.real, h = l.complexTensorInfos.imag;
      u.shape = o, h.shape = o;
    }
    return {dataId: i.dataId, shape: o, dtype: i.dtype};
  }
  var H8 = {kernelName: S.Reshape, backendName: "cpu", kernelFunc: zn};
  function Yw(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.a, a = t.b, s = r.transposeA, o = r.transposeB;
    ae([i, a], "matMul");
    var c = i.shape.length, l = a.shape.length, u = s ? i.shape[c - 2] : i.shape[c - 1], h = o ? a.shape[l - 1] : a.shape[l - 2], d = s ? i.shape[c - 1] : i.shape[c - 2], p = o ? a.shape[l - 2] : a.shape[l - 1], f = i.shape.slice(0, -2), m = a.shape.slice(0, -2), g = S.util.sizeFromShape(f), y = S.util.sizeFromShape(m), w = g === y || g === 1 || y === 1;
    S.util.assert(c >= 2 && l >= 2 && w, function() {
      return "Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input " + ("batch dimensions of (" + f + ") and (" + m + ").");
    });
    var b = g > y ? i.shape.slice(0, -2) : a.shape.slice(0, -2), L = b.concat([d, p]);
    S.util.assert(u === h, function() {
      return "Error in matMul: inner shapes (" + u + ") and (" + (h + ") of Tensors with shapes " + i.shape + " and ") + (a.shape + " and transposeA=" + s) + (" and transposeB=" + o + " must match.");
    });
    for (var x = s ? [g, u, d] : [g, d, u], N = o ? [y, p, h] : [y, h, p], I = zn({inputs: {x: i}, backend: e, attrs: {shape: x}}), C = zn({inputs: {x: a}, backend: e, attrs: {shape: N}}), O = s ? I.shape[1] : I.shape[2], D = s ? I.shape[2] : I.shape[1], F = o ? C.shape[1] : C.shape[2], k = Math.max(g, y), B = e.data.get(I.dataId).values, V = e.data.get(C.dataId).values, P = S.util.computeStrides(I.shape), G = S.util.computeStrides(C.shape), j = s ? [P[0], 1, P[1]] : [P[0], P[1], 1], q = j[0], H = j[1], J = j[2], $ = o ? [1, G[1], G[0]] : [G[1], 1, G[0]], ee = $[0], te = $[1], ne = $[2], re = D * F, ie = S.buffer([k, D, F], I.dtype), oe = ie.values, se = e.blockSize, me = 0; me < k; me++)
      for (var ye = 0; ye < D; ye += se)
        for (var ve = 0; ve < F; ve += se)
          for (var Ee = 0; Ee < O; Ee += se)
            for (var Be = Math.min(ye + se, D), We = Math.min(ve + se, F), Ke = Math.min(Ee + se, O), ze = ye; ze < Be; ze++)
              for (var Ie = ve; Ie < We; Ie++) {
                for (var ue = 0, Qe = Ee; Qe < Ke; Qe++) {
                  var ft = Math.min(me, g - 1) * q, He = Math.min(me, y - 1) * ne, Ot = B[ft + ze * H + Qe * J], ht = V[Qe * ee + Ie * te + He];
                  ue += Ot * ht;
                }
                oe[me * re + (ze * F + Ie)] += ue;
              }
    return e.disposeIntermediateTensorInfo(I), e.disposeIntermediateTensorInfo(C), e.makeTensorInfo(L, ie.dtype, ie.values);
  }
  var V8 = {kernelName: S.BatchMatMul, backendName: "cpu", kernelFunc: Yw};
  function G8(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.a, a = t.b, s = t.bias, o = t.preluActivationWeights, c = r.transposeA, l = r.transposeB, u = r.activation, h, d, p, f = [], m = Yw({inputs: {a: i, b: a}, attrs: {transposeA: c, transposeB: l}, backend: e});
    h = m, s && (d = ts({inputs: {a: h, b: s}, backend: e}), f.push(h), h = d), u && (p = Md(e, h, u, o), f.push(h), h = p);
    for (var g = 0, y = f; g < y.length; g++) {
      var w = y[g];
      e.disposeIntermediateTensorInfo(w);
    }
    return h;
  }
  var q8 = {kernelName: S._FusedMatMul, backendName: "cpu", kernelFunc: G8};
  var Y8 = je(S.Acos, function(n) {
    return Math.acos(n);
  }), K8 = {kernelName: S.Acos, backendName: "cpu", kernelFunc: Y8};
  var j8 = je(S.Acosh, function(n) {
    return Math.acosh(n);
  }), $8 = {kernelName: S.Acosh, backendName: "cpu", kernelFunc: j8};
  var X8 = je(S.Asin, function(n) {
    return Math.asin(n);
  }), J8 = {kernelName: S.Asin, backendName: "cpu", kernelFunc: X8};
  var Z8 = je(S.Asinh, function(n) {
    return Math.asinh(n);
  }), Q8 = {kernelName: S.Asinh, backendName: "cpu", kernelFunc: Z8};
  var e9 = je(S.Atan, function(n) {
    return Math.atan(n);
  }), t9 = {kernelName: S.Atan, backendName: "cpu", kernelFunc: e9};
  var n9 = je(S.Atanh, function(n) {
    return Math.atanh(n);
  }), r9 = {kernelName: S.Atanh, backendName: "cpu", kernelFunc: n9};
  function Hd(n, t, e, r, i, a) {
    for (var s = i.strideHeight, o = i.strideWidth, c = i.dilationHeight, l = i.dilationWidth, u = i.effectiveFilterHeight, h = i.effectiveFilterWidth, d = i.padInfo.top, p = i.padInfo.left, f = a === "max" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY, m = S.buffer(i.outShape, e), g = m.values, y = i.outShape[1] * i.outShape[2] * i.outShape[3], w = i.outShape[2] * i.outShape[3], b = i.outShape[3], L = 0; L < i.batchSize; ++L)
      for (var x = L * y, N = L * r[0], I = 0; I < i.inChannels; ++I)
        for (var C = 0; C < i.outHeight; ++C)
          for (var O = C * s - d, D = Math.max(0, O), F = Math.min(i.inHeight, u + O), k = x + C * w, B = 0; B < i.outWidth; ++B) {
            for (var V = B * o - p, P = Math.max(0, V), G = Math.min(i.inWidth, h + V), j = f, q = 0, H = 0, J = D; J < F; J += c) {
              for (var $ = N + J * r[1], ee = P; ee < G; ee += l) {
                var te = $ + ee * r[2], ne = n[te + I];
                a === "max" && ne > j ? j = ne : a === "avg" && (q += ne, H++);
              }
              if (isNaN(j))
                break;
            }
            var re = k + B * b + I;
            g[re] = a === "avg" ? q / H : j;
          }
    return m;
  }
  function Kw(n, t, e, r, i, a) {
    i === void 0 && (i = false), a === void 0 && (a = false);
    for (var s = S.buffer(r.outShape, "int32"), o = r.strideHeight, c = r.strideWidth, l = r.dilationHeight, u = r.dilationWidth, h = r.effectiveFilterHeight, d = r.effectiveFilterWidth, p = r.padInfo.top, f = r.padInfo.left, m = S.buffer(t, e, n), g = 0; g < r.batchSize; ++g)
      for (var y = 0; y < r.inChannels; ++y)
        for (var w = 0; w < r.outHeight; ++w) {
          for (var b = w * o - p, L = b; L < 0; )
            L += l;
          for (var x = Math.min(r.inHeight, h + b), N = 0; N < r.outWidth; ++N) {
            for (var I = N * c - f, C = I; C < 0; )
              C += u;
            for (var O = Math.min(r.inWidth, d + I), D = Number.NEGATIVE_INFINITY, F = -1, k = L; k < x; k += l)
              for (var B = k - b, V = C; V < O; V += u) {
                var P = V - I, G = m.get(g, k, V, y);
                G > D && (D = G, i ? F = a ? ((g * r.inHeight + k) * r.inWidth + V) * r.inChannels + y : (k * r.inWidth + V) * r.inChannels + y : F = B * d + P);
              }
            s.set(F, g, w, N, y);
          }
        }
    return s;
  }
  function i9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x;
    ae(i, "avgPool");
    var a = r.filterSize, s = r.strides, o = r.pad, c = r.dimRoundingMode, l = 1;
    S.util.assert(S.backend_util.eitherStridesOrDilationsAreOne(s, l), function() {
      return "Error in avgPool: Either strides or dilations must be 1. " + ("Got strides " + s + " and dilations '" + l + "'");
    });
    var u = S.backend_util.computePool2DInfo(i.shape, a, s, l, o, c), h;
    if (u.filterWidth === 1 && u.filterHeight === 1 && S.util.arraysEqual(u.inShape, u.outShape))
      h = hi({inputs: {x: i}, backend: e});
    else {
      var d = e.data.get(i.dataId).values, p = S.util.computeStrides(i.shape), f = Hd(d, i.shape, i.dtype, p, u, "avg");
      h = e.makeTensorInfo(u.outShape, i.dtype, f.values);
    }
    return h;
  }
  var a9 = {kernelName: S.AvgPool, backendName: "cpu", kernelFunc: i9};
  function s9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.dy, a = t.input, s = a;
    ae([i, a], "avgPoolBackprop");
    for (var o = r.filterSize, c = r.strides, l = r.pad, u = S.backend_util.computePool2DInfo(s.shape, o, c, 1, l), h = u.strideHeight, d = u.strideWidth, p = u.filterHeight, f = u.filterWidth, m = u.dilationHeight, g = u.dilationWidth, y = u.effectiveFilterHeight, w = u.effectiveFilterWidth, b = w - 1 - u.padInfo.left, L = y - 1 - u.padInfo.top, x = S.buffer(s.shape, "float32"), N = 1 / (p * f), I = e.data.get(i.dataId).values, C = S.buffer(i.shape, "float32", I), O = 0; O < u.batchSize; ++O)
      for (var D = 0; D < u.inChannels; ++D)
        for (var F = 0; F < u.inHeight; ++F)
          for (var k = 0; k < u.inWidth; ++k) {
            for (var B = F - L, V = k - b, P = 0, G = 0; G < y; G += m) {
              var j = (B + G) / h;
              if (j < 0 || j >= u.outHeight || Math.floor(j) !== j)
                continue;
              for (var q = 0; q < w; q += g) {
                var H = (V + q) / d;
                if (H < 0 || H >= u.outWidth || Math.floor(H) !== H)
                  continue;
                var J = C.get(O, j, H, D);
                P += J;
              }
            }
            x.set(P * N, O, F, k, D);
          }
    return e.makeTensorInfo(x.shape, x.dtype, x.values);
  }
  var o9 = {kernelName: S.AvgPoolBackprop, backendName: "cpu", kernelFunc: s9};
  function c9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.scale, s = t.offset, o = t.mean, c = t.variance;
    S.util.assert(o.shape.length === c.shape.length, function() {
      return "Batch normalization gradient requires mean and variance to have equal ranks.";
    }), S.util.assert(s == null || o.shape.length === s.shape.length, function() {
      return "Batch normalization gradient requires mean and offset to have equal ranks.";
    }), S.util.assert(a == null || o.shape.length === a.shape.length, function() {
      return "Batch normalization gradient requires mean and scale to have equal ranks.";
    }), ae([i, o, c, a, s], "batchNorm");
    var l = r.varianceEpsilon;
    l == null && (l = 1e-3);
    for (var u = e.data.get(i.dataId).values, h = e.data.get(o.dataId).values, d = e.data.get(c.dataId).values, p = a ? e.data.get(a.dataId).values : new Float32Array([1]), f = s ? e.data.get(s.dataId).values : new Float32Array([0]), m = new Float32Array(u.length), g = f.length, y = p.length, w = d.length, b = h.length, L = 0, x = 0, N = 0, I = 0, C = 0; C < u.length; ++C)
      m[C] = f[L++] + (u[C] - h[x++]) * p[N++] / Math.sqrt(d[I++] + l), L >= g && (L = 0), x >= b && (x = 0), N >= y && (N = 0), I >= w && (I = 0);
    return e.makeTensorInfo(i.shape, i.dtype, m);
  }
  var l9 = {kernelName: S.FusedBatchNorm, backendName: "cpu", kernelFunc: c9};
  var u9 = je(S.ClipByValue, function(n, t) {
    var e = t;
    return n > e.clipValueMax ? e.clipValueMax : n < e.clipValueMin ? e.clipValueMin : n;
  }), h9 = {kernelName: S.ClipByValue, backendName: "cpu", kernelFunc: u9};
  function qo(n) {
    var t = n.inputs, e = n.backend, r = t.input, i = e.data.get(r.dataId).complexTensorInfos.imag, a = e.data.get(i.dataId).values;
    return e.makeTensorInfo(i.shape, i.dtype, a);
  }
  var d9 = {kernelName: S.Imag, backendName: "cpu", kernelFunc: qo};
  function ns(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = r.axis, a = S.util.parseAxisParam(i, t[0].shape)[0], s = S.backend_util.computeOutShape(t.map(function(L) {
      return L.shape;
    }), a);
    if (S.util.sizeFromShape(s) === 0)
      return e.makeTensorInfo(s, t[0].dtype, []);
    var o = t.filter(function(L) {
      return S.util.sizeFromShape(L.shape) > 0;
    });
    if (o.length === 1)
      return o[0];
    var c = o.map(function(L) {
      return L.shape;
    });
    if (S.backend_util.assertParamsConsistent(c, a), o[0].dtype === "complex64") {
      var l = o.map(function(L) {
        return Qa({inputs: {input: L}, backend: e});
      }), u = o.map(function(L) {
        return qo({inputs: {input: L}, backend: e});
      }), h = ns({inputs: l, backend: e, attrs: {axis: a}}), d = ns({inputs: u, backend: e, attrs: {axis: a}}), p = Tn({inputs: {real: h, imag: d}, backend: e});
      return l.forEach(function(L) {
        return e.disposeIntermediateTensorInfo(L);
      }), u.forEach(function(L) {
        return e.disposeIntermediateTensorInfo(L);
      }), e.disposeIntermediateTensorInfo(h), e.disposeIntermediateTensorInfo(d), p;
    }
    var f = o.map(function(L) {
      var x = S.util.sizeFromShape(L.shape.slice(a)), N = [-1, x];
      return zn({inputs: {x: L}, backend: e, attrs: {shape: N}});
    });
    s = S.backend_util.computeOutShape(f.map(function(L) {
      return L.shape;
    }), 1);
    var m = S.util.getTypedArrayFromDType(o[0].dtype, S.util.sizeFromShape(s));
    if (f[0].shape[0] === 1) {
      var g = 0;
      f.forEach(function(L) {
        var x = e.data.get(L.dataId).values, N = S.util.sizeFromShape(L.shape);
        m.set(x, g), g += N;
      });
    } else {
      var y = 0;
      f.forEach(function(L) {
        for (var x = e.data.get(L.dataId).values, N = 0, I = 0; I < L.shape[0]; ++I)
          for (var C = I * s[1] + y, O = 0; O < L.shape[1]; ++O)
            m[C + O] = x[N++];
        y += L.shape[1];
      });
    }
    var w = S.backend_util.computeOutShape(o.map(function(L) {
      return L.shape;
    }), a), b = e.makeTensorInfo(w, t[0].dtype, m);
    return f.forEach(function(L) {
      return e.disposeIntermediateTensorInfo(L);
    }), b;
  }
  var p9 = {kernelName: S.Concat, backendName: "cpu", kernelFunc: ns};
  function jw(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.filter, s = r.strides, o = r.pad, c = r.dataFormat, l = r.dilations, u = r.dimRoundingMode;
    ae([i, a], "conv2d");
    for (var h = S.backend_util.convertConv2DDataFormat(c), d = S.backend_util.computeConv2DInfo(i.shape, a.shape, s, l, o, u, false, h), p = d.filterHeight, f = d.filterWidth, m = d.dilationHeight, g = d.dilationWidth, y = d.padInfo.left, w = d.padInfo.top, b = d.dataFormat === "channelsLast", L = new S.TensorBuffer(d.outShape, i.dtype), x = S.util.computeStrides(i.shape), N = S.util.computeStrides(a.shape), I = x[0], C = b ? x[1] : x[2], O = b ? x[2] : 1, D = b ? 1 : x[1], F = L.strides[0], k = b ? L.strides[1] : L.strides[2], B = b ? L.strides[2] : 1, V = b ? 1 : L.strides[1], P = e.data.get(i.dataId).values, G = e.data.get(a.dataId).values, j = L.values, q = 0; q < d.batchSize; ++q)
      for (var H = q * I, J = q * F, $ = 0; $ < d.outHeight; ++$)
        for (var ee = J + $ * k, te = $ * d.strideHeight - w, ne = 0; ne < p; ++ne) {
          var re = te + ne * m;
          if (re < 0 || re >= d.inHeight)
            continue;
          for (var ie = ne * N[0], oe = H + re * C, se = 0; se < d.outWidth; ++se)
            for (var me = ee + se * B, ye = se * d.strideWidth - y, ve = 0; ve < f; ++ve) {
              var Ee = ye + ve * g;
              if (Ee < 0 || Ee >= d.inWidth)
                continue;
              for (var Be = ie + ve * N[1], We = oe + Ee * O, Ke = Be, ze = 0; ze < d.inChannels; ++ze) {
                for (var Ie = P[We + ze * D], ue = 0; ue < d.outChannels; ++ue)
                  j[me + ue * V] += Ie * G[Ke + ue];
                Ke += d.outChannels;
              }
            }
        }
    return e.makeTensorInfo(L.shape, L.dtype, j);
  }
  var f9 = {kernelName: S.Conv2D, backendName: "cpu", kernelFunc: jw};
  function m9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.dy, s = r.strides, o = r.pad, c = r.dataFormat, l = r.dimRoundingMode, u = r.filterShape;
    ae([i, a], "conv2dBackpropFilter");
    for (var h = S.backend_util.convertConv2DDataFormat(c), d = S.backend_util.computeConv2DInfo(i.shape, u, s, 1, o, l, false, h), p = d.strideHeight, f = d.strideWidth, m = d.filterHeight, g = d.filterWidth, y = d.dataFormat === "channelsLast", w = new S.TensorBuffer(d.filterShape, "float32"), b = d.padInfo.left, L = d.padInfo.top, x = e.data.get(i.dataId).values, N = e.data.get(a.dataId).values, I = new S.TensorBuffer(i.shape, i.dtype, x), C = new S.TensorBuffer(a.shape, a.dtype, N), O = 0; O < m; ++O)
      for (var D = Math.max(0, Math.ceil((L - O) / p)), F = Math.min(d.outHeight, (d.inHeight + L - O) / p), k = 0; k < g; ++k)
        for (var B = Math.max(0, Math.ceil((b - k) / f)), V = Math.min(d.outWidth, (d.inWidth + b - k) / f), P = 0; P < d.inChannels; ++P)
          for (var G = 0; G < d.outChannels; ++G) {
            for (var j = 0, q = 0; q < d.batchSize; ++q)
              for (var H = D; H < F; ++H)
                for (var J = O + H * p - L, $ = B; $ < V; ++$) {
                  var ee = k + $ * f - b;
                  y ? j += I.get(q, J, ee, P) * C.get(q, H, $, G) : j += I.get(q, P, J, ee) * C.get(q, G, H, $);
                }
            w.set(j, O, k, P, G);
          }
    return e.makeTensorInfo(w.shape, w.dtype, w.values);
  }
  var g9 = {kernelName: S.Conv2DBackpropFilter, backendName: "cpu", kernelFunc: m9};
  function y9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.dy, a = t.filter, s = r.inputShape, o = r.strides, c = r.pad, l = r.dataFormat, u = r.dimRoundingMode;
    ae([i, a], "conv2dBackpropInput");
    var h = S.util.computeStrides(a.shape), d = S.util.computeStrides(i.shape), p = S.backend_util.convertConv2DDataFormat(l), f = S.backend_util.computeConv2DInfo(s, a.shape, o, 1, c, u, false, p), m = new S.TensorBuffer(f.inShape, "float32"), g = m.values, y = e.data.get(i.dataId).values, w = e.data.get(a.dataId).values, b = h[0], L = h[1], x = h[2], N = f.batchSize, I = f.filterHeight, C = f.filterWidth, O = f.inChannels, D = f.inHeight, F = f.inWidth, k = f.outChannels, B = f.outHeight, V = f.outWidth, P = f.strideHeight, G = f.strideWidth;
    p = f.dataFormat;
    for (var j = I - 1 - f.padInfo.top, q = C - 1 - f.padInfo.left, H = p === "channelsLast", J = m.strides[0], $ = H ? m.strides[1] : m.strides[2], ee = H ? m.strides[2] : 1, te = H ? 1 : m.strides[1], ne = d[0], re = H ? d[1] : d[2], ie = H ? d[2] : 1, oe = H ? 1 : d[1], se = 0; se < N; ++se)
      for (var me = 0; me < O; ++me)
        for (var ye = 0; ye < D; ++ye)
          for (var ve = ye - j, Ee = Math.max(0, Math.ceil(ve / P)), Be = Math.min(B, (I + ve) / P), We = 0; We < F; ++We) {
            for (var Ke = We - q, ze = Math.max(0, Math.ceil(Ke / G)), Ie = Math.min(V, (C + Ke) / G), ue = 0, Qe = Ee; Qe < Be; ++Qe)
              for (var ft = Qe * P - ve, He = ze; He < Ie; ++He)
                for (var Ot = He * G - Ke, ht = ne * se + re * Qe + ie * He, wt = b * (I - 1 - ft) + L * (C - 1 - Ot) + x * me, Te = 0; Te < k; ++Te) {
                  var dt = y[ht + oe * Te], mt = w[wt + Te];
                  ue += dt * mt;
                }
            var Ve = J * se + $ * ye + ee * We + te * me;
            g[Ve] = ue;
          }
    return e.makeTensorInfo(m.shape, m.dtype, m.values);
  }
  var v9 = {kernelName: S.Conv2DBackpropInput, backendName: "cpu", kernelFunc: y9};
  function w9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.filter, s = r.strides, o = r.pad, c = r.dilations;
    ae([i, a], "conv3d");
    for (var l = S.backend_util.computeConv3DInfo(i.shape, a.shape, s, c, o), u = l.filterDepth, h = l.filterHeight, d = l.filterWidth, p = l.dilationDepth, f = l.dilationHeight, m = l.dilationWidth, g = l.padInfo, y = g.front, w = g.left, b = g.top, L = new S.TensorBuffer(l.outShape, i.dtype), x = e.data.get(i.dataId).values, N = e.data.get(a.dataId).values, I = L.values, C = S.util.computeStrides(i.shape), O = S.util.computeStrides(a.shape), D = 0; D < l.batchSize; ++D)
      for (var F = D * C[0], k = D * L.strides[0], B = 0; B < l.outDepth; ++B)
        for (var V = k + B * L.strides[1], P = B * l.strideDepth - y, G = 0; G < u; ++G) {
          var j = P + G * p;
          if (j < 0 || j >= l.inDepth)
            continue;
          for (var q = G * O[0], H = F + j * C[1], J = 0; J < l.outHeight; ++J)
            for (var $ = V + J * L.strides[2], ee = J * l.strideHeight - b, te = 0; te < h; ++te) {
              var ne = ee + te * f;
              if (ne < 0 || ne >= l.inHeight)
                continue;
              for (var re = q + te * O[1], ie = H + ne * C[2], oe = 0; oe < l.outWidth; ++oe)
                for (var se = $ + oe * l.outChannels, me = oe * l.strideWidth - w, ye = 0; ye < d; ++ye) {
                  var ve = me + ye * m;
                  if (ve < 0 || ve >= l.inWidth)
                    continue;
                  for (var Ee = re + ye * O[2], Be = ie + ve * l.inChannels, We = Ee, Ke = 0; Ke < l.inChannels; ++Ke) {
                    for (var ze = x[Be + Ke], Ie = 0; Ie < l.outChannels; ++Ie)
                      I[se + Ie] += ze * N[We + Ie];
                    We += l.outChannels;
                  }
                }
            }
        }
    return e.makeTensorInfo(L.shape, L.dtype, L.values);
  }
  var b9 = {kernelName: S.Conv3D, backendName: "cpu", kernelFunc: w9};
  function x9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.dy, s = r.strides, o = r.pad, c = r.filterShape;
    ae([i, a], "conv3dBackpropFilterV2");
    for (var l = S.util.computeStrides(i.shape), u = S.util.computeStrides(a.shape), h = S.backend_util.computeConv3DInfo(i.shape, c, s, 1, o), d = h.strideDepth, p = h.strideHeight, f = h.strideWidth, m = h.filterDepth, g = h.filterHeight, y = h.filterWidth, w = new S.TensorBuffer(h.filterShape, "float32"), b = w.values, L = w.strides, x = L[0], N = L[1], I = L[2], C = L[3], O = e.data.get(a.dataId).values, D = u[0], F = u[1], k = u[2], B = u[3], V = e.data.get(i.dataId).values, P = l[0], G = l[1], j = l[2], q = l[3], H = h.padInfo.front, J = h.padInfo.left, $ = h.padInfo.top, ee = 0; ee < m; ++ee)
      for (var te = Math.max(0, Math.ceil((H - ee) / d)), ne = Math.min(h.outDepth, (h.inDepth + H - ee) / d), re = ee * x, ie = 0; ie < g; ++ie)
        for (var oe = Math.max(0, Math.ceil(($ - ie) / p)), se = Math.min(h.outHeight, (h.inHeight + $ - ie) / p), me = ie * N + re, ye = 0; ye < y; ++ye)
          for (var ve = Math.max(0, Math.ceil((J - ye) / f)), Ee = Math.min(h.outWidth, (h.inWidth + J - ye) / f), Be = ye * I + me, We = 0; We < h.inChannels; ++We)
            for (var Ke = We * C + Be, ze = 0; ze < h.outChannels; ++ze) {
              for (var Ie = 0, ue = 0; ue < h.batchSize; ++ue)
                for (var Qe = ue * P, ft = ue * D, He = te; He < ne; ++He)
                  for (var Ot = ee + He * d - H, ht = Ot * G + Qe, wt = He * F + ft, Te = oe; Te < se; ++Te)
                    for (var dt = ie + Te * p - $, mt = dt * j + ht, Ve = Te * k + wt, Kt = ve; Kt < Ee; ++Kt) {
                      var Gn = ye + Kt * f - J, kt = Gn * q + mt, ma = Kt * B + Ve;
                      Ie += V[kt + We] * O[ma + ze];
                    }
              b[Ke + ze] = Ie;
            }
    return e.makeTensorInfo(w.shape, w.dtype, w.values);
  }
  var L9 = {kernelName: S.Conv3DBackpropFilterV2, backendName: "cpu", kernelFunc: x9};
  function S9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.dy, a = t.filter, s = r.pad, o = r.strides, c = r.inputShape;
    ae([i], "conv3dBackpropInputV2");
    for (var l = S.util.computeStrides(i.shape), u = S.util.computeStrides(a.shape), h = S.backend_util.computeConv3DInfo(c, a.shape, o, 1, s), d = new S.TensorBuffer(h.inShape, "float32"), p = d.values, f = d.strides, m = f[0], g = f[1], y = f[2], w = f[3], b = e.data.get(i.dataId).values, L = l[0], x = l[1], N = l[2], I = l[3], C = e.data.get(a.dataId).values, O = u[0], D = u[1], F = u[2], k = u[3], B = h.batchSize, V = h.filterDepth, P = h.filterHeight, G = h.filterWidth, j = h.inChannels, q = h.inDepth, H = h.inHeight, J = h.inWidth, $ = h.outChannels, ee = h.outDepth, te = h.outHeight, ne = h.outWidth, re = h.strideDepth, ie = h.strideHeight, oe = h.strideWidth, se = V - 1 - h.padInfo.front, me = P - 1 - h.padInfo.top, ye = G - 1 - h.padInfo.left, ve = 0; ve < B; ++ve)
      for (var Ee = 0; Ee < j; ++Ee)
        for (var Be = 0; Be < q; ++Be)
          for (var We = Be - se, Ke = Math.max(0, Math.ceil(We / re)), ze = Math.min(ee, (V + We) / re), Ie = 0; Ie < H; ++Ie)
            for (var ue = Ie - me, Qe = Math.max(0, Math.ceil(ue / ie)), ft = Math.min(te, (P + ue) / ie), He = 0; He < J; ++He) {
              for (var Ot = He - ye, ht = Math.max(0, Math.ceil(Ot / oe)), wt = Math.min(ne, (G + Ot) / oe), Te = 0, dt = Ke; dt < ze; ++dt)
                for (var mt = dt * re - We, Ve = Qe; Ve < ft; ++Ve)
                  for (var Kt = Ve * ie - ue, Gn = ht; Gn < wt; ++Gn)
                    for (var kt = Gn * oe - Ot, ma = L * ve + x * dt + N * Ve + I * Gn, sr = O * (V - 1 - mt) + D * (P - 1 - Kt) + F * (G - 1 - kt) + k * Ee, wi = 0; wi < $; ++wi) {
                      var fc = b[ma + wi], mc = C[sr + wi];
                      Te += fc * mc;
                    }
              p[m * ve + g * Be + y * Ie + w * He + Ee] = Te;
            }
    return e.makeTensorInfo(d.shape, d.dtype, d.values);
  }
  var I9 = {kernelName: S.Conv3DBackpropInputV2, backendName: "cpu", kernelFunc: S9};
  var A9 = je(S.Cos, function(n) {
    return Math.cos(n);
  }), T9 = {kernelName: S.Cos, backendName: "cpu", kernelFunc: A9};
  var N9 = je(S.Cosh, function(n) {
    return Math.cosh(n);
  }), _9 = {kernelName: S.Cosh, backendName: "cpu", kernelFunc: N9};
  function $w(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.filter, s = r.strides, o = r.pad, c = r.dilations, l = r.dimRoundingMode;
    ae([i, a], "depthwiseConv2DNative");
    var u = S.util.computeStrides(i.shape), h = S.util.computeStrides(a.shape), d = c;
    d == null && (d = [1, 1]), S.util.assert(S.backend_util.eitherStridesOrDilationsAreOne(s, d), function() {
      return "Error in depthwiseConv2d: Either strides or dilations must be " + ("1. Got strides " + s + " and dilations '" + d + "'");
    });
    for (var p = S.backend_util.computeConv2DInfo(i.shape, a.shape, s, d, o, l, true), f = p.filterHeight, m = p.filterWidth, g = p.dilationHeight, y = p.dilationWidth, w = p.padInfo, b = w.left, L = w.top, x = p.outChannels / p.inChannels, N = new S.TensorBuffer(p.outShape, i.dtype), I = e.data.get(i.dataId).values, C = e.data.get(a.dataId).values, O = N.values, D = 0; D < p.batchSize; ++D)
      for (var F = D * u[0], k = D * N.strides[0], B = 0; B < p.outHeight; ++B)
        for (var V = k + B * N.strides[1], P = B * p.strideHeight - b, G = 0; G < f; ++G) {
          var j = P + G * g;
          if (j < 0 || j >= p.inHeight)
            continue;
          for (var q = G * h[0], H = F + j * u[1], J = 0; J < p.outWidth; ++J)
            for (var $ = V + J * N.strides[2], ee = J * p.strideWidth - L, te = 0; te < m; ++te) {
              var ne = ee + te * y;
              if (ne < 0 || ne >= p.inWidth)
                continue;
              for (var re = q + te * h[1], ie = H + ne * p.inChannels, oe = $, se = re, me = 0; me < p.inChannels; ++me) {
                for (var ye = I[ie + me], ve = 0; ve < x; ++ve)
                  O[oe + ve] += ye * C[se + ve];
                oe += x, se += x;
              }
            }
        }
    return e.makeTensorInfo(N.shape, N.dtype, N.values);
  }
  var C9 = {kernelName: S.DepthwiseConv2dNative, backendName: "cpu", kernelFunc: $w};
  function R9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.dy, s = r.strides, o = r.dilations, c = r.pad, l = r.dimRoundingMode, u = r.filterShape;
    ae([i, a], "depthwiseConv2dNativeBackpropFilter");
    for (var h = S.backend_util.computeConv2DInfo(i.shape, u, s, o, c, l, true), d = h.strideHeight, p = h.strideWidth, f = h.filterHeight, m = h.filterWidth, g = new S.TensorBuffer(h.filterShape, "float32"), y = h.padInfo.left, w = h.padInfo.top, b = h.outChannels / h.inChannels, L = e.data.get(i.dataId).values, x = new S.TensorBuffer(i.shape, i.dtype, L), N = e.data.get(a.dataId).values, I = new S.TensorBuffer(a.shape, a.dtype, N), C = 0; C < f; ++C)
      for (var O = Math.max(0, Math.ceil((w - C) / d)), D = Math.min(h.outHeight, (h.inHeight + w - C) / d), F = 0; F < m; ++F)
        for (var k = Math.max(0, Math.ceil((y - F) / p)), B = Math.min(h.outWidth, (h.inWidth + y - F) / p), V = 0; V < h.outChannels; ++V) {
          for (var P = Math.trunc(V / b), G = V % b, j = 0, q = 0; q < h.batchSize; ++q)
            for (var H = O; H < D; ++H)
              for (var J = C + H * d - w, $ = k; $ < B; ++$) {
                var ee = F + $ * p - y;
                j += x.get(q, J, ee, P) * I.get(q, H, $, V);
              }
          g.set(j, C, F, P, G);
        }
    return e.makeTensorInfo(g.shape, g.dtype, g.values);
  }
  var O9 = {kernelName: S.DepthwiseConv2dNativeBackpropFilter, backendName: "cpu", kernelFunc: R9};
  function E9(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.dy, a = t.filter, s = r.strides, o = r.dilations, c = r.pad, l = r.dimRoundingMode, u = r.inputShape;
    ae([i, a], "depthwiseConv2DNativeBackpropInput");
    for (var h = S.util.computeStrides(i.shape), d = S.util.computeStrides(a.shape), p = S.backend_util.computeConv2DInfo(u, a.shape, s, o, c, l, true), f = new S.TensorBuffer(p.inShape, "float32"), m = f.values, g = f.strides, y = g[0], w = g[1], b = g[2], L = e.data.get(i.dataId).values, x = h[0], N = h[1], I = h[2], C = e.data.get(a.dataId).values, O = d[0], D = d[1], F = d[2], k = p.batchSize, B = p.filterHeight, V = p.filterWidth, P = p.inChannels, G = p.inHeight, j = p.inWidth, q = p.outChannels, H = p.outHeight, J = p.outWidth, $ = p.strideHeight, ee = p.strideWidth, te = B - 1 - p.padInfo.top, ne = V - 1 - p.padInfo.left, re = q / P, ie = 0; ie < k; ++ie)
      for (var oe = 0; oe < P; ++oe)
        for (var se = 0; se < G; ++se)
          for (var me = se - te, ye = Math.max(0, Math.ceil(me / $)), ve = Math.min(H, (B + me) / $), Ee = 0; Ee < j; ++Ee) {
            for (var Be = Ee - ne, We = Math.max(0, Math.ceil(Be / ee)), Ke = Math.min(J, (V + Be) / ee), ze = 0, Ie = ye; Ie < ve; ++Ie)
              for (var ue = Ie * $ - me, Qe = We; Qe < Ke; ++Qe)
                for (var ft = Qe * ee - Be, He = x * ie + N * Ie + I * Qe, Ot = O * (B - 1 - ue) + D * (V - 1 - ft) + F * oe, ht = 0; ht < re; ++ht) {
                  var wt = oe * re + ht, Te = L[He + wt], dt = C[Ot + ht];
                  ze += Te * dt;
                }
            m[y * ie + w * se + b * Ee + oe] = ze;
          }
    return e.makeTensorInfo(f.shape, f.dtype, f.values);
  }
  var D9 = {kernelName: S.DepthwiseConv2dNativeBackpropInput, backendName: "cpu", kernelFunc: E9};
  var k9 = {kernelName: S.Dilation2D, backendName: "cpu", kernelFunc: function(n) {
    for (var t = n.inputs, e = n.backend, r = n.attrs, i = t, a = i.x, s = i.filter, o = r, c = o.strides, l = o.pad, u = o.dilations, h = e, d = h.data.get(a.dataId).values, p = a.shape.length, f = h.data.get(s.dataId).values, m = s.shape.length, g = S.backend_util.computeDilation2DInfo(a.shape, s.shape, c, l, "NHWC", u), y = g.batchSize, w = g.inHeight, b = g.inWidth, L = g.inChannels, x = g.outHeight, N = g.outWidth, I = g.padInfo, C = g.strideHeight, O = g.strideWidth, D = g.filterHeight, F = g.filterWidth, k = g.dilationHeight, B = g.dilationWidth, V = g.outShape, P = S.util.sizeFromShape(V), G = V.length, j = S.util.getArrayFromDType(a.dtype, P), q = 0; q < y; ++q)
      for (var H = 0; H < x; ++H)
        for (var J = H * C - I.top, $ = 0; $ < N; ++$)
          for (var ee = $ * O - I.left, te = 0; te < L; ++te) {
            for (var ne = Number.MIN_SAFE_INTEGER, re = 0; re < D; ++re) {
              var ie = J + re * k;
              if (ie >= 0 && ie < w)
                for (var oe = 0; oe < F; ++oe) {
                  var se = ee + oe * B;
                  if (se >= 0 && se < b) {
                    var me = S.util.locToIndex([q, ie, se, te], p, S.util.computeStrides(a.shape)), ye = S.util.locToIndex([re, oe, te], m, S.util.computeStrides(s.shape)), ve = d[me] + f[ye];
                    ve > ne && (ne = ve);
                  }
                }
            }
            var Ee = S.util.locToIndex([q, H, $, te], G, S.util.computeStrides(V));
            j[Ee] = ne;
          }
    var Be = h.write(S.util.toTypedArray(j, a.dtype), V, a.dtype);
    return {dataId: Be, shape: V, dtype: a.dtype};
  }};
  var F9 = {kernelName: S.Dilation2DBackpropFilter, backendName: "cpu", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t, a = i.x, s = i.filter, o = i.dy, c = r, l = c.strides, u = c.pad, h = c.dilations, d = e, p = S.util.toNestedArray(a.shape, d.data.get(a.dataId).values), f = S.util.toNestedArray(s.shape, d.data.get(s.dataId).values), m = S.backend_util.computeDilation2DInfo(a.shape, s.shape, l, u, "NHWC", h), g = m.batchSize, y = m.inHeight, w = m.inWidth, b = m.inChannels, L = m.outHeight, x = m.outWidth, N = m.padInfo, I = m.strideHeight, C = m.strideWidth, O = m.filterHeight, D = m.filterWidth, F = m.dilationHeight, k = m.dilationWidth, B = m.outShape;
    S.util.assert(o.rank === B.length, function() {
      return "Error in " + S.Dilation2DBackpropFilter + ", dy " + ("must have the same rank as output " + B.length + ", but got ") + ("" + o.rank);
    });
    for (var V = S.util.toNestedArray(B, d.data.get(o.dataId).values), P = S.util.makeZerosNestedTypedArray(s.shape, s.dtype), G = 0; G < g; ++G)
      for (var j = 0; j < L; ++j)
        for (var q = j * I - N.top, H = 0; H < x; ++H)
          for (var J = H * C - N.left, $ = 0; $ < b; ++$) {
            for (var ee = Number.MIN_SAFE_INTEGER, te = 0, ne = 0, re = 0; re < O; ++re) {
              var ie = q + re * F;
              if (ie >= 0 && ie < y)
                for (var oe = 0; oe < D; ++oe) {
                  var se = J + oe * k;
                  if (se >= 0 && se < w) {
                    var me = p[G][ie][se][$] + f[re][oe][$];
                    me > ee && (ee = me, te = re, ne = oe);
                  }
                }
            }
            P[te][ne][$] += V[G][j][H][$];
          }
    var ye = d.write(S.util.toTypedArray(P, a.dtype), s.shape, s.dtype);
    return {dataId: ye, shape: s.shape, dtype: s.dtype};
  }};
  var W9 = {kernelName: S.Dilation2DBackpropInput, backendName: "cpu", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t, a = i.x, s = i.filter, o = i.dy, c = r, l = c.strides, u = c.pad, h = c.dilations, d = e, p = S.util.toNestedArray(a.shape, d.data.get(a.dataId).values), f = S.util.toNestedArray(s.shape, d.data.get(s.dataId).values), m = S.backend_util.computeDilation2DInfo(a.shape, s.shape, l, u, "NHWC", h), g = m.batchSize, y = m.inHeight, w = m.inWidth, b = m.inChannels, L = m.outHeight, x = m.outWidth, N = m.padInfo, I = m.strideHeight, C = m.strideWidth, O = m.filterHeight, D = m.filterWidth, F = m.dilationHeight, k = m.dilationWidth, B = m.outShape;
    S.util.assert(o.rank === B.length, function() {
      return "Error in " + S.Dilation2DBackpropInput + ", dy " + ("must have the same rank as output " + B.length + ", but got ") + ("" + o.rank);
    });
    for (var V = S.util.toNestedArray(B, d.data.get(o.dataId).values), P = S.util.makeZerosNestedTypedArray(a.shape, a.dtype), G = 0; G < g; ++G)
      for (var j = 0; j < L; ++j)
        for (var q = j * I - N.top, H = 0; H < x; ++H)
          for (var J = H * C - N.left, $ = 0; $ < b; ++$) {
            for (var ee = Number.MIN_SAFE_INTEGER, te = q < 0 ? 0 : q, ne = J < 0 ? 0 : J, re = 0; re < O; ++re) {
              var ie = q + re * F;
              if (ie >= 0 && ie < y)
                for (var oe = 0; oe < D; ++oe) {
                  var se = J + oe * k;
                  if (se >= 0 && se < w) {
                    var me = p[G][ie][se][$] + f[re][oe][$];
                    me > ee && (ee = me, te = ie, ne = se);
                  }
                }
            }
            P[G][te][ne][$] += V[G][j][H][$];
          }
    var ye = d.write(S.util.toTypedArray(P, a.dtype), a.shape, a.dtype);
    return {dataId: ye, shape: a.shape, dtype: a.dtype};
  }};
  var U9 = Rr(function(n, t) {
    return n / t;
  }), B9 = Ji(S.Div, U9), Vd = {kernelName: S.Div, backendName: "cpu", kernelFunc: B9};
  var z9 = S.backend_util.ERF_P, P9 = S.backend_util.ERF_A1, M9 = S.backend_util.ERF_A2, H9 = S.backend_util.ERF_A3, V9 = S.backend_util.ERF_A4, G9 = S.backend_util.ERF_A5, q9 = je(S.Erf, function(n) {
    var t = Math.sign(n), e = Math.abs(n), r = 1 / (1 + z9 * e);
    return t * (1 - ((((G9 * r + V9) * r + H9) * r + M9) * r + P9) * r * Math.exp(-e * e));
  }), Y9 = {kernelName: S.Erf, backendName: "cpu", kernelFunc: q9};
  function Xw(n, t, e) {
    for (var r = n.shape, i = r[0], a = r[1], s = e.data.get(n.dataId), o = s.complexTensorInfos.real, c = s.complexTensorInfos.imag, l = [i, a], u = S.util.sizeFromShape(l), h = S.util.getTypedArrayFromDType("float32", u), d = S.util.getTypedArrayFromDType("float32", u), p = 0; p < i; p++) {
      for (var f = zd({inputs: {x: o}, backend: e, attrs: {begin: [p, 0], size: [1, a]}}), m = zd({inputs: {x: c}, backend: e, attrs: {begin: [p, 0], size: [1, a]}}), g = Tn({inputs: {real: f, imag: m}, backend: e}), y = K9(g, t, e), w = y.real, b = y.imag, L = S.backend_util.mergeRealAndImagArrays(w, b), x = 0; x < a; x++) {
        var N = S.backend_util.getComplexWithIndex(L, x);
        h[p * a + x] = N.real, d[p * a + x] = N.imag;
      }
      e.disposeIntermediateTensorInfo(f), e.disposeIntermediateTensorInfo(m), e.disposeIntermediateTensorInfo(g);
    }
    var I = e.makeTensorInfo(l, "float32", h), C = e.makeTensorInfo(l, "float32", d), O = Tn({inputs: {real: I, imag: C}, backend: e});
    return e.disposeIntermediateTensorInfo(I), e.disposeIntermediateTensorInfo(C), O;
  }
  function K9(n, t, e) {
    var r = S.util.sizeFromShape(n.shape), i = e.data.get(n.dataId), a = e.data.get(i.complexTensorInfos.real.dataId).values, s = e.data.get(i.complexTensorInfos.imag.dataId).values;
    if (j9(r)) {
      var o = Gd(a, s, r, t, e), c = [n.shape[0], n.shape[1]];
      if (t) {
        var l = e.makeTensorInfo(c, "float32", o.real), u = e.makeTensorInfo(c, "float32", o.imag), h = e.makeTensorInfo([], "float32", S.util.createScalarValue(r, "float32")), d = hi({inputs: {x: h}, backend: e}), p = Vd.kernelFunc({inputs: {a: l, b: h}, backend: e}), f = Vd.kernelFunc({inputs: {a: u, b: d}, backend: e}), m = e.data.get(p.dataId).values, g = e.data.get(f.dataId).values;
        return e.disposeIntermediateTensorInfo(l), e.disposeIntermediateTensorInfo(u), e.disposeIntermediateTensorInfo(h), e.disposeIntermediateTensorInfo(d), e.disposeIntermediateTensorInfo(p), e.disposeIntermediateTensorInfo(f), {real: m, imag: g};
      }
      return o;
    } else {
      var y = S.backend_util.mergeRealAndImagArrays(a, s), w = $9(y, r, t);
      return S.backend_util.splitRealAndImagArrays(w);
    }
  }
  function j9(n) {
    return (n & n - 1) === 0;
  }
  function Gd(n, t, e, r, i) {
    if (e === 1)
      return {real: n, imag: t};
    var a = S.backend_util.mergeRealAndImagArrays(n, t), s = e / 2, o = S.backend_util.complexWithEvenIndex(a), c = o.real, l = o.imag, u = [c.length], h = i.makeTensorInfo(u, "float32", c), d = i.makeTensorInfo(u, "float32", l), p = Tn({inputs: {real: h, imag: d}, backend: i}), f = S.backend_util.complexWithOddIndex(a), m = f.real, g = f.imag, y = [m.length], w = i.makeTensorInfo(y, "float32", m), b = i.makeTensorInfo(y, "float32", g), L = Tn({inputs: {real: w, imag: b}, backend: i}), x = Gd(c, l, s, r, i), N = x.real, I = x.imag, C = [N.length], O = i.makeTensorInfo(C, "float32", N), D = i.makeTensorInfo(C, "float32", I), F = Tn({inputs: {real: O, imag: D}, backend: i}), k = Gd(m, g, s, r, i), B = k.real, V = k.imag, P = [B.length], G = i.makeTensorInfo(P, "float32", B), j = i.makeTensorInfo(P, "float32", V), q = Tn({inputs: {real: G, imag: j}, backend: i}), H = S.backend_util.exponents(e, r), J = [H.real.length], $ = i.makeTensorInfo(J, "float32", H.real), ee = i.makeTensorInfo(J, "float32", H.imag), te = Tn({inputs: {real: $, imag: ee}, backend: i}), ne = kw({inputs: {a: te, b: q}, backend: i}), re = ts({inputs: {a: F, b: ne}, backend: i}), ie = Pw({inputs: {a: F, b: ne}, backend: i}), oe = Qa({inputs: {input: re}, backend: i}), se = Qa({inputs: {input: ie}, backend: i}), me = qo({inputs: {input: re}, backend: i}), ye = qo({inputs: {input: ie}, backend: i}), ve = ns({inputs: [oe, se], backend: i, attrs: {axis: 0}}), Ee = ns({inputs: [me, ye], backend: i, attrs: {axis: 0}}), Be = i.data.get(ve.dataId).values, We = i.data.get(Ee.dataId).values;
    return i.disposeIntermediateTensorInfo(h), i.disposeIntermediateTensorInfo(d), i.disposeIntermediateTensorInfo(p), i.disposeIntermediateTensorInfo(w), i.disposeIntermediateTensorInfo(b), i.disposeIntermediateTensorInfo(L), i.disposeIntermediateTensorInfo(O), i.disposeIntermediateTensorInfo(D), i.disposeIntermediateTensorInfo(F), i.disposeIntermediateTensorInfo(G), i.disposeIntermediateTensorInfo(j), i.disposeIntermediateTensorInfo(q), i.disposeIntermediateTensorInfo($), i.disposeIntermediateTensorInfo(ee), i.disposeIntermediateTensorInfo(te), i.disposeIntermediateTensorInfo(ne), i.disposeIntermediateTensorInfo(re), i.disposeIntermediateTensorInfo(ie), i.disposeIntermediateTensorInfo(oe), i.disposeIntermediateTensorInfo(me), i.disposeIntermediateTensorInfo(se), i.disposeIntermediateTensorInfo(ye), i.disposeIntermediateTensorInfo(ve), i.disposeIntermediateTensorInfo(Ee), {real: Be, imag: We};
  }
  function $9(n, t, e) {
    for (var r = new Float32Array(t * 2), i = 0; i < t; i++) {
      for (var a = 0, s = 0, o = 0; o < t; o++) {
        var c = S.backend_util.exponent(i * o, t, e), l = S.backend_util.getComplexWithIndex(n, o);
        a += l.real * c.real - l.imag * c.imag, s += l.real * c.imag + l.imag * c.real;
      }
      e && (a /= t, s /= t), S.backend_util.assignToTypedArray(r, a, s, i);
    }
    return r;
  }
  function X9(n) {
    var t = n.inputs, e = n.backend, r = t.input, i = S.util.sizeFromShape(r.shape), a = r.shape[r.shape.length - 1], s = i / a, o = zn({inputs: {x: r}, backend: e, attrs: {shape: [s, a]}}), c = Xw(o, false, e), l = zn({inputs: {x: c}, backend: e, attrs: {shape: r.shape}});
    return e.disposeIntermediateTensorInfo(o), e.disposeIntermediateTensorInfo(c), l;
  }
  var J9 = {kernelName: S.FFT, backendName: "cpu", kernelFunc: X9};
  function Q9(n) {
    var t = n.backend, e = n.attrs, r = e.shape, i = e.value, a = e.dtype, s = a || S.util.inferDtype(i), o = S.util.getArrayFromDType(s, S.util.sizeFromShape(r));
    return Z9(o, i, s), t.makeTensorInfo(r, s, o);
  }
  var eF = {kernelName: S.Fill, backendName: "cpu", kernelFunc: Q9};
  function Z9(n, t, e) {
    e === "string", n.fill(t);
  }
  var tF = {kernelName: S.FlipLeftRight, backendName: "cpu", kernelFunc: function(n) {
    for (var t = n.inputs, e = n.attrs, r = n.backend, i = t.image, a = r, s = S.util.getTypedArrayFromDType(i.dtype, S.util.sizeFromShape(i.shape)), o = i.shape, c = o[0], l = o[1], u = o[2], h = o[3], d = a.data.get(i.dataId).values, p = 0; p < c; p++)
      for (var f = p * u * l * h, m = 0; m < l; m++)
        for (var g = m * (u * h), y = 0; y < u; y++)
          for (var w = y * h, b = 0; b < h; b++) {
            var L = [c, m, y, b], x = L[2], N = Math.round(u - x), I = f + g + w + b, C = d[I];
            if (N >= 0 && N < u) {
              var O = N * h, D = f + g + O + b;
              C = d[D];
            }
            s[I] = C;
          }
    var F = a.write(s, i.shape, i.dtype);
    return {dataId: F, shape: i.shape, dtype: i.dtype};
  }};
  function nF(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.filter, s = t.bias, o = t.preluActivationWeights, c = r.strides, l = r.pad, u = r.dataFormat, h = r.dilations, d = r.dimRoundingMode, p = r.activation, f = jw({inputs: {x: i, filter: a}, backend: e, attrs: {strides: c, pad: l, dataFormat: u, dilations: h, dimRoundingMode: d}});
    if (s) {
      var m = f;
      f = ts({inputs: {a: f, b: s}, backend: e}), e.disposeIntermediateTensorInfo(m);
    }
    if (p) {
      var m = f;
      f = Md(e, f, p, o), e.disposeIntermediateTensorInfo(m);
    }
    return f;
  }
  var rF = {kernelName: S.FusedConv2D, backendName: "cpu", kernelFunc: nF};
  function iF(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.filter, s = t.bias, o = t.preluActivationWeights, c = r.strides, l = r.pad, u = r.dataFormat, h = r.dilations, d = r.dimRoundingMode, p = r.activation, f = $w({inputs: {x: i, filter: a}, backend: e, attrs: {strides: c, pad: l, dataFormat: u, dilations: h, dimRoundingMode: d}});
    if (s) {
      var m = f;
      f = ts({inputs: {a: f, b: s}, backend: e}), e.disposeIntermediateTensorInfo(m);
    }
    if (p) {
      var m = f;
      f = Md(e, f, p, o), e.disposeIntermediateTensorInfo(m);
    }
    return f;
  }
  var aF = {kernelName: S.FusedDepthwiseConv2D, backendName: "cpu", kernelFunc: iF};
  function sF(n) {
    var t = n.inputs, e = n.backend, r = t.input, i = S.util.sizeFromShape(r.shape), a = r.shape[r.shape.length - 1], s = i / a, o = zn({inputs: {x: r}, backend: e, attrs: {shape: [s, a]}}), c = Xw(o, true, e), l = zn({inputs: {x: c}, backend: e, attrs: {shape: r.shape}});
    return e.disposeIntermediateTensorInfo(o), e.disposeIntermediateTensorInfo(c), l;
  }
  var oF = {kernelName: S.IFFT, backendName: "cpu", kernelFunc: sF};
  var cF = je(S.IsFinite, function(n) {
    return Number.isFinite(n) ? 1 : 0;
  }, "bool"), lF = {kernelName: S.IsFinite, backendName: "cpu", kernelFunc: cF};
  var uF = je(S.IsInf, function(n) {
    return Math.abs(n) === Infinity ? 1 : 0;
  }, "bool"), hF = {kernelName: S.IsInf, backendName: "cpu", kernelFunc: uF};
  var dF = je(S.IsNan, function(n) {
    return Number.isNaN(n) ? 1 : 0;
  }, "bool"), pF = {kernelName: S.IsNan, backendName: "cpu", kernelFunc: dF};
  var fF = je(S.Log1p, function(n) {
    return Math.log1p(n);
  }), mF = {kernelName: S.Log1p, backendName: "cpu", kernelFunc: fF};
  var gF = je(S.LogicalNot, function(n) {
    return n ? 0 : 1;
  }, "bool"), yF = {kernelName: S.LogicalNot, backendName: "cpu", kernelFunc: gF};
  var vF = {kernelName: S.Max, backendName: "cpu", kernelFunc: function(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = t.x, a = e, s = a.reductionIndices, o = a.keepDims, c = r, l = i.shape, u = l.length, h = S.util.parseAxisParam(s, l), d = h, p = S.backend_util.getAxesPermutation(d, u), f = c.data.get(i.dataId).values;
    if (p != null) {
      for (var m = new Array(u), g = 0; g < m.length; g++)
        m[g] = l[p[g]];
      f = Pd(f, l, i.dtype, p, m), d = S.backend_util.getInnerMostAxes(d.length, u), l = m;
    }
    ae(i, "max"), S.backend_util.assertAxesAreInnerMostDims("max", d, u);
    var y = S.backend_util.computeOutAndReduceShapes(l, d), w = y[0], b = y[1], L = S.util.sizeFromShape(b), x = Ew(f, L, w, i.dtype), N = c.write(x, w, i.dtype), I = w;
    if (o) {
      var m = S.backend_util.expandShapeToKeepDim(w, h);
      I = m;
    }
    return {dataId: N, shape: I, dtype: i.dtype};
  }};
  function wF(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x;
    ae(i, "maxPool");
    var a = r.filterSize, s = r.strides, o = r.pad, c = r.dimRoundingMode, l = 1;
    S.util.assert(S.backend_util.eitherStridesOrDilationsAreOne(s, l), function() {
      return "Error in maxPool: Either strides or dilations must be 1. " + ("Got strides " + s + " and dilations '" + l + "'");
    });
    var u = S.backend_util.computePool2DInfo(i.shape, a, s, l, o, c), h;
    if (u.filterWidth === 1 && u.filterHeight === 1 && S.util.arraysEqual(u.inShape, u.outShape))
      h = hi({inputs: {x: i}, backend: e});
    else {
      var d = e.data.get(i.dataId).values, p = S.util.computeStrides(i.shape), f = Hd(d, i.shape, i.dtype, p, u, "max");
      h = e.makeTensorInfo(u.outShape, i.dtype, f.values);
    }
    return h;
  }
  var bF = {kernelName: S.MaxPool, backendName: "cpu", kernelFunc: wF};
  function xF(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.dy, a = t.input, s = t.output, o = a;
    ae([a, s], "maxPoolBackprop");
    for (var c = r.filterSize, l = r.strides, u = r.pad, h = r.dimRoundingMode, d = S.backend_util.computePool2DInfo(o.shape, c, l, 1, u, h), p = e.data.get(o.dataId).values, f = S.buffer(d.outShape, o.dtype, Kw(p, o.shape, o.dtype, d).values), m = d.strideHeight, g = d.strideWidth, y = d.dilationHeight, w = d.dilationWidth, b = d.effectiveFilterHeight, L = d.effectiveFilterWidth, x = L - 1 - d.padInfo.left, N = b - 1 - d.padInfo.top, I = S.buffer(o.shape, "float32"), C = e.data.get(i.dataId).values, O = S.buffer(i.shape, "float32", C), D = 0; D < d.batchSize; ++D)
      for (var F = 0; F < d.inChannels; ++F)
        for (var k = 0; k < d.inHeight; ++k)
          for (var B = 0; B < d.inWidth; ++B) {
            for (var V = k - N, P = B - x, G = 0, j = 0; j < b; j += y) {
              var q = (V + j) / m;
              if (q < 0 || q >= d.outHeight || Math.floor(q) !== q)
                continue;
              for (var H = 0; H < L; H += w) {
                var J = (P + H) / g;
                if (J < 0 || J >= d.outWidth || Math.floor(J) !== J)
                  continue;
                var $ = b * L - 1 - f.get(D, q, J, F), ee = j * L + H, te = $ === ee ? 1 : 0;
                if (te === 0)
                  continue;
                var ne = O.get(D, q, J, F);
                G += ne * te;
              }
            }
            I.set(G, D, k, B, F);
          }
    return e.makeTensorInfo(I.shape, I.dtype, I.values);
  }
  var LF = {kernelName: S.MaxPoolBackprop, backendName: "cpu", kernelFunc: xF};
  function SF(n, t, e, r, i) {
    var a = S.util.computeStrides(t), s = Hd(n, t, e, a, i, "max"), o = Kw(n, t, e, i, true, r);
    return [s.values, o.values];
  }
  var IF = {kernelName: S.MaxPoolWithArgmax, backendName: "cpu", kernelFunc: function(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = t.x, a = e, s = a.filterSize, o = a.strides, c = a.pad, l = a.includeBatchInIndex, u = r;
    ae(i, "MaxPoolWithArgmax");
    var h = u.data.get(i.dataId).values, d = S.backend_util.computePool2DInfo(i.shape, s, o, [1, 1], c), p = SF(h, i.shape, i.dtype, l, d), f = p[0], m = p[1], g = u.write(f, d.outShape, i.dtype), y = u.write(m, d.outShape, i.dtype);
    return [{dataId: g, shape: d.outShape, dtype: i.dtype}, {dataId: y, shape: d.outShape, dtype: "int32"}];
  }};
  function AF(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.paddings, s = r.mode;
    ae(i, "mirrorPad");
    for (var o = a.map(function(I, C) {
      return I[0] + i.shape[C] + I[1];
    }), c = a.map(function(I) {
      return I[0];
    }), l = a.map(function(I, C) {
      return I[0] + i.shape[C];
    }), u = s === "reflect" ? 0 : 1, h = e.data.get(i.dataId).values, d = i.shape.length, p = S.util.computeStrides(i.shape), f = S.util.sizeFromShape(o), m = o.length, g = S.util.computeStrides(o), y = S.util.getTypedArrayFromDType(i.dtype, f), w = 0; w < f; w++) {
      for (var b = S.util.indexToLoc(w, m, g), L = 0; L < m; L++)
        b[L] < c[L] ? b[L] = c[L] * 2 - b[L] - u : b[L] >= l[L] && (b[L] = (l[L] - 1) * 2 - b[L] + u);
      b = b.map(function(I, C) {
        return I - c[C];
      });
      var x = S.util.locToIndex(b, d, p);
      y[w] = h[x];
    }
    var N = e.write(y, o, i.dtype);
    return {dataId: N, shape: o, dtype: i.dtype};
  }
  var TF = {kernelName: S.MirrorPad, backendName: "cpu", kernelFunc: AF};
  var NF = S.kernel_impls.nonMaxSuppressionV4Impl, _F = {kernelName: S.NonMaxSuppressionV4, backendName: "cpu", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t, a = i.boxes, s = i.scores, o = r, c = o.maxOutputSize, l = o.iouThreshold, u = o.scoreThreshold, h = o.padToMaxOutputSize, d = e;
    ae(a, "NonMaxSuppressionPadded");
    var p = d.data.get(a.dataId).values, f = d.data.get(s.dataId).values, m = NF(p, f, c, l, u, h), g = m.selectedIndices, y = m.validOutputs;
    return [g, y];
  }};
  var CF = S.kernel_impls.nonMaxSuppressionV5Impl, RF = {kernelName: S.NonMaxSuppressionV5, backendName: "cpu", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t, a = i.boxes, s = i.scores, o = r, c = o.maxOutputSize, l = o.iouThreshold, u = o.scoreThreshold, h = o.softNmsSigma, d = e;
    ae(a, "NonMaxSuppressionWithScore");
    var p = d.data.get(a.dataId).values, f = d.data.get(s.dataId).values, m = c, g = l, y = u, w = h, b = CF(p, f, m, g, y, w), L = b.selectedIndices, x = b.selectedScores;
    return [L, x];
  }};
  function OF(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.paddings, s = r.constantValue;
    ae(i, "pad");
    var o = a.map(function(N, I) {
      return N[0] + i.shape[I] + N[1];
    }), c = a.map(function(N) {
      return N[0];
    }), l = e.data.get(i.dataId).values, u = S.util.sizeFromShape(i.shape), h = i.shape.length, d = S.util.computeStrides(i.shape), p = S.util.sizeFromShape(o), f = o.length, m = S.util.computeStrides(o), g = S.util.getTypedArrayFromDType(i.dtype, p);
    s !== 0 && g.fill(s);
    for (var y = 0; y < u; y++) {
      var w = S.util.indexToLoc(y, h, d), b = w.map(function(N, I) {
        return N + c[I];
      }), L = S.util.locToIndex(b, f, m);
      g[L] = l[y];
    }
    var x = e.write(g, o, i.dtype);
    return {dataId: x, shape: o, dtype: i.dtype};
  }
  var Jw = {kernelName: S.PadV2, backendName: "cpu", kernelFunc: OF};
  var EF = je(S.Reciprocal, function(n) {
    return 1 / n;
  }), DF = {kernelName: S.Reciprocal, backendName: "cpu", kernelFunc: EF};
  var kF = {kernelName: S.RotateWithOffset, backendName: "cpu", kernelFunc: function(n) {
    for (var t = n.inputs, e = n.attrs, r = n.backend, i = t.image, a = e, s = a.radians, o = a.fillValue, c = a.center, l = r, u = S.util.getTypedArrayFromDType(i.dtype, S.util.sizeFromShape(i.shape)), h = i.shape, d = h[0], p = h[1], f = h[2], m = h[3], g = S.backend_util.getImageCenter(c, p, f), y = g[0], w = g[1], b = 255, L = Math.sin(s), x = Math.cos(s), N = l.data.get(i.dataId).values, I = 0; I < d; I++)
      for (var C = I * f * p * m, O = 0; O < p; O++)
        for (var D = O * (f * m), F = 0; F < f; F++)
          for (var k = F * m, B = 0; B < m; B++) {
            var V = [d, O, F, B], P = V[2], G = V[1], j = (P - y) * x - (G - w) * L, q = (P - y) * L + (G - w) * x;
            j = Math.round(j + y), q = Math.round(q + w);
            var H = o;
            if (typeof o != "number" && (B === 3 ? H = b : H = o[B]), j >= 0 && j < f && q >= 0 && q < p) {
              var J = q * (f * m), $ = j * m, ee = C + J + $ + B;
              H = N[ee];
            }
            var te = C + D + k + B;
            u[te] = H;
          }
    var ne = l.write(u, i.shape, i.dtype);
    return {dataId: ne, shape: i.shape, dtype: i.dtype};
  }};
  var FF = je(S.Round, function(n) {
    var t = Math.floor(n);
    return n - t < 0.5 ? Math.floor(n) : n - t > 0.5 ? Math.ceil(n) : t % 2 === 0 ? t : t + 1;
  }), WF = {kernelName: S.Round, backendName: "cpu", kernelFunc: FF};
  var UF = S.backend_util.SELU_SCALEALPHA, BF = S.backend_util.SELU_SCALE, zF = je(S.Selu, function(n) {
    return n >= 0 ? BF * n : UF * (Math.exp(n) - 1);
  }), PF = {kernelName: S.Selu, backendName: "cpu", kernelFunc: zF};
  var MF = je(S.Sigmoid, function(n) {
    return 1 / (1 + Math.exp(-n));
  }), HF = {kernelName: S.Sigmoid, backendName: "cpu", kernelFunc: MF};
  var VF = je(S.Sign, function(n) {
    return n < 0 ? -1 : n > 0 ? 1 : 0;
  }), GF = {kernelName: S.Sign, backendName: "cpu", kernelFunc: VF};
  var qF = je(S.Sin, function(n) {
    return Math.sin(n);
  }), YF = {kernelName: S.Sin, backendName: "cpu", kernelFunc: qF};
  var KF = je(S.Sinh, function(n) {
    return Math.sinh(n);
  }), jF = {kernelName: S.Sinh, backendName: "cpu", kernelFunc: KF};
  var $F = 11920928955078125e-23, Zw = Math.log($F) + 2, XF = je(S.Softplus, function(n) {
    var t = n > -Zw, e = n < Zw, r = Math.exp(n), i;
    return e ? i = r : t ? i = n : i = Math.log(1 + r), i;
  }), JF = {kernelName: S.Softplus, backendName: "cpu", kernelFunc: XF};
  function Qw(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = t.x, a = e.perm;
    ae(i, "transpose");
    for (var s = i.shape.length, o = new Array(s), c = 0; c < o.length; c++)
      o[c] = i.shape[a[c]];
    var l = r.data.get(i.dataId).values, u = Pd(l, i.shape, i.dtype, a, o), h = r.write(u, o, i.dtype);
    return {dataId: h, shape: o, dtype: i.dtype};
  }
  var ZF = {kernelName: S.Transpose, backendName: "cpu", kernelFunc: Qw};
  function QF(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.blockShape, s = r.paddings;
    ae([i], "spaceToBatchND");
    var o = S.util.sizeFromShape(a), c = [[0, 0]];
    c.push.apply(c, s);
    for (var l = 1 + a.length; l < i.shape.length; ++l)
      c.push([0, 0]);
    var u = Jw.kernelFunc({inputs: {x: i}, backend: e, attrs: {paddings: c, constantValue: 0}}), h = S.backend_util.getReshaped(u.shape, a, o, false), d = S.backend_util.getPermuted(h.length, a.length, false), p = S.backend_util.getReshapedPermuted(u.shape, a, o, false), f = {x: u}, m = {shape: h}, g = zn({inputs: f, backend: e, attrs: m}), y = {x: g}, w = {perm: d}, b = Qw({inputs: y, backend: e, attrs: w}), L = {x: b}, x = {shape: p}, N = zn({inputs: L, backend: e, attrs: x});
    return e.disposeIntermediateTensorInfo(u), e.disposeIntermediateTensorInfo(g), e.disposeIntermediateTensorInfo(b), N;
  }
  var eW = {kernelName: S.SpaceToBatchND, backendName: "cpu", kernelFunc: QF};
  var tW = je(S.Sqrt, function(n) {
    return Math.sqrt(n);
  }), nW = {kernelName: S.Sqrt, backendName: "cpu", kernelFunc: tW};
  var rW = {kernelName: S.Square, backendName: "cpu", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = t.x, i = e;
    ae(r, "square");
    for (var a = i.data.get(r.dataId).values, s = new Float32Array(a.length), o = 0; o < a.length; ++o) {
      var c = a[o];
      s[o] = c * c;
    }
    var l = i.write(s, r.shape, r.dtype);
    return {dataId: l, shape: r.shape, dtype: r.dtype};
  }};
  var iW = je(S.Step, function(n, t) {
    var e = t;
    return isNaN(n) ? NaN : n > 0 ? 1 : e.alpha;
  }), aW = {kernelName: S.Step, backendName: "cpu", kernelFunc: iW};
  var sW = je(S.Tan, function(n) {
    return Math.tan(n);
  }), oW = {kernelName: S.Tan, backendName: "cpu", kernelFunc: sW};
  var cW = je(S.Tanh, function(n) {
    return Math.tanh(n);
  }), lW = {kernelName: S.Tanh, backendName: "cpu", kernelFunc: cW};
  function uW(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = e.axis, a = t.x;
    ae(a, "unique");
    var s = r.data.get(a.dataId).values, o = Mw(s, i, a.shape, a.dtype), c = o.outputValues, l = o.outputShape, u = o.indices;
    return [r.makeTensorInfo(l, a.dtype, c), r.makeTensorInfo([u.length], "int32", u)];
  }
  var hW = {kernelName: S.Unique, backendName: "cpu", kernelFunc: uW};
  var dW = [q8, o8, K8, $8, p8, J8, Q8, t9, r9, a9, o9, V8, l9, h8, m8, h9, c8, p9, g9, v9, f9, L9, I9, b9, T9, _9, C9, O9, D9, k9, W9, F9, Vd, U8, Y9, y8, w8, J9, eF, tF, x8, rF, aF, l8, oF, d9, lF, hF, pF, S8, mF, yF, bF, LF, IF, vF, TF, A8, _F, RF, N8, Jw, z8, u8, DF, P8, M8, H8, kF, WF, C8, PF, HF, GF, YF, jF, R8, JF, eW, nW, rW, E8, aW, k8, oW, lW, ZF, hW];
  for (var qd = 0, eb = dW; qd < eb.length; qd++) {
    var pW = eb[qd];
    S.registerKernel(pW);
  }
  Za.MathBackendCPU = Iw;
  Za.shared = F8;
  Za.version_cpu = W8;
});
var M2 = we((Pn) => {
  "use strict";
  Object.defineProperty(Pn, "__esModule", {value: true});
  var _ = Qr();
  var Yd = function(n, t) {
    return Yd = Object.setPrototypeOf || {__proto__: []} instanceof Array && function(e, r) {
      e.__proto__ = r;
    } || function(e, r) {
      for (var i in r)
        r.hasOwnProperty(i) && (e[i] = r[i]);
    }, Yd(n, t);
  };
  function fW(n, t) {
    Yd(n, t);
    function e() {
      this.constructor = n;
    }
    n.prototype = t === null ? Object.create(t) : (e.prototype = t.prototype, new e());
  }
  function Yo(n, t, e, r) {
    function i(a) {
      return a instanceof e ? a : new e(function(s) {
        s(a);
      });
    }
    return new (e || (e = Promise))(function(a, s) {
      function o(u) {
        try {
          l(r.next(u));
        } catch (h) {
          s(h);
        }
      }
      function c(u) {
        try {
          l(r.throw(u));
        } catch (h) {
          s(h);
        }
      }
      function l(u) {
        u.done ? a(u.value) : i(u.value).then(o, c);
      }
      l((r = r.apply(n, t || [])).next());
    });
  }
  function Ko(n, t) {
    var e = {label: 0, sent: function() {
      if (a[0] & 1)
        throw a[1];
      return a[1];
    }, trys: [], ops: []}, r, i, a, s;
    return s = {next: o(0), throw: o(1), return: o(2)}, typeof Symbol == "function" && (s[Symbol.iterator] = function() {
      return this;
    }), s;
    function o(l) {
      return function(u) {
        return c([l, u]);
      };
    }
    function c(l) {
      if (r)
        throw new TypeError("Generator is already executing.");
      for (; e; )
        try {
          if (r = 1, i && (a = l[0] & 2 ? i.return : l[0] ? i.throw || ((a = i.return) && a.call(i), 0) : i.next) && !(a = a.call(i, l[1])).done)
            return a;
          (i = 0, a) && (l = [l[0] & 2, a.value]);
          switch (l[0]) {
            case 0:
            case 1:
              a = l;
              break;
            case 4:
              return e.label++, {value: l[1], done: false};
            case 5:
              e.label++, i = l[1], l = [0];
              continue;
            case 7:
              l = e.ops.pop(), e.trys.pop();
              continue;
            default:
              if (!(a = e.trys, a = a.length > 0 && a[a.length - 1]) && (l[0] === 6 || l[0] === 2)) {
                e = 0;
                continue;
              }
              if (l[0] === 3 && (!a || l[1] > a[0] && l[1] < a[3])) {
                e.label = l[1];
                break;
              }
              if (l[0] === 6 && e.label < a[1]) {
                e.label = a[1], a = l;
                break;
              }
              if (a && e.label < a[2]) {
                e.label = a[2], e.ops.push(l);
                break;
              }
              a[2] && e.ops.pop(), e.trys.pop();
              continue;
          }
          l = t.call(n, e);
        } catch (u) {
          l = [6, u], i = 0;
        } finally {
          r = a = 0;
        }
      if (l[0] & 5)
        throw l[1];
      return {value: l[0] ? l[1] : void 0, done: true};
    }
  }
  var di = {}, Kd = {alpha: false, antialias: false, premultipliedAlpha: false, preserveDrawingBuffer: false, depth: false, stencil: false, failIfMajorPerformanceCaveat: true};
  function nb(n, t) {
    di[n] = t;
  }
  function Mn(n) {
    if (!(n in di)) {
      var t = mW(n);
      if (t !== null)
        di[n] = t;
      else
        return console.log("Could not get context for WebGL version", n), null;
    }
    var e = di[n];
    return e.isContextLost() ? (delete di[n], Mn(n)) : (e.disable(e.DEPTH_TEST), e.disable(e.STENCIL_TEST), e.disable(e.BLEND), e.disable(e.DITHER), e.disable(e.POLYGON_OFFSET_FILL), e.disable(e.SAMPLE_COVERAGE), e.enable(e.SCISSOR_TEST), e.enable(e.CULL_FACE), e.cullFace(e.BACK), di[n]);
  }
  function gW(n) {
    if (typeof OffscreenCanvas != "undefined" && n === 2)
      return new OffscreenCanvas(300, 150);
    if (typeof document != "undefined")
      return document.createElement("canvas");
    throw new Error("Cannot create a canvas in this context");
  }
  function mW(n) {
    if (n !== 1 && n !== 2)
      throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");
    var t = gW(n);
    return t.addEventListener("webglcontextlost", function(e) {
      e.preventDefault(), delete di[n];
    }, false), n === 1 ? t.getContext("webgl", Kd) || t.getContext("experimental-webgl", Kd) : t.getContext("webgl2", Kd);
  }
  var rs;
  (function(n) {
    n[n.DENSE = 0] = "DENSE", n[n.SHARED_BATCH = 1] = "SHARED_BATCH";
  })(rs || (rs = {}));
  var cn;
  (function(n) {
    n[n.RENDER = 0] = "RENDER", n[n.UPLOAD = 1] = "UPLOAD", n[n.PIXELS = 2] = "PIXELS", n[n.DOWNLOAD = 3] = "DOWNLOAD";
  })(cn || (cn = {}));
  var Dt;
  (function(n) {
    n[n.UNPACKED_FLOAT16 = 0] = "UNPACKED_FLOAT16", n[n.UNPACKED_FLOAT32 = 1] = "UNPACKED_FLOAT32", n[n.PACKED_4X1_UNSIGNED_BYTE = 2] = "PACKED_4X1_UNSIGNED_BYTE", n[n.PACKED_2X2_FLOAT32 = 3] = "PACKED_2X2_FLOAT32", n[n.PACKED_2X2_FLOAT16 = 4] = "PACKED_2X2_FLOAT16";
  })(Dt || (Dt = {}));
  function is(n, t) {
    return [t, n];
  }
  function yW(n, t) {
    return n * t;
  }
  function as(n) {
    var t = _.util.sizeFromShape(n), e = Math.ceil(t / 4);
    return _.util.sizeToSquarishShape(e);
  }
  function ea(n, t) {
    return [Math.max(1, Math.ceil(t / 2)), Math.max(1, Math.ceil(n / 2))];
  }
  function vW(n, t) {
    var e = ea(n, t), r = e[0], i = e[1];
    return r * i * 4;
  }
  function jd(n, t) {
    var e = n, r, i, a, s, o, c, l, u, h, d;
    return _.env().getNumber("WEBGL_VERSION") === 2 ? (r = e.R32F, i = e.R16F, a = e.RGBA16F, s = e.RGBA32F, o = e.RED, l = 4, u = 1, h = e.HALF_FLOAT, d = e.FLOAT) : (r = n.RGBA, i = n.RGBA, a = n.RGBA, s = e.RGBA, o = n.RGBA, l = 4, u = 4, h = t != null ? t.HALF_FLOAT_OES : null, d = n.FLOAT), c = n.RGBA, {internalFormatFloat: r, internalFormatHalfFloat: i, internalFormatPackedHalfFloat: a, internalFormatPackedFloat: s, textureFormatFloat: o, downloadTextureFormat: c, downloadUnpackNumChannels: l, defaultNumChannels: u, textureTypeHalfFloat: h, textureTypeFloat: d};
  }
  function de(n, t) {
    var e = t();
    return _.env().getBool("DEBUG") && wW(n), e;
  }
  function wW(n) {
    var t = n.getError();
    if (t !== n.NO_ERROR)
      throw new Error("WebGL Error: " + rb(n, t));
  }
  var bW = 596e-10, xW = 65504;
  function ib(n) {
    return !!(_.env().getBool("WEBGL_RENDER_FLOAT32_ENABLED") || n === 0 || bW < Math.abs(n) && Math.abs(n) < xW);
  }
  function rb(n, t) {
    switch (t) {
      case n.NO_ERROR:
        return "NO_ERROR";
      case n.INVALID_ENUM:
        return "INVALID_ENUM";
      case n.INVALID_VALUE:
        return "INVALID_VALUE";
      case n.INVALID_OPERATION:
        return "INVALID_OPERATION";
      case n.INVALID_FRAMEBUFFER_OPERATION:
        return "INVALID_FRAMEBUFFER_OPERATION";
      case n.OUT_OF_MEMORY:
        return "OUT_OF_MEMORY";
      case n.CONTEXT_LOST_WEBGL:
        return "CONTEXT_LOST_WEBGL";
      default:
        return "Unknown error code " + t;
    }
  }
  function ss(n, t) {
    return tr(n, function() {
      return n.getExtension(t);
    }, 'Extension "' + t + '" not supported on this browser.');
  }
  function ab(n, t) {
    var e = tr(n, function() {
      return n.createShader(n.VERTEX_SHADER);
    }, "Unable to create vertex WebGLShader.");
    if (de(n, function() {
      return n.shaderSource(e, t);
    }), de(n, function() {
      return n.compileShader(e);
    }), n.getShaderParameter(e, n.COMPILE_STATUS) === false)
      throw console.log(n.getShaderInfoLog(e)), new Error("Failed to compile vertex shader.");
    return e;
  }
  function sb(n, t) {
    var e = tr(n, function() {
      return n.createShader(n.FRAGMENT_SHADER);
    }, "Unable to create fragment WebGLShader.");
    if (de(n, function() {
      return n.shaderSource(e, t);
    }), de(n, function() {
      return n.compileShader(e);
    }), n.getShaderParameter(e, n.COMPILE_STATUS) === false)
      throw LW(t, n.getShaderInfoLog(e)), new Error("Failed to compile fragment shader.");
    return e;
  }
  var SW = /ERROR: [0-9]+:([0-9]+):/g;
  function LW(n, t) {
    var e = SW.exec(t);
    if (e == null) {
      console.log("Couldn't parse line number in error: " + t), console.log(n);
      return;
    }
    for (var r = +e[1], i = n.split(`
`), a = i.length.toString().length + 2, s = i.map(function(d, p) {
      return _.util.rightPad((p + 1).toString(), a) + d;
    }), o = 0, c = 0; c < s.length; c++)
      o = Math.max(s[c].length, o);
    var l = s.slice(0, r - 1), u = s.slice(r - 1, r), h = s.slice(r);
    console.log(l.join(`
`)), console.log(t.split(`
`)[0]), console.log("%c " + _.util.rightPad(u[0], o), "border:1px solid red; background-color:#e3d2d2; color:#a61717"), console.log(h.join(`
`));
  }
  function ob(n) {
    return tr(n, function() {
      return n.createProgram();
    }, "Unable to create WebGLProgram.");
  }
  function cb(n, t) {
    if (de(n, function() {
      return n.linkProgram(t);
    }), n.getProgramParameter(t, n.LINK_STATUS) === false)
      throw console.log(n.getProgramInfoLog(t)), new Error("Failed to link vertex and fragment shaders.");
  }
  function jo(n, t) {
    if (de(n, function() {
      return n.validateProgram(t);
    }), n.getProgramParameter(t, n.VALIDATE_STATUS) === false)
      throw console.log(n.getProgramInfoLog(t)), new Error("Shader program validation failed.");
  }
  function lb(n, t) {
    var e = tr(n, function() {
      return n.createBuffer();
    }, "Unable to create WebGLBuffer");
    return de(n, function() {
      return n.bindBuffer(n.ARRAY_BUFFER, e);
    }), de(n, function() {
      return n.bufferData(n.ARRAY_BUFFER, t, n.STATIC_DRAW);
    }), e;
  }
  function ub(n, t) {
    var e = tr(n, function() {
      return n.createBuffer();
    }, "Unable to create WebGLBuffer");
    return de(n, function() {
      return n.bindBuffer(n.ELEMENT_ARRAY_BUFFER, e);
    }), de(n, function() {
      return n.bufferData(n.ELEMENT_ARRAY_BUFFER, t, n.STATIC_DRAW);
    }), e;
  }
  function IW() {
    return _.env().getNumber("WEBGL_VERSION") === 2 ? 1 : 4;
  }
  function hb(n) {
    return tr(n, function() {
      return n.createTexture();
    }, "Unable to create WebGLTexture.");
  }
  function db(n, t) {
    var e = _.env().getNumber("WEBGL_MAX_TEXTURE_SIZE");
    if (n <= 0 || t <= 0) {
      var r = "[" + n + "x" + t + "]";
      throw new Error("Requested texture size " + r + " is invalid.");
    }
    if (n > e || t > e) {
      var r = "[" + n + "x" + t + "]", i = "[" + e + "x" + e + "]";
      throw new Error("Requested texture size " + r + " greater than WebGL maximum on this browser / GPU " + i + ".");
    }
  }
  function pb(n) {
    return tr(n, function() {
      return n.createFramebuffer();
    }, "Unable to create WebGLFramebuffer.");
  }
  function $d(n, t, e, r, i, a, s) {
    var o = n.getAttribLocation(t, e);
    return o === -1 ? false : (de(n, function() {
      return n.bindBuffer(n.ARRAY_BUFFER, r);
    }), de(n, function() {
      return n.vertexAttribPointer(o, i, n.FLOAT, false, a, s);
    }), de(n, function() {
      return n.enableVertexAttribArray(o);
    }), true);
  }
  function mb(n, t, e) {
    fb(n, e), de(n, function() {
      return n.activeTexture(n.TEXTURE0 + e);
    }), de(n, function() {
      return n.bindTexture(n.TEXTURE_2D, t);
    });
  }
  function AW(n, t) {
    fb(n, t), de(n, function() {
      return n.activeTexture(n.TEXTURE0 + t);
    }), de(n, function() {
      return n.bindTexture(n.TEXTURE_2D, null);
    });
  }
  function gb(n, t, e) {
    return tr(n, function() {
      return n.getUniformLocation(t, e);
    }, 'uniform "' + e + '" not present in program.');
  }
  function yb(n, t, e) {
    return n.getUniformLocation(t, e);
  }
  function vb(n, t, e, r) {
    de(n, function() {
      return mb(n, t, r);
    }), de(n, function() {
      return n.uniform1i(e, r);
    });
  }
  function TW(n) {
    de(n, function() {
      return n.bindFramebuffer(n.FRAMEBUFFER, null);
    }), de(n, function() {
      return n.viewport(0, 0, n.canvas.width, n.canvas.height);
    }), de(n, function() {
      return n.scissor(0, 0, n.canvas.width, n.canvas.height);
    });
  }
  function $o(n, t, e) {
    de(n, function() {
      return n.bindFramebuffer(n.FRAMEBUFFER, e);
    }), de(n, function() {
      return n.framebufferTexture2D(n.FRAMEBUFFER, n.COLOR_ATTACHMENT0, n.TEXTURE_2D, t, 0);
    });
  }
  function Xd(n, t) {
    de(n, function() {
      return n.bindFramebuffer(n.FRAMEBUFFER, t);
    }), de(n, function() {
      return n.framebufferTexture2D(n.FRAMEBUFFER, n.COLOR_ATTACHMENT0, n.TEXTURE_2D, null, 0);
    });
  }
  function os(n) {
    var t = n.checkFramebufferStatus(n.FRAMEBUFFER);
    if (t !== n.FRAMEBUFFER_COMPLETE)
      throw new Error("Error binding framebuffer: " + wb(n, t));
  }
  function wb(n, t) {
    switch (t) {
      case n.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:
        return "FRAMEBUFFER_INCOMPLETE_ATTACHMENT";
      case n.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:
        return "FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";
      case n.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:
        return "FRAMEBUFFER_INCOMPLETE_DIMENSIONS";
      case n.FRAMEBUFFER_UNSUPPORTED:
        return "FRAMEBUFFER_UNSUPPORTED";
      default:
        return "unknown error " + t;
    }
  }
  function tr(n, t, e) {
    var r = de(n, function() {
      return t();
    });
    if (r == null)
      throw new Error(e);
    return r;
  }
  function fb(n, t) {
    var e = n.MAX_COMBINED_TEXTURE_IMAGE_UNITS - 1, r = t + n.TEXTURE0;
    if (r < n.TEXTURE0 || r > e) {
      var i = "[gl.TEXTURE0, gl.TEXTURE" + e + "]";
      throw new Error("textureUnit must be in " + i + ".");
    }
  }
  function pi(n, t) {
    return t === void 0 && (t = 2), _.util.sizeFromShape(n.slice(0, n.length - t));
  }
  function fi(n) {
    if (n.length === 0)
      throw Error("Cannot get rows and columns of an empty shape array.");
    return [n.length > 1 ? n[n.length - 2] : 1, n[n.length - 1]];
  }
  function Xo(n) {
    var t = [1, 1, 1], e = n.length === 0 || n.length === 1 && n[0] === 1;
    return e || (t = [pi(n)].concat(fi(n))), t;
  }
  function bb(n, t) {
    var e;
    t === void 0 && (t = false);
    var r = _.env().getNumber("WEBGL_MAX_TEXTURE_SIZE");
    if (t && (r = r * 2, n = n.map(function(l, u) {
      return u >= n.length - 2 ? _.util.nearestLargerEven(n[u]) : n[u];
    }), n.length === 1 && (n = [2, n[0]])), n.length !== 2) {
      var i = _.util.squeezeShape(n);
      n = i.newShape;
    }
    var a = _.util.sizeFromShape(n);
    if (n.length <= 1 && a <= r)
      return [1, a];
    if (n.length === 2 && n[0] <= r && n[1] <= r)
      return n;
    if (n.length === 3 && n[0] * n[1] <= r && n[2] <= r)
      return [n[0] * n[1], n[2]];
    if (n.length === 3 && n[0] <= r && n[1] * n[2] <= r)
      return [n[0], n[1] * n[2]];
    if (n.length === 4 && n[0] * n[1] * n[2] <= r && n[3] <= r)
      return [n[0] * n[1] * n[2], n[3]];
    if (n.length === 4 && n[0] <= r && n[1] * n[2] * n[3] <= r)
      return [n[0], n[1] * n[2] * n[3]];
    if (t) {
      var s = pi(n), o = 2, c = 2;
      return n.length && (e = fi(n), o = e[0], c = e[1]), a = s * (o / 2) * (c / 2), _.util.sizeToSquarishShape(a).map(function(l) {
        return l * 2;
      });
    }
    return _.util.sizeToSquarishShape(a);
  }
  function Jo(n) {
    return n % 2 === 0;
  }
  function cs(n, t) {
    if (n = n.slice(-2), t = t.slice(-2), _.util.arraysEqual(n, t))
      return true;
    if (!n.length || !t.length)
      return true;
    if (n[0] === 0 || n[1] === 0 || t[0] === 0 || t[1] === 0)
      return true;
    if (n.length !== t.length) {
      var e = n.slice(-1)[0], r = t.slice(-1)[0];
      if (e === r)
        return true;
      if (Jo(e) && Jo(r) && (n[0] === 1 || t[0] === 1))
        return true;
    }
    return n[1] === t[1] && Jo(n[0]) && Jo(t[0]);
  }
  var Zo, Qo;
  function xb(n) {
    if (Zo == null) {
      var t = Mn(n);
      Zo = t.getParameter(t.MAX_TEXTURE_SIZE);
    }
    return Zo;
  }
  function NW() {
    Zo = null;
  }
  function _W() {
    Qo = null;
  }
  function Lb(n) {
    if (Qo == null) {
      var t = Mn(n);
      Qo = t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS);
    }
    return Math.min(16, Qo);
  }
  function Sb(n) {
    if (n === 0)
      return 0;
    var t, e = Mn(n);
    return ln(e, "EXT_disjoint_timer_query_webgl2") && n === 2 ? t = 2 : ln(e, "EXT_disjoint_timer_query") ? t = 1 : t = 0, t;
  }
  function ln(n, t) {
    var e = n.getExtension(t);
    return e != null;
  }
  function Jd(n) {
    try {
      var t = Mn(n);
      if (t != null)
        return true;
    } catch (e) {
      return console.log("Error when getting WebGL context: ", e), false;
    }
    return false;
  }
  function Ib(n) {
    if (n === 0)
      return false;
    var t = Mn(n);
    if (n === 1) {
      if (!ln(t, "OES_texture_float"))
        return false;
    } else if (!ln(t, "EXT_color_buffer_float"))
      return false;
    var e = Zd(t);
    return e;
  }
  function Ab(n) {
    if (n === 0)
      return false;
    var t = Mn(n);
    if (n === 1) {
      if (!ln(t, "OES_texture_float"))
        return false;
      if (!ln(t, "WEBGL_color_buffer_float"))
        return false;
    } else {
      if (ln(t, "EXT_color_buffer_float"))
        return Zd(t);
      var e = "EXT_color_buffer_half_float";
      if (ln(t, e)) {
        var r = t.getExtension(e);
        return CW(t, r);
      }
      return false;
    }
    var i = Zd(t);
    return i;
  }
  function Zd(n) {
    var t = jd(n), e = n.createTexture();
    n.bindTexture(n.TEXTURE_2D, e);
    var r = 1, i = 1;
    n.texImage2D(n.TEXTURE_2D, 0, t.internalFormatFloat, r, i, 0, t.textureFormatFloat, t.textureTypeFloat, null);
    var a = n.createFramebuffer();
    n.bindFramebuffer(n.FRAMEBUFFER, a), n.framebufferTexture2D(n.FRAMEBUFFER, n.COLOR_ATTACHMENT0, n.TEXTURE_2D, e, 0);
    var s = n.checkFramebufferStatus(n.FRAMEBUFFER) === n.FRAMEBUFFER_COMPLETE;
    return n.bindTexture(n.TEXTURE_2D, null), n.bindFramebuffer(n.FRAMEBUFFER, null), n.deleteTexture(e), n.deleteFramebuffer(a), s;
  }
  function CW(n, t) {
    var e = jd(n, t), r = n.createTexture();
    n.bindTexture(n.TEXTURE_2D, r);
    var i = 1, a = 1;
    n.texImage2D(n.TEXTURE_2D, 0, e.internalFormatHalfFloat, i, a, 0, e.textureFormatFloat, e.textureTypeHalfFloat, null);
    var s = n.createFramebuffer();
    n.bindFramebuffer(n.FRAMEBUFFER, s), n.framebufferTexture2D(n.FRAMEBUFFER, n.COLOR_ATTACHMENT0, n.TEXTURE_2D, r, 0);
    var o = n.checkFramebufferStatus(n.FRAMEBUFFER) === n.FRAMEBUFFER_COMPLETE;
    return n.bindTexture(n.TEXTURE_2D, null), n.bindFramebuffer(n.FRAMEBUFFER, null), n.deleteTexture(r), n.deleteFramebuffer(s), o;
  }
  function Tb(n) {
    if (n !== 2)
      return false;
    var t = Mn(n), e = t.fenceSync != null;
    return e;
  }
  function ta(n, t) {
    Array.isArray(n) || (n = [n]), n.forEach(function(e) {
      e != null && _.util.assert(e.dtype !== "complex64", function() {
        return t + " does not support complex64 tensors in the WebGL backend.";
      });
    });
  }
  var RW = {__proto__: null, callAndCheck: de, canBeRepresented: ib, getWebGLErrorMessage: rb, getExtensionOrThrow: ss, createVertexShader: ab, createFragmentShader: sb, createProgram: ob, linkProgram: cb, validateProgram: jo, createStaticVertexBuffer: lb, createStaticIndexBuffer: ub, getNumChannels: IW, createTexture: hb, validateTextureSize: db, createFramebuffer: pb, bindVertexBufferToProgramAttribute: $d, bindTextureUnit: mb, unbindTextureUnit: AW, getProgramUniformLocationOrThrow: gb, getProgramUniformLocation: yb, bindTextureToProgramUniformSampler: vb, bindCanvasToFramebuffer: TW, bindColorTextureToFramebuffer: $o, unbindColorTextureFromFramebuffer: Xd, validateFramebuffer: os, getFramebufferErrorMessage: wb, getBatchDim: pi, getRowsCols: fi, getShapeAs3D: Xo, getTextureShapeFromLogicalShape: bb, isReshapeFree: cs, getWebGLMaxTextureSize: xb, resetMaxTextureSize: NW, resetMaxTexturesInShader: _W, getMaxTexturesInShader: Lb, getWebGLDisjointQueryTimerVersion: Sb, hasExtension: ln, isWebGLVersionEnabled: Jd, isCapableOfRenderingToFloatTexture: Ib, isDownloadFloatTextureEnabled: Ab, isWebGLFenceEnabled: Tb, assertNotComplex: ta};
  var Se = _.env();
  Se.registerFlag("HAS_WEBGL", function() {
    return Se.getNumber("WEBGL_VERSION") > 0;
  });
  Se.registerFlag("WEBGL_VERSION", function() {
    return Jd(2) ? 2 : Jd(1) ? 1 : 0;
  });
  Se.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS", function() {
    return false;
  });
  Se.registerFlag("WEBGL_BUFFER_SUPPORTED", function() {
    return Se.get("WEBGL_VERSION") === 2;
  });
  Se.registerFlag("WEBGL_CPU_FORWARD", function() {
    return true;
  });
  Se.registerFlag("WEBGL_FORCE_F16_TEXTURES", function() {
    return false;
  });
  Se.registerFlag("WEBGL_PACK", function() {
    return Se.getBool("HAS_WEBGL");
  });
  Se.registerFlag("WEBGL_PACK_NORMALIZATION", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_PACK_CLIP", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_PACK_DEPTHWISECONV", function() {
    return false;
  });
  Se.registerFlag("WEBGL_PACK_BINARY_OPERATIONS", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_PACK_UNARY_OPERATIONS", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_PACK_REDUCE", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_LAZILY_UNPACK", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_CONV_IM2COL", function() {
    return Se.getBool("WEBGL_PACK");
  });
  Se.registerFlag("WEBGL_MAX_TEXTURE_SIZE", function() {
    return xb(Se.getNumber("WEBGL_VERSION"));
  });
  Se.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER", function() {
    return Lb(Se.getNumber("WEBGL_VERSION"));
  });
  Se.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION", function() {
    var n = Se.getNumber("WEBGL_VERSION");
    return n === 0 ? 0 : Sb(n);
  });
  Se.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE", function() {
    return Se.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") > 0 && !_.device_util.isMobile();
  });
  Se.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE", function() {
    return Ib(Se.getNumber("WEBGL_VERSION"));
  });
  Se.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED", function() {
    return Se.getBool("WEBGL_FORCE_F16_TEXTURES") ? false : Se.getBool("WEBGL_RENDER_FLOAT32_CAPABLE");
  });
  Se.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED", function() {
    return Ab(Se.getNumber("WEBGL_VERSION"));
  });
  Se.registerFlag("WEBGL_FENCE_API_ENABLED", function() {
    return Tb(Se.getNumber("WEBGL_VERSION"));
  });
  Se.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM", function() {
    var n = Se.getBool("WEBGL_RENDER_FLOAT32_ENABLED");
    return n ? 4 : 0;
  });
  Se.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD", function() {
    return -1;
  }, function(n) {
    if (n < 0 && n !== -1)
      throw new Error("WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never " + ("delete) or at least 0, but got " + n + "."));
  });
  function OW(n) {
    const t = new Float32Array(n.length);
    for (let e = 0; e < n.length; ++e)
      t[e] = Math.abs(n[e]);
    return t;
  }
  function Qd(n) {
    return (t, e, r, i, a) => {
      const s = _.backend_util.assertAndGetBroadcastShape(t, e), o = s.length, c = _.util.computeStrides(s), l = _.util.sizeFromShape(s), u = _.util.getTypedArrayFromDType(a, l), h = t.length, d = e.length, p = _.util.computeStrides(t), f = _.util.computeStrides(e), m = _.backend_util.getBroadcastDims(t, s), g = _.backend_util.getBroadcastDims(e, s);
      if (m.length + g.length === 0)
        for (let y = 0; y < u.length; ++y)
          u[y] = n(r[y % r.length], i[y % i.length]);
      else
        for (let y = 0; y < u.length; ++y) {
          const w = _.util.indexToLoc(y, o, c), b = w.slice(-h);
          m.forEach((I) => b[I] = 0);
          const L = _.util.locToIndex(b, h, p), x = w.slice(-d);
          g.forEach((I) => x[I] = 0);
          const N = _.util.locToIndex(x, d, f);
          u[y] = n(r[L], i[N]);
        }
      return [u, s];
    };
  }
  const EW = Qd((n, t) => n + t);
  function na(n) {
    return (t, e, r) => {
      const i = _.util.getTypedArrayFromDType(e, t.length);
      for (let a = 0; a < t.length; ++a)
        i[a] = n(t[a], r);
      return i;
    };
  }
  const DW = na((n) => Math.ceil(n));
  const kW = na((n) => Math.exp(n));
  const FW = na((n) => Math.expm1(n));
  const WW = na((n) => Math.floor(n));
  const UW = na((n) => Math.log(n));
  function BW(n, t, e, r) {
    const i = _.util.getTypedArrayFromDType(r, _.util.sizeFromShape(e));
    for (let a = 0; a < i.length; ++a) {
      const s = a * t;
      let o = n[s];
      for (let c = 0; c < t; ++c) {
        const l = n[s + c];
        l > o && (o = l);
      }
      i[a] = o;
    }
    return i;
  }
  const zW = Qd((n, t) => n * t);
  const PW = na((n) => 1 / Math.sqrt(n));
  function MW(n, t, e, r, i) {
    const a = _.slice_util.isSliceContinous(r, t, e), s = _.util.sizeFromShape(e), o = _.util.computeStrides(r);
    if (a) {
      const l = _.slice_util.computeFlatOffset(t, o);
      return n.subarray(l, l + s);
    }
    const c = _.util.getTypedArrayFromDType(i, s);
    for (let l = 0; l < s; ++l) {
      const u = e.length, h = _.util.computeStrides(e), d = _.util.indexToLoc(l, u, h), p = d.map((m, g) => m + t[g]), f = _.util.locToIndex(p, r.length, o);
      c[l] = n[f];
    }
    return c;
  }
  const HW = Qd((n, t) => n - t);
  function VW(n, t, e, r, i) {
    const a = t.length, s = _.util.sizeFromShape(t), o = _.util.computeStrides(t), c = _.util.computeStrides(i), l = _.util.getTypedArrayFromDType(e, _.util.sizeFromShape(i));
    for (let u = 0; u < s; ++u) {
      const h = _.util.indexToLoc(u, a, o), d = new Array(h.length);
      for (let f = 0; f < d.length; f++)
        d[f] = h[r[f]];
      const p = _.util.locToIndex(d, a, c);
      l[p] = n[u];
    }
    return l;
  }
  function GW(n, t, e, r) {
    const i = _.util.parseAxisParam(t, e)[0], a = [1, e[0], 1];
    for (let f = 0; f < i; f++)
      a[0] *= e[f];
    a[1] = e[i];
    for (let f = i + 1; f < e.length; f++)
      a[2] *= e[f];
    const s = {}, o = new Int32Array(e[i]), c = new _.TensorBuffer(a, r, n), l = [], u = a[0] === 1 && a[2] === 1;
    for (let f = 0; f < e[i]; f++) {
      let m;
      if (u)
        m = n[f].toString();
      else {
        const g = [];
        for (let y = 0; y < a[0]; y++)
          for (let w = 0; w < a[2]; w++)
            g.push(c.get(y, f, w));
        m = g.join(",");
      }
      if (s[m] !== void 0)
        o[f] = s[m];
      else {
        const g = Object.keys(s).length;
        s[m] = g, o[f] = g, l.push(f);
      }
    }
    const h = a.slice();
    h[1] = Object.keys(s).length;
    const d = new _.TensorBuffer(h, r);
    l.forEach((f, m) => {
      for (let g = 0; g < a[0]; g++)
        for (let y = 0; y < a[2]; y++)
          d.set(c.get(g, f, y), g, m, y);
    });
    const p = e.slice();
    return p[i] = h[1], {outputValues: d.values, outputShape: p, indices: o};
  }
  var qW = OW, YW = EW, KW = DW, jW = kW, $W = FW, XW = WW, JW = UW, ZW = BW, QW = zW, eU = PW, tU = MW, nU = HW, ep = VW, rU = GW;
  var iU = function() {
    function n(t, e) {
      this.outputShape = [], this.outputShape = t, this.variableNames = e.map(function(a, s) {
        return "T" + s;
      });
      var r = [];
      this.variableNames.forEach(function(a) {
        r.push("float v" + a + " = get" + a + "AtOutCoords();");
      });
      var i = this.variableNames.map(function(a) {
        return "v" + a;
      }).join(" + ");
      this.userCode = `
      void main() {
        ` + r.join(`
        `) + `

        float result = ` + i + `;
        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var aU = function() {
    function n(t, e) {
      this.outputShape = [], this.packedInputs = true, this.packedOutput = true, this.outputShape = t, this.variableNames = e.map(function(a, s) {
        return "T" + s;
      });
      var r = [];
      this.variableNames.forEach(function(a) {
        r.push("vec4 v" + a + " = get" + a + "AtOutCoords();");
      });
      var i = this.variableNames.map(function(a) {
        return "v" + a;
      }).join(" + ");
      this.userCode = `
      void main() {
        ` + r.join(`
        `) + `

        vec4 result = ` + i + `;
        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var sU = function() {
    function n(t, e, r) {
      this.variableNames = ["A"];
      var i = t.windowSize, a = t.batchSize, s = t.outSize;
      r || this.variableNames.push("bestIndicesA"), this.outputShape = [a, s];
      var o = e === "max" ? ">" : "<", c = r ? "inOffset + i;" : "round(getBestIndicesA(batch, inOffset + i));";
      this.userCode = `
      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ` + i + `;

        int bestIndex = inOffset;
        float bestValue = getA(batch, bestIndex);

        for (int i = 0; i < ` + i + `; i++) {
          int inIdx = ` + c + `;
          float candidate = getA(batch, inIdx);
          if (candidate ` + o + ` bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `;
    }
    return n;
  }();
  function Nb(n, t) {
    return ["x", "y", "z", "w", "u", "v"].slice(0, t).map(function(e) {
      return n + "." + e;
    });
  }
  function Bt(n, t) {
    return t === 1 ? [n] : Nb(n, t);
  }
  function oU(n, t) {
    if (n === 1)
      return "rc";
    for (var e = "", r = 0; r < n; r++)
      e += t[r], r < n - 1 && (e += ",");
    return e;
  }
  function zt() {
    var n, t, e, r, i, a, s, o, c, l;
    return _.env().getNumber("WEBGL_VERSION") === 2 ? (n = "#version 300 es", t = "in", e = "out", r = "in", i = "texture", a = "outputColor", s = "out vec4 outputColor;", o = `
      bool isnan_custom(float val) {
        return (val > 0.0 || val < 0.0) ? false : val != 0.0;
      }

      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan_custom(val.x),
          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
      }

      #define isnan(value) isnan_custom(value)
    `, c = "", l = `
      #define round(value) newRound(value)
      int newRound(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 newRound(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `) : (n = "", t = "attribute", e = "varying", r = "varying", i = "texture2D", a = "gl_FragColor", s = "", o = `
      #define isnan(value) isnan_custom(value)
      bool isnan_custom(float val) {
        return (val > 0. || val < 1. || val == 0.) ? false : true;
      }
      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
      }
    `, c = `
      uniform float INFINITY;

      bool isinf(float val) {
        return abs(val) == INFINITY;
      }
      bvec4 isinf(vec4 val) {
        return equal(abs(val), vec4(INFINITY));
      }
    `, l = `
      int round(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 round(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `), {version: n, attribute: t, varyingVs: e, varyingFs: r, texture2D: i, output: a, defineOutput: s, defineSpecialNaN: o, defineSpecialInf: c, defineRound: l};
  }
  function mi(n, t, e) {
    e === void 0 && (e = "index");
    var r = _.util.computeStrides(t);
    return r.map(function(i, a) {
      var s = "int " + n[a] + " = " + e + " / " + i, o = a === r.length - 1 ? "int " + n[a + 1] + " = " + e + " - " + n[a] + " * " + i : "index -= " + n[a] + " * " + i;
      return s + "; " + o + ";";
    }).join("");
  }
  function tp(n) {
    var t = _.util.computeStrides(n).map(function(e) {
      return e.toString();
    });
    return `
  int getFlatIndex(ivec3 coords) {
    return coords.x * ` + t[0] + " + coords.y * " + t[1] + ` + coords.z;
  }
`;
  }
  var _b = `
  const float FLOAT_MAX = 1.70141184e38;
  const float FLOAT_MIN = 1.17549435e-38;

  lowp vec4 encode_float(highp float v) {
    if (isnan(v)) {
      return vec4(255, 255, 255, 255);
    }

    highp float av = abs(v);

    if(av < FLOAT_MIN) {
      return vec4(0.0, 0.0, 0.0, 0.0);
    } else if(v > FLOAT_MAX) {
      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
    } else if(v < -FLOAT_MAX) {
      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
    }

    highp vec4 c = vec4(0,0,0,0);

    highp float e = floor(log2(av));
    highp float m = exp2(fract(log2(av))) - 1.0;

    c[2] = floor(128.0 * m);
    m -= c[2] / 128.0;
    c[1] = floor(32768.0 * m);
    m -= c[1] / 32768.0;
    c[0] = floor(8388608.0 * m);

    highp float ebias = e + 127.0;
    c[3] = floor(ebias / 2.0);
    ebias -= c[3] * 2.0;
    c[2] += floor(ebias) * 128.0;

    c[3] += 128.0 * step(0.0, -v);

    return c / 255.0;
  }
`;
  var Cb = _.backend_util.getBroadcastDims;
  function gU(n, t, e, r) {
    var i = [];
    n.forEach(function(f) {
      var m = _.util.sizeFromShape(f.shapeInfo.logicalShape);
      f.shapeInfo.isUniform ? i.push("uniform float " + f.name + (m > 1 ? "[" + m + "]" : "") + ";") : (i.push("uniform sampler2D " + f.name + ";"), i.push("uniform int offset" + f.name + ";"));
    });
    var a = i.join(`
`), s = n.map(function(f) {
      return cU(f, t, r);
    }).join(`
`), o = t.texShape, c = zt(), l = hU(c), u, h, d = fU(c);
    t.isPacked ? (u = lU(t.logicalShape, o), h = pU(c)) : (u = uU(t.logicalShape, o), h = dU(c)), r && (d += mU);
    var p = [d, l, h, a, u, s, e].join(`
`);
    return p;
  }
  function ra(n) {
    var t = n.shapeInfo.logicalShape;
    switch (t.length) {
      case 0:
        return yU(n);
      case 1:
        return vU(n);
      case 2:
        return wU(n);
      case 3:
        return bU(n);
      case 4:
        return xU(n);
      case 5:
        return LU(n);
      case 6:
        return SU(n);
      default:
        throw new Error(t.length + "-D input sampling is not yet supported");
    }
  }
  function Rb(n) {
    var t = n.shapeInfo.logicalShape;
    switch (t.length) {
      case 0:
        return IU(n);
      case 1:
        return AU(n);
      case 2:
        return TU(n);
      case 3:
        return NU(n);
      default:
        return _U(n);
    }
  }
  function cU(n, t, e) {
    e === void 0 && (e = false);
    var r = "";
    e ? r += Rb(n) : r += ra(n);
    var i = n.shapeInfo.logicalShape, a = t.logicalShape;
    return i.length <= a.length && (e ? r += CU(n, t) : r += RU(n, t)), r;
  }
  function lU(n, t) {
    switch (n.length) {
      case 0:
        return Ob();
      case 1:
        return OU(n, t);
      case 2:
        return kU(n, t);
      case 3:
        return EU(n, t);
      default:
        return DU(n, t);
    }
  }
  function uU(n, t) {
    switch (n.length) {
      case 0:
        return Ob();
      case 1:
        return FU(n, t);
      case 2:
        return PU(n, t);
      case 3:
        return WU(n, t);
      case 4:
        return UU(n, t);
      case 5:
        return BU(n, t);
      case 6:
        return zU(n, t);
      default:
        throw new Error(n.length + "-D output sampling is not yet supported");
    }
  }
  function hU(n) {
    return `
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ` + n.texture2D + `(textureSampler, uv).r;
    }
  `;
  }
  function dU(n) {
    return `
    void setOutput(float val) {
      ` + n.output + ` = vec4(val, 0, 0, 0);
    }
  `;
  }
  function pU(n) {
    return `
    void setOutput(vec4 val) {
      ` + n.output + ` = val;
    }
  `;
  }
  function fU(n) {
    var t = n.version + `
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ` + n.varyingFs + ` vec2 resultUV;
    ` + n.defineOutput + `
    const vec2 halfCR = vec2(0.5, 0.5);

    struct ivec5
    {
      int x;
      int y;
      int z;
      int w;
      int u;
    };

    struct ivec6
    {
      int x;
      int y;
      int z;
      int w;
      int u;
      int v;
    };

    uniform float NAN;
    ` + n.defineSpecialNaN + `
    ` + n.defineSpecialInf + `
    ` + n.defineRound + `

    int imod(int x, int y) {
      return x - y * (x / y);
    }

    int idiv(int a, int b, float sign) {
      int res = a / b;
      int mod = imod(a, b);
      if (sign < 0. && mod != 0) {
        res -= 1;
      }
      return res;
    }

    //Based on the work of Dave Hoskins
    //https://www.shadertoy.com/view/4djSRW
    #define HASHSCALE1 443.8975
    float random(float seed){
      vec2 p = resultUV * seed;
      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);
      p3 += dot(p3, p3.yzx + 19.19);
      return fract((p3.x + p3.y) * p3.z);
    }

    ` + MU + `
    ` + HU + `
    ` + VU + `
  `;
    return t;
  }
  var MU = `
vec2 uvFromFlat(int texNumR, int texNumC, int index) {
  int texR = index / texNumC;
  int texC = index - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
  int texelIndex = index / 2;
  int texR = texelIndex / texNumC;
  int texC = texelIndex - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`, HU = `
vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
  int texNumC, int row, int col) {
  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
  int texR = texelIndex / texNumC;
  int texC = texelIndex - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`, VU = `
vec2 packedUVfrom3D(int texNumR, int texNumC,
    int texelsInBatch, int texelsInLogicalRow, int b,
    int row, int col) {
  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
  int texR = index / texNumC;
  int texC = index - texR * texNumC;
  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
}
`, mU = `
  float getChannel(vec4 frag, vec2 innerDims) {
    vec2 modCoord = mod(innerDims, 2.);
    return modCoord.x == 0. ?
      (modCoord.y == 0. ? frag.r : frag.g) :
      (modCoord.y == 0. ? frag.b : frag.a);
  }
  float getChannel(vec4 frag, int dim) {
    float modCoord = mod(float(dim), 2.);
    return modCoord == 0. ? frag.r : frag.g;
  }
`;
  function Ob() {
    return `
    int getOutputCoords() {
      return 0;
    }
  `;
  }
  function OU(n, t) {
    var e = [Math.ceil(t[0] / 2), Math.ceil(t[1] / 2)];
    return e[0] === 1 ? `
      int getOutputCoords() {
        return 2 * int(resultUV.x * ` + e[1] + `.0);
      }
    ` : e[1] === 1 ? `
      int getOutputCoords() {
        return 2 * int(resultUV.y * ` + e[0] + `.0);
      }
    ` : `
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(` + e[0] + ", " + e[1] + `));
      return 2 * (resTexRC.x * ` + e[1] + ` + resTexRC.y);
    }
  `;
  }
  function FU(n, t) {
    return t[0] === 1 ? `
      int getOutputCoords() {
        return int(resultUV.x * ` + t[1] + `.0);
      }
    ` : t[1] === 1 ? `
      int getOutputCoords() {
        return int(resultUV.y * ` + t[0] + `.0);
      }
    ` : `
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(` + t[0] + ", " + t[1] + `));
      return resTexRC.x * ` + t[1] + ` + resTexRC.y;
    }
  `;
  }
  function EU(n, t) {
    var e = [Math.ceil(t[0] / 2), Math.ceil(t[1] / 2)], r = Math.ceil(n[2] / 2), i = r * Math.ceil(n[1] / 2);
    return `
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(` + e[0] + ", " + e[1] + `));
      int index = resTexRC.x * ` + e[1] + ` + resTexRC.y;

      int b = index / ` + i + `;
      index -= b * ` + i + `;

      int r = 2 * (index / ` + r + `);
      int c = imod(index, ` + r + `) * 2;

      return ivec3(b, r, c);
    }
  `;
  }
  function WU(n, t) {
    var e = mi(["r", "c", "d"], n);
    return `
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(` + t[0] + ", " + t[1] + `));
      int index = resTexRC.x * ` + t[1] + ` + resTexRC.y;
      ` + e + `
      return ivec3(r, c, d);
    }
  `;
  }
  function DU(n, t) {
    for (var e = [Math.ceil(t[0] / 2), Math.ceil(t[1] / 2)], r = Math.ceil(n[n.length - 1] / 2), i = r * Math.ceil(n[n.length - 2] / 2), a = i, s = "", o = "b, r, c", c = 2; c < n.length - 1; c++)
      a *= n[n.length - c - 1], s = `
      int b` + c + " = index / " + a + `;
      index -= b` + c + " * " + a + `;
    ` + s, o = "b" + c + ", " + o;
    return `
    ivec` + n.length + ` getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(` + e[0] + ", " + e[1] + `));
      int index = resTexRC.x * ` + e[1] + ` + resTexRC.y;

      ` + s + `

      int b = index / ` + i + `;
      index -= b * ` + i + `;

      int r = 2 * (index / ` + r + `);
      int c = imod(index, ` + r + `) * 2;

      return ivec` + n.length + "(" + o + `);
    }
  `;
  }
  function UU(n, t) {
    var e = mi(["r", "c", "d", "d2"], n);
    return `
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(` + t[0] + ", " + t[1] + `));
      int index = resTexRC.x * ` + t[1] + ` + resTexRC.y;
      ` + e + `
      return ivec4(r, c, d, d2);
    }
  `;
  }
  function BU(n, t) {
    var e = mi(["r", "c", "d", "d2", "d3"], n);
    return `
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(` + t[0] + `,
                             ` + t[1] + `));

      int index = resTexRC.x * ` + t[1] + ` + resTexRC.y;

      ` + e + `

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `;
  }
  function zU(n, t) {
    var e = mi(["r", "c", "d", "d2", "d3", "d4"], n);
    return `
    ivec6 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(` + t[0] + ", " + t[1] + `));
      int index = resTexRC.x * ` + t[1] + ` + resTexRC.y;

      ` + e + `

      ivec6 result = ivec6(r, c, d, d2, d3, d4);
      return result;
    }
  `;
  }
  function kU(n, t) {
    var e = [Math.ceil(t[0] / 2), Math.ceil(t[1] / 2)];
    if (_.util.arraysEqual(n, t))
      return `
      ivec2 getOutputCoords() {
        return 2 * ivec2(resultUV.yx * vec2(` + e[0] + ", " + e[1] + `));
      }
    `;
    var r = Math.ceil(n[1] / 2);
    return `
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(` + e[0] + ", " + e[1] + `));

      int index = resTexRC.x * ` + e[1] + ` + resTexRC.y;
      int r = 2 * (index / ` + r + `);
      int c = imod(index, ` + r + `) * 2;

      return ivec2(r, c);
    }
  `;
  }
  function PU(n, t) {
    return _.util.arraysEqual(n, t) ? `
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(` + t[0] + ", " + t[1] + `));
      }
    ` : n[1] === 1 ? `
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(` + t[0] + ", " + t[1] + `));
        int index = resTexRC.x * ` + t[1] + ` + resTexRC.y;
        return ivec2(index, 0);
      }
    ` : n[0] === 1 ? `
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(` + t[0] + ", " + t[1] + `));
        int index = resTexRC.x * ` + t[1] + ` + resTexRC.y;
        return ivec2(0, index);
      }
    ` : `
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(` + t[0] + ", " + t[1] + `));
      int index = resTexRC.x * ` + t[1] + ` + resTexRC.y;
      int r = index / ` + n[1] + `;
      int c = index - r * ` + n[1] + `;
      return ivec2(r, c);
    }
  `;
  }
  function gi(n) {
    return "offset" + n;
  }
  function IU(n) {
    var t = n.name, e = "get" + t.charAt(0).toUpperCase() + t.slice(1), r = zt();
    return `
    vec4 ` + e + `() {
      return ` + r.texture2D + "(" + t + `, halfCR);
    }
  `;
  }
  function yU(n) {
    var t = n.name, e = "get" + t.charAt(0).toUpperCase() + t.slice(1);
    if (n.shapeInfo.isUniform)
      return "float " + e + "() {return " + t + ";}";
    var r = n.shapeInfo.texShape, i = r[0], a = r[1];
    if (i === 1 && a === 1)
      return `
      float ` + e + `() {
        return sampleTexture(` + t + `, halfCR);
      }
    `;
    var s = n.shapeInfo.texShape, o = s[0], c = s[1], l = gi(t);
    return `
    float ` + e + `() {
      vec2 uv = uvFromFlat(` + o + ", " + c + ", " + l + `);
      return sampleTexture(` + t + `, uv);
    }
  `;
  }
  function AU(n) {
    var t = n.name, e = "get" + t.charAt(0).toUpperCase() + t.slice(1), r = n.shapeInfo.texShape, i = [Math.ceil(r[0] / 2), Math.ceil(r[1] / 2)], a = zt();
    return `
    vec4 ` + e + `(int index) {
      vec2 uv = packedUVfrom1D(
        ` + i[0] + ", " + i[1] + `, index);
      return ` + a.texture2D + "(" + t + `, uv);
    }
  `;
  }
  function vU(n) {
    var t = n.name, e = "get" + t.charAt(0).toUpperCase() + t.slice(1);
    if (n.shapeInfo.isUniform)
      return `
      float ` + e + `(int index) {
        ` + ia(n) + `
      }
    `;
    var r = n.shapeInfo.texShape, i = r[0], a = r[1];
    if (a === 1 && i === 1)
      return `
      float ` + e + `(int index) {
        return sampleTexture(` + t + `, halfCR);
      }
    `;
    var s = gi(t);
    return a === 1 ? `
      float ` + e + `(int index) {
        vec2 uv = vec2(0.5, (float(index + ` + s + ") + 0.5) / " + i + `.0);
        return sampleTexture(` + t + `, uv);
      }
    ` : i === 1 ? `
      float ` + e + `(int index) {
        vec2 uv = vec2((float(index + ` + s + ") + 0.5) / " + a + `.0, 0.5);
        return sampleTexture(` + t + `, uv);
      }
    ` : `
    float ` + e + `(int index) {
      vec2 uv = uvFromFlat(` + i + ", " + a + ", index + " + s + `);
      return sampleTexture(` + t + `, uv);
    }
  `;
  }
  function TU(n) {
    var t = n.shapeInfo.logicalShape, e = n.name, r = "get" + e.charAt(0).toUpperCase() + e.slice(1), i = n.shapeInfo.texShape, a = i[0], s = i[1], o = zt();
    if (i != null && _.util.arraysEqual(t, i))
      return `
      vec4 ` + r + `(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(` + s + ".0, " + a + `.0);

        return ` + o.texture2D + "(" + e + `, uv);
      }
    `;
    var c = [Math.ceil(i[0] / 2), Math.ceil(i[1] / 2)], l = Math.ceil(t[1] / 2);
    return `
    vec4 ` + r + `(int row, int col) {
      vec2 uv = packedUVfrom2D(` + l + ", " + c[0] + ", " + c[1] + `, row, col);
      return ` + o.texture2D + "(" + e + `, uv);
    }
  `;
  }
  function wU(n) {
    var t = n.shapeInfo.logicalShape, e = n.name, r = "get" + e.charAt(0).toUpperCase() + e.slice(1), i = n.shapeInfo.texShape;
    if (i != null && _.util.arraysEqual(t, i)) {
      var a = i[0], s = i[1];
      return `
    float ` + r + `(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(` + s + ".0, " + a + `.0);
      return sampleTexture(` + e + `, uv);
    }
  `;
    }
    var o = _.util.squeezeShape(t), c = o.newShape, l = o.keptDims, u = c;
    if (u.length < t.length) {
      var h = aa(n, u), d = ["row", "col"];
      return `
      ` + ra(h) + `
      float ` + r + `(int row, int col) {
        return ` + r + "(" + sa(d, l) + `);
      }
    `;
    }
    if (n.shapeInfo.isUniform)
      return `
      float ` + r + `(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(` + t[1] + `, 1)));
        ` + ia(n) + `
      }
    `;
    var p = i[0], f = i[1], m = gi(e);
    return f === 1 ? `
    float ` + r + `(int row, int col) {
      float index = dot(vec3(row, col, ` + m + "), vec3(" + t[1] + `, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ` + p + `.0);
      return sampleTexture(` + e + `, uv);
    }
  ` : p === 1 ? `
    float ` + r + `(int row, int col) {
      float index = dot(vec3(row, col, ` + m + "), vec3(" + t[1] + `, 1, 1));
      vec2 uv = vec2((index + 0.5) / ` + f + `.0, 0.5);
      return sampleTexture(` + e + `, uv);
    }
  ` : `
  float ` + r + `(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ` + t[1] + " + col + " + m + `;
    vec2 uv = uvFromFlat(` + p + ", " + f + `, index);
    return sampleTexture(` + e + `, uv);
  }
`;
  }
  function NU(n) {
    var t = n.shapeInfo.logicalShape, e = n.name, r = "get" + e.charAt(0).toUpperCase() + e.slice(1), i = n.shapeInfo.texShape, a = [Math.ceil(i[0] / 2), Math.ceil(i[1] / 2)];
    if (t[0] === 1) {
      var s = t.slice(1), o = [1, 2], c = aa(n, s), l = ["b", "row", "col"];
      return `
        ` + Rb(c) + `
        vec4 ` + r + `(int b, int row, int col) {
          return ` + r + "(" + sa(l, o) + `);
        }
      `;
    }
    var u = a[0], h = a[1], d = Math.ceil(t[2] / 2), p = d * Math.ceil(t[1] / 2), f = zt();
    return `
    vec4 ` + r + `(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ` + u + ", " + h + ", " + p + ", " + d + `, b, row, col);
      return ` + f.texture2D + "(" + e + `, uv);
    }
  `;
  }
  function bU(n) {
    var t = n.shapeInfo.logicalShape, e = n.name, r = "get" + e.charAt(0).toUpperCase() + e.slice(1), i = t[1] * t[2], a = t[2], s = _.util.squeezeShape(t), o = s.newShape, c = s.keptDims, l = o;
    if (l.length < t.length) {
      var u = aa(n, l), h = ["row", "col", "depth"];
      return `
        ` + ra(u) + `
        float ` + r + `(int row, int col, int depth) {
          return ` + r + "(" + sa(h, c) + `);
        }
      `;
    }
    if (n.shapeInfo.isUniform)
      return `
      float ` + r + `(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(` + i + ", " + a + `, 1)));
        ` + ia(n) + `
      }
    `;
    var d = n.shapeInfo.texShape, p = d[0], f = d[1], m = n.shapeInfo.flatOffset;
    if (f === i && m == null)
      return `
        float ` + r + `(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(` + a + `, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(` + f + ".0, " + p + `.0);
          return sampleTexture(` + e + `, uv);
        }
      `;
    if (f === a && m == null)
      return `
    float ` + r + `(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(` + t[1] + `, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(` + f + ".0, " + p + `.0);
      return sampleTexture(` + e + `, uv);
    }
  `;
    var g = gi(e);
    return `
      float ` + r + `(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ` + i + " + col * " + a + " + depth + " + g + `;
        vec2 uv = uvFromFlat(` + p + ", " + f + `, index);
        return sampleTexture(` + e + `, uv);
      }
  `;
  }
  function _U(n) {
    for (var t = n.shapeInfo.logicalShape, e = t.length, r = n.name, i = "get" + r.charAt(0).toUpperCase() + r.slice(1), a = n.shapeInfo.texShape, s = [Math.ceil(a[0] / 2), Math.ceil(a[1] / 2)], o = s[0], c = s[1], l = Math.ceil(t[e - 1] / 2), u = l * Math.ceil(t[e - 2] / 2), h = "int b, int row, int col", d = "b * " + u + " + (row / 2) * " + l + " + (col / 2)", p = 2; p < e - 1; p++)
      h = "int b" + p + ", " + h, u *= t[e - p - 1], d = "b" + p + " * " + u + " + " + d;
    var f = zt();
    return `
    vec4 ` + i + "(" + h + `) {
      int index = ` + d + `;
      int texR = index / ` + c + `;
      int texC = index - texR * ` + c + `;
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(` + c + ", " + o + `);
      return ` + f.texture2D + "(" + r + `, uv);
    }
  `;
  }
  function xU(n) {
    var t = n.shapeInfo.logicalShape, e = n.name, r = "get" + e.charAt(0).toUpperCase() + e.slice(1), i = t[3], a = t[2] * i, s = t[1] * a, o = _.util.squeezeShape(t), c = o.newShape, l = o.keptDims;
    if (c.length < t.length) {
      var u = aa(n, c), h = ["row", "col", "depth", "depth2"];
      return `
      ` + ra(u) + `
      float ` + r + `(int row, int col, int depth, int depth2) {
        return ` + r + "(" + sa(h, l) + `);
      }
    `;
    }
    if (n.shapeInfo.isUniform)
      return `
      float ` + r + `(int row, int col, int depth, int depth2) {
        int index = round(dot(vec4(row, col, depth, depth2),
                          vec4(` + s + ", " + a + ", " + i + `, 1)));
        ` + ia(n) + `
      }
    `;
    var d = n.shapeInfo.flatOffset, p = n.shapeInfo.texShape, f = p[0], m = p[1];
    if (m === s && d == null)
      return `
      float ` + r + `(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(` + a + ", " + i + `, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(` + m + ".0, " + f + `.0);
        return sampleTexture(` + e + `, uv);
      }
    `;
    if (m === i && d == null)
      return `
      float ` + r + `(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(` + t[1] * t[2] + ", " + t[2] + `, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(` + m + ".0, " + f + `.0);
        return sampleTexture(` + e + `, uv);
      }
    `;
    var g = gi(e);
    return `
    float ` + r + `(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ` + s + " + col * " + a + ` +
          depth * ` + i + ` + depth2;
      vec2 uv = uvFromFlat(` + f + ", " + m + ", index + " + g + `);
      return sampleTexture(` + e + `, uv);
    }
  `;
  }
  function LU(n) {
    var t = n.shapeInfo.logicalShape, e = n.name, r = "get" + e.charAt(0).toUpperCase() + e.slice(1), i = t[4], a = t[3] * i, s = t[2] * a, o = t[1] * s, c = _.util.squeezeShape(t), l = c.newShape, u = c.keptDims;
    if (l.length < t.length) {
      var h = aa(n, l), d = ["row", "col", "depth", "depth2", "depth3"];
      return `
      ` + ra(h) + `
      float ` + r + `(int row, int col, int depth, int depth2, int depth3) {
        return ` + r + "(" + sa(d, u) + `);
      }
    `;
    }
    if (n.shapeInfo.isUniform)
      return `
      float ` + r + `(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
          vec4(row, col, depth, depth2),
          vec4(` + o + ", " + s + ", " + a + ", " + i + `)) +
          depth3;
        ` + ia(n) + `
      }
    `;
    var p = n.shapeInfo.flatOffset, f = n.shapeInfo.texShape, m = f[0], g = f[1];
    if (g === o && p == null)
      return `
      float ` + r + `(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(` + s + ", " + a + ", " + i + `, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(` + g + ".0, " + m + `.0);
        return sampleTexture(` + e + `, uv);
      }
    `;
    if (g === i && p == null)
      return `
      float ` + r + `(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(` + t[1] * t[2] * t[3] + `,
               ` + t[2] * t[3] + ", " + t[3] + `, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(` + g + ".0, " + m + `.0);
        return sampleTexture(` + e + `, uv);
      }
    `;
    var y = gi(e);
    return `
    float ` + r + `(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ` + o + " + col * " + s + " + depth * " + a + ` +
          depth2 * ` + i + " + depth3 + " + y + `;
      vec2 uv = uvFromFlat(` + m + ", " + g + `, index);
      return sampleTexture(` + e + `, uv);
    }
  `;
  }
  function SU(n) {
    var t = n.shapeInfo.logicalShape, e = n.name, r = "get" + e.charAt(0).toUpperCase() + e.slice(1), i = _.util.squeezeShape(t), a = i.newShape, s = i.keptDims;
    if (a.length < t.length) {
      var o = aa(n, a), c = ["row", "col", "depth", "depth2", "depth3", "depth4"];
      return `
      ` + ra(o) + `
      float ` + r + `(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ` + r + "(" + sa(c, s) + `);
      }
    `;
    }
    var l = t[5], u = t[4] * l, h = t[3] * u, d = t[2] * h, p = t[1] * d;
    if (n.shapeInfo.isUniform)
      return `
      float ` + r + `(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
        int index = round(dot(
          vec4(row, col, depth, depth2),
          vec4(` + p + ", " + d + ", " + h + ", " + u + `)) +
          dot(
            vec2(depth3, depth4),
            vec2(` + l + `, 1)));
        ` + ia(n) + `
      }
    `;
    var f = n.shapeInfo.flatOffset, m = n.shapeInfo.texShape, g = m[0], y = m[1];
    if (y === p && f == null)
      return `
      float ` + r + `(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
          vec4(` + d + ", " + h + ", " + u + ", " + l + `)) +
               float(depth4);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(` + y + ".0, " + g + `.0);
        return sampleTexture(` + e + `, uv);
      }
    `;
    if (y === l && f == null)
      return `
      float ` + r + `(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
          vec4(` + t[1] * t[2] * t[3] * t[4] + `,
               ` + t[2] * t[3] * t[4] + `,
               ` + t[3] * t[4] + `,
               ` + t[4] + `)) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(` + y + ".0, " + g + `.0);
        return sampleTexture(` + e + `, uv);
      }
    `;
    var w = gi(e);
    return `
    float ` + r + `(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ` + p + " + col * " + d + " + depth * " + h + ` +
          depth2 * ` + u + " + depth3 * " + l + " + depth4 + " + w + `;
      vec2 uv = uvFromFlat(` + g + ", " + y + `, index);
      return sampleTexture(` + e + `, uv);
    }
  `;
  }
  function ia(n) {
    var t = n.name, e = _.util.sizeFromShape(n.shapeInfo.logicalShape);
    return e < 2 ? "return " + t + ";" : `
    for (int i = 0; i < ` + e + `; i++) {
      if (i == index) {
        return ` + t + `[i];
      }
    }
  `;
  }
  function CU(n, t) {
    var e = n.name, r = e.charAt(0).toUpperCase() + e.slice(1), i = "get" + r + "AtOutCoords", a = n.shapeInfo.logicalShape.length, s = t.logicalShape.length, o = Cb(n.shapeInfo.logicalShape, t.logicalShape), c = Ze(s), l = s - a, u, h = ["x", "y", "z", "w", "u", "v"];
    a === 0 ? u = "" : s < 2 && o.length >= 1 ? u = "coords = 0;" : u = o.map(function(L) {
      return "coords." + h[L + l] + " = 0;";
    }).join(`
`);
    var d = "";
    s < 2 && a > 0 ? d = "coords" : d = n.shapeInfo.logicalShape.map(function(L, x) {
      return "coords." + h[x + l];
    }).join(", ");
    var p = "return outputValue;", f = _.util.sizeFromShape(n.shapeInfo.logicalShape), m = f === 1, g = _.util.sizeFromShape(t.logicalShape), y = g === 1;
    if (a === 1 && !m && !y)
      p = `
      return vec4(outputValue.xy, outputValue.xy);
    `;
    else if (m && !y)
      s === 1 ? p = `
        return vec4(outputValue.x, outputValue.x, 0., 0.);
      ` : p = `
        return vec4(outputValue.x);
      `;
    else if (o.length) {
      var w = a - 2, b = a - 1;
      o.indexOf(w) > -1 && o.indexOf(b) > -1 ? p = "return vec4(outputValue.x);" : o.indexOf(w) > -1 ? p = "return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);" : o.indexOf(b) > -1 && (p = "return vec4(outputValue.xx, outputValue.zz);");
    }
    return `
    vec4 ` + i + `() {
      ` + c + ` coords = getOutputCoords();
      ` + u + `
      vec4 outputValue = get` + r + "(" + d + `);
      ` + p + `
    }
  `;
  }
  function RU(n, t) {
    var e = n.name, r = e.charAt(0).toUpperCase() + e.slice(1), i = "get" + r + "AtOutCoords", a = t.texShape, s = n.shapeInfo.texShape, o = n.shapeInfo.logicalShape.length, c = t.logicalShape.length;
    if (!n.shapeInfo.isUniform && o === c && n.shapeInfo.flatOffset == null && _.util.arraysEqual(s, a))
      return `
      float ` + i + `() {
        return sampleTexture(` + e + `, resultUV);
      }
    `;
    var l = Ze(c), u = Cb(n.shapeInfo.logicalShape, t.logicalShape), h = c - o, d, p = ["x", "y", "z", "w", "u", "v"];
    o === 0 ? d = "" : c < 2 && u.length >= 1 ? d = "coords = 0;" : d = u.map(function(m) {
      return "coords." + p[m + h] + " = 0;";
    }).join(`
`);
    var f = "";
    return c < 2 && o > 0 ? f = "coords" : f = n.shapeInfo.logicalShape.map(function(m, g) {
      return "coords." + p[g + h];
    }).join(", "), `
    float ` + i + `() {
      ` + l + ` coords = getOutputCoords();
      ` + d + `
      return get` + r + "(" + f + `);
    }
  `;
  }
  function Ze(n) {
    if (n <= 1)
      return "int";
    if (n === 2)
      return "ivec2";
    if (n === 3)
      return "ivec3";
    if (n === 4)
      return "ivec4";
    if (n === 5)
      return "ivec5";
    if (n === 6)
      return "ivec6";
    throw Error("GPU for rank " + n + " is not yet supported");
  }
  function aa(n, t) {
    var e = JSON.parse(JSON.stringify(n));
    return e.shapeInfo.logicalShape = t, e;
  }
  function sa(n, t) {
    return t.map(function(e) {
      return n[e];
    }).join(", ");
  }
  var GU = function() {
    function n(t, e, r, i) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = true, _.util.assert(t.length > 2, function() {
        return "Packed arg" + (r.charAt(0).toUpperCase() + r.slice(1)) + " supports only inputs with rank above 2.";
      });
      var a = t[t.length - 1], s = Math.ceil(a / e);
      this.outputShape = t.slice(0, -1), s > 1 && this.outputShape.push(s), i || this.variableNames.push("bestIndicesA");
      var o = this.outputShape, c = o.length, l = Ze(c), u = Bt("coords", c), h, d;
      if (s === 1) {
        d = c + 1;
        var p = Ze(d);
        h = `
        ` + p + " sourceLocR = " + p + "(" + u.join() + `, 0);
        ++` + u[c - 1] + `;
        ` + p + " sourceLocG = " + p + "(" + u.join() + `, 0);
        ++` + u[c - 2] + `;
        ` + p + " sourceLocA = " + p + "(" + u.join() + `, 0);
        --` + u[c - 1] + `;
        ` + p + " sourceLocB = " + p + "(" + u.join() + `, 0);
        --` + u[c - 2] + ";";
      } else
        d = c, h = `
        ` + l + ` sourceLocR = coords;
        ++` + u[c - 1] + `;
        ` + l + ` sourceLocG = coords;
        ++` + u[c - 2] + `;
        ` + l + ` sourceLocA = coords;
        --` + u[c - 1] + `;
        ` + l + ` sourceLocB = coords;
        --` + u[c - 2] + ";";
      var f = ["x", "y", "z", "w", "u", "v"].slice(0, d), m = "." + f[d - 1], g = f.map(function(O) {
        return "int " + O;
      }), y = Bt("sourceLocR", d - 1).concat("inIdx.r"), w = Bt("sourceLocG", d - 1).concat("inIdx.g"), b = Bt("sourceLocB", d - 1).concat("inIdx.b"), L = Bt("sourceLocA", d - 1).concat("inIdx.a"), x = r === "max" ? "greaterThan" : "lessThan", N = i ? "" : `
          inIdx = round(vec4(getBestIndicesAChannel(` + y.join() + `),
                             getBestIndicesAChannel(` + w.join() + `),
                             getBestIndicesAChannel(` + b.join() + `),
                             getBestIndicesAChannel(` + L.join() + ")));", I = `vec4(
            getAChannel(` + y.join() + `),
            hasNextCol ? getAChannel(` + w.join() + `) : 0.,
            hasNextRow ? getAChannel(` + b.join() + `) : 0.,
            hasNextRow && hasNextCol ? getAChannel(` + L.join() + ") : 0.)", C = i ? "" : `
      float getBestIndicesAChannel(` + g.join() + `) {
        return getChannel(getBestIndicesA(` + f.join() + `),
                                          vec2(` + f.slice(-2).join() + `));
      }`;
      this.userCode = `
      float getAChannel(` + g.join() + `) {
        return getChannel(getA(` + f.join() + `),
                               vec2(` + f.slice(-2).join() + `));
      }
      ` + C + `
      void main() {
        ` + l + ` coords = getOutputCoords();
        bool hasNextCol = ` + u[c - 1] + " < " + (o[c - 1] - 1) + `;
        bool hasNextRow = ` + u[c - 2] + " < " + (o[c - 2] - 1) + `;
        ` + h + `
        ivec4 srcIdx = ivec4(sourceLocR` + m + ", sourceLocG" + m + `,
          sourceLocB` + m + ", sourceLocA" + m + ") * " + e + `;
        ivec4 inIdx = srcIdx;
        vec4 bestIndex = vec4(inIdx);
        vec4 bestValue = ` + I + `;

        for (int i = 0; i < ` + e + `; i++) {
          inIdx = srcIdx;
          ` + N + `
          vec4 candidate = ` + I + `;
          bvec4 nan = isnan(candidate);
          bvec4 replace = bvec4(
            vec4(` + x + `(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));

          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
                           replace.y  ? candidate.y : bestValue.y,
                           replace.z  ? candidate.z : bestValue.z,
                           replace.w  ? candidate.w : bestValue.w);
          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
          srcIdx++;
        }
        setOutput(bestIndex);
      }
    `;
    }
    return n;
  }();
  var qU = function() {
    function n(t) {
      this.variableNames = ["dy"], this.outputShape = t.inShape;
      var e = t.filterHeight, r = t.filterWidth, i = t.strideHeight, a = t.strideWidth, s = t.dilationHeight, o = t.dilationWidth, c = t.effectiveFilterHeight, l = t.effectiveFilterWidth, u = c - 1 - t.padInfo.top, h = l - 1 - t.padInfo.left, d = 1 / (e * r);
      this.userCode = `
      const ivec2 pads = ivec2(` + u + ", " + h + `);
      const float avgMultiplier = float(` + d + `);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ` + c + `;
            wR += ` + s + `) {
          float dyR = float(dyRCorner + wR) / ` + i + `.0;

          if (dyR < 0.0 || dyR >= ` + t.outHeight + `.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ` + l + `;
            wC+= ` + o + `) {
            float dyC = float(dyCCorner + wC) / ` + a + `.0;

            if (dyC < 0.0 || dyC >= ` + t.outWidth + `.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);

            dotProd += dyValue * avgMultiplier;
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }(), YU = function() {
    function n(t) {
      this.variableNames = ["dy"], this.outputShape = t.inShape;
      var e = t.filterDepth, r = t.filterHeight, i = t.filterWidth, a = t.strideDepth, s = t.strideHeight, o = t.strideWidth, c = t.dilationDepth, l = t.dilationHeight, u = t.dilationWidth, h = t.effectiveFilterDepth, d = t.effectiveFilterHeight, p = t.effectiveFilterWidth, f = h - 1 - t.padInfo.front, m = d - 1 - t.padInfo.top, g = p - 1 - t.padInfo.left, y = 1 / (e * r * i);
      this.userCode = `
      const ivec3 pads = ivec3(` + f + ", " + m + ", " + g + `);
      const float avgMultiplier = float(` + y + `);

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ` + h + `;
            wD += ` + c + `) {
          float dyD = float(dyDCorner + wD) / ` + a + `.0;

          if (dyD < 0.0 || dyD >= ` + t.outDepth + `.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ` + d + `;
              wR += ` + l + `) {
            float dyR = float(dyRCorner + wR) / ` + s + `.0;

            if (dyR < 0.0 || dyR >= ` + t.outHeight + `.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ` + p + `;
                wC += ` + u + `) {
              float dyC = float(dyCCorner + wC) / ` + o + `.0;

              if (dyC < 0.0 || dyC >= ` + t.outWidth + `.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);

              dotProd += dyValue * avgMultiplier;
            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }();
  var Eb = `
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`, KU = `
  float s = sign(a) * sign(b);
  int ia = round(a);
  int ib = round(b);
  if (ib != 0) {
    // Windows (D3D) wants guaranteed non-zero int division at compile-time.
    return float(idiv(ia, ib, s));
  } else {
    return NAN;
  }
`, jU = `
if(a < 0.0 && floor(b) < b){
  return NAN;
}
if (b == 0.0) {
  return 1.0;
}
return (round(mod(b, 2.0)) != 1) ?
    pow(abs(a), b) : sign(a) * pow(abs(a), b);
`, $U = "return float(a == b);", XU = "return float(a < b);", JU = "return float(a <= b);", ZU = "return float(a > b);", QU = "return float(a >= b);", eB = "return float(a >= 1.0 && b >= 1.0);", tB = "return float(a >= 1.0 || b >= 1.0);", nB = Eb + `
  return max(a, b);
`, rB = Eb + `
  return min(a, b);
`, iB = `if (b == 0.0) return NAN;
  return mod(a, b);`, aB = "return (b >= 1.0) ? a : a * (b + 1.0);", Db = "return (a < 0.) ? b * a : a;", Wt = function() {
    function n(t, e, r) {
      this.variableNames = ["A", "B"], this.outputShape = _.backend_util.assertAndGetBroadcastShape(e, r), this.userCode = `
      float binaryOperation(float a, float b) {
        ` + t + `
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `;
    }
    return n;
  }();
  var ec = `
  result.r = isNaN.r > 0. ? NAN : result.r;
  result.g = isNaN.g > 0. ? NAN : result.g;
  result.b = isNaN.b > 0. ? NAN : result.b;
  result.a = isNaN.a > 0. ? NAN : result.a;
`, sB = `
  ivec4 ia = round(a);
  ivec4 ib = round(b);
  bvec4 cond = notEqual(ib, ivec4(0));
  ivec4 result = ivec4(0);
  vec4 s = sign(a) * sign(b);

  // Windows (D3D) wants guaranteed non-zero int division at compile-time.
  if (cond[0]) {
    result[0] = idiv(ia[0], ib[0], s[0]);
  }
  if (cond[1]) {
    result[1] = idiv(ia[1], ib[1], s[1]);
  }
  if (cond[2]) {
    result[2] = idiv(ia[2], ib[2], s[2]);
  }
  if (cond[3]) {
    result[3] = idiv(ia[3], ib[3], s[3]);
  }
  return vec4(result);
`, oB = `
  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
  vec4 result = multiplier * pow(abs(a), b);

  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
  bvec4 isExpZero = equal(b, vec4(0.0));
  result.r = isExpZero.r ? 1.0 : result.r;
  result.g = isExpZero.g ? 1.0 : result.g;
  result.b = isExpZero.b ? 1.0 : result.b;
  result.a = isExpZero.a ? 1.0 : result.a;

  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
  ` + ec + `
  return result;
`, kb = `
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`, cB = `
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`, lB = `
  return vec4(equal(a, b));
`, uB = `
  return vec4(lessThan(a, b));
`, hB = `
  return vec4(lessThanEqual(a, b));
`, dB = `
  return vec4(greaterThan(a, b));
`, pB = `
  return vec4(greaterThanEqual(a, b));
`, fB = `
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`, mB = `
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`, gB = `
  vec4 result = vec4(max(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  ` + ec + `
  return result;
`, yB = `
  vec4 result = vec4(min(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  ` + ec + `
  return result;
`, vB = `
  vec4 result = mod(a, b);
  vec4 isNaN = vec4(equal(b, vec4(0.0)));
  ` + ec + `
  return result;
`, nr = function() {
    function n(t, e, r, i) {
      i === void 0 && (i = false), this.variableNames = ["A", "B"], this.supportsBroadcasting = true, this.packedInputs = true, this.packedOutput = true, this.outputShape = _.backend_util.assertAndGetBroadcastShape(e, r);
      var a = this.outputShape.length, s = "";
      if (i)
        if (a === 0 || _.util.sizeFromShape(this.outputShape) === 1)
          s = `
          result.y = 0.;
          result.z = 0.;
          result.w = 0.;
        `;
        else {
          var o = Ze(a);
          if (s = `
          ` + o + ` coords = getOutputCoords();
        `, a === 1)
            s += `
            result.y = (coords + 1) >= ` + this.outputShape[0] + ` ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;
          else {
            var c = Bt("coords", a);
            s += `
            bool nextRowOutOfBounds =
              (` + c[a - 2] + " + 1) >= " + this.outputShape[a - 2] + `;
            bool nextColOutOfBounds =
              (` + c[a - 1] + " + 1) >= " + this.outputShape[a - 1] + `;
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `;
          }
        }
      this.userCode = `
      vec4 binaryOperation(vec4 a, vec4 b) {
        ` + t + `
      }

      void main() {
        vec4 a = getAAtOutCoords();
        vec4 b = getBAtOutCoords();

        vec4 result = binaryOperation(a, b);
        ` + s + `

        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var wB = function() {
    function n(t) {
      this.variableNames = ["A"], this.outputShape = t, this.userCode = `
      uniform float minVal;
      uniform float maxVal;

      void main() {
        float value = getAAtOutCoords();
        if (isnan(value)) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, minVal, maxVal));
      }
    `;
    }
    return n.prototype.getCustomSetupFunc = function(t, e) {
      var r = this;
      return function(i, a) {
        r.minLoc == null && (r.minLoc = i.getUniformLocationNoThrow(a, "minVal"), r.maxLoc = i.getUniformLocationNoThrow(a, "maxVal")), i.gl.uniform1f(r.minLoc, t), i.gl.uniform1f(r.maxLoc, e);
      };
    }, n;
  }();
  var bB = function() {
    function n(t) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = true, this.outputShape = t, this.userCode = `
      uniform float minVal;
      uniform float maxVal;

      void main() {
        vec4 value = getAAtOutCoords();

        if (any(isnan(value))) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
      }
    `;
    }
    return n.prototype.getCustomSetupFunc = function(t, e) {
      var r = this;
      return function(i, a) {
        r.minLoc == null && (r.minLoc = i.getUniformLocationNoThrow(a, "minVal"), r.maxLoc = i.getUniformLocationNoThrow(a, "maxVal")), i.gl.uniform1f(r.minLoc, t), i.gl.uniform1f(r.maxLoc, e);
      };
    }, n;
  }();
  var xB = function() {
    function n(t) {
      this.variableNames = ["real", "imag"], this.outputShape = t, this.userCode = `
      void main() {
        float re = abs(getRealAtOutCoords());
        float im = abs(getImagAtOutCoords());
        float mx = max(re, im);

        // sadly the length function in glsl is not underflow-safe
        // (at least not on Intel GPUs). So the safe solution is
        // to ensure underflow-safety in all cases.
        setOutput(
          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
        );
      }
    `;
    }
    return n;
  }();
  var LB = function() {
    function n(t) {
      this.variableNames = ["x", "dy"], this.outputShape = t.filterShape;
      var e = t.strideHeight, r = t.strideWidth, i = t.padInfo.top, a = t.padInfo.left, s = t.dataFormat === "channelsLast";
      this.userCode = `
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int d2 = coords.w;

        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int b = 0; b < ` + t.batchSize + `; b++) {
          for (int yR = 0; yR < ` + t.outHeight + `; yR++) {
            int xR = wR + yR * ` + e + " - " + i + `;

            if (xR < 0 || xR >= ` + t.inHeight + `) {
              continue;
            }

            for (int yC = 0; yC < ` + t.outWidth + `; yC++) {
              int xC = wC + yC * ` + r + " - " + a + `;

              if (xC < 0 || xC >= ` + t.inWidth + `) {
                continue;
              }

              if (` + s + `) {
                float dyValue = getDy(b, yR, yC, d2);
                float xValue = getX(b, xR, xC, d1);
                dotProd += (xValue * dyValue);
              } else {
                float dyValue = getDy(b, d2, yR, yC);
                float xValue = getX(b, d1, xR, xC);
                dotProd += (xValue * dyValue);
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }(), SB = function() {
    function n(t) {
      this.variableNames = ["dy", "W"], this.outputShape = t.inShape;
      var e = t.filterHeight, r = t.filterWidth, i = t.strideHeight, a = t.strideWidth, s = t.dataFormat === "channelsLast", o = e - 1 - t.padInfo.top, c = r - 1 - t.padInfo.left, l = s ? 1 : 2, u = s ? 2 : 3, h = s ? 3 : 1;
      this.userCode = `
      const ivec2 pads = ivec2(` + o + ", " + c + `);

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[` + h + `];

        ivec2 dyCorner = ivec2(coords[` + l + "], coords[" + u + `]) - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ` + e + `; wR++) {
          float dyR = float(dyRCorner + wR) / ` + i + `.0;

          if (dyR < 0.0 || dyR >= ` + t.outHeight + `.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ` + e + ` - 1 - wR;

          for (int wC = 0; wC < ` + r + `; wC++) {
            float dyC = float(dyCCorner + wC) / ` + a + `.0;

            if (dyC < 0.0 || dyC >= ` + t.outWidth + `.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ` + r + ` - 1 - wC;

            for (int d2 = 0; d2 < ` + t.outChannels + `; d2++) {

              if (` + s + `) {
                float xValue = getDy(batch, idyR, idyC, d2);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              } else {
                float xValue = getDy(batch, d2, idyR, idyC);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }(), IB = function() {
    function n(t) {
      this.variableNames = ["x", "dy"], this.outputShape = t.filterShape;
      var e = t.strideDepth, r = t.strideHeight, i = t.strideWidth, a = t.padInfo.front, s = t.padInfo.top, o = t.padInfo.left;
      this.userCode = `
      void main() {
        ivec5 coords = getOutputCoords();
        int wF = coords.x;
        int wR = coords.y;
        int wC = coords.z;
        int d1 = coords.w;
        int d2 = coords.u;

        float dotProd = 0.0;

        for (int b = 0; b < ` + t.batchSize + `; b++) {
          for (int yF = 0; yF < ` + t.outDepth + `; yF++) {
            int xF = wF + yF * ` + e + " - " + a + `;

            if (xF < 0 || xF >= ` + t.inDepth + `) {
              continue;
            }

            for (int yR = 0; yR < ` + t.outHeight + `; yR++) {
              int xR = wR + yR * ` + r + " - " + s + `;

              if (xR < 0 || xR >= ` + t.inHeight + `) {
                continue;
              }

              for (int yC = 0; yC < ` + t.outWidth + `; yC++) {
                int xC = wC + yC * ` + i + " - " + o + `;

                if (xC < 0 || xC >= ` + t.inWidth + `) {
                  continue;
                }

                float dyValue = getDy(b, yF, yR, yC, d2);
                float xValue = getX(b, xF, xR, xC, d1);
                dotProd += (xValue * dyValue);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }(), AB = function() {
    function n(t) {
      this.variableNames = ["dy", "W"], this.outputShape = t.inShape;
      var e = t.filterDepth, r = t.filterHeight, i = t.filterWidth, a = t.strideDepth, s = t.strideHeight, o = t.strideWidth, c = e - 1 - t.padInfo.front, l = r - 1 - t.padInfo.top, u = i - 1 - t.padInfo.left;
      this.userCode = `
      const ivec3 pads = ivec3(` + c + ", " + l + ", " + u + `);

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.u;


        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyFCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        float dotProd = 0.0;
        for (int wF = 0; wF < ` + e + `; wF++) {
          float dyF = float(dyFCorner + wF) / ` + a + `.0;

          if (dyF < 0.0 || dyF >= ` + t.outDepth + `.0 || fract(dyF) > 0.0) {
            continue;
          }
          int idyF = int(dyF);

          int wFPerm = ` + e + ` - 1 - wF;

          for (int wR = 0; wR < ` + r + `; wR++) {
            float dyR = float(dyRCorner + wR) / ` + s + `.0;

            if (dyR < 0.0 || dyR >= ` + t.outHeight + `.0 ||
              fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            int wRPerm = ` + r + ` - 1 - wR;

            for (int wC = 0; wC < ` + i + `; wC++) {
              float dyC = float(dyCCorner + wC) / ` + o + `.0;

              if (dyC < 0.0 || dyC >= ` + t.outWidth + `.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              int wCPerm = ` + i + ` - 1 - wC;

              for (int d2 = 0; d2 < ` + t.outChannels + `; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }();
  var TB = function() {
    function n(t) {
      this.variableNames = ["x", "dy"], this.outputShape = t.filterShape;
      var e = t.strideHeight, r = t.strideWidth, i = t.padInfo.top, a = t.padInfo.left, s = t.outChannels / t.inChannels;
      this.userCode = `
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int dm = coords.w;
        int d2 = d1 * ` + s + ` + dm;

        float dotProd = 0.0;

        // TO DO: Vec4 over the batch size
        for (int b = 0; b < ` + t.batchSize + `; b++) {
          for (int yR = 0; yR < ` + t.outHeight + `; yR++) {
            int xR = wR + yR * ` + e + " - " + i + `;

            if (xR < 0 || xR >= ` + t.inHeight + `) {
              continue;
            }

            for (int yC = 0; yC < ` + t.outWidth + `; yC++) {
              int xC = wC + yC * ` + r + " - " + a + `;

              if (xC < 0 || xC >= ` + t.inWidth + `) {
                continue;
              }

              float dyValue = getDy(b, yR, yC, d2);
              float xValue = getX(b, xR, xC, d1);
              dotProd += (xValue * dyValue);
            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }(), NB = function() {
    function n(t) {
      this.variableNames = ["dy", "W"], this.outputShape = t.inShape;
      var e = t.filterHeight, r = t.filterWidth, i = t.strideHeight, a = t.strideWidth, s = e - 1 - t.padInfo.top, o = r - 1 - t.padInfo.left, c = t.outChannels / t.inChannels;
      this.userCode = `
      const ivec2 pads = ivec2(` + s + ", " + o + `);

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[3];
        ivec2 dyCorner = coords.yz - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        float dotProd = 0.0;

        for (int wR = 0; wR < ` + e + `; wR++) {
          float dyR = float(dyRCorner + wR) / ` + i + `.0;

          if (dyR < 0.0 || dyR >= ` + t.outHeight + `.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ` + e + ` - 1 - wR;

          for (int wC = 0; wC < ` + r + `; wC++) {
            float dyC = float(dyCCorner + wC) / ` + a + `.0;

            if (dyC < 0.0 || dyC >= ` + t.outWidth + `.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ` + r + ` - 1 - wC;

            // TO DO: Vec4 over the channelMul
            for (int dm = 0; dm < ` + c + `; dm++) {
              int d2 = d1 * ` + c + ` + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }();
  var Fb = function() {
    function n(t, e, r, i) {
      e === void 0 && (e = false), r === void 0 && (r = null), i === void 0 && (i = false), this.variableNames = ["x", "W"], this.outputShape = t.outShape;
      var a = t.padInfo.top, s = t.padInfo.left, o = t.strideHeight, c = t.strideWidth, l = t.dilationHeight, u = t.dilationWidth, h = t.filterHeight, d = t.filterWidth, p = Math.floor(t.inChannels / 4) * 4, f = t.inChannels % 4, m = t.dataFormat === "channelsLast", g = m ? 1 : 2, y = m ? 2 : 3, w = m ? 3 : 1, b = "", L = "";
      r && (i ? b = `float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ` + r + `
        }` : b = `
          float activation(float x) {
            ` + r + `
          }
        `, L = "result = activation(result);");
      var x = e ? "result += getBiasAtOutCoords();" : "";
      e && this.variableNames.push("bias"), i && this.variableNames.push("preluActivationWeights"), this.userCode = `
      ` + b + `

      const ivec2 strides = ivec2(` + o + ", " + c + `);
      const ivec2 pads = ivec2(` + a + ", " + s + `);

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d2 = coords[` + w + `];

        ivec2 xRCCorner =
            ivec2(coords[` + g + "], coords[" + y + `]) * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ` + h + `; wR++) {
          int xR = xRCorner + wR * ` + l + `;

          if (xR < 0 || xR >= ` + t.inHeight + `) {
            continue;
          }

          for (int wC = 0; wC < ` + d + `; wC++) {
            int xC = xCCorner + wC * ` + u + `;

            if (xC < 0 || xC >= ` + t.inWidth + `) {
              continue;
            }

            for (int d1 = 0; d1 < ` + p + `; d1 += 4) {
              vec4 wValues = vec4(
                getW(wR, wC, d1, d2),
                getW(wR, wC, d1 + 1, d2),
                getW(wR, wC, d1 + 2, d2),
                getW(wR, wC, d1 + 3, d2)
              );

              if (` + m + `) {
                vec4 xValues = vec4(
                  getX(batch, xR, xC, d1),
                  getX(batch, xR, xC, d1 + 1),
                  getX(batch, xR, xC, d1 + 2),
                  getX(batch, xR, xC, d1 + 3)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec4 xValues = vec4(
                  getX(batch, d1, xR, xC),
                  getX(batch, d1 + 1, xR, xC),
                  getX(batch, d1 + 2, xR, xC),
                  getX(batch, d1 + 3, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }
            }

            if (` + (f === 1) + `) {

              if (` + m + `) {
                dotProd +=
                    getX(batch, xR, xC, ` + p + `) *
                    getW(wR, wC, ` + p + `, d2);
              } else {
                dotProd +=
                    getX(batch, ` + p + `, xR, xC) *
                    getW(wR, wC, ` + p + `, d2);
              }

            } else if (` + (f === 2) + `) {
              vec2 wValues = vec2(
                getW(wR, wC, ` + p + `, d2),
                getW(wR, wC, ` + p + ` + 1, d2)
              );

              if (` + m + `) {
                vec2 xValues = vec2(
                  getX(batch, xR, xC, ` + p + `),
                  getX(batch, xR, xC, ` + p + ` + 1)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec2 xValues = vec2(
                  getX(batch, ` + p + `, xR, xC),
                  getX(batch, ` + p + ` + 1, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            } else if (` + (f === 3) + `) {
              vec3 wValues = vec3(
                getW(wR, wC, ` + p + `, d2),
                getW(wR, wC, ` + p + ` + 1, d2),
                getW(wR, wC, ` + p + ` + 2, d2)
              );

              if (` + m + `) {
                vec3 xValues = vec3(
                  getX(batch, xR, xC, ` + p + `),
                  getX(batch, xR, xC, ` + p + ` + 1),
                  getX(batch, xR, xC, ` + p + ` + 2)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec3 xValues = vec3(
                  getX(batch, ` + p + `, xR, xC),
                  getX(batch, ` + p + ` + 1, xR, xC),
                  getX(batch, ` + p + ` + 2, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            }
          }
        }

        float result = dotProd;
        ` + x + `
        ` + L + `
        setOutput(result);
      }
    `;
    }
    return n;
  }(), _B = function() {
    function n(t) {
      this.variableNames = ["x", "W"], this.outputShape = t.outShape;
      var e = t.padInfo.front, r = t.padInfo.top, i = t.padInfo.left, a = t.strideDepth, s = t.strideHeight, o = t.strideWidth, c = t.dilationDepth, l = t.dilationHeight, u = t.dilationWidth, h = t.filterDepth, d = t.filterHeight, p = t.filterWidth, f = Math.floor(t.inChannels / 4) * 4, m = t.inChannels % 4;
      this.userCode = `
      const ivec3 strides = ivec3(` + a + ", " + s + ", " + o + `);
      const ivec3 pads = ivec3(` + e + ", " + r + ", " + i + `);

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d2 = coords.u;

        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xFCorner = xFRCCorner.x;
        int xRCorner = xFRCCorner.y;
        int xCCorner = xFRCCorner.z;

        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
        // y(yF, yR, yC, d2). ? = to be determined. : = across all
        // values in that axis.
        float dotProd = 0.0;
        for (int wF = 0; wF < ` + h + `; wF++) {
          int xF = xFCorner + wF * ` + c + `;

          if (xF < 0 || xF >= ` + t.inDepth + `) {
            continue;
          }

          for (int wR = 0; wR < ` + d + `; wR++) {
            int xR = xRCorner + wR * ` + l + `;

            if (xR < 0 || xR >= ` + t.inHeight + `) {
              continue;
            }

            for (int wC = 0; wC < ` + p + `; wC++) {
              int xC = xCCorner + wC * ` + u + `;

              if (xC < 0 || xC >= ` + t.inWidth + `) {
                continue;
              }

              for (int d1 = 0; d1 < ` + f + `; d1 += 4) {
                vec4 xValues = vec4(
                  getX(batch, xF, xR, xC, d1),
                  getX(batch, xF, xR, xC, d1 + 1),
                  getX(batch, xF, xR, xC, d1 + 2),
                  getX(batch, xF, xR, xC, d1 + 3)
                );
                vec4 wValues = vec4(
                  getW(wF, wR, wC, d1, d2),
                  getW(wF, wR, wC, d1 + 1, d2),
                  getW(wF, wR, wC, d1 + 2, d2),
                  getW(wF, wR, wC, d1 + 3, d2)
                );

                dotProd += dot(xValues, wValues);
              }

              if (` + (m === 1) + `) {
                dotProd +=
                  getX(batch, xF, xR, xC, ` + f + `) *
                  getW(wF, wR, wC, ` + f + `, d2);
              } else if (` + (m === 2) + `) {
                vec2 xValues = vec2(
                  getX(batch, xF, xR, xC, ` + f + `),
                  getX(batch, xF, xR, xC, ` + f + ` + 1)
                );
                vec2 wValues = vec2(
                  getW(wF, wR, wC, ` + f + `, d2),
                  getW(wF, wR, wC, ` + f + ` + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (` + (m === 3) + `) {
                vec3 xValues = vec3(
                  getX(batch, xF, xR, xC, ` + f + `),
                  getX(batch, xF, xR, xC, ` + f + ` + 1),
                  getX(batch, xF, xR, xC, ` + f + ` + 2)
                );
                vec3 wValues = vec3(
                  getW(wF, wR, wC, ` + f + `, d2),
                  getW(wF, wR, wC, ` + f + ` + 1, d2),
                  getW(wF, wR, wC, ` + f + ` + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }();
  var Wb = function() {
    function n(t, e, r, i) {
      e === void 0 && (e = false), r === void 0 && (r = null), i === void 0 && (i = false), this.variableNames = ["x", "W"], this.outputShape = t.outShape;
      var a = t.inHeight, s = t.inWidth, o = t.padInfo.top, c = t.padInfo.left, l = t.strideHeight, u = t.strideWidth, h = t.dilationHeight, d = t.dilationWidth, p = t.filterHeight, f = t.filterWidth, m = t.outChannels / t.inChannels, g = "", y = "";
      r && (i ? g = `float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ` + r + `
        }` : g = `
          float activation(float x) {
            ` + r + `
          }
        `, y = "result = activation(result);");
      var w = e ? "result += getBiasAtOutCoords();" : "";
      e && this.variableNames.push("bias"), i && this.variableNames.push("preluActivationWeights"), this.userCode = `
      ` + g + `

      const ivec2 strides = ivec2(` + l + ", " + u + `);
      const ivec2 pads = ivec2(` + o + ", " + c + `);

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ` + m + `;
        int q = d2 - d1 * ` + m + `;

        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
        for (int wR = 0; wR < ` + p + `; wR++) {
          int xR = xRCorner + wR * ` + h + `;

          if (xR < 0 || xR >= ` + a + `) {
            continue;
          }

          for (int wC = 0; wC < ` + f + `; wC++) {
            int xC = xCCorner + wC * ` + d + `;

            if (xC < 0 || xC >= ` + s + `) {
              continue;
            }

            float xVal = getX(batch, xR, xC, d1);
            float wVal = getW(wR, wC, d1, q);
            dotProd += xVal * wVal;
          }
        }

        float result = dotProd;
        ` + w + `
        ` + y + `
        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var Ub = function() {
    function n(t, e, r, i) {
      e === void 0 && (e = false), r === void 0 && (r = null), i === void 0 && (i = false), this.variableNames = ["x", "W"], this.packedInputs = true, this.packedOutput = true, this.outputShape = t.outShape;
      for (var a = t.inHeight, s = t.inWidth, o = t.padInfo.top, c = t.padInfo.left, l = t.strideHeight, u = t.strideWidth, h = t.dilationHeight, d = t.dilationWidth, p = t.filterHeight, f = t.filterWidth, m = f, g = "int xR; int xC; int xCOffset;", y = 0; y < p; y++)
        for (var w = 0; w < f; w++)
          g += `
          vec4 xTexelR` + y + "C" + w * 2 + ` = vec4(0.);
          vec4 wR` + y + "C" + w + ` = vec4(0.);
          vec4 xR` + y + "C" + w + " = vec4(0.);";
      for (var y = 0; y < p; y++)
        for (var b = 0; b < m; b++) {
          var w = b * 2;
          if (g += `
          xR = xRCorner + ` + y * h + `;
          xC = xCCorner + ` + w * d + `;
        `, u === 1) {
            if (w < f && (c % 2 === 1 ? g += `
                xCOffset = xC + 1;
                if(xR >= 0 && xR < ` + a + " && xCOffset >= 0 && xCOffset < " + s + `) {
                  xTexelR` + y + "C" + w + ` = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if(xCOffset + 1 >= ` + s + `) {
                    xTexelR` + y + "C" + w + `.zw = vec2(0.);
                  }
                } else {
                  xTexelR` + y + "C" + w + ` = vec4(0.);
                }

                xCOffset = xC + 1 - 2;
                if(xR >= 0 && xR < ` + a + " && xCOffset >= 0 && xCOffset < " + s + `) {
                  vec4 previous = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if(xCOffset + 1 >= ` + s + `) {
                    previous.zw = vec2(0.);
                  }

                  xR` + y + "C" + w + " = vec4(previous.zw, xTexelR" + y + "C" + w + `.xy);
                } else {
                  xR` + y + "C" + w + " = vec4(0, 0, xTexelR" + y + "C" + w + `.xy);
                }
              ` : g += `
                if(xR >= 0 && xR < ` + a + " && xC >= 0 && xC < " + s + `) {
                  xTexelR` + y + "C" + w + ` = getX(batch, xR, xC, d1);
                } else {
                  xTexelR` + y + "C" + w + ` = vec4(0.);
                }

                xR` + y + "C" + w + " = xTexelR" + y + "C" + w + `;
              `, w + 1 < f)) {
              var L = c % 2 === 0 ? _.util.nearestLargerEven(d) : d;
              d % 2 === 0 && c % 2 === 1 || d % 2 !== 0 && c % 2 !== 1 ? (g += `
                  xCOffset = xC + ` + c % 2 + " + " + L + `;

                  if(xR >= 0 && xR < ` + a + ` &&
                    xCOffset >= 0 && xCOffset < ` + s + `) {
                    xTexelR` + y + "C" + (w + 2) + ` = getX(batch, xR, xCOffset, d1);
                  }
                `, d > 1 && (g += `
                    xCOffset -= 2;
                    if(xR >= 0 && xR < ` + a + ` &&
                      xCOffset >= 0 && xCOffset < ` + s + `) {
                      xTexelR` + y + "C" + w + ` = getX(batch, xR, xCOffset, d1);
                    } else {
                      xTexelR` + y + "C" + w + ` = vec4(0.);
                    }
                  `), g += `
                  xR` + y + "C" + (w + 1) + ` = vec4(
                    xTexelR` + y + "C" + w + ".zw, xTexelR" + y + "C" + (w + 2) + `.xy);
                `) : g += `
                  xCOffset = xC + ` + L + `;

                  if(xR >= 0 && xR < ` + a + ` &&
                    xCOffset >= 0 && xCOffset < ` + s + `) {
                    xTexelR` + y + "C" + (w + 2) + ` = getX(batch, xR, xCOffset, d1);
                  }

                  xR` + y + "C" + (w + 1) + " = xTexelR" + y + "C" + (w + 2) + `;
                `;
            }
          } else
            w < f && (g += `
              if(xR >= 0 && xR < ` + a + `) {
            `, c % 2 === 1 ? (g += `
                xCOffset = xC + 1 - ` + u + `;
                if(xCOffset >= 0 && xCOffset < ` + s + `) {
                  xTexelR` + y + "C" + w + ` = getX(batch, xR, xCOffset, d1);
                } else {
                  xTexelR` + y + "C" + w + ` = vec4(0.);
                }

                if(xC + 1 >= 0 && xC + 1 < ` + s + `) {
                  xTexelR` + y + "C" + (w + 2) + ` = getX(batch, xR, xC + 1, d1);
                } else {
                  xTexelR` + y + "C" + (w + 2) + ` = vec4(0.);
                }

                xR` + y + "C" + w + ` = vec4(
                  xTexelR` + y + "C" + w + ".zw, xTexelR" + y + "C" + (w + 2) + `.zw);
              `, w + 1 < f && (g += `
                  vec4 final = vec4(0.);
                  xCOffset = xC + 1 + ` + u + `;
                  if(xCOffset >= 0 && xCOffset < ` + s + `) {
                    final = getX(batch, xR, xCOffset, d1);
                  }
                  xR` + y + "C" + (w + 1) + " = vec4(xTexelR" + y + "C" + (w + 2) + `.xy, final.xy);
                `)) : (g += `
                if(xC >= 0 && xC < ` + s + `) {
                  xTexelR` + y + "C" + w + ` = getX(batch, xR, xC, d1);
                } else {
                  xTexelR` + y + "C" + w + ` = vec4(0.);
                }

                xCOffset = xC + ` + u + `;
                if(xCOffset >= 0 && xCOffset < ` + s + `) {
                  xTexelR` + y + "C" + (w + 2) + ` = getX(batch, xR, xCOffset, d1);
                } else {
                  xTexelR` + y + "C" + (w + 2) + ` = vec4(0.);
                }

                xR` + y + "C" + w + ` = vec4(
                  xTexelR` + y + "C" + w + ".xy, xTexelR" + y + "C" + (w + 2) + `.xy);
              `, w + 1 < f && (g += `
                  xR` + y + "C" + (w + 1) + ` = vec4(
                    xTexelR` + y + "C" + w + ".zw, xTexelR" + y + "C" + (w + 2) + `.zw);
                `)), g += "}");
          w < f && (g += `
            vec4 wTexelR` + y + "C" + w + " = getW(" + y + ", " + w + `, d1, q);
            wR` + y + "C" + w + " = vec4(wTexelR" + y + "C" + w + ".xz, wTexelR" + y + "C" + w + `.xz);
          `, w + 1 < f && (g += `
              vec4 wTexelR` + y + "C" + (w + 1) + " = getW(" + y + ", " + (w + 1) + `, d1, q);
              wR` + y + "C" + (w + 1) + ` =
                vec4(wTexelR` + y + "C" + (w + 1) + ".xz, wTexelR" + y + "C" + (w + 1) + ".xz);"));
        }
      for (var y = 0; y < p; y++)
        for (var w = 0; w < f; w++)
          g += "dotProd += xR" + y + "C" + w + " * wR" + y + "C" + w + ";";
      var x = "", N = "";
      r && (i ? x = `vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ` + r + `
        }` : x = `vec4 activation(vec4 x) {
          ` + r + `
        }`, N = "result = activation(result);");
      var I = e ? "result += getBiasAtOutCoords();" : "";
      e && this.variableNames.push("bias"), i && this.variableNames.push("preluActivationWeights"), this.userCode = `
      ` + x + `

      const ivec2 strides = ivec2(` + l + ", " + u + `);
      const ivec2 pads = ivec2(` + o + ", " + c + `);

      void main() {

        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2;
        int q = 0;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        vec4 dotProd = vec4(0.);

        ` + g + `

        vec4 result = dotProd;
        ` + I + `
        ` + N + `
        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var CB = function() {
    function n(t, e, r, i, a) {
      this.variableNames = ["Image", "Boxes", "BoxInd"], this.outputShape = [];
      var s = t[0], o = t[1], c = t[2], l = t[3], u = e[0], h = r[0], d = r[1];
      this.outputShape = [u, h, d, l];
      var p = i === "bilinear" ? 1 : 0, f = [o - 1 + ".0", c - 1 + ".0"], m = f[0], g = f[1], y = h > 1 ? ["" + (o - 1) / (h - 1), "(y2-y1) * height_ratio", "y1*" + m + " + float(y)*(height_scale)"] : ["0.0", "0.0", "0.5 * (y1+y2) * " + m], w = y[0], b = y[1], L = y[2], x = d > 1 ? ["" + (c - 1) / (d - 1), "(x2-x1) * width_ratio", "x1*" + g + " + float(x)*(width_scale)"] : ["0.0", "0.0", "0.5 * (x1+x2) * " + g], N = x[0], I = x[1], C = x[2];
      this.userCode = `
      const float height_ratio = float(` + w + `);
      const float width_ratio = float(` + N + `);
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int y = coords[1];
        int x = coords[2];
        int d = coords[3];

        // get box vals
        float y1 = getBoxes(b,0);
        float x1 = getBoxes(b,1);
        float y2 = getBoxes(b,2);
        float x2 = getBoxes(b,3);

        // get image in batch index
        int bInd = round(getBoxInd(b));
        if(bInd < 0 || bInd >= ` + s + `) {
          return;
        }

        float height_scale = ` + b + `;
        float width_scale = ` + I + `;

        float in_y = ` + L + `;
        if( in_y < 0.0 || in_y > ` + m + ` ) {
          setOutput(float(` + a + `));
          return;
        }
        float in_x = ` + C + `;
        if( in_x < 0.0 || in_x > ` + g + ` ) {
          setOutput(float(` + a + `));
          return;
        }

        vec2 sourceFracIndexCR = vec2(in_x,in_y);
        if(` + p + ` == 1) {
          // Compute the four integer indices.
          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));

          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);

          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);

          float top = topLeft + (topRight - topLeft) * fracCR.x;
          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          float newValue = top + (bottom - top) * fracCR.y;
          setOutput(newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          ivec2 sourceNearestCR = ivec2(floor(
            sourceFracIndexCR + vec2(0.5,0.5)));
          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutput(newValue);
        }
      }
    `;
    }
    return n;
  }(), Pb = function() {
    function n(t, e, r) {
      this.variableNames = ["x"], this.outputShape = t;
      var i = t.length, a = e ? "0.0" : "getX(" + Bb(i, "coords") + ")", s = t[t.length - 1], o = "", c = "";
      e ? (o = r ? "end != " + (s - 1) : "end != 0", c = r ? "end + 1" : "end - 1") : (o = r ? "end + pow2 < " + s : "end >= pow2", c = r ? "end + pow2" : "end - pow2"), this.userCode = `
      uniform float index;
      void main() {
        ` + Ze(i) + ` coords = getOutputCoords();
        int end = ` + zb(i, "coords") + `;
        float val = ` + a + `;
        int pow2 = int(pow(2.0, index));
        if (` + o + `) {
          int idx = ` + c + `;
          ` + zb(i, "coords") + ` = idx;
          val += getX(` + Bb(i, "coords") + `);
        }
        setOutput(val);
      }
    `;
    }
    return n.prototype.getCustomSetupFunc = function(t) {
      var e = this;
      return function(r, i) {
        e.index == null && (e.index = r.getUniformLocation(i, "index")), r.gl.uniform1f(e.index, t);
      };
    }, n;
  }();
  function Bb(n, t) {
    if (n === 1)
      return "" + t;
    if (n === 2)
      return t + ".x, " + t + ".y";
    if (n === 3)
      return t + ".x, " + t + ".y, " + t + ".z";
    if (n === 4)
      return t + ".x, " + t + ".y, " + t + ".z, " + t + ".w";
    throw Error("Cumulative sum for rank " + n + " is not yet supported");
  }
  function zb(n, t) {
    if (n === 1)
      return "" + t;
    if (n === 2)
      return t + ".y";
    if (n === 3)
      return t + ".z";
    if (n === 4)
      return t + ".w";
    throw Error("Cumulative sum for rank " + n + " is not yet supported");
  }
  var RB = function() {
    function n(t) {
      this.variableNames = ["A"], this.packedInputs = false, this.packedOutput = true, this.outPackingScheme = rs.DENSE;
      var e = as(t), r = zt();
      this.outputShape = t, this.userCode = `
      ivec3 outCoordsFromFlatIndex(int index) {
        ` + mi(["r", "c", "d"], t) + `
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx *
          vec2(` + e[0] + ", " + e[1] + `));
        int index = 4 * (resTexRC.x * ` + e[1] + ` + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getA(rc.x, rc.y, rc.z);
        }

        ` + r.output + ` = result;
      }
    `;
    }
    return n;
  }();
  var OB = function() {
    function n(t) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = true, this.outPackingScheme = rs.DENSE;
      var e = as(t), r = zt();
      this.outputShape = t, this.userCode = `
      ivec3 outCoordsFromFlatIndex(int index) {
        ` + mi(["r", "c", "d"], t) + `
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx *
          vec2(` + e[0] + ", " + e[1] + `));
        int index = 4 * (resTexRC.x * ` + e[1] + ` + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
        }

        ` + r.output + ` = result;
      }
    `;
    }
    return n;
  }();
  var EB = function() {
    function n(t, e, r) {
      this.variableNames = ["x"], this.outputShape = [], this.outputShape = t, this.blockSize = e, this.dataFormat = r, this.userCode = `
    void main() {
      ivec4 coords = getOutputCoords();
      int b = coords[0];
      int h = ` + this.getHeightCoordString() + `;
      int w = ` + this.getWidthCoordString() + `;
      int d = ` + this.getDepthCoordString() + `;

      int in_h = h / ` + e + `;
      int offset_h = imod(h, ` + e + `);
      int in_w = w / ` + e + `;
      int offset_w = imod(w, ` + e + `);
      int offset_d = (offset_h * ` + e + ` + offset_w) *
        ` + this.getOutputDepthSize() + `;
      int in_d = d + offset_d;

      float result = ` + this.getInputSamplingString() + `;
      setOutput(result);
    }
  `;
    }
    return n.prototype.getHeightCoordString = function() {
      return this.dataFormat === "NHWC" ? "coords[1]" : "coords[2]";
    }, n.prototype.getWidthCoordString = function() {
      return this.dataFormat === "NHWC" ? "coords[2]" : "coords[3]";
    }, n.prototype.getDepthCoordString = function() {
      return this.dataFormat === "NHWC" ? "coords[3]" : "coords[1]";
    }, n.prototype.getOutputDepthSize = function() {
      return this.dataFormat === "NHWC" ? this.outputShape[3] : this.outputShape[1];
    }, n.prototype.getInputSamplingString = function() {
      return this.dataFormat === "NHWC" ? "getX(b, in_h, in_w, in_d)" : "getX(b, in_d, in_h, in_w)";
    }, n;
  }();
  var DB = function() {
    function n(t) {
      this.variableNames = ["X"], this.outputShape = [t, t], this.userCode = `
      void main() {
          ivec2 coords = getOutputCoords();
          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
          setOutput(val);
      }
    `;
    }
    return n;
  }();
  var kB = function() {
    function n(t) {
      this.variableNames = ["A"], this.outTexUsage = cn.DOWNLOAD;
      var e = zt();
      this.outputShape = t, this.userCode = `
      ` + _b + `

      void main() {
        float x = getAAtOutCoords();
        ` + e.output + ` = encode_float(x);
      }
    `;
    }
    return n;
  }();
  var FB = function() {
    function n(t) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = false, this.outTexUsage = cn.DOWNLOAD;
      var e = zt();
      this.outputShape = t, this.userCode = `
      ` + _b + `

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ` + e.output + ` = encode_float(x);
      }
    `;
    }
    return n;
  }();
  var WB = function() {
    function n(t, e, r) {
      r === void 0 && (r = false), this.variableNames = ["A"];
      var i = zt(), a = e[0], s = e[1];
      this.outputShape = t;
      var o = "result";
      r && (o = "floor(result * 255. + 0.5)"), this.userCode = `
      ` + tp(t) + `

      void main() {
        ivec3 coords = getOutputCoords();

        int flatIndex = getFlatIndex(coords);
        int offset = imod(flatIndex, 4);

        flatIndex = idiv(flatIndex, 4, 1.);

        int r = flatIndex / ` + s + `;
        int c = imod(flatIndex, ` + s + `);
        vec2 uv = (vec2(c, r) + halfCR) / vec2(` + s + ".0, " + a + `.0);
        vec4 values = ` + i.texture2D + `(A, uv);

        float result;

        if(offset == 0) {
          result = values[0];
        } else if(offset == 1) {
          result = values[1];
        } else if(offset == 2) {
          result = values[2];
        } else {
          result = values[3];
        }

        ` + i.output + " = vec4(" + o + `, 0., 0., 0.);
      }
    `;
    }
    return n;
  }();
  var UB = function() {
    function n(t, e, r) {
      r === void 0 && (r = false), this.variableNames = ["A"], this.packedInputs = false, this.packedOutput = true;
      var i = zt(), a = e[0], s = e[1];
      this.outputShape = t;
      var o = "", c = "result";
      r && (c = "floor(result * 255. + 0.5)");
      for (var l = 0; l <= 1; l++)
        for (var u = 0; u <= 1; u++) {
          var h = l * 2 + u;
          o += `
          localCoords = coords;
          if(localCoords[2] + ` + u + " < " + t[2] + `) {
            localCoords[2] += ` + u + `;
            if(localCoords[1] + ` + l + " < " + t[1] + `) {
              localCoords[1] += ` + l + `;

              flatIndex = getFlatIndex(localCoords);
              offset = imod(flatIndex, 4);

              flatIndex = idiv(flatIndex, 4, 1.);

              r = flatIndex / ` + s + `;
              c = imod(flatIndex, ` + s + `);
              uv = (vec2(c, r) + halfCR) / vec2(` + s + ".0, " + a + `.0);
              values = ` + i.texture2D + `(A, uv);

              if(offset == 0) {
                result[` + h + `] = values[0];
              } else if(offset == 1) {
                result[` + h + `] = values[1];
              } else if(offset == 2) {
                result[` + h + `] = values[2];
              } else {
                result[` + h + `] = values[3];
              }
            }
          }
        `;
        }
      this.userCode = `
      ` + tp(t) + `

      void main() {
        ivec3 coords = getOutputCoords();

        vec4 result = vec4(0.);
        int flatIndex, r, c, offset;
        ivec3 localCoords;
        vec2 uv;
        vec4 values;

        ` + o + `

        ` + i.output + " = " + c + `;
      }
    `;
    }
    return n;
  }();
  var BB = function() {
    function n(t, e) {
      this.outputShape = [], this.variableNames = ["x"], this.outputShape = t, this.userCode = `
      uniform float value;
      void main() {
        // Input can be obtained from uniform value.
        setOutput(value);
      }
    `;
    }
    return n.prototype.getCustomSetupFunc = function(t) {
      var e = this;
      return function(r, i) {
        e.valueLoc == null && (e.valueLoc = r.getUniformLocationNoThrow(i, "value")), r.gl.uniform1f(e.valueLoc, t);
      };
    }, n;
  }();
  var PB = function() {
    function n(t, e, r) {
      this.variableNames = ["A", "indices"];
      var i = t.slice();
      i[r] = e, this.outputShape = i, this.rank = i.length;
      var a = Ze(this.rank), s = zB(t, r);
      this.userCode = `
      void main() {
        ` + a + ` resRC = getOutputCoords();
        setOutput(getA(` + s + `));
      }
    `;
    }
    return n;
  }();
  function zB(n, t) {
    var e = n.length;
    if (e > 4)
      throw Error("Gather for rank " + e + " is not yet supported");
    if (e === 1)
      return "int(getIndices(resRC))";
    for (var r = ["resRC.x", "resRC.y", "resRC.z", "resRC.w"], i = [], a = 0; a < n.length; a++)
      a === t ? i.push("int(getIndices(" + r[a] + "))") : i.push("" + r[a]);
    return i.join();
  }
  var MB = function() {
    function n(t, e, r) {
      this.sliceDim = t, this.strides = e, this.variableNames = ["x", "indices"], this.outputShape = r;
      var i = Ze(e.length), a = Ze(r.length), s = this.sliceDim > 1 ? "strides[j]" : "strides";
      this.userCode = `
        ` + i + " strides = " + i + "(" + this.strides + `);
         void main() {
          ` + a + ` coords = getOutputCoords();
          int flattenIndex = 0;
          for (int j = 0; j < ` + this.sliceDim + `; j++) {
            int index = round(getIndices(coords[0], j));
            flattenIndex += index * ` + s + `;
          }
          setOutput(getX(flattenIndex, coords[1]));
        }
      `;
    }
    return n;
  }();
  function Mb(n) {
    var t = zt(), e = t.version + `
    precision highp float;
    ` + t.attribute + ` vec3 clipSpacePos;
    ` + t.attribute + ` vec2 uv;
    ` + t.varyingVs + ` vec2 resultUV;

    void main() {
      gl_Position = vec4(clipSpacePos, 1);
      resultUV = uv;
    }`;
    return ab(n, e);
  }
  function Hb(n) {
    var t = new Float32Array([-1, 1, 0, 0, 1, -1, -1, 0, 0, 0, 1, 1, 0, 1, 1, 1, -1, 0, 1, 0]);
    return lb(n, t);
  }
  function Vb(n) {
    var t = new Uint16Array([0, 1, 2, 2, 1, 3]);
    return ub(n, t);
  }
  function ls(n, t, e, r, i, a) {
    db(t, e);
    var s = hb(n), o = n.TEXTURE_2D;
    return de(n, function() {
      return n.bindTexture(o, s);
    }), de(n, function() {
      return n.texParameteri(o, n.TEXTURE_WRAP_S, n.CLAMP_TO_EDGE);
    }), de(n, function() {
      return n.texParameteri(o, n.TEXTURE_WRAP_T, n.CLAMP_TO_EDGE);
    }), de(n, function() {
      return n.texParameteri(o, n.TEXTURE_MIN_FILTER, n.NEAREST);
    }), de(n, function() {
      return n.texParameteri(o, n.TEXTURE_MAG_FILTER, n.NEAREST);
    }), de(n, function() {
      return n.texImage2D(o, 0, r, t, e, 0, i, a, null);
    }), de(n, function() {
      return n.bindTexture(n.TEXTURE_2D, null);
    }), s;
  }
  function np(n) {
    return n.internalFormatFloat;
  }
  function Gb(n, t, e, r) {
    var i = is(t, e), a = i[0], s = i[1];
    return ls(n, a, s, np(r), r.textureFormatFloat, n.FLOAT);
  }
  function rp(n) {
    return n.internalFormatHalfFloat;
  }
  function qb(n, t, e, r) {
    var i = is(t, e), a = i[0], s = i[1];
    return ls(n, a, s, rp(r), r.textureFormatFloat, r.textureTypeHalfFloat);
  }
  function ip(n) {
    return n.downloadTextureFormat;
  }
  function Yb(n, t, e, r) {
    var i = is(t, e), a = i[0], s = i[1];
    return ls(n, a, s, ip(r), n.RGBA, n.UNSIGNED_BYTE);
  }
  function ap(n) {
    return n.internalFormatPackedFloat;
  }
  function Kb(n, t, e, r) {
    var i = ea(t, e), a = i[0], s = i[1];
    return ls(n, a, s, ap(r), n.RGBA, n.FLOAT);
  }
  function sp(n) {
    return n.internalFormatPackedHalfFloat;
  }
  function jb(n, t, e, r) {
    var i = ea(t, e), a = i[0], s = i[1];
    return ls(n, a, s, sp(r), n.RGBA, r.textureTypeHalfFloat);
  }
  function $b(n, t, e) {
    var r = 0, i = 3 * 4, a = 3 * 4 + 2 * 4;
    de(n, function() {
      return n.bindBuffer(n.ARRAY_BUFFER, e);
    });
    var s = $d(n, t, "clipSpacePos", e, 3, a, r);
    return s && $d(n, t, "uv", e, 2, a, i);
  }
  function Xb(n, t, e, r, i, a) {
    de(n, function() {
      return n.bindTexture(n.TEXTURE_2D, t);
    });
    var s, o, c;
    i instanceof Uint8Array ? (s = new Uint8Array(e * r * 4), o = n.UNSIGNED_BYTE, c = n.RGBA) : (s = new Float32Array(e * r * 4), o = n.FLOAT, c = a.internalFormatPackedFloat), s.set(i), de(n, function() {
      return n.texImage2D(n.TEXTURE_2D, 0, c, e, r, 0, n.RGBA, o, s);
    }), de(n, function() {
      return n.bindTexture(n.TEXTURE_2D, null);
    });
  }
  function Jb(n, t, e) {
    de(n, function() {
      return n.bindTexture(n.TEXTURE_2D, t);
    }), e.data instanceof Uint8Array ? de(n, function() {
      return n.texImage2D(n.TEXTURE_2D, 0, n.RGBA, e.width, e.height, 0, n.RGBA, n.UNSIGNED_BYTE, e.data);
    }) : de(n, function() {
      return n.texImage2D(n.TEXTURE_2D, 0, n.RGBA, n.RGBA, n.UNSIGNED_BYTE, e);
    }), de(n, function() {
      return n.bindTexture(n.TEXTURE_2D, null);
    });
  }
  function Zb(n, t, e, r) {
    var i = n.createBuffer();
    de(n, function() {
      return n.bindBuffer(n.PIXEL_PACK_BUFFER, i);
    });
    var a = 4, s = 4, o = a * s * t * e;
    return de(n, function() {
      return n.bufferData(n.PIXEL_PACK_BUFFER, o, n.STREAM_READ);
    }), de(n, function() {
      return n.readPixels(0, 0, e, t, n.RGBA, n.FLOAT, 0);
    }), de(n, function() {
      return n.bindBuffer(n.PIXEL_PACK_BUFFER, null);
    }), i;
  }
  function Qb(n, t, e) {
    var r = n, i = new Float32Array(e);
    return r.bindBuffer(r.PIXEL_PACK_BUFFER, t), r.getBufferSubData(r.PIXEL_PACK_BUFFER, 0, i), r.bindBuffer(r.PIXEL_PACK_BUFFER, null), i;
  }
  function e2(n, t, e, r) {
    var i = is(t, e), a = i[0], s = i[1], o = 4, c = new Uint8Array(yW(t * e, o));
    return de(n, function() {
      return n.readPixels(0, 0, a, s, r.downloadTextureFormat, n.UNSIGNED_BYTE, c);
    }), new Float32Array(c.buffer);
  }
  function t2(n, t, e, r, i, a, s, o) {
    var c = n, l = new Float32Array(vW(a, s));
    return c.bindBuffer(c.PIXEL_PACK_BUFFER, t), c.getBufferSubData(c.PIXEL_PACK_BUFFER, 0, l), c.bindBuffer(c.PIXEL_PACK_BUFFER, null), l;
  }
  function n2(n, t, e) {
    var r = new Float32Array(t * e * 4);
    return de(n, function() {
      return n.readPixels(0, 0, e, t, n.RGBA, n.FLOAT, r);
    }), r;
  }
  var HB = {__proto__: null, createVertexShader: Mb, createVertexBuffer: Hb, createIndexBuffer: Vb, getInternalFormatForFloat32MatrixTexture: np, createFloat32MatrixTexture: Gb, getInternalFormatForFloat16MatrixTexture: rp, createFloat16MatrixTexture: qb, getInternalFormatForUnsignedBytesMatrixTexture: ip, createUnsignedBytesMatrixTexture: Yb, getInternalFormatForPackedMatrixTexture: ap, createPackedMatrixTexture: Kb, getInternalFormatForFloat16PackedMatrixTexture: sp, createFloat16PackedMatrixTexture: jb, bindVertexProgramAttributeStreams: $b, uploadDenseMatrixToTexture: Xb, uploadPixelDataToTexture: Jb, createBufferFromOutputTexture: Zb, downloadFloat32MatrixFromBuffer: Qb, downloadByteEncodedFloatMatrixFromOutputTexture: e2, downloadPackedMatrixFromBuffer: t2, downloadMatrixFromPackedOutputTexture: n2};
  var r2 = function() {
    function n(t) {
      this.outputTexture = null, this.program = null, this.disposed = false, this.vertexAttrsAreBound = false, this.itemsToPoll = [];
      var e = _.env().getNumber("WEBGL_VERSION");
      t != null ? (this.gl = t, nb(e, t)) : this.gl = Mn(e);
      var r = "WEBGL_color_buffer_float", i = "EXT_color_buffer_half_float";
      if (_.env().getNumber("WEBGL_VERSION") === 1) {
        var a = "OES_texture_float", s = "OES_texture_half_float";
        if (this.textureFloatExtension = ss(this.gl, a), ln(this.gl, s))
          this.textureHalfFloatExtension = ss(this.gl, s);
        else if (_.env().get("WEBGL_FORCE_F16_TEXTURES"))
          throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");
        if (this.colorBufferFloatExtension = this.gl.getExtension(r), ln(this.gl, i))
          this.colorBufferHalfFloatExtension = ss(this.gl, i);
        else if (_.env().get("WEBGL_FORCE_F16_TEXTURES"))
          throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");
      } else if (r = "EXT_color_buffer_float", ln(this.gl, r))
        this.colorBufferFloatExtension = this.gl.getExtension(r);
      else if (ln(this.gl, i))
        this.colorBufferHalfFloatExtension = this.gl.getExtension(i);
      else
        throw new Error("GL context does not support color renderable floats");
      this.vertexBuffer = Hb(this.gl), this.indexBuffer = Vb(this.gl), this.framebuffer = pb(this.gl), this.textureConfig = jd(this.gl, this.textureHalfFloatExtension);
    }
    return Object.defineProperty(n.prototype, "debug", {get: function() {
      return _.env().getBool("DEBUG");
    }, enumerable: true, configurable: true}), n.prototype.dispose = function() {
      var t = this;
      if (this.disposed)
        return;
      this.program != null && console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."), this.outputTexture != null && console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");
      var e = this.gl;
      de(e, function() {
        return e.finish();
      }), de(e, function() {
        return e.bindFramebuffer(e.FRAMEBUFFER, null);
      }), de(e, function() {
        return e.deleteFramebuffer(t.framebuffer);
      }), de(e, function() {
        return e.bindBuffer(e.ARRAY_BUFFER, null);
      }), de(e, function() {
        return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER, null);
      }), de(e, function() {
        return e.deleteBuffer(t.indexBuffer);
      }), this.disposed = true;
    }, n.prototype.createFloat32MatrixTexture = function(t, e) {
      return this.throwIfDisposed(), Gb(this.gl, t, e, this.textureConfig);
    }, n.prototype.createFloat16MatrixTexture = function(t, e) {
      return this.throwIfDisposed(), qb(this.gl, t, e, this.textureConfig);
    }, n.prototype.createUnsignedBytesMatrixTexture = function(t, e) {
      return this.throwIfDisposed(), Yb(this.gl, t, e, this.textureConfig);
    }, n.prototype.uploadPixelDataToTexture = function(t, e) {
      this.throwIfDisposed(), Jb(this.gl, t, e);
    }, n.prototype.uploadDenseMatrixToTexture = function(t, e, r, i) {
      this.throwIfDisposed(), Xb(this.gl, t, e, r, i, this.textureConfig);
    }, n.prototype.createFloat16PackedMatrixTexture = function(t, e) {
      return this.throwIfDisposed(), jb(this.gl, t, e, this.textureConfig);
    }, n.prototype.createPackedMatrixTexture = function(t, e) {
      return this.throwIfDisposed(), Kb(this.gl, t, e, this.textureConfig);
    }, n.prototype.deleteMatrixTexture = function(t) {
      var e = this;
      this.throwIfDisposed(), this.outputTexture === t && (Xd(this.gl, this.framebuffer), this.outputTexture = null), de(this.gl, function() {
        return e.gl.deleteTexture(t);
      });
    }, n.prototype.downloadByteEncodedFloatMatrixFromOutputTexture = function(t, e, r) {
      var i = this;
      return this.downloadMatrixDriver(t, function() {
        return e2(i.gl, e, r, i.textureConfig);
      });
    }, n.prototype.downloadPackedMatrixFromBuffer = function(t, e, r, i, a, s) {
      return t2(this.gl, t, e, r, i, a, s, this.textureConfig);
    }, n.prototype.downloadFloat32MatrixFromBuffer = function(t, e) {
      return Qb(this.gl, t, e);
    }, n.prototype.createBufferFromTexture = function(t, e, r) {
      this.bindTextureToFrameBuffer(t);
      var i = Zb(this.gl, e, r, this.textureConfig);
      return this.unbindTextureToFrameBuffer(), i;
    }, n.prototype.createAndWaitForFence = function() {
      var t = this.createFence(this.gl);
      return this.pollFence(t);
    }, n.prototype.createFence = function(t) {
      var e = this, r, i;
      if (_.env().getBool("WEBGL_FENCE_API_ENABLED")) {
        var a = t, s = a.fenceSync(a.SYNC_GPU_COMMANDS_COMPLETE, 0);
        t.flush(), i = function() {
          var o = a.clientWaitSync(s, 0, 0);
          return o === a.ALREADY_SIGNALED || o === a.CONDITION_SATISFIED;
        }, r = s;
      } else
        _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") > 0 ? (r = this.beginQuery(), this.endQuery(), i = function() {
          return e.isQueryAvailable(r, _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"));
        }) : i = function() {
          return true;
        };
      return {query: r, isFencePassed: i};
    }, n.prototype.downloadMatrixFromPackedTexture = function(t, e, r) {
      var i = this;
      return this.downloadMatrixDriver(t, function() {
        return n2(i.gl, e, r);
      });
    }, n.prototype.createProgram = function(t) {
      this.throwIfDisposed();
      var e = this.gl, r = sb(e, t), i = Mb(e), a = ob(e);
      return de(e, function() {
        return e.attachShader(a, i);
      }), de(e, function() {
        return e.attachShader(a, r);
      }), cb(e, a), this.debug && jo(e, a), this.vertexAttrsAreBound || (this.setProgram(a), this.vertexAttrsAreBound = $b(e, this.program, this.vertexBuffer)), a;
    }, n.prototype.deleteProgram = function(t) {
      var e = this;
      this.throwIfDisposed(), t === this.program && (this.program = null), t != null && de(this.gl, function() {
        return e.gl.deleteProgram(t);
      });
    }, n.prototype.setProgram = function(t) {
      var e = this;
      this.throwIfDisposed(), this.program = t, this.program != null && this.debug && jo(this.gl, this.program), de(this.gl, function() {
        return e.gl.useProgram(t);
      });
    }, n.prototype.getUniformLocation = function(t, e, r) {
      return r === void 0 && (r = true), this.throwIfDisposed(), r ? gb(this.gl, t, e) : yb(this.gl, t, e);
    }, n.prototype.getAttributeLocation = function(t, e) {
      var r = this;
      return this.throwIfDisposed(), de(this.gl, function() {
        return r.gl.getAttribLocation(t, e);
      });
    }, n.prototype.getUniformLocationNoThrow = function(t, e) {
      return this.throwIfDisposed(), this.gl.getUniformLocation(t, e);
    }, n.prototype.setInputMatrixTexture = function(t, e, r) {
      this.throwIfDisposed(), this.throwIfNoProgram(), vb(this.gl, t, e, r);
    }, n.prototype.setOutputMatrixTexture = function(t, e, r) {
      this.setOutputMatrixTextureDriver(t, r, e);
    }, n.prototype.setOutputPackedMatrixTexture = function(t, e, r) {
      this.throwIfDisposed();
      var i = ea(e, r), a = i[0], s = i[1];
      this.setOutputMatrixTextureDriver(t, a, s);
    }, n.prototype.setOutputMatrixWriteRegion = function(t, e, r, i) {
      this.setOutputMatrixWriteRegionDriver(r, t, i, e);
    }, n.prototype.setOutputPackedMatrixWriteRegion = function(t, e, r, i) {
      throw new Error("setOutputPackedMatrixWriteRegion not implemented.");
    }, n.prototype.debugValidate = function() {
      this.program != null && jo(this.gl, this.program), os(this.gl);
    }, n.prototype.executeProgram = function() {
      this.throwIfDisposed(), this.throwIfNoProgram();
      var t = this.gl;
      this.debug && this.debugValidate(), de(t, function() {
        return t.drawElements(t.TRIANGLES, 6, t.UNSIGNED_SHORT, 0);
      });
    }, n.prototype.blockUntilAllProgramsCompleted = function() {
      var t = this;
      this.throwIfDisposed(), de(this.gl, function() {
        return t.gl.finish();
      });
    }, n.prototype.getQueryTimerExtension = function() {
      return this.disjointQueryTimerExtension == null && (this.disjointQueryTimerExtension = ss(this.gl, _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2 ? "EXT_disjoint_timer_query_webgl2" : "EXT_disjoint_timer_query")), this.disjointQueryTimerExtension;
    }, n.prototype.getQueryTimerExtensionWebGL2 = function() {
      return this.getQueryTimerExtension();
    }, n.prototype.getQueryTimerExtensionWebGL1 = function() {
      return this.getQueryTimerExtension();
    }, n.prototype.beginQuery = function() {
      if (_.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2) {
        var t = this.gl, e = this.getQueryTimerExtensionWebGL2(), r = t.createQuery();
        return t.beginQuery(e.TIME_ELAPSED_EXT, r), r;
      }
      var i = this.getQueryTimerExtensionWebGL1(), a = i.createQueryEXT();
      return i.beginQueryEXT(i.TIME_ELAPSED_EXT, a), a;
    }, n.prototype.endQuery = function() {
      if (_.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION") === 2) {
        var t = this.gl, e = this.getQueryTimerExtensionWebGL2();
        t.endQuery(e.TIME_ELAPSED_EXT);
        return;
      }
      var r = this.getQueryTimerExtensionWebGL1();
      r.endQueryEXT(r.TIME_ELAPSED_EXT);
    }, n.prototype.waitForQueryAndGetTime = function(t) {
      return Yo(this, void 0, void 0, function() {
        var e = this;
        return Ko(this, function(r) {
          switch (r.label) {
            case 0:
              return [4, _.util.repeatedTry(function() {
                return e.disposed || e.isQueryAvailable(t, _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"));
              })];
            case 1:
              return r.sent(), [2, this.getQueryTime(t, _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))];
          }
        });
      });
    }, n.prototype.getQueryTime = function(t, e) {
      if (e === 0)
        return null;
      if (e === 2) {
        var r = this.gl, i = r.getQueryParameter(t, r.QUERY_RESULT);
        return i / 1e6;
      } else {
        var a = this.getQueryTimerExtensionWebGL1(), i = a.getQueryObjectEXT(t, a.QUERY_RESULT_EXT);
        return i / 1e6;
      }
    }, n.prototype.isQueryAvailable = function(t, e) {
      if (e === 0)
        return true;
      if (e === 2) {
        var r = this.gl, i = this.getQueryTimerExtensionWebGL2(), a = r.getQueryParameter(t, r.QUERY_RESULT_AVAILABLE);
        return this.disjoint == null && (this.disjoint = this.gl.getParameter(i.GPU_DISJOINT_EXT)), a && !this.disjoint;
      } else {
        var i = this.getQueryTimerExtensionWebGL1(), a = i.getQueryObjectEXT(t, i.QUERY_RESULT_AVAILABLE_EXT);
        return this.disjoint == null && (this.disjoint = this.gl.getParameter(i.GPU_DISJOINT_EXT)), a && !this.disjoint;
      }
    }, n.prototype.pollFence = function(t) {
      var e = this;
      return new Promise(function(r) {
        e.addItemToPoll(function() {
          return t.isFencePassed();
        }, function() {
          return r();
        });
      });
    }, n.prototype.pollItems = function() {
      for (var t = VB(this.itemsToPoll.map(function(i) {
        return i.isDoneFn;
      })), e = 0; e <= t; ++e) {
        var r = this.itemsToPoll[e].resolveFn;
        r();
      }
      this.itemsToPoll = this.itemsToPoll.slice(t + 1);
    }, n.prototype.addItemToPoll = function(t, e) {
      var r = this;
      if (this.itemsToPoll.push({isDoneFn: t, resolveFn: e}), this.itemsToPoll.length > 1)
        return;
      _.util.repeatedTry(function() {
        return r.pollItems(), r.itemsToPoll.length === 0;
      });
    }, n.prototype.bindTextureToFrameBuffer = function(t) {
      this.throwIfDisposed(), $o(this.gl, t, this.framebuffer), this.debug && os(this.gl);
    }, n.prototype.unbindTextureToFrameBuffer = function() {
      this.outputTexture != null ? ($o(this.gl, this.outputTexture, this.framebuffer), this.debug && os(this.gl)) : Xd(this.gl, this.framebuffer);
    }, n.prototype.downloadMatrixDriver = function(t, e) {
      this.bindTextureToFrameBuffer(t);
      var r = e();
      return this.unbindTextureToFrameBuffer(), r;
    }, n.prototype.setOutputMatrixTextureDriver = function(t, e, r) {
      this.throwIfDisposed();
      var i = this.gl;
      $o(i, t, this.framebuffer), this.debug && os(i), this.outputTexture = t, de(i, function() {
        return i.viewport(0, 0, e, r);
      }), de(i, function() {
        return i.scissor(0, 0, e, r);
      });
    }, n.prototype.setOutputMatrixWriteRegionDriver = function(t, e, r, i) {
      var a = this;
      this.throwIfDisposed(), de(this.gl, function() {
        return a.gl.scissor(t, e, r, i);
      });
    }, n.prototype.throwIfDisposed = function() {
      if (this.disposed)
        throw new Error("Attempted to use disposed GPGPUContext.");
    }, n.prototype.throwIfNoProgram = function() {
      if (this.program == null)
        throw new Error("No GPU program is currently set.");
    }, n;
  }();
  function VB(n) {
    for (var t = 0; t < n.length; ++t) {
      var e = n[t]();
      if (!e)
        break;
    }
    return t - 1;
  }
  function GB(n, t, e, r) {
    var i = t.userCode, a = e.map(function(g, y) {
      var w = {logicalShape: g.shape, texShape: g.isUniform ? null : g.texData.texShape, isUniform: g.isUniform, isPacked: g.isUniform ? false : g.texData.isPacked, flatOffset: null};
      return g.texData != null && g.texData.slice != null && g.texData.slice.flatOffset > 0 && (w.flatOffset = g.texData.slice.flatOffset), {name: t.variableNames[y], shapeInfo: w};
    }), s = a.map(function(g) {
      return g.shapeInfo;
    }), o = {logicalShape: r.shape, texShape: r.texData.texShape, isUniform: false, isPacked: r.texData.isPacked, flatOffset: null}, c = gU(a, o, i, t.packedInputs), l = n.createProgram(c), u = null, h = n.getUniformLocation(l, "NAN", false);
    _.env().getNumber("WEBGL_VERSION") === 1 && (u = n.getUniformLocation(l, "INFINITY", false));
    for (var d = {}, p = 0; p < t.variableNames.length; p++) {
      var f = t.variableNames[p], m = false;
      d[f] = n.getUniformLocation(l, f, m), d["offset" + f] = n.getUniformLocation(l, "offset" + f, m);
    }
    return {program: t, source: c, webGLProgram: l, uniformLocations: d, inShapeInfos: s, outShapeInfo: o, infLoc: u, nanLoc: h};
  }
  function i2(n, t) {
    if (n.length !== t.length)
      throw Error("Binary was compiled with " + n.length + " inputs, but " + ("was executed with " + t.length + " inputs"));
    n.forEach(function(e, r) {
      var i = e.logicalShape, a = t[r], s = a.shape;
      if (!_.util.arraysEqual(i, s))
        throw Error("Binary was compiled with different shapes than " + ("the current args. Shapes " + i + " and " + s + " must match"));
      if (e.isUniform && a.isUniform)
        return;
      var o = e.texShape, c = a.isUniform ? null : a.texData.texShape;
      if (!_.util.arraysEqual(o, c))
        throw Error("Binary was compiled with different texture shapes than the" + (" current args. Shape " + o + " and " + c + " must match"));
    });
  }
  function qB(n, t, e, r, i) {
    i2(t.inShapeInfos, e), i2([t.outShapeInfo], [r]);
    var a = r.texData.texture, s = r.texData.texShape;
    r.texData.isPacked ? n.setOutputPackedMatrixTexture(a, s[0], s[1]) : n.setOutputMatrixTexture(a, s[0], s[1]), n.setProgram(t.webGLProgram), _.env().getNumber("WEBGL_VERSION") === 1 && (t.infLoc !== null && n.gl.uniform1f(t.infLoc, Infinity)), t.nanLoc !== null && n.gl.uniform1f(t.nanLoc, NaN), e.forEach(function(o, c) {
      var l = t.program.variableNames[c], u = t.uniformLocations[l], h = t.uniformLocations["offset" + l];
      if (u == null)
        return;
      if (o.isUniform) {
        if (_.util.sizeFromShape(o.shape) < 2)
          n.gl.uniform1f(u, o.uniformValues[0]);
        else {
          var d = o.uniformValues;
          d instanceof Float32Array || (d = new Float32Array(d)), n.gl.uniform1fv(u, d);
        }
        return;
      }
      o.texData.slice != null && h != null && n.gl.uniform1i(h, o.texData.slice.flatOffset), n.setInputMatrixTexture(o.texData.texture, u, c);
    }), i != null && i(n, t.webGLProgram), n.executeProgram();
  }
  function YB(n, t, e) {
    var r = "";
    t.concat(e).forEach(function(s) {
      var o = s.texData != null && s.texData.slice != null && s.texData.slice.flatOffset > 0, c = s.isUniform ? "uniform" : s.texData.texShape;
      r += s.shape + "_" + c + "_" + o;
    });
    var i = n.userCode, a = n.constructor.name;
    return a += "_" + r + "_" + i, a;
  }
  var KB = function() {
    function n(t, e, r) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = true, this.outputShape = t;
      for (var i = r.filterWidth, a = r.inChannels, s = r.strideWidth, o = r.strideHeight, c = r.padInfo, l = r.outWidth, u = r.dilationWidth, h = r.dilationHeight, d = r.dataFormat, p = c.left, f = c.top, m = a * i, g = zt(), y = d === "channelsLast", w = y ? 0 : 1, b = y ? 1 : 2, L = "", x = 0; x <= 1; x++)
        for (var N = 0; N <= 1; N++)
          L += `
          blockIndex = rc.y + ` + N + `;
          pos = rc.x + ` + x + `;

          if(blockIndex < ` + t[1] + " && pos < " + t[0] + `) {
            offsetY = int(blockIndex / (` + l + ")) * " + o + " - " + f + `;
            d0 = offsetY + ` + h + " * (pos / " + m + `);

            if(d0 < ` + e[w] + ` && d0 >= 0) {

              offsetX = int(mod(float(blockIndex), ` + l + ".) * " + s + ". - " + p + `.);
              d1 = offsetX + ` + u + " * (int(mod(float(pos), " + m + ".) / " + a + `.));

              if(d1 < ` + e[b] + ` && d1 >= 0) {

                ch = int(mod(float(pos), ` + a + `.));

                if (` + y + `) {
                  innerDims = vec2(d1, ch);
                  result[` + (x * 2 + N) + `] = getChannel(
                    getA(d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[` + (x * 2 + N) + `] = getChannel(
                    getA(ch, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                }
              }
            }
          }
        `;
      this.userCode = `
      void main() {
        ivec2 rc = getOutputCoords();

        vec4 result = vec4(0);

        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
        vec2 innerDims;

        ` + L + `

        ` + g.output + ` = result;
      }
    `;
    }
    return n;
  }();
  var jB = function() {
    function n(t, e, r, i, a) {
      this.variableNames = ["x"], this.outputShape = [];
      var s = e, o = t[3] - 1;
      this.outputShape = t;
      var c, l = "float(" + r + ") + float(" + i + ") * sum";
      a === 0.5 ? c = "inversesqrt(" + l + ")" : a === 1 ? c = "1.0/(" + l + ")" : c = "exp(log(" + l + ") * float(-" + a + "));", this.userCode = `
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];
        int d = coords[3];
        float x = getX(b, r, c, d);
        float sum = 0.0;
        for (int j = -` + s + "; j <= " + s + `; j++) {
          int idx = d + j;
          if (idx >= 0 && idx <=  ` + o + `) {
            float z = getX(b, r, c, idx);
            sum += z * z;
          }
        }
        float val = x * ` + c + `;
        setOutput(val);
      }
    `;
    }
    return n;
  }();
  var $B = function() {
    function n(t, e, r, i, a) {
      this.variableNames = ["inputImage", "outputImage", "dy"], this.outputShape = [], this.outputShape = t, this.depth = t[3], this.depthRadius = e, this.bias = r, this.alpha = i, this.beta = a, this.userCode = `
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];

        float result = 0.0;
        for (int d = 0; d < ` + this.depth + `; ++d) {
          int depthBegin = int(max(0.0, float(d - ` + e + `)));
          int depthEnd = int(min(float(` + this.depth + `),
              float(d + ` + e + ` + 1)));

          const int MIN_DEPTH_BEGIN = 0;
          const int MAX_DEPTH_END = ` + this.depth + `;

          float norm = 0.0;
          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd) {
              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
            }
            else {
              break;
            }
          }

          norm = float(` + i + ") * norm + float(" + r + `);

          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd){
              float dyi = -2.0 * float(` + i + `)
                * float(` + a + `)
                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ` + a + `);
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `;
    }
    return n;
  }();
  var XB = function() {
    function n(t, e, r, i, a) {
      this.variableNames = ["x"], this.outputShape = [], this.packedInputs = true, this.packedOutput = true;
      var s = e, o = t[3] - 1;
      this.outputShape = t;
      var c, l = "float(" + r + ") + float(" + i + ") * sum";
      a === 0.5 ? c = "inversesqrt(" + l + ")" : a === 1 ? c = "1.0/(" + l + ")" : c = "exp(log(" + l + ") * float(-" + a + "));", this.userCode = `
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords.x;
        int r = coords.y;
        int c = coords.z;
        int d = coords.w;

        bool hasNextCol = d < ` + this.outputShape[3] + `;
        bool hasNextRow = c < ` + this.outputShape[2] + `;

        vec4 sum = vec4(0.);
        vec4 xFragAtOutputCoords = getX(b, r, c, d);

        vec4 xAtOutputCoords = vec4(
          getChannel(xFragAtOutputCoords, vec2(c, d)),
          hasNextCol ?
            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
          hasNextRow ?
            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
          (hasNextRow && hasNextCol) ?
            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
        );

        int firstChannel = d - ` + s + `;
        vec2 cache = vec2(0.);
        if(firstChannel >= 0){
          vec4 firstChannelFrag = getX(b, r, c, firstChannel);
          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
            if(hasNextRow){
              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
            }
        }

        ivec2 depth = ivec2(d, d + 1);
        for (int j = - ` + s + "; j <= " + s + `; j++) {
          ivec2 idx = depth + j;
          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(` + o + `));

          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;

          if(depthInRange || depthPlusOneInRange){
            vec4 z = vec4(0.);
            vec4 xFragAtCurrentDepth;
            z.xz = cache.xy;
            if(depthPlusOneInRange && hasNextCol){
              xFragAtCurrentDepth = idx.y != d ?
                getX(b, r, c, idx.y) : xFragAtOutputCoords;
              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
              if(hasNextRow){
                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
              }
            }
            cache.xy = z.yw;
            sum += z * z;
          }
        }
        vec4 result = xAtOutputCoords * ` + c + `;
        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var JB = function() {
    function n(t) {
      this.variableNames = ["dy", "maxPos"], this.outputShape = t.inShape;
      var e = t.strideHeight, r = t.strideWidth, i = t.dilationHeight, a = t.effectiveFilterHeight, s = t.effectiveFilterWidth, o = a - 1 - t.padInfo.top, c = s - 1 - t.padInfo.left, l = a * s - 1;
      this.userCode = `
      const ivec2 pads = ivec2(` + o + ", " + c + `);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ` + a + `;
          wR += ` + i + `) {
          float dyR = float(dyRCorner + wR) / ` + e + `.0;

          if (dyR < 0.0 || dyR >= ` + t.outHeight + `.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ` + s + `; wC++) {
            float dyC = float(dyCCorner + wC) / ` + r + `.0;

            if (dyC < 0.0 || dyC >= ` + t.outWidth + `.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);
            int maxPosValue = ` + l + ` - int(getMaxPos(b, idyR, idyC, d));

            // Get the current value, check it against the value from the
            // position matrix.
            int curPosValue = wR * ` + s + ` + wC;
            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

            dotProd += dyValue * mask;
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }(), ZB = function() {
    function n(t) {
      this.variableNames = ["dy", "maxPos"], this.outputShape = t.inShape;
      var e = t.strideDepth, r = t.strideHeight, i = t.strideWidth, a = t.dilationDepth, s = t.dilationHeight, o = t.dilationWidth, c = t.effectiveFilterDepth, l = t.effectiveFilterHeight, u = t.effectiveFilterWidth, h = c - 1 - t.padInfo.front, d = l - 1 - t.padInfo.top, p = u - 1 - t.padInfo.left, f = c * l * u - 1;
      this.userCode = `
      const ivec3 pads = ivec3(` + h + ", " + d + ", " + p + `);

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ` + c + `;
           wD += ` + a + `) {
          float dyD = float(dyDCorner + wD) / ` + e + `.0;

          if (dyD < 0.0 || dyD >= ` + t.outDepth + `.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ` + l + `;
              wR += ` + s + `) {
            float dyR = float(dyRCorner + wR) / ` + r + `.0;

            if (dyR < 0.0 || dyR >= ` + t.outHeight + `.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ` + u + `;
                wC += ` + o + `) {
              float dyC = float(dyCCorner + wC) / ` + i + `.0;

              if (dyC < 0.0 || dyC >= ` + t.outWidth + `.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
              int maxPosValue = ` + f + ` -
                  int(getMaxPos(batch, idyD, idyR, idyC, ch));

              // Get the current value, check it against the value from the
              // position matrix.
              int curPosValue =
                  wD * ` + l + " * " + u + ` +
                  wR * ` + u + ` + wC;
              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `;
    }
    return n;
  }();
  var op = function() {
    function n(t, e, r, i, a, s, o, c) {
      i === void 0 && (i = false), a === void 0 && (a = false), s === void 0 && (s = false), o === void 0 && (o = null), c === void 0 && (c = false), this.variableNames = ["matrixA", "matrixB"], this.packedInputs = true, this.packedOutput = true, this.outputShape = r;
      var l = i ? t[1] : t[2], u = Math.ceil(l / 2), h = i ? "i * 2, rc.y" : "rc.y, i * 2", d = a ? "rc.z, i * 2" : "i * 2, rc.z", p = i ? ["a.xxyy", "a.zzww"] : ["a.xxzz", "a.yyww"], f = a ? ["b.xzxz", "b.ywyw"] : ["b.xyxy", "b.zwzw"], m = "", g = "";
      o && (c ? m = `vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ` + o + `
        }` : m = `vec4 activation(vec4 x) {
          ` + o + `
        }`, g = "result = activation(result);");
      var y = s ? "result += getBiasAtOutCoords();" : "";
      s && this.variableNames.push("bias"), c && this.variableNames.push("preluActivationWeights");
      var w = "rc.x", b = "rc.x";
      t[0] < e[0] ? w = "int(min(float(rc.x), " + (t[0] - 1) + ".))" : e[0] < t[0] && (b = "int(min(float(rc.x), " + (e[0] - 1) + ".))"), this.userCode = `
      ` + m + `

      const float sharedDimension = ` + u + `.0;

      vec4 dot2x2ARowBCol(ivec3 rc) {
        vec4 result = vec4(0);
        for (int i = 0; i < ` + u + `; i++) {
          int batchA = ` + w + `;
          int batchB = ` + b + `;
          vec4 a = getMatrixA(batchA, ` + h + `);
          vec4 b = getMatrixB(batchB, ` + d + `);

          // These swizzled products need to be separately added.
          // See: https://github.com/tensorflow/tfjs/issues/1735
          result += (` + p[0] + " * " + f[0] + `);
          result += (` + p[1] + " * " + f[1] + `);
        }
        return result;
      }

      void main() {
        ivec3 rc = getOutputCoords();
        vec4 result = dot2x2ARowBCol(rc);

        ` + y + `

        ` + g + `

        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var QB = function() {
    function n(t, e, r) {
      this.variableNames = ["probs"], this.outputShape = [t, r], this.userCode = `
      uniform float seed;

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];

        float r = random(seed);
        float cdf = 0.0;

        for (int i = 0; i < ` + (e - 1) + `; i++) {
          cdf += getProbs(batch, i);

          if (r < cdf) {
            setOutput(float(i));
            return;
          }
        }

        // If no other event happened, last event happened.
        setOutput(float(` + (e - 1) + `));
      }
    `;
    }
    return n.prototype.getCustomSetupFunc = function(t) {
      var e = this;
      return function(r, i) {
        e.seedLoc == null && (e.seedLoc = r.getUniformLocation(i, "seed")), r.gl.uniform1f(e.seedLoc, t);
      };
    }, n;
  }();
  var ez = function() {
    function n(t, e, r, i) {
      this.variableNames = ["indices"], this.outputShape = [t, e], this.userCode = `
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(` + i + "), float(" + r + `),
                      float(index == coords.y)));
      }
    `;
    }
    return n;
  }();
  var iz = function() {
    function n(t) {
      this.variableNames = ["A"], this.packedInputs = false, this.packedOutput = true, this.outputShape = t;
      var e = t.length;
      if (e === 0)
        this.userCode = `
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;
      else {
        var r = Bt("rc", e), i = Ze(e), a = tz(e, t, r), s = nz(e, t[t.length - 1], t[t.length - 2], r), o = rz(t, r);
        this.userCode = `
        void main() {
          ` + i + ` rc = getOutputCoords();

          if(` + a + `) {
            setOutput(vec4(0));
          } else {
            ` + s + `

            setOutput(vec4(` + o + `));
          }
        }
      `;
      }
    }
    return n;
  }();
  function az(n, t) {
    for (var e = [], r = 0; r <= 1; r++)
      for (var i = 0; i <= 1; i++) {
        for (var a = (r === 0 ? "r" : "rp1") + ", " + (i === 0 ? "c" : "cp1"), s = 2; s < n; s++)
          a = t[t.length - 1 - s] + "," + a;
        e.push(a);
      }
    return e;
  }
  function tz(n, t, e) {
    if (n === 1)
      return "rc > " + t[0];
    for (var r = "", i = n - 2; i < n; i++)
      r += e[i] + " >= " + t[i], i < n - 1 && (r += "||");
    return r;
  }
  function nz(n, t, e, r) {
    if (n === 1)
      return "";
    var i = r.slice(-2);
    return `
    int r = ` + i[0] + `;
    int c = ` + i[1] + `;
    int rp1 = r + 1;
    int cp1 = c + 1;

    bool cEdge = cp1 >= ` + t + `;
    bool rEdge = rp1 >= ` + e + `;
  `;
  }
  function rz(n, t) {
    var e = n.length, r = az(e, t);
    return e === 1 ? `getA(rc),
            rc + 1 >= ` + n[0] + ` ? 0. : getA(rc + 1),
            0, 0` : "getA(" + r[0] + `),
          cEdge ? 0. : getA(` + r[1] + `),
          rEdge ? 0. : getA(` + r[2] + `),
          rEdge || cEdge ? 0. : getA(` + r[3] + ")";
  }
  var sz = function() {
    function n(t, e, r) {
      this.variableNames = ["x"], this.outputShape = e.map(function(l, u) {
        return l[0] + t[u] + l[1];
      });
      var i = t.length, a = Ze(i), s = e.map(function(l) {
        return l[0];
      }).join(","), o = e.map(function(l, u) {
        return l[0] + t[u];
      }).join(","), c = ["coords[0]", "coords[1]", "coords[2]", "coords[3]"].slice(0, i);
      if (i === 1) {
        this.userCode = `
        int start = ` + s + `;
        int end = ` + o + `;

        void main() {
          int outC = getOutputCoords();
          if (outC < start || outC >= end) {
            setOutput(float(` + r + `));
          } else {
            setOutput(getX(outC - start));
          }
        }
      `;
        return;
      }
      this.userCode = `
      ` + a + " start = " + a + "(" + s + `);
      ` + a + " end = " + a + "(" + o + `);

      void main() {
        ` + a + ` outC = getOutputCoords();
        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
          setOutput(float(` + r + `));
        } else {
          ` + a + ` coords = outC - start;
          setOutput(getX(` + c + `));
        }
      }
    `;
    }
    return n;
  }();
  var oz = function() {
    function n(t, e, r) {
      this.variableNames = ["x"], this.packedInputs = true, this.packedOutput = true, this.outputShape = e.map(function(y, w) {
        return y[0] + t[w] + y[1];
      });
      for (var i = t.length, a = Ze(i), s = e.map(function(y) {
        return y[0];
      }).join(","), o = e.map(function(y, w) {
        return y[0] + t[w];
      }).join(","), c = Bt("rc", i), l = Bt("source", i), u = c[i - 1] + " < " + this.outputShape[i - 1], h = i === 1 ? "source" : "vec2(" + l.slice(-2).join() + ")", d = [a + " rc = outputLoc;", c[i - 1] + ` += 1;
       if(` + u + `) {
      `, i === 1 ? "" : `}
       rc = outputLoc;
       ` + c[i - 2] + ` += 1;
       if(` + c[i - 2] + " < " + this.outputShape[i - 2] + ") {", i === 1 ? "" : "  " + c[i - 1] + ` += 1;
         if(` + u + ") {"], p = i === 1 ? "rc < start || rc >= end" : "any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))", f = "", m = 0, g = i === 1 ? 2 : 4; m < g; m++)
        f += `
        ` + d[m] + `
        if (` + p + `) {
          result[` + m + "] = float(" + r + `);
        } else {
          ` + a + ` source = rc - start;
          result[` + m + "] = getChannel(getX(" + l.join() + "), " + h + `);
        }
      `;
      f += i === 1 ? "} " : "}}", this.userCode = `
      const ` + a + " start = " + a + "(" + s + `);
      const ` + a + " end = " + a + "(" + o + `);

      void main() {
        ` + a + ` outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ` + f + `
        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var us = function() {
    function n(t, e, r, i, a) {
      if (i === void 0 && (i = false), a === void 0 && (a = false), this.variableNames = ["x"], e === "avg" && r)
        throw new Error("Cannot compute positions for average pool.");
      var s = t.filterWidth, o = t.strideHeight, c = t.strideWidth, l = t.dilationHeight, u = t.dilationWidth, h = t.effectiveFilterHeight, d = t.effectiveFilterWidth, p = t.padInfo.top, f = t.padInfo.left;
      this.outputShape = t.outShape;
      var m = e === "avg", g = "((batch  * " + t.inHeight + " + xR) * " + t.inWidth + " + xC) * " + t.inChannels + " + d", y = "(xR * " + t.inWidth + " + xC) * " + t.inChannels + " + d", w = "0.0";
      if (m || (w = "-1.0 / 1e-20"), r) {
        var b = ">=";
        this.userCode = `
        const ivec2 strides = ivec2(` + o + ", " + c + `);
        const ivec2 pads = ivec2(` + p + ", " + f + `);

        void main() {
          ivec4 coords = getOutputCoords();
          int batch = coords[0];
          int d = coords[3];

          ivec2 xRCCorner = coords.yz * strides - pads;
          int xRCorner = xRCCorner.x;
          int xCCorner = xRCCorner.y;

          // max/min x(?, ?, d) to get y(yR, yC, d).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;
          float avgValue = 0.0;

          for (int wR = 0; wR < ` + h + `;
              wR += ` + l + `) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ` + t.inHeight + `) {
              continue;
            }

            for (int wC = 0; wC < ` + d + `;
                wC += ` + u + `) {
              int xC = xCCorner + wC;

              if (xC < 0 || xC >= ` + t.inWidth + `) {
                continue;
              }

              float value = getX(batch, xR, xC, d);

              // If a min / max value has already been found, use it. If not,
              // use the current value.
              float currMinMaxValue = mix(
                  value, minMaxValue, minMaxValueFound);
              if (value ` + b + ` currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ` + (i ? a ? g : y : "wR * " + d + " + wC") + `;
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;
        return;
      }
      var L = "max", x = e + "(" + e + "(" + e + "(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
      e === "avg" && (x = "avgValue / count");
      var N = Math.floor(s / 4) * 4, I = s % 4, C = `
      if (` + m + `) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ` + L + `(values, minMaxValue);
      }
    `;
      this.userCode = `
      const ivec2 strides = ivec2(` + o + ", " + c + `);
      const ivec2 pads = ivec2(` + p + ", " + f + `);
      const float initializationValue = ` + w + `;
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xR, int xC, int d) {
        if (xC < 0 || xC >= ` + t.inWidth + `) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xR, xC, d);
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d = coords[3];

        ivec2 xRCCorner = coords.yz * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // max/min x(?, ?, d) to get y(yR, yC, d).
        // ? = to be determined
        vec4 minMaxValue = vec4(` + w + `);
        float avgValue = 0.0;
        count = 0.0;

        for (int wR = 0; wR < ` + h + `;
            wR += ` + l + `) {
          int xR = xRCorner + wR;

          if (xR < 0 || xR >= ` + t.inHeight + `) {
            continue;
          }

          for (int wC = 0; wC < ` + N + `; wC += 4) {
            int xC = xCCorner + wC * ` + u + `;

            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ` + u + `, d),
              getValue(batch, xR, xC + 2 * ` + u + `, d),
              getValue(batch, xR, xC + 3 * ` + u + `, d)
            );

            ` + C + `
          }

          int xC = xCCorner + ` + N + `;
          if (` + (I === 1) + `) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              initializationValue,
              initializationValue,
              initializationValue
            );

            ` + C + `
          } else if (` + (I === 2) + `) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ` + u + `, d),
              initializationValue,
              initializationValue
            );

            ` + C + `
          } else if (` + (I === 3) + `) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ` + u + `, d),
              getValue(batch, xR, xC + 2 * ` + u + `, d),
              initializationValue
            );

            ` + C + `
          }
        }
        setOutput(` + x + `);
      }
    `;
    }
    return n;
  }(), cp = function() {
    function n(t, e, r, i, a) {
      if (i === void 0 && (i = false), a === void 0 && (a = false), this.variableNames = ["x"], e === "avg" && r)
        throw new Error("Cannot compute positions for average pool.");
      var s = t.filterWidth, o = t.strideDepth, c = t.strideHeight, l = t.strideWidth, u = t.dilationDepth, h = t.dilationHeight, d = t.dilationWidth, p = t.effectiveFilterDepth, f = t.effectiveFilterHeight, m = t.effectiveFilterWidth, g = t.padInfo.front, y = t.padInfo.top, w = t.padInfo.left;
      this.outputShape = t.outShape;
      var b = e === "avg", L = "0.0";
      if (b || (L = "-1.0 / 1e-20"), r) {
        var x = ">=";
        this.userCode = `
        const ivec3 strides =
            ivec3(` + o + ", " + c + ", " + l + `);
        const ivec3 pads = ivec3(` + g + ", " + y + ", " + w + `);

        void main() {
          ivec5 coords = getOutputCoords();
          int batch = coords.x;
          int ch = coords.u;

          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
          int xDCorner = xCorner.x;
          int xRCorner = xCorner.y;
          int xCCorner = xCorner.z;

          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;

          for (int wD = 0; wD < ` + p + `;
              wD += ` + u + `) {
            int xD = xDCorner + wD;

            if (xD < 0 || xD >= ` + t.inDepth + `) {
              continue;
            }

            for (int wR = 0; wR < ` + f + `;
                wR += ` + h + `) {
              int xR = xRCorner + wR;

              if (xR < 0 || xR >= ` + t.inHeight + `) {
                continue;
              }

              for (int wC = 0; wC < ` + m + `;
                  wC += ` + d + `) {
                int xC = xCCorner + wC;

                if (xC < 0 || xC >= ` + t.inWidth + `) {
                  continue;
                }

                float value = getX(batch, xD, xR, xC, ch);

                // If a min / max value has already been found, use it. If not,
                // use the current value.
                float currMinMaxValue = mix(
                    value, minMaxValue, minMaxValueFound);
                if (value ` + x + ` currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ` + (i ? a ? "(((batch * " + t.inDepth + " + xD) * " + t.inHeight + " + xR) * " + t.inWidth + " + xC) * " + t.inChannels + " + ch" : "((xD * " + t.inHeight + " + xR) * " + t.inWidth + " + xC) * " + t.inChannels + " + ch" : "wD * " + f + " * " + m + ` +
                      wR * ` + m + " + wC") + `;
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;
        return;
      }
      var N = "max", I = e + "(" + e + "(" + e + "(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
      e === "avg" && (I = "avgValue / count");
      var C = Math.floor(s / 4) * 4, O = s % 4, D = `
      if (` + b + `) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ` + N + `(values, minMaxValue);
      }
    `;
      this.userCode = `
      const ivec3 strides =
        ivec3(` + o + ", " + c + ", " + l + `);
      const ivec3 pads = ivec3(` + g + ", " + y + ", " + w + `);
      const float initializationValue = ` + L + `;
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xD, int xR, int xC, int ch) {
        if (xC < 0 || xC >= ` + t.inWidth + `) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xD, xR, xC, ch);
      }

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xDCorner = xCorner.x;
        int xRCorner = xCorner.y;
        int xCCorner = xCorner.z;

        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
        // ? = to be determined
        vec4 minMaxValue = vec4(` + L + `);
        float avgValue = 0.0;
        count = 0.0;

        for (int wD = 0; wD < ` + p + `;
            wD += ` + u + `) {
          int xD = xDCorner + wD;

          if (xD < 0 || xD >= ` + t.inDepth + `) {
            continue;
          }

          for (int wR = 0; wR < ` + f + `;
            wR += ` + h + `) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ` + t.inHeight + `) {
              continue;
            }

            for (int wC = 0; wC < ` + C + `; wC += 4) {
              int xC = xCCorner + wC * ` + d + `;

              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ` + d + `, ch),
                getValue(batch, xD, xR, xC + 2 * ` + d + `, ch),
                getValue(batch, xD, xR, xC + 3 * ` + d + `, ch)
              );

              ` + D + `
            }

            int xC = xCCorner + ` + C + `;
            if (` + (O === 1) + `) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                initializationValue,
                initializationValue,
                initializationValue
              );

              ` + D + `
            } else if (` + (O === 2) + `) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ` + d + `, ch),
                initializationValue,
                initializationValue
              );

              ` + D + `
            } else if (` + (O === 3) + `) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ` + d + `, ch),
                getValue(batch, xD, xR, xC + 2 * ` + d + `, ch),
                initializationValue
              );

              ` + D + `
            }
          }
          setOutput(` + I + `);
        }
      }
    `;
    }
    return n;
  }();
  var a2 = function() {
    function n(t, e) {
      this.variableNames = ["x"];
      var r = t.windowSize, i = t.batchSize, a = t.inSize, s = t.outSize;
      this.outputShape = [i, s];
      var o = "0.0", c = "";
      e === "prod" ? o = "1.0" : e === "min" ? (o = "1.0 / 1e-20", c = "min") : e === "max" && (o = "-1.0 / 1e-20", c = "max");
      var l = e + "(" + e + "(" + e + "(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";
      e === "sum" ? l = "sumValue" : e === "prod" ? l = "prodValue" : e === "all" ? l = "allValue" : e === "any" && (l = "anyValue");
      var u = Math.floor(r / 4) * 4, h = r % 4, d = `
      if (` + (e === "sum") + `) {
        sumValue += dot(values, ones);
      } else if (` + (e === "prod") + `) {
        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
        prodValue *= tmp[0] * tmp[1];
      } else {
        minMaxValue = ` + c + `(values, minMaxValue);
      }
    `, p = "vec4";
      e === "all" ? (o = "1.0", d = `
        bool reducedAllValue = all(values);
        float floatedReducedAllValue = float(reducedAllValue);
        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
      `, p = "bvec4") : e === "any" && (o = "0.0", d = `
        bool reducedAnyValue = any(values);
        float floatedReducedAnyValue = float(reducedAnyValue);
        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
      `, p = "bvec4");
      var f = "";
      a % r > 0 && (f = `
        if (inIdx < 0 || inIdx >= ` + a + `) {
          return initializationValue;
        }
      `), this.userCode = `
      const float initializationValue = ` + o + `;
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ` + f + `
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ` + r + `;

        vec4 minMaxValue = vec4(` + o + `);
        float prodValue = 1.0;
        float sumValue = 0.0;
        float allValue = 1.0;
        float anyValue = 0.0;

        for (int i = 0; i < ` + u + `; i += 4) {
          int inIdx = inOffset + i;
          ` + p + " values = " + p + `(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ` + d + `
        }

        int inIdx = inOffset + ` + u + `;
        if (` + (h === 1) + `) {
          ` + p + " values = " + p + `(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          ` + d + `
        } else if (` + (h === 2) + `) {
          ` + p + " values = " + p + `(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          ` + d + `
        } else if (` + (h === 3) + `) {
          ` + p + " values = " + p + `(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          ` + d + `
        }
        setOutput(` + l + `);
      }
    `;
    }
    return n;
  }();
  var s2 = function() {
    function n(t, e) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = true, this.outputShape = t;
      for (var r = "", i = 0; i < 4; i++) {
        var a = "thisRC = rc;";
        i % 2 === 1 && (a += "thisRC.z += 1;"), i > 1 && (a += "thisRC.y += 1;"), r += `
        ` + a + `
        ` + (i > 0 ? "if(thisRC.y < rows && thisRC.z < cols){" : "") + `
          int flatIndex = getFlatIndex(thisRC);

          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));

          result[` + i + `] =
            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
        ` + (i > 0 ? "}" : "") + `
      `;
      }
      this.userCode = `
      ` + cz(e) + `
      ` + tp(t) + `

      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0.);

        ivec3 thisRC;
        int rows = ` + t[1] + `;
        int cols = ` + t[2] + `;

        ` + r + `

        setOutput(result);
      }
    `;
    }
    return n;
  }();
  function cz(n) {
    var t = mi(["r", "c", "d"], n);
    return `
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ` + t + `
      return ivec3(r, c, d);
    }
  `;
  }
  var lz = function() {
    function n(t, e, r) {
      this.variableNames = ["dy"], this.outputShape = [], this.outputShape = e.shape;
      var i = e.shape, a = i[1], s = i[2], o = t.shape, c = o[1], l = o[2], u = [r && c > 1 ? a - 1 : a, r && l > 1 ? s - 1 : s], h = [r && c > 1 ? c - 1 : c, r && l > 1 ? l - 1 : l], d = u[0] / h[0], p = u[1] / h[1], f = 1 / d, m = 1 / p, g = Math.ceil(f) * 2 + 2, y = Math.ceil(m) * 2 + 2;
      this.userCode = `
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(` + d + `);
        const float widthScale = float(` + p + `);

        const float invHeightScale = float(` + f + `);
        const float invWidthScale = float(` + m + `);

        const int winHeight = int(` + g + `);
        const int winWidth = int(` + y + `);

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(startRLerp - float(winHeight / 2));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(startCLerp - float(winWidth / 2));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ` + c + `) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ` + l + `) {
              continue;
            }

            float dxR = float(dyR) * heightScale;
            int topDxRIndex = int(floor(dxR));
            int bottomDxRIndex = int(min(ceil(dxR), ` + (a - 1) + `.0));
            float dxRLerp = dxR - float(topDxRIndex);
            float inverseDxRLerp = 1.0 - dxRLerp;

            float dxC = float(dyC) * widthScale;
            int leftDxCIndex = int(floor(dxC));
            int rightDxCIndex = int(min(ceil(dxC), ` + (s - 1) + `.0));
            float dxCLerp = dxC - float(leftDxCIndex);
            float inverseDxCLerp = 1.0 - dxCLerp;

            if (r == topDxRIndex && c == leftDxCIndex) {
              // topLeft
              accumulator +=
                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
            }

            if (r == topDxRIndex && c == rightDxCIndex) {
              // topRight
              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
            }

            if (r == bottomDxRIndex && c == leftDxCIndex) {
              // bottomLeft
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
            }

            if (r == bottomDxRIndex && c == rightDxCIndex) {
              // bottomRight
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `;
    }
    return n;
  }();
  var uz = function() {
    function n(t, e, r, i) {
      this.variableNames = ["A"], this.outputShape = [];
      var a = t[0], s = t[1], o = t[2], c = t[3];
      this.outputShape = [a, e, r, c];
      var l = [i && e > 1 ? s - 1 : s, i && r > 1 ? o - 1 : o], u = [i && e > 1 ? e - 1 : e, i && r > 1 ? r - 1 : r];
      this.userCode = `
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ` + l[0] / u[0] + `,
          ` + l[1] / u[1] + `);
      const vec2 inputShapeRC = vec2(` + s + ".0, " + o + `.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;

        // Compute the four integer indices.
        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);
        ivec2 sourceCeilRC = ivec2(
          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));

        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);
        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);
        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);
        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);

        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);

        float top = topLeft + (topRight - topLeft) * fracRC.y;
        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
        float newValue = top + (bottom - top) * fracRC.x;

        setOutput(newValue);
      }
    `;
    }
    return n;
  }();
  var hz = function() {
    function n(t, e, r, i) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = true, this.outputShape = [];
      var a = t[0], s = t[1], o = t[2], c = t[3];
      this.outputShape = [a, e, r, c];
      var l = [i && e > 1 ? s - 1 : s, i && r > 1 ? o - 1 : o], u = [i && e > 1 ? e - 1 : e, i && r > 1 ? r - 1 : r];
      this.userCode = `
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ` + l[0] / u[0] + `,
          ` + l[1] / u[1] + `,
          ` + l[1] / u[1] + `);
      const vec3 inputShapeRC = vec3(` + s + ".0, " + o + `.0,
                                     ` + o + `.0);

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;

        // Compute the four integer indices.
        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);
        ivec3 sourceCeilRC = ivec3(
          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ` + (c - 1) + `;
        bool hasNextRow = coords.z < ` + (r - 1) + `;

        // In parallel, construct four corners for all four components in
        // packed 2x2 cell.
        vec4 topLeft = vec4(
          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);

        vec4 bottomLeft = vec4(
          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);

        vec4 topRight = vec4(
          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);

        vec4 bottomRight = vec4(
          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);

        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);

        vec4 top = mix(topLeft, topRight, fracRC.yyzz);
        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
        vec4 newValue = mix(top, bottom, fracRC.x);

        setOutput(newValue);
      }
    `;
    }
    return n;
  }();
  var dz = function() {
    function n(t, e, r) {
      this.variableNames = ["dy"], this.outputShape = [], this.outputShape = e.shape;
      var i = e.shape, a = i[1], s = i[2], o = t.shape, c = o[1], l = o[2], u = [r && c > 1 ? a - 1 : a, r && l > 1 ? s - 1 : s], h = [r && c > 1 ? c - 1 : c, r && l > 1 ? l - 1 : l], d = u[0] / h[0], p = u[1] / h[1], f = 1 / d, m = 1 / p, g = Math.ceil(f) * 2 + 2, y = Math.ceil(m) * 2 + 2;
      this.userCode = `
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(` + d + `);
        const float widthScale = float(` + p + `);

        const float invHeightScale = float(` + f + `);
        const float invWidthScale = float(` + m + `);

        const int winHeight = int(` + g + `);
        const int winWidth = int(` + y + `);

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(floor(startRLerp - float(winHeight / 2)));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(floor(startCLerp - float(winWidth / 2)));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ` + c + `) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ` + l + `) {
              continue;
            }

            float sourceFracRow =
              float(` + u[0] + `) *
                (float(dyR) / float(` + h[0] + `));

            float sourceFracCol =
                float(` + u[1] + `) *
                  (float(dyC) / float(` + h[1] + `));

            int sourceNearestRow = int(min(
                float(int(` + a + `) - 1),
                ` + r + ` ? float(round(sourceFracRow)) :
                                  float(floor(sourceFracRow))));

            int sourceNearestCol = int(min(
                float(int(` + s + `) - 1),
                ` + r + ` ? float(round(sourceFracCol)) :
                                  float(floor(sourceFracCol))));

            if (r == sourceNearestRow && c == sourceNearestCol) {
              accumulator += getDy(b, dyR, dyC, d);
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `;
    }
    return n;
  }();
  var pz = function() {
    function n(t, e, r, i) {
      this.variableNames = ["A"], this.outputShape = [];
      var a = t[0], s = t[1], o = t[2], c = t[3];
      this.outputShape = [a, e, r, c];
      var l = [i && e > 1 ? s - 1 : s, i && r > 1 ? o - 1 : o], u = [i && e > 1 ? e - 1 : e, i && r > 1 ? r - 1 : r], h = i ? "0.5" : "0.0";
      this.userCode = `
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ` + l[0] / u[0] + `,
          ` + l[1] / u[1] + `);
      const vec2 inputShapeRC = vec2(` + s + ".0, " + o + `.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;

        // Compute the coordinators of nearest neighbor point.
        ivec2 sourceNearestRC = ivec2(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ` + h + `)));

        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);

        setOutput(newValue);
      }
    `;
    }
    return n;
  }();
  var fz = function() {
    function n(t, e) {
      this.variableNames = ["x"];
      var r = t.length;
      if (r > 4)
        throw new Error("WebGL backend: Reverse of rank-" + r + " tensor is not yet supported");
      if (this.outputShape = t, r === 1) {
        this.userCode = `
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(` + t[0] + ` - coord - 1));
        }
      `;
        return;
      }
      var i = function(o) {
        return e.indexOf(o) !== -1 && t[o] !== 1 ? t[o] + " - coords[" + o + "] - 1" : "coords[" + o + "]";
      }, a = t.map(function(o, c) {
        return i(c);
      }).join(","), s = Ze(r);
      this.userCode = `
      void main() {
        ` + s + ` coords = getOutputCoords();
        setOutput(getX(` + a + `));
      }
    `;
    }
    return n;
  }();
  var mz = function() {
    function n(t, e) {
      this.variableNames = ["x"], this.packedInputs = true, this.packedOutput = true;
      var r = t.length;
      if (r > 4)
        throw new Error("WebGL backend: Reverse of rank-" + r + " tensor is not yet supported");
      this.outputShape = t;
      var i = Bt("rc", r), a = i[r - 1] + " + 1 < " + this.outputShape[r - 1], s = i[r - 2] + " + 1 < " + this.outputShape[r - 2], o = Ze(r);
      r === 1 ? this.userCode = `
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(` + t[0] + ` - rc - 1),
            ` + t[0] + ` - rc - 1);
          if(` + a + `){
              result.g = getChannel(getX(` + t[0] + ` - (rc  + 1) - 1),
                ` + t[0] + ` - (rc  + 1) - 1);
          }
          setOutput(result);
        }
      ` : this.userCode = `
        void main() {
          ` + o + ` rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = ` + c(i.slice()) + `;
          if(` + a + `){
            result.g = ` + l(i.slice()) + `;
          }
          if(` + s + `) {
            result.b = ` + u(i.slice()) + `;
            if(` + a + `) {
              result.a = ` + h(i.slice()) + `;
            }
          }
          setOutput(result);
        }
    `;
      function c(f) {
        return d(f);
      }
      function l(f) {
        return f[r - 1] = "(" + f[r - 1] + " + 1)", d(f);
      }
      function u(f) {
        return f[r - 2] = "(" + f[r - 2] + " + 1)", d(f);
      }
      function h(f) {
        return f[r - 1] = "(" + f[r - 1] + " + 1)", f[r - 2] = "(" + f[r - 2] + " + 1)", d(f);
      }
      function d(f) {
        var m = t.map(function(w, b) {
          return p(b, f);
        }), g = m.join(","), y = m.slice(-2).join(",");
        return "getChannel(getX(" + g + "), vec2(" + y + "))";
      }
      function p(f, m) {
        return e.indexOf(f) !== -1 && t[f] !== 1 ? t[f] + " - " + m[f] + " - 1" : "" + m[f];
      }
    }
    return n;
  }();
  var o2 = function() {
    function n(t, e, r, i, a, s, o) {
      this.variableNames = ["updates", "indices", "defaultValue"], this.outputShape = s;
      var c = Ze(a.length), l = Ze(s.length), u = "";
      r === 1 ? u = "i" : r === 2 && (u = "i, j");
      var h = "getIndices(" + u + ")", d = "";
      i === 1 ? d = "i" : i === 2 && (d = "i, coords[1]");
      var p = "getUpdates(" + d + ")", f = e > 1 ? "strides[j]" : "strides";
      this.userCode = `
        ` + c + " strides = " + c + "(" + a + `);

        void main() {
          ` + l + ` coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ` + t + `; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ` + e + `; j++) {
              int index = round(` + h + `);
              flattenedIndex += index * ` + f + `;
            }
            if (flattenedIndex == coords[0]) {
              sum += ` + p + `;
              found = true;
            }
          }
          setOutput(mix(getDefaultValue(), sum, float(found)));
        }
      `;
    }
    return n;
  }();
  var gz = function() {
    function n(t, e) {
      this.variableNames = ["x", "segmentIds"];
      var r = t.windowSize, i = t.batchSize, a = t.inSize, s = t.numSegments, o = s * Math.ceil(a / r);
      this.outputShape = [i, o];
      var c = "0.0", l = "sumValue", u = Math.floor(r / 4) * 4, h = r % 4, d = `
        sumValue += dot(values, segFilter);
    `, p = "";
      a % r > 0 && (p = `
        if (inIdx < 0 || inIdx >= ` + a + `) {
          return initializationValue;
        }
      `);
      var f = "";
      a % r > 0 && (f = `
        if (inIdx < 0 || inIdx >= ` + a + `) {
          return -1.0;
        }
      `), this.userCode = `
      const float initializationValue = ` + c + `;

      float getValue(int batch, int inIdx) {
        ` + p + `
        return getX(batch, inIdx);
      }

      float getSegmentIdAtIndex(int inIdx) {
        ` + f + `
        return getSegmentIds(inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = int(floor(float(outIdx) / float(
          ` + s + ")) * float(" + r + `));
        int currentSeg = int(mod(float(outIdx), float(` + s + `)));

        float sumValue = 0.0;

        for (int i = 0; i < ` + u + `; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
          );

          ` + d + `
        }

        int inIdx = inOffset + ` + u + `;
        if (` + (h === 1) + `) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            0,
            0,
            0
          );

          ` + d + `
        } else if (` + (h === 2) + `) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
              0,
              0
          );

          ` + d + `
        } else if (` + (h === 3) + `) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            0
          );

          ` + d + `
        }
        setOutput(` + l + `);
      }
    `;
    }
    return n;
  }();
  var yz = function() {
    function n(t, e, r) {
      this.variableNames = ["c", "a", "b"], this.outputShape = e;
      var i, a;
      if (r > 4)
        throw Error("Where for rank " + r + " is not yet supported");
      if (r === 1)
        a = "resRC", i = "resRC";
      else {
        for (var s = ["resRC.x", "resRC.y", "resRC.z", "resRC.w"], o = [], c = [], l = 0; l < e.length; l++)
          c.push("" + s[l]), l < t && o.push("" + s[l]);
        i = o.join(), a = c.join();
      }
      var u = Ze(r);
      this.userCode = `
      void main() {
        ` + u + ` resRC = getOutputCoords();
        float cVal = getC(` + i + `);
        if (cVal >= 1.0) {
          setOutput(getA(` + a + `));
        } else {
          setOutput(getB(` + a + `));
        }
      }
    `;
    }
    return n;
  }();
  var wz = function() {
    function n(t) {
      this.variableNames = ["source"], this.outputShape = t, this.rank = t.length;
      var e = Ze(this.rank), r = "uniform int start[" + this.rank + "];", i = vz(this.rank), a, s = t.map(function(o, c) {
        return "sourceLoc." + lp[c] + " = start[" + c + "] + coords." + lp[c] + ";";
      });
      a = `
        ` + e + ` sourceLoc;
        ` + e + ` coords = getOutputCoords();
        ` + s.join(`
`) + `
      `, this.userCode = `
      ` + r + `
      void main() {
        ` + a + `
        setOutput(getSource(` + i + `));
      }
    `;
    }
    return n.prototype.getCustomSetupFunc = function(t) {
      var e = this;
      if (t.length !== this.rank)
        throw Error("The rank (" + this.rank + ") of the program must match the " + ("length of start (" + t.length + ")"));
      return function(r, i) {
        if (e.startLoc == null && (e.startLoc = r.getUniformLocationNoThrow(i, "start"), e.startLoc == null))
          return;
        r.gl.uniform1iv(e.startLoc, t);
      };
    }, n;
  }(), lp = ["x", "y", "z", "w", "u", "v"];
  function vz(n) {
    if (n === 1)
      return "sourceLoc";
    if (n <= 6)
      return lp.slice(0, n).map(function(t) {
        return "sourceLoc." + t;
      }).join(",");
    throw Error("Slicing for rank " + n + " is not yet supported");
  }
  var bz = function() {
    function n(t) {
      this.variableNames = ["source"], this.packedInputs = true, this.packedOutput = true, this.outputShape = t, this.rank = t.length;
      var e = Ze(this.rank), r = Bt("coords", this.rank), i = Bt("sourceLoc", this.rank), a = this.rank === 1 ? "sourceLoc" : "vec2(" + i.slice(-2).join() + ")", s = "getChannel(getSource(" + i.join() + "), " + a + ")", o = `
      result.x = ` + s + `;
      if (++` + r[this.rank - 1] + " < " + t[this.rank - 1] + `) {
        ++` + i[this.rank - 1] + `;
        result.y = ` + s + `;
        --` + i[this.rank - 1] + `;
      }
    `, c = this.rank === 1 ? "" : `
      --` + r[this.rank - 1] + `;
      if (++` + r[this.rank - 2] + " < " + t[this.rank - 2] + `) {
        ++` + i[this.rank - 2] + `;
        result.z = ` + s + `;
        if (++` + r[this.rank - 1] + " < " + t[this.rank - 1] + `) {
          ++` + i[this.rank - 1] + `;
          result.w = ` + s + `;
        }
      }
    `, l = this.rank <= 4 ? `sourceLoc = coords +
            ` + e + "(" + t.map(function(u, h) {
        return "start[" + h + "]";
      }).join() + ");" : t.map(function(u, h) {
        return i[h] + " = " + r[h] + " + start[" + h + "];";
      }).join(`
`);
      this.userCode = `
      uniform int start[` + this.rank + `];
      void main() {
        ` + e + ` coords = getOutputCoords();
        ` + e + ` sourceLoc;
        ` + l + `
        vec4 result = vec4(0.);
        ` + o + `
        ` + c + `
        setOutput(result);
      }
    `;
    }
    return n.prototype.getCustomSetupFunc = function(t) {
      var e = this;
      if (t.length !== this.rank)
        throw Error("The rank (" + this.rank + ") of the program must match the " + ("length of start (" + t.length + ")"));
      return function(r, i) {
        if (e.startLoc == null && (e.startLoc = r.getUniformLocationNoThrow(i, "start"), e.startLoc == null))
          return;
        r.gl.uniform1iv(e.startLoc, t);
      };
    }, n;
  }();
  var xz = function() {
    function n(t, e, r) {
      this.variableNames = ["x"], this.outputShape = r;
      var i = r.length, a = Ze(r.length), s = Ze(r.length), o = "";
      if (i === 1)
        o = "coords * strides + begin";
      else {
        var c = 0;
        o = r.map(function(l, u) {
          return c++, r.length === 1 ? "coords * strides[" + u + "] + begin[" + u + "]" : "coords[" + (c - 1) + "] * strides[" + u + "] + begin[" + u + "]";
        }).join(",");
      }
      this.userCode = `
      ` + a + " begin = " + a + "(" + t + `);
      ` + a + " strides = " + a + "(" + e + `);

      void main() {
        ` + s + ` coords = getOutputCoords();
        setOutput(getX(` + o + `));
      }
    `;
    }
    return n;
  }();
  var Lz = function() {
    function n(t) {
      this.gpgpu = t, this.numUsedTextures = 0, this.numFreeTextures = 0, this._numBytesAllocated = 0, this._numBytesFree = 0, this.freeTextures = {}, this.logEnabled = false, this.usedTextures = {};
    }
    return n.prototype.acquireTexture = function(t, e, r) {
      var i = l2(e, r), a = u2(t, i, r);
      a in this.freeTextures || (this.freeTextures[a] = []), a in this.usedTextures || (this.usedTextures[a] = []);
      var s = c2(t, i, this.gpgpu.gl, this.gpgpu.textureConfig, r);
      if (this.freeTextures[a].length > 0) {
        this.numFreeTextures--, this.numUsedTextures++, this._numBytesFree -= s, this.log();
        var o = this.freeTextures[a].shift();
        return this.usedTextures[a].push(o), o;
      }
      var c;
      return i === Dt.PACKED_2X2_FLOAT32 ? c = this.gpgpu.createPackedMatrixTexture(t[0], t[1]) : i === Dt.PACKED_2X2_FLOAT16 ? c = this.gpgpu.createFloat16PackedMatrixTexture(t[0], t[1]) : i === Dt.UNPACKED_FLOAT32 ? c = this.gpgpu.createFloat32MatrixTexture(t[0], t[1]) : i === Dt.UNPACKED_FLOAT16 ? c = this.gpgpu.createFloat16MatrixTexture(t[0], t[1]) : i === Dt.PACKED_4X1_UNSIGNED_BYTE && (c = this.gpgpu.createUnsignedBytesMatrixTexture(t[0], t[1])), this.usedTextures[a].push(c), this.numUsedTextures++, this._numBytesAllocated += s, this.log(), c;
    }, n.prototype.releaseTexture = function(t, e, r, i) {
      if (this.freeTextures == null)
        return;
      var a = l2(r, i), s = u2(e, a, i);
      s in this.freeTextures || (this.freeTextures[s] = []);
      var o = c2(e, a, this.gpgpu.gl, this.gpgpu.textureConfig, i), c = _.env().get("WEBGL_DELETE_TEXTURE_THRESHOLD");
      c !== -1 && this._numBytesAllocated > c ? (this.gpgpu.deleteMatrixTexture(t), this._numBytesAllocated -= o) : (this.freeTextures[s].push(t), this.numFreeTextures++, this._numBytesFree += o), this.numUsedTextures--;
      var l = this.usedTextures[s], u = l.indexOf(t);
      if (u < 0)
        throw new Error("Cannot release a texture that was never provided by this texture manager");
      l.splice(u, 1), this.log();
    }, n.prototype.log = function() {
      if (!this.logEnabled)
        return;
      var t = this.numFreeTextures + this.numUsedTextures;
      console.log("Free/Used", this.numFreeTextures + " / " + this.numUsedTextures, "(" + t + ")");
      var e = this._numBytesFree / this._numBytesAllocated;
      console.log("Bytes allocated: " + this._numBytesAllocated), console.log("Bytes unused: " + this._numBytesFree + " (" + Math.round(100 * e) + "%)");
    }, Object.defineProperty(n.prototype, "numBytesAllocated", {get: function() {
      return this._numBytesAllocated;
    }, enumerable: true, configurable: true}), Object.defineProperty(n.prototype, "numBytesFree", {get: function() {
      return this._numBytesFree;
    }, enumerable: true, configurable: true}), n.prototype.getNumUsedTextures = function() {
      return this.numUsedTextures;
    }, n.prototype.getNumFreeTextures = function() {
      return this.numFreeTextures;
    }, n.prototype.dispose = function() {
      var t = this;
      if (this.freeTextures == null)
        return;
      for (var e in this.freeTextures)
        this.freeTextures[e].forEach(function(r) {
          t.gpgpu.deleteMatrixTexture(r);
        });
      for (var e in this.usedTextures)
        this.usedTextures[e].forEach(function(i) {
          t.gpgpu.deleteMatrixTexture(i);
        });
      this.freeTextures = null, this.usedTextures = null, this.numUsedTextures = 0, this.numFreeTextures = 0, this._numBytesAllocated = 0, this._numBytesFree = 0;
    }, n;
  }();
  function Sz(n, t) {
    var e = n;
    if (t === e.R32F)
      return 4;
    if (t === e.R16F)
      return 2;
    if (t === e.RGBA32F)
      return 16;
    if (t === n.RGBA)
      return 16;
    if (t === e.RGBA16F)
      return 8;
    throw new Error("Unknown internal format " + t);
  }
  function c2(n, t, e, r, i) {
    var a = Iz(t, r), s;
    if (i) {
      var o = ea(n[0], n[1]), c = o[0], l = o[1];
      s = c * l;
    } else {
      var u = is(n[0], n[1]), h = u[0], d = u[1];
      s = h * d;
    }
    var p = Sz(e, a);
    return s * p;
  }
  function Iz(n, t) {
    switch (n) {
      case Dt.PACKED_2X2_FLOAT32:
        return ap(t);
      case Dt.PACKED_2X2_FLOAT16:
        return sp(t);
      case Dt.UNPACKED_FLOAT32:
        return np(t);
      case Dt.UNPACKED_FLOAT16:
        return rp(t);
      case Dt.PACKED_4X1_UNSIGNED_BYTE:
        return ip(t);
      default:
        throw new Error("Unknown physical texture type " + n);
    }
  }
  function Az(n) {
    return _.env().getBool("WEBGL_RENDER_FLOAT32_ENABLED") ? n ? Dt.PACKED_2X2_FLOAT32 : Dt.UNPACKED_FLOAT32 : n ? Dt.PACKED_2X2_FLOAT16 : Dt.UNPACKED_FLOAT16;
  }
  function l2(n, t) {
    if (n === cn.UPLOAD)
      return Dt.PACKED_2X2_FLOAT32;
    if (n === cn.RENDER || n == null)
      return Az(t);
    if (n === cn.DOWNLOAD || n === cn.PIXELS)
      return Dt.PACKED_4X1_UNSIGNED_BYTE;
    throw new Error("Unknown logical texture type " + n);
  }
  function u2(n, t, e) {
    return n[0] + "_" + n[1] + "_" + t + "_" + e;
  }
  var Nz = function() {
    function n(t, e) {
      this.variableNames = ["A"];
      for (var r = new Array(t.length), i = 0; i < r.length; i++)
        r[i] = t[i] * e[i];
      this.outputShape = r, this.rank = r.length;
      var a = Ze(this.rank), s = Tz(t);
      this.userCode = `
      void main() {
        ` + a + ` resRC = getOutputCoords();
        setOutput(getA(` + s + `));
      }
    `;
    }
    return n;
  }();
  function Tz(n) {
    var t = n.length;
    if (t > 5)
      throw Error("Tile for rank " + t + " is not yet supported");
    if (t === 1)
      return "imod(resRC, " + n[0] + ")";
    for (var e = ["resRC.x", "resRC.y", "resRC.z", "resRC.w", "resRC.u"], r = [], i = 0; i < n.length; i++)
      r.push("imod(" + e[i] + ", " + n[i] + ")");
    return r.join();
  }
  var De = function() {
    function n(t, e) {
      this.variableNames = ["A"], this.outputShape = t, this.userCode = `
      float unaryOperation(float x) {
        ` + e + `
      }

      void main() {
        float x = getAAtOutCoords();
        float y = unaryOperation(x);

        setOutput(y);
      }
    `;
    }
    return n;
  }(), rr = "if (isnan(x)) return x;", _z = "return x;", h2 = "return abs(x);", d2 = rr + `
  return (x < 0.0) ? 0.0 : x;
`, p2 = rr + `
  return (x < 0.0) ? 0.0 : min(6.0, x);
`, f2 = "return (x >= 0.0) ? x : (exp(x) - 1.0);", Cz = `
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ` + _.backend_util.SELU_SCALEALPHA + `;
  float scale = ` + _.backend_util.SELU_SCALE + `;
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`;
  function Rz(n) {
    return n === void 0 && (n = 0), rr + (`
    return x > 0.0 ? 1.0 : float(` + n + `);
  `);
  }
  var m2 = "return -x;", g2 = "return ceil(x);", y2 = "return floor(x);", Oz = `
  if (isnan(x)) { return 0.0; }
  return sign(x);
`, Ez = "return float(isnan(x));", Dz = "return float(isinf(x));", kz = "return float(!isnan(x) && !isinf(x));", Fz = `
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`, v2 = "return exp(x);", w2 = "return exp(x) - 1.0;", Wz = `if (x < 0.0) return NAN;
  return log(x);`, Uz = "return log(1.0 + x);", Bz = "return sqrt(x);", zz = "return inversesqrt(x);", Pz = "return 1.0 / (1.0 + exp(-1.0 * x));", Mz = `
  float epsilon = 1.1920928955078125e-7;
  float threshold = log(epsilon) + 2.0;

  bool too_large = x > -threshold;
  bool too_small = x < threshold;

  float result;
  float exp_x = exp(x);

  if (too_large){
    result = x;
  }
  else if (too_small){
    result = exp_x;
  }
  else{
    result = log(exp_x + 1.0);
  }
  return result;
`, Hz = rr + `
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`, Vz = rr + `
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`, Gz = rr + `
  return atan(x);
`, qz = `
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`, Yz = `
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`, Kz = `
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`, jz = rr + "return log(x + sqrt(x * x + 1.0));", $z = rr + `
  if (x < 1.0) return NAN;
  return log(x + sqrt(x * x - 1.0));`, Xz = rr + `
  if ((x < -1.0) || (x > 1.0)) return NAN;
  return (log(1.0 + x) - log(1.0 - x)) / 2.0;`, Jz = `
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ` + _.backend_util.ERF_P + `;
  float a1 = ` + _.backend_util.ERF_A1 + `;
  float a2 = ` + _.backend_util.ERF_A2 + `;
  float a3 = ` + _.backend_util.ERF_A3 + `;
  float a4 = ` + _.backend_util.ERF_A4 + `;
  float a5 = ` + _.backend_util.ERF_A5 + `;

  float sign = sign(x);
  x = abs(x);
  float t = 1.0 / (1.0 + p * x);
  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`, Zz = "return 1.0 / x;", Qz = "return float(!(x >= 1.0));", tc = "return x;";
  var eP = "return x;", tP = `
  vec4 result = log(x);
  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
  result.r = isNaN.r == 1.0 ? NAN : result.r;
  result.g = isNaN.g == 1.0 ? NAN : result.g;
  result.b = isNaN.b == 1.0 ? NAN : result.b;
  result.a = isNaN.a == 1.0 ? NAN : result.a;

  return result;
`, b2 = `
  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`, x2 = `
  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`, L2 = `
  vec4 result;

  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);

  return result;
`, hs = function() {
    function n(t, e) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = true, this.outputShape = t, this.userCode = `
      vec4 unaryOperation(vec4 x) {
        ` + e + `
      }

      void main() {
        vec4 x = getAAtOutCoords();
        vec4 y = unaryOperation(x);

        setOutput(y);
      }
    `;
    }
    return n;
  }();
  var nP = function() {
    function n(t) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = false, this.outputShape = t;
      var e = t.length, r = Bt("rc", e), i = Ze(e), a = oU(e, r), s = r.slice(-2), o = e <= 1 ? "rc" : "vec2(" + s.join(",") + ")";
      this.userCode = `
      void main() {
        ` + i + ` rc = getOutputCoords();
        vec4 packedInput = getA(` + a + `);

        setOutput(getChannel(packedInput, ` + o + `));
      }
    `;
    }
    return n;
  }();
  var S2 = _.backend_util.segment_util, rP = _.kernel_impls.split, iP = _.kernel_impls.tile, aP = _.kernel_impls.topkImpl, sP = _.kernel_impls.whereImpl, oP = 1e-7, cP = 1e-4, nc = {};
  function lP(n) {
    return n in nc || (nc[n] = {}), nc[n];
  }
  function rc(n, t) {
    if (t === void 0 && (t = false), n === "linear")
      return t ? eP : _z;
    if (n === "relu")
      return t ? b2 : d2;
    if (n === "elu")
      return t ? L2 : f2;
    if (n === "relu6")
      return t ? x2 : p2;
    if (n === "prelu")
      return t ? kb : Db;
    throw new Error("Activation " + n + " has not been implemented for the WebGL backend.");
  }
  var uP = 128, hP = 600;
  function dP() {
    return _.env().global.screen == null ? 1024 : _.env().global.screen.height * _.env().global.screen.width * window.devicePixelRatio * hP / 1024 / 1024;
  }
  var I2 = 1e3, A2 = function(n) {
    fW(t, n);
    function t(e) {
      var r = n.call(this) || this;
      if (r.pendingRead = new WeakMap(), r.pendingDisposal = new WeakSet(), r.dataRefCount = new WeakMap(), r.numBytesInGPU = 0, r.uploadWaitMs = 0, r.downloadWaitMs = 0, r.warnedAboutMemory = false, r.warnedAboutCPUBackend = false, r.pendingDeletes = 0, r.disposed = false, !_.env().getBool("HAS_WEBGL"))
        throw new Error("WebGL is not supported on this device");
      if (e == null) {
        var i = Mn(_.env().getNumber("WEBGL_VERSION"));
        r.binaryCache = lP(_.env().getNumber("WEBGL_VERSION")), r.gpgpu = new r2(i), r.canvas = i.canvas, r.gpgpuCreatedLocally = true;
      } else
        r.gpgpu = e, r.binaryCache = {}, r.gpgpuCreatedLocally = false, r.canvas = e.gl.canvas;
      return r.textureManager = new Lz(r.gpgpu), r.numMBBeforeWarning = dP(), r.texData = new _.DataStorage(r, _.engine()), r;
    }
    return t.prototype.numDataIds = function() {
      return this.texData.numDataIds() + (this.cpuBackend ? this.cpuBackend.numDataIds() : 0) - this.pendingDeletes;
    }, t.prototype.write = function(e, r, i) {
      if ((_.env().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS") || _.env().getBool("DEBUG")) && this.checkNumericalProblems(e), i === "complex64" && e != null)
        throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");
      var a = {};
      return this.texData.set(a, {shape: r, dtype: i, values: e, usage: cn.UPLOAD, refCount: 1, complexParentRefCount: 0}), a;
    }, t.prototype.incRef = function(e) {
      var r = this.texData.get(e);
      r.refCount++;
    }, t.prototype.decRef = function(e) {
      if (this.texData.has(e)) {
        var r = this.texData.get(e);
        r.refCount--;
      }
    }, t.prototype.move = function(e, r, i, a) {
      if (_.env().getBool("DEBUG") && this.checkNumericalProblems(r), a === "complex64")
        throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");
      this.texData.set(e, {shape: i, dtype: a, values: r, usage: cn.UPLOAD, refCount: 1, complexParentRefCount: 0});
    }, t.prototype.disposeIntermediateTensorInfo = function(e) {
      var r = e.dataId;
      if (this.texData.has(r)) {
        var i = this.texData.get(r);
        i.refCount--, i.refCount < 1 && this.disposeData(r);
      }
    }, t.prototype.readSync = function(e) {
      var r = this.texData.get(e), i = r.values, a = r.dtype, s = r.complexTensorInfos, o = r.slice, c = r.shape, l = r.isPacked;
      if (o != null) {
        var u = void 0;
        l ? u = new hs(c, tc) : u = new De(c, tc);
        var h = this.runWebGLProgram(u, [{dataId: e, shape: c, dtype: a}], a), d = this.readSync(h.dataId);
        return this.disposeIntermediateTensorInfo(h), d;
      }
      if (i != null)
        return this.convertAndCacheOnCPU(e);
      if (a === "string")
        return i;
      var p = this.activeTimers != null, f;
      p && (f = _.util.now());
      var m;
      if (a === "complex64") {
        var g = this.readSync(s.real.dataId), y = this.readSync(s.imag.dataId);
        m = _.backend_util.mergeRealAndImagArrays(g, y);
      } else
        m = this.getValuesFromTexture(e);
      return p && (this.downloadWaitMs += _.util.now() - f), this.convertAndCacheOnCPU(e, m);
    }, t.prototype.read = function(e) {
      return Yo(this, void 0, void 0, function() {
        var r, i, a, s, o, c, l, u, h, d, p, f, m, g, y, w, b, L, x, N, I, C;
        return Ko(this, function(O) {
          switch (O.label) {
            case 0:
              if (this.pendingRead.has(e))
                return r = this.pendingRead.get(e), [2, new Promise(function(D) {
                  return r.push(D);
                })];
              if (i = this.texData.get(e), a = i.values, s = i.shape, o = i.slice, c = i.dtype, l = i.complexTensorInfos, u = i.isPacked, o != null)
                return h = void 0, u ? h = new hs(s, tc) : h = new De(s, tc), d = this.runWebGLProgram(h, [{dataId: e, shape: s, dtype: c}], c), p = this.read(d.dataId), this.disposeIntermediateTensorInfo(d), [2, p];
              if (a != null)
                return [2, this.convertAndCacheOnCPU(e)];
              if (!_.env().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED") && _.env().getNumber("WEBGL_VERSION") === 2)
                throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");
              return f = null, c !== "complex64" && _.env().get("WEBGL_BUFFER_SUPPORTED") && (m = this.decode(e), g = this.texData.get(m.dataId), f = (C = this.gpgpu).createBufferFromTexture.apply(C, [g.texture].concat(as(s)))), this.pendingRead.set(e, []), c !== "complex64" ? [4, this.gpgpu.createAndWaitForFence()] : [3, 2];
            case 1:
              O.sent(), O.label = 2;
            case 2:
              return c === "complex64" ? [4, Promise.all([this.read(l.real.dataId), this.read(l.imag.dataId)])] : [3, 4];
            case 3:
              return w = O.sent(), b = w[0], L = w[1], y = _.backend_util.mergeRealAndImagArrays(b, L), [3, 5];
            case 4:
              f == null ? y = this.getValuesFromTexture(e) : (x = _.util.sizeFromShape(s), y = this.gpgpu.downloadFloat32MatrixFromBuffer(f, x)), O.label = 5;
            case 5:
              return m != null && this.disposeIntermediateTensorInfo(m), N = this.convertAndCacheOnCPU(e, y), I = this.pendingRead.get(e), this.pendingRead.delete(e), I.forEach(function(D) {
                return D(N);
              }), this.pendingDisposal.has(e) && (this.pendingDisposal.delete(e), this.disposeData(e), this.pendingDeletes--), [2, N];
          }
        });
      });
    }, t.prototype.checkNumericalProblems = function(e) {
      if (e == null)
        return;
      for (var r = 0; r < e.length; r++) {
        var i = e[r];
        if (!ib(i))
          throw _.env().getBool("WEBGL_RENDER_FLOAT32_CAPABLE") ? Error("The value " + i + " cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'") : Error("The value " + i + " cannot be represented on this device.");
      }
    }, t.prototype.getValuesFromTexture = function(e) {
      var r, i = this.texData.get(e), a = i.shape, s = i.dtype, o = i.isPacked, c = _.util.sizeFromShape(a);
      if (_.env().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")) {
        var l = this.decode(e), u = this.texData.get(l.dataId), h = (r = this.gpgpu).downloadMatrixFromPackedTexture.apply(r, [u.texture].concat(as(a))).subarray(0, c);
        return this.disposeIntermediateTensorInfo(l), h;
      }
      var d = _.env().getBool("WEBGL_PACK") && o === true, p = d ? Xo(a) : a, f = d ? new FB(p) : new kB(p), m = this.runWebGLProgram(f, [{shape: p, dtype: s, dataId: e}], "float32"), g = this.texData.get(m.dataId), y = this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(g.texture, g.texShape[0], g.texShape[1]).subarray(0, c);
      return this.disposeIntermediateTensorInfo(m), y;
    }, t.prototype.time = function(e) {
      return Yo(this, void 0, void 0, function() {
        var r, i, a, s, o, c, l;
        return Ko(this, function(u) {
          switch (u.label) {
            case 0:
              return r = this.activeTimers, i = [], a = false, this.programTimersStack == null ? (this.programTimersStack = i, a = true) : this.activeTimers.push(i), this.activeTimers = i, e(), s = _.util.flatten(this.activeTimers.map(function(h) {
                return h.query;
              })).filter(function(h) {
                return h != null;
              }), o = _.util.flatten(this.activeTimers.map(function(h) {
                return h.name;
              })).filter(function(h) {
                return h != null;
              }), this.activeTimers = r, a && (this.programTimersStack = null), c = {uploadWaitMs: this.uploadWaitMs, downloadWaitMs: this.downloadWaitMs, kernelMs: null, wallMs: null}, _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0 ? [4, Promise.all(s)] : [3, 2];
            case 1:
              return l = u.sent(), c.kernelMs = _.util.sum(l), c.getExtraProfileInfo = function() {
                return l.map(function(h, d) {
                  return {name: o[d], ms: h};
                }).map(function(h) {
                  return h.name + ": " + h.ms;
                }).join(", ");
              }, [3, 3];
            case 2:
              c.kernelMs = {error: "WebGL query timers are not supported in this environment."}, u.label = 3;
            case 3:
              return this.uploadWaitMs = 0, this.downloadWaitMs = 0, [2, c];
          }
        });
      });
    }, t.prototype.memory = function() {
      return {unreliable: false, numBytesInGPU: this.numBytesInGPU, numBytesInGPUAllocated: this.textureManager.numBytesAllocated, numBytesInGPUFree: this.textureManager.numBytesFree};
    }, t.prototype.startTimer = function() {
      return _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0 ? this.gpgpu.beginQuery() : {startMs: _.util.now(), endMs: null};
    }, t.prototype.endTimer = function(e) {
      return _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0 ? (this.gpgpu.endQuery(), e) : (e.endMs = _.util.now(), e);
    }, t.prototype.getQueryTime = function(e) {
      return Yo(this, void 0, void 0, function() {
        var r;
        return Ko(this, function(i) {
          return _.env().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE") > 0 ? [2, this.gpgpu.waitForQueryAndGetTime(e)] : (r = e, [2, r.endMs - r.startMs]);
        });
      });
    }, t.prototype.disposeData = function(e) {
      if (this.pendingDisposal.has(e))
        return;
      if (this.pendingRead.has(e)) {
        this.pendingDisposal.add(e), this.pendingDeletes++;
        return;
      }
      if (!this.texData.has(e))
        return;
      if (this.texData.get(e).complexParentRefCount > 0) {
        this.texData.get(e).refCount--;
        return;
      }
      this.releaseGPUData(e);
      var r = this.texData.get(e).complexTensorInfos;
      r != null && (this.texData.get(r.real.dataId).complexParentRefCount--, this.disposeIntermediateTensorInfo(r.real), this.texData.get(r.imag.dataId).complexParentRefCount--, this.disposeIntermediateTensorInfo(r.imag)), this.texData.delete(e);
    }, t.prototype.releaseGPUData = function(e) {
      var r = this.texData.get(e), i = r.texture, a = r.dtype, s = r.texShape, o = r.usage, c = r.isPacked, l = r.slice, u = l && l.origDataId || e, h = this.dataRefCount.get(u);
      h > 1 ? this.dataRefCount.set(u, h - 1) : (this.dataRefCount.delete(u), i != null && (this.numBytesInGPU -= this.computeBytes(s, a), this.textureManager.releaseTexture(i, s, o, c)));
      var d = this.texData.get(e);
      d.texture = null, d.texShape = null, d.isPacked = false, d.slice = null;
    }, t.prototype.getTexture = function(e) {
      return this.uploadToGPU(e), this.texData.get(e).texture;
    }, t.prototype.getDataInfo = function(e) {
      return this.texData.get(e);
    }, t.prototype.getCPUBackend = function() {
      return _.env().getBool("WEBGL_CPU_FORWARD") ? (this.cpuBackend == null && (this.cpuBackend = _.engine().findBackend("cpu")), this.cpuBackend) : null;
    }, t.prototype.shouldExecuteOnCPU = function(e, r) {
      var i = this;
      r === void 0 && (r = uP);
      var a = this.getCPUBackend();
      return !this.warnedAboutCPUBackend && a == null && (console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."), this.warnedAboutCPUBackend = true), a != null && e.every(function(s) {
        return i.texData.get(s.dataId).texture == null && _.util.sizeFromShape(s.shape) < r;
      });
    }, t.prototype.getGPGPUContext = function() {
      return this.gpgpu;
    }, t.prototype.slice = function(e, r, i) {
      if (this.shouldExecuteOnCPU([e])) {
        var a = tU(this.texData.get(e.dataId).values, r, i, e.shape, e.dtype);
        return this.makeOutput(i, e.dtype, a);
      }
      if (_.util.sizeFromShape(i) === 0)
        return _.tensor([], i, e.dtype);
      var s = this.texData.get(e.dataId).isPacked, o = _.slice_util.isSliceContinous(e.shape, r, i);
      if (s || !o) {
        var c = _.env().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new bz(i) : new wz(i), l = c.getCustomSetupFunc(r);
        return this.compileAndRun(c, [e], null, l);
      }
      return this.uploadToGPU(e.dataId), this.shallowSlice(e, r, i);
    }, t.prototype.shallowSlice = function(e, r, i) {
      var a = this.texData.get(e.dataId), s = this.makeOutput(i, e.dtype), o = this.texData.get(s.dataId);
      Object.assign(o, a), o.shape = i, o.dtype = e.dtype;
      var c = _.slice_util.computeFlatOffset(r, e.strides);
      a.slice && (c += a.slice.flatOffset), o.slice = {flatOffset: c, origDataId: a.slice && a.slice.origDataId || e.dataId};
      var l = this.dataRefCount.get(o.slice.origDataId) || 1;
      return this.dataRefCount.set(o.slice.origDataId, l + 1), s;
    }, t.prototype.stridedSlice = function(e, r, i, a) {
      var s = this, o = this.tryRunOnCpuOrThrow([e], function() {
        return s.cpuBackend.stridedSlice(e, r, i, a);
      });
      if (o)
        return o;
      var c = _.slice_util.computeOutShape(r, i, a);
      if (c.some(function(u) {
        return u === 0;
      }))
        return _.tensor([], c);
      var l = new xz(r, a, c);
      return this.compileAndRun(l, [e]);
    }, t.prototype.reverse = function(e, r) {
      var i = _.env().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new mz(e.shape, r) : new fz(e.shape, r);
      return this.compileAndRun(i, [e]);
    }, t.prototype.neg = function(e) {
      var r = this, i = this.tryRunOnCpuOrThrow([e], function() {
        return r.cpuBackend.neg(e);
      });
      if (i)
        return i;
      if (_.env().getBool("WEBGL_PACK_UNARY_OPERATIONS"))
        return this.packedUnaryOp(e, m2, e.dtype);
      var a = new De(e.shape, m2);
      return this.compileAndRun(a, [e]);
    }, t.prototype.batchMatMul = function(e, r, i, a) {
      var s = i ? e.shape[2] : e.shape[1], o = a ? r.shape[1] : r.shape[2], c = i ? e.shape[1] : e.shape[2], l = Math.max(e.shape[0], r.shape[0]);
      if ((s === 1 || o === 1) && c > I2) {
        i && (e = _.transpose(e, [0, 2, 1])), a && (r = _.transpose(r, [0, 2, 1]));
        var u = o === 1 ? e : e.as3D(l, c, 1), h = o === 1 ? 2 : 1, d = o === 1 ? r.as3D(l, 1, c) : r, p = _.mul(u, d);
        return p.sum(h, true);
      }
      var f = _.upcastType(e.dtype, r.dtype), m = new op(e.shape, r.shape, [l, s, o], i, a);
      return this.compileAndRun(m, [e, r], f);
    }, t.prototype.fusedBatchMatMul = function(e) {
      var r = e.a, i = e.b, a = e.transposeA, s = e.transposeB, o = e.bias, c = e.activation, l = e.preluActivationWeights, u = a ? r.shape[2] : r.shape[1], h = s ? i.shape[1] : i.shape[2], d = Math.max(r.shape[0], i.shape[0]), p = _.upcastType(r.dtype, i.dtype), f = o != null, m = l != null, g = c ? rc(c, true) : null, y = new op(r.shape, i.shape, [d, u, h], a, s, f, g, m), w = [r, i];
      return o && w.push(o), l && w.push(l), this.compileAndRun(y, w, p);
    }, t.prototype.localResponseNormalization4D = function(e, r, i, a, s) {
      var o = _.env().getBool("WEBGL_PACK_NORMALIZATION") ? new XB(e.shape, r, i, a, s) : new jB(e.shape, r, i, a, s);
      return this.compileAndRun(o, [e]);
    }, t.prototype.LRNGrad = function(e, r, i, a, s, o, c) {
      var l = new $B(r.shape, a, s, o, c);
      return this.compileAndRun(l, [r, i, e]);
    }, t.prototype.tile = function(e, r) {
      if (e.dtype === "string") {
        var i = this.readSync(e.dataId), a = i.map(function(c) {
          return _.util.decodeString(c);
        }), s = _.buffer(e.shape, e.dtype, a);
        return iP(s, r);
      }
      var o = new Nz(e.shape, r);
      return this.compileAndRun(o, [e]);
    }, t.prototype.pad = function(e, r, i) {
      var a = _.env().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new oz(e.shape, r, i) : new sz(e.shape, r, i);
      return this.compileAndRun(a, [e]);
    }, t.prototype.gather = function(e, r, i) {
      var a = this, s = this.tryRunOnCpuOrThrow([e, r], function() {
        return a.cpuBackend.gather(e, r, i);
      });
      if (s)
        return s;
      var o = new PB(e.shape, r.size, i);
      return this.compileAndRun(o, [e, r]);
    }, t.prototype.batchToSpaceND = function(e, r, i) {
      _.util.assert(e.rank <= 4, function() {
        return "batchToSpaceND for rank > 4 with a WebGL backend not implemented yet";
      });
      var a = r.reduce(function(h, d) {
        return h * d;
      }), s = _.backend_util.getReshaped(e.shape, r, a), o = _.backend_util.getPermuted(s.length, r.length), c = _.backend_util.getReshapedPermuted(e.shape, r, a), l = _.backend_util.getSliceBeginCoords(i, r.length), u = _.backend_util.getSliceSize(c, i, r.length);
      return _.transpose(e.reshape(s), o).reshape(c).slice(l, u);
    }, t.prototype.spaceToBatchND = function(e, r, i) {
      _.util.assert(e.rank <= 4, function() {
        return "spaceToBatchND for rank > 4 with a WebGL backend not implemented yet";
      });
      var a = r.reduce(function(p, f) {
        return p * f;
      }), s = [[0, 0]];
      s.push.apply(s, i);
      for (var o = 1 + r.length; o < e.shape.length; ++o)
        s.push([0, 0]);
      var c = e.pad(s), l = _.backend_util.getReshaped(c.shape, r, a, false), u = _.backend_util.getPermuted(l.length, r.length, false), h = _.backend_util.getReshapedPermuted(c.shape, r, a, false), d = _.transpose(c.reshape(l), u);
      return _.reshape(d, h);
    }, t.prototype.reduce = function(e, r, i) {
      var a = e.shape[0], s = e.shape[1], o = _.backend_util.computeOptimalWindowSize(s), c = Math.ceil(s / o), l = {windowSize: o, inSize: s, batchSize: a, outSize: c}, u = new a2(l, r), h = this.compileAndRun(u, [e], i);
      return h.shape[1] === 1 ? h : this.reduce(h, r, i);
    }, t.prototype.argReduce = function(e, r, i) {
      i === void 0 && (i = null);
      var a = e.shape[0], s = e.shape[1];
      i != null && (a = i.shape[0], s = i.shape[1]);
      var o = _.backend_util.computeOptimalWindowSize(s), c = {windowSize: o, inSize: s, batchSize: a, outSize: Math.ceil(s / o)}, l = new sU(c, r, i == null), u = [e];
      i != null && u.push(i);
      var h = this.compileAndRun(l, u, "int32");
      return h.shape[1] === 1 ? h : this.argReduce(e, r, h);
    }, t.prototype.argReducePacked = function(e, r, i) {
      i === void 0 && (i = null);
      var a = i != null ? i.shape : e.shape, s = a[a.length - 1], o = _.backend_util.computeOptimalWindowSize(s), c = new GU(a, o, r, i == null), l = i == null ? [e] : [e, i], u = this.compileAndRun(c, l, "int32");
      return u.rank === e.rank ? this.argReducePacked(e, r, u) : u;
    }, t.prototype.sum = function(e, r) {
      _.backend_util.assertAxesAreInnerMostDims("sum", r, e.rank);
      var i = _.backend_util.computeOutAndReduceShapes(e.shape, r), a = i[0], s = i[1], o = _.util.sizeFromShape(s), c = e.as2D(-1, o), l = _.sumOutType(e.dtype);
      return this.reduce(c, "sum", l).reshape(a);
    }, t.prototype.prod = function(e, r) {
      var i = this, a = this.tryRunOnCpuOrThrow([e], function() {
        return i.cpuBackend.prod(e, r);
      });
      if (a)
        return a;
      var s = _.backend_util.computeOutAndReduceShapes(e.shape, r), o = s[0], c = s[1], l = _.util.sizeFromShape(c), u = e.as2D(-1, l), h = _.sumOutType(e.dtype);
      return this.reduce(u, "prod", h).reshape(o);
    }, t.prototype.unsortedSegmentSum = function(e, r, i) {
      var a = 0, s = _.backend_util.getAxesPermutation([a], e.rank), o = e;
      s != null && (o = _.transpose(e, s), a = _.backend_util.getInnerMostAxes(1, e.rank)[0]);
      var c = S2.computeOutShape(o.shape, a, i), l = _.util.sizeFromShape([o.shape[a]]), u = o.as2D(-1, l), h = _.sumOutType(e.dtype), d = this.segOpCompute(u, "unsortedSegmentSum", r, h, i).reshape(c);
      return s != null && (d = _.transpose(d, _.backend_util.getUndoAxesPermutation(s))), d;
    }, t.prototype.segOpCompute = function(e, r, i, a, s) {
      var o = e.shape[0], c = e.shape[1], l = S2.segOpComputeOptimalWindowSize(c, s), u = {windowSize: l, inSize: c, batchSize: o, numSegments: s}, h = new gz(u, r), d = this.compileAndRun(h, [e, i], a);
      return d.shape[1] === s ? d : (i = _.range(0, s).tile([c / l]), this.segOpCompute(d, r, i, a, s));
    }, t.prototype.argMinMaxReduce = function(e, r, i) {
      var a = [r];
      if (_.backend_util.assertAxesAreInnerMostDims("arg" + i.charAt(0).toUpperCase() + i.slice(1), a, e.rank), !_.env().getBool("WEBGL_PACK_REDUCE") || e.rank <= 2) {
        var s = _.backend_util.computeOutAndReduceShapes(e.shape, a), o = s[0], c = s[1], l = _.util.sizeFromShape(c), u = e.as2D(-1, l);
        return this.argReduce(u, i).reshape(o);
      }
      return this.argReducePacked(e, i);
    }, t.prototype.argMin = function(e, r) {
      return this.argMinMaxReduce(e, r, "min");
    }, t.prototype.argMax = function(e, r) {
      return this.argMinMaxReduce(e, r, "max");
    }, t.prototype.cumsum = function(e, r, i, a) {
      if (r !== e.rank - 1)
        throw new Error("WebGL cumsum shader expects an inner-most axis=" + (e.rank - 1) + " " + ("but got axis=" + r));
      for (var s = e.shape[r], o = e, c = 0; c <= Math.ceil(Math.log2(s)) - 1; c++) {
        var l = new Pb(e.shape, false, a), u = l.getCustomSetupFunc(c), h = o;
        o = this.compileAndRun(l, [o], o.dtype, u), h.dispose();
      }
      if (i) {
        var l = new Pb(e.shape, i, a), h = o;
        o = this.compileAndRun(l, [o]), h.dispose();
      }
      return o;
    }, t.prototype.equal = function(e, r) {
      if (_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"))
        return this.packedBinaryOp(e, r, lB, "bool");
      var i = new Wt($U, e.shape, r.shape);
      return this.compileAndRun(i, [e, r], "bool");
    }, t.prototype.less = function(e, r) {
      var i = this, a = this.tryRunOnCpuOrThrow([e, r], function() {
        return i.cpuBackend.less(e, r);
      });
      if (a)
        return a;
      if (_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"))
        return this.packedBinaryOp(e, r, uB, "bool");
      var s = new Wt(XU, e.shape, r.shape);
      return this.compileAndRun(s, [e, r], "bool");
    }, t.prototype.lessEqual = function(e, r) {
      if (_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"))
        return this.packedBinaryOp(e, r, hB, "bool");
      var i = new Wt(JU, e.shape, r.shape);
      return this.compileAndRun(i, [e, r], "bool");
    }, t.prototype.greater = function(e, r) {
      var i = this, a = this.tryRunOnCpuOrThrow([e, r], function() {
        return i.cpuBackend.greater(e, r);
      });
      if (a)
        return a;
      if (_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"))
        return this.packedBinaryOp(e, r, dB, "bool");
      var s = new Wt(ZU, e.shape, r.shape);
      return this.compileAndRun(s, [e, r], "bool");
    }, t.prototype.greaterEqual = function(e, r) {
      if (_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"))
        return this.packedBinaryOp(e, r, pB, "bool");
      var i = new Wt(QU, e.shape, r.shape);
      return this.compileAndRun(i, [e, r], "bool");
    }, t.prototype.logicalNot = function(e) {
      var r = new De(e.shape, Qz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.logicalAnd = function(e, r) {
      if (_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"))
        return this.packedBinaryOp(e, r, fB, "bool");
      var i = new Wt(eB, e.shape, r.shape);
      return this.compileAndRun(i, [e, r], "bool");
    }, t.prototype.logicalOr = function(e, r) {
      if (_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"))
        return this.packedBinaryOp(e, r, mB, "bool");
      var i = new Wt(tB, e.shape, r.shape);
      return this.compileAndRun(i, [e, r], "bool");
    }, t.prototype.select = function(e, r, i) {
      var a = new yz(e.rank, r.shape, r.rank);
      return this.compileAndRun(a, [e, r, i], _.upcastType(r.dtype, i.dtype));
    }, t.prototype.where = function(e) {
      _.backend_util.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");
      var r = e.dataSync();
      return sP(e.shape, r);
    }, t.prototype.topk = function(e, r, i) {
      var a = e.dataSync();
      return aP(a, e.shape, e.dtype, r, i);
    }, t.prototype.min = function(e, r) {
      _.backend_util.assertAxesAreInnerMostDims("min", r, e.rank);
      var i = _.backend_util.computeOutAndReduceShapes(e.shape, r), a = i[0], s = i[1], o = _.util.sizeFromShape(s), c = e.as2D(-1, o);
      return this.reduce(c, "min", c.dtype).reshape(a);
    }, t.prototype.minimum = function(e, r) {
      var i = this, a = this.tryRunOnCpuOrThrow([e, r], function() {
        return i.cpuBackend.minimum(e, r);
      });
      if (a)
        return a;
      var s = _.env().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new nr(yB, e.shape, r.shape) : new Wt(rB, e.shape, r.shape);
      return this.compileAndRun(s, [e, r]);
    }, t.prototype.mod = function(e, r) {
      var i = _.env().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new nr(vB, e.shape, r.shape) : new Wt(iB, e.shape, r.shape);
      return this.compileAndRun(i, [e, r]);
    }, t.prototype.maximum = function(e, r) {
      var i = this, a = this.tryRunOnCpuOrThrow([e, r], function() {
        return i.cpuBackend.maximum(e, r);
      });
      if (a)
        return a;
      var s = _.env().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new nr(gB, e.shape, r.shape) : new Wt(nB, e.shape, r.shape);
      return this.compileAndRun(s, [e, r]);
    }, t.prototype.all = function(e, r) {
      _.backend_util.assertAxesAreInnerMostDims("all", r, e.rank);
      var i = _.backend_util.computeOutAndReduceShapes(e.shape, r), a = i[0], s = i[1], o = _.util.sizeFromShape(s), c = e.as2D(-1, o);
      return this.reduce(c, "all", c.dtype).reshape(a);
    }, t.prototype.any = function(e, r) {
      _.backend_util.assertAxesAreInnerMostDims("any", r, e.rank);
      var i = _.backend_util.computeOutAndReduceShapes(e.shape, r), a = i[0], s = i[1], o = _.util.sizeFromShape(s), c = e.as2D(-1, o);
      return this.reduce(c, "any", c.dtype).reshape(a);
    }, t.prototype.floorDiv = function(e, r) {
      var i = KU, a = "int32";
      if (_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"))
        return this.packedBinaryOp(e, r, sB, a);
      var s = new Wt(i, e.shape, r.shape);
      return this.compileAndRun(s, [e, r], a);
    }, t.prototype.packedUnaryOp = function(e, r, i) {
      var a = new hs(e.shape, r);
      return this.compileAndRun(a, [e], i);
    }, t.prototype.packedBinaryOp = function(e, r, i, a, s) {
      s === void 0 && (s = false);
      var o = new nr(i, e.shape, r.shape, s);
      return this.compileAndRun(o, [e, r], a);
    }, t.prototype.makeComplexComponentTensorInfo = function(e, r) {
      return {dataId: r.dataId, dtype: r.dtype, shape: e.shape};
    }, t.prototype.addN = function(e) {
      if (e.length === 1)
        return e[0];
      if (e.length > _.env().get("WEBGL_MAX_TEXTURES_IN_SHADER")) {
        var r = Math.floor(e.length / 2), i = this.addN(e.slice(0, r)), a = this.addN(e.slice(r));
        return this.addN([i, a]);
      }
      var s = e.map(function(u) {
        return u.dtype;
      }).reduce(function(u, h) {
        return _.upcastType(u, h);
      }), o = e.map(function(u) {
        return u.shape;
      }), c = _.env().getBool("WEBGL_PACK"), l = c ? new aU(e[0].shape, o) : new iU(e[0].shape, o);
      return this.compileAndRun(l, e, s);
    }, t.prototype.pow = function(e, r) {
      var i = _.env().getBool("WEBGL_PACK_BINARY_OPERATIONS"), a = i ? new nr(oB, e.shape, r.shape) : new Wt(jU, e.shape, r.shape), s = _.upcastType(e.dtype, r.dtype);
      return this.compileAndRun(a, [e, r], s);
    }, t.prototype.ceil = function(e) {
      if (this.shouldExecuteOnCPU([e])) {
        var r = KW(this.texData.get(e.dataId).values, e.dtype);
        return this.makeOutput(e.shape, e.dtype, r);
      }
      if (_.env().getBool("WEBGL_PACK_UNARY_OPERATIONS"))
        return this.packedUnaryOp(e, g2, e.dtype);
      var i = new De(e.shape, g2);
      return this.compileAndRun(i, [e]);
    }, t.prototype.floor = function(e) {
      if (this.shouldExecuteOnCPU([e])) {
        var r = XW(this.texData.get(e.dataId).values, e.dtype);
        return this.makeOutput(e.shape, e.dtype, r);
      }
      if (_.env().getBool("WEBGL_PACK_UNARY_OPERATIONS"))
        return this.packedUnaryOp(e, y2, e.dtype);
      var i = new De(e.shape, y2);
      return this.compileAndRun(i, [e]);
    }, t.prototype.sign = function(e) {
      var r = new De(e.shape, Oz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.isNaN = function(e) {
      var r = new De(e.shape, Ez);
      return this.compileAndRun(r, [e], "bool");
    }, t.prototype.isInf = function(e) {
      var r = new De(e.shape, Dz);
      return this.compileAndRun(r, [e], "bool");
    }, t.prototype.isFinite = function(e) {
      var r = new De(e.shape, kz);
      return this.compileAndRun(r, [e], "bool");
    }, t.prototype.round = function(e) {
      var r = new De(e.shape, Fz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.exp = function(e) {
      if (this.shouldExecuteOnCPU([e])) {
        var r = jW(this.texData.get(e.dataId).values, e.dtype);
        return this.makeOutput(e.shape, e.dtype, r);
      }
      if (_.env().getBool("WEBGL_PACK_UNARY_OPERATIONS"))
        return this.packedUnaryOp(e, v2, e.dtype);
      var i = new De(e.shape, v2);
      return this.compileAndRun(i, [e]);
    }, t.prototype.expm1 = function(e) {
      if (this.shouldExecuteOnCPU([e])) {
        var r = $W(this.texData.get(e.dataId).values, e.dtype);
        return this.makeOutput(e.shape, e.dtype, r);
      }
      if (_.env().getBool("WEBGL_PACK_UNARY_OPERATIONS"))
        return this.packedUnaryOp(e, w2, e.dtype);
      var i = new De(e.shape, w2);
      return this.compileAndRun(i, [e]);
    }, t.prototype.softmax = function(e, r) {
      var i = _.util.parseAxisParam([r], e.shape), a = _.max(e, i), s = _.backend_util.expandShapeToKeepDim(a.shape, i), o = _.sub(e, a.reshape(s)), c = this.exp(o), l = this.sum(c, i).reshape(s);
      return _.div(c, l);
    }, t.prototype.log = function(e) {
      if (this.shouldExecuteOnCPU([e])) {
        var r = JW(this.texData.get(e.dataId).values, e.dtype);
        return this.makeOutput(e.shape, e.dtype, r);
      }
      if (_.env().getBool("WEBGL_PACK_UNARY_OPERATIONS"))
        return this.packedUnaryOp(e, tP, e.dtype);
      var i = new De(e.shape, Wz);
      return this.compileAndRun(i, [e]);
    }, t.prototype.log1p = function(e) {
      var r = new De(e.shape, Uz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.sqrt = function(e) {
      var r = new De(e.shape, Bz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.rsqrt = function(e) {
      if (this.shouldExecuteOnCPU([e])) {
        var r = eU(this.texData.get(e.dataId).values, e.dtype);
        return this.makeOutput(e.shape, e.dtype, r);
      }
      var i = new De(e.shape, zz);
      return this.compileAndRun(i, [e]);
    }, t.prototype.reciprocal = function(e) {
      var r = new De(e.shape, Zz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.relu = function(e) {
      var r;
      return _.env().getBool("WEBGL_PACK") ? r = new hs(e.shape, b2) : r = new De(e.shape, d2), this.compileAndRun(r, [e]);
    }, t.prototype.relu6 = function(e) {
      var r;
      return _.env().getBool("WEBGL_PACK") ? r = new hs(e.shape, x2) : r = new De(e.shape, p2), this.compileAndRun(r, [e]);
    }, t.prototype.prelu = function(e, r) {
      var i = _.env().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new nr(kb, e.shape, r.shape) : new Wt(Db, e.shape, r.shape);
      return this.compileAndRun(i, [e, r]);
    }, t.prototype.elu = function(e) {
      if (_.env().getBool("WEBGL_PACK_UNARY_OPERATIONS"))
        return this.packedUnaryOp(e, L2, e.dtype);
      var r = new De(e.shape, f2);
      return this.compileAndRun(r, [e]);
    }, t.prototype.eluDer = function(e, r) {
      var i = _.env().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? new nr(cB, e.shape, r.shape) : new Wt(aB, e.shape, r.shape);
      return this.compileAndRun(i, [e, r]);
    }, t.prototype.selu = function(e) {
      var r = new De(e.shape, Cz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.clip = function(e, r, i) {
      var a;
      _.env().getBool("WEBGL_PACK_CLIP") ? a = new bB(e.shape) : a = new wB(e.shape);
      var s = a.getCustomSetupFunc(r, i);
      return this.compileAndRun(a, [e], null, s);
    }, t.prototype.abs = function(e) {
      if (this.shouldExecuteOnCPU([e]) && e.dtype !== "complex64") {
        var r = qW(this.texData.get(e.dataId).values);
        return this.makeOutput(e.shape, e.dtype, r);
      }
      if (_.env().getBool("WEBGL_PACK_UNARY_OPERATIONS"))
        return this.packedUnaryOp(e, h2, e.dtype);
      var i = new De(e.shape, h2);
      return this.compileAndRun(i, [e]);
    }, t.prototype.complexAbs = function(e) {
      var r = this.texData.get(e.dataId), i = new xB(e.shape), a = [this.makeComplexComponentTensorInfo(e, r.complexTensorInfos.real), this.makeComplexComponentTensorInfo(e, r.complexTensorInfos.imag)];
      return this.compileAndRun(i, a);
    }, t.prototype.sigmoid = function(e) {
      var r = new De(e.shape, Pz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.softplus = function(e) {
      var r = new De(e.shape, Mz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.asin = function(e) {
      var r = new De(e.shape, Hz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.acos = function(e) {
      var r = new De(e.shape, Vz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.atan = function(e) {
      var r = new De(e.shape, Gz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.sinh = function(e) {
      var r = new De(e.shape, qz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.cosh = function(e) {
      var r = new De(e.shape, Yz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.tanh = function(e) {
      var r = new De(e.shape, Kz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.asinh = function(e) {
      var r = new De(e.shape, jz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.acosh = function(e) {
      var r = new De(e.shape, $z);
      return this.compileAndRun(r, [e]);
    }, t.prototype.atanh = function(e) {
      var r = new De(e.shape, Xz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.erf = function(e) {
      var r = new De(e.shape, Jz);
      return this.compileAndRun(r, [e]);
    }, t.prototype.step = function(e, r) {
      var i = new De(e.shape, Rz(r));
      return this.compileAndRun(i, [e]);
    }, t.prototype.conv2dByMatMul = function(e, r, i, a, s, o) {
      var c = e.shape, l = this.texData.get(e.dataId), u = i.inChannels, h = c[0] * c[1] * c[2], d = i.outChannels, p = i.dataFormat === "channelsLast", f = false, m = false, g = (h === 1 || d === 1) && u > I2, y = c[2] % 2 !== 0 && !!l.isPacked;
      if (g || !_.env().getBool("WEBGL_LAZILY_UNPACK") || !_.env().getBool("WEBGL_PACK_BINARY_OPERATIONS") || !y) {
        var w = p ? c[0] * c[1] * c[2] : c[0] * c[2] * c[3], b = _.reshape(e, [1, w, i.inChannels]), L = _.reshape(r, [1, i.inChannels, i.outChannels]), x = this.fusedBatchMatMul({a: b, b: L, transposeA: f, transposeB: m, bias: a, activation: s, preluActivationWeights: o});
        return _.reshape(x, i.outShape);
      }
      var N = p ? c[0] * c[1] * (c[2] + 1) : c[0] * c[2] * (c[3] + 1), I = {dataId: e.dataId, shape: [1, N, i.inChannels], dtype: e.dtype}, C = l.shape;
      l.shape = l.shape.slice(), l.shape[l.shape.length - 2]++, _.util.assert(cs(l.shape, I.shape), function() {
        return "packed reshape " + l.shape + " to " + I.shape + " isn't free";
      });
      var O = _.reshape(r, [1, i.inChannels, i.outChannels]), D = this.fusedBatchMatMul({a: I, b: O, transposeA: f, transposeB: m, bias: a, activation: s, preluActivationWeights: o}), F = this.texData.get(D.dataId);
      return _.util.assert(F.isPacked, function() {
        return "batchMatMul result is expected to be packed";
      }), l.shape = C, F.shape = i.outShape, _.engine().makeTensorFromDataId(D.dataId, i.outShape, D.dtype);
    }, t.prototype.conv2dWithIm2Row = function(e, r, i, a, s, o) {
      var c = i.filterWidth, l = i.filterHeight, u = i.inChannels, h = i.outWidth, d = i.outHeight, p = i.dataFormat, f = p === "channelsLast", m = c * l * u, g = d * h, y = [m, g], w = true, b = false, L = e.squeeze([0]), x = r.reshape([1, m, -1]), N = new KB(y, L.shape, i), I = this.compileAndRun(N, [L]).reshape([1, y[0], y[1]]), C = a != null, O = o != null, D = s ? rc(s, true) : null, F = new op(I.shape, x.shape, [1, g, i.outChannels], w, b, C, D, O), k = [I, x];
      a && k.push(a), O && k.push(o);
      var B = this.compileAndRun(F, k);
      return f ? B.reshape([1, d, h, i.outChannels]) : B.reshape([1, i.outChannels, d, h]);
    }, t.prototype.fusedConv2d = function(e) {
      var r = e.input, i = e.filter, a = e.convInfo, s = e.bias, o = e.activation, c = e.preluActivationWeights;
      if (a.filterHeight === 1 && a.filterWidth === 1 && a.dilationHeight === 1 && a.dilationWidth === 1 && a.strideHeight === 1 && a.strideWidth === 1 && (a.padInfo.type === "SAME" || a.padInfo.type === "VALID"))
        return this.conv2dByMatMul(r, i, a, s, o, c);
      if (_.env().getBool("WEBGL_CONV_IM2COL") && r.shape[0] === 1)
        return this.conv2dWithIm2Row(r, i, a, s, o, c);
      var l = s != null, u = c != null, h = o ? rc(o, false) : null, d = new Fb(a, l, h, u), p = [r, i];
      return s && p.push(s), c && p.push(c), this.compileAndRun(d, p);
    }, t.prototype.conv2d = function(e, r, i) {
      if (i.filterHeight === 1 && i.filterWidth === 1 && i.dilationHeight === 1 && i.dilationWidth === 1 && i.strideHeight === 1 && i.strideWidth === 1 && (i.padInfo.type === "SAME" || i.padInfo.type === "VALID"))
        return this.conv2dByMatMul(e, r, i);
      if (_.env().getBool("WEBGL_CONV_IM2COL") && e.shape[0] === 1)
        return this.conv2dWithIm2Row(e, r, i);
      var a = new Fb(i);
      return this.compileAndRun(a, [e, r]);
    }, t.prototype.conv2dDerInput = function(e, r, i) {
      var a = new SB(i);
      return this.compileAndRun(a, [e, r]);
    }, t.prototype.conv2dDerFilter = function(e, r, i) {
      var a = new LB(i);
      return this.compileAndRun(a, [e, r]);
    }, t.prototype.fusedDepthwiseConv2D = function(e) {
      var r = e.input, i = e.filter, a = e.convInfo, s = e.bias, o = e.activation, c = e.preluActivationWeights, l = _.env().getBool("WEBGL_PACK_DEPTHWISECONV") && a.strideWidth <= 2 && a.outChannels / a.inChannels === 1, u = o ? rc(o, l) : null, h = [r, i], d = s != null, p = c != null;
      d && h.push(s), p && h.push(c);
      var f;
      return l ? (f = new Ub(a, d, u, p), this.compileAndRun(f, h)) : (f = new Wb(a, d, u, p), this.compileAndRun(f, h));
    }, t.prototype.depthwiseConv2D = function(e, r, i) {
      var a;
      return _.env().getBool("WEBGL_PACK_DEPTHWISECONV") && i.strideWidth <= 2 && i.outChannels / i.inChannels === 1 ? (a = new Ub(i), this.compileAndRun(a, [e, r])) : (a = new Wb(i), this.compileAndRun(a, [e, r]));
    }, t.prototype.depthwiseConv2DDerInput = function(e, r, i) {
      var a = new NB(i);
      return this.compileAndRun(a, [e, r]);
    }, t.prototype.depthwiseConv2DDerFilter = function(e, r, i) {
      var a = new TB(i);
      return this.compileAndRun(a, [e, r]);
    }, t.prototype.conv3d = function(e, r, i) {
      var a = new _B(i);
      return this.compileAndRun(a, [e, r]);
    }, t.prototype.conv3dDerInput = function(e, r, i) {
      var a = new AB(i);
      return this.compileAndRun(a, [e, r]);
    }, t.prototype.conv3dDerFilter = function(e, r, i) {
      var a = new IB(i);
      return this.compileAndRun(a, [e, r]);
    }, t.prototype.unstack = function(e, r) {
      for (var i = e.shape[r], a = new Array(e.rank - 1), s = 0, o = 0; o < e.rank; o++)
        o !== r && (a[s++] = e.shape[o]);
      var c = new Array(e.rank).fill(0), l = e.shape.slice();
      l[r] = 1;
      for (var u = new Array(i), o = 0; o < u.length; o++)
        c[r] = o, u[o] = this.slice(e, c, l).reshape(a);
      return u;
    }, t.prototype.avgPool3d = function(e, r) {
      var i = new cp(r, "avg", false);
      return this.compileAndRun(i, [e], "float32");
    }, t.prototype.avgPool3dBackprop = function(e, r, i) {
      var a = new YU(i);
      return this.compileAndRun(a, [e], r.dtype);
    }, t.prototype.maxPool3d = function(e, r) {
      var i = new cp(r, "max", false);
      return this.compileAndRun(i, [e], "float32");
    }, t.prototype.maxPool3dBackprop = function(e, r, i, a) {
      var s = true, o = new cp(a, "max", s), c = this.compileAndRun(o, [r]), l = new ZB(a), u = this.compileAndRun(l, [e, c], r.dtype);
      return c.dispose(), u;
    }, t.prototype.resizeBilinear = function(e, r, i, a) {
      var s = _.env().getBool("WEBGL_PACK_IMAGE_OPERATIONS") ? new hz(e.shape, r, i, a) : new uz(e.shape, r, i, a);
      return this.compileAndRun(s, [e], "float32");
    }, t.prototype.resizeBilinearBackprop = function(e, r, i) {
      var a = new lz(e, r, i);
      return this.compileAndRun(a, [e]);
    }, t.prototype.resizeNearestNeighbor = function(e, r, i, a) {
      var s = new pz(e.shape, r, i, a);
      return this.compileAndRun(s, [e]);
    }, t.prototype.resizeNearestNeighborBackprop = function(e, r, i) {
      var a = new dz(e, r, i);
      return this.compileAndRun(a, [e]);
    }, t.prototype.multinomial = function(e, r, i, a) {
      var s = r ? e : _.softmax(e), o = s.shape[0], c = s.shape[1], l = new QB(o, c, i), u = l.getCustomSetupFunc(a);
      return this.compileAndRun(l, [s], "int32", u);
    }, t.prototype.oneHot = function(e, r, i, a) {
      var s = new ez(e.size, r, i, a);
      return this.compileAndRun(s, [e]);
    }, t.prototype.diag = function(e) {
      var r = new DB(e.size);
      return this.compileAndRun(r, [e]);
    }, t.prototype.cropAndResize = function(e, r, i, a, s, o) {
      var c = new CB(e.shape, r.shape, a, s, o);
      return this.compileAndRun(c, [e, r, i], "float32");
    }, t.prototype.depthToSpace = function(e, r, i) {
      _.util.assert(r > 1, function() {
        return "blockSize should be > 1 for depthToSpace, but was: " + r;
      });
      var a = e.shape[0], s = i === "NHWC" ? e.shape[1] : e.shape[2], o = i === "NHWC" ? e.shape[2] : e.shape[3], c = i === "NHWC" ? e.shape[3] : e.shape[1], l = s * r, u = o * r, h = c / (r * r), d = i === "NHWC" ? [a, l, u, h] : [a, h, l, u], p = new EB(d, r, i);
      return this.compileAndRun(p, [e]);
    }, t.prototype.split = function(e, r, i) {
      return rP(e, r, i);
    }, t.prototype.scatterND = function(e, r, i) {
      var a = _.backend_util.calculateShapes(r, e, i), s = a.sliceRank, o = a.numUpdates, c = a.sliceSize, l = a.strides, u = a.outputSize, h = [u / c, c], d = e.reshape([o, s]), p = r.reshape([o, c]);
      if (u === 0)
        return _.backend_util.reshapeTensor(_.tensor([]), i);
      var f = _.scalar(0), m = new o2(o, s, d.rank, p.rank, l, h), g = this.compileAndRun(m, [p, d, f]);
      return g.reshape(i);
    }, t.prototype.sparseToDense = function(e, r, i, a) {
      var s = _.backend_util.calculateShapes(r, e, i), o = s.sliceRank, c = s.numUpdates, l = s.strides, u = s.outputSize, h = false, d = new o2(c, o, e.rank, r.rank, l, [u, 1], h), p = this.compileAndRun(d, [r, e, a]);
      return p.reshape(i);
    }, t.prototype.gatherND = function(e, r) {
      var i = r.shape, a = i[i.length - 1], s = _.backend_util.prepareAndValidate(e, r), o = s[0], c = s[1], l = s[2], u = s[3], h = r.reshape([c, a]), d = e.reshape([e.size / l, l]), p = new MB(a, u, [c, l]), f = this.compileAndRun(p, [d, h]);
      return f.reshape(o);
    }, t.prototype.fill = function(e, r, i) {
      if (i = i || _.util.inferDtype(r), i === "string") {
        var a = _.util.getArrayFromDType(i, _.util.sizeFromShape(e));
        return a.fill(r), _.engine().makeTensor(a, e, i, this);
      } else {
        var s = new BB(e, r), o = s.getCustomSetupFunc(r);
        return this.compileAndRun(s, [], i, o);
      }
    }, t.prototype.onesLike = function(e) {
      if (e.dtype === "string")
        throw new Error("onesLike is not supported under string dtype");
      return this.fill(e.shape, 1, e.dtype);
    }, t.prototype.zerosLike = function(e) {
      return this.fill(e.shape, e.dtype === "string" ? "" : 0, e.dtype);
    }, t.prototype.linspace = function(e, r, i) {
      return _.backend_util.linspaceImpl(e, r, i);
    }, t.prototype.makeTensorInfo = function(e, r, i) {
      var a = this.write(i, e, r);
      return this.texData.get(a).usage = null, {dataId: a, shape: e, dtype: r};
    }, t.prototype.makeOutput = function(e, r, i) {
      var a = this.makeTensorInfo(e, r, i).dataId;
      return _.engine().makeTensorFromDataId(a, e, r, this);
    }, t.prototype.unpackTensor = function(e) {
      var r = new nP(e.shape);
      return this.runWebGLProgram(r, [e], e.dtype);
    }, t.prototype.packTensor = function(e) {
      var r = new iz(e.shape), i = true;
      return this.runWebGLProgram(r, [e], e.dtype, null, i);
    }, t.prototype.packedReshape = function(e, r) {
      var i = [pi(e.shape)].concat(fi(e.shape)), a = {dtype: e.dtype, shape: i, dataId: e.dataId}, s = [pi(r)].concat(fi(r)), o = new s2(s, i), c = true, l = this.runWebGLProgram(o, [a], e.dtype, null, c);
      return {dataId: l.dataId, shape: r, dtype: l.dtype};
    }, t.prototype.decode = function(e) {
      var r = this.texData.get(e), i = r.isPacked, a = r.shape, s = r.dtype, o = Xo(a), c;
      i ? c = new OB(o) : c = new RB(o);
      var l = true, u = this.runWebGLProgram(c, [{shape: o, dtype: s, dataId: e}], s, null, l);
      return {dtype: s, shape: a, dataId: u.dataId};
    }, t.prototype.runWebGLProgram = function(e, r, i, a, s) {
      var o = this;
      s === void 0 && (s = false);
      var c = this.makeTensorInfo(e.outputShape, i), l = this.texData.get(c.dataId);
      if (e.packedOutput && (l.isPacked = true), e.outPackingScheme === rs.DENSE) {
        var u = as(e.outputShape);
        l.texShape = u.map(function(b) {
          return b * 2;
        });
      }
      if (e.outTexUsage != null && (l.usage = e.outTexUsage), _.util.sizeFromShape(c.shape) === 0)
        return l.values = _.util.getTypedArrayFromDType(c.dtype, 0), c;
      var h = [], d = r.map(function(b) {
        if (b.dtype === "complex64")
          throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");
        var L = o.texData.get(b.dataId);
        if (L.texture == null) {
          if (!e.packedInputs && _.util.sizeFromShape(b.shape) <= _.env().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))
            return {shape: b.shape, texData: null, isUniform: true, uniformValues: L.values};
          e.packedInputs && (L.isPacked = true, L.shape = b.shape);
        } else if (!!L.isPacked !== !!e.packedInputs)
          b = L.isPacked ? o.unpackTensor(b) : o.packTensor(b), h.push(b), L = o.texData.get(b.dataId);
        else if (L.isPacked && !cs(L.shape, b.shape)) {
          var x = b, N = b.shape;
          b.shape = L.shape, b = o.packedReshape(b, N), h.push(b), L = o.texData.get(b.dataId), x.shape = N;
        }
        return o.uploadToGPU(b.dataId), {shape: b.shape, texData: L, isUniform: false};
      });
      this.uploadToGPU(c.dataId);
      var p = {shape: c.shape, texData: l, isUniform: false}, f = YB(e, d, p), m = this.getAndSaveBinary(f, function() {
        return GB(o.gpgpu, e, d, p);
      }), g = this.activeTimers != null, y;
      if (g && (y = this.startTimer()), qB(this.gpgpu, m, d, p, a), h.forEach(function(b) {
        return o.disposeIntermediateTensorInfo(b);
      }), g && (y = this.endTimer(y), this.activeTimers.push({name: e.constructor.name, query: this.getQueryTime(y)})), !_.env().getBool("WEBGL_LAZILY_UNPACK") && l.isPacked && s === false) {
        var w = this.unpackTensor(c);
        return this.disposeIntermediateTensorInfo(c), w;
      }
      return c;
    }, t.prototype.compileAndRun = function(e, r, i, a, s) {
      s === void 0 && (s = false), i = i || r[0].dtype;
      var o = this.runWebGLProgram(e, r, i, a, s);
      return _.engine().makeTensorFromDataId(o.dataId, o.shape, o.dtype);
    }, t.prototype.getAndSaveBinary = function(e, r) {
      return e in this.binaryCache || (this.binaryCache[e] = r()), this.binaryCache[e];
    }, t.prototype.getTextureManager = function() {
      return this.textureManager;
    }, t.prototype.dispose = function() {
      var e = this;
      if (this.disposed)
        return;
      if (!_.env().getBool("IS_TEST")) {
        var r = Object.keys(this.binaryCache);
        r.forEach(function(i) {
          e.gpgpu.deleteProgram(e.binaryCache[i].webGLProgram), delete e.binaryCache[i];
        });
      }
      this.textureManager.dispose(), this.canvas != null && typeof HTMLCanvasElement != "undefined" && this.canvas instanceof HTMLCanvasElement ? this.canvas.remove() : this.canvas = null, this.gpgpuCreatedLocally && (this.gpgpu.program = null, this.gpgpu.dispose()), this.disposed = true;
    }, t.prototype.floatPrecision = function() {
      var e = this;
      return this.floatPrecisionValue == null && (this.floatPrecisionValue = _.tidy(function() {
        if (!_.env().get("WEBGL_RENDER_FLOAT32_ENABLED")) {
          var r = _.env().getBool("DEBUG");
          _.env().set("DEBUG", false);
          var i = e.abs(_.scalar(1e-8)).dataSync()[0];
          if (_.env().set("DEBUG", r), i > 0)
            return 32;
        }
        return 16;
      })), this.floatPrecisionValue;
    }, t.prototype.epsilon = function() {
      return this.floatPrecision() === 32 ? oP : cP;
    }, t.prototype.uploadToGPU = function(e) {
      var r, i = this.texData.get(e), a = i.shape, s = i.dtype, o = i.values, c = i.texture, l = i.usage, u = i.isPacked;
      if (c != null)
        return;
      var h = this.activeTimers != null, d;
      h && (d = _.util.now());
      var p = i.texShape;
      if (p == null && (p = bb(a, u), i.texShape = p), o != null) {
        var f = Xo(a), m = void 0, g = p[1], y = p[0], w = o instanceof Uint8Array;
        u ? (r = ea(p[0], p[1]), g = r[0], y = r[1], m = new UB(f, [y, g], w)) : m = new WB(f, [y, g], w);
        var b = this.makeTensorInfo([y, g], s);
        w ? this.texData.get(b.dataId).usage = cn.PIXELS : this.texData.get(b.dataId).usage = cn.UPLOAD, this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId), g, y, o);
        var L = true, x = this.runWebGLProgram(m, [b], s, null, L), N = this.texData.get(x.dataId);
        i.texture = N.texture, i.texShape = N.texShape, i.isPacked = N.isPacked, i.usage = N.usage, this.disposeIntermediateTensorInfo(b), this.texData.delete(x.dataId), i.values = null, h && (this.uploadWaitMs += _.util.now() - d);
      } else {
        var I = this.acquireTexture(p, l, s, u);
        i.texture = I;
      }
    }, t.prototype.convertAndCacheOnCPU = function(e, r) {
      var i = this.texData.get(e), a = i.dtype;
      return this.releaseGPUData(e), r != null && (i.values = pP(r, a)), i.values;
    }, t.prototype.acquireTexture = function(e, r, i, a) {
      if (this.numBytesInGPU += this.computeBytes(e, i), !this.warnedAboutMemory && this.numBytesInGPU > this.numMBBeforeWarning * 1024 * 1024) {
        var s = (this.numBytesInGPU / 1024 / 1024).toFixed(2);
        this.warnedAboutMemory = true, console.warn("High memory usage in GPU: " + s + " MB, most likely due to a memory leak");
      }
      return this.textureManager.acquireTexture(e, r, a);
    }, t.prototype.computeBytes = function(e, r) {
      return e[0] * e[1] * _.util.bytesPerElement(r);
    }, t.prototype.tryRunOnCpuOrThrow = function(e, r) {
      if (this.shouldExecuteOnCPU(e))
        try {
          return r();
        } catch (i) {
          if (_.env().getBool("IS_TEST"))
            throw new Error("CPU forwarding failed");
        }
      return null;
    }, t;
  }(_.KernelBackend);
  function pP(n, t) {
    if (t === "float32" || t === "complex64")
      return n;
    if (t === "int32" || t === "bool") {
      for (var e = t === "int32" ? new Int32Array(n.length) : new Uint8Array(n.length), r = 0; r < e.length; ++r)
        e[r] = Math.round(n[r]);
      return e;
    } else
      throw new Error("Unknown dtype " + t);
  }
  var fP = "2.7.0";
  function T2() {
    _.env().set("WEBGL_FORCE_F16_TEXTURES", true);
  }
  _.device_util.isBrowser() && _.registerBackend("webgl", function() {
    return new A2();
  }, 2);
  var mP = {forceHalfFloat: T2};
  function ir(n) {
    var t = n.inputs, e = n.backend, r = t.x;
    return e.incRef(r.dataId), {dataId: r.dataId, shape: r.shape, dtype: r.dtype};
  }
  var gP = {kernelName: _.Identity, backendName: "webgl", kernelFunc: ir};
  function oa(n) {
    var t = n.inputs, e = n.backend, r = t.real, i = t.imag, a = e.makeTensorInfo(r.shape, "complex64"), s = e.texData.get(a.dataId), o = ir({inputs: {x: r}, backend: e}), c = e.texData.get(o.dataId);
    c.complexParentRefCount++;
    var l = ir({inputs: {x: i}, backend: e}), u = e.texData.get(l.dataId);
    return u.complexParentRefCount++, s.complexTensorInfos = {real: o, imag: l}, a;
  }
  var yP = {kernelName: _.Complex, backendName: "webgl", kernelFunc: oa};
  var N2 = "if (isnan(x)) return x;", vP = `
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`, wP = `
  result.r = isNaN.r > 0. ? NAN : result.r;
  result.g = isNaN.g > 0. ? NAN : result.g;
  result.b = isNaN.b > 0. ? NAN : result.b;
  result.a = isNaN.a > 0. ? NAN : result.a;
`;
  function ic(n) {
    return function(t) {
      var e = t.inputs, r = t.backend, i = e.x, a = r, s = new De(i.shape, n);
      return a.runWebGLProgram(s, [i], i.dtype);
    };
  }
  function ca(n) {
    var t = n.opSnippet, e = n.packedOpSnippet, r = n.checkOutOfBounds, i = r === void 0 ? false : r, a = n.supportsComplex, s = a === void 0 ? false : a, o = n.cpuKernelImpl, c = n.dtype;
    return function(l) {
      var u = l.inputs, h = l.backend, d = u, p = d.a, f = d.b, m = h;
      if (s && p.dtype === "complex64") {
        var g = m.texData.get(p.dataId), y = m.texData.get(f.dataId), w = [[g.complexTensorInfos.real, y.complexTensorInfos.real], [g.complexTensorInfos.imag, y.complexTensorInfos.imag]].map(function(V) {
          var P = V[0], G = V[1], j = {dataId: P.dataId, dtype: P.dtype, shape: p.shape}, q = {dataId: G.dataId, dtype: G.dtype, shape: f.shape}, H = new Wt(t, p.shape, f.shape);
          return m.runWebGLProgram(H, [j, q], _.upcastType(P.dtype, G.dtype));
        }), b = w[0], L = w[1], x = oa({inputs: {real: b, imag: L}, backend: m});
        return m.disposeIntermediateTensorInfo(b), m.disposeIntermediateTensorInfo(L), x;
      }
      var N = c || _.upcastType(p.dtype, f.dtype);
      if (m.shouldExecuteOnCPU([p, f]) && o != null) {
        var g = m.texData.get(p.dataId), y = m.texData.get(f.dataId), I = o(p.shape, f.shape, g.values, y.values, N), C = I[0], O = I[1], D = m.makeTensorInfo(O, N), F = m.texData.get(D.dataId);
        return F.values = C, D;
      }
      var k = _.env().getBool("WEBGL_PACK_BINARY_OPERATIONS") && e != null, B;
      return k ? B = new nr(e, p.shape, f.shape, i) : B = new Wt(t, p.shape, f.shape), m.runWebGLProgram(B, [p, f], N);
    };
  }
  var _2 = "return a + b;", bP = ca({opSnippet: _2, packedOpSnippet: _2, supportsComplex: true, cpuKernelImpl: YW}), xP = {kernelName: _.Add, backendName: "webgl", kernelFunc: bP};
  var LP = vP + `
  return atan(a, b);
`, SP = `
  vec4 result = atan(a, b);
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  ` + wP + `
  return result;
`, IP = ca({opSnippet: LP, packedOpSnippet: SP}), AP = {kernelName: _.Atan2, backendName: "webgl", kernelFunc: IP};
  function TP(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x;
    ta(i, "avgPool");
    var a = r.filterSize, s = r.strides, o = r.pad, c = r.dimRoundingMode, l = 1;
    _.util.assert(_.backend_util.eitherStridesOrDilationsAreOne(s, l), function() {
      return "Error in avgPool: Either strides or dilations must be 1. " + ("Got strides " + s + " and dilations '" + l + "'");
    });
    var u = _.backend_util.computePool2DInfo(i.shape, a, s, l, o, c);
    if (u.filterWidth === 1 && u.filterHeight === 1 && _.util.arraysEqual(u.inShape, u.outShape))
      return ir({inputs: {x: i}, backend: e});
    var h = new us(u, "avg", false);
    return e.runWebGLProgram(h, [i], "float32");
  }
  var NP = {kernelName: _.AvgPool, backendName: "webgl", kernelFunc: TP};
  function _P(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.dy, a = t.input, s = a;
    ta([i, a], "avgPoolBackprop");
    var o = r.filterSize, c = r.strides, l = r.pad, u = _.backend_util.computePool2DInfo(s.shape, o, c, 1, l), h = new qU(u);
    return e.runWebGLProgram(h, [i], s.dtype);
  }
  var CP = {kernelName: _.AvgPoolBackprop, backendName: "webgl", kernelFunc: _P};
  var RP = function() {
    function n(t, e, r, i, a, s) {
      this.outputShape = [], this.variableNames = ["x", "mean", "variance"], _.backend_util.assertAndGetBroadcastShape(t, e), _.backend_util.assertAndGetBroadcastShape(t, r);
      var o = "0.0";
      i != null && (_.backend_util.assertAndGetBroadcastShape(t, i), this.variableNames.push("offset"), o = "getOffsetAtOutCoords()");
      var c = "1.0";
      a != null && (_.backend_util.assertAndGetBroadcastShape(t, a), this.variableNames.push("scale"), c = "getScaleAtOutCoords()"), this.outputShape = t, this.userCode = `
      void main() {
        float x = getXAtOutCoords();
        float mean = getMeanAtOutCoords();
        float variance = getVarianceAtOutCoords();
        float offset = ` + o + `;
        float scale = ` + c + `;
        float inv = scale * inversesqrt(variance + float(` + s + `));
        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
      }
    `;
    }
    return n;
  }();
  var OP = function() {
    function n(t, e, r, i, a, s) {
      this.packedInputs = true, this.packedOutput = true, this.variableNames = ["x", "mean", "variance"], _.backend_util.assertAndGetBroadcastShape(t, e), _.backend_util.assertAndGetBroadcastShape(t, r);
      var o = "vec4(0.0)";
      i != null && (_.backend_util.assertAndGetBroadcastShape(t, i), this.variableNames.push("offset"), o = "getOffsetAtOutCoords()");
      var c = "vec4(1.0)";
      a != null && (_.backend_util.assertAndGetBroadcastShape(t, a), this.variableNames.push("scale"), c = "getScaleAtOutCoords()"), this.outputShape = t, this.userCode = `
      void main() {
        vec4 offset = ` + o + `;
        vec4 scale = ` + c + `;

        vec4 x = getXAtOutCoords();
        vec4 mean = getMeanAtOutCoords();
        vec4 variance = getVarianceAtOutCoords();

        vec4 inv = scale * inversesqrt(variance + vec4(` + s + `));

        setOutput((x - mean) * inv + offset);
      }
    `;
    }
    return n;
  }();
  var EP = function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = t.mean, s = t.variance, o = t.offset, c = t.scale;
    _.util.assert(a.shape.length === s.shape.length, function() {
      return "Batch normalization gradient requires mean and variance to have equal ranks.";
    }), _.util.assert(o == null || a.shape.length === o.shape.length, function() {
      return "Batch normalization gradient requires mean and offset to have equal ranks.";
    }), _.util.assert(c == null || a.shape.length === c.shape.length, function() {
      return "Batch normalization gradient requires mean and scale to have equal ranks.";
    });
    var l = r.varianceEpsilon;
    l == null && (l = 1e-3);
    var u = [i, a, s], h = null;
    o != null && (h = o.shape, u.push(o));
    var d = null;
    c != null && (d = c.shape, u.push(c));
    var p = _.env().getBool("WEBGL_PACK_NORMALIZATION") ? new OP(i.shape, a.shape, s.shape, h, d, l) : new RP(i.shape, a.shape, s.shape, h, d, l), f = e.runWebGLProgram(p, u, u[0].dtype);
    return f;
  }, DP = {kernelName: _.FusedBatchNorm, backendName: "webgl", kernelFunc: EP};
  var kP = "return float(a != b);", C2 = ca({opSnippet: kP, dtype: "bool"}), FP = {kernelName: _.NotEqual, backendName: "webgl", kernelFunc: C2};
  function up(n) {
    var t = n.inputs, e = n.backend, r = t.input, i = e.texData.get(r.dataId);
    return ir({inputs: {x: i.complexTensorInfos.real}, backend: e});
  }
  var WP = {kernelName: _.Real, backendName: "webgl", kernelFunc: up};
  var UP = "return float(int(x));";
  function BP(n, t) {
    var e = new De(n.shape, UP), r = t.runWebGLProgram(e, [n], "int32");
    return {dataId: r.dataId, shape: r.shape, dtype: r.dtype};
  }
  function hp(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.dtype;
    if (a === "complex64") {
      if (i.dtype === "complex64")
        return ir({inputs: {x: i}, backend: e});
      var s = _.zeros(i.shape), o = hp({inputs: {x: i}, backend: e, attrs: {dtype: "float32"}}), c = oa({inputs: {real: o, imag: s}, backend: e});
      return s.dispose(), e.disposeIntermediateTensorInfo(o), c;
    }
    if (i.dtype === "complex64") {
      var l = up({inputs: {input: i}, backend: e}), c = hp({inputs: {x: l}, backend: e, attrs: {dtype: a}});
      return e.disposeIntermediateTensorInfo(l), c;
    }
    if (!_.util.hasEncodingLoss(i.dtype, a)) {
      var c = ir({inputs: {x: i}, backend: e});
      return {dataId: c.dataId, shape: c.shape, dtype: a};
    }
    if (a === "int32")
      return BP(i, e);
    if (a === "bool") {
      var u = e.makeTensorInfo([], "bool", _.util.getTypedArrayFromDType("bool", 1)), h = {a: i, b: u}, c = C2({inputs: h, backend: e});
      return e.disposeIntermediateTensorInfo(u), c;
    }
    throw new Error("Error in Cast: failed to cast " + i.dtype + " to " + a);
  }
  var zP = {kernelName: _.Cast, backendName: "webgl", kernelFunc: hp};
  var PP = function() {
    function n(t) {
      this.outputShape = [], this.outputShape = _.backend_util.computeOutShape(t, 1), this.variableNames = t.map(function(c, l) {
        return "T" + l;
      });
      var e = new Array(t.length - 1);
      e[0] = t[0][1];
      for (var r = 1; r < e.length; r++)
        e[r] = e[r - 1] + t[r][1];
      for (var i = ["if (yC < " + e[0] + ") setOutput(getT0(yR, yC));"], r = 1; r < e.length; r++) {
        var a = e[r - 1];
        i.push("else if (yC < " + e[r] + ") " + ("setOutput(getT" + r + "(yR, yC-" + a + "));"));
      }
      var s = e.length, o = e[e.length - 1];
      i.push("else setOutput(getT" + s + "(yR, yC-" + o + "));"), this.userCode = `
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

        ` + i.join(`
        `) + `
      }
    `;
    }
    return n;
  }();
  var MP = function() {
    function n(t, e) {
      this.packedInputs = true, this.packedOutput = true, this.outputShape = [], this.outputShape = _.backend_util.computeOutShape(t, e);
      var r = this.outputShape, i = r.length, a = Ze(i), s = Bt("coords", i), o = ["x", "y", "z", "w", "u", "v"].slice(0, i);
      this.variableNames = t.map(function(y, w) {
        return "T" + w;
      });
      var c = new Array(t.length - 1);
      c[0] = t[0][e];
      for (var l = 1; l < c.length; l++)
        c[l] = c[l - 1] + t[l][e];
      for (var u = o[e], h = o.slice(-2), d = o.join(), p = "if (" + u + " < " + c[0] + `) {
        return getChannel(
            getT0(` + d + "), vec2(" + h.join() + `));
        }`, l = 1; l < c.length; l++) {
        var f = c[l - 1];
        p += `
        if (` + u + " < " + c[l] + "  && " + u + " >= " + c[l - 1] + `) {
          return getChannel(
            getT` + l + "(" + ac(o, u, f) + `),
            vec2(` + ac(h, u, f) + `));
        }`;
      }
      var m = c.length, g = c[c.length - 1];
      p += `
        return getChannel(
          getT` + m + "(" + ac(o, u, g) + `),
          vec2(` + ac(h, u, g) + "));", this.userCode = `
      float getValue(` + o.map(function(y) {
        return "int " + y;
      }) + `) {
        ` + p + `
      }

      void main() {
        ` + a + ` coords = getOutputCoords();
        vec4 result = vec4(getValue(` + s + `), 0., 0., 0.);

        ` + s[i - 1] + " = " + s[i - 1] + ` + 1;
        if (` + s[i - 1] + " < " + r[i - 1] + `) {
          result.g = getValue(` + s + `);
        }

        ` + s[i - 2] + " = " + s[i - 2] + ` + 1;
        if (` + s[i - 2] + " < " + r[i - 2] + `) {
          result.a = getValue(` + s + `);
        }

        ` + s[i - 1] + " = " + s[i - 1] + ` - 1;
        if (` + s[i - 2] + " < " + r[i - 2] + ` &&
            ` + s[i - 1] + " < " + r[i - 1] + `) {
          result.b = getValue(` + s + `);
        }
        setOutput(result);
      }
    `;
    }
    return n;
  }();
  function ac(n, t, e) {
    var r = n.indexOf(t), i = n.map(function(a, s) {
      return s === r ? a + " - " + e : a;
    });
    return i.join();
  }
  function R2(n) {
    var t = n.inputs, e = n.backend, r = t.input, i = e.texData.get(r.dataId);
    return ir({inputs: {x: i.complexTensorInfos.imag}, backend: e});
  }
  var HP = {kernelName: _.Imag, backendName: "webgl", kernelFunc: R2};
  function VP(n, t, e) {
    var r = [pi(n.shape)].concat(fi(n.shape)), i = {dtype: n.dtype, shape: r, dataId: n.dataId}, a = [pi(t)].concat(fi(t)), s = new s2(a, r), o = true, c = e.runWebGLProgram(s, [i], n.dtype, null, o);
    return {dataId: c.dataId, shape: t, dtype: c.dtype};
  }
  function ar(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.shape, s = e, o = _.util.sizeFromShape(i.shape), c = _.util.inferFromImplicitShape(a, o), l = _.util.sizeFromShape(c);
    _.util.assert(o === l, function() {
      return "The new shape (" + c + ") has " + l + " elements and the old " + ("shape (" + i.shape + ") has " + o + " elements. The new shape and old ") + "shape must have the same number of elements.";
    });
    var u = s.texData.get(i.dataId);
    return u.isPacked && !cs(i.shape, c) && !(u.texture !== null && cs(u.shape, c)) ? VP(i, c, s) : (s.incRef(i.dataId), {dataId: i.dataId, shape: c, dtype: i.dtype});
  }
  var GP = {kernelName: _.Reshape, backendName: "webgl", kernelFunc: ar};
  function la(n, t, e) {
    var r = n[0].dtype;
    if (r === "complex64") {
      var i = n.map(function(b) {
        return up({inputs: {input: b}, backend: e});
      }), a = n.map(function(b) {
        return R2({inputs: {input: b}, backend: e});
      }), s = la(i, t, e), o = la(a, t, e), c = oa({inputs: {real: s, imag: o}, backend: e});
      return i.forEach(function(b) {
        return e.disposeIntermediateTensorInfo(b);
      }), a.forEach(function(b) {
        return e.disposeIntermediateTensorInfo(b);
      }), e.disposeIntermediateTensorInfo(s), e.disposeIntermediateTensorInfo(o), c;
    }
    if (n.length > _.env().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")) {
      var l = Math.floor(n.length / 2), u = la(n.slice(0, l), t, e), h = la(n.slice(l), t, e), d = la([u, h], t, e);
      return e.disposeIntermediateTensorInfo(u), e.disposeIntermediateTensorInfo(h), d;
    }
    if (_.env().getBool("WEBGL_PACK_ARRAY_OPERATIONS") && n[0].shape.length > 1) {
      var p = new MP(n.map(function(b) {
        return b.shape;
      }), t);
      return e.runWebGLProgram(p, n, r);
    }
    var f = _.backend_util.computeOutShape(n.map(function(b) {
      return b.shape;
    }), t), m = n.map(function(b) {
      return ar({inputs: {x: b}, attrs: {shape: [-1, _.util.sizeFromShape(b.shape.slice(t))]}, backend: e});
    }), g = new PP(m.map(function(b) {
      return b.shape;
    })), y = e.runWebGLProgram(g, m, r);
    m.forEach(function(b) {
      return e.disposeIntermediateTensorInfo(b);
    });
    var w = ar({inputs: {x: y}, attrs: {shape: f}, backend: e});
    return e.disposeIntermediateTensorInfo(y), w;
  }
  function qP(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = r.axis, a = _.util.parseAxisParam(i, t[0].shape)[0], s = _.backend_util.computeOutShape(t.map(function(l) {
      return l.shape;
    }), a);
    if (_.util.sizeFromShape(s) === 0)
      return e.makeTensorInfo(s, t[0].dtype, []);
    var o = t.filter(function(l) {
      return _.util.sizeFromShape(l.shape) > 0;
    });
    if (o.length === 1)
      return o[0];
    var c = o.map(function(l) {
      return l.shape;
    });
    return _.backend_util.assertParamsConsistent(c, a), la(o, a, e);
  }
  var YP = {kernelName: _.Concat, backendName: "webgl", kernelFunc: qP};
  var KP = N2 + `
  return cos(x);
`, jP = ic(KP), $P = {kernelName: _.Cos, backendName: "webgl", kernelFunc: jP};
  var XP = `
if (a == b) {
  return 1.0;
};
return a / b;`, JP = `
  // vec4 one = vec4(equal(a, b));
  // return one + (vec4(1.0) - one) * a / b;
  vec4 result = a / b;
  if(a.x == b.x) {
    result.x = 1.;
  }
  if(a.y == b.y) {
    result.y = 1.;
  }
  if(a.z == b.z) {
    result.z = 1.;
  }
  if(a.w == b.w) {
    result.w = 1.;
  }

  return result;
`, ZP = ca({opSnippet: XP, packedOpSnippet: JP, checkOutOfBounds: true}), QP = {kernelName: _.Div, backendName: "webgl", kernelFunc: ZP};
  var O2 = function() {
    function n(t, e, r) {
      this.variableNames = ["real", "imag"];
      var i = e[1];
      this.outputShape = e;
      var a = r ? "2.0 * " + Math.PI : "-2.0 * " + Math.PI, s = r ? i + ".0" : "1.0", o;
      if (t === "real")
        o = "return real * expR - imag * expI;";
      else if (t === "imag")
        o = "return real * expI + imag * expR;";
      else
        throw new Error('FFT component must be either "real" or "imag", got ' + t + ".");
      this.userCode = `
      const float exponentMultiplier = ` + a + `;

      float unaryOpComplex(float real, float expR, float imag, float expI) {
        ` + o + `
      }

      float mulMatDFT(int batch, int index) {
        float indexRatio = float(index) / float(` + i + `);
        float exponentMultiplierTimesIndexRatio =
            exponentMultiplier * indexRatio;

        float result = 0.0;

        for (int i = 0; i < ` + i + `; i++) {
          // x = (-2|2 * PI / N) * index * i;
          float x = exponentMultiplierTimesIndexRatio * float(i);
          float expR = cos(x);
          float expI = sin(x);
          float real = getReal(batch, i);
          float imag = getImag(batch, i);

          result +=
              unaryOpComplex(real, expR, imag, expI) / ` + s + `;
        }

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `;
    }
    return n;
  }();
  function E2(n, t, e) {
    var r = e.texData.get(n.dataId), i = _.util.sizeFromShape(n.shape), a = n.shape[n.shape.length - 1], s = i / a, o = ar({inputs: {x: n}, backend: e, attrs: {shape: [s, a]}}), c = o.shape, l = new O2("real", c, t), u = new O2("imag", c, t), h = [{dataId: r.complexTensorInfos.real.dataId, dtype: r.complexTensorInfos.real.dtype, shape: c}, {dataId: r.complexTensorInfos.imag.dataId, dtype: r.complexTensorInfos.imag.dtype, shape: c}], d = e.runWebGLProgram(l, h, "float32"), p = e.runWebGLProgram(u, h, "float32"), f = oa({inputs: {real: d, imag: p}, backend: e});
    e.disposeIntermediateTensorInfo(d), e.disposeIntermediateTensorInfo(p);
    var m = ar({inputs: {x: f}, backend: e, attrs: {shape: n.shape}});
    return e.disposeIntermediateTensorInfo(m), m;
  }
  function eM(n) {
    var t = n.inputs, e = n.backend, r = t.input;
    return E2(r, false, e);
  }
  var tM = {kernelName: _.FFT, backendName: "webgl", kernelFunc: eM};
  var nM = function() {
    function n(t) {
      this.variableNames = ["Image"], this.outputShape = [];
      var e = t[2];
      this.outputShape = t, this.userCode = `
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];

          int coordX = ` + e + ` - x;
          float outputValue;
          if(coordX >= 0 && coordX < ` + e + `) {
            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
          } else {
            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
          }
          setOutput(outputValue);
        }
    `;
    }
    return n;
  }();
  var rM = {kernelName: _.FlipLeftRight, backendName: "webgl", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = t.image, i = e, a = new nM(r.shape), s = i.runWebGLProgram(a, [r], r.dtype);
    return s;
  }};
  var iM = function() {
    function n(t) {
      this.variableNames = ["A"];
      var e = zt(), r = t[0], i = t[1];
      this.outputShape = t, this.userCode = `
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(` + i + ".0, " + r + `.0);

        vec4 values = ` + e.texture2D + `(A, uv);
        float value;
        if (depth == 0) {
          value = values.r;
        } else if (depth == 1) {
          value = values.g;
        } else if (depth == 2) {
          value = values.b;
        } else if (depth == 3) {
          value = values.a;
        }

        setOutput(floor(value * 255.0 + 0.5));
      }
    `;
    }
    return n;
  }();
  var aM = function() {
    function n(t) {
      this.variableNames = ["A"], this.packedInputs = false, this.packedOutput = true;
      var e = zt(), r = t[0], i = t[1];
      this.outputShape = t, this.userCode = `
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];

        vec4 result = vec4(0.);

        for(int row=0; row<=1; row++) {
          for(int col=0; col<=1; col++) {
            texC = coords[1] + row;
            depth = coords[2] + col;

            vec2 uv = (vec2(texC, texR) + halfCR) /
                       vec2(` + i + ".0, " + r + `.0);
            vec4 values = ` + e.texture2D + `(A, uv);
            float value;
            if (depth == 0) {
              value = values.r;
            } else if (depth == 1) {
              value = values.g;
            } else if (depth == 2) {
              value = values.b;
            } else if (depth == 3) {
              value = values.a;
            }

            result[row * 2 + col] = floor(value * 255.0 + 0.5);
          }
        }

        ` + e.output + ` = result;
      }
    `;
    }
    return n;
  }();
  var oM = {kernelName: _.FromPixels, backendName: "webgl", kernelFunc: sM}, ua;
  function sM(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.pixels, a = r.numChannels, s = typeof HTMLVideoElement != "undefined" && i instanceof HTMLVideoElement, o = typeof HTMLImageElement != "undefined" && i instanceof HTMLImageElement, c = s ? [i.videoWidth, i.videoHeight] : [i.width, i.height], l = c[0], u = c[1], h = [u, l], d = [u, l, a];
    (o || s) && (ua == null && (ua = document.createElement("canvas").getContext("2d")), ua.canvas.width = l, ua.canvas.height = u, ua.drawImage(i, 0, 0, l, u), i = ua.canvas);
    var p = e.makeTensorInfo(h, "int32");
    e.texData.get(p.dataId).usage = cn.PIXELS, e.gpgpu.uploadPixelDataToTexture(e.getTexture(p.dataId), i);
    var f = _.env().getBool("WEBGL_PACK") ? new aM(d) : new iM(d), m = e.runWebGLProgram(f, [p], "int32");
    return e.disposeData(p.dataId), m;
  }
  function cM(n) {
    var t = n.inputs, e = n.backend, r = t.input;
    return E2(r, true, e);
  }
  var lM = {kernelName: _.IFFT, backendName: "webgl", kernelFunc: cM};
  var D2 = function() {
    function n(t, e) {
      this.variableNames = ["x"];
      var r = t.windowSize, i = t.batchSize, a = t.inSize, s = t.outSize;
      this.outputShape = [i, s];
      var o = Math.floor(r / 4) * 4, c = r % 4, l = "sumValue += dot(values, ones);";
      if (e != null) {
        var u = 1 / e;
        l = "sumValue += dot(values * " + (_.util.isInt(u) ? u.toPrecision(2) : u) + ", ones);";
      }
      var h = "";
      a % r > 0 && (h = `
        if (inIdx < 0 || inIdx >= ` + a + `) {
          return 0.0;
        }
      `), this.userCode = `
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ` + h + `
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ` + r + `;

        float sumValue = 0.0;

        for (int i = 0; i < ` + o + `; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ` + l + `
        }

        int inIdx = inOffset + ` + o + `;
        if (` + (c === 1) + `) {
          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);

          ` + l + `
        } else if (` + (c === 2) + `) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1), 0.0, 0.0);

          ` + l + `
        } else if (` + (c === 3) + `) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2), 0.0);

          ` + l + `
        }
        setOutput(sumValue);
      }
    `;
    }
    return n;
  }();
  function uM(n) {
    for (var t = []; t.length === 0 || t[t.length - 1].outSize !== 1; ) {
      var e = t.length ? t[t.length - 1].outSize : n[1], r = _.backend_util.computeOptimalWindowSize(e);
      t.push({inSize: e, windowSize: r, outSize: Math.ceil(e / r)});
    }
    return t;
  }
  function k2(n, t, e, r) {
    for (var i = uM(n.shape), a = n, s = 0; s < i.length; s++) {
      var o = i[s], c = o.inSize, l = o.windowSize, u = o.outSize, h = void 0, d = void 0;
      e === "mean" ? h = s === 0 ? new D2({windowSize: l, inSize: c, batchSize: n.shape[0], outSize: u}, c) : new D2({windowSize: l, inSize: c, batchSize: n.shape[0], outSize: u}) : h = new a2({windowSize: l, inSize: c, batchSize: n.shape[0], outSize: u}, e), d = a, a = r.runWebGLProgram(h, [a], t), d.dataId !== n.dataId && r.disposeIntermediateTensorInfo(d);
    }
    return a;
  }
  function hM(n, t, e, r) {
    var i = _.util.sizeFromShape(t), a = _.util.sizeFromShape(n.shape), s = a / i, o = ar({inputs: {x: n}, attrs: {shape: [s, i]}, backend: r}), c = k2(o, n.dtype, "max", r), l = ar({inputs: {x: c}, attrs: {shape: e}, backend: r});
    return r.disposeIntermediateTensorInfo(o), r.disposeIntermediateTensorInfo(c), l;
  }
  var pM = function() {
    function n(t, e) {
      this.variableNames = ["A"];
      for (var r = new Array(t.length), i = 0; i < r.length; i++)
        r[i] = t[e[i]];
      this.outputShape = r, this.rank = r.length;
      var a = Ze(this.rank), s = dM(e);
      this.userCode = `
    void main() {
      ` + a + ` resRC = getOutputCoords();
      setOutput(getA(` + s + `));
    }
    `;
    }
    return n;
  }();
  function dM(n) {
    var t = n.length;
    if (t > 6)
      throw Error("Transpose for rank " + t + " is not yet supported");
    for (var e = ["resRC.x", "resRC.y", "resRC.z", "resRC.w", "resRC.u", "resRC.v"], r = new Array(t), i = 0; i < n.length; i++)
      r[n[i]] = e[i];
    return r.join();
  }
  var fM = function() {
    function n(t, e) {
      this.variableNames = ["A"], this.packedInputs = true, this.packedOutput = true;
      for (var r = new Array(t.length), i = 0; i < r.length; i++)
        r[i] = t[e[i]];
      if (this.outputShape = r, this.rank = r.length, this.rank > 6)
        throw Error("Packed transpose for rank " + this.rank + " is not yet supported.");
      for (var a = Ze(this.rank), s = Nb("rc", this.rank), o = new Array(this.rank), i = 0; i < e.length; i++)
        o[e[i]] = s[i];
      var c = "vec2(" + o.slice(-2).join() + ")", l = "++" + s[this.rank - 1] + " < " + r[this.rank - 1], u = "getChannel(getA(" + o.join() + "), " + c + ")";
      this.userCode = `
    void main() {
      ` + a + ` rc = getOutputCoords();
      vec4 result = vec4(0.);
      result[0] = ` + u + `;
      if(` + l + `) {
        result[1] = ` + u + `;
      }
      --` + s[this.rank - 1] + `;
      if(++` + s[this.rank - 2] + " < " + r[this.rank - 2] + `) {
        result[2] = ` + u + `;
        if(` + l + `) {
          result[3] = ` + u + `;
        }
      }
      setOutput(result);
    }
    `;
    }
    return n;
  }();
  function dp(n, t, e) {
    var r = _.env().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new fM(n.shape, t) : new pM(n.shape, t);
    return e.runWebGLProgram(r, [n], n.dtype);
  }
  var mM = {kernelName: _.Max, backendName: "webgl", kernelFunc: function(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = t.x, a = e, s = a.reductionIndices, o = a.keepDims, c = r, l = i.shape.length, u = _.util.parseAxisParam(s, i.shape), h = u, d = _.backend_util.getAxesPermutation(h, l), p = d != null, f = c.shouldExecuteOnCPU([i]), m = i;
    if (p) {
      if (f) {
        for (var g = c.texData.get(m.dataId), y = g.values, w = new Array(l), b = 0; b < w.length; b++)
          w[b] = i.shape[d[b]];
        var L = ep(y, i.shape, i.dtype, d, w);
        m = c.makeTensorInfo(w, i.dtype);
        var x = c.texData.get(m.dataId);
        x.values = L;
      } else
        m = dp(i, d, c);
      h = _.backend_util.getInnerMostAxes(h.length, l);
    }
    _.backend_util.assertAxesAreInnerMostDims("max", h, l);
    var N = _.backend_util.computeOutAndReduceShapes(m.shape, h), I = N[0], C = N[1], O = I;
    o && (O = _.backend_util.expandShapeToKeepDim(I, u));
    var D;
    if (f) {
      var g = c.texData.get(m.dataId), y = g.values, F = ZW(y, _.util.sizeFromShape(C), O, i.dtype);
      D = c.makeTensorInfo(O, i.dtype);
      var k = c.texData.get(D.dataId);
      k.values = F;
    } else
      D = hM(m, C, O, c);
    return p && c.disposeIntermediateTensorInfo(m), D;
  }};
  function gM(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x;
    ta(i, "maxPool");
    var a = r.filterSize, s = r.strides, o = r.pad, c = r.dimRoundingMode, l = 1;
    _.util.assert(_.backend_util.eitherStridesOrDilationsAreOne(s, l), function() {
      return "Error in maxPool: Either strides or dilations must be 1. " + ("Got strides " + s + " and dilations '" + l + "'");
    });
    var u = _.backend_util.computePool2DInfo(i.shape, a, s, l, o, c);
    if (u.filterWidth === 1 && u.filterHeight === 1 && _.util.arraysEqual(u.inShape, u.outShape))
      return ir({inputs: {x: i}, backend: e});
    var h = new us(u, "max", false);
    return e.runWebGLProgram(h, [i], i.dtype);
  }
  var yM = {kernelName: _.MaxPool, backendName: "webgl", kernelFunc: gM};
  function vM(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.dy, a = t.input, s = t.output, o = a;
    ta([a, s], "maxPoolBackprop");
    var c = r.filterSize, l = r.strides, u = r.pad, h = r.dimRoundingMode, d = _.backend_util.computePool2DInfo(o.shape, c, l, 1, u, h), p = true, f = new us(d, "max", p), m = e.runWebGLProgram(f, [o], o.dtype), g = new JB(d), y = e.runWebGLProgram(g, [i, m], o.dtype);
    return e.disposeIntermediateTensorInfo(m), y;
  }
  var wM = {kernelName: _.MaxPoolBackprop, backendName: "webgl", kernelFunc: vM};
  function bM(n, t, e, r) {
    var i = new us(e, "max", false), a = r.runWebGLProgram(i, [n], "float32");
    i = new us(e, "max", true, true, t);
    var s = r.runWebGLProgram(i, [n], "float32");
    return [a, s];
  }
  var xM = {kernelName: _.MaxPoolWithArgmax, backendName: "webgl", kernelFunc: function(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = t.x, a = e, s = a.filterSize, o = a.strides, c = a.pad, l = a.includeBatchInIndex, u = r;
    _.util.assert(i.shape.length === 4, function() {
      return "Error in maxPool: input must be rank 4 but got rank " + i.shape.length + ".";
    });
    var h = [1, 1];
    _.util.assert(_.backend_util.eitherStridesOrDilationsAreOne(o, h), function() {
      return "Error in maxPool: Either strides or dilations must be 1. " + ("Got strides " + o + " and dilations '" + h + "'");
    });
    var d = _.backend_util.computePool2DInfo(i.shape, s, o, h, c), p = bM(i, l, d, u), f = p[0], m = p[1];
    return [f, m];
  }};
  function LM(n, t, e, r) {
    var i = _.util.sizeFromShape(t), a = _.util.sizeFromShape(n.shape), s = a / i, o = ar({inputs: {x: n}, attrs: {shape: [s, i]}, backend: r}), c = k2(o, "float32", "mean", r), l = ar({inputs: {x: c}, attrs: {shape: e}, backend: r});
    return r.disposeIntermediateTensorInfo(o), r.disposeIntermediateTensorInfo(c), l;
  }
  var SM = {kernelName: _.Mean, backendName: "webgl", kernelFunc: function(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = t.x, a = e, s = a.keepDims, o = a.axis, c = r, l = i.shape.length, u = _.util.parseAxisParam(o, i.shape), h = u, d = _.backend_util.getAxesPermutation(h, l), p = d != null, f = c.shouldExecuteOnCPU([i]), m = [], g = i;
    if (p) {
      if (f) {
        for (var y = c.texData.get(g.dataId), w = y.values, b = new Array(l), L = 0; L < b.length; L++)
          b[L] = i.shape[d[L]];
        var x = ep(w, i.shape, i.dtype, d, b);
        g = c.makeTensorInfo(b, i.dtype);
        var N = c.texData.get(g.dataId);
        N.values = x;
      } else
        g = dp(i, d, c);
      m.push(g), h = _.backend_util.getInnerMostAxes(h.length, l);
    }
    _.backend_util.assertAxesAreInnerMostDims("sum", h, l);
    var I = _.backend_util.computeOutAndReduceShapes(g.shape, h), C = I[0], O = I[1], D = C;
    s && (D = _.backend_util.expandShapeToKeepDim(C, u));
    for (var F = LM(g, O, D, c), k = 0, B = m; k < B.length; k++) {
      var L = B[k];
      c.disposeIntermediateTensorInfo(L);
    }
    return F;
  }};
  var IM = function() {
    function n(t, e, r) {
      this.variableNames = ["x"], this.outputShape = e.map(function(u, h) {
        return u[0] + t[h] + u[1];
      });
      var i = t.length, a = Ze(i), s = e.map(function(u) {
        return u[0];
      }).join(","), o = e.map(function(u, h) {
        return u[0] + t[h];
      }).join(","), c = ["coords[0]", "coords[1]", "coords[2]", "coords[3]"].slice(0, i), l = r === "reflect" ? 0 : 1;
      if (i === 1) {
        this.userCode = `
        int start = ` + s + `;
        int end = ` + o + `;

        void main() {
          int outC = getOutputCoords();
          if (outC < start) {
            outC = start * 2 - outC - ` + l + `;
          } else if(outC >= end) {
            outC = (end - 1) * 2 - outC + ` + l + `;
          }
          setOutput(getX(outC - start));
        }
      `;
        return;
      }
      this.userCode = `
      ` + a + " start = " + a + "(" + s + `);
      ` + a + " end = " + a + "(" + o + `);

      void main() {
        ` + a + ` outC = getOutputCoords();
        for (int i = 0; i < ` + i + `; i++) {
          if (outC[i] < start[i]) {
            outC[i] = start[i] * 2 - outC[i] - ` + l + `;
          } else if(outC[i] >= end[i]) {
            outC[i] = (end[i] - 1) * 2 - outC[i] + ` + l + `;
          }
        }
        ` + a + ` coords = outC - start;
        setOutput(getX(` + c + `));
      }
    `;
    }
    return n;
  }();
  var AM = function() {
    function n(t, e, r) {
      this.variableNames = ["x"], this.packedInputs = true, this.packedOutput = true, this.outputShape = e.map(function(m, g) {
        return m[0] + t[g] + m[1];
      });
      var i = t.length, a = Ze(i), s = e.map(function(m) {
        return m[0];
      }).join(","), o = e.map(function(m, g) {
        return m[0] + t[g];
      }).join(","), c = Bt("rc", i), l = Bt("source", i), u = c[i - 1] + " < " + this.outputShape[i - 1], h = i === 1 ? "source" : "vec2(" + l.slice(-2).join() + ")", d = r === "reflect" ? 0 : 1, p = "";
      if (i === 1) {
        var f = `
        ` + a + ` source = rc;
        if (source < start) {
          source = start * 2 - source - ` + d + `;
        } else if (source >= end) {
          source = (end - 1) * 2 - source + ` + d + `;
        }
        source -= start;
      `;
        p = `
        ` + a + ` rc = outputLoc;
        ` + f + `
        result[0] = getChannel(getX(` + l.join() + "), " + h + `);
        ` + c[i - 1] + ` += 1;
        if(` + u + `) {
          ` + f + `
          result[1] = getChannel(getX(` + l.join() + "), " + h + `);
        }
      `;
      } else {
        var f = `
        ` + a + ` source = rc;
        ` + a + " lt = " + a + `(lessThan(source, start));
        ` + a + " gte = " + a + `(greaterThanEqual(source, end));
        ` + a + ` orig = 1 - (lt + gte);
        source = orig * source +
                lt * (start * 2 - source - ` + d + `) +
                gte * ((end - 1) * 2 - source + ` + d + `);
        source -= start;
      `;
        p = `
        ` + a + ` rc = outputLoc;
        ` + f + `
        result[0] = getChannel(getX(` + l.join() + "), " + h + `);
        ` + c[i - 1] + ` += 1;
        if(` + u + `) {
          ` + f + `
          result[1] = getChannel(getX(` + l.join() + "), " + h + `);
        }
        rc = outputLoc;
        ` + c[i - 2] + ` += 1;
        if(` + c[i - 2] + " < " + this.outputShape[i - 2] + `) {
          ` + f + `
          result[2] = getChannel(getX(` + l.join() + "), " + h + `);
          ` + c[i - 1] + ` += 1;
          if(` + u + `) {
            ` + f + `
            result[3] = getChannel(getX(` + l.join() + "), " + h + `);
          }
        }
      `;
      }
      this.userCode = `
      const ` + a + " start = " + a + "(" + s + `);
      const ` + a + " end = " + a + "(" + o + `);

      void main() {
        ` + a + ` outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ` + p + `
        setOutput(result);
      }
    `;
    }
    return n;
  }();
  var TM = function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs, i = t.x, a = r.paddings, s = r.mode, o = _.env().getBool("WEBGL_PACK_ARRAY_OPERATIONS") ? new AM(i.shape, a, s) : new IM(i.shape, a, s), c = e.runWebGLProgram(o, [i], i.dtype);
    return c;
  }, NM = {kernelName: _.MirrorPad, backendName: "webgl", kernelFunc: TM};
  var F2 = {REAL: "return areal * breal - aimag * bimag;", IMAG: "return areal * bimag + aimag * breal;"}, W2 = function() {
    function n(t, e, r) {
      this.variableNames = ["AReal", "AImag", "BReal", "BImag"], this.outputShape = _.backend_util.assertAndGetBroadcastShape(e, r), this.userCode = `
      float binaryOpComplex(
          float areal, float aimag, float breal, float bimag) {
        ` + t + `
      }

      void main() {
        float areal = getARealAtOutCoords();
        float aimag = getAImagAtOutCoords();
        float breal = getBRealAtOutCoords();
        float bimag = getBImagAtOutCoords();
        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
      }
    `;
    }
    return n;
  }();
  var U2 = "return a * b;";
  function _M(n) {
    var t = n.inputs, e = n.backend, r = t.a, i = t.b, a = _.backend_util.upcastType(r.dtype, i.dtype);
    if (r.dtype === "complex64") {
      var s = e.texData.get(r.dataId), o = e.texData.get(i.dataId), c = new W2(F2.REAL, r.shape, i.shape), l = new W2(F2.IMAG, r.shape, i.shape), u = [{dataId: s.complexTensorInfos.real.dataId, dtype: s.complexTensorInfos.real.dtype, shape: r.shape}, {dataId: s.complexTensorInfos.imag.dataId, dtype: s.complexTensorInfos.imag.dtype, shape: r.shape}, {dataId: o.complexTensorInfos.real.dataId, dtype: o.complexTensorInfos.real.dtype, shape: i.shape}, {dataId: o.complexTensorInfos.imag.dataId, dtype: o.complexTensorInfos.imag.dtype, shape: i.shape}], h = e.runWebGLProgram(c, u, "float32"), d = e.runWebGLProgram(l, u, "float32"), p = oa({inputs: {real: h, imag: d}, backend: e});
      return e.disposeIntermediateTensorInfo(h), e.disposeIntermediateTensorInfo(d), p;
    }
    if (e.shouldExecuteOnCPU([r, i])) {
      var s = e.texData.get(r.dataId), o = e.texData.get(i.dataId), f = QW(r.shape, i.shape, s.values, o.values, a), m = f[0], g = f[1], y = e.makeTensorInfo(g, a), w = e.texData.get(y.dataId);
      return w.values = m, y;
    }
    var b;
    return _.env().getBool("WEBGL_PACK_BINARY_OPERATIONS") ? b = new nr(U2, r.shape, i.shape) : b = new Wt(U2, r.shape, i.shape), e.runWebGLProgram(b, [r, i], a);
  }
  var CM = {kernelName: _.Multiply, backendName: "webgl", kernelFunc: _M};
  var RM = {kernelName: _.NonMaxSuppressionV3, backendName: "webgl", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs;
    _.backend_util.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");
    var i = t, a = i.boxes, s = i.scores, o = r, c = o.maxOutputSize, l = o.iouThreshold, u = o.scoreThreshold, h = e, d = h.readSync(a.dataId), p = h.readSync(s.dataId), f = c, m = l, g = u;
    return _.kernel_impls.nonMaxSuppressionV3Impl(d, p, f, m, g);
  }};
  var OM = _.kernel_impls.nonMaxSuppressionV4Impl, EM = {kernelName: _.NonMaxSuppressionV4, backendName: "webgl", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs;
    _.backend_util.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");
    var i = t, a = i.boxes, s = i.scores, o = r, c = o.maxOutputSize, l = o.iouThreshold, u = o.scoreThreshold, h = o.padToMaxOutputSize, d = e, p = d.readSync(a.dataId), f = d.readSync(s.dataId), m = OM(p, f, c, l, u, h), g = m.selectedIndices, y = m.validOutputs;
    return [g, y];
  }};
  var DM = _.kernel_impls.nonMaxSuppressionV5Impl, kM = {kernelName: _.NonMaxSuppressionV5, backendName: "webgl", kernelFunc: function(n) {
    var t = n.inputs, e = n.backend, r = n.attrs;
    _.backend_util.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");
    var i = t, a = i.boxes, s = i.scores, o = r, c = o.maxOutputSize, l = o.iouThreshold, u = o.scoreThreshold, h = o.softNmsSigma, d = e, p = d.readSync(a.dataId), f = d.readSync(s.dataId), m = c, g = l, y = u, w = h, b = DM(p, f, m, g, y, w), L = b.selectedIndices, x = b.selectedScores;
    return [L, x];
  }};
  var FM = function() {
    function n(t, e, r, i) {
      this.variableNames = ["Image"], this.outputShape = [];
      var a = t[1], s = t[2], o = Math.sin(e).toFixed(3), c = Math.cos(e).toFixed(3);
      this.outputShape = t;
      var l = _.backend_util.getImageCenter(i, a, s), u = l[0], h = l[1], d = u.toFixed(3), p = h.toFixed(3), f = "";
      typeof r == "number" ? f = "float outputValue = " + r.toFixed(2) + ";" : f = `
        vec3 fill = vec3(` + r.join(",") + `);
        float outputValue = fill[coords[3]];`, this.userCode = `
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];
          int y = coords[1];
          float coordXFloat = (float(x) - ` + d + ") * " + c + " - (float(y) - " + p + ") * " + o + `;
          float coordYFloat = (float(x) - ` + d + ") * " + o + " + (float(y) - " + p + ") * " + c + `;
          int coordX = int(round(coordXFloat + ` + d + `));
          int coordY = int(round(coordYFloat + ` + p + `));
          ` + f + `
          if(coordX >= 0 && coordX < ` + s + " && coordY >= 0 && coordY < " + a + `) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `;
    }
    return n;
  }();
  var WM = {kernelName: _.RotateWithOffset, backendName: "webgl", kernelFunc: function(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = t.image, a = e, s = a.radians, o = a.fillValue, c = a.center, l = r, u = new FM(i.shape, s, o, c), h = l.runWebGLProgram(u, [i], i.dtype);
    return h;
  }};
  var UM = N2 + `
  return sin(x);
`, BM = ic(UM), zM = {kernelName: _.Sin, backendName: "webgl", kernelFunc: BM};
  var PM = "return x * x;", MM = ic(PM), HM = {kernelName: _.Square, backendName: "webgl", kernelFunc: MM};
  var B2 = "return (a - b) * (a - b);", VM = ca({opSnippet: B2, packedOpSnippet: B2}), GM = {kernelName: _.SquaredDifference, backendName: "webgl", kernelFunc: VM};
  var z2 = "return a - b;", qM = ca({opSnippet: z2, packedOpSnippet: z2, supportsComplex: true, cpuKernelImpl: nU}), YM = {kernelName: _.Sub, backendName: "webgl", kernelFunc: qM};
  var KM = "return tan(x);", jM = ic(KM), $M = {kernelName: _.Tan, backendName: "webgl", kernelFunc: jM};
  var XM = {kernelName: _.Transpose, backendName: "webgl", kernelFunc: function(n) {
    for (var t = n.inputs, e = n.attrs, r = n.backend, i = t.x, a = e.perm, s = r, o = i.shape.length, c = new Array(o), l = 0; l < c.length; l++)
      c[l] = i.shape[a[l]];
    var u;
    if (s.shouldExecuteOnCPU([i])) {
      var h = s.texData.get(i.dataId), d = h.values, p = ep(d, i.shape, i.dtype, a, c);
      u = s.makeTensorInfo(c, i.dtype);
      var f = s.texData.get(u.dataId);
      f.values = p;
    } else
      u = dp(i, a, s);
    return u;
  }};
  function JM(n) {
    var t = n.inputs, e = n.attrs, r = n.backend, i = e.axis, a = t.x;
    ta(a, "unique"), console.warn("WARNING: ", "UI might be locked temporarily as data is being downloaded");
    var s = r.readSync(a.dataId), o = rU(s, i, a.shape, a.dtype), c = o.outputValues, l = o.outputShape, u = o.indices;
    return [r.makeTensorInfo(l, a.dtype, c), r.makeTensorInfo([u.length], "int32", u)];
  }
  var ZM = {kernelName: _.Unique, backendName: "webgl", kernelFunc: JM};
  var QM = [xP, AP, NP, CP, DP, zP, yP, YP, $P, QP, tM, rM, oM, gP, lM, HP, mM, yM, wM, xM, SM, NM, CM, RM, EM, kM, FP, WP, GP, WM, zM, HM, YM, GM, $M, XM, ZM];
  for (var pp = 0, P2 = QM; pp < P2.length; pp++) {
    var eH = P2[pp];
    _.registerKernel(eH);
  }
  Pn.GPGPUContext = r2;
  Pn.MathBackendWebGL = A2;
  Pn.forceHalfFloat = T2;
  Pn.gpgpu_util = HB;
  Pn.setWebGLContext = nb;
  Pn.version_webgl = fP;
  Pn.webgl = mP;
  Pn.webgl_util = RW;
});
var Ut = we((yi) => {
  "use strict";
  Object.defineProperty(yi, "__esModule", {value: true});
  var fp = Qr(), mp = I1(), gp = z1(), H2 = sw(), tH = tb(), nH = M2();
  var rH = "2.7.0";
  var iH = {"tfjs-core": fp.version_core, "tfjs-backend-cpu": tH.version_cpu, "tfjs-backend-webgl": nH.version_webgl, "tfjs-data": H2.version_data, "tfjs-layers": mp.version_layers, "tfjs-converter": gp.version_converter, tfjs: rH};
  Object.keys(fp).forEach(function(n) {
    n !== "default" && Object.defineProperty(yi, n, {enumerable: true, get: function() {
      return fp[n];
    }});
  });
  Object.keys(mp).forEach(function(n) {
    n !== "default" && Object.defineProperty(yi, n, {enumerable: true, get: function() {
      return mp[n];
    }});
  });
  Object.keys(gp).forEach(function(n) {
    n !== "default" && Object.defineProperty(yi, n, {enumerable: true, get: function() {
      return gp[n];
    }});
  });
  yi.data = H2;
  yi.version = iH;
});
var j2 = we((sc) => {
  const Ye = Ut(), V2 = 6;
  function aH(n) {
    const t = {strides: [n / 16, n / 8], anchors: [2, 6]}, e = [];
    for (let r = 0; r < t.strides.length; r++) {
      const i = t.strides[r], a = Math.floor((n + i - 1) / i), s = Math.floor((n + i - 1) / i), o = t.anchors[r];
      for (let c = 0; c < a; c++) {
        const l = i * (c + 0.5);
        for (let u = 0; u < s; u++) {
          const h = i * (u + 0.5);
          for (let d = 0; d < o; d++)
            e.push([h, l]);
        }
      }
    }
    return e;
  }
  const G2 = (n) => {
    n.startEndTensor.dispose(), n.startPoint.dispose(), n.endPoint.dispose();
  }, q2 = (n) => ({startEndTensor: n, startPoint: Ye.slice(n, [0, 0], [-1, 2]), endPoint: Ye.slice(n, [0, 2], [-1, 2])}), Y2 = (n, t) => {
    const e = Ye.mul(n.startPoint, t), r = Ye.mul(n.endPoint, t), i = Ye.concat2d([e, r], 1);
    return q2(i);
  };
  function sH(n, t, e) {
    const r = Ye.slice(n, [0, 1], [-1, 2]), i = Ye.add(r, t), a = Ye.slice(n, [0, 3], [-1, 2]), s = Ye.div(a, e), o = Ye.div(i, e), c = Ye.div(s, 2), l = Ye.sub(o, c), u = Ye.add(o, c), h = Ye.mul(l, e), d = Ye.mul(u, e), p = 1;
    return Ye.concat2d([h, d], p);
  }
  function oH(n, t) {
    return Ye.tidy(() => {
      const e = n.box ? n.box : n;
      return Y2(e, t).startEndTensor.squeeze();
    });
  }
  class K2 {
    constructor(n, t) {
      this.blazeFaceModel = n, this.width = t.detector.inputSize, this.height = t.detector.inputSize, this.anchorsData = aH(t.detector.inputSize), this.anchors = Ye.tensor2d(this.anchorsData), this.inputSize = Ye.tensor1d([this.width, this.height]), this.config = t, this.scaleFaces = 0.8;
    }
    async getBoundingBoxes(n) {
      if (!n || n.isDisposedInternal || n.shape.length !== 4 || n.shape[1] < 1 || n.shape[2] < 1)
        return null;
      const [t, e, r] = Ye.tidy(() => {
        const u = n.resizeBilinear([this.width, this.height]), h = Ye.sub(u.div(127.5), 1), d = this.blazeFaceModel.predict(h);
        let p;
        if (Array.isArray(d)) {
          const y = d.sort((x, N) => x.size - N.size), w = Ye.concat([y[0], y[2]], 2), b = Ye.concat([y[1], y[3]], 2), L = Ye.concat([b, w], 1);
          p = L.squeeze(0);
        } else
          p = d.squeeze();
        const f = sH(p, this.anchors, this.inputSize), m = Ye.slice(p, [0, 0], [-1, 1]), g = Ye.sigmoid(m).squeeze();
        return [p, f, g];
      }), i = await Ye.image.nonMaxSuppressionAsync(e, r, this.config.detector.maxFaces, this.config.detector.iouThreshold, this.config.detector.scoreThreshold), a = i.arraySync();
      i.dispose();
      const s = a.map((u) => Ye.slice(e, [u, 0], [1, -1])), o = s.map((u) => {
        const h = u.arraySync();
        return u.dispose(), h;
      }), c = r.dataSync(), l = [];
      for (const u in o) {
        const h = a[u], d = c[h];
        if (d > this.config.detector.minConfidence) {
          const p = q2(o[u]), f = this.anchorsData[h], m = Ye.tidy(() => Ye.slice(t, [h, V2 - 1], [1, -1]).squeeze().reshape([V2, -1]));
          l.push({box: p, landmarks: m, anchor: f, confidence: d});
        }
      }
      return t.dispose(), e.dispose(), r.dispose(), t.dispose(), {boxes: l, scaleFactor: [n.shape[2] / this.width, n.shape[1] / this.height]};
    }
    async estimateFaces(n) {
      const {boxes: t, scaleFactor: e} = await this.getBoundingBoxes(n), r = [];
      for (const i of t) {
        const a = i.landmarks.arraySync(), s = oH(i, e), o = Y2.arraySync(), c = i.probability.arraySync(), l = i.anchor, [u, h] = e, d = a.map((f) => [(f[0] + l[0]) * u, (f[1] + l[1]) * h]), p = {topLeft: o.slice(0, 2), bottomRight: o.slice(2), landmarks: d, probability: c};
        G2(i.box), i.landmarks.dispose(), i.probability.dispose(), s.dispose(), r.push(p);
      }
      return r;
    }
  }
  async function cH(n) {
    const t = await Ye.loadGraphModel(n.detector.modelPath, {fromTFHub: n.detector.modelPath.includes("tfhub.dev")}), e = new K2(t, n);
    return console.log(`Human: load model: ${n.detector.modelPath.match(/\/(.*)\./)[1]}`), e;
  }
  sc.load = cH;
  sc.BlazeFaceModel = K2;
  sc.disposeBox = G2;
});
var vp = we((yp) => {
  yp.MESH_ANNOTATIONS = {silhouette: [10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288, 397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136, 172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109], lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291], lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291], lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308], lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308], rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173], rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133], rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190], rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243], rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189], rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244], rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245], rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193], rightEyebrowLower: [35, 124, 46, 53, 52, 65], rightEyeIris: [473, 474, 475, 476, 477], leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398], leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362], leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414], leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463], leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413], leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464], leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465], leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417], leftEyebrowLower: [265, 353, 276, 283, 282, 295], leftEyeIris: [468, 469, 470, 471, 472], midwayBetweenEyes: [168], noseTip: [1], noseBottom: [2], noseRightCorner: [98], noseLeftCorner: [327], rightCheek: [205], leftCheek: [425]};
  yp.MESH_TO_IRIS_INDICES_MAP = [{key: "EyeUpper0", indices: [9, 10, 11, 12, 13, 14, 15]}, {key: "EyeUpper1", indices: [25, 26, 27, 28, 29, 30, 31]}, {key: "EyeUpper2", indices: [41, 42, 43, 44, 45, 46, 47]}, {key: "EyeLower0", indices: [0, 1, 2, 3, 4, 5, 6, 7, 8]}, {key: "EyeLower1", indices: [16, 17, 18, 19, 20, 21, 22, 23, 24]}, {key: "EyeLower2", indices: [32, 33, 34, 35, 36, 37, 38, 39, 40]}, {key: "EyeLower3", indices: [54, 55, 56, 57, 58, 59, 60, 61, 62]}, {key: "EyebrowUpper", indices: [63, 64, 65, 66, 67, 68, 69, 70]}, {key: "EyebrowLower", indices: [48, 49, 50, 51, 52, 53]}];
});
var $2 = we((vi) => {
  const lH = Ut();
  function uH(n, t) {
    const e = [n.startPoint[0] * t[0], n.startPoint[1] * t[1]], r = [n.endPoint[0] * t[0], n.endPoint[1] * t[1]];
    return {startPoint: e, endPoint: r};
  }
  vi.scaleBoxCoordinates = uH;
  function wp(n) {
    return [Math.abs(n.endPoint[0] - n.startPoint[0]), Math.abs(n.endPoint[1] - n.startPoint[1])];
  }
  vi.getBoxSize = wp;
  function bp(n) {
    return [n.startPoint[0] + (n.endPoint[0] - n.startPoint[0]) / 2, n.startPoint[1] + (n.endPoint[1] - n.startPoint[1]) / 2];
  }
  vi.getBoxCenter = bp;
  function hH(n, t, e) {
    const r = t.shape[1], i = t.shape[2], a = [[n.startPoint[1] / r, n.startPoint[0] / i, n.endPoint[1] / r, n.endPoint[0] / i]];
    return lH.image.cropAndResize(t, a, [0], e);
  }
  vi.cutBoxFromImageAndResize = hH;
  function dH(n, t = 1.5) {
    const e = bp(n), r = wp(n), i = [t * r[0] / 2, t * r[1] / 2], a = [e[0] - i[0], e[1] - i[1]], s = [e[0] + i[0], e[1] + i[1]];
    return {startPoint: a, endPoint: s, landmarks: n.landmarks};
  }
  vi.enlargeBox = dH;
  function pH(n) {
    const t = bp(n), e = wp(n), r = Math.max(...e), i = r / 2, a = [t[0] - i, t[1] - i], s = [t[0] + i, t[1] + i];
    return {startPoint: a, endPoint: s, landmarks: n.landmarks};
  }
  vi.squarifyBox = pH;
});
var ex = we((Nn) => {
  Nn.IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];
  function X2(n) {
    return n - 2 * Math.PI * Math.floor((n + Math.PI) / (2 * Math.PI));
  }
  Nn.normalizeRadians = X2;
  function fH(n, t) {
    const e = Math.PI / 2 - Math.atan2(-(t[1] - n[1]), t[0] - n[0]);
    return X2(e);
  }
  Nn.computeRotation = fH;
  function mH(n) {
    return n * 180 / Math.PI;
  }
  Nn.radToDegrees = mH;
  function J2(n, t) {
    return [[1, 0, n], [0, 1, t], [0, 0, 1]];
  }
  function ha(n, t) {
    let e = 0;
    for (let r = 0; r < n.length; r++)
      e += n[r] * t[r];
    return e;
  }
  Nn.dot = ha;
  function Z2(n, t) {
    const e = [];
    for (let r = 0; r < n.length; r++)
      e.push(n[r][t]);
    return e;
  }
  Nn.getColumnFrom2DArr = Z2;
  function Q2(n, t) {
    const e = [], r = n.length;
    for (let i = 0; i < r; i++) {
      e.push([]);
      for (let a = 0; a < r; a++)
        e[i].push(ha(n[i], Z2(t, a)));
    }
    return e;
  }
  function gH(n, t) {
    const e = Math.cos(n), r = Math.sin(n), i = [[e, -r, 0], [r, e, 0], [0, 0, 1]], a = J2(t[0], t[1]), s = Q2(a, i), o = J2(-t[0], -t[1]);
    return Q2(s, o);
  }
  Nn.buildRotationMatrix = gH;
  function yH(n) {
    const t = [[n[0][0], n[1][0]], [n[0][1], n[1][1]]], e = [n[0][2], n[1][2]], r = [-ha(t[0], e), -ha(t[1], e)];
    return [t[0].concat(r[0]), t[1].concat(r[1]), [0, 0, 1]];
  }
  Nn.invertTransformMatrix = yH;
  function vH(n, t) {
    return [ha(n, t[0]), ha(n, t[1])];
  }
  Nn.rotatePoint = vH;
  function wH(n, t) {
    return Math.sqrt((n[0] - t[0]) ** 2 + (n[1] - t[1]) ** 2);
  }
  Nn.xyDistanceBetweenPoints = wH;
});
var nx = we((tx) => {
  const Or = Ut(), Hn = $2(), Er = vp(), Dr = ex(), bH = 468, xH = 13, LH = [xH, Er.MESH_ANNOTATIONS.midwayBetweenEyes[0]], SH = 3, IH = 2, AH = [SH, IH], xp = Er.MESH_ANNOTATIONS.leftEyeLower0, Lp = [xp[0], xp[xp.length - 1]], Sp = Er.MESH_ANNOTATIONS.rightEyeLower0, Ip = [Sp[0], Sp[Sp.length - 1]], TH = 3, NH = 4, _H = 71, Ap = 76;
  function oc(n, t, e, r) {
    for (let i = 0; i < Er.MESH_TO_IRIS_INDICES_MAP.length; i++) {
      const {key: a, indices: s} = Er.MESH_TO_IRIS_INDICES_MAP[i], o = Er.MESH_ANNOTATIONS[`${e}${a}`], c = r == null;
      if (c || r.includes(a))
        for (let l = 0; l < s.length; l++) {
          const u = s[l];
          n[o[l]] = [t[u][0], t[u][1], (t[u][2] + n[o[l]][2]) / 2];
        }
    }
  }
  class CH {
    constructor(n, t, e, r) {
      this.storedBoxes = [], this.runsWithoutFaceDetector = 0, this.boundingBoxDetector = n, this.meshDetector = t, this.irisModel = e, this.meshWidth = r.mesh.inputSize, this.meshHeight = r.mesh.inputSize, this.irisSize = r.iris.inputSize, this.irisEnlarge = 2.3, this.skipped = 1e3, this.detectedFaces = 0;
    }
    transformRawCoords(n, t, e, r) {
      const i = Hn.getBoxSize({startPoint: t.startPoint, endPoint: t.endPoint}), a = [i[0] / this.meshWidth, i[1] / this.meshHeight], s = n.map((d) => [a[0] * (d[0] - this.meshWidth / 2), a[1] * (d[1] - this.meshHeight / 2), d[2]]), o = Dr.buildRotationMatrix(e, [0, 0]), c = s.map((d) => [...Dr.rotatePoint(d, o), d[2]]), l = Dr.invertTransformMatrix(r), u = [...Hn.getBoxCenter({startPoint: t.startPoint, endPoint: t.endPoint}), 1], h = [Dr.dot(u, l[0]), Dr.dot(u, l[1])];
      return c.map((d) => [d[0] + h[0], d[1] + h[1], d[2]]);
    }
    getLeftToRightEyeDepthDifference(n) {
      const t = n[Lp[0]][2], e = n[Ip[0]][2];
      return t - e;
    }
    getEyeBox(n, t, e, r, i = false) {
      const a = Hn.squarifyBox(Hn.enlargeBox(this.calculateLandmarksBoundingBox([n[e], n[r]]), this.irisEnlarge)), s = Hn.getBoxSize(a);
      let o = Or.image.cropAndResize(t, [[a.startPoint[1] / this.meshHeight, a.startPoint[0] / this.meshWidth, a.endPoint[1] / this.meshHeight, a.endPoint[0] / this.meshWidth]], [0], [this.irisSize, this.irisSize]);
      return i && (o = Or.image.flipLeftRight(o)), {box: a, boxSize: s, crop: o};
    }
    getEyeCoords(n, t, e, r = false) {
      const i = [];
      for (let a = 0; a < Ap; a++) {
        const s = n[a * 3], o = n[a * 3 + 1], c = n[a * 3 + 2];
        i.push([(r ? 1 - s / this.irisSize : s / this.irisSize) * e[0] + t.startPoint[0], o / this.irisSize * e[1] + t.startPoint[1], c]);
      }
      return {rawCoords: i, iris: i.slice(_H)};
    }
    getAdjustedIrisCoords(n, t, e) {
      const r = n[Er.MESH_ANNOTATIONS[`${e}EyeUpper0`][TH]][2], i = n[Er.MESH_ANNOTATIONS[`${e}EyeLower0`][NH]][2], a = (r + i) / 2;
      return t.map((s, o) => {
        let c = a;
        return o === 2 ? c = r : o === 4 && (c = i), [s[0], s[1], c];
      });
    }
    async predict(n, t) {
      this.skipped++;
      let e = false, r;
      if ((this.skipped > t.detector.skipFrames || !t.mesh.enabled) && (r = await this.boundingBoxDetector.getBoundingBoxes(n), n.shape[1] !== 255 && n.shape[2] !== 255 && (this.skipped = 0)), r && r.boxes && r.boxes.length > 0 && (!t.mesh.enabled || r.boxes.length !== this.detectedFaces && this.detectedFaces !== t.detector.maxFaces)) {
        this.storedBoxes = [], this.detectedFaces = 0;
        for (const a of r.boxes)
          this.storedBoxes.push({startPoint: a.box.startPoint.dataSync(), endPoint: a.box.endPoint.dataSync(), landmarks: a.landmarks, confidence: a.confidence});
        this.storedBoxes.length > 0 && (e = true);
      }
      if (e) {
        if (!r || !r.boxes || r.boxes.length === 0)
          return this.storedBoxes = [], this.detectedFaces = 0, null;
        for (const a in this.storedBoxes) {
          const s = Hn.scaleBoxCoordinates({startPoint: this.storedBoxes[a].startPoint, endPoint: this.storedBoxes[a].endPoint}, r.scaleFactor), o = Hn.enlargeBox(s), c = this.storedBoxes[a].landmarks.arraySync(), l = this.storedBoxes[a].confidence;
          this.storedBoxes[a] = {...o, confidence: l, landmarks: c};
        }
        this.runsWithoutFaceDetector = 0;
      }
      r && r.boxes && r.boxes.forEach((a) => {
        a.box.startPoint.dispose(), a.box.endPoint.dispose(), a.landmarks.dispose();
      });
      let i = Or.tidy(() => this.storedBoxes.map((a, s) => {
        let o = 0;
        const c = a.landmarks.length >= bH;
        let [l, u] = LH;
        c === false && ([l, u] = AH), o = Dr.computeRotation(a.landmarks[l], a.landmarks[u]);
        const h = Hn.getBoxCenter({startPoint: a.startPoint, endPoint: a.endPoint}), d = [h[0] / n.shape[2], h[1] / n.shape[1]];
        let p = n, f = Dr.IDENTITY_MATRIX;
        o !== 0 && (p = Or.image.rotateWithOffset(n, o, 0, d), f = Dr.buildRotationMatrix(-o, h));
        const m = {startPoint: a.startPoint, endPoint: a.endPoint}, g = Hn.cutBoxFromImageAndResize(m, p, [this.meshHeight, this.meshWidth]).div(255);
        if (!t.mesh.enabled) {
          const D = {coords: null, box: a, faceConfidence: null, confidence: a.confidence, image: g};
          return D;
        }
        const [, y, w] = this.meshDetector.predict(g), b = y.dataSync()[0];
        if (y.dispose(), b < t.detector.minConfidence)
          return w.dispose(), null;
        const L = Or.reshape(w, [-1, 3]);
        let x = L.arraySync();
        if (t.iris.enabled) {
          const {box: D, boxSize: F, crop: k} = this.getEyeBox(x, g, Lp[0], Lp[1], true), {box: B, boxSize: V, crop: P} = this.getEyeBox(x, g, Ip[0], Ip[1]), G = this.irisModel.predict(Or.concat([k, P])), j = G.dataSync();
          G.dispose();
          const q = j.slice(0, Ap * 3), {rawCoords: H, iris: J} = this.getEyeCoords(q, D, F, true), $ = j.slice(Ap * 3), {rawCoords: ee, iris: te} = this.getEyeCoords($, B, V), ne = this.getLeftToRightEyeDepthDifference(x);
          Math.abs(ne) < 30 ? (oc(x, H, "left"), oc(x, ee, "right")) : ne < 1 ? oc(x, H, "left", ["EyeUpper0", "EyeLower0"]) : oc(x, ee, "right", ["EyeUpper0", "EyeLower0"]);
          const re = this.getAdjustedIrisCoords(x, J, "left"), ie = this.getAdjustedIrisCoords(x, te, "right");
          x = x.concat(re).concat(ie);
        }
        const N = this.transformRawCoords(x, a, o, f);
        Or.dispose(x);
        const I = Hn.enlargeBox(this.calculateLandmarksBoundingBox(N)), C = Or.tensor2d(N), O = {coords: C, box: I, faceConfidence: b, confidence: a.confidence, image: g};
        return this.storedBoxes[s] = {...I, landmarks: C.arraySync(), confidence: a.confidence, faceConfidence: b}, O;
      }));
      return i = i.filter((a) => a !== null), this.detectedFaces = i.length, i;
    }
    calculateLandmarksBoundingBox(n) {
      const t = n.map((a) => a[0]), e = n.map((a) => a[1]), r = [Math.min(...t), Math.min(...e)], i = [Math.max(...t), Math.max(...e)];
      return {startPoint: r, endPoint: i, landmarks: n};
    }
  }
  tx.Pipeline = CH;
});
var ix = we((rx) => {
  rx.UV_COORDS = [[0.499976992607117, 0.652534008026123], [0.500025987625122, 0.547487020492554], [0.499974012374878, 0.602371990680695], [0.482113003730774, 0.471979022026062], [0.500150978565216, 0.527155995368958], [0.499909996986389, 0.498252987861633], [0.499523013830185, 0.40106201171875], [0.289712011814117, 0.380764007568359], [0.499954998493195, 0.312398016452789], [0.499987006187439, 0.269918978214264], [0.500023007392883, 0.107050001621246], [0.500023007392883, 0.666234016418457], [0.5000159740448, 0.679224014282227], [0.500023007392883, 0.692348003387451], [0.499976992607117, 0.695277988910675], [0.499976992607117, 0.70593398809433], [0.499976992607117, 0.719385027885437], [0.499976992607117, 0.737019002437592], [0.499967992305756, 0.781370997428894], [0.499816000461578, 0.562981009483337], [0.473773002624512, 0.573909997940063], [0.104906998574734, 0.254140973091125], [0.365929991006851, 0.409575998783112], [0.338757991790771, 0.41302502155304], [0.311120003461838, 0.409460008144379], [0.274657994508743, 0.389131009578705], [0.393361985683441, 0.403706014156342], [0.345234006643295, 0.344011008739471], [0.370094001293182, 0.346076011657715], [0.319321990013123, 0.347265005111694], [0.297903001308441, 0.353591024875641], [0.24779200553894, 0.410809993743896], [0.396889001131058, 0.842755019664764], [0.280097991228104, 0.375599980354309], [0.106310002505779, 0.399955987930298], [0.2099249958992, 0.391353011131287], [0.355807989835739, 0.534406006336212], [0.471751004457474, 0.65040397644043], [0.474155008792877, 0.680191993713379], [0.439785003662109, 0.657229006290436], [0.414617002010345, 0.66654098033905], [0.450374007225037, 0.680860996246338], [0.428770989179611, 0.682690978050232], [0.374971002340317, 0.727805018424988], [0.486716985702515, 0.547628998756409], [0.485300987958908, 0.527395009994507], [0.257764995098114, 0.314490020275116], [0.401223003864288, 0.455172002315521], [0.429818987846375, 0.548614978790283], [0.421351999044418, 0.533740997314453], [0.276895999908447, 0.532056987285614], [0.483370006084442, 0.499586999416351], [0.33721199631691, 0.282882988452911], [0.296391993761063, 0.293242990970612], [0.169294998049736, 0.193813979625702], [0.447580009698868, 0.302609980106354], [0.392390012741089, 0.353887975215912], [0.354490011930466, 0.696784019470215], [0.067304998636246, 0.730105042457581], [0.442739009857178, 0.572826027870178], [0.457098007202148, 0.584792017936707], [0.381974011659622, 0.694710969924927], [0.392388999462128, 0.694203019142151], [0.277076005935669, 0.271932005882263], [0.422551989555359, 0.563233017921448], [0.385919004678726, 0.281364023685455], [0.383103013038635, 0.255840003490448], [0.331431001424789, 0.119714021682739], [0.229923993349075, 0.232002973556519], [0.364500999450684, 0.189113974571228], [0.229622006416321, 0.299540996551514], [0.173287004232407, 0.278747975826263], [0.472878992557526, 0.666198015213013], [0.446828007698059, 0.668527007102966], [0.422762006521225, 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});
var ax = we((RH) => {
  As(RH, {default: () => OH});
  var OH = [127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9, 151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56, 157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91, 181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117, 228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211, 170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173, 155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28, 158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49, 102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89, 90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122, 196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110, 246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246, 117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162, 153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13, 63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214, 135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61, 76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59, 166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56, 190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213, 112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228, 110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347, 348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313, 314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320, 321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258, 466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256, 429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467, 293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436, 427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424, 431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432, 434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330, 348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419, 318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445, 373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355, 340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368, 351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461, 164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391, 327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314, 405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309, 438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254, 449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259, 444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453, 464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133, 243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60, 166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155, 119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17, 77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83, 201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196, 103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47, 217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95, 78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43, 57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203, 142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96, 90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22, 178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38, 224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111, 143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145, 153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70, 63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32, 241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212, 186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2, 141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221, 223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245, 128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267, 451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337, 344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260, 424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406, 321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8, 448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283, 281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325, 283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329, 432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345, 268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299, 6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279, 317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310, 272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337, 336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285, 441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387, 373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330, 425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315, 403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264, 383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339, 254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257, 259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357, 453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];
});
var cx = we((ds) => {
  const Tp = Ut(), EH = j2(), sx = vp(), DH = nx(), kH = ix(), FH = ax().default;
  class ox {
    constructor(n, t, e, r) {
      this.pipeline = new DH.Pipeline(n, t, e, r), r && (this.config = r);
    }
    async estimateFaces(n, t) {
      t && (this.config = t);
      const e = await this.pipeline.predict(n, t), r = [];
      for (const i of e || []) {
        if (i.isDisposedInternal)
          continue;
        const a = i.coords ? i.coords.arraySync() : null, s = {};
        if (a && a.length > 0)
          for (const o in sx.MESH_ANNOTATIONS)
            (this.config.iris.enabled || o.includes("Iris") === false) && (s[o] = sx.MESH_ANNOTATIONS[o].map((c) => a[c]));
        r.push({confidence: i.confidence || 0, box: i.box ? [i.box.startPoint[0], i.box.startPoint[1], i.box.endPoint[0] - i.box.startPoint[0], i.box.endPoint[1] - i.box.startPoint[1]] : 0, mesh: a, annotations: s, image: i.image ? Tp.clone(i.image) : null}), i.coords && i.coords.dispose(), i.image && i.image.dispose();
      }
      return r;
    }
  }
  async function WH(n) {
    const t = await Promise.all([EH.load(n), Tp.loadGraphModel(n.mesh.modelPath, {fromTFHub: n.mesh.modelPath.includes("tfhub.dev")}), Tp.loadGraphModel(n.iris.modelPath, {fromTFHub: n.iris.modelPath.includes("tfhub.dev")})]), e = new ox(t[0], t[1], t[2], n);
    return console.log(`Human: load model: ${n.mesh.modelPath.match(/\/(.*)\./)[1]}`), console.log(`Human: load model: ${n.iris.modelPath.match(/\/(.*)\./)[1]}`), e;
  }
  ds.load = WH;
  ds.MediaPipeFaceMesh = ox;
  ds.uv_coords = kH;
  ds.triangulation = FH;
});
var ps = we((lx) => {
  const UH = {};
  function BH(n, t) {
    if (!t || !t.kernels)
      return;
    const e = 5, r = t.kernels.filter((o) => o.kernelTimeMs > 0).reduce((o, c) => o += c.kernelTimeMs, 0), i = t.kernels.map((o, c) => (o.id = c, o)).filter((o) => o.kernelTimeMs > 0).sort((o, c) => c.kernelTimeMs - o.kernelTimeMs), a = t.kernels.map((o, c) => (o.id = c, o)).filter((o) => o.totalBytesSnapshot > 0).sort((o, c) => c.totalBytesSnapshot - o.totalBytesSnapshot);
    i.length > e && (i.length = e), a.length > e && (a.length = e);
    const s = {newBytes: t.newBytes, newTensors: t.newTensors, peakBytes: t.peakBytes, numKernelOps: t.kernels.length, timeKernelOps: r, slowestKernelOps: i, largestKernelOps: a};
    UH[n] = s, console.log("Human profiler", n, s);
  }
  lx.run = BH;
});
var ux = we((Np) => {
  const fs = Ut(), zH = ps(), ms = {};
  let cc = {age: 0}, _p = Number.MAX_SAFE_INTEGER;
  const lc = [0, 0];
  async function PH(n) {
    return ms.age || (ms.age = await fs.loadGraphModel(n.face.age.modelPath), console.log(`Human: load model: ${n.face.age.modelPath.match(/\/(.*)\./)[1]}`)), ms.age;
  }
  async function MH(n, t) {
    return _p < t.face.age.skipFrames && cc.age && cc.age > 0 ? (_p += 1, cc) : (_p = 0, new Promise(async (e) => {
      const r = [[n.shape[1] * lc[0] / n.shape[1], n.shape[2] * lc[1] / n.shape[2], (n.shape[1] - n.shape[1] * lc[0]) / n.shape[1], (n.shape[2] - n.shape[2] * lc[1]) / n.shape[2]]], i = fs.image.cropAndResize(n, r, [0], [t.face.age.inputSize, t.face.age.inputSize]), a = fs.mul(i, [255]);
      fs.dispose(i);
      let s;
      const o = {};
      if (!t.profile)
        t.face.age.enabled && (s = await ms.age.predict(a));
      else {
        const c = t.face.age.enabled ? await fs.profile(() => ms.age.predict(a)) : {};
        s = c.result.clone(), c.result.dispose(), zH.run("age", c);
      }
      if (a.dispose(), s) {
        const c = s.dataSync();
        o.age = Math.trunc(10 * c[0]) / 10;
      }
      s.dispose(), cc = o, e(o);
    }));
  }
  Np.predict = MH;
  Np.load = PH;
});
var hx = we((Cp) => {
  const _n = Ut(), HH = ps(), da = {};
  let Rp = {gender: ""}, Op = Number.MAX_SAFE_INTEGER, Ep = false;
  const uc = [0, 0], Dp = [0.2989, 0.587, 0.114];
  async function VH(n) {
    return da.gender || (da.gender = await _n.loadGraphModel(n.face.gender.modelPath), Ep = da.gender.inputs[0].shape[3] === 1, console.log(`Human: load model: ${n.face.gender.modelPath.match(/\/(.*)\./)[1]}`)), da.gender;
  }
  async function GH(n, t) {
    return Op < t.face.gender.skipFrames && Rp.gender !== "" ? (Op += 1, Rp) : (Op = 0, new Promise(async (e) => {
      const r = [[n.shape[1] * uc[0] / n.shape[1], n.shape[2] * uc[1] / n.shape[2], (n.shape[1] - n.shape[1] * uc[0]) / n.shape[1], (n.shape[2] - n.shape[2] * uc[1]) / n.shape[2]]], i = _n.image.cropAndResize(n, r, [0], [t.face.gender.inputSize, t.face.gender.inputSize]);
      let a;
      Ep ? a = _n.tidy(() => {
        const [c, l, u] = _n.split(i, 3, 3), h = _n.mul(c, Dp[0]), d = _n.mul(l, Dp[1]), p = _n.mul(u, Dp[2]), f = _n.addN([h, d, p]);
        return f.sub(0.5).mul(2);
      }) : a = _n.mul(i, [255]), _n.dispose(i);
      let s;
      const o = {};
      if (!t.profile)
        t.face.gender.enabled && (s = await da.gender.predict(a));
      else {
        const c = t.face.gender.enabled ? await _n.profile(() => da.gender.predict(a)) : {};
        s = c.result.clone(), c.result.dispose(), HH.run("gender", c);
      }
      if (a.dispose(), s) {
        const c = s.dataSync();
        if (Ep) {
          const l = Math.trunc(100 * Math.abs(c[0] - c[1])) / 100;
          l > t.face.gender.minConfidence && (o.gender = c[0] > c[1] ? "female" : "male", o.confidence = l);
        } else {
          const l = Math.trunc(200 * Math.abs(c[0] - 0.5)) / 100;
          l > t.face.gender.minConfidence && (o.gender = c[0] <= 0.5 ? "female" : "male", o.confidence = l);
        }
      }
      s.dispose(), Rp = o, e(o);
    }));
  }
  Cp.predict = GH;
  Cp.load = VH;
});
var px = we((kp) => {
  const Vn = Ut(), qH = ps(), YH = ["angry", "disgust", "fear", "happy", "sad", "surpise", "neutral"], gs = {};
  let Fp = [], Wp = Number.MAX_SAFE_INTEGER;
  const hc = [0, 0], Up = [0.2989, 0.587, 0.114], dx = 1;
  async function KH(n) {
    return gs.emotion || (gs.emotion = await Vn.loadGraphModel(n.face.emotion.modelPath), console.log(`Human: load model: ${n.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)), gs.emotion;
  }
  async function jH(n, t) {
    return Wp < t.face.emotion.skipFrames && Fp.length > 0 ? (Wp += 1, Fp) : (Wp = 0, new Promise(async (e) => {
      const r = [[n.shape[1] * hc[0] / n.shape[1], n.shape[2] * hc[1] / n.shape[2], (n.shape[1] - n.shape[1] * hc[0]) / n.shape[1], (n.shape[2] - n.shape[2] * hc[1]) / n.shape[2]]], i = Vn.image.cropAndResize(n, r, [0], [t.face.emotion.inputSize, t.face.emotion.inputSize]), [a, s, o] = Vn.split(i, 3, 3);
      i.dispose();
      const c = Vn.mul(a, Up[0]), l = Vn.mul(s, Up[1]), u = Vn.mul(o, Up[2]);
      a.dispose(), s.dispose(), o.dispose();
      const h = Vn.addN([c, l, u]);
      c.dispose(), l.dispose(), u.dispose();
      const d = Vn.tidy(() => h.sub(0.5).mul(2));
      h.dispose();
      const p = [];
      if (t.face.emotion.enabled) {
        let f;
        if (t.profile) {
          const m = await Vn.profile(() => gs.emotion.predict(d));
          f = m.result.dataSync(), m.result.dispose(), qH.run("emotion", m);
        } else {
          const m = await gs.emotion.predict(d);
          f = m.dataSync(), Vn.dispose(m);
        }
        for (let m = 0; m < f.length; m++)
          dx * f[m] > t.face.emotion.minConfidence && p.push({score: Math.min(0.99, Math.trunc(100 * dx * f[m]) / 100), emotion: YH[m]});
        p.sort((m, g) => g.score - m.score);
      }
      d.dispose(), Fp = p, e(p);
    }));
  }
  kp.predict = jH;
  kp.load = KH;
});
var mx = we((fx) => {
  const $H = Ut();
  class XH {
    constructor(n, t) {
      this.model = n, this.outputStride = t;
    }
    predict(n) {
      return $H.tidy(() => {
        const t = this.preprocessInput(n.toFloat()), e = t.expandDims(0), r = this.model.predict(e), i = r.map((s) => s.squeeze([0])), a = this.nameOutputResults(i);
        return {heatmapScores: a.heatmap.sigmoid(), offsets: a.offsets, displacementFwd: a.displacementFwd, displacementBwd: a.displacementBwd};
      });
    }
    dispose() {
      this.model.dispose();
    }
  }
  fx.BaseModel = XH;
});
var Bp = we((gx) => {
  const yx = Ut(), JH = mx();
  class ZH extends JH.BaseModel {
    preprocessInput(n) {
      return yx.tidy(() => yx.div(n, 127.5).sub(1));
    }
    nameOutputResults(n) {
      const [t, e, r, i] = n;
      return {offsets: t, heatmap: e, displacementFwd: r, displacementBwd: i};
    }
  }
  gx.MobileNet = ZH;
});
var wx = we((vx) => {
  function zp(n) {
    return Math.floor(n / 2);
  }
  class QH {
    constructor(n, t) {
      this.priorityQueue = new Array(n), this.numberOfElements = -1, this.getElementValue = t;
    }
    enqueue(n) {
      this.priorityQueue[++this.numberOfElements] = n, this.swim(this.numberOfElements);
    }
    dequeue() {
      const n = this.priorityQueue[0];
      return this.exchange(0, this.numberOfElements--), this.sink(0), this.priorityQueue[this.numberOfElements + 1] = null, n;
    }
    empty() {
      return this.numberOfElements === -1;
    }
    size() {
      return this.numberOfElements + 1;
    }
    all() {
      return this.priorityQueue.slice(0, this.numberOfElements + 1);
    }
    max() {
      return this.priorityQueue[0];
    }
    swim(n) {
      for (; n > 0 && this.less(zp(n), n); )
        this.exchange(n, zp(n)), n = zp(n);
    }
    sink(n) {
      for (; 2 * n <= this.numberOfElements; ) {
        let t = 2 * n;
        if (t < this.numberOfElements && this.less(t, t + 1) && t++, !this.less(n, t))
          break;
        this.exchange(n, t), n = t;
      }
    }
    getValueAt(n) {
      return this.getElementValue(this.priorityQueue[n]);
    }
    less(n, t) {
      return this.getValueAt(n) < this.getValueAt(t);
    }
    exchange(n, t) {
      const e = this.priorityQueue[n];
      this.priorityQueue[n] = this.priorityQueue[t], this.priorityQueue[t] = e;
    }
  }
  vx.MaxHeap = QH;
});
var xx = we((bx) => {
  const eV = wx();
  function tV(n, t, e, r, i, a) {
    const [s, o] = a.shape;
    let c = true;
    const l = Math.max(e - i, 0), u = Math.min(e + i + 1, s);
    for (let h = l; h < u; ++h) {
      const d = Math.max(r - i, 0), p = Math.min(r + i + 1, o);
      for (let f = d; f < p; ++f)
        if (a.get(h, f, n) > t) {
          c = false;
          break;
        }
      if (!c)
        break;
    }
    return c;
  }
  function nV(n, t, e) {
    const [r, i, a] = e.shape, s = new eV.MaxHeap(r * i * a, ({score: o}) => o);
    for (let o = 0; o < r; ++o)
      for (let c = 0; c < i; ++c)
        for (let l = 0; l < a; ++l) {
          const u = e.get(o, c, l);
          if (u < n)
            continue;
          tV(l, u, o, c, t, e) && s.enqueue({score: u, part: {heatmapY: o, heatmapX: c, id: l}});
        }
    return s;
  }
  bx.buildPartWithScoreQueue = nV;
});
var ys = we((Cn) => {
  Cn.partNames = ["nose", "leftEye", "rightEye", "leftEar", "rightEar", "leftShoulder", "rightShoulder", "leftElbow", "rightElbow", "leftWrist", "rightWrist", "leftHip", "rightHip", "leftKnee", "rightKnee", "leftAnkle", "rightAnkle"];
  Cn.NUM_KEYPOINTS = Cn.partNames.length;
  Cn.partIds = Cn.partNames.reduce((n, t, e) => (n[t] = e, n), {});
  const rV = [["leftHip", "leftShoulder"], ["leftElbow", "leftShoulder"], ["leftElbow", "leftWrist"], ["leftHip", "leftKnee"], ["leftKnee", "leftAnkle"], ["rightHip", "rightShoulder"], ["rightElbow", "rightShoulder"], ["rightElbow", "rightWrist"], ["rightHip", "rightKnee"], ["rightKnee", "rightAnkle"], ["leftShoulder", "rightShoulder"], ["leftHip", "rightHip"]];
  Cn.poseChain = [["nose", "leftEye"], ["leftEye", "leftEar"], ["nose", "rightEye"], ["rightEye", "rightEar"], ["nose", "leftShoulder"], ["leftShoulder", "leftElbow"], ["leftElbow", "leftWrist"], ["leftShoulder", "leftHip"], ["leftHip", "leftKnee"], ["leftKnee", "leftAnkle"], ["nose", "rightShoulder"], ["rightShoulder", "rightElbow"], ["rightElbow", "rightWrist"], ["rightShoulder", "rightHip"], ["rightHip", "rightKnee"], ["rightKnee", "rightAnkle"]];
  Cn.connectedPartIndices = rV.map(([n, t]) => [Cn.partIds[n], Cn.partIds[t]]);
  Cn.partChannels = ["left_face", "right_face", "right_upper_leg_front", "right_lower_leg_back", "right_upper_leg_back", "left_lower_leg_front", "left_upper_leg_front", "left_upper_leg_back", "left_lower_leg_back", "right_feet", "right_lower_leg_front", "left_feet", "torso_front", "torso_back", "right_upper_arm_front", "right_upper_arm_back", "right_lower_arm_back", "left_lower_arm_front", "left_upper_arm_front", "left_upper_arm_back", "left_lower_arm_back", "right_hand", "right_lower_arm_front", "left_hand"];
});
var Mp = we((kr) => {
  const iV = ys();
  function Lx(n, t, e, r) {
    return {y: r.get(n, t, e), x: r.get(n, t, e + iV.NUM_KEYPOINTS)};
  }
  kr.getOffsetPoint = Lx;
  function aV(n, t, e) {
    const {heatmapY: r, heatmapX: i, id: a} = n, {y: s, x: o} = Lx(r, i, a, e);
    return {x: n.heatmapX * t + o, y: n.heatmapY * t + s};
  }
  kr.getImageCoords = aV;
  function sV(n, t) {
    const e = new Array(t);
    for (let r = 0; r < t; r++)
      e[r] = n;
    return e;
  }
  kr.fillArray = sV;
  function Pp(n, t, e) {
    return n < t ? t : n > e ? e : n;
  }
  kr.clamp = Pp;
  function oV(n, t, e, r) {
    const i = e - n, a = r - t;
    return i * i + a * a;
  }
  kr.squaredDistance = oV;
  function cV(n, t) {
    return {x: n.x + t.x, y: n.y + t.y};
  }
  kr.addVectors = cV;
  function lV(n, t, e) {
    return {y: Pp(n.y, t, e), x: Pp(n.x, t, e)};
  }
  kr.clampVector = lV;
});
var Nx = we((Sx) => {
  const vs = ys(), pa = Mp(), Ix = vs.poseChain.map(([n, t]) => [vs.partIds[n], vs.partIds[t]]), Hp = Ix.map(([, n]) => n), Ax = Ix.map(([n]) => n);
  function uV(n, t, e) {
    const r = e.shape[2] / 2;
    return {y: e.get(t.y, t.x, n), x: e.get(t.y, t.x, r + n)};
  }
  function Vp(n, t, e, r) {
    return {y: pa.clamp(Math.round(n.y / t), 0, e - 1), x: pa.clamp(Math.round(n.x / t), 0, r - 1)};
  }
  function Tx(n, t, e, r, i, a, s, o = 2) {
    const [c, l] = r.shape, u = Vp(t.position, a, c, l), h = uV(n, u, s), d = pa.addVectors(t.position, h);
    let p = d;
    for (let g = 0; g < o; g++) {
      const y = Vp(p, a, c, l), w = pa.getOffsetPoint(y.y, y.x, e, i);
      p = pa.addVectors({x: y.x * a, y: y.y * a}, {x: w.x, y: w.y});
    }
    const f = Vp(p, a, c, l), m = r.get(f.y, f.x, e);
    return {position: p, part: vs.partNames[e], score: m};
  }
  function hV(n, t, e, r, i, a) {
    const s = t.shape[2], o = Hp.length, c = new Array(s), {part: l, score: u} = n, h = pa.getImageCoords(l, r, e);
    c[l.id] = {score: u, part: vs.partNames[l.id], position: h};
    for (let d = o - 1; d >= 0; --d) {
      const p = Hp[d], f = Ax[d];
      c[p] && !c[f] && (c[f] = Tx(d, c[p], f, t, e, r, a));
    }
    for (let d = 0; d < o; ++d) {
      const p = Ax[d], f = Hp[d];
      c[p] && !c[f] && (c[f] = Tx(d, c[p], f, t, e, r, i));
    }
    return c;
  }
  Sx.decodePose = hV;
});
var Gp = we((_x) => {
  const dV = xx(), pV = Nx(), Cx = Mp();
  function Rx(n, t, {x: e, y: r}, i) {
    return n.some(({keypoints: a}) => {
      const s = a[i].position;
      return Cx.squaredDistance(r, e, s.y, s.x) <= t;
    });
  }
  function fV(n, t, e) {
    const r = e.reduce((i, {position: a, score: s}, o) => (Rx(n, t, a, o) || (i += s), i), 0);
    return r / e.length;
  }
  const mV = 1;
  function gV(n, t, e, r, i, a, s = 0.5, o = 20) {
    const c = [], l = dV.buildPartWithScoreQueue(s, mV, n), u = o * o;
    for (; c.length < a && !l.empty(); ) {
      const h = l.dequeue(), d = Cx.getImageCoords(h.part, i, t);
      if (Rx(c, u, d, h.part.id))
        continue;
      const p = pV.decodePose(h, n, t, i, e, r), f = fV(c, u, p);
      c.push({keypoints: p, score: f});
    }
    return c;
  }
  _x.decodeMultiplePoses = gV;
});
var qp = we((Fr) => {
  const yV = ys();
  function vV(n, t, e) {
    return n < e || t < e;
  }
  function wV(n, t) {
    return yV.connectedPartIndices.reduce((e, [r, i]) => (vV(n[r].score, n[i].score, t) || e.push([n[r], n[i]]), e), []);
  }
  Fr.getAdjacentKeyPoints = wV;
  const {NEGATIVE_INFINITY: Ox, POSITIVE_INFINITY: Ex} = Number;
  function Dx(n) {
    return n.reduce(({maxX: t, maxY: e, minX: r, minY: i}, {position: {x: a, y: s}}) => ({maxX: Math.max(t, a), maxY: Math.max(e, s), minX: Math.min(r, a), minY: Math.min(i, s)}), {maxX: Ox, maxY: Ox, minX: Ex, minY: Ex});
  }
  Fr.getBoundingBox = Dx;
  function bV(n) {
    const {minX: t, minY: e, maxX: r, maxY: i} = Dx(n);
    return [{x: t, y: e}, {x: r, y: e}, {x: r, y: i}, {x: t, y: i}];
  }
  Fr.getBoundingBoxPoints = bV;
  async function xV(n) {
    return Promise.all(n.map((t) => t.buffer()));
  }
  Fr.toTensorBuffers3D = xV;
  function kx(n, t, e) {
    return {score: n.score, keypoints: n.keypoints.map(({score: r, part: i, position: a}) => ({score: r, part: i, position: {x: a.x * e, y: a.y * t}}))};
  }
  Fr.scalePose = kx;
  function LV(n, [t, e]) {
    const r = n.squeeze(0), i = r.resizeBilinear([t, e]);
    return r.dispose(), i;
  }
  Fr.resizeTo = LV;
  function SV(n, [t, e], [r, i]) {
    const a = n.map((s) => kx(s, t / r, e / i));
    return a;
  }
  Fr.scaleAndFlipPoses = SV;
});
var Wx = we((Yp) => {
  const IV = Ut(), AV = Bp(), TV = Gp(), Kp = qp();
  class Fx {
    constructor(n) {
      this.baseModel = n, this.outputStride = 16;
    }
    async estimatePoses(n, t) {
      return new Promise(async (e) => {
        const r = n.shape[1], i = n.shape[2], a = Kp.resizeTo(n, [t.body.inputSize, t.body.inputSize]), s = this.baseModel.predict(a), o = await Kp.toTensorBuffers3D([s.heatmapScores, s.offsets, s.displacementFwd, s.displacementBwd]), c = o[0], l = o[1], u = o[2], h = o[3], d = await TV.decodeMultiplePoses(c, l, u, h, this.outputStride, t.body.maxDetections, t.body.scoreThreshold, t.body.nmsRadius), p = Kp.scaleAndFlipPoses(d, [r, i], [t.body.inputSize, t.body.inputSize]);
        s.heatmapScores.dispose(), s.offsets.dispose(), s.displacementFwd.dispose(), s.displacementBwd.dispose(), a.dispose(), e(p);
      });
    }
    dispose() {
      this.baseModel.dispose();
    }
  }
  Yp.PoseNet = Fx;
  async function NV(n) {
    const t = await IV.loadGraphModel(n.body.modelPath), e = new AV.MobileNet(t, this.outputStride);
    return console.log(`Human: load model: ${n.body.modelPath.match(/\/(.*)\./)[1]}`), new Fx(e);
  }
  Yp.load = NV;
});
var Bx = we((tn) => {
  const _V = Bp(), Ux = Wx(), CV = Gp(), dc = ys(), ws = qp();
  tn.load = Ux.load;
  tn.PoseNet = Ux.PoseNet;
  tn.MobileNet = _V.MobileNet;
  tn.decodeMultiplePoses = CV.decodeMultiplePoses;
  tn.partChannels = dc.partChannels;
  tn.partIds = dc.partIds;
  tn.partNames = dc.partNames;
  tn.poseChain = dc.poseChain;
  tn.getAdjacentKeyPoints = ws.getAdjacentKeyPoints;
  tn.getBoundingBox = ws.getBoundingBox;
  tn.getBoundingBoxPoints = ws.getBoundingBoxPoints;
  tn.scaleAndFlipPoses = ws.scaleAndFlipPoses;
  tn.scalePose = ws.scalePose;
});
var Xp = we((RV) => {
  As(RV, {cutBoxFromImageAndResize: () => EV, enlargeBox: () => kV, getBoxCenter: () => $p, getBoxSize: () => jp, scaleBoxCoordinates: () => DV, shiftBox: () => WV, squarifyBox: () => FV});
  const OV = Ut();
  function jp(n) {
    return [Math.abs(n.endPoint[0] - n.startPoint[0]), Math.abs(n.endPoint[1] - n.startPoint[1])];
  }
  function $p(n) {
    return [n.startPoint[0] + (n.endPoint[0] - n.startPoint[0]) / 2, n.startPoint[1] + (n.endPoint[1] - n.startPoint[1]) / 2];
  }
  function EV(n, t, e) {
    const r = t.shape[1], i = t.shape[2], a = [[n.startPoint[1] / r, n.startPoint[0] / i, n.endPoint[1] / r, n.endPoint[0] / i]];
    return OV.image.cropAndResize(t, a, [0], e);
  }
  function DV(n, t) {
    const e = [n.startPoint[0] * t[0], n.startPoint[1] * t[1]], r = [n.endPoint[0] * t[0], n.endPoint[1] * t[1]], i = n.palmLandmarks.map((a) => {
      const s = [a[0] * t[0], a[1] * t[1]];
      return s;
    });
    return {startPoint: e, endPoint: r, palmLandmarks: i, confidence: n.confidence};
  }
  function kV(n, t = 1.5) {
    const e = $p(n), r = jp(n), i = [t * r[0] / 2, t * r[1] / 2], a = [e[0] - i[0], e[1] - i[1]], s = [e[0] + i[0], e[1] + i[1]];
    return {startPoint: a, endPoint: s, palmLandmarks: n.palmLandmarks};
  }
  function FV(n) {
    const t = $p(n), e = jp(n), r = Math.max(...e), i = r / 2, a = [t[0] - i, t[1] - i], s = [t[0] + i, t[1] + i];
    return {startPoint: a, endPoint: s, palmLandmarks: n.palmLandmarks};
  }
  function WV(n, t) {
    const e = [n.endPoint[0] - n.startPoint[0], n.endPoint[1] - n.startPoint[1]], r = [e[0] * t[0], e[1] * t[1]], i = [n.startPoint[0] + r[0], n.startPoint[1] + r[1]], a = [n.endPoint[0] + r[0], n.endPoint[1] + r[1]];
    return {startPoint: i, endPoint: a, palmLandmarks: n.palmLandmarks};
  }
});
var Px = we((zx) => {
  const et = Ut(), UV = Xp();
  class BV {
    constructor(n, t, e) {
      this.model = n, this.anchors = e.map((r) => [r.x_center, r.y_center]), this.anchorsTensor = et.tensor2d(this.anchors), this.inputSizeTensor = et.tensor1d([t, t]), this.doubleInputSizeTensor = et.tensor1d([t * 2, t * 2]);
    }
    normalizeBoxes(n) {
      return et.tidy(() => {
        const t = et.slice(n, [0, 0], [-1, 2]), e = et.slice(n, [0, 2], [-1, 2]), r = et.add(et.div(t, this.inputSizeTensor), this.anchorsTensor), i = et.div(e, this.doubleInputSizeTensor), a = et.mul(et.sub(r, i), this.inputSizeTensor), s = et.mul(et.add(r, i), this.inputSizeTensor);
        return et.concat2d([a, s], 1);
      });
    }
    normalizeLandmarks(n, t) {
      return et.tidy(() => {
        const e = et.add(et.div(n.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[t]);
        return et.mul(e, this.inputSizeTensor);
      });
    }
    async getBoxes(n, t) {
      const e = this.model.predict(n), r = e.squeeze();
      e.dispose();
      const i = et.tidy(() => et.sigmoid(et.slice(r, [0, 0], [-1, 1])).squeeze()), a = i.dataSync(), s = et.slice(r, [0, 1], [-1, 4]), o = this.normalizeBoxes(s);
      s.dispose();
      const c = await et.image.nonMaxSuppressionAsync(o, i, t.maxHands, t.iouThreshold, t.scoreThreshold), l = c.arraySync();
      i.dispose(), c.dispose();
      const u = [];
      for (const h of l)
        if (a[h] >= t.minConfidence) {
          const d = et.slice(o, [h, 0], [1, -1]), p = et.slice(r, [h, 5], [1, 14]), f = et.tidy(() => this.normalizeLandmarks(p, h).reshape([-1, 2]));
          p.dispose(), u.push({box: d, palmLandmarks: f, confidence: a[h]});
        }
      return r.dispose(), o.dispose(), u;
    }
    async estimateHandBounds(n, t) {
      const e = n.shape[1], r = n.shape[2], i = et.tidy(() => n.resizeBilinear([t.inputSize, t.inputSize]).div(127.5).sub(1)), a = await this.getBoxes(i, t);
      if (i.dispose(), !a || a.length === 0)
        return null;
      const s = [];
      for (const o of a) {
        const c = o.box.dataSync(), l = c.slice(0, 2), u = c.slice(2, 4), h = o.palmLandmarks.arraySync();
        o.box.dispose(), o.palmLandmarks.dispose(), s.push(UV.scaleBoxCoordinates({startPoint: l, endPoint: u, palmLandmarks: h, confidence: o.confidence}, [r / t.inputSize, e / t.inputSize]));
      }
      return s;
    }
  }
  zx.HandDetector = BV;
});
var qx = we((zV) => {
  As(zV, {buildRotationMatrix: () => MV, computeRotation: () => PV, dot: () => fa, getColumnFrom2DArr: () => Vx, invertTransformMatrix: () => HV, normalizeRadians: () => Mx, rotatePoint: () => VV});
  function Mx(n) {
    return n - 2 * Math.PI * Math.floor((n + Math.PI) / (2 * Math.PI));
  }
  function PV(n, t) {
    const e = Math.PI / 2 - Math.atan2(-(t[1] - n[1]), t[0] - n[0]);
    return Mx(e);
  }
  const Hx = (n, t) => [[1, 0, n], [0, 1, t], [0, 0, 1]];
  function fa(n, t) {
    let e = 0;
    for (let r = 0; r < n.length; r++)
      e += n[r] * t[r];
    return e;
  }
  function Vx(n, t) {
    const e = [];
    for (let r = 0; r < n.length; r++)
      e.push(n[r][t]);
    return e;
  }
  function Gx(n, t) {
    const e = [], r = n.length;
    for (let i = 0; i < r; i++) {
      e.push([]);
      for (let a = 0; a < r; a++)
        e[i].push(fa(n[i], Vx(t, a)));
    }
    return e;
  }
  function MV(n, t) {
    const e = Math.cos(n), r = Math.sin(n), i = [[e, -r, 0], [r, e, 0], [0, 0, 1]], a = Hx(t[0], t[1]), s = Gx(a, i), o = Hx(-t[0], -t[1]);
    return Gx(s, o);
  }
  function HV(n) {
    const t = [[n[0][0], n[1][0]], [n[0][1], n[1][1]]], e = [n[0][2], n[1][2]], r = [-fa(t[0], e), -fa(t[1], e)];
    return [t[0].concat(r[0]), t[1].concat(r[1]), [0, 0, 1]];
  }
  function VV(n, t) {
    return [fa(n, t[0]), fa(n, t[1])];
  }
});
var Jx = we((Yx) => {
  const Kx = Ut(), un = Xp(), Wr = qx(), GV = [0, -0.4], qV = 3, jx = [0, -0.1], $x = 1.65, Xx = [0, 5, 9, 13, 17, 1, 2], YV = 0, KV = 2;
  class jV {
    constructor(n, t, e) {
      this.boxDetector = n, this.meshDetector = t, this.inputSize = e, this.storedBoxes = [], this.skipped = 1e3, this.detectedHands = 0;
    }
    getBoxForPalmLandmarks(n, t) {
      const e = n.map((i) => {
        const a = [...i, 1];
        return Wr.rotatePoint(a, t);
      }), r = this.calculateLandmarksBoundingBox(e);
      return un.enlargeBox(un.squarifyBox(un.shiftBox(r, GV)), qV);
    }
    getBoxForHandLandmarks(n) {
      const t = this.calculateLandmarksBoundingBox(n), e = un.enlargeBox(un.squarifyBox(un.shiftBox(t, jx)), $x), r = [];
      for (let i = 0; i < Xx.length; i++)
        r.push(n[Xx[i]].slice(0, 2));
      return e.palmLandmarks = r, e;
    }
    transformRawCoords(n, t, e, r) {
      const i = un.getBoxSize(t), a = [i[0] / this.inputSize, i[1] / this.inputSize], s = n.map((d) => [a[0] * (d[0] - this.inputSize / 2), a[1] * (d[1] - this.inputSize / 2), d[2]]), o = Wr.buildRotationMatrix(e, [0, 0]), c = s.map((d) => {
        const p = Wr.rotatePoint(d, o);
        return [...p, d[2]];
      }), l = Wr.invertTransformMatrix(r), u = [...un.getBoxCenter(t), 1], h = [Wr.dot(u, l[0]), Wr.dot(u, l[1])];
      return c.map((d) => [d[0] + h[0], d[1] + h[1], d[2]]);
    }
    async estimateHands(n, t) {
      this.skipped++;
      let e = false, r;
      if ((this.skipped > t.skipFrames || !t.landmarks) && (r = await this.boxDetector.estimateHandBounds(n, t), n.shape[1] !== 255 && n.shape[2] !== 255 && (this.skipped = 0)), r && r.length > 0 && (r.length !== this.detectedHands && this.detectedHands !== t.maxHands || !t.landmarks)) {
        this.storedBoxes = [], this.detectedHands = 0;
        for (const a of r)
          this.storedBoxes.push(a);
        this.storedBoxes.length > 0 && (e = true);
      }
      const i = [];
      for (const a in this.storedBoxes) {
        const s = this.storedBoxes[a];
        if (!s)
          continue;
        if (t.landmarks) {
          const o = Wr.computeRotation(s.palmLandmarks[YV], s.palmLandmarks[KV]), c = un.getBoxCenter(s), l = [c[0] / n.shape[2], c[1] / n.shape[1]], u = Kx.image.rotateWithOffset(n, o, 0, l), h = Wr.buildRotationMatrix(-o, c), d = e ? this.getBoxForPalmLandmarks(s.palmLandmarks, h) : s, p = un.cutBoxFromImageAndResize(d, u, [this.inputSize, this.inputSize]), f = p.div(255);
          p.dispose(), u.dispose();
          const [m, g] = await this.meshDetector.predict(f);
          f.dispose();
          const y = m.dataSync()[0];
          if (m.dispose(), y >= t.minConfidence) {
            const w = Kx.reshape(g, [-1, 3]), b = w.arraySync();
            g.dispose(), w.dispose();
            const L = this.transformRawCoords(b, d, o, h), x = this.getBoxForHandLandmarks(L);
            this.storedBoxes[a] = x;
            const N = {landmarks: L, confidence: y, box: {topLeft: x.startPoint, bottomRight: x.endPoint}};
            i.push(N);
          } else
            this.storedBoxes[a] = null;
          g.dispose();
        } else {
          const o = un.enlargeBox(un.squarifyBox(un.shiftBox(s, jx)), $x), c = {confidence: s.confidence, box: {topLeft: o.startPoint, bottomRight: o.endPoint}};
          i.push(c);
        }
      }
      return this.storedBoxes = this.storedBoxes.filter((a) => a !== null), this.detectedHands = i.length, i;
    }
    calculateLandmarksBoundingBox(n) {
      const t = n.map((a) => a[0]), e = n.map((a) => a[1]), r = [Math.min(...t), Math.min(...e)], i = [Math.max(...t), Math.max(...e)];
      return {startPoint: r, endPoint: i};
    }
  }
  Yx.HandPipeline = jV;
});
var Qx = we((Zx) => {
  Zx.anchors = [{w: 1, h: 1, x_center: 0.015625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.015625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.046875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.046875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.078125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.078125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.109375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.109375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.140625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.140625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.171875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.171875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.203125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.203125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.234375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.234375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.265625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.265625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.296875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.296875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.328125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.328125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.359375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.359375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.390625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.390625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.421875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.421875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.453125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.453125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.484375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.484375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.515625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.515625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.546875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.546875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.578125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.578125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.609375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.609375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.640625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.640625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.671875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.671875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.703125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.703125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.734375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.734375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.765625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.765625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.796875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.796875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.828125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.828125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.859375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.859375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.890625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.890625, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.921875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.921875, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.953125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.953125, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.984375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.984375, y_center: 0.015625}, {w: 1, h: 1, x_center: 0.015625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.015625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.046875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.046875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.078125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.078125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.109375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.109375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.140625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.140625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.171875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.171875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.203125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.203125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.234375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.234375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.265625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.265625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.296875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.296875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.328125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.328125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.359375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.359375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.390625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.390625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.421875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.421875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.453125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.453125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.484375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.484375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.515625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.515625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.546875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.546875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.578125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.578125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.609375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.609375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.640625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.640625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.671875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.671875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.703125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.703125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.734375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.734375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.765625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.765625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.796875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.796875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.828125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.828125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.859375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.859375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.890625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.890625, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.921875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.921875, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.953125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.953125, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.984375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.984375, y_center: 0.046875}, {w: 1, h: 1, x_center: 0.015625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.015625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.046875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.046875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.078125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.078125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.109375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.109375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.140625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.140625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.171875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.171875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.203125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.203125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.234375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.234375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.265625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.265625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.296875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.296875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.328125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.328125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.359375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.359375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.390625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.390625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.421875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.421875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.453125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.453125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.484375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.484375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.515625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.515625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.546875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.546875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.578125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.578125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.609375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.609375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.640625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.640625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.671875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.671875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.703125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.703125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.734375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.734375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.765625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.765625, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.796875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.796875, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.828125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.828125, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.859375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.859375, y_center: 0.078125}, {w: 1, h: 1, x_center: 0.890625, 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h: 1, x_center: 0.3125, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.3125, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.4375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.4375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.4375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.4375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.4375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.4375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.5625, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.5625, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.5625, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.5625, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.5625, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.5625, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.6875, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.6875, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.6875, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.6875, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.6875, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.6875, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.8125, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.8125, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.8125, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.8125, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.8125, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.8125, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.9375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.9375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.9375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.9375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.9375, y_center: 0.9375}, {w: 1, h: 1, x_center: 0.9375, y_center: 0.9375}];
});
var nL = we((Jp) => {
  const eL = Ut(), $V = Px(), XV = Jx(), JV = Qx(), Zp = {thumb: [1, 2, 3, 4], indexFinger: [5, 6, 7, 8], middleFinger: [9, 10, 11, 12], ringFinger: [13, 14, 15, 16], pinky: [17, 18, 19, 20], palmBase: [0]};
  class tL {
    constructor(n) {
      this.pipeline = n;
    }
    static getAnnotations() {
      return Zp;
    }
    async estimateHands(n, t) {
      const e = await this.pipeline.estimateHands(n, t);
      if (!e)
        return [];
      const r = [];
      for (const i of e) {
        const a = {};
        if (i.landmarks)
          for (const s of Object.keys(Zp))
            a[s] = Zp[s].map((o) => i.landmarks[o]);
        r.push({confidence: i.confidence, box: i.box ? [i.box.topLeft[0], i.box.topLeft[1], i.box.bottomRight[0] - i.box.topLeft[0], i.box.bottomRight[1] - i.box.topLeft[1]] : 0, landmarks: i.landmarks, annotations: a});
      }
      return r;
    }
  }
  Jp.HandPose = tL;
  async function ZV(n) {
    const [t, e] = await Promise.all([eL.loadGraphModel(n.detector.modelPath, {fromTFHub: n.detector.modelPath.includes("tfhub.dev")}), eL.loadGraphModel(n.skeleton.modelPath, {fromTFHub: n.skeleton.modelPath.includes("tfhub.dev")})]), r = new $V.HandDetector(t, n.inputSize, JV.anchors), i = new XV.HandPipeline(r, e, n.inputSize), a = new tL(i);
    return console.log(`Human: load model: ${n.detector.modelPath.match(/\/(.*)\./)[1]}`), console.log(`Human: load model: ${n.skeleton.modelPath.match(/\/(.*)\./)[1]}`), a;
  }
  Jp.load = ZV;
});
var rL = we((pc) => {
  pc.body = (n) => {
    if (!n)
      return [];
    const t = [];
    for (const e of n) {
      const r = e.keypoints.find((c) => c.part === "leftWrist"), i = e.keypoints.find((c) => c.part === "rightWrist"), a = e.keypoints.find((c) => c.part === "nose");
      a && r && i && r.position.y < a.position.y && i.position.y < a.position.y ? t.push("i give up") : a && r && r.position.y < a.position.y ? t.push("raise left hand") : a && i && i.position.y < a.position.y && t.push("raise right hand");
      const s = e.keypoints.find((c) => c.part === "leftShoulder"), o = e.keypoints.find((c) => c.part === "rightShoulder");
      s && o && t.push(`leaning ${s.position.y > o.position.y ? "left" : "right"}`);
    }
    return t;
  };
  pc.face = (n) => {
    if (!n)
      return [];
    const t = [];
    for (const e of n)
      if (e.mesh && e.mesh.length > 0) {
        const r = e.mesh[35][2] - e.mesh[263][2];
        Math.abs(r) < 10 ? t.push("facing camera") : t.push(`facing ${r < 0 ? "right" : "left"}`);
        const i = Math.abs(e.mesh[374][1] - e.mesh[386][1]) / Math.abs(e.mesh[443][1] - e.mesh[450][1]);
        i < 0.2 && t.push("blink left eye");
        const a = Math.abs(e.mesh[145][1] - e.mesh[159][1]) / Math.abs(e.mesh[223][1] - e.mesh[230][1]);
        a < 0.2 && t.push("blink right eye");
        const s = Math.min(100, 500 * Math.abs(e.mesh[13][1] - e.mesh[14][1]) / Math.abs(e.mesh[10][1] - e.mesh[152][1]));
        s > 10 && t.push(`mouth ${Math.trunc(s)}% open`);
        const o = e.mesh[152][2];
        Math.abs(o) > 10 && t.push(`head ${o < 0 ? "up" : "down"}`);
      }
    return t;
  };
  pc.hand = (n) => {
    if (!n)
      return [];
    const t = [];
    for (const e of n) {
      const r = [];
      for (const [i, a] of Object.entries(e.annotations))
        i !== "palmBase" && r.push({name: i.toLowerCase(), position: a[0]});
      if (r && r.length > 0) {
        const i = r.reduce((s, o) => s.position[2] < o.position[2] ? s : o), a = r.reduce((s, o) => s.position[1] < o.position[1] ? s : o);
        t.push(`${i.name} forward ${a.name} up`);
      }
    }
    return t;
  };
});
var aL = we((iL) => {
  const QV = function(n, t, e) {
    const r = function(o, c, l) {
      const u = new RegExp("\\b" + c + " \\w+ (\\w+)", "ig");
      o.replace(u, (h, d) => (l[d] = 0, h));
    }, i = function(o, c) {
      const l = n.createShader(c);
      if (n.shaderSource(l, o), n.compileShader(l), !n.getShaderParameter(l, n.COMPILE_STATUS))
        throw new Error("Filter: GL compile failed", n.getShaderInfoLog(l));
      return l;
    };
    this.uniform = {}, this.attribute = {};
    const a = i(t, n.VERTEX_SHADER), s = i(e, n.FRAGMENT_SHADER);
    if (this.id = n.createProgram(), n.attachShader(this.id, a), n.attachShader(this.id, s), n.linkProgram(this.id), !n.getProgramParameter(this.id, n.LINK_STATUS))
      throw new Error("Filter: GL link failed", n.getProgramInfoLog(this.id));
    n.useProgram(this.id), r(t, "attribute", this.attribute);
    for (const o in this.attribute)
      this.attribute[o] = n.getAttribLocation(this.id, o);
    r(t, "uniform", this.uniform), r(e, "uniform", this.uniform);
    for (const o in this.uniform)
      this.uniform[o] = n.getUniformLocation(this.id, o);
  }, eG = function(n) {
    n || (n = {});
    let t = 0, e = null, r = false, i = -1, a = [null, null], s = [], o = -1, c = -1, l = null, u = null;
    const h = n.canvas || document.createElement("canvas"), d = {}, p = h.getContext("webgl");
    if (!p)
      throw new Error("Filter: getContext() failed");
    this.addFilter = function(N) {
      const I = Array.prototype.slice.call(arguments, 1), C = x[N];
      s.push({func: C, args: I});
    }, this.reset = function() {
      s = [];
    }, this.apply = function(N) {
      if (f(N.width, N.height), t = 0, e || (e = p.createTexture()), p.bindTexture(p.TEXTURE_2D, e), p.texParameteri(p.TEXTURE_2D, p.TEXTURE_WRAP_S, p.CLAMP_TO_EDGE), p.texParameteri(p.TEXTURE_2D, p.TEXTURE_WRAP_T, p.CLAMP_TO_EDGE), p.texParameteri(p.TEXTURE_2D, p.TEXTURE_MIN_FILTER, p.NEAREST), p.texParameteri(p.TEXTURE_2D, p.TEXTURE_MAG_FILTER, p.NEAREST), p.texImage2D(p.TEXTURE_2D, 0, p.RGBA, p.RGBA, p.UNSIGNED_BYTE, N), s.length === 0)
        return y(), h;
      for (let I = 0; I < s.length; I++) {
        r = I === s.length - 1;
        const C = s[I];
        C.func.apply(this, C.args || []);
      }
      return h;
    };
    const f = function(N, I) {
      if (N === o && I === c)
        return;
      if (h.width = N, o = N, h.height = I, c = I, !l) {
        const C = new Float32Array([-1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0]);
        l = p.createBuffer(), p.bindBuffer(p.ARRAY_BUFFER, l), p.bufferData(p.ARRAY_BUFFER, C, p.STATIC_DRAW), p.pixelStorei(p.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);
      }
      p.viewport(0, 0, o, c), a = [null, null];
    }, m = function(N) {
      return a[N] = a[N] || g(o, c), a[N];
    }, g = function(N, I) {
      const C = p.createFramebuffer();
      p.bindFramebuffer(p.FRAMEBUFFER, C);
      const O = p.createRenderbuffer();
      p.bindRenderbuffer(p.RENDERBUFFER, O);
      const D = p.createTexture();
      return p.bindTexture(p.TEXTURE_2D, D), p.texImage2D(p.TEXTURE_2D, 0, p.RGBA, N, I, 0, p.RGBA, p.UNSIGNED_BYTE, null), p.texParameteri(p.TEXTURE_2D, p.TEXTURE_MAG_FILTER, p.LINEAR), p.texParameteri(p.TEXTURE_2D, p.TEXTURE_MIN_FILTER, p.LINEAR), p.texParameteri(p.TEXTURE_2D, p.TEXTURE_WRAP_S, p.CLAMP_TO_EDGE), p.texParameteri(p.TEXTURE_2D, p.TEXTURE_WRAP_T, p.CLAMP_TO_EDGE), p.framebufferTexture2D(p.FRAMEBUFFER, p.COLOR_ATTACHMENT0, p.TEXTURE_2D, D, 0), p.bindTexture(p.TEXTURE_2D, null), p.bindFramebuffer(p.FRAMEBUFFER, null), {fbo: C, texture: D};
    }, y = function(N) {
      let I = null, C = null, O = false;
      t === 0 ? I = e : I = m(i).texture, t++, r && !(N & b.INTERMEDIATE) ? (C = null, O = t % 2 === 0) : (i = (i + 1) % 2, C = m(i).fbo), p.bindTexture(p.TEXTURE_2D, I), p.bindFramebuffer(p.FRAMEBUFFER, C), p.uniform1f(u.uniform.flipY, O ? -1 : 1), p.drawArrays(p.TRIANGLES, 0, 6);
    }, w = function(N) {
      if (d[N])
        return u = d[N], p.useProgram(u.id), u;
      u = new QV(p, L.VERTEX_IDENTITY, N);
      const I = Float32Array.BYTES_PER_ELEMENT, C = 4 * I;
      return p.enableVertexAttribArray(u.attribute.pos), p.vertexAttribPointer(u.attribute.pos, 2, p.FLOAT, false, C, 0 * I), p.enableVertexAttribArray(u.attribute.uv), p.vertexAttribPointer(u.attribute.uv, 2, p.FLOAT, false, C, 2 * I), d[N] = u, u;
    };
    let b = {INTERMEDIATE: 1}, L = {};
    L.VERTEX_IDENTITY = ["precision highp float;", "attribute vec2 pos;", "attribute vec2 uv;", "varying vec2 vUv;", "uniform float flipY;", "void main(void) {", "vUv = uv;", "gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);", "}"].join(`
`), L.FRAGMENT_IDENTITY = ["precision highp float;", "varying vec2 vUv;", "uniform sampler2D texture;", "void main(void) {", "gl_FragColor = texture2D(texture, vUv);", "}"].join(`
`);
    let x = {};
    x.colorMatrix = function(N) {
      const I = new Float32Array(N);
      I[4] /= 255, I[9] /= 255, I[14] /= 255, I[19] /= 255;
      const C = I[18] === 1 && I[3] === 0 && I[8] === 0 && I[13] === 0 && I[15] === 0 && I[16] === 0 && I[17] === 0 && I[19] === 0 ? x.colorMatrix.SHADER.WITHOUT_ALPHA : x.colorMatrix.SHADER.WITH_ALPHA, O = w(C);
      p.uniform1fv(O.uniform.m, I), y();
    }, x.colorMatrix.SHADER = {}, x.colorMatrix.SHADER.WITH_ALPHA = ["precision highp float;", "varying vec2 vUv;", "uniform sampler2D texture;", "uniform float m[20];", "void main(void) {", "vec4 c = texture2D(texture, vUv);", "gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];", "gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];", "gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];", "gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];", "}"].join(`
`), x.colorMatrix.SHADER.WITHOUT_ALPHA = ["precision highp float;", "varying vec2 vUv;", "uniform sampler2D texture;", "uniform float m[20];", "void main(void) {", "vec4 c = texture2D(texture, vUv);", "gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];", "gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];", "gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];", "gl_FragColor.a = c.a;", "}"].join(`
`), x.brightness = function(N) {
      const I = (N || 0) + 1;
      x.colorMatrix([I, 0, 0, 0, 0, 0, I, 0, 0, 0, 0, 0, I, 0, 0, 0, 0, 0, 1, 0]);
    }, x.saturation = function(N) {
      const I = (N || 0) * 2 / 3 + 1, C = (I - 1) * -0.5;
      x.colorMatrix([I, C, C, 0, 0, C, I, C, 0, 0, C, C, I, 0, 0, 0, 0, 0, 1, 0]);
    }, x.desaturate = function() {
      x.saturation(-1);
    }, x.contrast = function(N) {
      const I = (N || 0) + 1, C = -128 * (I - 1);
      x.colorMatrix([I, 0, 0, 0, C, 0, I, 0, 0, C, 0, 0, I, 0, C, 0, 0, 0, 1, 0]);
    }, x.negative = function() {
      x.contrast(-2);
    }, x.hue = function(N) {
      N = (N || 0) / 180 * Math.PI;
      const I = Math.cos(N), C = Math.sin(N), O = 0.213, D = 0.715, F = 0.072;
      x.colorMatrix([O + I * (1 - O) + C * -O, D + I * -D + C * -D, F + I * -F + C * (1 - F), 0, 0, O + I * -O + C * 0.143, D + I * (1 - D) + C * 0.14, F + I * -F + C * -0.283, 0, 0, O + I * -O + C * -(1 - O), D + I * -D + C * D, F + I * (1 - F) + C * F, 0, 0, 0, 0, 0, 1, 0]);
    }, x.desaturateLuminance = function() {
      x.colorMatrix([0.2764723, 0.929708, 0.0938197, 0, -37.1, 0.2764723, 0.929708, 0.0938197, 0, -37.1, 0.2764723, 0.929708, 0.0938197, 0, -37.1, 0, 0, 0, 1, 0]);
    }, x.sepia = function() {
      x.colorMatrix([0.393, 0.7689999, 0.18899999, 0, 0, 0.349, 0.6859999, 0.16799999, 0, 0, 0.272, 0.5339999, 0.13099999, 0, 0, 0, 0, 0, 1, 0]);
    }, x.brownie = function() {
      x.colorMatrix([0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873, -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127, 0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283, 0, 0, 0, 1, 0]);
    }, x.vintagePinhole = function() {
      x.colorMatrix([0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123, 0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591, 0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296, 0, 0, 0, 1, 0]);
    }, x.kodachrome = function() {
      x.colorMatrix([1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502, -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203, -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946, 0, 0, 0, 1, 0]);
    }, x.technicolor = function() {
      x.colorMatrix([1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337, -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398, -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138, 0, 0, 0, 1, 0]);
    }, x.polaroid = function() {
      x.colorMatrix([1.438, -0.062, -0.062, 0, 0, -0.122, 1.378, -0.122, 0, 0, -0.016, -0.016, 1.483, 0, 0, 0, 0, 0, 1, 0]);
    }, x.shiftToBGR = function() {
      x.colorMatrix([0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0]);
    }, x.convolution = function(N) {
      const I = new Float32Array(N), C = 1 / o, O = 1 / c, D = w(x.convolution.SHADER);
      p.uniform1fv(D.uniform.m, I), p.uniform2f(D.uniform.px, C, O), y();
    }, x.convolution.SHADER = ["precision highp float;", "varying vec2 vUv;", "uniform sampler2D texture;", "uniform vec2 px;", "uniform float m[9];", "void main(void) {", "vec4 c11 = texture2D(texture, vUv - px);", "vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));", "vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));", "vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );", "vec4 c22 = texture2D(texture, vUv);", "vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );", "vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );", "vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );", "vec4 c33 = texture2D(texture, vUv + px );", "gl_FragColor = ", "c11 * m[0] + c12 * m[1] + c22 * m[2] +", "c21 * m[3] + c22 * m[4] + c23 * m[5] +", "c31 * m[6] + c32 * m[7] + c33 * m[8];", "gl_FragColor.a = c22.a;", "}"].join(`
`), x.detectEdges = function() {
      x.convolution.call(this, [0, 1, 0, 1, -4, 1, 0, 1, 0]);
    }, x.sobelX = function() {
      x.convolution.call(this, [-1, 0, 1, -2, 0, 2, -1, 0, 1]);
    }, x.sobelY = function() {
      x.convolution.call(this, [-1, -2, -1, 0, 0, 0, 1, 2, 1]);
    }, x.sharpen = function(N) {
      const I = N || 1;
      x.convolution.call(this, [0, -1 * I, 0, -1 * I, 1 + 4 * I, -1 * I, 0, -1 * I, 0]);
    }, x.emboss = function(N) {
      const I = N || 1;
      x.convolution.call(this, [-2 * I, -1 * I, 0, -1 * I, 1, 1 * I, 0, 1 * I, 2 * I]);
    }, x.blur = function(N) {
      const I = N / 7 / o, C = N / 7 / c, O = w(x.blur.SHADER);
      p.uniform2f(O.uniform.px, 0, C), y(b.INTERMEDIATE), p.uniform2f(O.uniform.px, I, 0), y();
    }, x.blur.SHADER = ["precision highp float;", "varying vec2 vUv;", "uniform sampler2D texture;", "uniform vec2 px;", "void main(void) {", "gl_FragColor = vec4(0.0);", "gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;", "gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;", "gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;", "gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;", "gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;", "gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;", "gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;", "gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;", "gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;", "gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;", "gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;", "gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;", "gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;", "gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;", "gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;", "}"].join(`
`), x.pixelate = function(N) {
      const I = N / o, C = N / c, O = w(x.pixelate.SHADER);
      p.uniform2f(O.uniform.size, I, C), y();
    }, x.pixelate.SHADER = ["precision highp float;", "varying vec2 vUv;", "uniform vec2 size;", "uniform sampler2D texture;", "vec2 pixelate(vec2 coord, vec2 size) {", "return floor( coord / size ) * size;", "}", "void main(void) {", "gl_FragColor = vec4(0.0);", "vec2 coord = pixelate(vUv, size);", "gl_FragColor += texture2D(texture, coord);", "}"].join(`
`);
  };
  iL.Canvas = eG;
});
var oL = we((sL) => {
  const bs = Ut(), tG = aL();
  let vt = null, nn = null;
  function nG(n, t) {
    let e;
    if (n instanceof bs.Tensor)
      e = bs.clone(n);
    else {
      const r = n.naturalWidth || n.videoWidth || n.width || n.shape && n.shape[1] > 0, i = n.naturalHeight || n.videoHeight || n.height || n.shape && n.shape[2] > 0;
      let a = r, s = i;
      t.filter.width > 0 ? a = t.filter.width : t.filter.height > 0 && (a = r * (t.filter.height / i)), t.filter.height > 0 ? s = t.filter.height : t.filter.width > 0 && (s = i * (t.filter.width / r)), (!vt || vt.width !== a || vt.height !== s) && (vt = typeof OffscreenCanvas != "undefined" ? new OffscreenCanvas(a, s) : document.createElement("canvas"), vt.width !== a && (vt.width = a), vt.height !== s && (vt.height = s));
      const o = vt.getContext("2d");
      n instanceof ImageData ? o.putImageData(n, 0, 0) : o.drawImage(n, 0, 0, r, i, 0, 0, vt.width, vt.height), t.filter.enabled ? ((!this.fx || !nn || vt.width !== nn.width || vt.height !== nn.height) && (nn = typeof OffscreenCanvas != "undefined" ? new OffscreenCanvas(vt.width, vt.height) : document.createElement("canvas"), nn.width !== vt.width && (nn.width = vt.width), nn.height !== vt.height && (nn.height = vt.height), this.fx = bs.ENV.flags.IS_BROWSER ? new tG.Canvas({canvas: nn}) : null), this.fx.reset(), this.fx.addFilter("brightness", t.filter.brightness), t.filter.contrast !== 0 && this.fx.addFilter("contrast", t.filter.contrast), t.filter.sharpness !== 0 && this.fx.addFilter("sharpen", t.filter.sharpness), t.filter.blur !== 0 && this.fx.addFilter("blur", t.filter.blur), t.filter.saturation !== 0 && this.fx.addFilter("saturation", t.filter.saturation), t.filter.hue !== 0 && this.fx.addFilter("hue", t.filter.hue), t.filter.negative && this.fx.addFilter("negative"), t.filter.sepia && this.fx.addFilter("sepia"), t.filter.vintage && this.fx.addFilter("brownie"), t.filter.sepia && this.fx.addFilter("sepia"), t.filter.kodachrome && this.fx.addFilter("kodachrome"), t.filter.technicolor && this.fx.addFilter("technicolor"), t.filter.polaroid && this.fx.addFilter("polaroid"), t.filter.pixelate !== 0 && this.fx.addFilter("pixelate", t.filter.pixelate), this.fx.apply(vt)) : nn = vt;
      let c;
      if (t.backend === "webgl" || nn instanceof ImageData)
        c = bs.browser.fromPixels(nn);
      else {
        const u = typeof OffscreenCanvas != "undefined" ? new OffscreenCanvas(a, s) : document.createElement("canvas");
        u.width = a, u.height = s;
        const h = u.getContext("2d");
        h.drawImage(nn, 0, 0);
        const d = h.getImageData(0, 0, a, s);
        c = bs.browser.fromPixels(d);
      }
      const l = c.toFloat();
      e = l.expandDims(0), c.dispose(), l.dispose();
    }
    return {tensor: e, canvas: t.filter.return ? nn : null};
  }
  sL.process = nG;
});
var cL = we((rG) => {
  As(rG, {default: () => iG});
  var iG = {backend: "webgl", console: true, async: true, profile: false, deallocate: false, scoped: false, videoOptimized: true, filter: {enabled: true, width: 0, height: 0, return: true, brightness: 0, contrast: 0, sharpness: 0, blur: 0, saturation: 0, hue: 0, negative: false, sepia: false, vintage: false, kodachrome: false, technicolor: false, polaroid: false, pixelate: 0}, gesture: {enabled: true}, face: {enabled: true, detector: {modelPath: "../models/blazeface-back.json", inputSize: 256, maxFaces: 10, skipFrames: 15, minConfidence: 0.5, iouThreshold: 0.2, scoreThreshold: 0.5}, mesh: {enabled: true, modelPath: "../models/facemesh.json", inputSize: 192}, iris: {enabled: true, modelPath: "../models/iris.json", inputSize: 64}, age: {enabled: true, modelPath: "../models/age-ssrnet-imdb.json", inputSize: 64, skipFrames: 15}, gender: {enabled: true, minConfidence: 0.1, modelPath: "../models/gender-ssrnet-imdb.json", inputSize: 64, skipFrames: 15}, emotion: {enabled: true, inputSize: 64, minConfidence: 0.2, skipFrames: 15, modelPath: "../models/emotion-large.json"}}, body: {enabled: true, modelPath: "../models/posenet.json", inputSize: 257, maxDetections: 10, scoreThreshold: 0.8, nmsRadius: 20}, hand: {enabled: true, inputSize: 256, skipFrames: 15, minConfidence: 0.5, iouThreshold: 0.1, scoreThreshold: 0.8, maxHands: 1, landmarks: true, detector: {modelPath: "../models/handdetect.json"}, skeleton: {modelPath: "../models/handskeleton.json"}}};
});
var uL = we((uq, lL) => {
  lL.exports = {name: "@vladmandic/human", version: "0.8.4", description: "human: 3D Face Detection, Body Pose, Hand & Finger Tracking, Iris Tracking, Age & Gender Prediction, Emotion Prediction & Gesture Recognition", sideEffects: false, main: "dist/human.node.js", module: "dist/human.esm.js", browser: "dist/human.esm.js", author: "Vladimir Mandic <mandic00@live.com>", bugs: {url: "https://github.com/vladmandic/human/issues"}, homepage: "https://github.com/vladmandic/human#readme", license: "MIT", engines: {node: ">=14.0.0"}, repository: {type: "git", url: "git+https://github.com/vladmandic/human.git"}, dependencies: {}, peerDependencies: {}, devDependencies: {"@tensorflow/tfjs": "^2.7.0", "@tensorflow/tfjs-node": "^2.7.0", "@vladmandic/pilogger": "^0.2.7", chokidar: "^3.4.3", dayjs: "^1.9.5", esbuild: "^0.7.22", eslint: "^7.13.0", "eslint-config-airbnb-base": "^14.2.1", "eslint-plugin-import": "^2.22.1", "eslint-plugin-json": "^2.1.2", "eslint-plugin-node": "^11.1.0", "eslint-plugin-promise": "^4.2.1", rimraf: "^3.0.2", seedrandom: "^3.0.5", "simple-git": "^2.21.0"}, scripts: {start: "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js", lint: "eslint src/*.js demo/*.js", dev: "npm install && node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation dev-server/dev-server.js", changelog: "node dev-server/changelog.js", "build-iife": "esbuild --bundle --minify --platform=browser --sourcemap --target=es2018 --format=iife --external:fs --global-name=Human --metafile=dist/human.json --outfile=dist/human.js src/human.js", "build-esm-bundle": "esbuild --bundle --minify --platform=browser --sourcemap --target=es2018 --format=esm --external:fs --metafile=dist/human.esm.json --outfile=dist/human.esm.js src/human.js", "build-esm-nobundle": "esbuild --bundle --minify --platform=browser --sourcemap --target=es2018 --format=esm --external:@tensorflow --external:fs --metafile=dist/human.esm-nobundle.json --outfile=dist/human.esm-nobundle.js src/human.js", "build-node": "esbuild --bundle --minify --platform=node --sourcemap --target=es2018 --format=cjs --metafile=dist/human.node.json --outfile=dist/human.node.js src/human.js", "build-node-nobundle": "esbuild --bundle --minify --platform=node --sourcemap --target=es2018 --format=cjs --external:@tensorflow --metafile=dist/human.node.json --outfile=dist/human.node-nobundle.js src/human.js", "build-demo": "esbuild --bundle --log-level=error --platform=browser --sourcemap --target=es2018 --format=esm --external:fs --metafile=dist/demo-browser-index.json --outfile=dist/demo-browser-index.js demo/browser.js", build: "rimraf dist/* && npm run build-iife && npm run build-esm-bundle && npm run build-esm-nobundle && npm run build-node && npm run build-node-nobundle && npm run build-demo && npm run changelog", update: "npm update --depth 20 --force && npm dedupe && npm prune && npm audit"}, keywords: ["tensorflowjs", "face-detection", "face-geometry", "body-tracking", "hand-tracking", "iris-tracking", "age-estimation", "emotion-detection", "gender-prediction", "gesture-recognition"]};
});
const Yt = Ut();
const Qp = cx();
const xs = ux();
const Ls = hx();
const Ss = px();
const ef = Bx();
const tf = nL();
const nf = rL();
const aG = oL();
const sG = ps();
const oG = cL().default;
const cG = uL();
const lG = {face: {detector: {skipFrames: 0}, age: {skipFrames: 0}, gender: {skipFrames: 0}, emotion: {skipFrames: 0}}, hand: {skipFrames: 0}};
const ut = () => typeof performance != "undefined" ? performance.now() : parseInt(Number(process.hrtime.bigint()) / 1e3 / 1e3);
function Is(...n) {
  const t = (e) => e && typeof e == "object";
  return n.reduce((e, r) => (Object.keys(r || {}).forEach((i) => {
    const a = e[i], s = r[i];
    Array.isArray(a) && Array.isArray(s) ? e[i] = a.concat(...s) : t(a) && t(s) ? e[i] = Is(a, s) : e[i] = s;
  }), e), {});
}
class uG {
  constructor(n = {}) {
    this.tf = Yt, this.version = cG.version, this.config = Is(oG, n), this.fx = null, this.state = "idle", this.numTensors = 0, this.analyzeMemoryLeaks = false, this.checkSanity = false, this.firstRun = true, this.perf = {}, this.models = {facemesh: null, posenet: null, handpose: null, iris: null, age: null, gender: null, emotion: null}, this.facemesh = Qp, this.age = xs, this.gender = Ls, this.emotion = Ss, this.body = ef, this.hand = tf;
  }
  log(...n) {
    n && this.config.console && console.log("Human:", ...n);
  }
  profile() {
    return this.config.profile ? sG.data : {};
  }
  analyze(...n) {
    if (!this.analyzeMemoryLeaks)
      return;
    const t = Yt.engine().state.numTensors, e = this.numTensors;
    this.numTensors = t;
    const r = t - e;
    r !== 0 && this.log(...n, r);
  }
  sanity(n) {
    if (!this.checkSanity)
      return null;
    if (!n)
      return "input is not defined";
    if (Yt.ENV.flags.IS_NODE && !(n instanceof Yt.Tensor))
      return "input must be a tensor";
    try {
      Yt.getBackend();
    } catch (t) {
      return "backend not loaded";
    }
    return null;
  }
  async load(n) {
    this.state = "load";
    const t = ut();
    n && (this.config = Is(this.config, n)), this.firstRun && (this.checkBackend(true), this.log(`version: ${this.version} TensorFlow/JS version: ${Yt.version_core}`), this.log("configuration:", this.config), this.log("flags:", Yt.ENV.flags), this.firstRun = false), this.config.async ? [this.models.age, this.models.gender, this.models.emotion, this.models.facemesh, this.models.posenet, this.models.handpose] = await Promise.all([this.models.age || xs.load(this.config), this.models.gender || Ls.load(this.config), this.models.emotion || Ss.load(this.config), this.models.facemesh || Qp.load(this.config.face), this.models.posenet || ef.load(this.config), this.models.handpose || tf.load(this.config.hand)]) : (this.config.face.enabled && !this.models.facemesh && (this.models.facemesh = await Qp.load(this.config.face)), this.config.body.enabled && !this.models.posenet && (this.models.posenet = await ef.load(this.config)), this.config.hand.enabled && !this.models.handpose && (this.models.handpose = await tf.load(this.config.hand)), this.config.face.enabled && this.config.face.age.enabled && !this.models.age && (this.models.age = await xs.load(this.config)), this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender && (this.models.gender = await Ls.load(this.config)), this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion && (this.models.emotion = await Ss.load(this.config)));
    const e = Math.trunc(ut() - t);
    e > (this.perf.load || 0) && (this.perf.load = e);
  }
  async checkBackend(n) {
    const t = ut();
    (this.config.backend && this.config.backend !== "" && n || Yt.getBackend() !== this.config.backend) && (this.state = "backend", this.log("setting backend:", this.config.backend), await Yt.setBackend(this.config.backend), Yt.enableProdMode(), this.config.backend === "webgl" && (this.config.deallocate && (this.log("Changing WebGL: WEBGL_DELETE_TEXTURE_THRESHOLD:", this.config.deallocate), Yt.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD", this.config.deallocate ? 0 : -1)), Yt.ENV.set("WEBGL_PACK_DEPTHWISECONV", true)), await Yt.ready());
    const e = Math.trunc(ut() - t);
    e > (this.perf.backend || 0) && (this.perf.backend = e);
  }
  async detectFace(n) {
    let t, e, r, i;
    const a = [];
    this.state = "run:face", t = ut();
    const s = await this.models.facemesh.estimateFaces(n, this.config.face);
    this.perf.face = Math.trunc(ut() - t);
    for (const o of s) {
      if (this.analyze("Get Face"), !o.image || o.image.isDisposedInternal) {
        this.log("Face object is disposed:", o.image);
        continue;
      }
      this.analyze("Start Age:"), this.config.async ? e = this.config.face.age.enabled ? xs.predict(o.image, this.config) : {} : (this.state = "run:age", t = ut(), e = this.config.face.age.enabled ? await xs.predict(o.image, this.config) : {}, this.perf.age = Math.trunc(ut() - t)), this.analyze("Start Gender:"), this.config.async ? r = this.config.face.gender.enabled ? Ls.predict(o.image, this.config) : {} : (this.state = "run:gender", t = ut(), r = this.config.face.gender.enabled ? await Ls.predict(o.image, this.config) : {}, this.perf.gender = Math.trunc(ut() - t)), this.analyze("Start Emotion:"), this.config.async ? i = this.config.face.emotion.enabled ? Ss.predict(o.image, this.config) : {} : (this.state = "run:emotion", t = ut(), i = this.config.face.emotion.enabled ? await Ss.predict(o.image, this.config) : {}, this.perf.emotion = Math.trunc(ut() - t)), this.analyze("End Emotion:"), this.config.async && ([e, r, i] = await Promise.all([e, r, i])), this.analyze("Finish Face:"), o.image.dispose();
      const c = o.annotations.leftEyeIris && o.annotations.rightEyeIris ? 11.7 * Math.max(Math.abs(o.annotations.leftEyeIris[3][0] - o.annotations.leftEyeIris[1][0]), Math.abs(o.annotations.rightEyeIris[4][1] - o.annotations.rightEyeIris[2][1])) : 0;
      a.push({confidence: o.confidence, box: o.box, mesh: o.mesh, annotations: o.annotations, age: e.age, gender: r.gender, genderConfidence: r.confidence, emotion: i, iris: c !== 0 ? Math.trunc(c) / 100 : 0}), this.analyze("End Face");
    }
    return this.analyze("End FaceMesh:"), this.config.async && (this.perf.face && delete this.perf.face, this.perf.age && delete this.perf.age, this.perf.gender && delete this.perf.gender, this.perf.emotion && delete this.perf.emotion), a;
  }
  async detect(n, t = {}) {
    this.state = "config";
    let e;
    this.config = Is(this.config, t), this.config.videoOptimized || (this.config = Is(this.config, lG)), this.state = "check";
    const r = this.sanity(n);
    return r ? (this.log(r, n), {error: r}) : new Promise(async (i) => {
      let a, s, o;
      const c = ut();
      await this.checkBackend(), await this.load(), this.config.scoped && Yt.engine().startScope(), this.analyze("Start Scope:"), e = ut();
      const l = aG.process(n, this.config);
      this.perf.image = Math.trunc(ut() - e), this.analyze("Get Image:"), this.config.async ? (o = this.config.face.enabled ? this.detectFace(l.tensor) : [], this.perf.face && delete this.perf.face) : (this.state = "run:face", e = ut(), o = this.config.face.enabled ? await this.detectFace(l.tensor) : [], this.perf.face = Math.trunc(ut() - e)), this.analyze("Start Body:"), this.config.async ? (a = this.config.body.enabled ? this.models.posenet.estimatePoses(l.tensor, this.config) : [], this.perf.body && delete this.perf.body) : (this.state = "run:body", e = ut(), a = this.config.body.enabled ? await this.models.posenet.estimatePoses(l.tensor, this.config) : [], this.perf.body = Math.trunc(ut() - e)), this.analyze("End Body:"), this.analyze("Start Hand:"), this.config.async ? (s = this.config.hand.enabled ? this.models.handpose.estimateHands(l.tensor, this.config.hand) : [], this.perf.hand && delete this.perf.hand) : (this.state = "run:hand", e = ut(), s = this.config.hand.enabled ? await this.models.handpose.estimateHands(l.tensor, this.config.hand) : [], this.perf.hand = Math.trunc(ut() - e)), this.config.async && ([o, a, s] = await Promise.all([o, a, s])), l.tensor.dispose(), this.config.scoped && Yt.engine().endScope(), this.analyze("End Scope:");
      let u = [];
      this.config.gesture.enabled && (e = ut(), u = {face: nf.face(o), body: nf.body(a), hand: nf.hand(s)}, this.config.async ? this.perf.gesture && delete this.perf.gesture : this.perf.gesture = Math.trunc(ut() - e)), this.perf.total = Math.trunc(ut() - c), this.state = "idle", i({face: o, body: a, hand: s, gesture: u, performance: this.perf, canvas: l.canvas});
    });
  }
  async warmup(n) {
    const t = new ImageData(255, 255);
    await this.detect(t, n), this.log("warmed up");
  }
}
/*! *****************************************************************************
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use
this file except in compliance with the License. You may obtain a copy of the
License at http://www.apache.org/licenses/LICENSE-2.0

THIS CODE IS PROVIDED ON AN *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
MERCHANTABLITY OR NON-INFRINGEMENT.

See the Apache Version 2.0 License for specific language governing permissions
and limitations under the License.
***************************************************************************** */
/**
 * @license
 * Copyright 2017 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2018 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2018 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 * =============================================================================
 */
/**
 * @license
 * Copyright 2018 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2019 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2019 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 * =============================================================================
 */
/**
 * @license
 * Copyright 2019 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google Inc. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the License);
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an AS IS BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/** @license See the LICENSE file. */

// demo/draw.js
async function drawGesture(result, canvas, ui2) {
  if (!result)
    return;
  const ctx = canvas.getContext("2d");
  ctx.font = ui2.baseFont;
  ctx.fillStyle = ui2.baseLabel;
  let i = 1;
  for (const [key, val] of Object.entries(result)) {
    if (val.length > 0) {
      const label = `${key}: ${val.join(", ")}`;
      ctx.fillText(label, 6, i * (ui2.baseLineHeight + 24));
      i += 1;
    }
  }
}
async function drawFace(result, canvas, ui2, triangulation) {
  if (!result)
    return;
  const ctx = canvas.getContext("2d");
  for (const face of result) {
    ctx.font = ui2.baseFont;
    ctx.strokeStyle = ui2.baseColor;
    ctx.fillStyle = ui2.baseColor;
    ctx.lineWidth = ui2.baseLineWidth;
    ctx.beginPath();
    if (ui2.drawBoxes) {
      ctx.rect(face.box[0], face.box[1], face.box[2], face.box[3]);
    }
    const labels = [];
    if (face.genderConfidence)
      labels.push(`${Math.trunc(100 * face.genderConfidence)}% ${face.gender || ""}`);
    if (face.age)
      labels.push(`age: ${face.age || ""}`);
    if (face.iris)
      labels.push(`iris: ${face.iris}`);
    if (face.emotion && face.emotion.length > 0) {
      const emotion = face.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);
      labels.push(emotion.join(" "));
    }
    ctx.fillStyle = ui2.baseLabel;
    for (const i in labels)
      ctx.fillText(labels[i], face.box[0] + 8, face.box[1] + 24 + (i + 1) * ui2.baseLineHeight);
    ctx.stroke();
    ctx.lineWidth = 1;
    if (face.mesh) {
      if (ui2.drawPoints) {
        for (const point of face.mesh) {
          ctx.fillStyle = ui2.useDepth ? `rgba(${127.5 + 2 * point[2]}, ${127.5 - 2 * point[2]}, 255, 0.5)` : ui2.baseColor;
          ctx.beginPath();
          ctx.arc(point[0], point[1], 2, 0, 2 * Math.PI);
          ctx.fill();
        }
      }
      if (ui2.drawPolygons) {
        for (let i = 0; i < triangulation.length / 3; i++) {
          const points = [
            triangulation[i * 3 + 0],
            triangulation[i * 3 + 1],
            triangulation[i * 3 + 2]
          ].map((index) => face.mesh[index]);
          const path = new Path2D();
          path.moveTo(points[0][0], points[0][1]);
          for (const point of points) {
            path.lineTo(point[0], point[1]);
          }
          path.closePath();
          ctx.strokeStyle = ui2.useDepth ? `rgba(${127.5 + 2 * points[0][2]}, ${127.5 - 2 * points[0][2]}, 255, 0.3)` : ui2.baseColor;
          ctx.stroke(path);
          if (ui2.fillPolygons) {
            ctx.fillStyle = ui2.useDepth ? `rgba(${127.5 + 2 * points[0][2]}, ${127.5 - 2 * points[0][2]}, 255, 0.3)` : ui2.baseColor;
            ctx.fill(path);
          }
        }
        if (face.annotations && face.annotations.leftEyeIris) {
          ctx.strokeStyle = ui2.useDepth ? "rgba(255, 200, 255, 0.3)" : ui2.baseColor;
          ctx.beginPath();
          const sizeX = Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]) / 2;
          const sizeY = Math.abs(face.annotations.leftEyeIris[4][1] - face.annotations.leftEyeIris[2][1]) / 2;
          ctx.ellipse(face.annotations.leftEyeIris[0][0], face.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);
          ctx.stroke();
          if (ui2.fillPolygons) {
            ctx.fillStyle = ui2.useDepth ? "rgba(255, 255, 200, 0.3)" : ui2.baseColor;
            ctx.fill();
          }
        }
        if (face.annotations && face.annotations.rightEyeIris) {
          ctx.strokeStyle = ui2.useDepth ? "rgba(255, 200, 255, 0.3)" : ui2.baseColor;
          ctx.beginPath();
          const sizeX = Math.abs(face.annotations.rightEyeIris[3][0] - face.annotations.rightEyeIris[1][0]) / 2;
          const sizeY = Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]) / 2;
          ctx.ellipse(face.annotations.rightEyeIris[0][0], face.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);
          ctx.stroke();
          if (ui2.fillPolygons) {
            ctx.fillStyle = ui2.useDepth ? "rgba(255, 255, 200, 0.3)" : ui2.baseColor;
            ctx.fill();
          }
        }
      }
    }
  }
}
async function drawBody(result, canvas, ui2) {
  if (!result)
    return;
  const ctx = canvas.getContext("2d");
  ctx.lineJoin = "round";
  for (const pose of result) {
    ctx.fillStyle = ui2.baseColor;
    ctx.strokeStyle = ui2.baseColor;
    ctx.font = ui2.baseFont;
    ctx.lineWidth = ui2.baseLineWidth;
    if (ui2.drawPoints) {
      for (const point of pose.keypoints) {
        ctx.beginPath();
        ctx.arc(point.position.x, point.position.y, 2, 0, 2 * Math.PI);
        ctx.fill();
      }
    }
    if (ui2.drawPolygons) {
      const path = new Path2D();
      let part;
      part = pose.keypoints.find((a) => a.part === "leftShoulder");
      path.moveTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightShoulder");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightHip");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftHip");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftShoulder");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftHip");
      path.moveTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftKnee");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftAnkle");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightHip");
      path.moveTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightKnee");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightAnkle");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightShoulder");
      path.moveTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftShoulder");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftElbow");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftWrist");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "leftShoulder");
      path.moveTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightShoulder");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightElbow");
      path.lineTo(part.position.x, part.position.y);
      part = pose.keypoints.find((a) => a.part === "rightWrist");
      path.lineTo(part.position.x, part.position.y);
      ctx.stroke(path);
    }
  }
}
async function drawHand(result, canvas, ui2) {
  if (!result)
    return;
  const ctx = canvas.getContext("2d");
  ctx.lineJoin = "round";
  for (const hand of result) {
    ctx.font = ui2.baseFont;
    ctx.lineWidth = ui2.baseLineWidth;
    if (ui2.drawBoxes) {
      ctx.lineWidth = ui2.baseLineWidth;
      ctx.beginPath();
      ctx.strokeStyle = ui2.baseColor;
      ctx.fillStyle = ui2.baseColor;
      ctx.rect(hand.box[0], hand.box[1], hand.box[2], hand.box[3]);
      ctx.fillStyle = ui2.baseLabel;
      ctx.fillText("hand", hand.box[0] + 2, hand.box[1] + 22, hand.box[2]);
      ctx.stroke();
    }
    if (ui2.drawPoints) {
      if (hand.landmarks && hand.landmarks.length > 0) {
        for (const point of hand.landmarks) {
          ctx.fillStyle = ui2.useDepth ? `rgba(${127.5 + 2 * point[2]}, ${127.5 - 2 * point[2]}, 255, 0.5)` : ui2.baseColor;
          ctx.beginPath();
          ctx.arc(point[0], point[1], 2, 0, 2 * Math.PI);
          ctx.fill();
        }
      }
    }
    if (ui2.drawPolygons) {
      const addPart = (part) => {
        if (!part)
          return;
        for (let i = 0; i < part.length; i++) {
          ctx.lineWidth = ui2.baseLineWidth;
          ctx.beginPath();
          ctx.strokeStyle = ui2.useDepth ? `rgba(${127.5 + 2 * part[i][2]}, ${127.5 - 2 * part[i][2]}, 255, 0.5)` : ui2.baseColor;
          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);
          ctx.lineTo(part[i][0], part[i][1]);
          ctx.stroke();
        }
      };
      addPart(hand.annotations.indexFinger);
      addPart(hand.annotations.middleFinger);
      addPart(hand.annotations.ringFinger);
      addPart(hand.annotations.pinky);
      addPart(hand.annotations.thumb);
    }
  }
}
const draw = {
  face: drawFace,
  body: drawBody,
  hand: drawHand,
  gesture: drawGesture
};
var draw_default = draw;

// demo/menu.js
let instance = 0;
let CSScreated = false;
let theme = {
  background: "darkslategray",
  hover: "lightgray",
  itemBackground: "black",
  itemColor: "white",
  buttonBackground: "lightblue",
  buttonHover: "lightgreen",
  checkboxOn: "lightgreen",
  checkboxOff: "lightcoral",
  rangeBackground: "lightblue",
  rangeLabel: "white",
  chartColor: "lightblue"
};
function createCSS() {
  if (CSScreated)
    return;
  const css = `
  :root { --rounded: 0.2rem; }
  .menu { position: absolute; top: 0rem; right: 0; width: fit-content; padding: 0 0.8rem 0 0.8rem; line-height: 1.8rem; z-index: 10; max-height: calc(100% - 4rem);
          box-shadow: 0 0 8px dimgrey; background: ${theme.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; }

  .menu:hover { box-shadow: 0 0 8px ${theme.hover}; }
  .menu-container { display: block; max-height: 100vh; }
  .menu-container-fadeout { max-height: 0; overflow: hidden; transition: max-height, 0.5s ease; }
  .menu-container-fadein { max-height: 100vh; overflow: hidden; transition: max-height, 0.5s ease; }
  .menu-item { display: flex; white-space: nowrap; padding: 0.2rem; width: max-content; cursor: default; }
  .menu-title { text-align: right; cursor: pointer; }
  .menu-hr { margin: 0.2rem; border: 1px solid rgba(0, 0, 0, 0.5) }
  .menu-label { padding: 0; font-weight: 800; }

  .menu-list { margin-right: 0.8rem; }
  select:focus { outline: none; }
  .menu-list-item { background: ${theme.itemBackground}; color: ${theme.itemColor}; border: none; padding: 0.2rem; font-family: inherit; font-variant: inherit; border-radius: var(--rounded); font-weight: 800; }

  .menu-chart-title { padding: 0; font-size: 0.8rem; font-weight: 800; align-items: center}
  .menu-chart-canvas { background: transparent; margin: 0.2rem 0 0.2rem 0.6rem; }
  
  .menu-button { border: 0; background: ${theme.buttonBackground}; width: -webkit-fill-available; padding: 8px; margin: 8px 0 8px 0; cursor: pointer; box-shadow: 4px 4px 4px 0 dimgrey;
                 border-radius: var(--rounded); justify-content: center; font-family: inherit; font-variant: inherit; font-size: 1rem; font-weight: 800; }
  .menu-button:hover { background: ${theme.buttonHover}; box-shadow: 4px 4px 4px 0 black; }
  .menu-button:focus { outline: none; }

  .menu-checkbox { width: 2.8rem; height: 1rem; background: ${theme.itemBackground}; margin: 0.5rem 0.8rem 0 0; position: relative; border-radius: var(--rounded); }
  .menu-checkbox:after { content: 'OFF'; color: ${theme.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
  .menu-checkbox:before { content: 'ON'; color: ${theme.checkboxOn}; position: absolute; left: 0.3rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
  .menu-checkbox-label { width: 1.3rem; height: 0.8rem; cursor: pointer; position: absolute; top: 0.1rem; left: 0.1rem; z-index: 1; background: ${theme.checkboxOff}; border-radius: var(--rounded); transition: left 0.6s ease; }
  input[type=checkbox] { visibility: hidden; }
  input[type=checkbox]:checked + label { left: 1.4rem; background: ${theme.checkboxOn}; }

  .menu-range { margin: 0 0.8rem 0 0; width: 5rem; background: transparent; color: ${theme.rangeBackground}; }
  .menu-range:before { content: attr(value); color: ${theme.rangeLabel}; margin: 0 0.4rem 0 0; font-weight: 800; font-size: 0.6rem; position: relative; top: 0.3rem; }
  input[type=range] { -webkit-appearance: none; }
  input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 1rem; cursor: pointer; background: ${theme.itemBackground}; border-radius: var(--rounded); border: 1px; }
  input[type=range]::-webkit-slider-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1.5rem; border-radius: var(--rounded); background: ${theme.rangeBackground}; cursor: pointer; -webkit-appearance: none; }

  .svg-background { fill:darkslategrey; cursor:pointer; opacity: 0.6; }
  .svg-foreground { fill:white; cursor:pointer; opacity: 0.8; }
  `;
  const el = document.createElement("style");
  el.innerHTML = css;
  document.getElementsByTagName("head")[0].appendChild(el);
  CSScreated = true;
}
class Menu {
  constructor(parent, title, position, userTheme) {
    if (userTheme)
      theme = {...theme, ...userTheme};
    createCSS();
    this.createMenu(parent, title, position);
    this.id = 0;
    this.instance = instance;
    instance++;
    this._maxFPS = 0;
    this.hidden = 0;
  }
  createMenu(parent, title = "", position = {top: null, left: null, bottom: null, right: null}) {
    this.menu = document.createElement("div");
    this.menu.id = `menu-${instance}`;
    this.menu.className = "menu";
    if (position) {
      if (position.top)
        this.menu.style.top = position.top;
      if (position.bottom)
        this.menu.style.bottom = position.bottom;
      if (position.left)
        this.menu.style.left = position.left;
      if (position.right)
        this.menu.style.right = position.right;
    }
    this.container = document.createElement("div");
    this.container.id = `menu-container-${instance}`;
    this.container.className = "menu-container menu-container-fadein";
    const elTitle = document.createElement("div");
    elTitle.className = "menu-title";
    elTitle.id = `menu-title-${instance}`;
    const svg = `<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" style="width: 2rem; height: 2rem; vertical-align: top;">
        <path d="M400 32H48A48 48 0 0 0 0 80v352a48 48 0 0 0 48 48h352a48 48 0 0 0 48-48V80a48 48 0 0 0-48-48zm-51.37 182.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z" class="svg-background"/>
        <path d="M348.63 214.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z" class="svg-foreground"/>
      </svg>`;
    elTitle.innerHTML = `${title}${svg}`;
    this.menu.appendChild(elTitle);
    elTitle.addEventListener("click", () => {
      this.container.classList.toggle("menu-container-fadeout");
      this.container.classList.toggle("menu-container-fadein");
      this.menu.style.borderStyle = this.container.classList.contains("menu-container-fadeout") ? "none" : "solid";
    });
    this.menu.appendChild(this.container);
    if (typeof parent === "object")
      parent.appendChild(this.menu);
    else
      document.getElementById(parent).appendChild(this.menu);
  }
  get newID() {
    this.id++;
    return `menu-${this.instance}-${this.id}`;
  }
  get ID() {
    return `menu-${this.instance}-${this.id}`;
  }
  get width() {
    return this.menu.offsetWidth;
  }
  get height() {
    return this.menu.offsetHeight;
  }
  hide() {
    if (this.container.classList.contains("menu-container-fadein")) {
      this.container.classList.toggle("menu-container-fadeout");
      this.container.classList.toggle("menu-container-fadein");
    }
  }
  visible() {
    return this.container.classList.contains("menu-container-fadein");
  }
  toggle(evt) {
    this.container.classList.toggle("menu-container-fadeout");
    this.container.classList.toggle("menu-container-fadein");
    if (this.container.classList.contains("menu-container-fadein") && evt) {
      const x = evt.x || (evt.touches && evt.touches[0] ? evt.touches[0].pageX : null);
      const y = evt.y || (evt.touches && evt.touches[0] ? evt.touches[0].pageY : null);
      if (x)
        this.menu.style.left = `${x - 105}px`;
      if (y)
        this.menu.style.top = "5.5rem";
      if (this.menu.offsetLeft < 0)
        this.menu.style.left = 0;
      if (this.menu.offsetLeft + this.menu.offsetWidth > window.innerWidth) {
        this.menu.style.left = null;
        this.menu.style.right = 0;
      }
      this.menu.style.borderStyle = "solid";
    } else {
      this.menu.style.borderStyle = "none";
    }
  }
  addTitle(title) {
    const el = document.createElement("div");
    el.className = "menu-title";
    el.id = this.newID;
    el.innerHTML = title;
    this.menu.appendChild(el);
    el.addEventListener("click", () => {
      this.hidden = !this.hidden;
      const all = document.getElementsByClassName("menu");
      for (const item of all) {
        item.style.display = this.hidden ? "none" : "block";
      }
    });
    return el;
  }
  addLabel(title) {
    const el = document.createElement("div");
    el.className = "menu-item menu-label";
    el.id = this.newID;
    el.innerHTML = title;
    this.container.appendChild(el);
    return el;
  }
  addBool(title, object, variable, callback) {
    const el = document.createElement("div");
    el.className = "menu-item";
    el.innerHTML = `<div class="menu-checkbox"><input class="menu-checkbox" type="checkbox" id="${this.newID}" ${object[variable] ? "checked" : ""}/><label class="menu-checkbox-label" for="${this.ID}"></label></div>${title}`;
    this.container.appendChild(el);
    el.addEventListener("change", (evt) => {
      object[variable] = evt.target.checked;
      if (callback)
        callback(evt.target.checked);
    });
    return el;
  }
  async addList(title, items, selected, callback) {
    const el = document.createElement("div");
    el.className = "menu-item";
    let options = "";
    for (const item of items) {
      const def = item === selected ? "selected" : "";
      options += `<option value="${item}" ${def}>${item}</option>`;
    }
    el.innerHTML = `<div class="menu-list"><select name="${this.ID}" class="menu-list-item">${options}</select><label for="${this.ID}"></label></div>${title}`;
    el.style.fontFamily = document.body.style.fontFamily;
    el.style.fontSize = document.body.style.fontSize;
    el.style.fontVariant = document.body.style.fontVariant;
    this.container.appendChild(el);
    el.addEventListener("change", (evt) => {
      if (callback)
        callback(items[evt.target.selectedIndex]);
    });
    return el;
  }
  addRange(title, object, variable, min, max, step, callback) {
    const el = document.createElement("div");
    el.className = "menu-item";
    el.innerHTML = `<input class="menu-range" type="range" id="${this.newID}" min="${min}" max="${max}" step="${step}" value="${object[variable]}">${title}`;
    this.container.appendChild(el);
    el.addEventListener("change", (evt) => {
      object[variable] = parseInt(evt.target.value) === parseFloat(evt.target.value) ? parseInt(evt.target.value) : parseFloat(evt.target.value);
      evt.target.setAttribute("value", evt.target.value);
      if (callback)
        callback(evt.target.value);
    });
    el.input = el.children[0];
    return el;
  }
  addHTML(html) {
    const el = document.createElement("div");
    el.className = "menu-item";
    el.id = this.newID;
    if (html)
      el.innerHTML = html;
    this.container.appendChild(el);
    return el;
  }
  addButton(titleOn, titleOff, callback) {
    const el = document.createElement("button");
    el.className = "menu-item menu-button";
    el.style.fontFamily = document.body.style.fontFamily;
    el.style.fontSize = document.body.style.fontSize;
    el.style.fontVariant = document.body.style.fontVariant;
    el.type = "button";
    el.id = this.newID;
    el.innerText = titleOn;
    this.container.appendChild(el);
    el.addEventListener("click", () => {
      if (el.innerText === titleOn)
        el.innerText = titleOff;
      else
        el.innerText = titleOn;
      if (callback)
        callback(el.innerText !== titleOn);
    });
    return el;
  }
  addValue(title, val, suffix = "") {
    const el = document.createElement("div");
    el.className = "menu-item";
    el.id = `menu-val-${title}`;
    el.innerText = `${title}: ${val}${suffix}`;
    this.container.appendChild(el);
    return el;
  }
  updateValue(title, val, suffix = "") {
    const el = document.getElementById(`menu-val-${title}`);
    if (el)
      el.innerText = `${title}: ${val}${suffix}`;
    else
      this.addValue(title, val);
  }
  addChart(title, id, width = 200, height = 40, color) {
    if (color)
      theme.chartColor = color;
    const el = document.createElement("div");
    el.className = "menu-item menu-chart-title";
    el.id = this.newID;
    el.innerHTML = `<font color=${theme.chartColor}>${title}</font><canvas id="menu-canvas-${id}" class="menu-chart-canvas" width="${width}px" height="${height}px"></canvas>`;
    this.container.appendChild(el);
    return el;
  }
  async updateChart(id, values) {
    if (!values || values.length === 0)
      return;
    const canvas = document.getElementById(`menu-canvas-${id}`);
    if (!canvas)
      return;
    const ctx = canvas.getContext("2d");
    ctx.fillStyle = theme.background;
    ctx.fillRect(0, 0, canvas.width, canvas.height);
    const width = canvas.width / values.length;
    const max = 1 + Math.max(...values);
    const height = canvas.height / max;
    for (const i in values) {
      const gradient = ctx.createLinearGradient(0, (max - values[i]) * height, 0, 0);
      gradient.addColorStop(0.1, theme.chartColor);
      gradient.addColorStop(0.4, theme.background);
      ctx.fillStyle = gradient;
      ctx.fillRect(i * width, 0, width - 4, canvas.height);
      ctx.fillStyle = theme.background;
      ctx.font = `${width / 1.5}px "Segoe UI"`;
      ctx.fillText(Math.round(values[i]), i * width + 1, canvas.height - 1, width - 1);
    }
  }
}
var menu_default = Menu;

// demo/browser.js
const human = new uG();
const userConfig = {};
const ui = {
  baseColor: "rgba(173, 216, 230, 0.3)",
  baseBackground: "rgba(50, 50, 50, 1)",
  baseLabel: "rgba(173, 216, 230, 0.9)",
  baseFontProto: 'small-caps {size} "Segoe UI"',
  baseLineWidth: 12,
  baseLineHeightProto: 2,
  crop: true,
  columns: 2,
  busy: false,
  facing: true,
  useWorker: false,
  worker: "demo/worker.js",
  samples: ["../assets/sample6.jpg", "../assets/sample1.jpg", "../assets/sample4.jpg", "../assets/sample5.jpg", "../assets/sample3.jpg", "../assets/sample2.jpg"],
  drawBoxes: true,
  drawPoints: false,
  drawPolygons: true,
  fillPolygons: false,
  useDepth: true,
  console: true,
  maxFrames: 10,
  modelsPreload: true,
  modelsWarmup: true,
  menuWidth: 0,
  menuHeight: 0,
  camera: {},
  fps: []
};
let menu2;
let menuFX;
let worker;
let timeStamp;
function str(...msg) {
  if (!Array.isArray(msg))
    return msg;
  let line = "";
  for (const entry of msg) {
    if (typeof entry === "object")
      line += JSON.stringify(entry).replace(/{|}|"|\[|\]/g, "").replace(/,/g, ", ");
    else
      line += entry;
  }
  return line;
}
const log = (...msg) => {
  if (ui.console)
    console.log(...msg);
};
const status = (msg) => {
  document.getElementById("status").innerText = msg;
};
function drawResults(input, result, canvas) {
  const elapsed = performance.now() - timeStamp;
  ui.fps.push(1e3 / elapsed);
  if (ui.fps.length > ui.maxFrames)
    ui.fps.shift();
  if (input.srcObject) {
    if (elapsed > 33)
      requestAnimationFrame(() => runHumanDetect(input, canvas));
    else
      setTimeout(() => runHumanDetect(input, canvas), 33 - elapsed);
  }
  menu2.updateChart("FPS", ui.fps);
  const ctx = canvas.getContext("2d");
  ctx.fillStyle = ui.baseBackground;
  ctx.fillRect(0, 0, canvas.width, canvas.height);
  if (result.canvas) {
    if (result.canvas.width !== canvas.width)
      canvas.width = result.canvas.width;
    if (result.canvas.height !== canvas.height)
      canvas.height = result.canvas.height;
    ctx.drawImage(result.canvas, 0, 0, result.canvas.width, result.canvas.height, 0, 0, result.canvas.width, result.canvas.height);
  } else {
    ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);
  }
  draw_default.face(result.face, canvas, ui, human.facemesh.triangulation);
  draw_default.body(result.body, canvas, ui);
  draw_default.hand(result.hand, canvas, ui);
  draw_default.gesture(result.gesture, canvas, ui);
  const engine = human.tf.engine();
  const gpu = engine.backendInstance ? `gpu: ${(engine.backendInstance.numBytesInGPU ? engine.backendInstance.numBytesInGPU : 0).toLocaleString()} bytes` : "";
  const memory = `system: ${engine.state.numBytes.toLocaleString()} bytes ${gpu} | tensors: ${engine.state.numTensors.toLocaleString()}`;
  const processing = result.canvas ? `processing: ${result.canvas.width} x ${result.canvas.height}` : "";
  const avg = Math.trunc(10 * ui.fps.reduce((a, b) => a + b) / ui.fps.length) / 10;
  document.getElementById("log").innerText = `
    video: ${ui.camera.name} | facing: ${ui.camera.facing} | resolution: ${ui.camera.width} x ${ui.camera.height} ${processing}
    backend: ${human.tf.getBackend()} | ${memory}
    performance: ${str(result.performance)} FPS:${avg}
  `;
}
async function setupCamera() {
  if (ui.busy)
    return null;
  ui.busy = true;
  const video = document.getElementById("video");
  const canvas = document.getElementById("canvas");
  const output = document.getElementById("log");
  const live = video.srcObject ? video.srcObject.getVideoTracks()[0].readyState === "live" && video.readyState > 2 && !video.paused : false;
  let msg = "";
  status("setting up camera");
  if (!navigator.mediaDevices) {
    msg = "camera access not supported";
    output.innerText += `
${msg}`;
    log(msg);
    status(msg);
    return null;
  }
  let stream;
  const constraints = {
    audio: false,
    video: {
      facingMode: ui.facing ? "user" : "environment",
      resizeMode: ui.crop ? "crop-and-scale" : "none",
      width: {ideal: window.innerWidth},
      height: {ideal: window.innerHeight}
    }
  };
  try {
    stream = await navigator.mediaDevices.getUserMedia(constraints);
  } catch (err) {
    if (err.name === "PermissionDeniedError")
      msg = "camera permission denied";
    else if (err.name === "SourceUnavailableError")
      msg = "camera not available";
    else
      msg = "camera error";
    output.innerText += `
${msg}`;
    status(msg);
    log(err);
  }
  if (stream)
    video.srcObject = stream;
  else
    return null;
  const track = stream.getVideoTracks()[0];
  const settings = track.getSettings();
  ui.camera = {name: track.label, width: settings.width, height: settings.height, facing: settings.facingMode === "user" ? "front" : "back"};
  return new Promise((resolve) => {
    video.onloadeddata = async () => {
      video.width = video.videoWidth;
      video.height = video.videoHeight;
      canvas.width = video.width;
      canvas.height = video.height;
      canvas.style.width = canvas.width > canvas.height ? "100vw" : "";
      canvas.style.height = canvas.width > canvas.height ? "" : "100vh";
      ui.menuWidth.input.setAttribute("value", video.width);
      ui.menuHeight.input.setAttribute("value", video.height);
      const size = 14 + 6 * canvas.width / window.innerWidth;
      ui.baseFont = ui.baseFontProto.replace(/{size}/, `${size}px`);
      if (live)
        video.play();
      ui.busy = false;
      status("");
      resolve(video);
    };
  });
}
function webWorker(input, image, canvas) {
  if (!worker) {
    log("creating worker thread");
    worker = new Worker(ui.worker, {type: "module"});
    worker.warned = false;
    worker.addEventListener("message", (msg) => {
      if (!worker.warned) {
        log("warning: cannot transfer canvas from worked thread");
        log("warning: image will not show filter effects");
        worker.warned = true;
      }
      drawResults(input, msg.data.result, canvas);
    });
  }
  worker.postMessage({image: image.data.buffer, width: canvas.width, height: canvas.height}, [image.data.buffer]);
}
function runHumanDetect(input, canvas) {
  var _a;
  timeStamp = performance.now();
  const live = input.srcObject && input.srcObject.getVideoTracks()[0].readyState === "live" && input.readyState > 2 && !input.paused;
  if (!live && input.srcObject) {
    if (input.paused)
      log("camera paused");
    else if (input.srcObject.getVideoTracks()[0].readyState === "live" && input.readyState <= 2)
      setTimeout(() => runHumanDetect(input, canvas), 500);
    else
      log(`camera not ready: track state: ${(_a = input.srcObject) == null ? void 0 : _a.getVideoTracks()[0].readyState} stream state: ${input.readyState}`);
    return;
  }
  status("");
  if (ui.useWorker) {
    const offscreen = new OffscreenCanvas(canvas.width, canvas.height);
    const ctx = offscreen.getContext("2d");
    ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);
    const data = ctx.getImageData(0, 0, canvas.width, canvas.height);
    webWorker(input, data, canvas, userConfig);
  } else {
    human.detect(input, userConfig).then((result) => {
      if (result.error)
        log(result.error);
      else
        drawResults(input, result, canvas);
    });
  }
}
async function processImage(input) {
  timeStamp = performance.now();
  return new Promise((resolve) => {
    const image = new Image();
    image.onload = async () => {
      log("Processing image:", image.src);
      const canvas = document.getElementById("canvas");
      image.width = image.naturalWidth;
      image.height = image.naturalHeight;
      canvas.width = human.config.filter.width && human.config.filter.width > 0 ? human.config.filter.width : image.naturalWidth;
      canvas.height = human.config.filter.height && human.config.filter.height > 0 ? human.config.filter.height : image.naturalHeight;
      const result = await human.detect(image, userConfig);
      drawResults(image, result, canvas);
      const thumb = document.createElement("canvas");
      thumb.className = "thumbnail";
      thumb.width = window.innerWidth / (ui.columns + 0.1);
      thumb.height = canvas.height / (window.innerWidth / thumb.width);
      const ctx = thumb.getContext("2d");
      ctx.drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, thumb.width, thumb.height);
      document.getElementById("samples-container").appendChild(thumb);
      image.src = "";
      resolve(true);
    };
    image.src = input;
  });
}
async function detectVideo() {
  human.config.videoOptimized = true;
  document.getElementById("samples-container").style.display = "none";
  document.getElementById("canvas").style.display = "block";
  const video = document.getElementById("video");
  const canvas = document.getElementById("canvas");
  ui.baseLineHeight = ui.baseLineHeightProto;
  if (video.srcObject !== null && !video.paused) {
    document.getElementById("play").style.display = "block";
    status("paused");
    video.pause();
  } else {
    await setupCamera();
    document.getElementById("play").style.display = "none";
    status("");
    video.play();
  }
  runHumanDetect(video, canvas);
}
async function detectSampleImages() {
  document.getElementById("play").style.display = "none";
  human.config.videoOptimized = false;
  const size = 12 + Math.trunc(12 * ui.columns * window.innerWidth / document.body.clientWidth);
  ui.baseFont = ui.baseFontProto.replace(/{size}/, `${size}px`);
  ui.baseLineHeight = ui.baseLineHeightProto * ui.columns;
  document.getElementById("canvas").style.display = "none";
  document.getElementById("samples-container").style.display = "block";
  log("Running detection of sample images");
  status("processing images");
  document.getElementById("samples-container").innerHTML = "";
  for (const sample of ui.samples)
    await processImage(sample);
  status("");
}
function setupMenu() {
  menu2 = new menu_default(document.body, "", {top: "1rem", right: "1rem"});
  const btn = menu2.addButton("start video", "pause video", () => detectVideo());
  menu2.addButton("process images", "process images", () => detectSampleImages());
  document.getElementById("play").addEventListener("click", () => btn.click());
  menu2.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
  menu2.addList("backend", ["cpu", "webgl", "wasm", "webgpu"], human.config.backend, (val) => human.config.backend = val);
  menu2.addBool("async operations", human.config, "async", (val) => human.config.async = val);
  menu2.addBool("enable profiler", human.config, "profile", (val) => human.config.profile = val);
  menu2.addBool("memory shield", human.config, "deallocate", (val) => human.config.deallocate = val);
  menu2.addBool("use web worker", ui, "useWorker");
  menu2.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
  menu2.addLabel("enabled models");
  menu2.addBool("face detect", human.config.face, "enabled");
  menu2.addBool("face mesh", human.config.face.mesh, "enabled");
  menu2.addBool("face iris", human.config.face.iris, "enabled");
  menu2.addBool("face age", human.config.face.age, "enabled");
  menu2.addBool("face gender", human.config.face.gender, "enabled");
  menu2.addBool("face emotion", human.config.face.emotion, "enabled");
  menu2.addBool("body pose", human.config.body, "enabled");
  menu2.addBool("hand pose", human.config.hand, "enabled");
  menu2.addBool("gesture analysis", human.config.gesture, "enabled");
  menu2.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
  menu2.addLabel("model parameters");
  menu2.addRange("max objects", human.config.face.detector, "maxFaces", 1, 50, 1, (val) => {
    human.config.face.detector.maxFaces = parseInt(val);
    human.config.body.maxDetections = parseInt(val);
    human.config.hand.maxHands = parseInt(val);
  });
  menu2.addRange("skip frames", human.config.face.detector, "skipFrames", 0, 50, 1, (val) => {
    human.config.face.detector.skipFrames = parseInt(val);
    human.config.face.emotion.skipFrames = parseInt(val);
    human.config.face.age.skipFrames = parseInt(val);
    human.config.hand.skipFrames = parseInt(val);
  });
  menu2.addRange("min confidence", human.config.face.detector, "minConfidence", 0, 1, 0.05, (val) => {
    human.config.face.detector.minConfidence = parseFloat(val);
    human.config.face.gender.minConfidence = parseFloat(val);
    human.config.face.emotion.minConfidence = parseFloat(val);
    human.config.hand.minConfidence = parseFloat(val);
  });
  menu2.addRange("score threshold", human.config.face.detector, "scoreThreshold", 0.1, 1, 0.05, (val) => {
    human.config.face.detector.scoreThreshold = parseFloat(val);
    human.config.hand.scoreThreshold = parseFloat(val);
    human.config.body.scoreThreshold = parseFloat(val);
  });
  menu2.addRange("overlap", human.config.face.detector, "iouThreshold", 0.1, 1, 0.05, (val) => {
    human.config.face.detector.iouThreshold = parseFloat(val);
    human.config.hand.iouThreshold = parseFloat(val);
  });
  menu2.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
  menu2.addChart("FPS", "FPS");
  menuFX = new menu_default(document.body, "", {top: "1rem", right: "18rem"});
  menuFX.addLabel("ui options");
  menuFX.addBool("crop & scale", ui, "crop", () => setupCamera());
  menuFX.addBool("camera front/back", ui, "facing", () => setupCamera());
  menuFX.addBool("use 3D depth", ui, "useDepth");
  menuFX.addBool("draw boxes", ui, "drawBoxes");
  menuFX.addBool("draw polygons", ui, "drawPolygons");
  menuFX.addBool("Fill Polygons", ui, "fillPolygons");
  menuFX.addBool("draw points", ui, "drawPoints");
  menuFX.addHTML('<hr style="min-width: 200px; border-style: inset; border-color: dimgray">');
  menuFX.addLabel("image processing");
  menuFX.addBool("enabled", human.config.filter, "enabled");
  ui.menuWidth = menuFX.addRange("image width", human.config.filter, "width", 0, 3840, 10, (val) => human.config.filter.width = parseInt(val));
  ui.menuHeight = menuFX.addRange("image height", human.config.filter, "height", 0, 2160, 10, (val) => human.config.filter.height = parseInt(val));
  menuFX.addRange("brightness", human.config.filter, "brightness", -1, 1, 0.05, (val) => human.config.filter.brightness = parseFloat(val));
  menuFX.addRange("contrast", human.config.filter, "contrast", -1, 1, 0.05, (val) => human.config.filter.contrast = parseFloat(val));
  menuFX.addRange("sharpness", human.config.filter, "sharpness", 0, 1, 0.05, (val) => human.config.filter.sharpness = parseFloat(val));
  menuFX.addRange("blur", human.config.filter, "blur", 0, 20, 1, (val) => human.config.filter.blur = parseInt(val));
  menuFX.addRange("saturation", human.config.filter, "saturation", -1, 1, 0.05, (val) => human.config.filter.saturation = parseFloat(val));
  menuFX.addRange("hue", human.config.filter, "hue", 0, 360, 5, (val) => human.config.filter.hue = parseInt(val));
  menuFX.addRange("pixelate", human.config.filter, "pixelate", 0, 32, 1, (val) => human.config.filter.pixelate = parseInt(val));
  menuFX.addBool("negative", human.config.filter, "negative");
  menuFX.addBool("sepia", human.config.filter, "sepia");
  menuFX.addBool("vintage", human.config.filter, "vintage");
  menuFX.addBool("kodachrome", human.config.filter, "kodachrome");
  menuFX.addBool("technicolor", human.config.filter, "technicolor");
  menuFX.addBool("polaroid", human.config.filter, "polaroid");
}
async function main() {
  log("Human: demo starting ...");
  setupMenu();
  document.getElementById("log").innerText = `Human: version ${human.version} TensorFlow/JS: version ${human.tf.version_core}`;
  if (ui.modelsPreload) {
    status("loading");
    await human.load(userConfig);
  }
  if (ui.modelsWarmup) {
    status("initializing");
    await human.warmup(userConfig);
  }
  status("human: ready");
  document.getElementById("loader").style.display = "none";
  document.getElementById("play").style.display = "block";
}
window.onload = main;
window.onresize = setupCamera;
//# sourceMappingURL=demo-browser-index.js.map