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human
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human/dist/demo-browser-index.js

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/*
Human library
homepage: <https://github.com/vladmandic/human>
author: <https://github.com/vladmandic>'
*/
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r=++this.pendingBackendInitId,a=n.then(s=>r<this.pendingBackendInitId?!1:(this.registry[e]=s,this.pendingBackendInit=null,!0)).catch(s=>(r<this.pendingBackendInitId||(this.pendingBackendInit=null,console.warn(`Initialization of backend ${e} failed`),console.warn(s.stack||s.message)),!1));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return console.warn(`Initialization of backend ${e} failed`),console.warn(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t],{success:r,asyncInit:a}=this.initializeBackend(n);if(a||r)return{name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),s=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,s),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function 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this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let r=this.backend.numDataIds(),a=0;n.forEach(o=>{a+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-t-a-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=Dm(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Dm(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let A=qh(p,this.backendName);M(A!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),i=()=>{let 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this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,c,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,c,t,h,n,u),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(p=>c[p]!=null?c[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=Cf(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let 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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*bm(e.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:n})),e instanceof bu||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;let t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,e.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),e.dtype!=="complex64"&&e.dtype!=="string"){let n=e.size*bm(e.dtype);this.state.numBytes-=n}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let 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s=this.state.activeScope.track[a];!s.kept&&!n.has(s.id)&&s.dispose()}let r=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(a=>{!a.kept&&a.scopeId===r.id&&this.track(a)})}gradients(e,t,n,r=!1){if(M(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));M(a instanceof Qe,()=>"The result y returned by f() must be a tensor.");let s=c9(this.state.activeTape,t,a);if(!r&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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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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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),
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#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)));
}
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#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));
}
`,l=`
uniform float INFINITY;
bool isinf(float val) {
return abs(val) == INFINITY;
}
bvec4 isinf(vec4 val) {
return equal(abs(val), vec4(INFINITY));
}
`,c=`
int round(float value) {
return int(floor(value + 0.5));
}
ivec4 round(vec4 value) {
return ivec4(floor(value + vec4(0.5)));
}
`),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:c}}function ui(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function TA(e){let t=v.computeStrides(e).map(n=>n.toString());return`
int getFlatIndex(ivec3 coords) {
return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
}
`}var Rw=`
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;
}
`,HO=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=oc.DENSE;let t=uc(e),n=on();this.outputShape=e,this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${ui(["r","c","d"],e)}
return ivec3(r, c, d);
}
void main() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = 4 * (resTexRC.x * ${t[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);
}
${n.output} = result;
}
`}},jO=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=oc.DENSE;let t=uc(e),n=on();this.outputShape=e,this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${ui(["r","c","d"],e)}
return ivec3(r, c, d);
}
void main() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = 4 * (resTexRC.x * ${t[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));
}
${n.output} = result;
}
`}},GO=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Hn.DOWNLOAD;let t=on();this.outputShape=e,this.userCode=`
${Rw}
void main() {
float x = getAAtOutCoords();
${t.output} = encode_float(x);
}
`}},qO=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Hn.DOWNLOAD;let t=on();this.outputShape=e,this.userCode=`
${Rw}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${t.output} = encode_float(x);
}
`}},XO=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=on(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
${TA(e)}
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 = ${r.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];
}
${r.output} = vec4(${i}, 0., 0., 0.);
}
`}},KO=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=on(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let c=0;c<=1;c++){let u=l*2+c;i+=`
localCoords = coords;
if(localCoords[2] + ${c} < ${e[2]}) {
localCoords[2] += ${c};
if(localCoords[1] + ${l} < ${e[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 = ${r.texture2D}(A, uv);
if(offset == 0) {
result[${u}] = values[0];
} else if(offset == 1) {
result[${u}] = values[1];
} else if(offset == 2) {
result[${u}] = values[2];
} else {
result[${u}] = values[3];
}
}
}
`}this.userCode=`
${TA(e)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${i}
${r.output} = ${o};
}
`}},T0={};ze(T0,{bindVertexProgramAttributeStreams:()=>Ww,createBufferFromOutputTexture:()=>Uw,createFloat16MatrixTexture:()=>Ow,createFloat16PackedMatrixTexture:()=>Lw,createFloat32MatrixTexture:()=>Dw,createIndexBuffer:()=>$w,createPackedMatrixTexture:()=>Pw,createUnsignedBytesMatrixTexture:()=>zw,createVertexBuffer:()=>Mw,createVertexShader:()=>Fw,downloadByteEncodedFloatMatrixFromOutputTexture:()=>jw,downloadFloat32MatrixFromBuffer:()=>Hw,downloadMatrixFromPackedOutputTexture:()=>qw,downloadPackedMatrixFromBuffer:()=>Gw,getInternalFormatForFloat16MatrixTexture:()=>CA,getInternalFormatForFloat16PackedMatrixTexture:()=>MA,getInternalFormatForFloat32MatrixTexture:()=>EA,getInternalFormatForPackedMatrixTexture:()=>FA,getInternalFormatForUnsignedBytesMatrixTexture:()=>RA,uploadDenseMatrixToTexture:()=>Bw,uploadPixelDataToTexture:()=>Vw});function Fw(e){let t=on(),n=`${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 uw(e,n)}function Mw(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return pw(e,t)}function $w(e){let t=new Uint16Array([0,1,2,2,1,3]);return fw(e,t)}function cc(e,t,n,r,a,s){Aw(t,n);let i=mw(e),o=e.TEXTURE_2D;return _e(e,()=>e.bindTexture(o,i)),_e(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),_e(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),_e(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),_e(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),_e(e,()=>e.texImage2D(o,0,r,t,n,0,a,s,null)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,null)),i}function EA(e){return e.internalFormatFloat}function Dw(e,t,n,r){let[a,s]=lc(t,n);return cc(e,a,s,EA(r),r.textureFormatFloat,e.FLOAT)}function CA(e){return e.internalFormatHalfFloat}function Ow(e,t,n,r){let[a,s]=lc(t,n);return cc(e,a,s,CA(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function RA(e){return e.downloadTextureFormat}function zw(e,t,n,r){let[a,s]=lc(t,n);return cc(e,a,s,RA(r),e.RGBA,e.UNSIGNED_BYTE)}function FA(e){return e.internalFormatPackedFloat}function Pw(e,t,n,r){let[a,s]=ml(t,n);return cc(e,a,s,FA(r),e.RGBA,e.FLOAT)}function MA(e){return e.internalFormatPackedHalfFloat}function Lw(e,t,n,r){let[a,s]=ml(t,n);return cc(e,a,s,MA(r),e.RGBA,r.textureTypeHalfFloat)}function Ww(e,t,n){let r=0,a=3*4,s=3*4+2*4;return _e(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),bA(e,t,"clipSpacePos",n,3,s,r)&&bA(e,t,"uv",n,2,s,a)}function Bw(e,t,n,r,a,s){_e(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;a instanceof Uint8Array?(i=new Uint8Array(n*r*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*r*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(a),_e(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,r,0,e.RGBA,o,i)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function Vw(e,t,n){_e(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?_e(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):_e(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),_e(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function Uw(e,t,n,r){let a=e.createBuffer();_e(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,a));let s=4*4*t*n;return _e(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),_e(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),_e(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),a}function Hw(e,t,n){let r=e,a=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,a),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),a}function jw(e,t,n,r){let[a,s]=lc(t,n),i=4,o=new Uint8Array(OO(t*n,i));return _e(e,()=>e.readPixels(0,0,a,s,r.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function Gw(e,t,n,r,a,s,i,o){let l=e,c=new Float32Array(zO(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,c),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),c}function qw(e,t,n){let r=new Float32Array(t*n*4);return _e(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)),r}var xm=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=Q().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,gm(t,e)):this.gl=Wr(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(Q().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=ac(this.gl,a),Un(this.gl,s))this.textureHalfFloatExtension=ac(this.gl,s);else if(Q().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(n),Un(this.gl,r))this.colorBufferHalfFloatExtension=ac(this.gl,r);else if(Q().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(n="EXT_color_buffer_float",Un(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Un(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=Mw(this.gl),this.indexBuffer=$w(this.gl),this.framebuffer=yw(this.gl),this.textureConfig=NA(this.gl,this.textureHalfFloatExtension)}get debug(){return Q().getBool("DEBUG")}dispose(){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.");let e=this.gl;_e(e,()=>e.finish()),_e(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),_e(e,()=>e.deleteFramebuffer(this.framebuffer)),_e(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),_e(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),_e(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),Dw(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),Ow(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),zw(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),Vw(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),Bw(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return 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_e(t,()=>t.attachShader(a,r)),_e(t,()=>t.attachShader(a,n)),dw(t,a),this.debug&&tp(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=Ww(t,this.program,this.vertexBuffer)),a}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&_e(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&tp(this.gl,this.program),_e(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?xw(this.gl,e,t):ww(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),_e(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),_w(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[r,a]=ml(t,n);this.setOutputMatrixTextureDriver(e,r,a)}setOutputMatrixWriteRegion(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}setOutputPackedMatrixWriteRegion(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&tp(this.gl,this.program),sc(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),_e(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),_e(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=ac(this.gl,Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await 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`),i=e.map(p=>JO(p,t,r)).join(`
`),o=t.texShape,l=on(),c=ez(l),u,h,d=rz(l);return t.isPacked?(u=YO(t.logicalShape,o),h=nz(l)):(u=QO(t.logicalShape,o),h=tz(l)),r&&(d+=az),[d,c,h,s,u,i,n].join(`
`)}function Al(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return iz(e);case 1:return oz(e);case 2:return lz(e);case 3:return uz(e);case 4:return cz(e);case 5:return hz(e);case 6:return dz(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function Kw(e){switch(e.shapeInfo.logicalShape.length){case 0:return pz(e);case 1:return fz(e);case 2:return mz(e);case 3:return Az(e);default:return yz(e)}}function JO(e,t,n=!1){let r="";n?r+=Kw(e):r+=Al(e);let a=e.shapeInfo.logicalShape,s=t.logicalShape;return a.length<=s.length&&(n?r+=gz(e,t):r+=xz(e,t)),r}function YO(e,t){switch(e.length){case 0:return Zw();case 1:return wz(e,t);case 2:return vz(e,t);case 3:return _z(e,t);default:return bz(e,t)}}function QO(e,t){switch(e.length){case 0:return Zw();case 1:return kz(e,t);case 2:return Ez(e,t);case 3:return Iz(e,t);case 4:return Nz(e,t);case 5:return Sz(e,t);case 6:return Tz(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function ez(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function tz(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function nz(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function rz(e){return`${e.version}
precision highp float;
precision highp int;
precision highp sampler2D;
${e.varyingFs} vec2 resultUV;
${e.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;
${e.defineSpecialNaN}
${e.defineSpecialInf}
${e.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);
}
${Cz}
${Rz}
${Fz}
`}var Cz=`
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);
}
`,Rz=`
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);
}
`,Fz=`
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);
}
`,az=`
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 Zw(){return`
int getOutputCoords() {
return 0;
}
`}function wz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
int getOutputCoords() {
return 2 * int(resultUV.x * ${n[1]}.0);
}
`:n[1]===1?`
int getOutputCoords() {
return 2 * int(resultUV.y * ${n[0]}.0);
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
}
`}function kz(e,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 * ${t[1]} + resTexRC.y;
}
`}function _z(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int b = index / ${a};
index -= b * ${a};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec3(b, r, c);
}
`}function Iz(e,t){let n=ui(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec3(r, c, d);
}
`}function bz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
int b${l} = index / ${s};
index -= b${l} * ${s};
`+i,o=`b${l}, `+o;return`
ivec${e.length} getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
${i}
int b = index / ${a};
index -= b * ${a};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec${e.length}(${o});
}
`}function Nz(e,t){let n=ui(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec4(r, c, d, d2);
}
`}function Sz(e,t){let n=ui(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function Tz(e,t){let n=ui(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function vz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
}
`;let r=Math.ceil(e[1]/2);return`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec2(r, c);
}
`}function Ez(e,t){return v.arraysEqual(e,t)?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
}
`:e[1]===1?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(index, 0);
}
`:e[0]===1?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${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 / ${e[1]};
int c = index - r * ${e[1]};
return ivec2(r, c);
}
`}function ci(e){return`offset${e}`}function pz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=on();return`
vec4 ${n}() {
return ${r.texture2D}(${t}, halfCR);
}
`}function iz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
float ${n}() {
return sampleTexture(${t}, halfCR);
}
`;let[s,i]=e.shapeInfo.texShape,o=ci(t);return`
float ${n}() {
vec2 uv = uvFromFlat(${s}, ${i}, ${o});
return sampleTexture(${t}, uv);
}
`}function fz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=on();return`
vec4 ${n}(int index) {
vec2 uv = packedUVfrom1D(
${a[0]}, ${a[1]}, index);
return ${s.texture2D}(${t}, uv);
}
`}function oz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
float ${n}(int index) {
${yl(e)}
}
`;let r=e.shapeInfo.texShape,a=r[0],s=r[1];if(s===1&&a===1)return`
float ${n}(int index) {
return sampleTexture(${t}, halfCR);
}
`;let i=ci(t);return s===1?`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${a}.0);
return sampleTexture(${t}, uv);
}
`:a===1?`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${i}) + 0.5) / ${s}.0, 0.5);
return sampleTexture(${t}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = uvFromFlat(${a}, ${s}, index + ${i});
return sampleTexture(${t}, uv);
}
`}function mz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=on();if(a!=null&&v.arraysEqual(t,a))return`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${s}.0);
return ${o.texture2D}(${n}, uv);
}
`;let l=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],c=Math.ceil(t[1]/2);return`
vec4 ${r}(int row, int col) {
vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
return ${o.texture2D}(${n}, uv);
}
`}function lz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${d}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`}let{newShape:s,keptDims:i}=v.squeezeShape(t),o=s;if(o.length<t.length){let h=gl(e,o),d=["row","col"];return`
${Al(h)}
float ${r}(int row, int col) {
return ${r}(${xl(d,i)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${t[1]}, 1)));
${yl(e)}
}
`;let l=a[0],c=a[1],u=ci(n);return c===1?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${u}), vec3(${t[1]}, 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
return sampleTexture(${n}, uv);
}
`:l===1?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${u}), vec3(${t[1]}, 1, 1));
vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${t[1]} + col + ${u};
vec2 uv = uvFromFlat(${l}, ${c}, index);
return sampleTexture(${n}, uv);
}
`}function Az(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=gl(e,h),f=["b","row","col"];return`
${Kw(p)}
vec4 ${r}(int b, int row, int col) {
return ${r}(${xl(f,d)});
}
`}let i=s[0],o=s[1],l=Math.ceil(t[2]/2),c=l*Math.ceil(t[1]/2),u=on();return`
vec4 ${r}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${i}, ${o}, ${c}, ${l}, b, row, col);
return ${u.texture2D}(${n}, uv);
}
`}function uz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=gl(e,l),m=["row","col","depth"];return`
${Al(f)}
float ${r}(int row, int col, int depth) {
return ${r}(${xl(m,o)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth) {
int index = round(dot(vec3(row, col, depth),
vec3(${a}, ${s}, 1)));
${yl(e)}
}
`;let c=e.shapeInfo.texShape,u=c[0],h=c[1],d=e.shapeInfo.flatOffset;if(h===a&&d==null)return`
float ${r}(int row, int col, int depth) {
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(${s}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${u}.0);
return sampleTexture(${n}, uv);
}
`;if(h===s&&d==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(${h}.0, ${u}.0);
return sampleTexture(${n}, uv);
}
`;let p=ci(n);return`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${a} + col * ${s} + depth + ${p};
vec2 uv = uvFromFlat(${u}, ${h}, index);
return sampleTexture(${n}, uv);
}
`}function yz(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],c=Math.ceil(t[n-1]/2),u=c*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${u} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,u*=t[n-f-1],d=`b${f} * ${u} + `+d;let p=on();return`
vec4 ${a}(${h}) {
int index = ${d};
int texR = index / ${l};
int texC = index - texR * ${l};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${o});
return ${p.texture2D}(${r}, uv);
}
`}function cz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=gl(e,o),m=["row","col","depth","depth2"];return`
${Al(f)}
float ${r}(int row, int col, int depth, int depth2) {
return ${r}(${xl(m,l)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth, int depth2) {
int index = round(dot(vec4(row, col, depth, depth2),
vec4(${i}, ${s}, ${a}, 1)));
${yl(e)}
}
`;let c=e.shapeInfo.flatOffset,u=e.shapeInfo.texShape,h=u[0],d=u[1];if(d===i&&c==null)return`
float ${r}(int row, int col, int depth, int depth2) {
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(${s}, ${a}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${d}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;if(d===a&&c==null)return`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${t[1]*t[2]}, ${t[2]}, 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${d}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;let p=ci(n);return`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${i} + col * ${s} +
depth * ${a} + depth2;
vec2 uv = uvFromFlat(${h}, ${d}, index + ${p});
return sampleTexture(${n}, uv);
}
`}function hz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:c}=v.squeezeShape(t);if(l.length<t.length){let m=gl(e,l),A=["row","col","depth","depth2","depth3"];return`
${Al(m)}
float ${r}(int row, int col, int depth, int depth2, int depth3) {
return ${r}(${xl(A,c)});
}
`}if(e.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}, ${i}, ${s}, ${a})) +
depth3;
${yl(e)}
}
`;let u=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],p=h[1];if(p===o&&u==null)return`
float ${r}(int row, int col, int depth, int depth2, int depth3) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${i}, ${s}, ${a}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${d}.0);
return sampleTexture(${n}, uv);
}
`;if(p===a&&u==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]}, ${t[3]}, 1));
int texC = depth3;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${d}.0);
return sampleTexture(${n}, uv);
}
`;let f=ci(n);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 * ${i} + depth * ${s} +
depth2 * ${a} + depth3 + ${f};
vec2 uv = uvFromFlat(${d}, ${p}, index);
return sampleTexture(${n}, uv);
}
`}function dz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=gl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
${Al(A)}
float ${r}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${r}(${xl(y,s)});
}
`}let i=t[5],o=t[4]*i,l=t[3]*o,c=t[2]*l,u=t[1]*c;if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${u}, ${c}, ${l}, ${o})) +
dot(
vec2(depth3, depth4),
vec2(${i}, 1)));
${yl(e)}
}
`;let h=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,p=d[0],f=d[1];if(f===u&&h==null)return`
float ${r}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${c}, ${l}, ${o}, ${i})) +
float(depth4);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`;if(f===i&&h==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]},
${t[4]})) + float(depth3);
int texC = depth4;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`;let m=ci(n);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 * ${u} + col * ${c} + depth * ${l} +
depth2 * ${o} + depth3 * ${i} + depth4 + ${m};
vec2 uv = uvFromFlat(${p}, ${f}, index);
return sampleTexture(${n}, uv);
}
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for (int i = 0; i < ${n}; i++) {
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return ${t}[i];
}
}
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vec4 ${a}() {
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${u}
vec4 outputValue = get${r}(${d});
${p}
}
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float ${a}() {
return sampleTexture(${n}, resultUV);
}
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${d}
return get${r}(${f});
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`}function ht(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function gl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function xl(e,t){return t.map(n=>e[n]).join(", ")}function Mz(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=sz(s,o,a,t.packedInputs),c=e.createProgram(l),u=null,h=e.getUniformLocation(c,"NAN",!1);Q().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(c,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(c,f,m),d[`offset${f}`]=e.getUniformLocation(c,`offset${f}`,m)}return{program:t,source:l,webGLProgram:c,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:u,nanLoc:h}}function Jw(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function $z(e,t,n,r,a){Jw(t.inShapeInfos,n),Jw([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),Q().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let c=t.program.variableNames[l],u=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`];if(u!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(u,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(u,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,u,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function Dz(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:Oz,bincountImpl:Yw,bincountReduceImpl:zz,ceilImpl:Pz,concatImpl:Lz,expImpl:Wz,expm1Impl:Bz,floorImpl:Vz,gatherV2Impl:Uz,greaterImpl:Hz,lessImpl:jz,linSpaceImpl:Gz,logImpl:qz,maxImpl:Xz,maximumImpl:Kz,minimumImpl:Zz,multiplyImpl:Jz,negImpl:Yz,prodImpl:Qz,rangeImpl:eP,rsqrtImpl:tP,simpleAbsImpl:Qw,sliceImpl:nP,stridedSliceImpl:rP,subImpl:aP,tileImpl:sP,topKImpl:iP,transposeImpl:$A,uniqueImpl:oP}=ym;function e_(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function ln(e,t){return t===1?[e]:e_(e,t)}function lP(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var dP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
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`;else{let n=ln("rc",t),r=ht(t),a=uP(t,e,n),s=cP(t,e[e.length-1],e[e.length-2],n),i=hP(e,n);this.userCode=`
void main() {
${r} rc = getOutputCoords();
if(${a}) {
setOutput(vec4(0));
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${s}
setOutput(vec4(${i}));
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}
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int rp1 = r + 1;
int cp1 = c + 1;
bool cEdge = cp1 >= ${t};
bool rEdge = rp1 >= ${n};
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cEdge ? 0. : getA(${r[1]}),
rEdge ? 0. : getA(${r[2]}),
rEdge || cEdge ? 0. : getA(${r[3]})`}var t_=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
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${r>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
int flatIndex = getFlatIndex(thisRC);
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
result[${r}] =
getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
${r>0?"}":""}
`}this.userCode=`
${fP(t)}
${TA(e)}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = vec4(0.);
ivec3 thisRC;
int rows = ${e[1]};
int cols = ${e[2]};
${n}
setOutput(result);
}
`}};function fP(e){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${ui(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var mP=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=r_(t,n),a=a_(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=n_(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===Kt.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===Kt.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===Kt.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===Kt.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===Kt.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=r_(n,r),s=a_(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=n_(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=Q().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],c=l.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function AP(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function n_(e,t,n,r,a){let s=yP(t,r),i;if(a){let[l,c]=ml(e[0],e[1]);i=l*c}else{let[l,c]=lc(e[0],e[1]);i=l*c}let o=AP(n,s);return i*o}function yP(e,t){switch(e){case Kt.PACKED_2X2_FLOAT32:return FA(t);case Kt.PACKED_2X2_FLOAT16:return MA(t);case Kt.UNPACKED_FLOAT32:return EA(t);case Kt.UNPACKED_FLOAT16:return CA(t);case Kt.PACKED_4X1_UNSIGNED_BYTE:return RA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function gP(e){return Q().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?Kt.PACKED_2X2_FLOAT32:Kt.UNPACKED_FLOAT32:e?Kt.PACKED_2X2_FLOAT16:Kt.UNPACKED_FLOAT16}function r_(e,t){if(e===Hn.UPLOAD)return Kt.PACKED_2X2_FLOAT32;if(e===Hn.RENDER||e==null)return gP(t);if(e===Hn.DOWNLOAD||e===Hn.PIXELS)return Kt.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function a_(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Ra=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
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result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
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vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
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void main() {
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`}},TP=Mr.whereImpl,EP=1e-7,CP=1e-4,DA={};function RP(e){return e in DA||(DA[e]={}),DA[e]}var FP=128,MP=600;function $P(){return Q().global.screen==null?1024:Q().global.screen.height*Q().global.screen.width*window.devicePixelRatio*MP/1024/1024}var Uu=class extends ru{constructor(e){super();if(this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.warnedAboutMemory=!1,this.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!Q().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Wr(Q().getNumber("WEBGL_VERSION"));this.binaryCache=RP(Q().getNumber("WEBGL_VERSION")),this.gpgpu=new xm(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new mP(this.gpgpu),this.numMBBeforeWarning=$P(),this.texData=new mh(this,pn())}nextDataId(){return Uu.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((Q().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||Q().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:Hn.UPLOAD,refCount:1}),r}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,n,r,a){if(Q().getBool("DEBUG")&&this.checkNumericalProblems(t),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:Hn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new wl(i,op):h=new Ra(i,op);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,c;l&&(c=v.now());let u;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);u=R.mergeRealAndImagArrays(h,d)}else u=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-c),this.convertAndCacheOnCPU(e,u)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new wl(r,op):p=new Ra(r,op);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!Q().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&Q().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,c;if(s!=="complex64"&&Q().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...uc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let u;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];u=R.mergeRealAndImagArrays(f,m)}else if(l==null)u=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);u=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}c!=null&&this.disposeIntermediateTensorInfo(c);let h=this.convertAndCacheOnCPU(e,u),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&pn().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return We(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!ow(n))throw Q().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(Q().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...uc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=Q().getBool("WEBGL_PACK")&&r===!0,i=s?rp(t):t,o=s?new qO(i):new GO(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(l.dataId),u=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),u}timerAvailable(){return Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,c)=>({name:s[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(Q().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return Q().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=pn().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=FP){let n=this.getCPUBackend();return!Q().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==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=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return TP(e.shape,t)}packedUnaryOp(e,t,n){let r=new wl(e.shape,t),a=this.compileAndRun(r,[e],n);return pn().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=Qw(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(Q().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,s_,e.dtype);let t=new Ra(e.shape,s_),n=this.compileAndRun(t,[e]);return pn().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return pn().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new SP(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new dP(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[ii(e.shape),...oi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[ii(t),...oi(t)],s=new t_(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=rp(r),i;n?i=new jO(s):i=new HO(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===oc.DENSE){let f=uc(e.outputShape);i.texShape=f.map(m=>m*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(f=>{if(f.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let m=this.texData.get(f.dataId);if(m.texture==null){if(!e.packedInputs&&v.sizeFromShape(f.shape)<=Q().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:f.shape,texData:null,isUniform:!0,uniformValues:m.values};e.packedInputs&&(m.isPacked=!0,m.shape=f.shape)}else if(!!m.isPacked!=!!e.packedInputs)f=m.isPacked?this.unpackTensor(f):this.packTensor(f),o.push(f),m=this.texData.get(f.dataId);else if(m.isPacked&&!ic(m.shape,f.shape)){let A=f,y=f.shape;f.shape=m.shape,f=this.packedReshape(f,y),o.push(f),m=this.texData.get(f.dataId),A.shape=y}return this.uploadToGPU(f.dataId),{shape:f.shape,texData:m,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=Dz(e,l,c),h=this.getAndSaveBinary(u,()=>Mz(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;if(d&&(p=this.startTimer()),$z(this.gpgpu,h,l,c,r),o.forEach(f=>this.disposeIntermediateTensorInfo(f)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)})),!Q().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let f=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),f}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(Q().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),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=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=U(()=>{if(!Q().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=Q().getBool("DEBUG");Q().set("DEBUG",!1);let t=this.abs(Se(1e-8)).dataSync()[0];if(Q().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?EP:CP}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,c;l&&(c=v.now());let u=t.texShape;if(u==null&&(u=vw(n,o),t.texShape=u),a!=null){let h=rp(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=ml(u[0],u[1]),d=new KO(h,[f,p],m)):d=new XO(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Hn.PIXELS:this.texData.get(A.dataId).usage=Hn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-c)}else{let h=this.acquireTexture(u,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=DP(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Uu.nextDataId=0;function DP(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let r=0;r<n.length;++r)n[r]=Math.round(e[r]);return n}else throw new Error(`Unknown dtype ${t}`)}var E0="3.1.0";function C0(){Q().set("WEBGL_FORCE_F16_TEXTURES",!0)}Kh.isBrowser()&&ku("webgl",()=>new Uu,2);var P8={forceHalfFloat:C0},i_=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,_l=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},lp=`
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;
`,hc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(s=`
${ht(a)} coords = getOutputCoords();
`,a===1)s+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=ln("coords",a);s+=`
bool nextRowOutOfBounds =
(${i[a-2]} + 1) >= ${this.outputShape[a-2]};
bool nextColOutOfBounds =
(${i[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) {
${e}
}
void main() {
vec4 a = getAAtOutCoords();
vec4 b = getBAtOutCoords();
vec4 result = binaryOperation(a, b);
${s}
setOutput(result);
}
`}};function Rn(e){let{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var OP={kernelName:ds,backendName:"webgl",kernelFunc:Rn};function Fa(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=Rn({inputs:{x:r},backend:n}),l=Rn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var zP={kernelName:_h,backendName:"webgl",kernelFunc:Fa},o_="return (a < 0.) ? b * a : a;",l_=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function PP(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(l_,a.shape,i.shape):new _l(o_,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var LP={kernelName:ps,backendName:"webgl",kernelFunc:PP},u_="return (a < 0.) ? b * a : a;",c_=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function WP(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(c_,r.shape,a.shape):new _l(u_,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var BP={kernelName:Is,backendName:"webgl",kernelFunc:WP},h_="if (isnan(x)) return x;",VP=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,UP=`
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 Je({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let c=Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new wl(i.shape,t):u=new Ra(i.shape,e),o.runWebGLProgram(u,[i],l)}}function Zt({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:c}=i,u=o;if(r&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[x,_]=w,I={dataId:x.dataId,dtype:x.dtype,shape:l.shape},S={dataId:_.dataId,dtype:_.dtype,shape:c.shape},T=new _l(e,l.shape,c.shape);return u.runWebGLProgram(T,[I,S],Qn(x.dtype,_.dtype))}),g=Fa({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||Qn(l.dtype,c.dtype);if(u.shouldExecuteOnCPU([l,c])&&a!=null){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=a(l.shape,c.shape,f.values,m.values,h),g=u.makeTensorInfo(y,h),w=u.texData.get(g.dataId);return w.values=A,g}let d=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new hc(t,l.shape,c.shape,n):p=new _l(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function up(e,t=!1){if(e==="linear")return t?vP:xP;if(e==="relu")return t?IP:_P;if(e==="elu")return t?kP:wP;if(e==="relu6")return t?NP:bP;if(e==="prelu")return t?c_:u_;if(e==="leakyrelu")return t?l_:o_;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var d_=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let c=r?e[1]:e[2],u=Math.ceil(c/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${i}
}`:l?m=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${i}
}`:m=`vec4 activation(vec4 x) {
${i}
}`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",w="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(w=`int(min(float(rc.x), ${t[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 = ${g};
int batchB = ${w};
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}
${A}
setOutput(result);
}
`}},p_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},f_=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${e}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}},m_="return a * b;";function A_(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),c=new f_(p_.REAL,r.shape,a.shape),u=new f_(p_.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Fa({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[c,u]=Jz(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(u,s),d=n.texData.get(h.dataId);return d.values=c,h}let i;return Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new hc(m_,r.shape,a.shape):i=new _l(m_,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var HP={kernelName:_s,backendName:"webgl",kernelFunc:A_};function jP(e,t,n){let r=[ii(e.shape),...oi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[ii(t),...oi(t)],i=new t_(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ge(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),c=v.sizeFromShape(l);v.assert(o===c,()=>`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!ic(a.shape,l)&&!(u.texture!==null&&ic(u.shape,l))?jP(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var GP={kernelName:ko,backendName:"webgl",kernelFunc:ge},y_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let u=1/t;l=`sumValue += dot(values * ${v.isInt(u)?u.toPrecision(2):u}, ones);`}let c="";a%n>0&&(c=`
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) {
${c}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
float sumValue = 0.0;
for (int i = 0; i < ${i}; 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 + ${i};
if (${o===1}) {
vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
${l}
} else if (${o===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1), 0.0, 0.0);
${l}
} else if (${o===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2), 0.0);
${l}
}
setOutput(sumValue);
}
`}},qP=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,u=n%4,h=`
if (${t==="sum"}) {
sumValue += dot(values, ones);
} else if (${t==="prod"}) {
vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
prodValue *= tmp[0] * tmp[1];
} else {
minMaxValue = ${o}(values, minMaxValue);
}
`,d="vec4";t==="all"?(i="1.0",h=`
bool reducedAllValue = all(values);
float floatedReducedAllValue = float(reducedAllValue);
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
`,d="bvec4"):t==="any"&&(i="0.0",h=`
bool reducedAnyValue = any(values);
float floatedReducedAnyValue = float(reducedAnyValue);
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
`,d="bvec4");let p="";a%n>0&&(p=`
if (inIdx < 0 || inIdx >= ${a}) {
return initializationValue;
}
`),this.userCode=`
const float initializationValue = ${i};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${p}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
vec4 minMaxValue = vec4(${i});
float prodValue = 1.0;
float sumValue = 0.0;
float allValue = 1.0;
float anyValue = 0.0;
for (int i = 0; i < ${c}; i += 4) {
int inIdx = inOffset + i;
${d} values = ${d}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${h}
}
int inIdx = inOffset + ${c};
if (${u===1}) {
${d} values = ${d}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${h}
} else if (${u===2}) {
${d} values = ${d}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${h}
} else if (${u===3}) {
${d} values = ${d}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${h}
}
setOutput(${l});
}
`}};function XP(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],r=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function hi(e,t,n,r){let a=XP(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:c}=a[i],u,h;n==="mean"?u=i===0?new y_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},o):new y_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c}):u=new qP({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},n),h=s,s=r.runWebGLProgram(u,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var ZP=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ht(this.rank),a=KP(t);this.userCode=`
void main() {
${r} resRC = getOutputCoords();
setOutput(getA(${a}));
}
`}};function KP(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var JP=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=ht(this.rank),a=e_("rc",this.rank),s=new Array(this.rank);for(let c=0;c<t.length;c++)s[t[c]]=a[c];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
void main() {
${r} rc = getOutputCoords();
vec4 result = vec4(0.);
result[0] = ${l};
if(${o}) {
result[1] = ${l};
}
--${a[this.rank-1]};
if(++${a[this.rank-2]} < ${n[this.rank-2]}) {
result[2] = ${l};
if(${o}) {
result[3] = ${l};
}
}
setOutput(result);
}
`}};function cp(e,t,n){let r=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new JP(e.shape,t):new ZP(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function YP(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),c=l!=null,u=e;c&&(u=cp(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(u.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=ge({inputs:{x:u},attrs:{shape:[m,f]},backend:r}),y=Xh(e.dtype),g=hi(A,y,"sum",r),w=ge({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),c&&r.disposeIntermediateTensorInfo(u),w}function OA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return YP(a,s,i,n)}var QP={kernelName:Ds,backendName:"webgl",kernelFunc:OA};function An(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let c;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,h=$A(u,a.shape,a.dtype,s,l);c=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(c.dataId);d.values=h}else c=cp(a,s,i);return c}var eL={kernelName:Ws,backendName:"webgl",kernelFunc:An},g_=1e3;function hp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let c=e.shape.length,u=t.shape.length,h=n?e.shape[c-2]:e.shape[c-1],d=r?t.shape[u-1]:t.shape[u-2],p=n?e.shape[c-1]:e.shape[c-2],f=r?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(c>=2&&u>=2&&w,()=>`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 (${m}) and (${A}).`);let x=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],I=r?[g,f,d]:[g,d,f],S=ge({inputs:{x:e},backend:a,attrs:{shape:_}}),T=ge({inputs:{x:t},backend:a,attrs:{shape:I}}),E=[S,T],C=Math.max(y,g),$=n?S.shape[1]:S.shape[2],D=s!=null,P=i!=null,H=l==="leakyrelu",V=l!=null?up(l,!0):null,K=D||P||H||V!=null,X;if((p===1||f===1)&&$>g_&&K===!1){let J=S,ae=T;n&&(J=An({inputs:{x:S},backend:a,attrs:{perm:[0,2,1]}}),E.push(J)),r&&(ae=An({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),E.push(ae));let Y=f!==1,ue=f===1,ne=J;Y&&(ne=ge({inputs:{x:J},backend:a,attrs:{shape:[C,$,1]}}),E.push(ne));let de=f===1?2:1,he=ae;ue&&(he=ge({inputs:{x:ae},backend:a,attrs:{shape:[C,1,$]}}),E.push(he));let me=A_({inputs:{a:ne,b:he},backend:a});X=OA({inputs:{x:me},backend:a,attrs:{axis:de,keepDims:!0}}),E.push(me)}else{let J=Qn(e.dtype,t.dtype),ae=new d_(_,I,[C,p,f],n,r,D,V,P,H),Y=[S,T];if(s!=null&&Y.push(s),P&&Y.push(i),H){let ue=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));Y.push(ue),E.push(ue)}X=a.runWebGLProgram(ae,Y,J)}let ee=ge({inputs:{x:X},backend:a,attrs:{shape:x}});E.push(X);for(let J of E)a.disposeIntermediateTensorInfo(J);return ee}function tL(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r;return hp({a,b:s,transposeA:l,transposeB:c,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:u})}var nL={kernelName:Bs,backendName:"webgl",kernelFunc:tL},x_="return abs(x);";function rL(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=Qw(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new wl(r.shape,x_):a=new Ra(r.shape,x_),n.runWebGLProgram(a,[r],r.dtype)}var aL={kernelName:Li,backendName:"webgl",kernelFunc:rL},sL=yr+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,iL=Je({opSnippet:sL}),oL={kernelName:Wi,backendName:"webgl",kernelFunc:iL},lL=yr+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,uL=Je({opSnippet:lL}),cL={kernelName:Bi,backendName:"webgl",kernelFunc:uL},w_="return a + b;",hL=Zt({opSnippet:w_,packedOpSnippet:w_,supportsComplex:!0,cpuKernelImpl:Oz}),dL={kernelName:fa,backendName:"webgl",kernelFunc:hL},pL=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
float result = ${r};
setOutput(result);
}
`}},fL=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
vec4 result = ${r};
setOutput(result);
}
`}};function dp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return Rn({inputs:{x:r[0]},backend:n});if(r.length>Q().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=dp({inputs:r.slice(0,o),backend:n}),c=dp({inputs:r.slice(o),backend:n});return dp({inputs:[l,c],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>Qn(o,l)),s=r.map(o=>o.shape),i=Q().getBool("WEBGL_PACK")?new fL(r[0].shape,s):new pL(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var mL={kernelName:Ka,backendName:"webgl",kernelFunc:dp};function AL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=An({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("all",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ge({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=hi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ge({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ge({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var yL={kernelName:Ah,backendName:"webgl",kernelFunc:AL};function gL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=An({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("any",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ge({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=hi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ge({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ge({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var xL={kernelName:yh,backendName:"webgl",kernelFunc:gL},wL=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"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 * ${r};
int bestIndex = inOffset;
float bestValue = getA(batch, bestIndex);
for (int i = 0; i < ${r}; i++) {
int inIdx = ${o};
float candidate = getA(batch, inIdx);
if (candidate ${i} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},_L=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ht(o),c=ln("coords",o),u,h;if(s===1){h=o+1;let S=ht(h);u=`
${S} sourceLocR = ${S}(${c.join()}, 0);
++${c[o-1]};
${S} sourceLocG = ${S}(${c.join()}, 0);
++${c[o-2]};
${S} sourceLocA = ${S}(${c.join()}, 0);
--${c[o-1]};
${S} sourceLocB = ${S}(${c.join()}, 0);
--${c[o-2]};`}else h=o,u=`
${l} sourceLocR = coords;
++${c[o-1]};
${l} sourceLocG = coords;
++${c[o-2]};
${l} sourceLocA = coords;
--${c[o-1]};
${l} sourceLocB = coords;
--${c[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(S=>"int "+S),m=ln("sourceLocR",h-1).concat("inIdx.r"),A=ln("sourceLocG",h-1).concat("inIdx.g"),y=ln("sourceLocB",h-1).concat("inIdx.b"),g=ln("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",x=r?"":`
inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
getBestIndicesAChannel(${A.join()}),
getBestIndicesAChannel(${y.join()}),
getBestIndicesAChannel(${g.join()})));`,_=`vec4(
getAChannel(${m.join()}),
hasNextCol ? getAChannel(${A.join()}) : 0.,
hasNextRow ? getAChannel(${y.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${g.join()}) : 0.)`,I=r?"":`
float getBestIndicesAChannel(${f.join()}) {
return getChannel(getBestIndicesA(${d.join()}),
vec2(${d.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${f.join()}) {
return getChannel(getA(${d.join()}),
vec2(${d.slice(-2).join()}));
}
${I}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${c[o-1]} < ${i[o-1]-1};
bool hasNextRow = ${c[o-2]} < ${i[o-2]-1};
${u}
ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p},
sourceLocB${p}, sourceLocA${p}) * ${t};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${_};
for (int i = 0; i < ${t}; i++) {
inIdx = srcIdx;
${x}
vec4 candidate = ${_};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${w}(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);
}
`}};function __(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new wL(o,n,r==null),c=[t];r!=null&&c.push(r);let u=e.runWebGLProgram(l,c,"int32");if(u.shape[1]===1)return u;let h=__(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function b_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new _L(a,i,n,r==null),l=r==null?[t]:[t,r],c=e.runWebGLProgram(o,l,"int32");if(c.shape.length===t.shape.length){let u=b_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function v_(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!Q().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=ge({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=__(e,c,r);s.push(u);let h=ge({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return b_(e,t,r)}function bL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=An({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=v_(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var vL={kernelName:Za,backendName:"webgl",kernelFunc:bL};function kL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=An({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=v_(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var IL={kernelName:au,backendName:"webgl",kernelFunc:kL},NL=yr+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,SL=Je({opSnippet:NL}),TL={kernelName:Vi,backendName:"webgl",kernelFunc:SL},EL=yr+"return log(x + sqrt(x * x + 1.0));",CL=Je({opSnippet:EL}),RL={kernelName:Ui,backendName:"webgl",kernelFunc:CL},FL=yr+`
return atan(x);
`,ML=Je({opSnippet:FL}),$L={kernelName:Hi,backendName:"webgl",kernelFunc:ML},DL=VP+`
return atan(a, b);
`,OL=`
vec4 result = atan(a, b);
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+UP+`
return result;
`,zL=Zt({opSnippet:DL,packedOpSnippet:OL}),PL={kernelName:Gi,backendName:"webgl",kernelFunc:zL},LL=yr+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,WL=Je({opSnippet:LL}),BL={kernelName:ji,backendName:"webgl",kernelFunc:WL},dc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let S=">=";this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${d}, ${p});
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 < ${u};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${h};
wC += ${c}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${e.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 ${S} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${r?a?m:A:`wR * ${h} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let g="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let x=Math.floor(s/4)*4,_=s%4,I=`
if (${f}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${g}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${d}, ${p});
const float initializationValue = ${y};
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 >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${y});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${u};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${x}; wC += 4) {
int xC = xCCorner + wC * ${c};
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
getValue(batch, xR, xC + 2 * ${c}, d),
getValue(batch, xR, xC + 3 * ${c}, d)
);
${I}
}
int xC = xCCorner + ${x};
if (${_===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${I}
} else if (${_===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
initializationValue,
initializationValue
);
${I}
} else if (${_===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
getValue(batch, xR, xC + 2 * ${c}, d),
initializationValue
);
${I}
}
}
setOutput(${w});
}
`}},zA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,c=e.dilationDepth,u=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let E=">=";this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${m}, ${A}, ${y});
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 < ${d};
wD += ${c}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${p};
wR += ${u}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${f};
wC += ${h}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${e.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 ${E} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${r?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${p} * ${f} +
wR * ${f} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let x="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let I=Math.floor(s/4)*4,S=s%4,T=`
if (${g}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${x}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${m}, ${A}, ${y});
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 xD, int xR, int xC, int ch) {
if (xC < 0 || xC >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${w});
float avgValue = 0.0;
count = 0.0;
for (int wD = 0; wD < ${d};
wD += ${c}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${p};
wR += ${u}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${I}; wC += 4) {
int xC = xCCorner + wC * ${h};
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${h}, ch),
getValue(batch, xD, xR, xC + 2 * ${h}, ch),
getValue(batch, xD, xR, xC + 3 * ${h}, ch)
);
${T}
}
int xC = xCCorner + ${I};
if (${S===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${T}
} else if (${S===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${h}, ch),
initializationValue,
initializationValue
);
${T}
} else if (${S===3}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${h}, ch),
getValue(batch, xD, xR, xC + 2 * ${h}, ch),
initializationValue
);
${T}
}
}
setOutput(${_});
}
}
`}};function VL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;fl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return Rn({inputs:{x:a},backend:n});let h=new dc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var UL={kernelName:Ja,backendName:"webgl",kernelFunc:VL};function HL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new zA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var jL={kernelName:su,backendName:"webgl",kernelFunc:HL},GL=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,c=o-1-e.padInfo.top,u=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
const ivec2 pads = ivec2(${c}, ${u});
const float avgMultiplier = float(${h});
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 < ${o};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${r}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${l};
wC+= ${i}) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},qL=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
const ivec3 pads = ivec3(${p}, ${f}, ${m});
const float avgMultiplier = float(${A});
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 < ${u};
wD += ${o}) {
float dyD = float(dyDCorner + wD) / ${a}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${h};
wR += ${l}) {
float dyR = float(dyRCorner + wR) / ${s}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${d};
wC += ${c}) {
float dyC = float(dyCCorner + wC) / ${i}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
dotProd += dyValue * avgMultiplier;
}
}
}
setOutput(dotProd);
}
`}};function XL(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new qL(d);return n.runWebGLProgram(p,[a],i.dtype)}var KL={kernelName:xh,backendName:"webgl",kernelFunc:XL};function ZL(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;fl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=new GL(u);return n.runWebGLProgram(h,[a],i.dtype)}var JL={kernelName:gh,backendName:"webgl",kernelFunc:ZL};function YL(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return hp({a,b:s,transposeA:i,transposeB:o,backend:n})}var QL={kernelName:Ya,backendName:"webgl",kernelFunc:YL},eW=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${i};
float scale = ${o};
float inv = scale * inversesqrt(variance + float(${s}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}},tW=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
vec4 offset = ${i};
vec4 scale = ${o};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${s}));
setOutput((x - mean) * inv + offset);
}
`}},nW=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let c=[r,a,s],u=null;i!=null&&(u=i.shape,c.push(i));let h=null;o!=null&&(h=o.shape,c.push(o));let d=Q().getBool("WEBGL_PACK_NORMALIZATION")?new tW(r.shape,a.shape,s.shape,u,h,l):new eW(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},rW={kernelName:cs,backendName:"webgl",kernelFunc:nW},sW=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ht(this.rank),n=`uniform int start[${this.rank}];`,r=aW(this.rank),a,s=e.map((i,o)=>`sourceLoc.${PA[o]} = start[${o}] + coords.${PA[o]};`);a=`
${t} sourceLoc;
${t} coords = getOutputCoords();
${s.join(`
`)}
`,this.userCode=`
${n}
void main() {
${a}
setOutput(getSource(${r}));
}
`}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},PA=["x","y","z","w","u","v"];function aW(e){if(e===1)return"sourceLoc";if(e<=6)return PA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var iW=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ht(this.rank),n=ln("coords",this.rank),r=ln("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
result.x = ${s};
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
++${r[this.rank-1]};
result.y = ${s};
--${r[this.rank-1]};
}
`,o=this.rank===1?"":`
--${n[this.rank-1]};
if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
++${r[this.rank-2]};
result.z = ${s};
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
++${r[this.rank-1]};
result.w = ${s};
}
}
`,l=this.rank<=4?`sourceLoc = coords +
${t}(${e.map((c,u)=>`start[${u}]`).join()});`:e.map((c,u)=>`${r[u]} = ${n[u]} + start[${u}];`).join(`
`);this.userCode=`
uniform int start[${this.rank}];
void main() {
${t} coords = getOutputCoords();
${t} sourceLoc;
${l}
vec4 result = vec4(0.);
${i}
${o}
setOutput(result);
}
`}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function oW(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=rn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function pc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=rn.parseSliceParams(a,s,i);if(rn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=nP(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:c}=n.texData.get(a.dataId),u=rn.isSliceContinous(a.shape,o,l);if(c||!u){let h=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new iW(l):new sW(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),oW(a,o,l,n)}var lW={kernelName:To,backendName:"webgl",kernelFunc:pc},uW=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=[],f=ge({inputs:{x:a},backend:n,attrs:{shape:l}}),m=An({inputs:{x:f},backend:n,attrs:{perm:c}}),A=ge({inputs:{x:m},backend:n,attrs:{shape:u}}),y=pc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},cW={kernelName:iu,backendName:"webgl",kernelFunc:uW};function hW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),c=Yw(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var dW={kernelName:wh,backendName:"webgl",kernelFunc:hW},pW="return float(a != b);",k_=Zt({opSnippet:pW,dtype:"bool"}),fW={kernelName:Ao,backendName:"webgl",kernelFunc:k_};function fc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Rn({inputs:{x:a.complexTensorInfos.real},backend:n})}var mW={kernelName:Bh,backendName:"webgl",kernelFunc:fc},AW="return float(int(x));";function yW(e,t){let n=new Ra(e.shape,AW),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function LA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return Rn({inputs:{x:a},backend:n});let i=Ct(a.shape),o=LA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Fa({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=fc({inputs:{input:a},backend:n}),o=LA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=Rn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return yW(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=k_({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var gW={kernelName:Qa,backendName:"webgl",kernelFunc:LA},I_="return ceil(x);",xW=Je({opSnippet:I_,packedOpSnippet:I_,cpuKernelImpl:Pz}),wW={kernelName:es,backendName:"webgl",kernelFunc:xW},_W=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
uniform float minVal;
uniform float maxVal;
void main() {
float value = getAAtOutCoords();
if (isnan(value)) {
setOutput(value);
return;
}
setOutput(clamp(value, minVal, maxVal));
}
`}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}},bW=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,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)));
}
`}getCustomSetupFunc(e,t){return(n,r)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(r,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(r,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};function vW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;Q().getBool("WEBGL_PACK_CLIP")?o=new bW(a.shape):o=new _W(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var kW={kernelName:ma,backendName:"webgl",kernelFunc:vW},IW=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,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))
);
}
`}};function N_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function NW(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new IW(r.shape),i=[N_(r,a.complexTensorInfos.real),N_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var SW={kernelName:ou,backendName:"webgl",kernelFunc:NW},TW=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${n.join(`
`)}
}
`}},EW=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ht(r),s=ln("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],c=i.slice(-2),u=i.join(),h=`if (${l} < ${o[0]}) {
return getChannel(
getT0(${u}), vec2(${c.join()}));
}`;for(let f=1;f<o.length;f++){let m=o[f-1];h+=`
if (${l} < ${o[f]} && ${l} >= ${o[f-1]}) {
return getChannel(
getT${f}(${pp(i,l,m)}),
vec2(${pp(c,l,m)}));
}`}let d=o.length,p=o[o.length-1];h+=`
return getChannel(
getT${d}(${pp(i,l,p)}),
vec2(${pp(c,l,p)}));`,this.userCode=`
float getValue(${i.map(f=>"int "+f)}) {
${h}
}
void main() {
${a} coords = getOutputCoords();
vec4 result = vec4(getValue(${s}), 0., 0., 0.);
${s[r-1]} = ${s[r-1]} + 1;
if (${s[r-1]} < ${n[r-1]}) {
result.g = getValue(${s});
}
${s[r-2]} = ${s[r-2]} + 1;
if (${s[r-2]} < ${n[r-2]}) {
result.a = getValue(${s});
}
${s[r-1]} = ${s[r-1]} - 1;
if (${s[r-2]} < ${n[r-2]} &&
${s[r-1]} < ${n[r-1]}) {
result.b = getValue(${s});
}
setOutput(result);
}
`}};function pp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function fp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Rn({inputs:{x:a.complexTensorInfos.imag},backend:n})}var CW={kernelName:$h,backendName:"webgl",kernelFunc:fp};function bl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(f=>fc({inputs:{input:f},backend:n})),u=e.map(f=>fp({inputs:{input:f},backend:n})),h=bl(c,t,n),d=bl(u,t,n),p=Fa({inputs:{real:h,imag:d},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),u.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:c,outShape:u}=S_(e,t,n),h=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=c[0].shape[0]===1,p=Lz(h,u,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>Q().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),u=bl(e.slice(0,c),t,n),h=bl(e.slice(c),t,n),d=bl([u,h],t,n);return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),d}if(Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new EW(e.map(u=>u.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:s}=S_(e,t,n),i=new TW(a.map(c=>c.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let l=ge({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function S_(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ge({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function T_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(c=>c.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(c=>v.sizeFromShape(c.shape)>0);if(o.length===1)return Rn({inputs:{x:o[0]},backend:n});let l=o.map(c=>c.shape);return R.assertParamsConsistent(l,s),bl(o,s,n)}var RW={kernelName:qi,backendName:"webgl",kernelFunc:T_},E_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,c=e.dilationHeight,u=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",x="";n&&(r?w=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:a?w=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:w=`
float activation(float x) {
${n}
}
`,x="result = activation(result);");let _=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${w}
const ivec2 strides = ivec2(${o}, ${l});
const ivec2 pads = ivec2(${s}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${g}];
ivec2 xRCCorner =
ivec2(coords[${A}], coords[${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 * ${c};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${d}; wC++) {
int xC = xCCorner + wC * ${u};
if (xC < 0 || xC >= ${e.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;
${_}
${x}
setOutput(result);
}
`}},FW=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${a}, ${s}, ${i});
const ivec3 pads = ivec3(${t}, ${n}, ${r});
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 < ${u}; wF++) {
int xF = xFCorner + wF * ${o};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${h}; wR++) {
int xR = xRCorner + wR * ${l};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${d}; wC++) {
int xC = xCCorner + wC * ${c};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${p}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${f===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${p}) *
getW(wF, wR, wC, ${p}, d2);
} else if (${f===2}) {
vec2 xValues = vec2(
getX(batch, xF, xR, xC, ${p}),
getX(batch, xF, xR, xC, ${p} + 1)
);
vec2 wValues = vec2(
getW(wF, wR, wC, ${p}, d2),
getW(wF, wR, wC, ${p} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${f===3}) {
vec3 xValues = vec3(
getX(batch, xF, xR, xC, ${p}),
getX(batch, xF, xR, xC, ${p} + 1),
getX(batch, xF, xR, xC, ${p} + 2)
);
vec3 wValues = vec3(
getW(wF, wR, wC, ${p}, d2),
getW(wF, wR, wC, ${p} + 1, d2),
getW(wF, wR, wC, ${p} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}},MW=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:c,dilationHeight:u,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=on(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let x=0;x<=1;x++)for(let _=0;_<=1;_++)w+=`
blockIndex = rc.y + ${_};
pos = rc.x + ${x};
if(blockIndex < ${e[1]} && pos < ${e[0]}) {
offsetY = int(blockIndex / (${l})) * ${i} - ${p};
d0 = offsetY + ${u} * (pos / ${f});
if(d0 < ${t[y]} && d0 >= 0) {
offsetX = int(mod(float(blockIndex), ${l}.) * ${s}. - ${d}.);
d1 = offsetX + ${c} * (int(mod(float(pos), ${f}.) / ${a}.));
if(d1 < ${t[g]} && d1 >= 0) {
ch = int(mod(float(pos), ${a}.));
if (${A}) {
innerDims = vec2(d1, ch);
result[${x*2+_}] = getChannel(
getA(d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${x*2+_}] = 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;
${w}
${m.output} = result;
}
`}};function C_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,c=r.texData.get(e.dataId),u=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&u>g_,w=l[2]%2!=0&&!!c.isPacked;if(g||!Q().getBool("WEBGL_LAZILY_UNPACK")||!Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let x=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=ge({inputs:{x:e},backend:r,attrs:{shape:[1,x,n.inChannels]}}),I=ge({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),S=hp({a:_,b:I,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=ge({inputs:{x:S},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(I),y.push(S)}else{let x=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,x,n.inChannels],dtype:e.dtype},I=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(ic(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let S=ge({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(S);let T=hp({a:_,b:S,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),E=r.texData.get(T.dataId);v.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=I,E.shape=n.outShape,A=Rn({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let x of y)r.disposeIntermediateTensorInfo(x);return A}function R_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,w=!1,x=[],_=ge({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),I=ge({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});x.push(_),x.push(I);let S=new MW(y,_.shape,n),T=r.runWebGLProgram(S,[_],"float32"),E=ge({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});x.push(T),x.push(E);let C=a!=null,$=s!=null,D=o==="leakyrelu",P=o?up(o,!0):null,H=new d_(E.shape,I.shape,[1,A,n.outChannels],g,w,C,P,$,D),V=[E,I];if(a&&V.push(a),$&&V.push(s),D){let J=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));V.push(J),x.push(J)}let K=r.runWebGLProgram(H,V,"float32"),X=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=ge({inputs:{x:K},backend:r,attrs:{shape:X}});x.push(K);for(let J of x)r.disposeIntermediateTensorInfo(J);return ee}function $W(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=C_({x:a,filter:s,convInfo:d,backend:n});else if(Q().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=R_({x:a,filter:s,convInfo:d,backend:n});else{let m=new E_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=ge({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var DW={kernelName:ts,backendName:"webgl",kernelFunc:$W},OW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.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 < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${r};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${a};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
if (${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);
}
`}},zW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,c=s?2:3,u=s?3:1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${u}];
ivec2 dyCorner = ivec2(coords[${l}], coords[${c}]) - 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 < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / ${r}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
if (${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);
}
`}},PW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.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 < ${e.batchSize}; b++) {
for (int yF = 0; yF < ${e.outDepth}; yF++) {
int xF = wF + yF * ${t} - ${a};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${n} - ${s};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${r} - ${i};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},LW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${o}, ${l}, ${c});
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 < ${t}; wF++) {
float dyF = float(dyFCorner + wF) / ${a}.0;
if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) {
continue;
}
int idyF = int(dyF);
int wFPerm = ${t} - 1 - wF;
for (int wR = 0; wR < ${n}; wR++) {
float dyR = float(dyRCorner + wR) / ${s}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${n} - 1 - wR;
for (int wC = 0; wC < ${r}; wC++) {
float dyC = float(dyCCorner + wC) / ${i}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${r} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
float xValue = getDy(batch, idyF, idyR, idyC, d2);
float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}};function WW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new OW(d);return n.runWebGLProgram(p,[a,s],"float32")}var BW={kernelName:bh,backendName:"webgl",kernelFunc:WW};function VW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(c),d=R.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new zW(d);return n.runWebGLProgram(p,[a,s],"float32")}var UW={kernelName:ns,backendName:"webgl",kernelFunc:VW};function HW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new FW(c);return n.runWebGLProgram(u,[a,s],"float32")}var jW={kernelName:lu,backendName:"webgl",kernelFunc:HW};function GW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=R.computeConv3DInfo(a.shape,l,i,1,o),u=new PW(c);return n.runWebGLProgram(u,[a,s],"float32")}var qW={kernelName:vh,backendName:"webgl",kernelFunc:GW};function XW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=R.computeConv3DInfo(l,s.shape,o,1,i),u=new LW(c);return n.runWebGLProgram(u,[a,s],"float32")}var KW={kernelName:kh,backendName:"webgl",kernelFunc:XW},ZW=h_+`
return cos(x);
`,JW=Je({opSnippet:ZW}),YW={kernelName:rs,backendName:"webgl",kernelFunc:JW},QW=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,eB=Je({opSnippet:QW}),tB={kernelName:Xi,backendName:"webgl",kernelFunc:eB},nB=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[c]=t,[u,h]=n;this.outputShape=[c,u,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,x]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
const float height_ratio = float(${m});
const float width_ratio = float(${g});
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 = ${A};
float width_scale = ${w};
float in_y = ${y};
if( in_y < 0.0 || in_y > ${p} ) {
setOutput(float(${a}));
return;
}
float in_x = ${x};
if( in_x < 0.0 || in_x > ${f} ) {
setOutput(float(${a}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${d} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}},rB=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new nB(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},aB={kernelName:Ki,backendName:"webgl",kernelFunc:rB},$_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${F_(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
uniform float index;
void main() {
${ht(r)} coords = getOutputCoords();
int end = ${M_(r,"coords")};
float val = ${a};
int pow2 = int(pow(2.0, index));
if (${i}) {
int idx = ${o};
${M_(r,"coords")} = idx;
val += getX(${F_(r,"coords")});
}
setOutput(val);
}
`}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function F_(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function M_(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function sB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=R.getAxesPermutation([s],l),u=a;c!=null&&(u=An({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=u.shape[h],p=Rn({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new $_(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new $_(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=R.getUndoAxesPermutation(c),m=An({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var iB={kernelName:as,backendName:"webgl",kernelFunc:sB};function oB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=Yw(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=zz(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var lB={kernelName:Ih,backendName:"webgl",kernelFunc:oB},uB=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,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 / ${t};
int offset_h = imod(h, ${t});
int in_w = w / ${t};
int offset_w = imod(w, ${t});
int offset_d = (offset_h * ${t} + offset_w) *
${this.getOutputDepthSize()};
int in_d = d + offset_d;
float result = ${this.getInputSamplingString()};
setOutput(result);
}
`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function cB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new uB(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var hB={kernelName:Zi,backendName:"webgl",kernelFunc:cB},D_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:a?A=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:A=`
float activation(float x) {
${n}
}
`,y="result = activation(result);");let g=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${A}
const ivec2 strides = ivec2(${c}, ${u});
const ivec2 pads = ivec2(${o}, ${l});
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 >= ${s}) {
continue;
}
for (int wC = 0; wC < ${f}; wC++) {
int xC = xCCorner + wC * ${d};
if (xC < 0 || xC >= ${i}) {
continue;
}
float xVal = getX(batch, xR, xC, d1);
float wVal = getW(wR, wC, d1, q);
dotProd += xVal * wVal;
}
}
float result = dotProd;
${g}
${y}
setOutput(result);
}
`}},O_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let x=0;x<p;x++)for(let _=0;_<f;_++)A+=`
vec4 xTexelR${x}C${_*2} = vec4(0.);
vec4 wR${x}C${_} = vec4(0.);
vec4 xR${x}C${_} = vec4(0.);`;for(let x=0;x<p;x++)for(let _=0;_<m;_++){let I=_*2;if(A+=`
xR = xRCorner + ${x*h};
xC = xCCorner + ${I*d};
`,u===1){if(I<f&&(l%2==1?A+=`
xCOffset = xC + 1;
if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if(xCOffset + 1 >= ${i}) {
xTexelR${x}C${I}.zw = vec2(0.);
}
} else {
xTexelR${x}C${I} = vec4(0.);
}
xCOffset = xC + 1 - 2;
if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
vec4 previous = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if(xCOffset + 1 >= ${i}) {
previous.zw = vec2(0.);
}
xR${x}C${I} = vec4(previous.zw, xTexelR${x}C${I}.xy);
} else {
xR${x}C${I} = vec4(0, 0, xTexelR${x}C${I}.xy);
}
`:A+=`
if(xR >= 0 && xR < ${s} && xC >= 0 && xC < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xC, d1);
} else {
xTexelR${x}C${I} = vec4(0.);
}
xR${x}C${I} = xTexelR${x}C${I};
`,I+1<f)){let S=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
xCOffset = xC + ${l%2} + ${S};
if(xR >= 0 && xR < ${s} &&
xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I+2} = getX(batch, xR, xCOffset, d1);
}
`,d>1&&(A+=`
xCOffset -= 2;
if(xR >= 0 && xR < ${s} &&
xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xCOffset, d1);
} else {
xTexelR${x}C${I} = vec4(0.);
}
`),A+=`
xR${x}C${I+1} = vec4(
xTexelR${x}C${I}.zw, xTexelR${x}C${I+2}.xy);
`):A+=`
xCOffset = xC + ${S};
if(xR >= 0 && xR < ${s} &&
xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I+2} = getX(batch, xR, xCOffset, d1);
}
xR${x}C${I+1} = xTexelR${x}C${I+2};
`}}else I<f&&(A+=`
if(xR >= 0 && xR < ${s}) {
`,l%2==1?(A+=`
xCOffset = xC + 1 - ${u};
if(xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xCOffset, d1);
} else {
xTexelR${x}C${I} = vec4(0.);
}
if(xC + 1 >= 0 && xC + 1 < ${i}) {
xTexelR${x}C${I+2} = getX(batch, xR, xC + 1, d1);
} else {
xTexelR${x}C${I+2} = vec4(0.);
}
xR${x}C${I} = vec4(
xTexelR${x}C${I}.zw, xTexelR${x}C${I+2}.zw);
`,I+1<f&&(A+=`
vec4 final = vec4(0.);
xCOffset = xC + 1 + ${u};
if(xCOffset >= 0 && xCOffset < ${i}) {
final = getX(batch, xR, xCOffset, d1);
}
xR${x}C${I+1} = vec4(xTexelR${x}C${I+2}.xy, final.xy);
`)):(A+=`
if(xC >= 0 && xC < ${i}) {
xTexelR${x}C${I} = getX(batch, xR, xC, d1);
} else {
xTexelR${x}C${I} = vec4(0.);
}
xCOffset = xC + ${u};
if(xCOffset >= 0 && xCOffset < ${i}) {
xTexelR${x}C${I+2} = getX(batch, xR, xCOffset, d1);
} else {
xTexelR${x}C${I+2} = vec4(0.);
}
xR${x}C${I} = vec4(
xTexelR${x}C${I}.xy, xTexelR${x}C${I+2}.xy);
`,I+1<f&&(A+=`
xR${x}C${I+1} = vec4(
xTexelR${x}C${I}.zw, xTexelR${x}C${I+2}.zw);
`)),A+="}");I<f&&(A+=`
vec4 wTexelR${x}C${I} = getW(${x}, ${I}, d1, q);
wR${x}C${I} = vec4(wTexelR${x}C${I}.xz, wTexelR${x}C${I}.xz);
`,I+1<f&&(A+=`
vec4 wTexelR${x}C${I+1} = getW(${x}, ${I+1}, d1, q);
wR${x}C${I+1} =
vec4(wTexelR${x}C${I+1}.xz, wTexelR${x}C${I+1}.xz);`))}for(let x=0;x<p;x++)for(let _=0;_<f;_++)A+=`dotProd += xR${x}C${_} * wR${x}C${_};`;let y="",g="";n&&(r?y=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${n}
}`:a?y=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${n}
}`:y=`vec4 activation(vec4 x) {
${n}
}`,g="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${y}
const ivec2 strides = ivec2(${c}, ${u});
const ivec2 pads = ivec2(${o}, ${l});
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.);
${A}
vec4 result = dotProd;
${w}
${g}
setOutput(result);
}
`}};function dB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r,u=l;u==null&&(u=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return Q().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new O_(h):d=new D_(h),n.runWebGLProgram(d,[a,s],"float32")}var pB={kernelName:ss,backendName:"webgl",kernelFunc:dB},fB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.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 < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${r};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${a};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},mB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${s}, ${i});
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 < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / ${r}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 1 - wC;
// TO DO: Vec4 over the channelMul
for (int dm = 0; dm < ${o}; dm++) {
int d2 = d1 * ${o} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function AB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new fB(h);return n.runWebGLProgram(d,[a,s],"float32")}var yB={kernelName:Nh,backendName:"webgl",kernelFunc:AB};function gB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new mB(h);return n.runWebGLProgram(d,[a,s],"float32")}var xB={kernelName:Sh,backendName:"webgl",kernelFunc:gB},wB=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function _B(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=ge({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new wB(s),l=n.runWebGLProgram(o,[i],i.dtype),c=ge({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var bB={kernelName:Th,backendName:"webgl",kernelFunc:_B},vB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=`
const ivec2 strides = ivec2(${a}, ${s});
const ivec2 pads = ivec2(${u}, ${h});
const float neg_infinity = -3.4e38;
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
int d1 = coords.w;
ivec2 outTopLeftCorner =
coords.yz * strides - pads;
int hBeg = outTopLeftCorner.x;
int wBeg = outTopLeftCorner.y;
float curVal = neg_infinity;
for (int h = 0; h < ${i}; h++) {
int hIn = hBeg + h * ${l};
if (hIn >= 0 && hIn < ${t}) {
for (int w = 0; w < ${o}; w++) {
int wIn = wBeg + w * ${c};
if (wIn >= 0 && wIn < ${n}) {
float xVal = getX(batch, hIn, wIn, d1);
float wVal = getW(h, w, d1);
float val = xVal + wVal;
if (val > curVal) {
curVal = val;
}
}
}
}
}
float result = curVal;
setOutput(result);
}
`}};function kB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new vB(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=ge({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var IB={kernelName:uu,backendName:"webgl",kernelFunc:kB},NB="return (x >= 0.0) ? x : (exp(x) - 1.0);",SB=`
vec4 result;
result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
return result;
`,TB=Je({opSnippet:NB,packedOpSnippet:SB}),EB={kernelName:Ji,backendName:"webgl",kernelFunc:TB},CB="return (b >= 1.0) ? a : a * (b + 1.0);",RB=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,FB=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=Q().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(RB,r.shape,a.shape):new _l(CB,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},MB={kernelName:Rh,backendName:"webgl",kernelFunc:FB},$B=`
return vec4(equal(a, b));
`,DB="return float(a == b);",OB=Zt({opSnippet:DB,packedOpSnippet:$B,dtype:"bool"}),zB={kernelName:Qi,backendName:"webgl",kernelFunc:OB},PB=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${R.ERF_P};
float a1 = ${R.ERF_A1};
float a2 = ${R.ERF_A2};
float a3 = ${R.ERF_A3};
float a4 = ${R.ERF_A4};
float a5 = ${R.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,LB=Je({opSnippet:PB}),WB={kernelName:Yi,backendName:"webgl",kernelFunc:LB},z_="return exp(x);",P_=Je({opSnippet:z_,packedOpSnippet:z_,cpuKernelImpl:Wz}),BB={kernelName:os,backendName:"webgl",kernelFunc:P_};function WA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),ge({inputs:{x:s},backend:r,attrs:{shape:o}})}var VB={kernelName:eo,backendName:"webgl",kernelFunc:WA},L_="return exp(x) - 1.0;",UB=Je({opSnippet:L_,packedOpSnippet:L_,cpuKernelImpl:Bz}),HB={kernelName:to,backendName:"webgl",kernelFunc:UB},W_=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
const float exponentMultiplier = ${a};
float unaryOpComplex(float real, float expR, float imag, float expI) {
${i}
}
float mulMatDFT(int batch, int index) {
float indexRatio = float(index) / float(${r});
float exponentMultiplierTimesIndexRatio =
exponentMultiplier * indexRatio;
float result = 0.0;
for (int i = 0; i < ${r}; 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]));
}
`}};function B_(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=ge({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,c=new W_("real",l,t),u=new W_("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Fa({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=ge({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function jB(e){let{inputs:t,backend:n}=e,{input:r}=t;return B_(r,!1,n)}var GB={kernelName:Fh,backendName:"webgl",kernelFunc:jB},qB=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
uniform float value;
void main() {
// Input can be obtained from uniform value.
setOutput(value);
}
`}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function BA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new qB(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var XB={kernelName:cu,backendName:"webgl",kernelFunc:BA},KB=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int x = coords[2];
int coordX = ${t} - x;
float outputValue;
if(coordX >= 0 && coordX < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},ZB={kernelName:no,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new KB(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},V_="return floor(x);",JB=Je({opSnippet:V_,packedOpSnippet:V_,cpuKernelImpl:Vz}),YB={kernelName:ls,backendName:"webgl",kernelFunc:JB},QB=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,eV=`
ivec4 ia = round(a);
ivec4 ib = round(b);
bvec4 cond = notEqual(ib, ivec4(0));
ivec4 result = ivec4(0);
vec4 s = sign(a) * sign(b);
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
if (cond[0]) {
result[0] = idiv(ia[0], ib[0], s[0]);
}
if (cond[1]) {
result[1] = idiv(ia[1], ib[1], s[1]);
}
if (cond[2]) {
result[2] = idiv(ia[2], ib[2], s[2]);
}
if (cond[3]) {
result[3] = idiv(ia[3], ib[3], s[3]);
}
return vec4(result);
`,tV=Zt({opSnippet:QB,packedOpSnippet:eV,dtype:"int32"}),nV={kernelName:us,backendName:"webgl",kernelFunc:tV},rV=class{constructor(e){this.variableNames=["A"];let t=on(),[n,r]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${r}.0, ${n}.0);
vec4 values = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},aV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=on(),[n,r]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${r}.0, ${n}.0);
vec4 values = ${t.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);
}
}
${t.output} = result;
}
`}},iV={kernelName:Gh,backendName:"webgl",kernelFunc:sV},vl;function sV(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,l=typeof ImageBitmap!="undefined"&&a instanceof ImageBitmap,[c,u]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],h=[u,c],d=[u,c,s];(o||i||l)&&(vl==null&&(vl=document.createElement("canvas").getContext("2d")),vl.canvas.width=c,vl.canvas.height=u,vl.drawImage(a,0,0,c,u),a=vl.canvas);let p=n.makeTensorInfo(h,"int32");n.texData.get(p.dataId).usage=Hn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(p.dataId),a);let f=Q().getBool("WEBGL_PACK")?new aV(d):new rV(d),m=n.runWebGLProgram(f,[p],"int32");return n.disposeData(p.dataId),m}function oV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(u),A=R.computeConv2DInfo(a.shape,s.shape,l,h,c,d,!1,m),y,g=[];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"))y=C_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(Q().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=R_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let x=i!=null,_=o!=null,I=p==="leakyrelu",S=p?up(p,!1):null,T=new E_(A,x,S,_,I),E=[a,s];if(i&&E.push(i),o&&E.push(o),I){let C=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push(C),g.push(C)}y=n.runWebGLProgram(T,E,"float32")}let w=ge({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(x=>n.disposeIntermediateTensorInfo(x)),w}var lV={kernelName:Vs,backendName:"webgl",kernelFunc:oV};function uV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=u;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,c,h,!0),y=Q().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?up(d,y):null,w=[a,s],x=i!=null,_=o!=null,I=d==="leakyrelu";if(x&&w.push(i),_&&w.push(o),I){let E=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(E),f.push(E)}let S;y?S=new O_(A,x,g,_,I):S=new D_(A,x,g,_,I);let T=n.runWebGLProgram(S,w,"float32");return f.forEach(E=>n.disposeIntermediateTensorInfo(E)),T}var cV={kernelName:Us,backendName:"webgl",kernelFunc:uV},hV=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ht(t.length),a=ht(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
${r} strides = ${r}(${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]));
}
`}};function dV(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,c,u]=R.prepareAndValidate(r,a),h=ge({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=ge({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/c,c]}}),p=new hV(i,u,[l,c]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=ge({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var pV={kernelName:ao,backendName:"webgl",kernelFunc:dV},mV=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ht(this.rank),r=fV(e,2);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function fV(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function AV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],c=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=v.sizeFromShape(s.shape),h=[],d=ge({inputs:{x:a},backend:n,attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]}}),p=ge({inputs:{x:s},backend:n,attrs:{shape:[c.batchSize,u/c.batchSize]}});h.push(d),h.push(p);let f=[c.batchSize,c.outerSize,u/c.batchSize,c.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),x=Uz(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(c.outputShape,x.dtype,x.values)}let m=new mV(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=ge({inputs:{x:A},backend:n,attrs:{shape:c.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var yV={kernelName:ro,backendName:"webgl",kernelFunc:AV},gV="return float(a > b);",xV=`
return vec4(greaterThan(a, b));
`,wV=Zt({opSnippet:gV,packedOpSnippet:xV,cpuKernelImpl:Hz,dtype:"bool"}),_V={kernelName:so,backendName:"webgl",kernelFunc:wV},bV="return float(a >= b);",vV=`
return vec4(greaterThanEqual(a, b));
`,kV=Zt({opSnippet:bV,packedOpSnippet:vV,dtype:"bool"}),IV={kernelName:hs,backendName:"webgl",kernelFunc:kV};function NV(e){let{inputs:t,backend:n}=e,{input:r}=t;return B_(r,!0,n)}var SV={kernelName:Mh,backendName:"webgl",kernelFunc:NV},TV="return float(!isnan(x) && !isinf(x));",EV=Je({opSnippet:TV,dtype:"bool"}),CV={kernelName:io,backendName:"webgl",kernelFunc:EV},RV="return float(isinf(x));",FV=Je({opSnippet:RV,dtype:"bool"}),MV={kernelName:oo,backendName:"webgl",kernelFunc:FV},$V="return float(isnan(x));",DV=Je({opSnippet:$V,dtype:"bool"}),OV={kernelName:lo,backendName:"webgl",kernelFunc:DV},zV="return float(a < b);",PV=`
return vec4(lessThan(a, b));
`,LV=Zt({opSnippet:zV,packedOpSnippet:PV,cpuKernelImpl:jz,dtype:"bool"}),WV={kernelName:uo,backendName:"webgl",kernelFunc:LV},BV="return float(a <= b);",VV=`
return vec4(lessThanEqual(a, b));
`,UV=Zt({opSnippet:BV,packedOpSnippet:VV,dtype:"bool"}),HV={kernelName:co,backendName:"webgl",kernelFunc:UV};function jV(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=Gz(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var GV={kernelName:Dh,backendName:"webgl",kernelFunc:jV},qV=`if (x < 0.0) return NAN;
return log(x);`,XV=`
vec4 result = log(x);
vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
result.r = isNaN.r == 1.0 ? NAN : result.r;
result.g = isNaN.g == 1.0 ? NAN : result.g;
result.b = isNaN.b == 1.0 ? NAN : result.b;
result.a = isNaN.a == 1.0 ? NAN : result.a;
return result;
`,KV=Je({opSnippet:qV,packedOpSnippet:XV,cpuKernelImpl:qz}),ZV={kernelName:fs,backendName:"webgl",kernelFunc:KV},JV="return log(1.0 + x);",YV=Je({opSnippet:JV}),QV={kernelName:ho,backendName:"webgl",kernelFunc:YV},eU="return float(a >= 1.0 && b >= 1.0);",tU=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,nU=Zt({opSnippet:eU,packedOpSnippet:tU,dtype:"bool"}),rU={kernelName:po,backendName:"webgl",kernelFunc:nU},aU="return float(!(x >= 1.0));",sU=Je({opSnippet:aU}),iU={kernelName:hu,backendName:"webgl",kernelFunc:sU},oU="return float(a >= 1.0 || b >= 1.0);",lU=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,uU=Zt({opSnippet:oU,packedOpSnippet:lU,dtype:"bool"}),cU={kernelName:du,backendName:"webgl",kernelFunc:uU},hU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${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 <= ${i}) {
float z = getX(b, r, c, idx);
sum += z * z;
}
}
float val = x * ${o};
setOutput(val);
}
`}},dU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${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 <= ${s}; j++) {
ivec2 idx = depth + j;
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));
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 * ${o};
setOutput(result);
}
`}},pU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=Q().getBool("WEBGL_PACK_NORMALIZATION")?new dU(a.shape,s,i,o,l):new hU(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},fU={kernelName:pu,backendName:"webgl",kernelFunc:pU},mU=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,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 - ${t})));
int depthEnd = int(min(float(${this.depth}),
float(d + ${t} + 1)));
const int MIN_DEPTH_BEGIN = 0;
const int MAX_DEPTH_END = ${this.depth};
float norm = 0.0;
for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd) {
norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
}
else {
break;
}
}
norm = float(${r}) * norm + float(${n});
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd){
float dyi = -2.0 * float(${r})
* float(${a})
* getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
/ norm;
if (k == d) {
dyi += pow(norm, -1.0 * ${a});
}
if (k == coords[3]) {
dyi *= getDy(b, r, c, d);
result += dyi;
}
}
else {
break;
}
}
}
setOutput(result);
}
`}},AU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r,h=new mU(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},yU={kernelName:Oh,backendName:"webgl",kernelFunc:AU};function gU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ge({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=hi(i,e.dtype,"max",r),l=ge({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function U_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let I=0;I<w.length;I++)w[I]=a.shape[u[I]];let x=$A(g,a.shape,a.dtype,u,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=x}else p=cp(a,u,n);c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("max",c,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,c),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=Xz(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let x=n.texData.get(y.dataId);x.values=w}else y=gU(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var xU={kernelName:ms,backendName:"webgl",kernelFunc:U_},wU=i_+`
return max(a, b);
`,_U=`
vec4 result = vec4(max(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+lp+`
return result;
`,bU=Zt({opSnippet:wU,packedOpSnippet:_U,cpuKernelImpl:Kz}),vU={kernelName:As,backendName:"webgl",kernelFunc:bU};function kU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;fl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return Rn({inputs:{x:a},backend:n});let h=new dc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var IU={kernelName:ys,backendName:"webgl",kernelFunc:kU};function NU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new zA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var SU={kernelName:fu,backendName:"webgl",kernelFunc:NU},TU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
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 += ${r}) {
float dyR = float(dyRCorner + wR) / ${t}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${s}; wC++) {
float dyC = float(dyCCorner + wC) / ${n}.0;
if (dyC < 0.0 || dyC >= ${e.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 * ${s} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},EU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=`
const ivec3 pads = ivec3(${u}, ${h}, ${d});
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 < ${o};
wD += ${a}) {
float dyD = float(dyDCorner + wD) / ${t}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${l};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${c};
wC += ${i}) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
int maxPosValue = ${p} -
int(getMaxPos(batch, idyD, idyR, idyC, ch));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue =
wD * ${l} * ${c} +
wR * ${c} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
}
setOutput(dotProd);
}
`}};function CU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new zA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new EU(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var RU={kernelName:Ph,backendName:"webgl",kernelFunc:CU};function FU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;fl([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new dc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new TU(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var MU={kernelName:zh,backendName:"webgl",kernelFunc:FU};function $U(e,t,n,r){let a=new dc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new dc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var DU={kernelName:Lh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let c=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=R.computePool2DInfo(r.shape,a,s,c,i),[h,d]=$U(r,o,u,l);return[h,d]}};function OU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ge({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=hi(i,"float32","mean",r),l=ge({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var zU={kernelName:gs,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,x=new Array(o);for(let S=0;S<x.length;S++)x[S]=r.shape[u[S]];let _=$A(w,r.shape,r.dtype,u,x);f=i.makeTensorInfo(x,r.dtype);let I=i.texData.get(f.dataId);I.values=_}else f=cp(r,u,i);p.push(f),c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("sum",c,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,c),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=OU(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function PU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=An({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ge({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=hi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ge({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ge({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var LU={kernelName:xs,backendName:"webgl",kernelFunc:PU},WU=i_+`
return min(a, b);
`,BU=`
vec4 result = vec4(min(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+lp+`
return result;
`,VU=Zt({opSnippet:WU,packedOpSnippet:BU,cpuKernelImpl:Zz}),UU={kernelName:ws,backendName:"webgl",kernelFunc:VU},HU=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,u)=>c[0]+e[u]+c[1]);let r=e.length,a=ht(r),s=t.map(c=>c[0]).join(","),i=t.map((c,u)=>c[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
int start = ${s};
int end = ${i};
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 = ${a}(${i});
void main() {
${a} outC = getOutputCoords();
for (int i = 0; i < ${r}; 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};
}
}
${a} coords = outC - start;
setOutput(getX(${o}));
}
`}},jU=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ht(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=ln("rc",r),l=ln("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
${a} source = rc;
if (source < start) {
source = start * 2 - source - ${h};
} else if (source >= end) {
source = (end - 1) * 2 - source + ${h};
}
source -= start;
`;d=`
${a} rc = outputLoc;
${p}
result[0] = getChannel(getX(${l.join()}), ${u});
${o[r-1]} += 1;
if(${c}) {
${p}
result[1] = getChannel(getX(${l.join()}), ${u});
}
`}else{let p=`
${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 - ${h}) +
gte * ((end - 1) * 2 - source + ${h});
source -= start;
`;d=`
${a} rc = outputLoc;
${p}
result[0] = getChannel(getX(${l.join()}), ${u});
${o[r-1]} += 1;
if(${c}) {
${p}
result[1] = getChannel(getX(${l.join()}), ${u});
}
rc = outputLoc;
${o[r-2]} += 1;
if(${o[r-2]} < ${this.outputShape[r-2]}) {
${p}
result[2] = getChannel(getX(${l.join()}), ${u});
${o[r-1]} += 1;
if(${c}) {
${p}
result[3] = getChannel(getX(${l.join()}), ${u});
}
}
`}this.userCode=`
const ${a} start = ${a}(${s});
const ${a} end = ${a}(${i});
void main() {
${a} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${d}
setOutput(result);
}
`}},GU=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jU(r.shape,a,s):new HU(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},qU={kernelName:mu,backendName:"webgl",kernelFunc:GU},XU=`if (b == 0.0) return NAN;
return mod(a, b);`,KU=`
vec4 result = mod(a, b);
vec4 isNaN = vec4(equal(b, vec4(0.0)));
`+lp+`
return result;
`,ZU=Zt({opSnippet:XU,packedOpSnippet:KU}),JU={kernelName:fo,backendName:"webgl",kernelFunc:ZU},YU=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],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 < ${t-1}; i++) {
cdf += getProbs(batch, i);
if (r < cdf) {
setOutput(float(i));
return;
}
}
// If no other event happened, last event happened.
setOutput(float(${t-1}));
}
`}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},QU=`
if (a == b) {
return 1.0;
};
return a / b;`,eH=`
// 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;
`,H_=Zt({opSnippet:QU,packedOpSnippet:eH,checkOutOfBounds:!0}),tH={kernelName:is,backendName:"webgl",kernelFunc:H_},j_="return a - b;",G_=Zt({opSnippet:j_,packedOpSnippet:j_,supportsComplex:!0,cpuKernelImpl:aP}),nH={kernelName:Ps,backendName:"webgl",kernelFunc:G_};function q_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=U_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),c=ge({inputs:{x:o},backend:n,attrs:{shape:l}}),u=G_({inputs:{a,b:c},backend:n}),h=P_({inputs:{x:u},backend:n}),d=OA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=ge({inputs:{x:d},backend:n,attrs:{shape:l}}),f=H_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var rH={kernelName:Os,backendName:"webgl",kernelFunc:q_};function aH(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:q_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new YU(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var sH={kernelName:Wh,backendName:"webgl",kernelFunc:aH},X_="return -x;";function iH(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=Yz(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return Q().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new wl(r.shape,X_):a=new Ra(r.shape,X_),n.runWebGLProgram(a,[r],r.dtype)}var oH={kernelName:mo,backendName:"webgl",kernelFunc:iH},lH=Mr.nonMaxSuppressionV3Impl;function uH(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=lH(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var cH={kernelName:yo,backendName:"webgl",kernelFunc:uH},hH=Mr.nonMaxSuppressionV4Impl;function dH(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=hH(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var pH={kernelName:go,backendName:"webgl",kernelFunc:dH},fH=Mr.nonMaxSuppressionV5Impl;function mH(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=fH(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var AH={kernelName:xo,backendName:"webgl",kernelFunc:mH},yH=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int index = round(getIndices(coords.x));
setOutput(mix(float(${r}), float(${n}),
float(index == coords.y)));
}
`}},gH=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),c=new yH(l,s,i,o),u=ge({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=ge({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},xH={kernelName:bs,backendName:"webgl",kernelFunc:gH};function mp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=fc({inputs:{input:r},backend:n}),s=mp({inputs:{x:a},backend:n}),i=fp({inputs:{input:r},backend:n}),o=mp({inputs:{x:i},backend:n}),l=Fa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return BA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var wH={kernelName:zo,backendName:"webgl",kernelFunc:mp};function K_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=fc({inputs:{input:r},backend:n}),s=K_({inputs:{x:a},backend:n}),i=fp({inputs:{input:r},backend:n}),o=mp({inputs:{x:i},backend:n}),l=Fa({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return BA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var _H={kernelName:wo,backendName:"webgl",kernelFunc:K_};function bH(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return WA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=WA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=T_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var vH={kernelName:_o,backendName:"webgl",kernelFunc:bH},kH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,c)=>l[0]+e[c]+l[1]);let r=e.length,a=ht(r),s=t.map(l=>l[0]).join(","),i=t.map((l,c)=>l[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
int start = ${s};
int end = ${i};
void main() {
int outC = getOutputCoords();
if (outC < start || outC >= end) {
setOutput(float(${n}));
} else {
setOutput(getX(outC - start));
}
}
`;return}this.userCode=`
${a} start = ${a}(${s});
${a} end = ${a}(${i});
void main() {
${a} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(float(${n}));
} else {
${a} coords = outC - start;
setOutput(getX(${o}));
}
}
`}},IH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ht(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=ln("rc",r),l=ln("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
if(${c}) {
`,r===1?"":`}
rc = outputLoc;
${o[r-2]} += 1;
if(${o[r-2]} < ${this.outputShape[r-2]}) {`,r===1?"":` ${o[r-1]} += 1;
if(${c}) {`],d=r===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=r===1?2:4;f<m;f++)p+=`
${h[f]}
if (${d}) {
result[${f}] = float(${n});
} else {
${a} source = rc - start;
result[${f}] = getChannel(getX(${l.join()}), ${u});
}
`;p+=r===1?"} ":"}}",this.userCode=`
const ${a} start = ${a}(${s});
const ${a} end = ${a}(${i});
void main() {
${a} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${p}
setOutput(result);
}
`}},Z_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new IH(a.shape,s,i):new kH(a.shape,s,i);return n.runWebGLProgram(o,[a],a.dtype)},NH={kernelName:vs,backendName:"webgl",kernelFunc:Z_},SH=`
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);
`,TH=`
// 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));
`+lp+`
return result;
`,EH=Zt({opSnippet:SH,packedOpSnippet:TH}),CH={kernelName:ks,backendName:"webgl",kernelFunc:EH};function RH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],c=v.parseAxisParam(s,a.shape),u=c,h=R.getAxesPermutation(u,o),d=a;h!=null&&(d=An({inputs:{x:a},backend:n,attrs:{perm:h}}),u=R.getInnerMostAxes(u.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=Qz(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=ge({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=Xh(a.dtype),w=hi(y,g,"prod",n);p=ge({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,c);p=ge({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var FH={kernelName:bo,backendName:"webgl",kernelFunc:RH},J_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=eP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},MH={kernelName:Au,backendName:"webgl",kernelFunc:J_},$H="return 1.0 / x;",DH=Je({opSnippet:$H}),OH={kernelName:vo,backendName:"webgl",kernelFunc:DH},zH=yr+`
return (x < 0.0) ? 0.0 : x;
`,PH=`
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;
`,LH=Je({opSnippet:zH,packedOpSnippet:PH}),WH={kernelName:Ns,backendName:"webgl",kernelFunc:LH},BH=yr+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,VH=`
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;
`,UH=Je({opSnippet:BH,packedOpSnippet:VH}),HH={kernelName:Ts,backendName:"webgl",kernelFunc:UH},jH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${c[0]/u[0]},
${c[1]/u[1]});
const vec2 inputShapeRC = vec2(${i}.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 = ${h};
// Compute the four integer indices.
ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));
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);
}
`}},GH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${c[0]/u[0]},
${c[1]/u[1]},
${c[1]/u[1]});
const vec3 inputShapeRC = vec3(${i}.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 = ${h};
// Compute the four integer indices.
ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));
ivec3 sourceCeilRC = ivec3(
min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${n-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);
}
`}};function qH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=Q().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new GH(a.shape,l,c,s,i):new jH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var XH={kernelName:Ss,backendName:"webgl",kernelFunc:qH},KH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*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(${c});
const float widthScale = float(${u});
const float invHeightScale = float(${h});
const float invWidthScale = float(${d});
const int winHeight = int(${p});
const int winWidth = int(${f});
// 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 >= ${s}) {
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 >= ${i}) {
continue;
}
float dxR = float(dyR) * heightScale;
int topDxRIndex = int(floor(dxR));
int bottomDxRIndex = int(min(ceil(dxR), ${r-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), ${a-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);
}
`}};function ZH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new KH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var JH={kernelName:Uh,backendName:"webgl",kernelFunc:ZH},YH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${c[0]/u[0]},
${c[1]/u[1]});
const vec2 inputShapeRC = vec2(${i}.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 = ${d};
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestRC = ivec2(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${h})));
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutput(newValue);
}
`}};function QH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new YH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var ej={kernelName:yu,backendName:"webgl",kernelFunc:QH},tj=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${c});
const float widthScale = float(${u});
const float invHeightScale = float(${h});
const float invWidthScale = float(${d});
const int winHeight = int(${p});
const int winWidth = int(${f});
// 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 >= ${s}) {
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 >= ${i}) {
continue;
}
float sourceFracRow =
float(${o[0]}) *
(float(dyR) / float(${l[0]}));
float sourceFracCol =
float(${o[1]}) *
(float(dyC) / float(${l[1]}));
int sourceNearestRow = int(min(
float(int(${r}) - 1),
${n} ? float(round(sourceFracRow)) :
float(floor(sourceFracRow))));
int sourceNearestCol = int(min(
float(int(${a}) - 1),
${n} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function nj(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new tj(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var rj={kernelName:Vh,backendName:"webgl",kernelFunc:nj},aj=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
void main() {
int coord = getOutputCoords();
setOutput(getX(${e[0]} - coord - 1));
}
`;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=ht(n);this.userCode=`
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${a}));
}
`}},sj=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=ln("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ht(n);n===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${e[0]} - rc - 1),
${e[0]} - rc - 1);
if(${a}){
result.g = getChannel(getX(${e[0]} - (rc + 1) - 1),
${e[0]} - (rc + 1) - 1);
}
setOutput(result);
}
`:this.userCode=`
void main() {
${i} rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = ${o(r.slice())};
if(${a}){
result.g = ${l(r.slice())};
}
if(${s}) {
result.b = ${c(r.slice())};
if(${a}) {
result.a = ${u(r.slice())};
}
}
setOutput(result);
}
`;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function c(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function u(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function ij(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return Rn({inputs:{x:a},backend:n});let l=Q().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new sj(a.shape,o):new aj(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var oj={kernelName:Es,backendName:"webgl",kernelFunc:ij},lj=class{constructor(e,t,n,r){this.variableNames=["Image"],this.outputShape=[];let a=e[1],s=e[2],i=Math.sin(t).toFixed(3),o=Math.cos(t).toFixed(3);this.outputShape=e;let[l,c]=R.getImageCenter(r,a,s),u=l.toFixed(3),h=c.toFixed(3),d="";typeof n=="number"?d=`float outputValue = ${n.toFixed(2)};`:d=`
vec3 fill = vec3(${n.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) - ${u}) * ${o} - (float(y) - ${h}) * ${i};
float coordYFloat = (float(x) - ${u}) * ${i} + (float(y) - ${h}) * ${o};
int coordX = int(round(coordXFloat + ${u}));
int coordY = int(round(coordYFloat + ${h}));
${d}
if(coordX >= 0 && coordX < ${s} && coordY >= 0 && coordY < ${a}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},uj={kernelName:Po,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new lj(r.shape,a,s,i);return o.runWebGLProgram(l,[r],r.dtype)}},cj=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,hj=Je({opSnippet:cj}),dj={kernelName:Cs,backendName:"webgl",kernelFunc:hj},pj="return inversesqrt(x);",fj=Je({opSnippet:pj,cpuKernelImpl:tP}),mj={kernelName:Rs,backendName:"webgl",kernelFunc:fj},Y_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ht(a.length),l=ht(s.length),c="";n===1?c="i":n===2&&(c="i, j");let u=`getIndices(${c})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
${o} strides = ${o}(${a});
void main() {
${l} coords = getOutputCoords();
float sum = 0.0;
bool found = false;
for (int i = 0; i < ${e}; i++) {
int flattenedIndex = 0;
for (int j = 0; j < ${t}; j++) {
int index = round(${u});
flattenedIndex += index * ${p};
}
if (flattenedIndex == coords[0]) {
sum += ${d};
found = true;
}
}
setOutput(mix(getDefaultValue(), sum, float(found)));
}
`}};function Aj(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=R.calculateShapes(s,a,i),d=[h/c,c];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=ge({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=ge({inputs:{x:s},backend:n,attrs:{shape:[l,c]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new Y_(l,o,p.shape.length,f.shape.length,u,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=ge({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var yj={kernelName:Io,backendName:"webgl",kernelFunc:Aj},gj=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c<t.length;c++)l.push(`${i[c]}`),c<e&&o.push(`${i[c]}`);r=o.join(),a=l.join()}let s=ht(n);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
float cVal = getC(${r});
if (cVal >= 1.0) {
setOutput(getA(${a}));
} else {
setOutput(getB(${a}));
}
}
`}};function xj(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new gj(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],Qn(a.dtype,s.dtype))}var wj={kernelName:No,backendName:"webgl",kernelFunc:xj},_j=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${R.SELU_SCALEALPHA};
float scale = ${R.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,bj=Je({opSnippet:_j}),vj={kernelName:So,backendName:"webgl",kernelFunc:bj},kj="return 1.0 / (1.0 + exp(-1.0 * x));",Ij=Je({opSnippet:kj}),Nj={kernelName:Ms,backendName:"webgl",kernelFunc:Ij},Sj=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,Tj=Je({opSnippet:Sj}),Ej={kernelName:Co,backendName:"webgl",kernelFunc:Tj},Cj=h_+`
return sin(x);
`,Rj=Je({opSnippet:Cj}),Fj={kernelName:Fs,backendName:"webgl",kernelFunc:Rj},Mj=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,$j=Je({opSnippet:Mj}),Dj={kernelName:Eo,backendName:"webgl",kernelFunc:$j},Oj=`
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;
`,zj=Je({opSnippet:Oj}),Pj={kernelName:Ro,backendName:"webgl",kernelFunc:zj},Lj=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let c=[],u=Z_({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(u.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(u.shape,s,o,!1),f=ge({inputs:{x:u},backend:n,attrs:{shape:h}}),m=An({inputs:{x:f},backend:n,attrs:{perm:d}}),A=ge({inputs:{x:m},backend:n,attrs:{shape:p}});return c.push(u),c.push(f),c.push(m),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},Wj={kernelName:gu,backendName:"webgl",kernelFunc:Lj};function Bj(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,strides:u,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new Y_(c,l,a.shape.length,s.shape.length,u,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=ge({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var Vj={kernelName:Hh,backendName:"webgl",kernelFunc:Bj};function Uj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),c=a.shape.length,u=new Array(c).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=pc({inputs:{x:a},backend:n,attrs:{begin:u,size:p}});return u[o]+=d,f})}var Hj={kernelName:Fo,backendName:"webgl",kernelFunc:Uj},jj="return sqrt(x);",Gj=Je({opSnippet:jj}),qj={kernelName:$s,backendName:"webgl",kernelFunc:Gj},Xj="return x * x;",Kj=Je({opSnippet:Xj}),Zj={kernelName:xu,backendName:"webgl",kernelFunc:Kj},Q_="return (a - b) * (a - b);",Jj=Zt({opSnippet:Q_,packedOpSnippet:Q_}),Yj={kernelName:zs,backendName:"webgl",kernelFunc:Jj};function Qj({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=yr+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,s=new Ra(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var eG={kernelName:ya,backendName:"webgl",kernelFunc:Qj},tG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ht(n.length),s=ht(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${o-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
${a} begin = ${a}(${e});
${a} strides = ${a}(${t});
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${i}));
}
`}};function nG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=rn.sliceInfo(a.shape,s,i,o,l,c,u,h,d),w=ge({inputs:{x:a},backend:n,attrs:{shape:y}}),x;if(p){let I=pc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});x=ge({inputs:{x:I},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(I)}else if(g.some(I=>I===0))x=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let I=n.texData.get(w.dataId).values,S=We(w.shape,w.dtype,I),T=rP(g,S,m,f);x=n.makeTensorInfo(g,w.dtype,T.values)}else{let I=new tG(f,m,g);x=n.runWebGLProgram(I,[w],w.dtype)}let _=ge({inputs:{x},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(x),_}var rG={kernelName:Mo,backendName:"webgl",kernelFunc:nG},aG="return tan(x);",sG=Je({opSnippet:aG}),iG={kernelName:$o,backendName:"webgl",kernelFunc:sG},oG=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,lG=Je({opSnippet:oG}),uG={kernelName:Ls,backendName:"webgl",kernelFunc:lG},hG=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=ht(this.rank),a=cG(e);this.userCode=`
void main() {
${r} resRC = getOutputCoords();
setOutput(getA(${a}));
}
`}};function cG(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function eb(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(u=>v.decodeString(u)),l=We(a.shape,a.dtype,o),c=sP(l,s);return n.makeTensorInfo(c.shape,c.dtype,c.values)}let i=new hG(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var dG={kernelName:Aa,backendName:"webgl",kernelFunc:eb};function pG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,c]=iP(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(c.shape,c.dtype,c.values)]}var fG={kernelName:Do,backendName:"webgl",kernelFunc:pG};function mG(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;fl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:c}=oP(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var AG={kernelName:jh,backendName:"webgl",kernelFunc:mG};function yG(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],c=new Array(o-1),u=0;for(let m=0;m<o;m++)m!==s&&(c[u++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=pc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=ge({inputs:{x:A},backend:n,attrs:{shape:c}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var gG={kernelName:Oo,backendName:"webgl",kernelFunc:yG},xG=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",c=Math.floor(n/4)*4,u=n%4,h=`
sumValue += dot(values, segFilter);
`,d="";a%n>0&&(d=`
if (inIdx < 0 || inIdx >= ${a}) {
return initializationValue;
}
`);let p="";a%n>0&&(p=`
if (inIdx < 0 || inIdx >= ${a}) {
return -1.0;
}
`),this.userCode=`
const float initializationValue = ${o};
float getValue(int batch, int inIdx) {
${d}
return getX(batch, inIdx);
}
float getSegmentIdAtIndex(int inIdx) {
${p}
return getSegmentIds(inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = int(floor(float(outIdx) / float(
${s})) * float(${n}));
int currentSeg = int(mod(float(outIdx), float(${s})));
float sumValue = 0.0;
for (int i = 0; i < ${c}; 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
);
${h}
}
int inIdx = inOffset + ${c};
if (${u===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
);
${h}
} else if (${u===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
);
${h}
} else if (${u===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
);
${h}
}
setOutput(${l});
}
`}};function wG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],c=0,u=R.getAxesPermutation([c],o),h=a;u!=null&&(h=An({inputs:{x:a},backend:n,attrs:{perm:u}}),l.push(h),c=R.getInnerMostAxes(1,o)[0]);let d=R.segment_util.computeOutShape(h.shape,c,i),p=v.sizeFromShape([h.shape[c]]),f=ge({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=Xh(a.dtype),A=(x,_,I,S,T)=>{let E=x.shape[0],C=x.shape[1],$=R.segment_util.segOpComputeOptimalWindowSize(C,T),D={windowSize:$,inSize:C,batchSize:E,numSegments:T},P=new xG(D,_),H=n.compileAndRun(P,[x,I],S);if(l.push(H),H.shape[1]===T)return H;let V=J_({backend:n,attrs:{start:0,stop:T,step:1,dtype:"float32"}}),K=eb({inputs:{x:V},backend:n,attrs:{reps:[C/$]}});return l.push(V),l.push(K),A(H,_,K,S,T)},y=A(f,"unsortedSegmentSum",s,m,i),g=ge({inputs:{x:y},backend:n,attrs:{shape:d}}),w=g;if(u!=null){l.push(g);let x=R.getUndoAxesPermutation(u);w=An({inputs:{x:w},backend:n,attrs:{perm:x}})}return 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Found: ${this.outputs.map(y=>y.name)}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(let y of this.outputs){let g=y.sourceLayer,w=y.nodeIndex,x=y.tensorIndex;this.outputLayers.push(g),this.outputLayersNodeIndices.push(w),this.outputLayersTensorIndices.push(x)}for(let y of this.inputs){let g=y.sourceLayer,w=y.nodeIndex,x=y.tensorIndex;Br(w===0,"input layer has >1 nodes"),Br(x===0,"input layer has >1 tensors"),this.inputLayers.push(g),this.inputLayersNodeIndices.push(w),this.inputLayersTensorIndices.push(x)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let y=0;y<this.inputLayers.length;y++){let g=this.inputLayers[y];if(!(g instanceof Sl))throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${e.inputs}. Input ${y} (0-based) originates from layer type ${g.getClassName()}.`);this.inputNames.push(g.name),this.feedInputShapes.push(g.batchInputShape),this.feedInputNames.push(g.name)}for(let y of this.outputLayers)this.outputNames.push(y.name);this.internalInputShapes=this.inputs.map(y=>y.shape),this.internalOutputShapes=this.outputs.map(y=>y.shape);let t={},n={},r={},a={},s={},i=[],o=(y,g,w,x,_,I)=>{(x==null||_==null||I==null)&&(x=y.sourceLayer,_=y.nodeIndex,I=y.tensorIndex);let S=x.inboundNodes[_];if(w.indexOf(S)!==-1)throw new wr(`The tensor ${y.name} at layer "${x.name}" is part of a cycle.`);if(g.indexOf(S)!==-1)return;this.containerNodes.add(Hr.nodeKey(x,_)),x.id in s||(s[x.id]=Object.keys(s).length),w.indexOf(S)===-1&&w.push(S);let T=S.inboundLayers.length;for(let E=0;E<T;E++){let C=S.inputTensors[E],$=S.inboundLayers[E],D=S.nodeIndices[E],P=S.tensorIndices[E];o(C,g,w,$,D,P)}for(g.push(S);w.indexOf(S)>=0;)w.splice(w.indexOf(S),1);i.push(S)},l=[],c=[];for(let y of this.outputs)o(y,l,c);let u=i.slice().reverse();for(let y of u){n[y.id]=y,y.id in t||(t[y.id]=0);let g=t[y.id],w=r[y.outboundLayer.id]==null?0:r[y.outboundLayer.id];g=Math.max(g,w),r[y.outboundLayer.id]=g,a[y.outboundLayer.id]=y.outboundLayer,t[y.id]=g;for(let x=0;x<y.inboundLayers.length;x++){let _=y.inboundLayers[x],I=y.nodeIndices[x],S=_.inboundNodes[I],T=t[S.id]==null?0:t[S.id];t[S.id]=Math.max(g+1,T),n[S.id]=S}}let h={};for(let y in t){let g=t[y];g in h||(h[g]=[]),h[g].push(n[y])}let d={};for(let y in r){let g=r[y];g in d||(d[g]=[]),d[g].push(a[y])}let p=Object.keys(d).map(y=>parseInt(y,10)).sort(_p);this.layers=[];for(let y of p){let g=d[y];g.sort((w,x)=>{let _=s[w.id],I=s[x.id];return _<I?-1:_>I?1:0});for(let w of g)w instanceof Hr&&this.internalContainerRefs.push(w),this.layers.push(w)}this.layersByDepth=d,p=Object.keys(h).map(y=>parseInt(y,10)).sort(_p);let f=this.inputs.slice(),m=[];for(let y of p)for(let g of h[y]){let w=g.outboundLayer;if(w!=null){for(let x of g.inputTensors)if(f.indexOf(x)===-1)throw new wr(`Graph disconnected: cannot obtain value for tensor ${x} at layer "${w.name}". 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Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let e=[];for(let t of this.layers)e=e.concat(t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.layers)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.layers)t.push(...n.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){let n={},r=0;for(let s of this.layers)for(let i of s.weights){if(n[i.originalName]!=null)throw new B(`Duplicate weight name: ${i.originalName}`);n[i.originalName]=i,r++}let a=[];for(let s in e){let i=s;if(n[s]==null){let o=s.split("/");i=o.slice(0,-2).concat([o[o.length-1]]).join("/")}if(n[i]!=null)a.push([n[i],e[s]]);else if(t)throw new B(`Provided weight data has no target variable: ${s}`);delete n[i]}if(t){let s=[];for(let i in n)s.push(i);if(s.length>0)throw new B(`${s.length} of ${r} weights are not set: ${s}`)}gy(a)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${wm}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=Iy(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return U(()=>{e=mt(e);let n=new gi;for(let r=0;r<this.inputs.length;++r)n.add(this.inputs[r],e[r]);return Ec(this.outputs,n,t)})}computeMask(e,t){return U(()=>{e=mt(e);let n;return t==null?n=di(null,e.length):n=mt(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=Mp(e);if(t.length!==this.inputLayers.length)throw new B(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let i=0;i<t.length;i++){let o=this.inputLayers[i],l=t[i],c=o.name+"_0_0";n[c]=l}let r=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(_p);if(r.length>1)for(let i of r){let o=this.nodesByDepth[i];for(let l of o){let c=l.outboundLayer;if(this.inputLayers.map(f=>f.id).indexOf(c.id)!==-1)continue;let u=[];for(let f=0;f<l.inboundLayers.length;f++){let m=l.inboundLayers[f],A=l.nodeIndices[f],y=l.tensorIndices[f],g=`${m.name}_${A}_${y}`,w=n[g];u.push(w)}let h=c.computeOutputShape(gn(u)),d=Mp(h),p=c.inboundNodes.indexOf(l);for(let f=0;f<d.length;f++){let m=`${c.name}_${p}_${f}`;n[m]=d[f]}}}let a=[],s=[];for(let i=0;i<this.outputLayers.length;i++){let o=this.outputLayers[i],l=this.outputLayersNodeIndices[i],c=this.outputLayersTensorIndices[i],u=`${o.name}_${l}_${c}`;s.push(u)}for(let i=0;i<s.length;i++){let o=s[i];Br(o in n),a.push(n[o])}return gn(a)}runInternalGraph(e,t){t==null&&(t=di(null,e.length));let n={};for(let o=0;o<this.inputs.length;++o){let l=this.inputs[o],c=e[o],u=t[o];n[l.id]=[c,u]}let r=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(_p);for(let o of r){let l=this.nodesByDepth[o];for(let c of l){let u=c.outboundLayer,h=c.inputTensors,d=c.outputTensors,p=new Array;for(let f of h)f.id in n&&p.push(n[f.id]);if(p.length===h.length){let f={},m,A,y,g;if(c.callArgs!=null&&(f=c.callArgs),p.length===1){let[w,x]=p[0];f.mask==null&&(f.mask=x),y=mt(u.call(w,f)),g=mt(u.computeMask(w,x)),m=[w],A=[x]}else m=p.map(w=>w[0]),A=p.map(w=>w[1]),f.mask==null&&(f.mask=A),y=mt(u.call(m,f)),g=mt(u.computeMask(m,A));if(u.activityRegularizer)throw new De("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let w=0;w<d.length;++w){let x=d[w],_=y[w],I=g[w];n[x.id]=[_,I]}}}}let a=[],s=[],i=[];for(let o of this.outputs){Br(o.id in n,`Could not compute output ${o.name} : ${o.id}`);let[l,c]=n[o.id];i.push(l.shape),a.push(l),s.push(c)}return[a,s,i]}buildNodeConversionMap(e){let t={},n;for(let r of this.layers){n=r instanceof Hr?1:0;for(let a=0;a<r.inboundNodes.length;a++){let s=Hr.nodeKey(r,a);this.containerNodes.has(s)&&(t[s]=n,n+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new B(`Was asked to retrieve layer at index ${t}, but model only has ${this.layers.length} layer(s).`);return this.layers[t]}else if(e==null)throw new B("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new B(`No such layer: ${e}`)}calculateLosses(){return U(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let r=Hr.nodeKey(t,n);this.containerNodes.has(r)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),n=[];for(let s of this.layers){let i=s.getClassName(),o=s.getConfig(),l=[];for(let u=0;u<s.inboundNodes.length;u++){let h=s.inboundNodes[u],d=Hr.nodeKey(s,u),p={};if(this.containerNodes.has(d)){if(h.callArgs)try{JSON.stringify(h.callArgs),p=h.callArgs}catch(f){console.warn(`Layer ${s.name} was passed non-serializable keyword arguments: ${h.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`),p={}}if(h.inboundLayers.length>0){let f=[];for(let m=0;m<h.inboundLayers.length;m++){let A=h.inboundLayers[m],y=h.nodeIndices[m],g=h.tensorIndices[m],w=Hr.nodeKey(A,y),x=t[w];x==null&&(x=0),f.push([A.name,x,g,p])}l.push(f)}}}let c={};c.name=s.name,c.className=i,c.config=o,c.inboundNodes=l,n.push(c)}e.layers=n;let r=[];for(let s=0;s<this.inputLayers.length;s++){let i=this.inputLayers[s],o=this.inputLayersNodeIndices[s],l=Hr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.inputLayersTensorIndices[s];r.push([i.name,c,u])}e.inputLayers=r;let a=[];for(let s=0;s<this.outputLayers.length;s++){let i=this.outputLayers[s],o=this.outputLayersNodeIndices[s],l=Hr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.outputLayersTensorIndices[s];a.push([i.name,c,u])}return e.outputLayers=a,e}static fromConfig(e,t,n={},r=!1){let a={},s={};function i(m,A){m.name in s?s[m.name].push(A):s[m.name]=[A]}function o(m,A){let y=[],g;for(let w of A){let x=w[0],_=w[1],I=w[2];if(g=w[3]==null?{}:w[3],!(x in a)){i(m,A);return}let S=a[x];if(S.inboundNodes.length<=_){i(m,A);return}let T=S.inboundNodes[_];y.push(T.outputTensors[I])}y.length>0&&m.apply(gn(y),g)}function l(m){let A=m.name,y=br(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(r),a[A]=y,m.inboundNodes.forEach(g=>{if(!(g instanceof Array))throw new B(`Corrupted configuration, expected array for nodeData: ${g}`);i(y,g)})}let c=t.name,u=t.layers;for(let m of u)l(m);for(;!bY(s);)for(let m of u){let A=a[m.name];if(A.name in s){let y=s[A.name];delete s[A.name];for(let g of y)o(A,g)}}let h=[],d=[],p=t.inputLayers;for(let m of p){let A=m[0],y=m[1],g=m[2];Br(A in a);let w=a[A].inboundNodes[y].outputTensors;h.push(w[g])}let f=t.outputLayers;for(let m of f){let A=m[0],y=m[1],g=m[2];Br(A in a);let w=a[A].inboundNodes[y].outputTensors;d.push(w[g])}return new e({inputs:h,outputs:d,name:c})}get stateful(){if(this._stateful)throw new B("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(let e of this.layers)if(e.stateful)return!0;return!1}resetStates(){U(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function Jee(e,t,n){let r=t.length;if(e==null||Array.isArray(e)&&e.length===0)return t.map(a=>null);if(r===1)return Array.isArray(e)&&e.length===1?e:typeof e=="object"&&t[0]in e?[e[t[0]]]:[e];if(Array.isArray(e)){if(e.length!==r)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${r} outputs. Make sure a set of weights is provided for each model output.`);return e}else if(typeof e=="object"&&Object.keys(e).length>0&&typeof e[Object.keys(e)[0]]=="object"){let a=[];return t.forEach(s=>{s in e?a.push(e[s]):a.push(null)}),a}else throw new Error(`The model has multiple (${r}) outputs, so ${n} must be either an array with ${r} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function W3(e,t){return Jee(e,t,"classWeight")}async function B3(e,t,n,r){if(t!=null||r!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let a=U(()=>{if(e.shape.length===1)return e.clone();if(e.shape.length===2)if(e.shape[1]>1){let o=1;return e.argMax(o)}else{if(e.shape[1]===1)return e.reshape([e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await a.data());Ce(a);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${o} exists in the data but not in classWeight`);i.push(n[o])}),Qt(i,"float32")}else return null}function Yee(e,t){return W(e,t)}var Qee=32;function U3(e,t){let n,r,a=t;n=a.xs,r=a.ys,v.assert(n!=null&&r!=null,()=>`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}`);let s=V3("input",e.inputNames,n),i=V3("output",e.outputNames,r),o=s[0].shape[0];v.assert(s.length===e.inputs.length,()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${s.length} inputs. (Expected input keys: ${JSON.stringify(e.inputNames)})`),v.assert(i.length===e.outputs.length,()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${i.length} outputs. (Expected output keys: ${JSON.stringify(e.outputNames)})`);for(let l=0;l<s.length;l++)v.assert(s[l].shape[0]===o,()=>`Batch size mismatch: input ${e.inputNames[l]} has ${s[l].shape[0]}; expected ${o} based on input ${e.inputNames[0]}.`);for(let l=0;l<i.length;l++)v.assert(i[l].shape[0]===o,()=>`Batch size mismatch: output ${e.outputNames[l]} has ${i[l].shape[0]}; expected ${o} based on input ${e.inputNames[0]}.`);return{xs:s,ys:i}}function V3(e,t,n){if(n instanceof Qe)return[n];if(Array.isArray(n))return v.assert(n.length===t.length,()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`),n;{let r=[];for(let a of t){if(n[a]==null)throw new B(`The feature data generated by the dataset lacks the required ${e} key '${a}'.`);r.push(n[a])}return r}}function ete(e){if(e.length===3)throw new De("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function nte(e,t,n){let r=n.batchesPerEpoch!=null;if(v.assert(e.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),v.assert(!r||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. Use validationData instead."),e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;try{let a=n.validationData!=null,s,i;if(a)if(H3(n.validationData))v.assert(n.validationBatches==null||n.validationBatches>0&&Number.isInteger(n.validationBatches),()=>`For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${n.validationBatches}`);else{let A=ete(n.validationData);s=A.xs,i=A.ys}let o=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),c;a?c=l.slice().concat(l.map(A=>"val_"+A)):c=l.slice();let u=T3(n.callbacks,n.yieldEvery),h=n.verbose==null?1:n.verbose,{callbackList:d,history:p}=E3(u,h,n.epochs,null,null,tte(t,n),null,a,c);d.setModel(e),e.history=p,await d.onTrainBegin(),e.stopTraining_=!1;let f=n.initialEpoch==null?0:n.initialEpoch,m=await t.iterator();for(;f<n.epochs;){let A={};await d.onEpochBegin(f);let y=0,g=0;for(r||(m=await t.iterator());r?y<n.batchesPerEpoch:!0;){let w=await m.next();if(r&&w.done){console.warn(`You provided \`batchesPerEpoch\` as ${n.batchesPerEpoch}, but your dataset iterator ran out of data after ${y} batches; interrupting training. 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t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),s=[],i=()=>{let c=[];for(let p=0;p<this.inputs.length;++p)c.push({key:this.inputs[p],value:n[p]});let u=new gi(c),h=Ec(this.outputs,u,{training:!0}),d;for(let p=0;p<this.lossFunctions.length;++p){let f=this.lossFunctions[p](r[p],h[p]);a[p]!=null&&(f=Yee(f,a[p]));let m=bt(f);t.push(m),p===0?d=f:d=oe(d,f)}for(let p=0;p<this.metricsTensors.length;++p){let f;if(this.outputs.length>1&&p<this.outputs.length)f=t[p];else{let m=this.metricsTensors[p][0],A=this.metricsTensors[p][1];f=bt(m(r[A],h[A]))}Bt(f),s.push(f)}return d=bt(d),this.calculateLosses().forEach(p=>{d=oe(d,p)}),d},o=this.collectedTrainableWeights.map(c=>c.read()),l=!0;return[this.optimizer_.minimize(i,l,o)].concat(s)}}makeTestFunction(){this.testFunction=e=>U(()=>{let t=[],n,r=e.slice(0,this.inputs.length),a=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=[];for(let l=0;l<this.inputs.length;++l)s.push({key:this.inputs[l],value:r[l]});let i=new gi(s),o=Ec(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let c=this.lossFunctions[l],u=bt(c(a[l],o[l]));l===0?n=u:n=oe(n,u),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let c=this.metricsTensors[l][0],u=this.metricsTensors[l][1],h=bt(c(a[u],o[u]));t.push(h)}return t})}async fit(e,t,n={}){return ite(this,e,t,n)}async fitDataset(e,t){return nte(this,e,t)}async trainOnBatch(e,t){let n=await this.standardizeUserData(e,t),r=n[0],a=n[1],s=this.makeTrainFunction()(r.concat(a)),i=[];for(let o of s){let l=await o.data();i.push(l[0])}return Ce(s),gn(i)}getNamedWeights(e){let t=[],n=e!=null&&e.trainableOnly,r=n?this.trainableWeights:this.weights,a=this.getWeights(n);for(let s=0;s<r.length;++s)n&&!r[s].trainable||t.push({name:r[s].originalName,tensor:a[s]});return t}set stopTraining(e){this.stopTraining_=e}get stopTraining(){return this.stopTraining_}get optimizer(){return this.optimizer_}set optimizer(e){this.optimizer_!==e&&(this.optimizer_=e,this.isOptimizerOwned=!1)}dispose(){let e=super.dispose();if(e.refCountAfterDispose===0&&this.optimizer!=null&&this.isOptimizerOwned){let t=Zh().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-Zh().numTensors}return e}getLossIdentifiers(){let e;if(typeof this.loss=="string")e=ia(this.loss);else if(Array.isArray(this.loss)){for(let t of this.loss)if(typeof t!="string")throw new Error("Serialization of non-string loss is not supported.");e=this.loss.map(t=>ia(t))}else{let t=Object.keys(this.loss);e={};let n=this.loss;for(let r of t)if(typeof n[r]=="string")e[r]=ia(n[r]);else throw new Error("Serialization of non-string loss is not supported.")}return e}getMetricIdentifiers(){if(typeof this.metrics=="string"||typeof this.metrics=="function")return[ia(Vp(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(e=>ia(Vp(e)));{let e={};for(let t in this.metrics)e[t]=ia(Vp(this.metrics[t]));return e}}getTrainingConfig(){return{loss:this.getLossIdentifiers(),metrics:this.getMetricIdentifiers(),optimizer_config:{class_name:this.optimizer.getClassName(),config:this.optimizer.getConfig()}}}loadTrainingConfig(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.");let t=Tc(e.optimizer_config),n=br(t),r;if(typeof e.loss=="string")r=pi(e.loss);else if(Array.isArray(e.loss))r=e.loss.map(s=>pi(s));else if(e.loss!=null){r={};for(let s in e.loss)r[s]=pi(e.loss[s])}let a;if(Array.isArray(e.metrics))a=e.metrics.map(s=>pi(s));else if(e.metrics!=null){a={};for(let s in e.metrics)a[s]=pi(e.metrics[s])}this.compile({loss:r,metrics:a,optimizer:n})}async save(e,t){if(typeof e=="string"){let i=dn.getSaveHandlers(e);if(i.length===0)throw new B(`Cannot find any save handlers for URL '${e}'`);if(i.length>1)throw new B(`Found more than one (${i.length}) save handlers for URL '${e}'`);e=i[0]}if(e.save==null)throw new B("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await dn.encodeWeights(this.getNamedWeights(t)),r=!1,a=null,s={modelTopology:this.toJSON(a,r),format:hte,generatedBy:`TensorFlow.js tfjs-layers v${wm}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){s.trainingConfig=this.getTrainingConfig();let i="optimizer",{data:o,specs:l}=await dn.encodeWeights(await this.optimizer.getWeights(),i);n.specs.push(...l),n.data=dn.concatenateArrayBuffers([n.data,o])}if(this.userDefinedMetadata!=null){let i=!0;O3(this.userDefinedMetadata,this.name,i),s.userDefinedMetadata=this.userDefinedMetadata}return s.weightData=n.data,s.weightSpecs=n.specs,e.save(s)}setUserDefinedMetadata(e){O3(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};ea.className="Model";re.registerClass(ea);var K3=class extends ea{};K3.className="Functional";re.registerClass(K3);async function dte(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let r=Tc(n),a=br(r,t);if(e.weightsManifest!=null){let s=await dn.loadWeights(e.weightsManifest,e.pathPrefix,a.weights.map(o=>o.originalName)),i={};for(let o of a.weights)i[o.originalName]=s[o.originalName];a.loadWeights(i),Ce(s)}return a}async function fte(e,t){if(t==null&&(t={}),typeof e=="string"){let n=dn.getLoadHandlers(e,t);if(n.length===0)n.push(dn.browserHTTPRequest(e,t));else if(n.length>1)throw new B(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return pte(e,void 0,t)}async function pte(e,t,n){if(n==null&&(n={}),e.load==null)throw new B("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let r=await e.load(),a=r.modelTopology;a.model_config!=null&&(a=a.model_config);let s=n.strict==null?!0:n.strict,i=r.weightData!=null&&r.weightSpecs!=null&&s,o=br(Tc(a),t,i),l=r.trainingConfig;if(l!=null&&o.loadTrainingConfig(l),r.userDefinedMetadata!=null&&o.setUserDefinedMetadata(r.userDefinedMetadata),r.weightData!=null){if(r.weightSpecs==null)throw new B("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");let{modelWeights:c,optimizerWeights:u}=mte(r.weightData,r.weightSpecs);o.loadWeights(c,s),o.optimizer!=null&&u.length>0&&await o.optimizer.setWeights(u),Ce(c),Ce(u.map(h=>h.tensor))}return o}function mte(e,t){let n=dn.decodeWeights(e,t),r={},a=[];return t.forEach(s=>{s.group==="optimizer"?a.push({name:s.name,tensor:n[s.name]}):r[s.name]=n[s.name]}),{modelWeights:r,optimizerWeights:a}}var Yo=class extends ea{constructor(e){super({inputs:[],outputs:[]});if(e=e||{},this.trainable=!0,this.built=!1,this.name=e.name!=null?e.name:Fp("sequential_"),e.layers!=null)for(let t of e.layers)this.add(t)}checkShape(e){if(e.inboundNodes[0].outputTensors[0].shape.some(t=>t<0))throw new B(`Negative dimension size caused by adding layer ${e.name} with input shape [${e.inboundNodes[0].inputTensors[0].shape}]`)}add(e){let t=e instanceof Yo||e instanceof ea,n;if(t){if(n=e,n.outputs.length!==1)throw new B("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");if(n.inputs.length!==1)throw new B("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 B("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");let r=I3({batchShape:e.batchInputShape,dtype:e.dtype,name:e.name+"_input"});e.apply(r)}if(t)this.outputs=n.outputs,this.inputs=n.inputs;else{if(e.inboundNodes.length!==1)throw new B(`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 B("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=k3(this.outputs[0])}this.inboundNodes=[],new Dp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:di(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(r=>r.shape),outputShapes:this.outputs[0].shape})}else{let r=e.apply(this.outputs[0]);if(Array.isArray(r))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=[r],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(e),this.built=!1}pop(){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{let 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]}}call(e,t){return this.model==null&&this.build(),this.model.call(e,t)}build(e){if(dt(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 ea({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=!0}countParams(){return this.built||this.build(),super.countParams()}summary(e,t,n=console.log){this.built||this.build(),super.summary(e,t,n)}setWeights(e){this.model==null&&this.build(),this.model.setWeights(e)}evaluate(e,t,n={}){if(!this.built)throw new wr("The model needs to be compiled before being used.");return this.model.evaluate(e,t,n)}async evaluateDataset(e,t){if(!this.built)throw new wr("The model needs to be compiled before being used.");return this.model.evaluateDataset(e,t)}predict(e,t={}){return this.model==null&&this.build(),this.model.predict(e,t)}predictOnBatch(e){return this.model==null&&this.build(),this.model.predictOnBatch(e)}compile(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}get optimizer(){return this.model==null?void 0:this.model.optimizer}set optimizer(e){this.model.optimizer=e}async fit(e,t,n={}){if(!this.built)throw new wr("The model needs to be compiled before being used.");return this.model.fit(e,t,n)}async fitDataset(e,t){if(!this.built)throw new wr("The model needs to be compiled before being used.");return this.model.fitDataset(e,t)}async trainOnBatch(e,t){return this.model.trainOnBatch(e,t)}static fromConfig(e,t,n={},r=!1){let a,s={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new B("Legacy serialization format not supported yet.");a=t}else v.assert(t.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),a=t.layers,delete t.layers,s=t;let i=new e(s);if(!(i instanceof Yo))throw new De(`Sequential.fromConfig called on non-Sequential input: ${i}`);for(let o of a){let l=br(o,void 0,r);r&&l.setFastWeightInitDuringBuild(!0),i.add(l)}return i}set stopTraining(e){if(this.model==null)throw new B("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=e}get stopTraining(){if(this.model==null)throw new B("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};Yo.className="Sequential";re.registerClass(Yo);function W8(e){return new ea(e)}function B8(e){return new Yo(e)}function V8(e,t){return t==null&&(t={}),fte(e,t)}function B0(e){return I3(e)}function U8(e,t){ur.registerCallbackConstructor(e,t)}var Mn=class extends re.Serializable{getConfig(){return{}}},Z3=class extends Mn{apply(e,t=1){return JY(e,t)}};Z3.className="elu";re.registerClass(Z3);var J3=class extends Mn{apply(e){return Ad(e)}};J3.className="selu";re.registerClass(J3);var Y3=class extends Mn{apply(e){return Fr(e)}};Y3.className="relu";re.registerClass(Y3);var Q3=class extends Mn{apply(e){return U(()=>Xo(6,Fr(e)))}};Q3.className="relu6";re.registerClass(Q3);var e7=class extends Mn{apply(e){return e}};e7.className="linear";re.registerClass(e7);var t7=class extends Mn{apply(e){return er(e)}};t7.className="sigmoid";re.registerClass(t7);var n7=class extends Mn{apply(e){return QY(e)}};n7.className="hardSigmoid";re.registerClass(n7);var r7=class extends Mn{apply(e){return Go(e)}};r7.className="softplus";re.registerClass(r7);var a7=class extends Mn{apply(e){return YY(e)}};a7.className="softsign";re.registerClass(a7);var s7=class extends Mn{apply(e){return Vo(e)}};s7.className="tanh";re.registerClass(s7);var Ry=class extends Mn{apply(e,t=-1){return Lu(e,t)}};Ry.className="softmax";re.registerClass(Ry);var i7=class extends Mn{apply(e,t=-1){return ud(e,t)}};i7.className="logSoftmax";re.registerClass(i7);var o7=class extends Mn{apply(e,t=1){return U(()=>er(e.mul(t)).mul(e))}};o7.className="swish";re.registerClass(o7);function za(e){return e.getClassName()}function Fy(e,t={}){return xc(e,re.SerializationMap.getMap().classNameMap,t,"activation")}function Pa(e){if(e==null){let t={};return t.className="linear",t.config={},Fy(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},Fy(t)}else return e instanceof Mn?e:Fy(e)}function My(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var l7=class extends re.Serializable{},Rc=class extends l7{constructor(e){super();My(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return U(()=>{let t=Ct([1]);return this.hasL1&&(t=oe(t,Te(W(this.l1,$t(e))))),this.hasL2&&(t=oe(t,Te(W(this.l2,kc(e))))),t.asScalar()})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Rc.className="L1L2";re.registerClass(Rc);function Ate(e){return My(e),new Rc({l1:e!=null?e.l1:null,l2:0})}function yte(e){return My(e),new Rc({l2:e!=null?e.l2:null,l1:0})}var u7={l1l2:"L1L2"};function pt(e){return XA(e)}function c7(e,t={}){return xc(e,re.SerializationMap.getMap().classNameMap,t,"regularizer")}function xt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in u7?u7[e]:e,config:{}};return c7(t)}else return e instanceof l7?e:c7(e)}var $y=class extends Xe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Pe(e);let n=Fr(e);return this.maxValue!=null&&(n=fn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};$y.className="ReLU";re.registerClass($y);var Dy=class extends Xe{constructor(e){super(e==null?{}:e);this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Pe(e);return Fu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};Dy.className="LeakyReLU";re.registerClass(Dy);var Oy=class extends Xe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=gt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=xt(e.alphaRegularizer),this.alphaConstraint=Lt(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new B(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=dt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r<e.length;++r)n[r]=e[r];this.inputSpec=[new Vt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Pe(e),Ou(e,this.alpha.read())}getConfig(){let e={alphaInitializer:kt(this.alphaInitializer),alphaRegularizer:pt(this.alphaRegularizer),alphaConstraint:Pt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};Oy.className="PReLU";re.registerClass(Oy);var zy=class extends Xe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new De(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Pe(e);return Ho(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};zy.className="ELU";re.registerClass(zy);var Py=class extends Xe{constructor(e){super(e==null?{}:e);this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=Pe(e);return n.mul(bc(n.greater(this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};Py.className="ThresholdedReLU";re.registerClass(Py);var Ly=class extends Xe{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new Ry().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Ly.className="Softmax";re.registerClass(Ly);function Cl(e,t,n){if(typeof e=="number")return di(e,t);if(e.length!==t)throw new B(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let r=0;r<t;++r){let a=e[r];if(!qY(a))throw new B(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${a}`)}return e}function vr(e,t,n,r,a=1){if(e==null)return e;let s=t+(t-1)*(a-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+r-1)/r)}function Hp(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+Da([n-t,0]);else if(r==="same")e=e*t;else throw new B(`Unsupport padding mode: ${r}.`);return e}function Wy(e,t){return U(()=>(Tt(t),t==="channelsFirst"?at(e,[0,2,3,1]):e))}function h7(e,t){return U(()=>(Tt(t),t==="channelsFirst"?at(e,[0,2,3,4,1]):e))}function gte(e,t,n,r=1,a="valid",s,i=1){return U(()=>{if(s==null&&(s=xr()),Tt(s),e.shape.length!==3)throw new B(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new B(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new B(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=at(e,[0,2,1])),a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=nd(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Ur(o,n)),o})}function d7(e,t,n,r=[1,1],a="valid",s,i,o=null){return U(()=>{if(s==null&&(s=xr()),Tt(s),e.rank!==3&&e.rank!==4)throw new B(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new B(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=Wy(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=va.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=at(l,[0,3,1,2])),l})}function xte(e,t,n,r=[1,1,1],a="valid",s,i){return U(()=>{if(s==null&&(s=xr()),Tt(s),e.rank!==4&&e.rank!==5)throw new B(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new B(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=h7(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=qf(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Ur(o,n)),s==="channelsFirst"&&(o=at(o,[0,4,1,2,3])),o})}var By=class extends Xe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",By.verifyArgs(t),this.rank=e,jt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new De(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Cl(t.kernelSize,e,"kernelSize"),this.strides=Cl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,jn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Tt(this.dataFormat),this.activation=Pa(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=gt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Lt(t.biasConstraint),this.biasRegularizer=xt(t.biasRegularizer),this.activityRegularizer=xt(t.activityRegularizer),this.dilationRate=Cl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new B(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new B(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new B(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Br("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!ZA(e.kernelSize,"number",1,3))throw new B(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:za(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),biasConstraint:Pt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Fc=class extends By{constructor(e,t){super(e,t);this.kernel=null,Fc.verifyArgs(t),this.filters=t.filters,jt(this.filters,"filters"),this.kernelInitializer=gt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Lt(t.kernelConstraint),this.kernelRegularizer=xt(t.kernelRegularizer)}build(e){e=dt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return U(()=>{e=Pe(e);let n,r=this.bias==null?null:this.bias.read(),a=a3(this.activation.getClassName());if(a!=null&&this.rank===2)n=d7(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=gte(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=d7(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=xte(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new De("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=dt(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let a=0;a<n.length;++a){let s=vr(n[a],this.kernelSize[a],this.padding,this.strides[a],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[a]);t.push(s)}let r=[e[0]];return this.dataFormat==="channelsLast"?(r=r.concat(t),r.push(this.filters)):(r.push(this.filters),r=r.concat(t)),r}getConfig(){let e={filters:this.filters,kernelInitializer:kt(this.kernelInitializer),kernelRegularizer:pt(this.kernelRegularizer),kernelConstraint:Pt(this.kernelConstraint)},t=super.getConfig();return Object.assign(e,t),e}static verifyArgs(e){if(!("filters"in e)||typeof e.filters!="number"||e.filters<1)throw new B(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Mc=class extends Fc{constructor(e){super(2,e);Mc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!ZA(e.kernelSize,"number",1,2))throw new B(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Mc.className="Conv2D";re.registerClass(Mc);var jp=class extends Fc{constructor(e){super(3,e);jp.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!(Array.isArray(e.kernelSize)&&(e.kernelSize.length===1||e.kernelSize.length===3)))throw new B(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};jp.className="Conv3D";re.registerClass(jp);var Vy=class extends Mc{constructor(e){super(e);if(this.inputSpec=[new Vt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new B(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=dt(e),e.length!==4)throw new B("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Vt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return U(()=>{let n=Pe(e);if(n.shape.length!==4)throw new B(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],c=this.kernelSize[0],u=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Hp(o,h,c,this.padding),f=Hp(l,d,u,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=at(n,[0,2,3,1]));let A=rd(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=at(A,[0,3,1,2])),this.bias!=null&&(A=Ur(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=dt(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Hp(t[r],o,s,this.padding),t[a]=Hp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Vy.className="Conv2DTranspose";re.registerClass(Vy);var p7=class extends Fc{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new B("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new B("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new B(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=xt(t.depthwiseRegularizer),this.depthwiseConstraint=Lt(t.depthwiseConstraint),this.pointwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=xt(t.pointwiseRegularizer),this.pointwiseConstraint=Lt(t.pointwiseConstraint)}build(e){if(e=dt(e),e.length<this.rank+2)throw new B(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Vt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return U(()=>{e=Pe(e);let n;if(this.rank===1)throw new De("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=at(e,[0,2,3,1])),n=om(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Ur(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=at(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=pt(this.depthwiseRegularizer),e.pointwiseRegularizer=pt(this.pointwiseRegularizer),e.depthwiseConstraint=Pt(this.depthwiseConstraint),e.pointwiseConstraint=Pt(this.pointwiseConstraint),e}};p7.className="SeparableConv";var Uy=class extends p7{constructor(e){super(2,e)}};Uy.className="SeparableConv2D";re.registerClass(Uy);var Gp=class extends Fc{constructor(e){super(1,e);Gp.verifyArgs(e),this.inputSpec=[{ndim:3}]}getConfig(){let e=super.getConfig();return delete e.rank,delete e.dataFormat,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!ZA(e.kernelSize,"number",1,1))throw new B(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Gp.className="Conv1D";re.registerClass(Gp);var Hy=class extends Xe{constructor(e){super(e);typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(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]]}call(e,t){return U(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=bp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return bp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=bp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return bp(n,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Hy.className="Cropping2D";re.registerClass(Hy);var jy=class extends Xe{constructor(e){super(e);this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Tt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,HY(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return U(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=at(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return at(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};jy.className="UpSampling2D";re.registerClass(jy);function wte(e,t,n=[1,1],r="valid",a,s){return U(()=>{a==null&&(a=xr()),Tt(a);let i=Wy(e,a);if(e.rank!==4)throw new B(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new B(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Uo(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=at(i,[0,3,1,2])),i})}var Gy=class extends By{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=gt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Lt(e.depthwiseConstraint),this.depthwiseRegularizer=xt(e.depthwiseRegularizer)}build(e){if(e=dt(e),e.length<4)throw new B(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return U(()=>{e=Pe(e);let n=wte(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Ur(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=dt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=vr(t,this.kernelSize[0],this.padding,this.strides[0]),s=vr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.depthwiseRegularizer=pt(this.depthwiseRegularizer),e.depthwiseConstraint=Pt(this.depthwiseRegularizer),e}};Gy.className="DepthwiseConv2D";re.registerClass(Gy);function f7(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new B("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function m7(e,t,n,r=!1,a,s,i=!1,o=!1){return U(()=>{let l=t.shape.length;if(l<3)throw new B(`Input should be at least 3D, but is ${l}D.`);let c=[1,0].concat(_r(2,l));if(t=at(t,c),s!=null)throw new De("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=In(a,-1)),a=at(a,c)),r&&(t=Tn(t,0),a!=null&&(a=Tn(a,0)));let u=[],h,d=n,p=t.shape[0],f=rr(t),m;a!=null&&(m=rr(a));for(let y=0;y<p;++y){let g=f[y],w=U(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let x=U(()=>{let _=m[y],I=Sn(_).sub(_),S=w[0].mul(_).add(d[0].mul(I)),T=d.map((E,C)=>w[1][C].mul(_).add(E.mul(I)));return{output:S,newStates:T}});h=x.output,d=x.newStates}o&&u.push(h)}let A;return o&&(A=En(u,1)),[h,A,d]})}var $r=class extends Xe{constructor(e){super(e);let t;if(e.cell==null)throw new B("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new qp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new B("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new Vt({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return _r(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){Ay(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return U(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new De("Constants support is not implemented in RNN yet.");Ay(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Vt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new De("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new B(`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(i=>new Vt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){U(()=>{if(!this.stateful)throw new sa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new B("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(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Ct([n,r])):this.states_=[Ct([n,this.cell.stateSize])];else if(e==null)Ce(this.states_),this.keptStates!=null&&(Ce(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Ct([n,r])):this.states_[0]=Ct([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t===!0?this.keptStates.push(this.states_.slice()):Ce(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new B(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Bt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=f7(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Vt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Ar){let o=[e].concat(s),l=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=l;let u=super.apply(o,t);return this.inputSpec=c,u}else return super.apply(e,t)}call(e,t){return U(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new B(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=m7((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],c=o[1],u=o[2];this.stateful&&this.resetStates(u,r);let h=this.returnSequences?c:l;return this.returnState?[h].concat(u):h})}getInitialState(e){return U(()=>{let t=Ct(e.shape);return t=Te(t,[1,2]),t=vc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?ny(t,[1,n]):t):this.cell.stateSize>1?[ny(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===$r.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=br(r,n);return new e(Object.assign(t,{cell:a}))}};$r.className="RNN";re.registerClass($r);var Nc=class extends Xe{},Xp=class extends Nc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,jt(this.units,"units"),this.activation=Pa(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Lt(e.kernelConstraint),this.recurrentConstraint=Lt(e.recurrentConstraint),this.biasConstraint=Lt(e.biasConstraint),this.dropout=Nl([1,Da([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Nl([1,Da([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=dt(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return U(()=>{if(e=e,e.length!==2)throw new B(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=La({ones:()=>Sn(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=La({ones:()=>Sn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Vr(W(e,s),this.kernel.read()):a=Vr(e,this.kernel.read()),this.bias!=null&&(a=Ur(a,this.bias.read())),i!=null&&(n=W(n,i));let o=oe(a,Vr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:za(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),recurrentConstraint:Pt(this.recurrentConstraint),biasConstraint:Pt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Xp.className="SimpleRNNCell";re.registerClass(Xp);var qy=class extends $r{constructor(e){e.cell=new Xp(e),super(e)}call(e,t){return U(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};qy.className="SimpleRNN";re.registerClass(qy);var Kp=class extends Nc{constructor(e){super(e);if(this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new B("GRUCell does not support reset_after parameter set to true.");this.units=e.units,jt(this.units,"units"),this.activation=Pa(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Pa(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Lt(e.kernelConstraint),this.recurrentConstraint=Lt(e.recurrentConstraint),this.biasConstraint=Lt(e.biasConstraint),this.dropout=Nl([1,Da([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Nl([1,Da([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=dt(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return U(()=>{if(e=e,e.length!==2)throw new B(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=La({ones:()=>Sn(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=La({ones:()=>Sn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=W(e,a[0]));let c=Vr(e,this.kernel.read());this.useBias&&(c=Ur(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=W(r,s[0]));let u=this.recurrentKernel.read(),[h,d]=an(u,[2*this.units,this.units],u.rank-1),p=Vr(r,h),[f,m,A]=an(c,3,c.rank-1),[y,g]=an(p,2,p.rank-1);i=this.recurrentActivation.apply(oe(f,y)),o=this.recurrentActivation.apply(oe(m,g));let w=Vr(W(o,r),d);l=this.activation.apply(oe(A,w));let x=oe(W(i,r),W(oe(1,_t(i)),l));return[x,x]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:za(this.activation),recurrentActivation:za(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),recurrentConstraint:Pt(this.recurrentConstraint),biasConstraint:Pt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};Kp.className="GRUCell";re.registerClass(Kp);var Xy=class extends $r{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Kp(e),super(e)}call(e,t){return U(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Xy.className="GRU";re.registerClass(Xy);var $c=class extends Nc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,jt(this.units,"units"),this.activation=Pa(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Pa(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Lt(e.kernelConstraint),this.recurrentConstraint=Lt(e.recurrentConstraint),this.biasConstraint=Lt(e.biasConstraint),this.dropout=Nl([1,Da([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Nl([1,Da([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=dt(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends lr{apply(i,o){let l=a.apply([s]),c=new kp().apply([s]),u=a.apply([s*2]);return p3(p3(l,c),u)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return U(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new B(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=La({ones:()=>Sn(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=La({ones:()=>Sn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0<this.dropout&&this.dropout<1&&(e=W(e,s[0]));let h=Vr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=W(r,i[0])),h=oe(h,Vr(r,this.recurrentKernel.read())),this.useBias&&(h=Ur(h,this.bias.read()));let[d,p,f,m]=an(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),c=oe(W(l,a),W(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let A=W(u,this.activation.apply(c));return[A,A,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:za(this.activation),recurrentActivation:za(this.recurrentActivation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),recurrentConstraint:Pt(this.recurrentConstraint),biasConstraint:Pt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};$c.className="LSTMCell";re.registerClass($c);var Ky=class extends $r{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new $c(e),super(e)}call(e,t){return U(()=>{this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ky.className="LSTM";re.registerClass(Ky);var qp=class extends Nc{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return U(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){Ay(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{mi(`RNNCell_${r}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(br(a,n));return new e({cells:r})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return yy(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}gy(t)}};qp.className="StackedRNNCells";re.registerClass(qp);function La(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>m3(t(),n),i=()=>Ic(s,t,r);return!a||a<=1?Bt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Bt(o.clone()))}var _te=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},A7=class extends $r{constructor(e){if(e.unroll)throw new De("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new De("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Vt({ndim:5})]}call(e,t){return U(()=>{if(this.cell.dropoutMask!=null&&(Ce(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ce(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new B("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return U(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Ct(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){U(()=>{if(!this.stateful)throw new sa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new B("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(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ct(a)):this.states_=[Ct(a)];else if(e==null)Ce(this.states_),this.keptStates!=null&&(Ce(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ct(a)):this.states_[0]=Ct(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):Ce(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new B(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Bt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],c=e[o?4:3],u=vr(l,r[0],a,s[0],i[0]),h=vr(c,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,u,h]:[u,h,n]]}};A7.className="ConvRNN2D";var Zp=class extends $c{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,jt(this.filters,"filters"),this.kernelSize=Cl(n,2,"kernelSize"),this.kernelSize.forEach(o=>jt(o,"kernelSize")),this.strides=Cl(r||1,2,"strides"),this.strides.forEach(o=>jt(o,"strides")),this.padding=a||"valid",jn(this.padding),this.dataFormat=s||"channelsLast",Tt(this.dataFormat),this.dilationRate=Cl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>jt(o,"dilationRate"))}build(e){var t;e=dt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;o=new(t=class extends lr{apply(u,h){let d=l.apply([c]),p=Rr([c]),f=l.apply([c*2]);return ay([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return U(()=>{if(e.length!==3)throw new B(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=La({ones:()=>Sn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(J,ae,Y)=>!ae||!ae[Y]?J:W(ae[Y],J),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=La({ones:()=>Sn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,x,_,I]=an(this.kernel.read(),i,g),[S,T,E,C]=this.useBias?an(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,w,S,this.padding),u=this.inputConv(u,x,T,this.padding),h=this.inputConv(h,_,E,this.padding),d=this.inputConv(d,I,C,this.padding);let[$,D,P,H]=an(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,$),m=this.recurrentConv(m,D),A=this.recurrentConv(A,P),y=this.recurrentConv(y,H);let V=this.recurrentActivation.apply(oe(c,f)),K=this.recurrentActivation.apply(oe(u,m)),X=oe(W(K,s),W(V,this.activation.apply(oe(h,A)))),ee=W(this.recurrentActivation.apply(oe(d,y)),this.activation.apply(X));return[ee,ee,X]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=_te(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=Zr(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Ur(a,n,this.dataFormat):a}recurrentConv(e,t){return Zr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Zp.className="ConvLSTM2DCell";re.registerClass(Zp);var Zy=class extends A7{constructor(e){let t=new Zp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Zy.className="ConvLSTM2D";re.registerClass(Zy);var Jp=class extends Xe{constructor(e){super(e);this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let r=0;r<this.noiseShape.length;++r)n.push(this.noiseShape[r]==null?t[r]:this.noiseShape[r]);return n}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Ic(()=>m3(n,this.rate,a,this.seed),()=>n,r)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};Jp.className="Dropout";re.registerClass(Jp);var Jy=class extends Jp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Jy.className="SpatialDropout1D";re.registerClass(Jy);var Yy=class extends Xe{constructor(e){super(e);if(this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,jt(this.units,"units"),this.activation=Pa(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Lt(e.kernelConstraint),this.biasConstraint=Lt(e.biasConstraint),this.kernelRegularizer=xt(e.kernelRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.activityRegularizer=xt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=dt(e);let t=e[e.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:t}}],this.built=!0}computeOutputShape(e){e=dt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=a3(this.activation.getClassName()),a;return r!=null?a=Vr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Vr(n,this.kernel.read()),this.bias!=null&&(a=Ur(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:za(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),biasConstraint:Pt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Yy.className="Dense";re.registerClass(Yy);var Qy=class extends Xe{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=dt(e);for(let t of e.slice(1))if(t==null)throw new B(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],$a(e,1)]}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return ZY(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Qy.className="Flatten";re.registerClass(Qy);var eg=class extends Xe{constructor(e){super(e);this.supportsMasking=!0,this.activation=Pa(e.activation)}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.activation.apply(n)})}getConfig(){let e={activation:za(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};eg.className="Activation";re.registerClass(eg);var tg=class extends Xe{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return U(()=>(e=Pe(e),XY(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};tg.className="RepeatVector";re.registerClass(tg);var ng=class extends Xe{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new B("Can only specifiy one unknown dimension.");else a*=l}let i=$a(e);if(s!==null){if(a===0||i%a!=0)throw new B(n);r[s]=i/a}else if(i!==a)throw new B(n);return r}computeOutputShape(e){let t=!1;for(let n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};ng.className="Reshape";re.registerClass(ng);var rg=class extends Xe{constructor(e){super(e);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.`);let t=_r(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Vt({ndim:this.dims.length+1})]}computeOutputShape(e){e=dt(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return at(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};rg.className="Permute";re.registerClass(rg);var ag=class extends Xe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Pe(e),r=-1;return Iu(qs(n,this.maskValue),r)}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=Iu(qs(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};ag.className="Masking";re.registerClass(ag);var sg=class extends Xe{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(mt(e.inputLength))}this.inputDim=e.inputDim,jt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,jt(this.outputDim,"outputDim"),this.embeddingsInitializer=gt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=xt(e.embeddingsRegularizer),this.activityRegularizer=xt(e.activityRegularizer),this.embeddingsConstraint=Lt(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return U(()=>this.maskZero?(e=Pe(e),qs(e,He(e))):null)}computeOutputShape(e){if(e=dt(e),this.inputLength==null)return[...e,this.outputDim];let t=mt(this.inputLength);if(t.length!==e.length-1)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=bc(n,"int32")),f3(this.embeddings.read(),n.as1D()).reshape(dt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:kt(this.embeddingsInitializer),embeddingsRegularizer:pt(this.embeddingsRegularizer),activityRegularizer:pt(this.activityRegularizer),embeddingsConstraint:Pt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};sg.className="Embedding";re.registerClass(sg);var wi=class extends Xe{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new De}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new B("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[dt(e)]),e=e,e.length<2)throw new B(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let a of e)a!=null&&a[0]!==null&&t.push(a[0]);if(t=Ma(t),t.length>1)throw new B(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let a=1;a<e.length;++a){let s=e[a]==null?null:e[a].slice(1);n=this.computeElementwiseOpOutputShape(n,s)}let r=e.map(a=>a.length);e.indexOf(null)===-1&&Ma(r).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return U(()=>{if(e=e,this.reshapeRequired){let n=[],r=e.map(a=>a.rank);if(r.indexOf(null)===-1){let a=Da(r);for(let s of e){let i=s.rank;for(let o=0;o<a-i;++o)s=vc(s,1);n.push(s)}return this.mergeFunction(n)}else{let a=!1;for(let o of e){let l=o.rank;if(l==null){let c=o.shape,u=c[0],h=c.slice(1).concat([u]),d=o.reshape([u].concat($a(c.slice(1))));d=at(d,[1,0]),d=d.reshape(h),n.push(d),a=!0}else if(l>1){let c=_r(1,l).concat([0]);n.push(at(o,c)),a=!0}else n.push(o)}let s=this.mergeFunction(n),i=s.rank;if(a){if(i==null){let o=s.shape,l=o.length,c=o[l-1],u=[c].concat(o.slice(0,o.length-1));s=at(s.reshape([-1,c]),[1,0]).reshape(u)}else if(i>1){let o=[i-1].concat(_r(0,i-1));s=at(s,o)}}return s}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);t=this.computeElementwiseOpOutputShape(t,a)}let n=[];for(let r of e)r!=null&&r[0]!==null&&n.push(r[0]);return n=Ma(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return U(()=>{if(t==null)return null;if(!Array.isArray(t))throw new B("`mask` should be an Array");if(!Array.isArray(e))throw new B("`inputs` should be an Array");if(t.length!==e.length)throw new B(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(r=>r==null))return null;t=t.map(r=>r==null?r:In(r,0));let n=t[0];for(let r=1;r<t.length-1;++r)n=nr(n,t[r]);return n})}},ig=class extends wi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=oe(t,e[n]);return t})}};ig.className="Add";re.registerClass(ig);var og=class extends wi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=W(t,e[n]);return t})}};og.className="Multiply";re.registerClass(og);var lg=class extends wi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=oe(t,e[n]);return W(1/e.length,t)})}};lg.className="Average";re.registerClass(lg);var ug=class extends wi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Cr(t,e[n]);return t})}};ug.className="Maximum";re.registerClass(ug);var cg=class extends wi{constructor(e){super(e)}mergeFunction(e){return U(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Xo(t,e[n]);return t})}};cg.className="Minimum";re.registerClass(cg);var hg=class extends wi{constructor(e){super(e);this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new B("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let r of e)if(r!=null){t=!1;break}if(t)return;let n=[];for(let r=0;r<e.length;++r){let a=e[r].slice();a.splice(this.axis,1);let s=!1;for(let i of n)if(v.arraysEqual(i,a)){s=!0;break}s||n.push(a)}if(n.length>1)throw new B("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return U(()=>ay(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new B("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis;for(let a of t.slice(1)){if(n[r]==null||a[r]==null){n[r]=null;break}n[r]+=a[r]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new B("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new B("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new B(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return U(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let r=[];for(let s=0;s<e.length;++s)t[s]==null?r.push(Sn(e[s]).asType("bool")):t[s].rank<e[s].rank?r.push(In(t[s],-1)):r.push(t[s]);let a=ct(r,this.axis);return ed(a,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};hg.className="Concatenate";re.registerClass(hg);function Dc(e,t){for(;e<0;)e+=t;return e}function bte(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new De("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new De("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return U(()=>{let i;if(r>a){i=r-a;let l=[];for(let c=0;c<i;++c)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let c=0;c<i;++c)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,c=s[1]===t.shape.length-1;o=e.matMul(t,l,c)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let c=[];for(let u=l;u<l+i;++u)c.push(u);o=o.squeeze(c)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var dg=class extends wi{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new B(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new B(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],r;return Array.isArray(this.axes)?r=this.axes.map((a,s)=>Dc(a,e[s].shape.length)):r=[Dc(this.axes,t.shape.length),Dc(this.axes,n.shape.length)],this.normalize&&(t=Op(t,r[0]),n=Op(n,r[1])),bte(t,n,r)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Dc(this.axes,e.length),Dc(this.axes,t.length)],n}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);t.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);let a=t.concat(n);return a.length===1&&a.push(1),a}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};dg.className="Dot";re.registerClass(dg);var pg=class extends Xe{constructor(e){super(e);this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Ic(()=>vp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};pg.className="GaussianNoise";re.registerClass(pg);var fg=class extends Xe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return U(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Ic(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(vp(n.shape,1,r))},()=>n,t.training||!1):n})}};fg.className="GaussianDropout";re.registerClass(fg);var mg=class extends Xe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Pe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return U(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Ic(()=>{let r=Pe(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=_a(Ko(n),this.rate);o=bc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(c)},()=>Pe(e),t.training||!1)}return e})}};mg.className="AlphaDropout";re.registerClass(mg);function Oc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=Q2(e,t,n,r,a,s);else if(e.rank===3)i=e0(e,t,n,r,a,s);else if(e.rank===4)i=t0(e,t,n,r,a,s);else throw new De(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function vte(e,t,n,r,a=.001){return U(()=>{let s=hd(e,r),i=s.mean,o=s.variance;return[Oc(e,i,o,n,t,a),i,o]})}function kte(e,t,n,r,a=.001){return U(()=>{let s=hd(e,r),i=s.mean,o=s.variance,l=[];for(let p of _r(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let c=i.reshape(l),u=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[Oc(e,c,u,d,h,a),i,o]})}function Ite(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),_r(0,e.rank-1))?vte(e,t,n,r,a):kte(e,t,n,r,a)}var Ag=class extends Xe{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=gt(e.betaInitializer||"zeros"),this.gammaInitializer=gt(e.gammaInitializer||"ones"),this.movingMeanInitializer=gt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=gt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Lt(e.betaConstraint),this.gammaConstraint=Lt(e.gammaConstraint),this.betaRegularizer=xt(e.betaRegularizer),this.gammaRegularizer=xt(e.gammaRegularizer)}build(e){e=dt(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new B(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Vt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return U(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=_r(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=di(1,s);l[o]=a[o];let c=i.slice();c.sort();let u=!v.arraysEqual(c,_r(0,s).slice(0,s-1)),h=()=>{if(u){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return Oc(r,A,y,g,w,this.epsilon)}else return Oc(r,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return h();let[d,p,f]=Ite(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{U(()=>{let w=1-g,x=A.read(),_=x.sub(y).mul(w);A.write(x.sub(_))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),movingMeanInitializer:kt(this.movingMeanInitializer),movingVarianceInitializer:kt(this.movingVarianceInitializer),betaRegularizer:pt(this.betaRegularizer),gammaRegularizer:pt(this.gammaRegularizer),betaConstraint:Pt(this.betaConstraint),gammaConstraint:Pt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Ag.className="BatchNormalization";re.registerClass(Ag);var yg=class extends Xe{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=gt(e.betaInitializer||"zeros"),this.gammaInitializer=gt(e.gammaInitializer||"ones"),this.betaRegularizer=xt(e.betaRegularizer),this.gammaRegularizer=xt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=dt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Ma(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return U(()=>{let s=!0,{mean:i,variance:o}=hd(n,this.axis,s),l=di(1,a);for(let f of this.axis)l[f]=r[f];let c=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,u=c(this.gamma.read()),h=c(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),u=u.tile(p),h=h.tile(p),Oc(n,i,o,h,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),betaRegularizer:pt(this.betaRegularizer),gammaRegularizer:pt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};yg.className="LayerNormalization";re.registerClass(yg);function Nte(e,t,n){return U(()=>{if(e.rank!==4)throw new B(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new B("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=xr()),n!=="channelsLast"&&n!=="channelsFirst")throw new B(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let r;return n==="channelsFirst"?r=[[0,0],[0,0],t[0],t[1]]:r=[[0,0],t[0],t[1],[0,0]],Jr(e,r)})}var gg=class extends Xe{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?xr():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new B(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new B(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new B(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Vt({ndim:4})]}computeOutputShape(e){e=dt(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return U(()=>Nte(Pe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};gg.className="ZeroPadding2D";re.registerClass(gg);function Yp(e,t,n,r,a,s){return U(()=>{Tt(a),o3(s),jn(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=xr()),s==null&&(s="max"),e=Wy(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=$u(e,t,n,o):i=Su(e,t,n,o),a==="channelsFirst"&&(i=at(i,[0,3,1,2])),i})}function y7(e,t,n,r,a,s){return U(()=>{Tt(a),o3(s),jn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=xr()),s==null&&(s="max"),e=h7(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=nm(e,t,n,o):i=jf(e,t,n,o),a==="channelsFirst"&&(i=at(i,[0,4,1,2,3])),i})}var g7=class extends Xe{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new B(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(jt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new B(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,jn(this.padding),this.inputSpec=[new Vt({ndim:3})]}computeOutputShape(e){e=dt(e);let t=vr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return U(()=>{this.invokeCallHook(e,t),e=vc(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return ba(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},xg=class extends g7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),Yp(e,t,n,r,a,"max")}};xg.className="MaxPooling1D";re.registerClass(xg);var wg=class extends g7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),Yp(e,t,n,r,a,"avg")}};wg.className="AveragePooling1D";re.registerClass(wg);var x7=class extends Xe{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new B(`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}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];jt(this.poolSize,"poolSize"),jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Tt(this.dataFormat),jn(this.padding),this.inputSpec=[new Vt({ndim:4})]}computeOutputShape(e){e=dt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=vr(t,this.poolSize[0],this.padding,this.strides[0]),n=vr(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return U(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},_g=class extends x7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),Yp(e,t,n,r,a,"max")}};_g.className="MaxPooling2D";re.registerClass(_g);var bg=class extends x7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),Yp(e,t,n,r,a,"avg")}};bg.className="AveragePooling2D";re.registerClass(bg);var w7=class extends Xe{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new B(`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}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];jt(this.poolSize,"poolSize"),jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Tt(this.dataFormat),jn(this.padding),this.inputSpec=[new Vt({ndim:5})]}computeOutputShape(e){e=dt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=vr(t,this.poolSize[0],this.padding,this.strides[0]),n=vr(n,this.poolSize[1],this.padding,this.strides[1]),r=vr(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return U(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},vg=class extends w7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),y7(e,t,n,r,a,"max")}};vg.className="MaxPooling3D";re.registerClass(vg);var kg=class extends w7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),jn(r),y7(e,t,n,r,a,"avg")}};kg.className="AveragePooling3D";re.registerClass(kg);var _7=class extends Xe{constructor(e){super(e);this.inputSpec=[new Vt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new De}},Ig=class extends _7{constructor(e){super(e||{})}call(e,t){return U(()=>{let n=Pe(e);return bt(n,1)})}};Ig.className="GlobalAveragePooling1D";re.registerClass(Ig);var Ng=class extends _7{constructor(e){super(e||{})}call(e,t){return U(()=>{let n=Pe(e);return Bn(n,1)})}};Ng.className="GlobalMaxPooling1D";re.registerClass(Ng);var b7=class extends Xe{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Tt(this.dataFormat),this.inputSpec=[new Vt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new De}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Sg=class extends b7{call(e,t){return U(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?bt(n,[1,2]):bt(n,[2,3])})}};Sg.className="GlobalAveragePooling2D";re.registerClass(Sg);var Tg=class extends b7{call(e,t){return U(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?Bn(n,[1,2]):Bn(n,[2,3])})}};Tg.className="GlobalMaxPooling2D";re.registerClass(Tg);var v7=class extends Xe{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let r=t.layer,a=br(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},Eg=class extends v7{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=dt(e),e.length<3)throw new B(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=dt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return U(()=>(e=Pe(e),m7((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};Eg.className="TimeDistributed";re.registerClass(Eg);function Ste(e){fi(UY,"BidirectionalMergeMode",e)}var Tte="concat",Cg=class extends v7{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=br(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=br(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?Tte:e.mergeMode,Ste(this.mergeMode),e.weights)throw new De("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):gn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=f7(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new B("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let c=n.map(u=>new Vt({shape:u.shape}));this.forwardLayer.stateSpec=c.slice(0,l/2),this.backwardLayer.stateSpec=c.slice(l/2),i.push(...c)}if(r!=null)throw new De("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof Ar;for(let l of s)if(l instanceof Ar!==o)throw new B("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){let l=[e].concat(s),c=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=c;let h=super.apply(l,t);return this.inputSpec=u,h}else return super.apply(e,t)}call(e,t){return U(()=>{let n=t.initialState,r,a;if(n==null)r=this.forwardLayer.call(e,t),a=this.backwardLayer.call(e,t);else{let o=n.slice(0,n.length/2),l=n.slice(n.length/2);r=this.forwardLayer.call(e,Object.assign(t,{initialState:o})),a=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let s;this.returnState&&(Array.isArray(r)&&(s=r.slice(1).concat(a.slice(1))),r=r[0],a=a[0]),this.returnSequences&&(a=Tn(a,1));let 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Ane=class{constructor(e,t,n,r,a,s,i){this.name=e,this.dtype=t,this.maxSize=n,this.elementShape=r,this.identicalElementShapes=a,this.dynamicSize=s,this.clearAfterRead=i,this.tensors=[],this.closed_=!1,this.idTensor=Se(0),Bt(this.idTensor)}get id(){return this.idTensor.id}get closed(){return this.closed_}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.tensor.id))&&t.tensor.dispose()}),this.tensors=[],this.closed_=!0,this.idTensor.dispose()}size(){return this.tensors.length}read(e){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||e>=this.size())throw new Error(`Tried to read from index ${e}, but array size is: ${this.size()}`);let t=this.tensors[e];if(t.cleared)throw new Error(`TensorArray ${this.name}: Could not read index ${e} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);return this.clearAfterRead&&(t.cleared=!0),t.read=!0,t.tensor}readMany(e){return e.map(t=>this.read(t))}write(e,t){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||!this.dynamicSize&&e>=this.maxSize)throw new Error(`Tried to write to index ${e}, but array is not resizeable and size is: ${this.maxSize}`);let n=this.tensors[e]||{};if(t.dtype!==this.dtype)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e},
because the value dtype is ${t.dtype}, but TensorArray dtype is ${this.dtype}.`);if(this.size()===0&&(this.elementShape==null||this.elementShape.length===0)&&(this.elementShape=t.shape),cr(this.elementShape,t.shape,`TensorArray ${this.name}: Could not write to TensorArray index ${e}.`),n.read)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been read.`);if(n.written)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been written.`);n.tensor=t,Bt(t),n.written=!0,this.tensors[e]=n}writeMany(e,t){if(e.length!==t.length)throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${e.length} is not the same as tensors size: ${t.length}.`);e.forEach((n,r)=>this.write(n,t[r]))}gather(e,t){if(!!t&&t!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${t}`);if(e)e=e.slice(0,this.size());else{e=[];for(let r=0;r<this.size();r++)e.push(r)}if(e.length===0)return fr([],[0].concat(this.elementShape));let n=this.readMany(e);return cr(this.elementShape,n[0].shape,"TensorArray shape mismatch: "),En(n,0)}concat(e){if(!!e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(this.size()===0)return fr([],[0].concat(this.elementShape));let t=[];for(let r=0;r<this.size();r++)t.push(r);let n=this.readMany(t);return cr(this.elementShape,n[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${n[0].shape})`),ct(n,0)}scatter(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);if(e.length!==t.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${e.length} vs. ${t.shape[0]}`);let n=Math.max(...e);if(!this.dynamicSize&&n>=this.maxSize)throw new Error(`Max index must be < array size (${n} vs. ${this.maxSize})`);this.writeMany(e,rr(t,0))}split(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);let n=0,r=e.map(o=>(n+=o,n));if(n!==t.shape[0])throw new Error(`Expected sum of lengths to be equal to
tensor.shape[0], but sum of lengths is
${n}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let a=n===0?0:t.size/n,s=[];U(()=>{t=q(t,[1,n,a]);for(let o=0;o<e.length;++o){let l=o===0?0:r[o-1],c=[0,l,0],u=[1,e[o],a];s[o]=q(Me(t,c,u),this.elementShape)}return s});let i=[];for(let o=0;o<e.length;o++)i[o]=o;this.writeMany(i,s)}},Pc=class{constructor(e,t,n,r=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(a=>{if(n!==a.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${a.dtype}`);cr(t,a.shape,"TensorList shape mismatch: "),Bt(a)}),this.idTensor=Se(0),this.maxNumElements=r,Bt(this.idTensor)}get id(){return this.idTensor.id}copy(){return new Pc([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.id))&&t.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(e,t,n=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(n!==-1&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);cr(e,this.elementShape,"TensorList shape mismatch: ");let r=zc(this.elementShape,this.tensors,e);return U(()=>{let a=this.tensors.map(s=>q(s,r));return En(a,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=zc(this.elementShape,this.tensors,e),r=this.tensors.pop();return cr(r.shape,e,"TensorList shape mismatch: "),q(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(cr(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Bt(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(this.maxNumElements!==-1&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);this.tensors.length=e}getItem(e,t,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${this.elementDtype}`);if(e<0||e>this.tensors.length)throw new Error(`Trying to access element ${e} in a list with ${this.tensors.length} elements.`);if(this.tensors[e]==null)throw new Error(`element at index ${e} is null.`);cr(this.tensors[e].shape,t,"TensorList shape mismatch: ");let r=zc(this.elementShape,this.tensors,t);return q(this.tensors[e],r)}setItem(e,t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(e<0||this.maxNumElements!==-1&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);cr(this.elementShape,t.shape,"TensorList shape mismatch: "),Bt(t),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);cr(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let r=zc(this.elementShape,this.tensors,n);return e.length===0?fr([],[0].concat(r)):U(()=>{let a=e.map(s=>q(this.tensors[s],r));return En(a,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);cr(this.elementShape,t,"TensorList shape mismatch: ");let n=zc(this.elementShape,this.tensors,t);return this.size()===0?fr([],[0].concat(n)):U(()=>{let r=this.tensors.map(a=>q(a,n));return ct(r,0)})}};function yne(e,t,n){let r=e.dtype;if(e.shape.length<1)throw new Error(`Tensor must be at least a vector, but saw shape: ${e.shape}`);if(e.dtype!==n)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${n}`);let a=e.shape.slice(1);cr(a,t,"TensorList shape mismatch: ");let s=rr(e);return new Pc(s,t,r)}function gne(e,t,n){return new Pc([],e,t,n)}function xne(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let a=Math.max(...t);if(r!=null&&r!==-1&&a>=r)throw new Error(`Max index must be < array size (${a} vs. ${r})`);let s=new Pc([],n,e.dtype,r),i=rr(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function wne(e,t,n){let r=0,a=t.map(u=>(r+=u,r));if(r!==e.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: ${e.shape}`);let s=e.shape.slice(1),i=Ug(s,n),o=r===0?0:e.size/r,l=U(()=>{let u=[];e=q(e,[1,r,o]);for(let h=0;h<t.length;++h){let d=h===0?0:a[h-1],p=[0,d,0],f=[1,t[h],o];u[h]=q(Me(e,p,f),i)}return e.dispose(),u}),c=new Pc([],n,e.dtype,t.length);for(let u=0;u<l.length;u++)c.setItem(u,l[u]);return c}var _ne=async(e,t,n)=>{switch(e.op){case"If":case"StatelessIf":{let r=k("thenBranch",e,t,n),a=k("elseBranch",e,t,n),s=k("cond",e,t,n),i=k("args",e,t,n);return(await s.data())[0]?n.functionMap[r].executeFunctionAsync(i,n.tensorArrayMap,n.tensorListMap):n.functionMap[a].executeFunctionAsync(i,n.tensorArrayMap,n.tensorListMap)}case"While":case"StatelessWhile":{let r=k("body",e,t,n),a=k("cond",e,t,n),s=k("args",e,t,n),i=await n.functionMap[a].executeFunctionAsync(s,n.tensorArrayMap,n.tensorListMap),o=s.map(u=>u.id),l=await i[0].data();i.forEach(u=>{!u.kept&&o.indexOf(u.id)===-1&&u.dispose()});let c=s;for(;l[0];){let u=c;c=await n.functionMap[r].executeFunctionAsync(c,n.tensorArrayMap,n.tensorListMap);let h=c.map(p=>p.id);u.forEach(p=>{!p.kept&&o.indexOf(p.id)===-1&&h.indexOf(p.id)===-1&&p.dispose()});let d=await n.functionMap[a].executeFunctionAsync(c,n.tensorArrayMap,n.tensorListMap);l=await d[0].data(),d.forEach(p=>{!p.kept&&o.indexOf(p.id)===-1&&h.indexOf(p.id)===-1&&p.dispose()})}return c}case"LoopCond":{let r=k("pred",e,t,n);return[la(r)]}case"Switch":{let r=k("pred",e,t,n),a=k("data",e,t,n);return a.kept||(a=la(a)),(await r.data())[0]?[void 0,a]:[a,void 0]}case"Merge":{let r=e.inputNames.find(a=>wn(a,t,n)!==void 0);if(r){let a=wn(r,t,n);return[la(a)]}return}case"Enter":{let r=k("frameName",e,t,n),a=k("tensor",e,t,n);return n.enterFrame(r),[la(a)]}case"Exit":{let r=k("tensor",e,t,n);return n.exitFrame(),[la(r)]}case"NextIteration":{let r=k("tensor",e,t,n);return n.nextIteration(),[la(r)]}case"TensorArrayV3":{let r=k("size",e,t,n),a=k("dtype",e,t,n),s=k("elementShape",e,t,n),i=k("dynamicSize",e,t,n),o=k("clearAfterRead",e,t,n),l=k("identicalElementShapes",e,t,n),c=k("name",e,t,n),u=new Ane(c,a,r,s,l,i,o);return n.addTensorArray(u),[u.idTensor,Se(1)]}case"TensorArrayWriteV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,s)]}case"TensorArrayScatterV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),s=k("dtype",e,t,n);return[a.concat(s)]}case"TensorArraySplitV3":{let r=k("tensorArrayId",e,t,n),a=k("tensor",e,t,n),s=k("lengths",e,t,n),i=n.getTensorArray(r.id);return i.split(s,a),[i.idTensor]}case"TensorArraySizeV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return[Se(a.size(),"int32")]}case"TensorArrayCloseV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorList(r.id);return i.setItem(a,s),[i.idTensor]}case"TensorListGetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let r=k("indices",e,t,n),a=k("tensor",e,t,n),s=k("elementShape",e,t,n),i=k("numElements",e,t,n),o=xne(a,r,s,i);return n.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let r=k("elementShape",e,t,n),a=k("elementDType",e,t,n),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,n),o=gne(r,a,i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{let r=k("tensorListId",e,t,n),a=k("indices",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,i,s)]}case"TensorListStack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=k("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,s,i)]}case"TensorListFromTensor":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=yne(r,a,s);return n.addTensorList(i),[i.idTensor]}case"TensorListConcat":{let r=k("tensorListId",e,t,n),a=n.getTensorList(r.id),s=k("dtype",e,t,n),i=k("elementShape",e,t,n);return[a.concat(s,i)]}case"TensorListPushBack":{let r=k("tensorListId",e,t,n),a=k("tensor",e,t,n),s=n.getTensorList(r.id);return s.pushBack(a),[s.idTensor]}case"TensorListPopBack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n);return[n.getTensorList(r.id).popBack(a,s)]}case"TensorListSplit":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("lengths",e,t,n),i=wne(r,s,a);return n.addTensorList(i),[i.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};function K7(e,t,n){let[r,a]=k("fusedOps",e,t,n),s=r==="biasadd",i=a==="prelu",o=r==="fusedbatchnorm",l=k("numArgs",e,t,n);if(s){if(i&&l!==2)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&l!==1)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(o)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported.");let c=k("strides",e,t,n),u=t1(e,t,n),h=k("dataFormat",e,t,n).toUpperCase(),d=k("dilations",e,t,n),[p,f]=k("args",e,t,n),m=k("leakyreluAlpha",e,t,n);return{stride:c,pad:u,dataFormat:h,dilations:d,biasArg:p,preluArg:f,activationFunc:a,leakyreluAlpha:m}}var bne=(e,t,n)=>{switch(e.op){case"Conv1D":{let r=k("stride",e,t,n),a=k("pad",e,t,n),s=k("dataFormat",e,t,n).toUpperCase(),i=k("dilation",e,t,n);return[nd(k("x",e,t,n),k("filter",e,t,n),r,a,s,i)]}case"Conv2D":{let r=k("strides",e,t,n),a=t1(e,t,n),s=k("dataFormat",e,t,n).toUpperCase(),i=k("dilations",e,t,n);return[Zr(k("x",e,t,n),k("filter",e,t,n),[r[1],r[2]],a,s,[i[1],i[2]])]}case"_FusedConv2D":{let{stride:r,pad:a,dataFormat:s,dilations:i,biasArg:o,preluArg:l,activationFunc:c,leakyreluAlpha:u}=K7(e,t,n);return[va.conv2d({x:k("x",e,t,n),filter:k("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:s,dilations:[i[1],i[2]],bias:o,activation:c,preluActivationWeights:l,leakyreluAlpha:u})]}case"FusedDepthwiseConv2dNative":{let{stride:r,pad:a,dataFormat:s,dilations:i,biasArg:o,preluArg:l,activationFunc:c,leakyreluAlpha:u}=K7(e,t,n);return[va.depthwiseConv2d({x:k("x",e,t,n),filter:k("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:s,dilations:[i[1],i[2]],bias:o,activation:c,preluActivationWeights:l,leakyreluAlpha:u})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let r=k("outputShape",e,t,n),a=k("strides",e,t,n),s=t1(e,t,n);return[rd(k("x",e,t,n),k("filter",e,t,n),r,[a[1],a[2]],s)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let r=k("strides",e,t,n),a=t1(e,t,n),s=k("dilations",e,t,n),i=k("dataFormat",e,t,n).toUpperCase();return[Uo(k("input",e,t,n),k("filter",e,t,n),[r[1],r[2]],a,i,[s[1],s[2]])]}case"Conv3D":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("dataFormat",e,t,n).toUpperCase(),i=k("dilations",e,t,n);return[qf(k("x",e,t,n),k("filter",e,t,n),[r[1],r[2],r[3]],a,s,[i[1],i[2],i[3]])]}case"AvgPool":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n);return[Su(k("x",e,t,n),[s[1],s[2]],[r[1],r[2]],a)]}case"MaxPool":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n);return[$u(k("x",e,t,n),[s[1],s[2]],[r[1],r[2]],a)]}case"MaxPoolWithArgmax":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n),i=k("includeBatchInIndex",e,t,n),{result:o,indexes:l}=m0(k("x",e,t,n),[s[1],s[2]],[r[1],r[2]],a,i);return[o,l]}case"AvgPool3D":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n);return[jf(k("x",e,t,n),[s[1],s[2],s[3]],[r[1],r[2],r[3]],a)]}case"MaxPool3D":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("kernelSize",e,t,n);return[nm(k("x",e,t,n),[s[1],s[2],s[3]],[r[1],r[2],r[3]],a)]}case"Dilation2D":{let r=k("strides",e,t,n),a=k("pad",e,t,n),s=k("dilations",e,t,n),i=r[1],o=r[2],l=s[1],c=s[2];return[Kf(k("x",e,t,n),k("filter",e,t,n),[i,o],a,[l,c],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},vne=(e,t,n)=>{switch(e.op){case"Fill":{let r=k("shape",e,t,n),a=k("dtype",e,t,n),s=k("value",e,t,n);return[Ru(r,s,a)]}case"LinSpace":{let r=k("start",e,t,n),a=k("stop",e,t,n),s=k("num",e,t,n);return[h0(r,a,s)]}case"Multinomial":{let r=k("logits",e,t,n),a=k("numSamples",e,t,n),s=k("seed",e,t,n);return[A0(r,a,s)]}case"OneHot":{let r=k("indices",e,t,n),a=k("depth",e,t,n),s=k("onValue",e,t,n),i=k("offValue",e,t,n);return[Wo(r,a,s,i)]}case"Ones":return[Rr(k("shape",e,t,n),k("dtype",e,t,n))];case"OnesLike":return[Sn(k("x",e,t,n))];case"RandomUniform":return[Ko(k("shape",e,t,n),k("minval",e,t,n),k("maxval",e,t,n),k("dtype",e,t,n))];case"Range":{let r=k("start",e,t,n),a=k("stop",e,t,n),s=k("step",e,t,n);return[pd(r,a,s,k("dtype",e,t,n))]}case"TruncatedNormal":{let r=k("shape",e,t,n),a=k("mean",e,t,n),s=k("stdDev",e,t,n),i=k("seed",e,t,n);return[vd(r,a,s,k("dtype",e,t,n),i)]}case"Zeros":return[Ct(k("shape",e,t,n),k("dtype",e,t,n))];case"ZerosLike":return[He(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Hg(e,t,n){let r=k("boxes",e,t,n),a=k("scores",e,t,n),s=k("maxOutputSize",e,t,n),i=k("iouThreshold",e,t,n),o=k("scoreThreshold",e,t,n),l=k("softNmsSigma",e,t,n);return{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o,softNmsSigma:l}}var kne=async(e,t,n)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o,softNmsSigma:l}=Hg(e,t,n),c=await St.nonMaxSuppressionWithScoreAsync(r,a,s,i,o,l);return[c.selectedIndices,c.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o}=Hg(e,t,n),l=k("padToMaxOutputSize",e,t,n),c=await St.nonMaxSuppressionPaddedAsync(r,a,s,i,o,l);return[c.selectedIndices,c.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:r,scores:a,maxOutputSize:s,iouThreshold:i,scoreThreshold:o}=Hg(e,t,n);return[await St.nonMaxSuppressionAsync(r,a,s,i,o)]}case"Where":{let r=ye(k("condition",e,t,n),"bool"),a=[await fm(r)];return r.dispose(),a}case"ListDiff":return x0(k("x",e,t,n),k("y",e,t,n));default:throw TypeError(`Node type ${e.op} is not implemented`)}},Ine=(e,t,n)=>{switch(e.op){case"TopKV2":{let r=k("x",e,t,n),a=k("k",e,t,n),s=k("sorted",e,t,n),i=dm(r,a,s);return[i.values,i.indices]}case"Unique":{let r=k("x",e,t,n),a=kd(r);return[a.values,a.indices]}case"UniqueV2":{let r=k("x",e,t,n),a=k("axis",e,t,n),s=kd(r,a);return[s.values,s.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Nne=(e,t,n)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let r=k("default",e,t,n);return[wn(e.name,t,n)||r];case"Placeholder":return[wn(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let c=k("x",e,t,n);return[la(c)]}case"IdentityN":return k("x",e,t,n).map(c=>la(c));case"Snapshot":let a=k("x",e,t,n);return[la(a)];case"Shape":return[Qt(k("x",e,t,n).shape,"int32")];case"ShapeN":return k("x",e,t,n).map(c=>Qt(c.shape));case"Size":return[Se(k("x",e,t,n).size,"int32")];case"Rank":return[Se(k("x",e,t,n).rank,"int32")];case"NoOp":return[Se(1)];case"Print":let s=k("x",e,t,n),i=k("data",e,t,n),o=k("message",e,t,n),l=k("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(o);for(let c=0;c<i.length;c++)console.log(Array.prototype.slice.call(i[c].dataSync()).slice(0,l));return[s];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Sne=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=Se(0),this.tensorMap=new Map,Bt(this.handle)}get id(){return this.handle.id}clearAndClose(){this.tensorMap.forEach(e=>e.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}async import(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return this.tensorMap.forEach(r=>r.dispose()),this.tensorMap.clear(),U(()=>{let r=rr(t),a=n.length,s=r.length;v.assert(a===s,()=>`The number of elements doesn't match, keys has ${a} elements, the values has ${s} elements.`);for(let i=0;i<a;i++){let o=n[i],l=r[i];Bt(l),this.tensorMap.set(o,l)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return U(()=>{let r=[];for(let a=0;a<n.length;a++){let s=n[a],i=this.findWithDefault(s,t);r.push(i)}return En(r)})}findWithDefault(e,t){let n=this.tensorMap.get(e);return n!=null?n:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}},Tne=async(e,t,n,r)=>{switch(e.op){case"HashTable":case"HashTableV2":{let a=k("keyDType",e,t,n),s=k("valueDType",e,t,n),i=new Sne(a,s);return r.addHashTable(e.name,i),[i.handle]}case"LookupTableImport":case"LookupTableImportV2":{let a=k("tableHandle",e,t,n,r),s=k("keys",e,t,n),i=k("values",e,t,n);return[await r.getHashTableById(a.id).import(s,i)]}case"LookupTableFind":case"LookupTableFindV2":{let a=k("tableHandle",e,t,n,r),s=k("keys",e,t,n),i=k("defaultValue",e,t,n);return[await r.getHashTableById(a.id).find(s,i)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Ene=(e,t,n)=>{switch(e.op){case"ResizeBilinear":{let r=k("images",e,t,n),a=k("size",e,t,n),s=k("alignCorners",e,t,n),i=k("halfPixelCenters",e,t,n);return[St.resizeBilinear(r,[a[0],a[1]],s,i)]}case"ResizeNearestNeighbor":{let r=k("images",e,t,n),a=k("size",e,t,n),s=k("alignCorners",e,t,n),i=k("halfPixelCenters",e,t,n);return[St.resizeNearestNeighbor(r,[a[0],a[1]],s,i)]}case"CropAndResize":{let r=k("image",e,t,n),a=k("boxes",e,t,n),s=k("boxInd",e,t,n),i=k("cropSize",e,t,n),o=k("method",e,t,n),l=k("extrapolationValue",e,t,n);return[St.cropAndResize(r,a,s,i,o,l)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Cne=(e,t,n)=>{switch(e.op){case"Equal":return[xa(k("a",e,t,n),k("b",e,t,n))];case"NotEqual":return[qs(k("a",e,t,n),k("b",e,t,n))];case"Greater":return[tr(k("a",e,t,n),k("b",e,t,n))];case"GreaterEqual":return[_a(k("a",e,t,n),k("b",e,t,n))];case"Less":return[od(k("a",e,t,n),k("b",e,t,n))];case"LessEqual":return[Gs(k("a",e,t,n),k("b",e,t,n))];case"LogicalAnd":return[nr(k("a",e,t,n),k("b",e,t,n))];case"LogicalNot":return[Mu(k("a",e,t,n))];case"LogicalOr":return[cd(k("a",e,t,n),k("b",e,t,n))];case"Select":case"SelectV2":return[mn(k("condition",e,t,n),k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Rne=(e,t,n)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[qe(k("a",e,t,n),k("b",e,t,n),k("transposeA",e,t,n),k("transposeB",e,t,n))];case"Transpose":return[at(k("x",e,t,n),k("perm",e,t,n))];case"_FusedMatMul":let[r,a]=k("fusedOps",e,t,n),s=r==="biasadd",i=a==="prelu",o=k("numArgs",e,t,n),l=k("leakyreluAlpha",e,t,n);if(s){if(i&&o!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&o!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[c,u]=k("args",e,t,n);return[va.matMul({a:k("a",e,t,n),b:k("b",e,t,n),transposeA:k("transposeA",e,t,n),transposeB:k("transposeB",e,t,n),bias:c,activation:a,preluActivationWeights:u,leakyreluAlpha:l})];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Fne=(e,t,n)=>{switch(e.op){case"FusedBatchNorm":case"FusedBatchNormV2":return[Hs(k("x",e,t,n),k("mean",e,t,n),k("variance",e,t,n),k("offset",e,t,n),k("scale",e,t,n),k("epsilon",e,t,n))];case"FusedBatchNormV3":return[Hs(k("x",e,t,n),k("mean",e,t,n),k("variance",e,t,n),k("offset",e,t,n),k("scale",e,t,n),k("epsilon",e,t,n))];case"LRN":return[em(k("x",e,t,n),k("radius",e,t,n),k("bias",e,t,n),k("alpha",e,t,n),k("beta",e,t,n))];case"Softmax":return[Lu(k("x",e,t,n))];case"LogSoftmax":return[ud(k("x",e,t,n))];case"SparseToDense":return[mm(k("sparseIndices",e,t,n),k("outputShape",e,t,n),k("sparseValues",e,t,n),k("defaultValue",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Mne=(e,t,n)=>{switch(e.op){case"Max":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Bn(k("x",e,t,n),i,o)]}case"Mean":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[bt(k("x",e,t,n),i,o)]}case"Min":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[qo(k("x",e,t,n),i,o)]}case"Sum":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Te(k("x",e,t,n),i,o)]}case"All":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[ed(k("x",e,t,n),i,o)]}case"Any":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[Iu(k("x",e,t,n),i,o)]}case"ArgMax":{let i=k("axis",e,t,n);return[Nu(k("x",e,t,n),i)]}case"ArgMin":{let i=k("axis",e,t,n);return[Lf(k("x",e,t,n),i)]}case"Prod":{let i=k("axis",e,t,n),o=k("keepDims",e,t,n);return[dd(k("x",e,t,n),i,o)]}case"Cumsum":{let i=k("axis",e,t,n),o=k("exclusive",e,t,n),l=k("reverse",e,t,n);return[sd(k("x",e,t,n),i,o,l)]}case"Bincount":let r=k("x",e,t,n),a=k("weights",e,t,n),s=k("size",e,t,n);return[n0(r,a,s)];case"DenseBincount":{let i=k("x",e,t,n),o=k("weights",e,t,n),l=k("size",e,t,n),c=k("binaryOutput",e,t,n);return[i0(i,o,l,c)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},$ne=(e,t,n)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=k("n",e,t,n),a=k("axis",e,t,n),s=k("tensors",e,t,n);return s=s.slice(0,r),[ct(s,a)]}case"Gather":{let r=k("x",e,t,n),a=k("indices",e,t,n);return[js(r,ye(a,"int32"),0)]}case"GatherV2":{let r=k("axis",e,t,n),a=k("batchDims",e,t,n),s=k("x",e,t,n),i=k("indices",e,t,n);return[js(s,ye(i,"int32"),r,a)]}case"Reverse":{let r=k("dims",e,t,n),a=[];for(let i=0;i<r.length;i++)r[i]&&a.push(i);let s=k("x",e,t,n);return[Tn(s,a)]}case"ReverseV2":{let r=k("axis",e,t,n),a=k("x",e,t,n);return[Tn(a,r)]}case"Slice":{let r=k("begin",e,t,n),a=k("size",e,t,n);return[Me(k("x",e,t,n),r,a)]}case"StridedSlice":{let r=k("begin",e,t,n),a=k("end",e,t,n),s=k("strides",e,t,n),i=k("beginMask",e,t,n),o=k("endMask",e,t,n),l=k("ellipsisMask",e,t,n),c=k("newAxisMask",e,t,n),u=k("shrinkAxisMask",e,t,n),h=k("x",e,t,n);return[cm(h,r,a,s,i,o,l,c,u)]}case"Pack":return U(()=>{let r=k("axis",e,t,n),a=k("tensors",e,t,n),s=a[0].shape,i=ba(a[0]).shape,o=a.map(l=>{let c=v.arraysEqual(l.shape,s);if(!c&&!v.arraysEqual(ba(l).shape,i))throw new Error("the input tensors shape does not match");return c?l:q(l,s)});return[En(o,r)]});case"Unpack":{let r=k("axis",e,t,n),a=k("tensor",e,t,n);return rr(a,r)}case"Tile":{let r=k("reps",e,t,n);return[wa(k("x",e,t,n),r)]}case"Split":case"SplitV":{let r=k("axis",e,t,n),a=k("numOrSizeSplits",e,t,n),s=k("x",e,t,n);return an(s,a,r)}case"ScatterNd":{let r=k("indices",e,t,n),a=k("values",e,t,n),s=k("shape",e,t,n);return[_0(r,a,s)]}case"GatherNd":{let r=k("x",e,t,n),a=k("indices",e,t,n);return[b0(r,a)]}case"SparseToDense":{let r=k("sparseIndices",e,t,n),a=k("outputShape",e,t,n),s=k("sparseValues",e,t,n),i=k("defaultValue",e,t,n);return[mm(r,s,a,s.dtype===i.dtype?i:ye(i,s.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Dne=(e,t,n)=>{switch(e.op){case"FFT":return[Wu(k("x",e,t,n))];case"IFFT":return[Zo(k("x",e,t,n))];case"RFFT":return[Bu(k("x",e,t,n))];case"IRFFT":return[_d(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},One=(e,t,n)=>{switch(e.op){case"Cast":return[ye(k("x",e,t,n),k("dtype",e,t,n))];case"ExpandDims":{let r=k("axis",e,t,n);return[In(k("x",e,t,n),r)]}case"Squeeze":{let r=k("axis",e,t,n);return[ba(k("x",e,t,n),r)]}case"Reshape":return[q(k("x",e,t,n),k("shape",e,t,n))];case"MirrorPad":return[rm(k("x",e,t,n),k("padding",e,t,n),k("mode",e,t,n))];case"PadV2":case"Pad":return[Jr(k("x",e,t,n),k("padding",e,t,n),k("constantValue",e,t,n))];case"SpaceToBatchND":{let r=k("blockShape",e,t,n),a=k("paddings",e,t,n);return[Du(k("x",e,t,n),r,a)]}case"BatchToSpaceND":{let r=k("blockShape",e,t,n),a=k("crops",e,t,n);return[Tu(k("x",e,t,n),r,a)]}case"DepthToSpace":{let r=k("blockSize",e,t,n),a=k("dataFormat",e,t,n).toUpperCase();return[Xf(k("x",e,t,n),r,a)]}case"BroadcastTo":return[Eu(k("x",e,t,n),k("shape",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Z7(e,t,n,r){let a=((s,i,o)=>{switch(s.category){case"arithmetic":return U(()=>fne(s,i,o));case"basic_math":return U(()=>mne(s,i,o));case"control":return _ne(s,i,o);case"convolution":return U(()=>bne(s,i,o));case"creation":return U(()=>vne(s,i,o));case"dynamic":return kne(s,i,o);case"evaluation":return U(()=>Ine(s,i,o));case"image":return U(()=>Ene(s,i,o));case"graph":return U(()=>Nne(s,i,o));case"logical":return U(()=>Cne(s,i,o));case"matrices":return U(()=>Rne(s,i,o));case"normalization":return U(()=>Fne(s,i,o));case"reduction":return U(()=>Mne(s,i,o));case"slice_join":return U(()=>$ne(s,i,o));case"spectral":return U(()=>Dne(s,i,o));case"transformation":return U(()=>One(s,i,o));case"hash_table":return Tne(s,i,o,r);case"custom":let l=N7(s.op);if(l&&l.customExecutor)return l.customExecutor(new pne(s,i,o));throw TypeError(`Custom op ${s.op} is not registered.`);default:throw TypeError(`Unknown op '${s.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,n);return v.isPromise(a)?a.then(s=>[].concat(s)):[].concat(a)}var J7=class{constructor(e={},t={},n={},r={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=r,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){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")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function Q7(e,t,n,r){let a=new Set,s=[],i=null,o=null,l=new Set,c=Object.keys(e).map(d=>$n(d)[0]),u=[];r!=null&&(u=r.map(d=>$n(d.name)[0]));let h=[...t];for(;h.length>0;){let d=h.pop();if((Y7(d)||zne(d)||Pne(d))&&i==null&&(i=d,o=i.children.map(p=>p.name).filter(p=>a.has(p))),a.add(d.name),n[d.name]==null&&c.indexOf(d.name)===-1&&u.indexOf(d.name)===-1){if(d.inputs.length===0){s.push(d.name);continue}d.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),h.push(p))})}}return{inputs:e,outputs:t,usedNodes:a,missingInputs:s,dynamicNode:i,syncInputs:o}}function Lne(e,t,n){let{usedNodes:r,inputs:a}=n,s=[],i=Object.keys(a).map(u=>$n(u)[0]).map(u=>e.nodes[u]),o=e.initNodes;i.forEach(u=>{r.has(u.name)&&s.push(u)}),e.weights.forEach(u=>{r.has(u.name)&&s.push(u)}),o!=null&&o.forEach(u=>{r.has(u.name)&&s.push(u)});let l=new Set,c=[];for(;s.length>0;){let u=s.pop();l.add(u.name),t[u.name]||c.push(u),u.children.forEach(h=>{!l.has(h.name)&&r.has(h.name)&&h.inputs.every(d=>l.has(d.name))&&s.push(h)})}return c}var Wne=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],Bne=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],Vne=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2"];function Y7(e){return Wne.indexOf(e.op)>=0}function zne(e){return Bne.indexOf(e.op)>=0}function Pne(e){return Vne.indexOf(e.op)>=0}var jg=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new jg(e.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(r=>r.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return 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in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=$n(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[t]!=null?this._signature.outputs[t].name:t,{})}checkOutputs(e){e.forEach(t=>{let[n]=$n(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},Une=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in 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t=dn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(dn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let r=dn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new jg(j7.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=j7.Instance.transformGraph(e.modelInitializer);this.initializer=new jg(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=dn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof Qe)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function Yn(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${jne}${Hne}`);let n=new q0(e,t);return await n.load(),n}var q8="3.1.0",X0={};ze(X0,{CSVDataset:()=>t6,Dataset:()=>Rl,FileDataSource:()=>n6,TextLineDataset:()=>e6,URLDataSource:()=>r6,array:()=>Gne,csv:()=>Xne,func:()=>Kne,generator:()=>Zne,microphone:()=>Yne,version_data:()=>Qne,webcam:()=>Jne,zip:()=>qne});var ere=Qo(K0()),tre=Qo(K0());function nre(e,t){return n1(e,t)}function n1(e,t,n=new Map,r=new Set){if(e==null)return null;if(r.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(a.recurse)if(Fl(e)){let s=Array.isArray(e)?[]:{};r.add(e);for(let i in e){let o=e[i],l=n1(o,t,n,r);s[i]=l}return r.delete(e),s}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else 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RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}},Gg=class extends o6{constructor(){super(Gg.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new Array(e),n=this.length();for(let r=0;r<n;r++)t[r]=this.get(this.wrap(this.begin+r));this.data=t,this.capacity=e,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};Gg.INITIAL_CAPACITY=32;function l6(e){return new lre(e)}function qg(e){return new ure(e)}function cre(e,t){return new u6(e,t)}function dre(e,t=Wa.FAIL){return new hre(e,t)}var Gt=class{async toArray(){let e=[],t=await this.next();for(;!t.done;)e.push(t.value),t=await this.next();return e}async toArrayForTest(){let e=this.prefetch(100),t=[],n=await e.next();for(;!n.done;)t.push(n.value),n=await e.next();return t}async resolveFully(){let e=await this.next();for(;!e.done;)e=await this.next()}async resolveWhile(e){let t=await this.next(),n=e(t.value);for(;!t.done&&n;)t=await this.next(),n=e(t.value)}handleErrors(e){return new xre(this,e)}filter(e){return new yre(this,e)}map(e){return new gre(this,e)}mapAsync(e){return new c6(this,e)}serialMapAsync(e){return new c6(this,e).serial()}flatmap(e){return new wre(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new Are(this,e,t)}columnMajorBatch(e,t=!0,n=s6){return this.rowMajorBatch(e,t).map(r=>rre(r,n))}concatenate(e,t){return new u6(l6([this,e]),t)}take(e){return e<0||e==null?this:new mre(this,e)}skip(e){return e<0||e==null?this:new fre(this,e)}prefetch(e){return new h6(this,e)}shuffle(e,t){return new _re(this,e,t)}serial(){return new pre(this)}},lre=class extends Gt{constructor(e){super();this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:ore(e),done:!1}}},ure=class extends Gt{constructor(e){super();this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},pre=class extends Gt{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},fre=class extends Gt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;Ce(e.value)}return this.upstream.next()}},mre=class extends Gt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},Are=class extends Gt{constructor(e,t,n=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},yre=class extends Gt{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Ce(e.value)}}},gre=class extends Gt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=pr.getTensorsInContainer(e.value),n=this.transform(e.value),r=pr.getTensorsInContainer(n);for(let a of t)pr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},xre=class extends Gt{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},c6=class extends Gt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=pr.getTensorsInContainer(e.value),n=await this.transform(e.value),r=pr.getTensorsInContainer(n);for(let a of t)pr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Xg=class extends Gt{constructor(){super();this.outputQueue=new Gg,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},wre=class extends Xg{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=pr.getTensorsInContainer(e.value),n=this.transform(e.value),r=pr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let a of t)pr.isTensorInList(a,r)||a.dispose();return!0}},u6=class extends Gt{constructor(e,t){super();this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,this.iterator==null){let n=await this.moreIterators.next();if(n.done)return{value:null,done:!0};this.iterator=n.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}},Wa;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(Wa||(Wa={}));var hre=class extends Gt{constructor(e,t=Wa.FAIL){super();this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function r(s){return s instanceof Gt?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await i6(this.iterators,r);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case Wa.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case Wa.SHORTEST:return{value:null,done:!0};case Wa.LONGEST:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},h6=class extends Gt{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new o6(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},_re=class extends h6{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=tre.alea(n||v.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Rl=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
${e}`);let r;return this.size===Infinity||this.size==null?r=this.size:t?r=Math.ceil(this.size/e):r=Math.floor(this.size/e),Dn(async()=>(await n.iterator()).columnMajorBatch(e,t,bre),r)}concatenate(e){let t=this,n;return this.size===Infinity||e.size===Infinity?n=Infinity:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Dn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,Dn(async()=>(await t.iterator()).filter(r=>U(()=>e(r))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Dn(async()=>(await t.iterator()).map(n=>U(()=>e(n))),this.size)}mapAsync(e){let t=this;return Dn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Dn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=Infinity:n=null,Dn(async()=>{let r=qg(async()=>({value:await t.iterator(),done:!1}));return cre(r.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Dn(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let r=this,a=ere.alea(t||v.now().toString());return Dn(async()=>{let s=a.int32();return n&&(s+=a.int32()),(await r.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Dn(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Rl.MAX_BUFFER_SIZE=1e4;function Dn(e,t=null){return new class extends Rl{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function Gne(e){return Dn(async()=>l6(e),e.length)}function qne(e){if(!Fl(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Dn(async()=>{let n=await i6(e,r=>{if(r instanceof Rl)return{value:r.iterator(),recurse:!1};if(Fl(r))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return dre(n,Wa.SHORTEST)},t)}function bre(e){if(e===null)return null;let t=e[0];return sre(t)?{value:vre(e),recurse:!1}:{value:null,recurse:!0}}function vre(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof Qe?En(e):fr(e)}var e6=class extends Rl{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},r1='"',Lc=Symbol("out"),d6=Symbol("field"),a1=Symbol("quote"),Kg=Symbol("quoteafterquote"),p6=Symbol("quoteinquote"),t6=class extends Rl{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new e6(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((r,a)=>(r[a]=r[a]+1||1,r),{}),n=Object.keys(t).filter(r=>t[r]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let r of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(r)===-1)throw new Error('The key "'+r+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},r={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let c=Number(o);if(isNaN(c))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=c;else switch(i.dtype){case"float32":l=c;break;case"int32":l=Math.floor(c);break;case"bool":l=this.getBoolean(o);break;default:l=c}}i&&i.isLabel?r[s]=l:n[s]=l}}return Object.keys(r).length===0?n:{xs:n,ys:r}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],r=0,a=e.length,s=Lc;for(let i=0;i<a;i++)switch(s){case Lc:switch(e.charAt(i)){case r1:r=i+1,s=a1;break;case this.delimiter:if(r=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=Lc;break;default:s=d6,r=i;break}break;case d6:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i)),s=Lc,r=i+1;break;default:}break;case a1:switch(e.charAt(i)){case r1:s=Kg;break;default:}break;case Kg:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i-1)),s=Lc,r=i+1;break;case r1:s=a1;break;default:s=p6;break}break;case p6:switch(e.charAt(i)){case r1:s=a1;break;default:}break;default:}if(s===Kg?n.push(e.substring(r,a-1)):n.push(e.substring(r)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},f6=class extends Gt{constructor(e){super();this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(Q().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new f6(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!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}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(a),r({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),fr(n,t)}},m6=class extends Gt{constructor(e,t){super();if(this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Qt([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=mr([s,a,o,i],[1,4])}else this.cropBox=mr([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(Q().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new m6(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=vu.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: 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o1(e,t,n,r=null){for(let a=0;a<I6.length;a++){let{key:s,indices:i}=I6[a],o=pa[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let c=i[l];e[o[l]]=[t[c][0],t[c][1],(t[c][2]+e[o[l]][2])/2]}}}var Z4=class{constructor(e,t,n,r){this.storedBoxes=[],this.runsWithoutFaceDetector=0,this.boundingBoxDetector=e,this.meshDetector=t,this.irisModel=n,this.meshWidth=r.face.mesh.inputSize,this.meshHeight=r.face.mesh.inputSize,this.irisSize=r.face.iris.inputSize,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,t,n,r){let a=s1({startPoint:t.startPoint,endPoint:t.endPoint}),s=[a[0]/this.meshWidth,a[1]/this.meshHeight],i=e.map(h=>[s[0]*(h[0]-this.meshWidth/2),s[1]*(h[1]-this.meshHeight/2),h[2]]),o=n!==0?k6(n,[0,0]):Yg,l=n!==0?i.map(h=>[...Bre(h,o),h[2]]):i,c=n!==0?Wre(r):Yg,u=[...i1({startPoint:t.startPoint,endPoint:t.endPoint}),1];return l.map(h=>[h[0]+_i(u,c[0]),h[1]+_i(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(e){let t=e[t2[0]][2],n=e[r2[0]][2];return t-n}getEyeBox(e,t,n,r,a=!1){let s=Jg(Zg(this.calculateLandmarksBoundingBox([e[n],e[r]]),this.irisEnlarge)),i=s1(s),o=St.cropAndResize(t,[[s.startPoint[1]/this.meshHeight,s.startPoint[0]/this.meshWidth,s.endPoint[1]/this.meshHeight,s.endPoint[0]/this.meshWidth]],[0],[this.irisSize,this.irisSize]);return a&&(o=St.flipLeftRight(o)),{box:s,boxSize:i,crop:o}}getEyeCoords(e,t,n,r=!1){let a=[];for(let s=0;s<a2;s++){let i=e[s*3],o=e[s*3+1],l=e[s*3+2];a.push([(r?1-i/this.irisSize:i/this.irisSize)*n[0]+t.startPoint[0],o/this.irisSize*n[1]+t.startPoint[1],l])}return{rawCoords:a,iris:a.slice(Qre)}}getAdjustedIrisCoords(e,t,n){let r=e[pa[`${n}EyeUpper0`][Jre]][2],a=e[pa[`${n}EyeLower0`][Yre]][2],s=(r+a)/2;return t.map((i,o)=>{let l=s;return o===2?l=r:o===4&&(l=a),[i[0],i[1],l]})}async predict(e,t){let n=!1,r;if((this.skipped===0||this.skipped>t.face.detector.skipFrames||!t.face.mesh.enabled||!t.videoOptimized)&&(r=await this.boundingBoxDetector.getBoundingBoxes(e),this.skipped=0),t.videoOptimized&&this.skipped++,r&&r.boxes&&(!t.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==t.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let s of r.boxes)this.storedBoxes.push({startPoint:s.box.startPoint.dataSync(),endPoint:s.box.endPoint.dataSync(),landmarks:s.landmarks,confidence:s.confidence});this.storedBoxes.length>0&&(n=!0)}if(n){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let s=0;s<this.storedBoxes.length;s++){let i=Ore({startPoint:this.storedBoxes[s].startPoint,endPoint:this.storedBoxes[s].endPoint},r.scaleFactor),o=Zg(i),l=Jg(o),c=this.storedBoxes[s].landmarks.arraySync(),u=this.storedBoxes[s].confidence;this.storedBoxes[s]={...l,confidence:u,landmarks:c}}this.runsWithoutFaceDetector=0}r&&r.boxes&&r.boxes.forEach(s=>{s.box.startPoint.dispose(),s.box.endPoint.dispose(),s.landmarks.dispose()});let a=U(()=>this.storedBoxes.map((s,i)=>{let o,l=0,c;if(t.face.detector.rotation){let[w,x]=s.landmarks.length>=jre?qre:Zre;l=Pre(s.landmarks[w],s.landmarks[x]);let _=i1({startPoint:s.startPoint,endPoint:s.endPoint}),I=[_[0]/e.shape[2],_[1]/e.shape[1]],S=St.rotateWithOffset(e,l,0,I);c=k6(-l,_),o=_6({startPoint:s.startPoint,endPoint:s.endPoint},S,[this.meshHeight,this.meshWidth]).div(255)}else{c=Yg;let w=e.clone();o=_6({startPoint:s.startPoint,endPoint:s.endPoint},w,[this.meshHeight,this.meshWidth]).div(255)}if(!t.face.mesh.enabled)return{coords:null,box:s,faceConfidence:null,confidence:s.confidence,image:o};let[,u,h]=this.meshDetector.predict(o),d=u.dataSync()[0];if(d<t.face.detector.minConfidence)return null;let p=q(h,[-1,3]).arraySync();if(t.face.iris.enabled){let{box:w,boxSize:x,crop:_}=this.getEyeBox(p,o,t2[0],t2[1],!0),{box:I,boxSize:S,crop:T}=this.getEyeBox(p,o,r2[0],r2[1]),E=this.irisModel.predict(ct([_,T])).dataSync(),C=E.slice(0,a2*3),{rawCoords:$,iris:D}=this.getEyeCoords(C,w,x,!0),P=E.slice(a2*3),{rawCoords:H,iris:V}=this.getEyeCoords(P,I,S),K=this.getLeftToRightEyeDepthDifference(p);Math.abs(K)<30?(o1(p,$,"left"),o1(p,H,"right")):K<1?o1(p,$,"left",["EyeUpper0","EyeLower0"]):o1(p,H,"right",["EyeUpper0","EyeLower0"]);let X=this.getAdjustedIrisCoords(p,D,"left"),ee=this.getAdjustedIrisCoords(p,V,"right");p=p.concat(X).concat(ee)}let f=this.transformRawCoords(p,s,l,c),m=Zg(this.calculateLandmarksBoundingBox(f)),A=Jg(m),y=mr(f),g={coords:y,box:m,faceConfidence:d,confidence:s.confidence,image:o,rawCoords:p};return t.face.mesh.returnRawData||delete g.rawCoords,this.storedBoxes[i]={...A,landmarks:y.arraySync(),confidence:s.confidence,faceConfidence:d},g}));return a=a.filter(s=>s!==null),this.detectedFaces=a.length,a}calculateLandmarksBoundingBox(e){let t=e.map(s=>s[0]),n=e.map(s=>s[1]),r=[Math.min(...t),Math.min(...n)],a=[Math.max(...t),Math.max(...n)];return{startPoint:r,endPoint:a,landmarks:e}}},N6=nu(J4()),S6={};Sr(S6,{FaceBoxes:()=>T6,load:()=>eae});var E6={};function Wc(e,t){if(!t||!t.kernels)return;let n=5,r=t.kernels.filter(o=>o.kernelTimeMs>0).reduce((o,l)=>o+=l.kernelTimeMs,0),a=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.kernelTimeMs>0).sort((o,l)=>l.kernelTimeMs-o.kernelTimeMs),s=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.totalBytesSnapshot>0).sort((o,l)=>l.totalBytesSnapshot-o.totalBytesSnapshot);a.length>n&&(a.length=n),s.length>n&&(s.length=n);let i={newBytes:t.newBytes,newTensors:t.newTensors,peakBytes:t.peakBytes,numKernelOps:t.kernels.length,timeKernelOps:r,slowestKernelOps:a,largestKernelOps:s};E6[e]=i,Ue("Human profiler",e,i)}var T6=class{constructor(e,t){this.enlarge=1.1,this.model=e,this.config=t}async estimateFaces(e,t){t&&(this.config=t);let n=[],r=St.resizeBilinear(e,[this.config.face.detector.inputSize,this.config.face.detector.inputSize]),a=r.toInt(),s,i;if(t.profile){let o=await Bo(()=>this.model.executeAsync(a));s=o.result[0].dataSync(),i=o.result[1].squeeze().arraySync(),o.result.forEach(l=>l.dispose()),Wc("faceboxes",o)}else{let[o,l,c]=await this.model.executeAsync(a);s=o.dataSync();let u=l.squeeze();i=u.arraySync(),o.dispose(),l.dispose(),u.dispose(),c.dispose()}a.dispose(),r.dispose();for(let o in i)if(s[o]&&s[o]>this.config.face.detector.minConfidence){let l=[i[o][0]/this.enlarge,i[o][1]/this.enlarge,i[o][2]*this.enlarge,i[o][3]*this.enlarge],c=[l[1],l[0],l[3]-l[1],l[2]-l[0]],u=[parseInt((c[0]*e.shape[2]).toString()),parseInt((c[1]*e.shape[1]).toString()),parseInt((c[2]*e.shape[2]).toString()),parseInt((c[3]*e.shape[1]).toString())],h=St.cropAndResize(e,[l],[0],[this.config.face.detector.inputSize,this.config.face.detector.inputSize]),d=h.div([255]);h.dispose(),n.push({confidence:s[o],box:u,boxRaw:this.config.face.mesh.returnRawData?c:null,image:d})}return n}};async function eae(e){let t=await Yn(e.face.detector.modelPath);Ue(`load model: ${e.face.detector.modelPath.match(/\/(.*)\./)[1]}`);let n=new T6(t,e);return e.face.mesh.enabled&&Ue(`load model: ${e.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),e.face.iris.enabled&&Ue(`load model: ${e.face.iris.modelPath.match(/\/(.*)\./)[1]}`),n}var C6={};Sr(C6,{load:()=>s2,predict:()=>i2});var Ml,l1={age:0},u1=Number.MAX_SAFE_INTEGER;async function s2(e){return Ml||(Ml=await Yn(e.face.age.modelPath),Ue(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),Ml}async function i2(e,t){return Ml?u1<t.face.age.skipFrames&&t.videoOptimized&&l1.age&&l1.age>0?(u1++,l1):(t.videoOptimized?u1=0:u1=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=St.resizeBilinear(e,[t.face.age.inputSize,t.face.age.inputSize],!1),a=W(r,[255]);Ce(r);let s,i={age:0};if(!t.profile)t.face.age.enabled&&(s=await Ml.predict(a));else{let o=t.face.age.enabled?await Bo(()=>Ml.predict(a)):{};s=o.result.clone(),o.result.dispose(),Wc("age",o)}if(a.dispose(),s){let o=s.dataSync();i.age=Math.trunc(10*o[0])/10}s.dispose(),l1=i,n(i)})):null}var R6={};Sr(R6,{load:()=>o2,predict:()=>l2});var bi,u2={gender:""},c1=Number.MAX_SAFE_INTEGER,c2=!1,h2=[.2989,.587,.114];async function o2(e){return bi||(bi=await Yn(e.face.gender.modelPath),c2=bi.inputs[0].shape[3]===1,Ue(`load model: ${e.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),bi}async function l2(e,t){return bi?c1<t.face.gender.skipFrames&&t.videoOptimized&&u2.gender!==""?(c1++,u2):(t.videoOptimized?c1=0:c1=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=St.resizeBilinear(e,[t.face.gender.inputSize,t.face.gender.inputSize],!1),a;c2?a=U(()=>{let[o,l,c]=an(r,3,3),u=W(o,h2[0]),h=W(l,h2[1]),d=W(c,h2[2]);return Qh([u,h,d]).sub(.5).mul(2)}):a=W(r,[255]),Ce(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await bi.predict(a));else{let o=t.face.gender.enabled?await Bo(()=>bi.predict(a)):{};s=o.result.clone(),o.result.dispose(),Wc("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(c2){let l=Math.trunc(100*Math.abs(o[0]-o[1]))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=l)}else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),u2=i,n(i)})):null}var F6={};Sr(F6,{load:()=>d2,predict:()=>p2});var tae=["angry","disgust","fear","happy","sad","surprise","neutral"],$l,f2=[],h1=Number.MAX_SAFE_INTEGER,m2=[.2989,.587,.114],M6=1;async function d2(e){return $l||($l=await Yn(e.face.emotion.modelPath),Ue(`load model: ${e.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),$l}async function p2(e,t){return $l?h1<t.face.emotion.skipFrames&&t.videoOptimized&&f2.length>0?(h1++,f2):(t.videoOptimized?h1=0:h1=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=St.resizeBilinear(e,[t.face.emotion.inputSize,t.face.emotion.inputSize],!1),[a,s,i]=an(r,3,3);r.dispose();let o=W(a,m2[0]),l=W(s,m2[1]),c=W(i,m2[2]);a.dispose(),s.dispose(),i.dispose();let u=Qh([o,l,c]);o.dispose(),l.dispose(),c.dispose();let h=U(()=>u.sub(.5).mul(2));u.dispose();let d=[];if(t.face.emotion.enabled){let p;if(t.profile){let f=await Bo(()=>$l.predict(h));p=f.result.dataSync(),f.result.dispose(),Wc("emotion",f)}else{let f=await $l.predict(h);p=f.dataSync(),Ce(f)}for(let f=0;f<p.length;f++)M6*p[f]>t.face.emotion.minConfidence&&d.push({score:Math.min(.99,Math.trunc(100*M6*p[f])/100),emotion:tae[f]});d.sort((f,m)=>m.score-f.score)}h.dispose(),f2=d,n(d)})):null}var Dl;async function $6(e){return Dl||(Dl=await Yn(e.face.embedding.modelPath),Ue(`load model: ${e.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),Dl}function nae(e,t){if((e==null?void 0:e.length)!==(t==null?void 0:t.length))return 0;let n=2,r=10*e.map((a,s)=>a-t[s]).reduce((a,s)=>a+s**n,0)**(1/n);return Math.trunc(1e3*(1-r))/1e3}async function D6(e,t){return Dl?new Promise(async n=>{let r=St.resizeBilinear(e,[t.face.embedding.inputSize,t.face.embedding.inputSize],!1),a=[];if(t.face.embedding.enabled)if(t.profile){let s=await Bo(()=>Dl.predict({img_inputs:r}));a=[...s.result.dataSync()],s.result.dispose(),Wc("emotion",s)}else{let s=await Dl.predict({img_inputs:r});a=[...s.dataSync()],Ce(s)}r.dispose(),n(a)}):null}var O6={};Sr(O6,{PoseNet:()=>z6,load:()=>A2});var rae=[-123.15,-115.9,-103.06];function aae(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}function sae(e){let[t,n,r,a]=e;return{offsets:r,heatmap:a,displacementFwd:t,displacementBwd:n}}var iae=class{constructor(e){this.model=e}predict(e,t){return U(()=>{let n=(t.body.modelType==="ResNet"?e.toFloat().add(rae):e.toFloat().div(127.5).sub(1)).expandDims(0),r=this.model.predict(n).map(s=>s.squeeze([0])),a=t.body.modelType==="ResNet"?sae(r):aae(r);return{heatmapScores:a.heatmap.sigmoid(),offsets:a.offsets,displacementFwd:a.displacementFwd,displacementBwd:a.displacementBwd}})}dispose(){this.model.dispose()}};function y2(e){return Math.floor(e/2)}var oae=class{constructor(e,t){this.priorityQueue=new Array(e),this.numberOfElements=-1,this.getElementValue=t}enqueue(e){this.priorityQueue[++this.numberOfElements]=e,this.swim(this.numberOfElements)}dequeue(){let e=this.priorityQueue[0];return 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oae(r*a*s,({score:o})=>o);for(let o=0;o<r;++o)for(let l=0;l<a;++l)for(let c=0;c<s;++c){let u=n.get(o,l,c);u<e||lae(c,u,o,l,t,n)&&i.enqueue({score:u,part:{heatmapY:o,heatmapX:l,id:c}})}return i}var Ol=nu(Ef()),cae=nu(Ef());function P6(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+cae.NUM_KEYPOINTS)}}function L6(e,t,n){let{heatmapY:r,heatmapX:a,id:s}=e,{y:i,x:o}=P6(r,a,s,n);return{x:e.heatmapX*t+o,y:e.heatmapY*t+i}}function W6(e,t,n){return e<t?t:e>n?n:e}function hae(e,t,n,r){let a=n-e,s=r-t;return a*a+s*s}function B6(e,t){return{x:e.x+t.x,y:e.y+t.y}}var g2=nu(Ef());function dae(e,t){let n=t.shape[0],r=new Float32Array(n);for(let a=0;a<n;a++){let s=t.get(a,0),i=t.get(a,1);r[a]=e.get(s,i,a)}return r}function pae(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+g2.NUM_KEYPOINTS)}}function fae(e,t){let n=[];for(let r=0;r<g2.NUM_KEYPOINTS;r++){let a=e.get(r,0).valueOf(),s=e.get(r,1).valueOf(),{x:i,y:o}=pae(a,s,r,t);n.push(o),n.push(i)}return mr(n,[g2.NUM_KEYPOINTS,2])}function mae(e,t,n){return U(()=>e.toTensor().mul(Se(t,"int32")).toFloat().add(fae(e,n)))}function Aae(e,t){return U(()=>{let n=e.div(Se(t,"int32"));return e.sub(n.mul(Se(t,"int32")))})}function yae(e){let[t,n,r]=e.shape;return U(()=>{let a=e.reshape([t*n,r]).argMax(0),s=a.div(Se(n,"int32")).expandDims(1),i=Aae(a,n).expandDims(1);return ct([s,i],1)})}var V6=Ol.poseChain.map(([e,t])=>[Ol.partIds[e],Ol.partIds[t]]),x2=V6.map(([,e])=>e),U6=V6.map(([e])=>e);function gae(e,t,n){let r=n.shape[2]/2;return{y:n.get(t.y,t.x,e),x:n.get(t.y,t.x,r+e)}}function w2(e,t,n,r){return{y:W6(Math.round(e.y/t),0,n-1),x:W6(Math.round(e.x/t),0,r-1)}}function H6(e,t,n,r,a,s,i,o=2){let[l,c]=r.shape,u=w2(t.position,s,l,c),h=gae(e,u,i),d=B6(t.position,h);for(let m=0;m<o;m++){let A=w2(d,s,l,c),y=P6(A.y,A.x,n,a);d=B6({x:A.x*s,y:A.y*s},{x:y.x,y:y.y})}let p=w2(d,s,l,c),f=r.get(p.y,p.x,n);return{position:d,part:Ol.partNames[n],score:f}}function xae(e,t,n,r,a,s){let i=t.shape[2],o=x2.length,l=new 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s=[],i=uae(a.body.scoreThreshold,_ae,e),o=a.body.nmsRadius^2;for(;s.length<a.body.maxDetections&&!i.empty();){let l=i.dequeue(),c=L6(l.part,a.body.outputStride,t);if(j6(s,o,c,l.part.id))continue;let u=xae(l,e,t,a.body.outputStride,n,r),h=bae(s,o,u);h>a.body.scoreThreshold&&s.push({keypoints:u,score:h})}return s}async function kae(e){return Promise.all(e.map(t=>t.buffer()))}function Iae(e,t,n){return{score:e.score,keypoints:e.keypoints.map(({score:r,part:a,position:s})=>({score:r,part:a,position:{x:s.x*n,y:s.y*t}}))}}function Nae(e,[t,n]){let r=e.squeeze(0),a=r.resizeBilinear([t,n]);return r.dispose(),a}function G6(e,[t,n],[r,a]){return e.map(s=>Iae(s,t/r,n/a))}async function Sae(e,t,n){return new Promise(async r=>{let a=e.shape[1],s=e.shape[2],i=await kae([t.heatmapScores,t.offsets,t.displacementFwd,t.displacementBwd]),o=i[0],l=i[1],c=i[2],u=i[3],h=await vae(o,l,c,u,n),d=G6(h,[a,s],[n.body.inputSize,n.body.inputSize]);r(d)})}async function Tae(e,t,n){return new Promise(async r=>{let a=e.shape[1],s=e.shape[2],i=[await wae(t.heatmapScores,t.offsets,n)],o=G6(i,[a,s],[n.body.inputSize,n.body.inputSize]);r(o)})}var z6=class{constructor(e){this.baseModel=e}async estimatePoses(e,t){let n=Nae(e,[t.body.inputSize,t.body.inputSize]),r=this.baseModel.predict(n,t),a=t.body.maxDetections<2?await Tae(e,r,t):await Sae(e,r,t);return r.heatmapScores.dispose(),r.offsets.dispose(),r.displacementFwd.dispose(),r.displacementBwd.dispose(),n.dispose(),a}dispose(){this.baseModel.dispose()}};async function A2(e){let t=await Yn(e.body.modelPath),n=new iae(t);return Ue(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`),new z6(n)}var q6={};Sr(q6,{HandPose:()=>X6,load:()=>_2});function b2(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function d1(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function Eae(e,t,n){let r=t.shape[1],a=t.shape[2],s=[[e.startPoint[1]/r,e.startPoint[0]/a,e.endPoint[1]/r,e.endPoint[0]/a]];return St.cropAndResize(t,s,[0],n)}function Cae(e,t){let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],r=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],a=e.palmLandmarks.map(s=>[s[0]*t[0],s[1]*t[1]]);return{startPoint:n,endPoint:r,palmLandmarks:a,confidence:e.confidence}}function v2(e,t=1.5){let n=d1(e),r=b2(e),a=[t*r[0]/2,t*r[1]/2],s=[n[0]-a[0],n[1]-a[1]],i=[n[0]+a[0],n[1]+a[1]];return{startPoint:s,endPoint:i,palmLandmarks:e.palmLandmarks}}function k2(e){let t=d1(e),n=b2(e),r=Math.max(...n)/2,a=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:a,endPoint:s,palmLandmarks:e.palmLandmarks}}var Rae=class{constructor(e,t,n){this.model=e,this.anchors=n.map(r=>[r.x_center,r.y_center]),this.anchorsTensor=mr(this.anchors),this.inputSizeTensor=Qt([t,t]),this.doubleInputSizeTensor=Qt([t*2,t*2])}normalizeBoxes(e){return U(()=>{let t=Me(e,[0,0],[-1,2]),n=Me(e,[0,2],[-1,2]),r=oe(Ne(t,this.inputSizeTensor),this.anchorsTensor),a=Ne(n,this.doubleInputSizeTensor),s=W(we(r,a),this.inputSizeTensor),i=W(oe(r,a),this.inputSizeTensor);return td([s,i],1)})}normalizeLandmarks(e,t){return U(()=>{let n=oe(Ne(e.reshape([-1,7,2]),this.inputSizeTensor),this.anchors[t]);return W(n,this.inputSizeTensor)})}async getBoxes(e,t){let n=this.model.predict(e),r=n.squeeze();n.dispose();let a=U(()=>er(Me(r,[0,0],[-1,1])).squeeze()),s=a.dataSync(),i=Me(r,[0,1],[-1,4]),o=this.normalizeBoxes(i);i.dispose();let l=await St.nonMaxSuppressionAsync(o,s,t.hand.maxHands,t.hand.iouThreshold,t.hand.scoreThreshold),c=l.arraySync();a.dispose(),l.dispose();let u=[];for(let h of c)if(s[h]>=t.hand.minConfidence){let d=Me(o,[h,0],[1,-1]),p=Me(r,[h,5],[1,14]),f=U(()=>this.normalizeLandmarks(p,h).reshape([-1,2]));p.dispose(),u.push({box:d,palmLandmarks:f,confidence:s[h]})}return r.dispose(),o.dispose(),u}async estimateHandBounds(e,t){let n=e.shape[1],r=e.shape[2],a=U(()=>e.resizeBilinear([t.hand.inputSize,t.hand.inputSize]).div(127.5).sub(1)),s=await this.getBoxes(a,t);a.dispose();let i=[];if(!s||s.length===0)return i;for(let o of s){let l=o.box.dataSync(),c=l.slice(0,2),u=l.slice(2,4),h=o.palmLandmarks.arraySync();o.box.dispose(),o.palmLandmarks.dispose(),i.push(Cae({startPoint:c,endPoint:u,palmLandmarks:h,confidence:o.confidence},[r/t.hand.inputSize,n/t.hand.inputSize]))}return i}};function Fae(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function Mae(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return Fae(n)}var K6=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function vi(e,t){let n=0;for(let r=0;r<e.length;r++)n+=e[r]*t[r];return n}function $ae(e,t){let n=[];for(let r=0;r<e.length;r++)n.push(e[r][t]);return n}function Z6(e,t){let n=[],r=e.length;for(let a=0;a<r;a++){n.push([]);for(let s=0;s<r;s++)n[a].push(vi(e[a],$ae(t,s)))}return n}function J6(e,t){let n=Math.cos(e),r=Math.sin(e),a=[[n,-r,0],[r,n,0],[0,0,1]],s=K6(t[0],t[1]),i=Z6(s,a),o=K6(-t[0],-t[1]);return Z6(i,o)}function Dae(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],r=[-vi(t[0],n),-vi(t[1],n)];return[t[0].concat(r[0]),t[1].concat(r[1]),[0,0,1]]}function Y6(e,t){return[vi(e,t[0]),vi(e,t[1])]}var Oae=5,Q6=1.65,ev=[0,5,9,13,17,1,2],zae=0,Pae=2,Lae=class{constructor(e,t,n){this.handDetector=e,this.landmarkDetector=t,this.inputSize=n,this.storedBoxes=[],this.skipped=0,this.detectedHands=0}getBoxForPalmLandmarks(e,t){let n=e.map(a=>Y6([...a,1],t)),r=this.calculateLandmarksBoundingBox(n);return v2(k2(r),Oae)}getBoxForHandLandmarks(e){let t=this.calculateLandmarksBoundingBox(e),n=v2(k2(t),Q6);n.palmLandmarks=[];for(let r=0;r<ev.length;r++)n.palmLandmarks.push(e[ev[r]].slice(0,2));return n}transformRawCoords(e,t,n,r){let a=b2(t),s=[a[0]/this.inputSize,a[1]/this.inputSize,(a[0]+a[1])/this.inputSize/2],i=e.map(d=>[s[0]*(d[0]-this.inputSize/2),s[1]*(d[1]-this.inputSize/2),s[2]*d[2]]),o=J6(n,[0,0]),l=i.map(d=>[...Y6(d,o),d[2]]),c=Dae(r),u=[...d1(t),1],h=[vi(u,c[0]),vi(u,c[1])];return l.map(d=>[d[0]+h[0],d[1]+h[1],d[2]])}async estimateHands(e,t){let n=!1,r;(this.skipped===0||this.skipped>t.hand.skipFrames||!t.hand.landmarks||!t.videoOptimized)&&(r=await this.handDetector.estimateHandBounds(e,t),this.skipped=0),t.videoOptimized&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==t.hand.maxHands||!t.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let a=[];for(let s=0;s<this.storedBoxes.length;s++){let i=this.storedBoxes[s];if(i)if(t.hand.landmarks){let o=t.hand.rotation?Mae(i.palmLandmarks[zae],i.palmLandmarks[Pae]):0,l=d1(i),c=[l[0]/e.shape[2],l[1]/e.shape[1]],u=t.hand.rotation?St.rotateWithOffset(e,o,0,c):e.clone(),h=J6(-o,l),d=n?this.getBoxForPalmLandmarks(i.palmLandmarks,h):i,p=Eae(d,u,[this.inputSize,this.inputSize]),f=p.div(255);p.dispose(),u.dispose();let[m,A]=await this.landmarkDetector.predict(f);f.dispose();let y=m.dataSync()[0];if(m.dispose(),y>=t.hand.minConfidence){let g=q(A,[-1,3]),w=g.arraySync();A.dispose(),g.dispose();let x=this.transformRawCoords(w,d,o,h),_=this.getBoxForHandLandmarks(x);this.storedBoxes[s]=_;let I={landmarks:x,confidence:y,box:{topLeft:_.startPoint,bottomRight:_.endPoint}};a.push(I)}else this.storedBoxes[s]=null;A.dispose()}else{let o=v2(k2(i),Q6),l={confidence:i.confidence,box:{topLeft:o.startPoint,bottomRight:o.endPoint}};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(s=>s!==null),this.detectedHands=a.length,a}calculateLandmarksBoundingBox(e){let 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${e.hand.skeleton.modelPath.match(/\/(.*)\./)[1]}`),s}var Bae=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let r=e[n].keypoints.find(l=>l.part==="leftWrist"),a=e[n].keypoints.find(l=>l.part==="rightWrist"),s=e[n].keypoints.find(l=>l.part==="nose");s&&r&&a&&r.position.y<s.position.y&&a.position.y<s.position.y?t.push({body:n,gesture:"i give up"}):s&&r&&r.position.y<s.position.y?t.push({body:n,gesture:"raise left hand"}):s&&a&&a.position.y<s.position.y&&t.push({body:n,gesture:"raise right hand"});let i=e[n].keypoints.find(l=>l.part==="leftShoulder"),o=e[n].keypoints.find(l=>l.part==="rightShoulder");i&&o&&t.push({body:n,gesture:`leaning ${i.position.y>o.position.y?"left":"right"}`})}return t},Vae=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++)if(e[n].mesh&&e[n].mesh.length>0){let r=e[n].mesh[35][2]-e[n].mesh[263][2];Math.abs(r)<10?t.push({face:n,gesture:"facing camera"}):t.push({face:n,gesture:`facing ${r<0?"right":"left"}`}),Math.abs(e[n].mesh[374][1]-e[n].mesh[386][1])/Math.abs(e[n].mesh[443][1]-e[n].mesh[450][1])<.2&&t.push({face:n,gesture:"blink left eye"}),Math.abs(e[n].mesh[145][1]-e[n].mesh[159][1])/Math.abs(e[n].mesh[223][1]-e[n].mesh[230][1])<.2&&t.push({face:n,gesture:"blink right eye"});let a=Math.min(100,500*Math.abs(e[n].mesh[13][1]-e[n].mesh[14][1])/Math.abs(e[n].mesh[10][1]-e[n].mesh[152][1]));a>10&&t.push({face:n,gesture:`mouth ${Math.trunc(a)}% open`});let s=e[n].mesh[152][2];Math.abs(s)>10&&t.push({face:n,gesture:`head ${s<0?"up":"down"}`})}return t},Uae=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){if(!e[n].annotations||!e[n].annotations.leftEyeIris||!e[n].annotations.rightEyeIris)continue;let 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--trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",lint:"eslint src demo server",dev:"npm install && node server/serve.js",build:"rimraf dist/* && rimraf types/* && node server/build.js && node server/changelog.js",update:"npm update --depth 20 --force && npm dedupe && npm prune && npm audit"},xv=["tensorflowjs","face-detection","face-geometry","face-embedding","face-recognition","body-tracking","hand-tracking","iris-tracking","age-estimation","emotion-detection","gender-prediction","gesture-recognition"],qae={name:rv,version:T2,description:av,sideEffects:sv,main:iv,module:ov,browser:lv,author:uv,bugs:cv,homepage:hv,license:dv,engines:pv,repository:fv,dependencies:mv,peerDependencies:Av,devDependencies:yv,scripts:gv,keywords:xv},ft=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function zl(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,r)=>(Object.keys(r||{}).forEach(a=>{let s=n[a],i=r[a];Array.isArray(s)&&Array.isArray(i)?n[a]=s.concat(...i):t(s)&&t(i)?n[a]=zl(s,i):n[a]=i}),n),{})}var wv=class{constructor(e={}){this.tf=L2,this.package=nv,this.version=T2,this.config=zl(Gae,e),this.fx=null,this.state="idle",this.numTensors=0,this.analyzeMemoryLeaks=!1,this.checkSanity=!1,this.firstRun=!0,this.perf={},this.models={facemesh:null,posenet:null,handpose:null,iris:null,age:null,gender:null,emotion:null},this.facemesh=N6,this.age=C6,this.gender=R6,this.emotion=F6,this.body=O6,this.hand=q6}profile(){return this.config.profile?E6:{}}analyze(...e){if(!this.analyzeMemoryLeaks)return;let t=pn().state.numTensors,n=this.numTensors;this.numTensors=t;let r=t-n;r!==0&&Ue(...e,r)}sanity(e){if(!this.checkSanity)return null;if(!e)return"input is not defined";if(kn.flags.IS_NODE&&!(e instanceof Qe))return"input must be a tensor";try{Jh()}catch(t){return"backend not loaded"}return null}simmilarity(e,t){return this.config.face.embedding.enabled?nae(e,t):0}async load(e=null){this.state="load";let t=ft();e&&(this.config=zl(this.config,e)),this.firstRun&&(Ue(`version: ${this.version} TensorFlow/JS version: ${X2}`),await this.checkBackend(!0),kn.flags.IS_BROWSER&&(Ue("configuration:",this.config),Ue("tf flags:",kn.flags)));let n=this.config.face.detector.modelPath.includes("faceboxes")?S6:N6;this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.posenet,this.models.handpose]=await Promise.all([this.models.face||(this.config.face.enabled?n.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?s2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?o2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?d2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?$6(this.config):null),this.models.posenet||(this.config.body.enabled?A2(this.config):null),this.models.handpose||(this.config.hand.enabled?_2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await n.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await s2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await o2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await d2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await $6(this.config)),this.config.body.enabled&&!this.models.posenet&&(this.models.posenet=await A2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await _2(this.config))),this.firstRun&&(Ue("tf engine state:",pn().state.numBytes,"bytes",pn().state.numTensors,"tensors"),this.firstRun=!1);let r=Math.trunc(ft()-t);r>(this.perf.load||0)&&(this.perf.load=r)}async checkBackend(e=!1){if(this.config.backend&&this.config.backend!==""&&e||Jh()!==this.config.backend){let t=ft();this.state="backend",Ue("setting backend:",this.config.backend),this.config.backend==="wasm"&&(Ue("settings wasm path:",this.config.wasmPath),F0(this.config.wasmPath),await Q().getAsync("WASM_HAS_SIMD_SUPPORT")||Ue("warning: wasm simd support is not enabled")),this.config.backend==="humangl"&&Rre();try{await Z2(this.config.backend)}catch(n){Ue("error: cannot set backend:",this.config.backend,n)}if(K2(),Jh()==="webgl"){this.config.deallocate&&(Ue("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),kn.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1)),kn.set("WEBGL_FORCE_F16_TEXTURES",!0),kn.set("WEBGL_PACK_DEPTHWISECONV",!0);let n=await Of().getGPGPUContext().gl;Ue(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}await J2(),this.perf.backend=Math.trunc(ft()-t)}}async detectFace(e){var t,n,r,a,s,i;let o,l,c,u,h,d=[];this.state="run:face",o=ft();let p=await((t=this.models.face)==null?void 0:t.estimateFaces(e,this.config));this.perf.face=Math.trunc(ft()-o);for(let f of p){if(this.analyze("Get Face"),!f.image||f.image.isDisposedInternal){Ue("Face object is disposed:",f.image);continue}this.analyze("Start Age:"),this.config.async?l=this.config.face.age.enabled?i2(f.image,this.config):{}:(this.state="run:age",o=ft(),l=this.config.face.age.enabled?await i2(f.image,this.config):{},this.perf.age=Math.trunc(ft()-o)),this.analyze("Start Gender:"),this.config.async?c=this.config.face.gender.enabled?l2(f.image,this.config):{}:(this.state="run:gender",o=ft(),c=this.config.face.gender.enabled?await l2(f.image,this.config):{},this.perf.gender=Math.trunc(ft()-o)),this.analyze("Start Emotion:"),this.config.async?u=this.config.face.emotion.enabled?p2(f.image,this.config):{}:(this.state="run:emotion",o=ft(),u=this.config.face.emotion.enabled?await p2(f.image,this.config):{},this.perf.emotion=Math.trunc(ft()-o)),this.analyze("End Emotion:"),this.analyze("Start Embedding:"),this.config.async?h=this.config.face.embedding.enabled?D6(f.image,this.config):{}:(this.state="run:embedding",o=ft(),h=this.config.face.embedding.enabled?await D6(f.image,this.config):{},this.perf.embedding=Math.trunc(ft()-o)),this.analyze("End Emotion:"),this.config.async&&([l,c,u,h]=await Promise.all([l,c,u,h])),this.analyze("Finish Face:"),!this.config.face.iris.enabled&&((n=f==null?void 0:f.annotations)==null?void 0:n.leftEyeIris)&&((r=f==null?void 0:f.annotations)==null?void 0:r.rightEyeIris)&&(delete f.annotations.leftEyeIris,delete f.annotations.rightEyeIris);let m=((a=f.annotations)==null?void 0:a.leftEyeIris)&&((s=f.annotations)==null?void 0:s.rightEyeIris)?11.7*Math.max(Math.abs(f.annotations.leftEyeIris[3][0]-f.annotations.leftEyeIris[1][0]),Math.abs(f.annotations.rightEyeIris[4][1]-f.annotations.rightEyeIris[2][1])):0;d.push({confidence:f.confidence,box:f.box,mesh:f.mesh,boxRaw:f.boxRaw,meshRaw:f.meshRaw,annotations:f.annotations,age:l.age,gender:c.gender,genderConfidence:c.confidence,emotion:u,embedding:h,iris:m!==0?Math.trunc(m)/100:0}),(i=f.image)==null||i.dispose(),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),d}async image(e,t={}){var n;this.state="image",this.config=zl(this.config,t);let r=tv(e,this.config);return(n=r==null?void 0:r.tensor)==null||n.dispose(),r==null?void 0:r.canvas}async detect(e,t={}){return new Promise(async n=>{var r,a,s,i;this.state="config";let o;this.config=zl(this.config,t),this.state="check";let l=this.sanity(e);l&&(Ue(l,e),n({error:l}));let c,u,h,d=ft();await this.checkBackend(),await this.load(),this.config.scoped&&pn().startScope(),this.analyze("Start Scope:"),o=ft();let p=tv(e,this.config);if(!p||!p.tensor){Ue("could not convert input to tensor"),n({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(ft()-o),this.analyze("Get Image:"),this.config.async?(h=this.config.face.enabled?this.detectFace(p.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",o=ft(),h=this.config.face.enabled?await this.detectFace(p.tensor):[],this.perf.face=Math.trunc(ft()-o)),this.analyze("Start Body:"),this.config.async?(c=this.config.body.enabled?(r=this.models.posenet)==null?void 0:r.estimatePoses(p.tensor,this.config):[],this.perf.body&&delete this.perf.body):(this.state="run:body",o=ft(),c=this.config.body.enabled?await((a=this.models.posenet)==null?void 0:a.estimatePoses(p.tensor,this.config)):[],this.perf.body=Math.trunc(ft()-o)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(u=this.config.hand.enabled?(s=this.models.handpose)==null?void 0:s.estimateHands(p.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",o=ft(),u=this.config.hand.enabled?await((i=this.models.handpose)==null?void 0:i.estimateHands(p.tensor,this.config)):[],this.perf.hand=Math.trunc(ft()-o)),this.analyze("End Hand:"),this.config.async&&([h,c,u]=await Promise.all([h,c,u])),p.tensor.dispose(),this.config.scoped&&pn().endScope(),this.analyze("End Scope:");let f=[];this.config.gesture.enabled&&(o=ft(),f=[...Vae(h),...Bae(c),...Hae(u),...Uae(h)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(ft()-o)),this.perf.total=Math.trunc(ft()-d),this.state="idle",n({face:h,body:c,hand:u,gesture:f,performance:this.perf,canvas:p.canvas})})}async warmupBitmap(){let e=(r,a="application/octet-stream")=>fetch(`data:${a};base64,${r}`).then(s=>s.blob()),t,n;switch(this.config.warmup){case"face":t=await e(N2);break;case"full":t=await e(S2);break;default:t=null}if(t){let r=await createImageBitmap(t);n=await this.detect(r,this.config),r.close()}return n}async warmupCanvas(){return new Promise(e=>{let t,n=0;switch(this.config.warmup){case"face":n=256,t="data:image/jpeg;base64,"+N2;break;case"full":n=1200,t="data:image/jpeg;base64,"+S2;break;default:t=null}let r=new Image(n,n);r.onload=()=>{let a=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(n,n):document.createElement("canvas");a.width=n,a.height=n;let s=a.getContext("2d");s==null||s.drawImage(r,0,0);let i=s==null?void 0:s.getImageData(0,0,n,n);this.detect(i,this.config).then(o=>e(o))},t?r.src=t:e(null)})}async warmupNode(){let e=s=>Buffer.from(s,"base64"),t=this.config.warmup==="face"?e(N2):e(S2),n=(void 0).decodeJpeg(t),r=n.expandDims(0);Ce(n);let a=await this.detect(r,this.config);return Ce(r),a}async warmup(e){let t=ft();e&&(this.config=zl(this.config,e));let n=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await this.warmupBitmap():typeof Image!="undefined"?r=await this.warmupCanvas():r=await this.warmupNode(),this.config.videoOptimized=n;let a=ft();return Ue("Warmup",this.config.warmup,Math.round(a-t),"ms",r),r}};async function Xae(e,t,n){if(!e)return;let r=t.getContext("2d");r.font=n.baseFont,r.fillStyle=n.baseLabel;let a=1;for(let s=0;s<e.length;s++){let[i,o]=Object.entries(e[s]);if(o.length>1&&o[1].length>0){let l=i[1]>0?`#${i[1]}`:"",c=`${i[0]} ${l}: ${o[1]}`;r.fillStyle="black",r.fillText(c,8,2+a*n.baseLineHeight),r.fillStyle=n.baseLabel,r.fillText(c,6,0+a*n.baseLineHeight),a+=1}}}async function Kae(e,t,n,r){if(!e)return;let a=t.getContext("2d");for(let s of e){a.font=n.baseFont,a.strokeStyle=n.baseColor,a.fillStyle=n.baseColor,a.lineWidth=n.baseLineWidth,a.beginPath(),n.drawBoxes&&a.rect(s.box[0],s.box[1],s.box[2],s.box[3]);let i=[];if(s.genderConfidence&&i.push(`${s.gender||""} ${Math.trunc(100*s.genderConfidence)}% confident`),s.age&&i.push(`age: ${s.age||""}`),s.iris&&i.push(`iris distance: ${s.iris}`),s.emotion&&s.emotion.length>0){let o=s.emotion.map(l=>`${Math.trunc(100*l.score)}% ${l.emotion}`);i.push(o.join(" "))}i.length===0&&i.push("face"),a.fillStyle=n.baseLabel;for(let o=0;o<i.length;o++)a.fillStyle="black",a.fillText(i[o],s.box[0]+1,s.box[1]-(i.length-o)*n.baseLineHeight+6),a.fillStyle=n.baseLabel,a.fillText(i[o],s.box[0]+0,s.box[1]-(i.length-o)*n.baseLineHeight+5);if(a.fillStyle=n.baseColor,a.stroke(),a.lineWidth=1,s.mesh){if(n.drawPoints)for(let o of s.mesh)a.fillStyle=n.useDepth?`rgba(${127.5+2*o[2]}, ${127.5-2*o[2]}, 255, 0.5)`:n.baseColor,a.beginPath(),a.arc(o[0],o[1],2,0,2*Math.PI),a.fill();if(n.drawPolygons){for(let o=0;o<r.length/3;o++){let l=[r[o*3+0],r[o*3+1],r[o*3+2]].map(u=>s.mesh[u]),c=new Path2D;c.moveTo(l[0][0],l[0][1]);for(let u of l)c.lineTo(u[0],u[1]);c.closePath(),a.strokeStyle=n.useDepth?`rgba(${127.5+2*l[0][2]}, ${127.5-2*l[0][2]}, 255, 0.3)`:n.baseColor,a.stroke(c),n.fillPolygons&&(a.fillStyle=n.useDepth?`rgba(${127.5+2*l[0][2]}, ${127.5-2*l[0][2]}, 255, 0.3)`:n.baseColor,a.fill(c))}if(s.annotations&&s.annotations.leftEyeIris){a.strokeStyle=n.useDepth?"rgba(255, 200, 255, 0.3)":n.baseColor,a.beginPath();let o=Math.abs(s.annotations.leftEyeIris[3][0]-s.annotations.leftEyeIris[1][0])/2,l=Math.abs(s.annotations.leftEyeIris[4][1]-s.annotations.leftEyeIris[2][1])/2;a.ellipse(s.annotations.leftEyeIris[0][0],s.annotations.leftEyeIris[0][1],o,l,0,0,2*Math.PI),a.stroke(),n.fillPolygons&&(a.fillStyle=n.useDepth?"rgba(255, 255, 200, 0.3)":n.baseColor,a.fill())}if(s.annotations&&s.annotations.rightEyeIris){a.strokeStyle=n.useDepth?"rgba(255, 200, 255, 0.3)":n.baseColor,a.beginPath();let o=Math.abs(s.annotations.rightEyeIris[3][0]-s.annotations.rightEyeIris[1][0])/2,l=Math.abs(s.annotations.rightEyeIris[4][1]-s.annotations.rightEyeIris[2][1])/2;a.ellipse(s.annotations.rightEyeIris[0][0],s.annotations.rightEyeIris[0][1],o,l,0,0,2*Math.PI),a.stroke(),n.fillPolygons&&(a.fillStyle=n.useDepth?"rgba(255, 255, 200, 0.3)":n.baseColor,a.fill())}}}}}var Ba=[];async function Zae(e,t,n){if(!e)return;let r=t.getContext("2d");r.lineJoin="round";for(let a=0;a<e.length;a++){if(!Ba[a]&&n.buffered&&(Ba[a]={...e[a]}),r.fillStyle=n.baseColor,r.strokeStyle=n.baseColor,r.font=n.baseFont,r.lineWidth=n.baseLineWidth,n.drawPoints)for(let s=0;s<e[a].keypoints.length;s++)r.beginPath(),n.buffered?(Ba[a].keypoints[s].position.x=(Ba[a].keypoints[s].position.x+e[a].keypoints[s].position.x)/2,Ba[a].keypoints[s].position.y=(Ba[a].keypoints[s].position.y+e[a].keypoints[s].position.y)/2,r.arc(Ba[a].keypoints[s].position.x,Ba[a].keypoints[s].position.y,2,0,2*Math.PI)):r.arc(e[a].keypoints[s].position.x,e[a].keypoints[s].position.y,2,0,2*Math.PI),r.fill();if(n.drawPolygons){let s=new Path2D,i,o;i=e[a].keypoints.find(l=>l.part==="leftShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightShoulder"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightHip"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftHip"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftShoulder"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="leftHip"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="leftKnee"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftAnkle"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="rightHip"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightKnee"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightAnkle"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="leftShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="leftElbow"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftWrist"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="rightShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightElbow"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightWrist"),o&&s.lineTo(o.position.x,o.position.y)),r.stroke(s)}}}async function Jae(e,t,n){if(!e)return;let r=t.getContext("2d");r.lineJoin="round";for(let a of e){if(r.font=n.baseFont,r.lineWidth=n.baseLineWidth,n.drawBoxes&&(r.lineWidth=n.baseLineWidth,r.beginPath(),r.strokeStyle=n.baseColor,r.fillStyle=n.baseColor,r.rect(a.box[0],a.box[1],a.box[2],a.box[3]),r.fillStyle="black",r.fillText("hand",a.box[0]+3,1+a.box[1]+n.baseLineHeight,a.box[2]),r.fillStyle=n.baseLabel,r.fillText("hand",a.box[0]+2,0+a.box[1]+n.baseLineHeight,a.box[2]),r.stroke()),n.drawPoints&&a.landmarks&&a.landmarks.length>0)for(let s of a.landmarks)r.fillStyle=n.useDepth?`rgba(${127.5+2*s[2]}, ${127.5-2*s[2]}, 255, 0.5)`:n.baseColor,r.beginPath(),r.arc(s[0],s[1],2,0,2*Math.PI),r.fill();if(n.drawPolygons){let s=i=>{if(!!i)for(let o=0;o<i.length;o++)r.lineWidth=n.baseLineWidth,r.beginPath(),r.strokeStyle=n.useDepth?`rgba(${127.5+2*i[o][2]}, ${127.5-2*i[o][2]}, 255, 0.5)`:n.baseColor,r.moveTo(i[o>0?o-1:0][0],i[o>0?o-1:0][1]),r.lineTo(i[o][0],i[o][1]),r.stroke()};s(a.annotations.indexFinger),s(a.annotations.middleFinger),s(a.annotations.ringFinger),s(a.annotations.pinky),s(a.annotations.thumb)}}}var Bc={face:Kae,body:Zae,hand:Jae,gesture:Xae};var Vc=0,_v=!1,wt={background:"darkslategray",hover:"lightgray",itemBackground:"black",itemColor:"white",buttonBackground:"lightblue",buttonHover:"lightgreen",checkboxOn:"lightgreen",checkboxOff:"lightcoral",rangeBackground:"lightblue",rangeLabel:"white",chartColor:"lightblue"};function Yae(){if(_v)return;let e=`
:root { --rounded: 0.2rem; }
.menu { position: absolute; top: 0rem; right: 0; width: max-content; padding: 0 0.2rem 0 0.2rem; line-height: 1.8rem; z-index: 10;
box-shadow: 0 0 8px dimgrey; background: ${wt.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; }
.menu:hover { box-shadow: 0 0 8px ${wt.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; cursor: default; width: 100%; }
.menu-title { 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: ${wt.itemBackground}; color: ${wt.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: ${wt.buttonBackground}; width: -webkit-fill-available; padding: 8px; margin: 8px; 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: ${wt.buttonHover}; box-shadow: 4px 4px 4px 0 black; }
.menu-button:focus { outline: none; }
.menu-checkbox { width: 2.8rem; height: 1rem; background: ${wt.itemBackground}; margin: 0.5rem 0.5rem 0 0; position: relative; border-radius: var(--rounded); }
.menu-checkbox:after { content: 'OFF'; color: ${wt.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
.menu-checkbox:before { content: 'ON'; color: ${wt.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: ${wt.checkboxOff};
border-radius: var(--rounded); transition: left 0.6s ease; }
input[type=checkbox] { visibility: hidden; }
input[type=checkbox]:checked + label { left: 1.4rem; background: ${wt.checkboxOn}; }
.menu-range { margin: 0.2rem 0.5rem 0 0; width: 3.5rem; background: transparent; color: ${wt.rangeBackground}; }
.menu-range:before { color: ${wt.rangeLabel}; margin: 0 0.4rem 0 0; font-weight: 800; font-size: 0.6rem; position: relative; top: 0.3rem; content: attr(value); }
input[type=range] { -webkit-appearance: none; }
input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 1rem; cursor: pointer; background: ${wt.itemBackground}; border-radius: var(--rounded); border: 1px; }
input[type=range]::-moz-range-track { width: 100%; height: 1rem; cursor: pointer; background: ${wt.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: 1rem; border-radius: var(--rounded); background: ${wt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
input[type=range]::-moz-range-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${wt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
.svg-background { fill:darkslategrey; cursor:pointer; opacity: 0.6; }
.svg-foreground { fill:white; cursor:pointer; opacity: 0.8; }
`,t=document.createElement("style");t.innerHTML=e,document.getElementsByTagName("head")[0].appendChild(t),_v=!0}var bv=class{constructor(t,n,r,a){a&&(wt={...wt,...a}),Yae(),this.createMenu(t,n,r),this.id=0,this.instance=Vc,Vc++,this._maxFPS=0,this.hidden=0}createMenu(t,n="",r={top:null,left:null,bottom:null,right:null}){this.menu=document.createElement("div"),this.menu.id=`menu-${Vc}`,this.menu.className="menu",r&&(r.top&&(this.menu.style.top=r.top),r.bottom&&(this.menu.style.bottom=r.bottom),r.left&&(this.menu.style.left=r.left),r.right&&(this.menu.style.right=r.right)),this.container=document.createElement("div"),this.container.id=`menu-container-${Vc}`,this.container.className="menu-container menu-container-fadein";let a=document.createElement("div");a.className="menu-title",a.id=`menu-title-${Vc}`;let s=`<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>`;n&&(a.innerHTML=`${n}${s}`),this.menu.appendChild(a),a.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),typeof t=="object"?t.appendChild(this.menu):document.getElementById(t).appendChild(this.menu)}get newID(){return this.id++,`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(){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(t){if(this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"),this.container.classList.contains("menu-container-fadein")&&t){let n=t.x||(t.touches&&t.touches[0]?t.touches[0].pageX:null);n&&(this.menu.style.left=`${n-this.menu.offsetWidth/2}px`),this.menu.offsetLeft<0&&(this.menu.style.left=0),this.menu.offsetLeft+this.menu.offsetWidth>window.innerWidth&&(this.menu.style.left=null,this.menu.style.right=0),this.menu.style.borderStyle="solid"}else this.menu.style.borderStyle="none"}addTitle(t){let n=document.createElement("div");return n.className="menu-title",n.id=this.newID,n.innerHTML=t,this.menu.appendChild(n),n.addEventListener("click",()=>{this.hidden=!this.hidden;let r=document.getElementsByClassName("menu");for(let a of r)a.style.display=this.hidden?"none":"block"}),n}addLabel(t){let n=document.createElement("div");return n.className="menu-item menu-label",n.id=this.newID,n.innerHTML=t,this.container.appendChild(n),n}addBool(t,n,r,a){let s=document.createElement("div");return s.className="menu-item",s.innerHTML=`<div class="menu-checkbox"><input class="menu-checkbox" type="checkbox" id="${this.newID}" ${n[r]?"checked":""}/><label class="menu-checkbox-label" for="${this.ID}"></label></div>${t}`,this.container.appendChild(s),s.addEventListener("change",i=>{n[r]=i.target.checked,a&&a(i.target.checked)}),s}async addList(t,n,r,a){let s=document.createElement("div");s.className="menu-item";let i="";for(let o of n)i+=`<option value="${o}" ${o===r?"selected":""}>${o}</option>`;return s.innerHTML=`<div class="menu-list"><select name="${this.ID}" class="menu-list-item">${i}</select><label for="${this.ID}"></label></div>${t}`,s.style.fontFamily=document.body.style.fontFamily,s.style.fontSize=document.body.style.fontSize,s.style.fontVariant=document.body.style.fontVariant,this.container.appendChild(s),s.addEventListener("change",o=>{a&&a(n[o.target.selectedIndex])}),s}addRange(t,n,r,a,s,i,o){let l=document.createElement("div");return l.className="menu-item",l.innerHTML=`<input class="menu-range" type="range" id="${this.newID}" min="${a}" max="${s}" step="${i}" value="${n[r]}">${t}`,this.container.appendChild(l),l.addEventListener("change",c=>{n[r]=parseInt(c.target.value)===parseFloat(c.target.value)?parseInt(c.target.value):parseFloat(c.target.value),c.target.setAttribute("value",c.target.value),o&&o(c.target.value)}),l.input=l.children[0],l}addHTML(t){let n=document.createElement("div");return n.className="menu-item",n.id=this.newID,t&&(n.innerHTML=t),this.container.appendChild(n),n}addButton(t,n,r){let a=document.createElement("button");return a.className="menu-item menu-button",a.style.fontFamily=document.body.style.fontFamily,a.style.fontSize=document.body.style.fontSize,a.style.fontVariant=document.body.style.fontVariant,a.type="button",a.id=this.newID,a.innerText=t,this.container.appendChild(a),a.addEventListener("click",()=>{a.innerText===t?a.innerText=n:a.innerText=t,r&&r(a.innerText!==t)}),a}addValue(t,n,r=""){let a=document.createElement("div");return a.className="menu-item",a.id=`menu-val-${t}`,a.innerText=`${t}: ${n}${r}`,this.container.appendChild(a),a}updateValue(t,n,r=""){let a=document.getElementById(`menu-val-${t}`);a?a.innerText=`${t}: ${n}${r}`:this.addValue(t,n)}addChart(t,n,r=150,a=40,s){s&&(wt.chartColor=s);let i=document.createElement("div");return i.className="menu-item menu-chart-title",i.id=this.newID,i.innerHTML=`<font color=${wt.chartColor}>${t}</font><canvas id="menu-canvas-${n}" class="menu-chart-canvas" width="${r}px" height="${a}px"></canvas>`,this.container.appendChild(i),i}async updateChart(t,n){if(!n||n.length===0)return;let r=document.getElementById(`menu-canvas-${t}`);if(!r)return;let a=r.getContext("2d");a.fillStyle=wt.background,a.fillRect(0,0,r.width,r.height);let s=r.width/n.length,i=1+Math.max(...n),o=r.height/i;for(let l=0;l<n.length;l++){let c=a.createLinearGradient(0,(i-n[l])*o,0,0);c.addColorStop(.1,wt.chartColor),c.addColorStop(.4,wt.background),a.fillStyle=c,a.fillRect(l*s,0,s-4,r.height),a.fillStyle=wt.background,a.font=`${s/1.5}px "Segoe UI"`,a.fillText(Math.round(n[l]),l*s+1,r.height-1,s-1)}}},Uc=bv;var Qae=`
#gl-bench { position: absolute; right: 1rem; bottom: 1rem; z-index:1000; -webkit-user-select: none; -moz-user-select: none; user-select: none; }
#gl-bench div { position: relative; display: block; margin: 4px; padding: 0 7px 0 10px; background: darkslategray; border-radius: 0.2rem; cursor: pointer; opacity: 0.9; }
#gl-bench svg { height: 60px; margin: 0 0px 0px 4px; }
#gl-bench text { font-size: 16px; font-family: 'Lato', 'Segoe UI'; dominant-baseline: middle; text-anchor: middle; }
#gl-bench .gl-mem { font-size: 12px; fill: white; }
#gl-bench .gl-fps { font-size: 13px; fill: white; }
#gl-bench line { stroke-width: 5; stroke: white; stroke-linecap: round; }
#gl-bench polyline { fill: none; stroke: white; stroke-linecap: round; stroke-linejoin: round; stroke-width: 3.5; }
#gl-bench rect { fill: black; }
#gl-bench .opacity { stroke: black; }
`,ese=`
<div class="gl-box">
<svg viewBox="0 0 55 60">
<text x="27" y="56" class="gl-fps">00 FPS</text>
<text x="30" y="8" class="gl-mem"></text>
<rect x="0" y="14" rx="4" ry="4" width="55" height="32"></rect>
<polyline class="gl-chart"></polyline>
</svg>
<svg viewBox="0 0 14 60" class="gl-cpu-svg">
<line x1="7" y1="38" x2="7" y2="11" class="opacity"/>
<line x1="7" y1="38" x2="7" y2="11" class="gl-cpu" stroke-dasharray="0 27"/>
<path d="M5.35 43c-.464 0-.812.377-.812.812v1.16c-.783.1972-1.421.812-1.595 1.624h-1.16c-.435 0-.812.348-.812.812s.348.812.812.812h1.102v1.653H1.812c-.464 0-.812.377-.812.812 0 .464.377.812.812.812h1.131c.1943.783.812 1.392 1.595 1.595v1.131c0 .464.377.812.812.812.464 0 .812-.377.812-.812V53.15h1.653v1.073c0 .464.377.812.812.812.464 0 .812-.377.812-.812v-1.131c.783-.1943 1.392-.812 1.595-1.595h1.131c.464 0 .812-.377.812-.812 0-.464-.377-.812-.812-.812h-1.073V48.22h1.102c.435 0 .812-.348.812-.812s-.348-.812-.812-.812h-1.16c-.1885-.783-.812-1.421-1.595-1.624v-1.131c0-.464-.377-.812-.812-.812-.464 0-.812.377-.812.812v1.073H6.162v-1.073c0-.464-.377-.812-.812-.812zm.58 3.48h2.088c.754 0 1.363.609 1.363 1.363v2.088c0 .754-.609 1.363-1.363 1.363H5.93c-.754 0-1.363-.609-1.363-1.363v-2.088c0-.754.609-1.363 1.363-1.363z" style="fill: grey"></path>
</svg>
<svg viewBox="0 0 14 60" class="gl-gpu-svg">
<line x1="7" y1="38" x2="7" y2="11" class="opacity"/>
<line x1="7" y1="38" x2="7" y2="11" class="gl-gpu" stroke-dasharray="0 27"/>
<path d="M1.94775 43.3772a.736.736 0 10-.00416 1.472c.58535.00231.56465.1288.6348.3197.07015.18975.04933.43585.04933.43585l-.00653.05405v8.671a.736.736 0 101.472 0v-1.4145c.253.09522.52785.1495.81765.1495h5.267c1.2535 0 2.254-.9752 2.254-2.185v-3.105c0-1.2075-1.00625-2.185-2.254-2.185h-5.267c-.28865 0-.5635.05405-.8165.1495.01806-.16445.04209-.598-.1357-1.0787-.22425-.6072-.9499-1.2765-2.0125-1.2765zm2.9095 3.6455c.42435 0 .7659.36225.7659.8119v2.9785c0 .44965-.34155.8119-.7659.8119s-.7659-.36225-.7659-.8119v-2.9785c0-.44965.34155-.8119.7659-.8119zm4.117 0a2.3 2.3 0 012.3 2.3 2.3 2.3 0 01-2.3 2.3 2.3 2.3 0 01-2.3-2.3 2.3 2.3 0 012.3-2.3z" style="fill: grey"></path>
</svg>
</div>
`,vv=class{constructor(t,n={}){this.css=Qae,this.svg=ese,this.paramLogger=()=>{},this.chartLogger=()=>{},this.chartLen=20,this.chartHz=20,this.names=[],this.cpuAccums=[],this.gpuAccums=[],this.activeAccums=[],this.chart=new Array(this.chartLen),this.now=()=>performance&&performance.now?performance.now():Date.now(),this.updateUI=()=>{[].forEach.call(this.nodes["gl-gpu-svg"],o=>o.style.display=this.trackGPU?"inline":"none")},Object.assign(this,n),this.detected=0,this.finished=[],this.isFramebuffer=0,this.frameId=0;let r,a=0,s,i=o=>{++a<20?r=requestAnimationFrame(i):(this.detected=Math.ceil(1e3*a/(o-s)/70),cancelAnimationFrame(r)),s||(s=o)};if(requestAnimationFrame(i),t){let o=async(u,h)=>Promise.resolve(setTimeout(()=>{t.getError();let d=this.now()-u;h.forEach((p,f)=>{p&&(this.gpuAccums[f]+=d)})},0)),l=(u,h,d)=>{let p=h.now();u.apply(d,arguments),h.trackGPU&&h.finished.push(o(p,h.activeAccums.slice(0)))},c="drawElements";t[c]?t[c]=l(t[c],this,t):console.log("bench: cannot attach to webgl 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s=0;s<n+1;s++)this.activeAccums[s]&&(this.cpuAccums[s]+=a);this.activeAccums[n]=!this.activeAccums[n],this.t0=r}},kv=vv;var jr={},se=new wv(jr),ie={baseColor:"rgba(173, 216, 230, 0.3)",baseBackground:"rgba(50, 50, 50, 1)",baseLabel:"rgba(173, 216, 230, 1)",baseFontProto:'small-caps {size} "Segoe UI"',baseLineWidth:12,crop:!0,columns:2,busy:!1,facing:!0,useWorker:!1,worker:"worker.js",samples:["../assets/sample6.jpg","../assets/sample1.jpg","../assets/sample4.jpg","../assets/sample5.jpg","../assets/sample3.jpg","../assets/sample2.jpg"],compare:"../assets/sample-me.jpg",drawBoxes:!0,drawPoints:!1,drawPolygons:!0,fillPolygons:!1,useDepth:!0,console:!0,maxFPSframes:10,modelsPreload:!0,menuWidth:0,menuHeight:0,camera:{},detectFPS:[],drawFPS:[],buffered:!1,drawThread:null,detectThread:null,framesDraw:0,framesDetect:0,bench:!1},xe={},p1,ki,f1={};function tse(...e){if(!Array.isArray(e))return e;let t="";for(let n of e)typeof n=="object"?t+=JSON.stringify(n).replace(/{|}|"|\[|\]/g,"").replace(/,/g,", "):t+=n;return t}function On(...e){let t=new Date,n=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;ie.console&&console.log(n,...e)}function Gn(e){document.getElementById("status").innerText=e}var Ii;async function nse(e){var n,r,a,s;if(document.getElementById("compare-container").style.display=se.config.face.embedding.enabled?"block":"none",!se.config.face.embedding.enabled||((n=e==null?void 0:e.face)==null?void 0:n.length)>0&&((r=e==null?void 0:e.face[0].embedding)==null?void 0:r.length)!==192)return;Ii||(Ii=e,document.getElementById("compare-canvas").getContext("2d").drawImage(Ii.canvas,0,0,200,200));let t=se.simmilarity((a=Ii==null?void 0:Ii.face[0])==null?void 0:a.embedding,(s=e==null?void 0:e.face[0])==null?void 0:s.embedding);document.getElementById("simmilarity").innerText=`simmilarity: ${Math.trunc(1e3*t)/10}%`}var Iv=performance.now();async function m1(e){let t=f1,n=document.getElementById("canvas");ie.drawFPS.push(1e3/(performance.now()-Iv)),ie.drawFPS.length>ie.maxFPSframes&&ie.drawFPS.shift(),Iv=performance.now(),await xe.process.updateChart("FPS",ie.detectFPS),(ie.buffered||!t.canvas)&&(t.canvas=await se.image(e,jr));let r=n.getContext("2d");r.fillStyle=ie.baseBackground,r.fillRect(0,0,n.width,n.height),t.canvas?(t.canvas.width!==n.width&&(n.width=t.canvas.width),t.canvas.height!==n.height&&(n.height=t.canvas.height),r.drawImage(t.canvas,0,0,t.canvas.width,t.canvas.height,0,0,t.canvas.width,t.canvas.height)):r.drawImage(e,0,0,e.width,e.height,0,0,n.width,n.height),await Bc.face(t.face,n,ie,se.facemesh.triangulation),await Bc.body(t.body,n,ie),await Bc.hand(t.hand,n,ie),await Bc.gesture(t.gesture,n,ie),await nse(t);let a=se.tf.engine(),s=a.backendInstance?`gpu: ${(a.backendInstance.numBytesInGPU?a.backendInstance.numBytesInGPU:0).toLocaleString()} bytes`:"",i=`system: ${a.state.numBytes.toLocaleString()} bytes ${s} | tensors: ${a.state.numTensors.toLocaleString()}`,o=t.canvas?`processing: ${t.canvas.width} x ${t.canvas.height}`:"",l=Math.trunc(10*ie.detectFPS.reduce((h,d)=>h+d,0)/ie.detectFPS.length)/10,c=Math.trunc(10*ie.drawFPS.reduce((h,d)=>h+d,0)/ie.drawFPS.length)/10,u=ie.detectFPS.length>5&&l<5?'<font color="lightcoral">warning: your performance is low: try switching to higher performance backend, lowering resolution or disabling some models</font>':"";document.getElementById("log").innerHTML=`
video: ${ie.camera.name} | facing: ${ie.camera.facing} | screen: ${window.innerWidth} x ${window.innerHeight} camera: ${ie.camera.width} x ${ie.camera.height} ${o}<br>
backend: ${se.tf.getBackend()} | ${i}<br>
performance: ${tse(t.performance)}ms FPS process:${l} refresh:${c}<br>
${u}<br>
`,ie.framesDraw++,ie.lastFrame=performance.now(),ie.buffered?ie.drawThread=requestAnimationFrame(()=>m1(e,n)):!ie.buffered&&ie.drawThread&&(On("stopping buffered refresh"),cancelAnimationFrame(ie.drawThread),ie.drawThread=null)}async function A1(){var c;if(ie.busy)return null;ie.busy=!0;let e=document.getElementById("video"),t=document.getElementById("canvas"),n=document.getElementById("log"),r=e.srcObject?e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused:!1,a="";if(Gn("setting up camera"),!navigator.mediaDevices)return a="camera access not supported",n.innerText+=`
${a}`,On(a),Gn(a),ie.busy=!1,a;let s,i={audio:!1,video:{facingMode:ie.facing?"user":"environment",resizeMode:ie.crop?"crop-and-scale":"none"}};window.innerWidth>window.innerHeight?i.video.width={ideal:window.innerWidth}:i.video.height={ideal:window.innerHeight-document.getElementById("menubar").offsetHeight};try{s=await navigator.mediaDevices.getUserMedia(i)}catch(u){return u.name==="PermissionDeniedError"||u.name==="NotAllowedError"?a="camera permission denied":u.name==="SourceUnavailableError"?a="camera not available":a=`camera error: ${u.message||u}`,n.innerText+=`
${a}`,Gn(a),On("camera error:",u),ie.busy=!1,a}if(s)e.srcObject=s;else return ie.busy=!1,"camera stream empty";let o=s.getVideoTracks()[0],l=o.getSettings();return ie.camera={name:(c=o.label)==null?void 0:c.toLowerCase(),width:l.width,height:l.height,facing:l.facingMode==="user"?"front":"back"},new Promise(u=>{e.onloadeddata=async()=>{e.width=e.videoWidth,e.height=e.videoHeight,t.width=e.width,t.height=e.height,t.style.width=t.width>t.height?"100vw":"",t.style.height=t.width>t.height?"":"100vh",ie.menuWidth.input.setAttribute("value",e.width),ie.menuHeight.input.setAttribute("value",e.height);let h=Math.trunc(window.devicePixelRatio*(8+4*t.width/window.innerWidth));ie.baseFont=ie.baseFontProto.replace(/{size}/,`${h}px`),ie.baseLineHeight=h+2,r&&e.play(),r&&!ie.detectThread&&Hc(e,t),ie.busy=!1,Gn(""),u()}})}function Nv(){if(!ki){let e=null;ki=new kv(e,{trackGPU:!1,chartHz:20,chartLen:20}),ki.begin()}}function rse(e,t,n,r){p1||(On("creating worker thread"),p1=new Worker(ie.worker,{type:"module"}),p1.addEventListener("message",a=>{a.data.result.performance&&a.data.result.performance.total&&ie.detectFPS.push(1e3/a.data.result.performance.total),ie.detectFPS.length>ie.maxFPSframes&&ie.detectFPS.shift(),ie.bench&&(ki||Nv(),ki.nextFrame(r)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=ie.bench?"block":"none"),f1=a.data.result,ie.framesDetect++,ie.drawThread||m1(e),ie.detectThread=requestAnimationFrame(s=>Hc(e,n,s))})),p1.postMessage({image:t.data.buffer,width:n.width,height:n.height,userConfig:jr},[t.data.buffer])}function Hc(e,t,n){var a;if(!(e.srcObject&&e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused)&&e.srcObject){ie.drawThread&&cancelAnimationFrame(ie.drawThread),ie.detectThread&&cancelAnimationFrame(ie.detectThread),ie.drawThread=null,ie.detectThread=null,e.paused?On("camera paused"):e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState<=2?setTimeout(()=>Hc(e,t),500):On(`camera not ready: track state: ${(a=e.srcObject)==null?void 0:a.getVideoTracks()[0].readyState} stream state: ${e.readyState}`),clearTimeout(ie.drawThread),ie.drawThread=null,On("frame statistics: process:",ie.framesDetect,"refresh:",ie.framesDraw),On("memory",se.tf.engine().memory());return}if(Gn(""),ie.useWorker){let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(t.width,t.height):document.createElement("canvas");s.width=t.width,s.height=t.height;let i=s.getContext("2d");i.drawImage(e,0,0,e.width,e.height,0,0,t.width,t.height);let o=i.getImageData(0,0,t.width,t.height);rse(e,o,t,jr,n)}else se.detect(e,jr).then(s=>{s.performance&&s.performance.total&&ie.detectFPS.push(1e3/s.performance.total),ie.detectFPS.length>ie.maxFPSframes&&ie.detectFPS.shift(),ie.bench&&(ki||Nv(),ki.nextFrame(n)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=ie.bench?"block":"none"),s.error?(On(s.error),document.getElementById("log").innerText+=`
Human error: ${s.error}`):(f1=s,ie.drawThread||m1(e),ie.framesDetect++,ie.detectThread=requestAnimationFrame(i=>Hc(e,t,i)))})}async function ase(e){return new Promise(t=>{let n=new Image;n.onload=async()=>{On("Processing image:",n.src);let r=document.getElementById("canvas");n.width=n.naturalWidth,n.height=n.naturalHeight,r.width=se.config.filter.width&&se.config.filter.width>0?se.config.filter.width:n.naturalWidth,r.height=se.config.filter.height&&se.config.filter.height>0?se.config.filter.height:n.naturalHeight,f1=await se.detect(n,jr),await m1(n);let s=document.createElement("canvas");s.className="thumbnail",s.width=window.innerWidth/(ie.columns+.1),s.height=r.height/(window.innerWidth/s.width),s.getContext("2d").drawImage(r,0,0,r.width,r.height,0,0,s.width,s.height),document.getElementById("samples-container").appendChild(s),n.src="",t(!0)},n.src=e})}async function Sv(){jr.videoOptimized=!0,document.getElementById("samples-container").style.display="none",document.getElementById("canvas").style.display="block";let e=document.getElementById("video"),t=document.getElementById("canvas");if(e.srcObject!==null&&!e.paused)document.getElementById("play").style.display="block",document.getElementById("btnStart").className="button button-start",document.getElementById("btnStart").innerHTML="start<br>video",Gn("paused"),e.pause();else{let n=await A1();if(n)Gn(n);else{document.getElementById("play").style.display="none";for(let r of Object.values(xe))r.hide();Gn(""),document.getElementById("btnStart").className="button button-stop",document.getElementById("btnStart").innerHTML="pause<br>video",await e.play(),ie.detectThread||Hc(e,t)}}}async function sse(){document.getElementById("play").style.display="none",jr.videoOptimized=!1;let e=Math.trunc(window.devicePixelRatio*(8+4*ie.columns));ie.baseFont=ie.baseFontProto.replace(/{size}/,`${e}px`),ie.baseLineHeight=e+2,document.getElementById("canvas").style.display="none",document.getElementById("samples-container").style.display="block",On("Running detection of sample images"),Gn("processing images"),document.getElementById("samples-container").innerHTML="";for(let t of ie.samples)await ase(t);Gn("")}function ise(){let e=[];window.innerWidth>800?e=[`${document.getElementById("btnDisplay").offsetLeft-50}px`,`${document.getElementById("btnImage").offsetLeft-50}px`,`${document.getElementById("btnProcess").offsetLeft-50}px`,`${document.getElementById("btnModel").offsetLeft-50}px`]:e=["0rem","11rem","21.1rem","33rem"],xe.display=new Uc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[0]}),xe.display.addBool("perf monitor",ie,"bench",t=>ie.bench=t),xe.display.addBool("buffered output",ie,"buffered",t=>ie.buffered=t),xe.display.addBool("crop & scale",ie,"crop",t=>{ie.crop=t,A1()}),xe.display.addBool("camera facing",ie,"facing",t=>{ie.facing=t,A1()}),xe.display.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.display.addBool("use 3D depth",ie,"useDepth"),xe.display.addBool("draw boxes",ie,"drawBoxes"),xe.display.addBool("draw polygons",ie,"drawPolygons"),xe.display.addBool("Fill Polygons",ie,"fillPolygons"),xe.display.addBool("draw points",ie,"drawPoints"),xe.image=new Uc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[1]}),xe.image.addBool("enabled",se.config.filter,"enabled",t=>se.config.filter.enabled=t),ie.menuWidth=xe.image.addRange("image width",se.config.filter,"width",0,3840,10,t=>se.config.filter.width=parseInt(t)),ie.menuHeight=xe.image.addRange("image height",se.config.filter,"height",0,2160,10,t=>se.config.filter.height=parseInt(t)),xe.image.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.image.addRange("brightness",se.config.filter,"brightness",-1,1,.05,t=>se.config.filter.brightness=parseFloat(t)),xe.image.addRange("contrast",se.config.filter,"contrast",-1,1,.05,t=>se.config.filter.contrast=parseFloat(t)),xe.image.addRange("sharpness",se.config.filter,"sharpness",0,1,.05,t=>se.config.filter.sharpness=parseFloat(t)),xe.image.addRange("blur",se.config.filter,"blur",0,20,1,t=>se.config.filter.blur=parseInt(t)),xe.image.addRange("saturation",se.config.filter,"saturation",-1,1,.05,t=>se.config.filter.saturation=parseFloat(t)),xe.image.addRange("hue",se.config.filter,"hue",0,360,5,t=>se.config.filter.hue=parseInt(t)),xe.image.addRange("pixelate",se.config.filter,"pixelate",0,32,1,t=>se.config.filter.pixelate=parseInt(t)),xe.image.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.image.addBool("negative",se.config.filter,"negative",t=>se.config.filter.negative=t),xe.image.addBool("sepia",se.config.filter,"sepia",t=>se.config.filter.sepia=t),xe.image.addBool("vintage",se.config.filter,"vintage",t=>se.config.filter.vintage=t),xe.image.addBool("kodachrome",se.config.filter,"kodachrome",t=>se.config.filter.kodachrome=t),xe.image.addBool("technicolor",se.config.filter,"technicolor",t=>se.config.filter.technicolor=t),xe.image.addBool("polaroid",se.config.filter,"polaroid",t=>se.config.filter.polaroid=t),xe.process=new Uc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[2]}),xe.process.addList("backend",["cpu","webgl","wasm","humangl"],se.config.backend,t=>se.config.backend=t),xe.process.addBool("async operations",se.config,"async",t=>se.config.async=t),xe.process.addBool("enable profiler",se.config,"profile",t=>se.config.profile=t),xe.process.addBool("memory shield",se.config,"deallocate",t=>se.config.deallocate=t),xe.process.addBool("use web worker",ie,"useWorker"),xe.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.process.addLabel("model parameters"),xe.process.addRange("max objects",se.config.face.detector,"maxFaces",1,50,1,t=>{se.config.face.detector.maxFaces=parseInt(t),se.config.body.maxDetections=parseInt(t),se.config.hand.maxHands=parseInt(t)}),xe.process.addRange("skip frames",se.config.face.detector,"skipFrames",0,50,1,t=>{se.config.face.detector.skipFrames=parseInt(t),se.config.face.emotion.skipFrames=parseInt(t),se.config.face.age.skipFrames=parseInt(t),se.config.hand.skipFrames=parseInt(t)}),xe.process.addRange("min confidence",se.config.face.detector,"minConfidence",0,1,.05,t=>{se.config.face.detector.minConfidence=parseFloat(t),se.config.face.gender.minConfidence=parseFloat(t),se.config.face.emotion.minConfidence=parseFloat(t),se.config.hand.minConfidence=parseFloat(t)}),xe.process.addRange("score threshold",se.config.face.detector,"scoreThreshold",.1,1,.05,t=>{se.config.face.detector.scoreThreshold=parseFloat(t),se.config.hand.scoreThreshold=parseFloat(t),se.config.body.scoreThreshold=parseFloat(t)}),xe.process.addRange("overlap",se.config.face.detector,"iouThreshold",.1,1,.05,t=>{se.config.face.detector.iouThreshold=parseFloat(t),se.config.hand.iouThreshold=parseFloat(t)}),xe.process.addBool("detection rotation",se.config.face.detector,"rotation",t=>{se.config.face.detector.rotation=t,se.config.hand.rotation=t}),xe.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.process.addButton("process sample images","process images",()=>sse()),xe.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.process.addChart("FPS","FPS"),xe.models=new Uc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[3]}),xe.models.addBool("face detect",se.config.face,"enabled",t=>se.config.face.enabled=t),xe.models.addBool("face mesh",se.config.face.mesh,"enabled",t=>se.config.face.mesh.enabled=t),xe.models.addBool("face iris",se.config.face.iris,"enabled",t=>se.config.face.iris.enabled=t),xe.models.addBool("face age",se.config.face.age,"enabled",t=>se.config.face.age.enabled=t),xe.models.addBool("face gender",se.config.face.gender,"enabled",t=>se.config.face.gender.enabled=t),xe.models.addBool("face emotion",se.config.face.emotion,"enabled",t=>se.config.face.emotion.enabled=t),xe.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.models.addBool("body pose",se.config.body,"enabled",t=>se.config.body.enabled=t),xe.models.addBool("hand pose",se.config.hand,"enabled",t=>se.config.hand.enabled=t),xe.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.models.addBool("gestures",se.config.gesture,"enabled",t=>se.config.gesture.enabled=t),xe.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),xe.models.addBool("face compare",se.config.face.embedding,"enabled",t=>{se.config.face.embedding.enabled=t,Ii=null}),document.getElementById("btnDisplay").addEventListener("click",t=>xe.display.toggle(t)),document.getElementById("btnImage").addEventListener("click",t=>xe.image.toggle(t)),document.getElementById("btnProcess").addEventListener("click",t=>xe.process.toggle(t)),document.getElementById("btnModel").addEventListener("click",t=>xe.models.toggle(t)),document.getElementById("btnStart").addEventListener("click",()=>Sv()),document.getElementById("play").addEventListener("click",()=>Sv())}async function ose(){On("Demo starting ..."),On("Browser:",navigator==null?void 0:navigator.userAgent),ise(),document.getElementById("log").innerText=`Human: version ${se.version}`,ie.modelsPreload&&!ie.useWorker&&(Gn("loading"),await se.load(jr)),ie.useWorker||(Gn("initializing"),await se.warmup(jr)),Gn("human: ready"),document.getElementById("loader").style.display="none",document.getElementById("play").style.display="block",On("Demo ready...")}window.onload=ose;window.onresize=A1;
/**
* @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
*
* 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 2021 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. */
//# sourceMappingURL=demo-browser-index.js.map
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