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className(){return"Adagrad"}constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=L.registeredVariables[t];this.accumulatedGrads[a]==null&&(this.accumulatedGrads[a]={originalName:`${t}/accumulator`,variable:Pe(()=>lr(n.shape,this.initialAccumulatorValue).variable(!1))});let r=Array.isArray(e)?e[a].tensor:e[t];if(r==null)return;let s=this.accumulatedGrads[a].variable;Pe(()=>{let i=we(s,En(r));s.assign(i);let o=we(te(ve(r,nr(we(i,L.backend.epsilon()))),-this.learningRate),n);n.assign(o)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&J(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(a=>({originalName:a.name,variable:a.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}},o3=class extends _s{static get className(){return"Adam"}constructor(e,t,a,n=null){super(),this.learningRate=e,this.beta1=t,this.beta2=a,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],Pe(()=>{this.accBeta1=Ge(t).variable(),this.accBeta2=Ge(a).variable()}),n==null&&(this.epsilon=L.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(a=>a.name):Object.keys(e);Pe(()=>{let a=xe(1,this.accBeta1),n=xe(1,this.accBeta2);t.forEach((r,s)=>{let i=L.registeredVariables[r],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${r}/m`,variable:Pe(()=>en(i).variable(o))}),this.accumulatedSecondMoment[s]==null&&(this.accumulatedSecondMoment[s]={originalName:`${r}/v`,variable:Pe(()=>en(i).variable(o))});let l=Array.isArray(e)?e[s].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[s].variable,d=this.accumulatedSecondMoment[s].variable,c=we(te(u,this.beta1),te(l,1-this.beta1)),p=we(te(d,this.beta2),te(En(l),1-this.beta2)),h=ve(c,a),m=ve(p,n);u.assign(c),d.assign(p);let f=we(te(ve(h,we(nr(m),this.epsilon)),-this.learningRate),i);i.assign(f)}),this.accBeta1.assign(te(this.accBeta1,this.beta1)),this.accBeta2.assign(te(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&J(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&J(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),Pe(()=>{this.accBeta1.assign(tu(this.beta1,this.iterations_+1)),this.accBeta2.assign(tu(this.beta2,this.iterations_+1))});let t=e.length/2,a=!1;this.accumulatedFirstMoment=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(a)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(a)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}},l3=class extends _s{static get className(){return"Adamax"}constructor(e,t,a,n=null,r=0){super(),this.learningRate=e,this.beta1=t,this.beta2=a,this.epsilon=n,this.decay=r,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],Pe(()=>{this.iteration=Ge(0).variable(),this.accBeta1=Ge(t).variable()}),n==null&&(this.epsilon=L.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(a=>a.name):Object.keys(e);Pe(()=>{let a=xe(1,this.accBeta1),n=ve(-this.learningRate,we(te(this.iteration,this.decay),1));t.forEach((r,s)=>{let 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}},i0=class extends _s{static get className(){return"SGD"}constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,a)=>{let n=Array.isArray(e)?e[a].tensor:e[t];if(n==null)return;let r=L.registeredVariables[t];Pe(()=>{let s=we(te(this.c,n),r);r.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Bn(Ge(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer 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r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a),o=k("includeBatchInIndex",e,t,a),{result:l,indexes:u}=n.maxPoolWithArgmax(k("x",e,t,a),[i[1],i[2]],[r[1],r[2]],s,o);return[l,u]}case"AvgPool3D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.avgPool3d(k("x",e,t,a),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"MaxPool3D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("kernelSize",e,t,a);return[n.maxPool3d(k("x",e,t,a),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"Dilation2D":{let r=k("strides",e,t,a),s=k("pad",e,t,a),i=k("dilations",e,t,a),o=r[1],l=r[2],u=i[1],d=i[2];return[n.dilation2d(k("x",e,t,a),k("filter",e,t,a),[o,l],s,[u,d],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},nz=(e,t,a,n=ta)=>{switch(e.op){case"Fill":{let r=k("shape",e,t,a),s=k("dtype",e,t,a),i=k("value",e,t,a);return[n.fill(r,i,s)]}case"LinSpace":{let r=k("start",e,t,a),s=k("stop",e,t,a),i=k("num",e,t,a);return[n.linspace(r,s,i)]}case"Multinomial":{let 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TypeError(`Node type ${e.op} is not implemented`)}},cz=(e,t,a,n=ta)=>{switch(e.op){case"EuclideanNorm":return[n.euclideanNorm(k("x",e,t,a),k("axis",e,t,a),k("keepDims",e,t,a))];case"FusedBatchNorm":case"FusedBatchNormV2":return[n.batchNorm(k("x",e,t,a),k("mean",e,t,a),k("variance",e,t,a),k("offset",e,t,a),k("scale",e,t,a),k("epsilon",e,t,a))];case"FusedBatchNormV3":return[n.batchNorm(k("x",e,t,a),k("mean",e,t,a),k("variance",e,t,a),k("offset",e,t,a),k("scale",e,t,a),k("epsilon",e,t,a))];case"LRN":return[n.localResponseNormalization(k("x",e,t,a),k("radius",e,t,a),k("bias",e,t,a),k("alpha",e,t,a),k("beta",e,t,a))];case"Softmax":return[n.softmax(k("x",e,t,a))];case"LogSoftmax":return[n.logSoftmax(k("x",e,t,a))];default:throw TypeError(`Node type ${e.op} is not 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s=((i,o,l)=>{switch(i.category){case"arithmetic":return r(()=>XO(i,o,l));case"basic_math":return r(()=>KO(i,o,l));case"control":return tz(i,o,l);case"convolution":return r(()=>az(i,o,l));case"creation":return r(()=>nz(i,o,l));case"dynamic":return rz(i,o,l);case"evaluation":return r(()=>sz(i,o,l));case"image":return r(()=>uz(i,o,l));case"graph":return r(()=>iz(i,o,l));case"logical":return r(()=>dz(i,o,l));case"matrices":return r(()=>pz(i,o,l));case"normalization":return r(()=>cz(i,o,l));case"ragged":return r(()=>hz(i,o,l));case"reduction":return r(()=>mz(i,o,l));case"slice_join":return r(()=>fz(i,o,l));case"sparse":return r(()=>gz(i,o,l));case"spectral":return r(()=>yz(i,o,l));case"string":return r(()=>xz(i,o,l));case"transformation":return r(()=>Az(i,o,l));case"hash_table":return lz(i,o,l,n);case"custom":let u=l6(i.op);if(u&&u.customExecutor)return u.customExecutor(new qO(i,o,l));throw TypeError(`Custom op ${i.op} is not registered.`);default:throw TypeError(`Unknown op '${i.op}'. 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Map(g.map(y=>[y.name,y])).values()]}let l=o([...r,...e.weights,...s]).filter(i),u=o([...l,...Object.values(e.nodes)]).filter(i),d=new Map(u.map(g=>[g.name,g])),c={};for(let g of u){c[g.name]=c[g.name]||0;for(let y of g.children)i(y)||(c[y.name]=Number.POSITIVE_INFINITY),c[y.name]=(c[y.name]||0)+1}let p=Object.entries(c).filter(([,g])=>g===0).map(([g])=>g),h=[...p];for(;p.length>0;){let g=p.pop(),y=d.get(g);for(let x of y.children.filter(i))--c[x.name]===0&&(h.push(x.name),p.push(x.name))}let m=h.map(g=>d.get(g)),f=vz(m,l);return wz(f,l),f}function vz(e,t){let a=new Map(e.map(s=>[s.name,s])),n=t.map(s=>s.name),r=new Set(n);for(;n.length>0;){let s=n.pop(),i=a.get(s);for(let o of i.children)!a.has(o.name)||r.has(o.name)||(r.add(o.name),n.push(o.name))}return e.filter(s=>r.has(s.name))}var th=class extends Error{constructor(e){super(`NodesExecutionOrderError: ${e}`)}};function wz(e,t){let a=new Map(e.map((o,l)=>[o.name,l])),n=new Set(t.map(o=>o.name)),r=o=>n.has(typeof o=="string"?o:o.name),s=new Set(e.map(o=>o.name)),i=o=>s.has(typeof o=="string"?o:o.name);for(let o of e){for(let l of o.children.filter(i)){if(!a.has(l.name))throw new th(`Child ${l.name} of node ${o.name} is unreachable.`);if(a.get(o.name)>a.get(l.name))throw new th(`Node ${o.name} is scheduled to run after its child ${l.name}.`)}if(!r(o))for(let l of o.inputs){if(!a.has(l.name))throw new th(`Input ${l.name} of node ${o.name} is unreachable.`);if(a.get(l.name)>a.get(o.name))throw new th(`Node ${o.name} is scheduled to run before its input ${l.name}.`)}}}function kz(e){let t=new Map(e.map((o,l)=>[o.name,l])),a=Number.MAX_SAFE_INTEGER,n=e.map((o,l)=>mi(o)?a:l),r=o=>{let l=n[t.get(o.name)];return l==null?-1:l},s=e.map((o,l)=>o.children.map(r).reduce((u,d)=>Math.max(u,d),n[l])),i=new Map;for(let o=0;ot[n].map(r=>r.id));this._weightIds=[].concat(...a),this._weightMap=t}set resourceManager(t){this._resourceManager=t}get inputs(){return this._inputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(t=>t.signatureKey||t.name)}get outputNodes(){return this._outputs.map(t=>{let a=t.signatureKey||t.name;return t.defaultOutput?`${a}:${t.defaultOutput}`:a})}get functions(){return Object.keys(this._functions).reduce((t,a)=>(t[a]=this._functions[a].signature,t),{})}constructor(t,a){this.graph=t,this.parent=a,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=t.outputs,this._inputs=t.inputs,this._initNodes=t.initNodes,this._signature=t.signature,this._functions=t.functions,t.functions!=null&&Object.keys(t.functions).forEach(n=>{this._functionExecutorMap[n]=new E6(t.functions[n],this)})}getCompilationKey(t,a){let n=t.map(s=>s.name).sort(),r=a.map(s=>s.name).sort();return n.join(this.SEPARATOR)+"--"+r.join(this.SEPARATOR)}compile(t,a){let n=N5(t,a,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:s,syncInputs:i}=n;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. 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d}processChildNodes(t,a,n,r,s,i){t.children.forEach(o=>{let[l]=kr(o.name,n);s[l]||!i.has(o.name)||(o.op==="Merge"?o.inputNames.some(u=>!!da(u,r,n))&&(s[l]=!0,a.push({contexts:n.currentContext,node:o})):o.inputNames.every(u=>!!da(u,r,n))&&(s[l]=!0,a.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(t=>this.weightMap[t].forEach(a=>a.dispose()))}checkInputShapeAndType(t){Object.keys(t).forEach(a=>{let n=t[a],[r]=Za(a),s=this.graph.nodes[r];if(s.attrParams.shape&&s.attrParams.shape.value){let i=s.attrParams.shape.value,o=i.length===n.shape.length&&n.shape.every((l,u)=>i[u]===-1||i[u]===l);v.assert(o,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${i}], but was [${n.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&v.assert(n.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(t){var a,n;let r={};for(let s in t){let i=(n=(a=this._signature)===null||a===void 0?void 0:a.inputs)===null||n===void 0?void 0:n[s];i!=null?r[i.name]=t[s]:r[s]=t[s]}return r}checkInputs(t){let a=Object.keys(t).filter(n=>{let[r]=Za(n);return this.graph.nodes[r]==null});if(a.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${a}] that are not part of graph`)}mapOutputs(t){return t.map(a=>{var n,r;let s=(r=(n=this._signature)===null||n===void 0?void 0:n.outputs)===null||r===void 0?void 0:r[a];return s!=null?s.name:a},{})}checkOutputs(t){t.forEach(a=>{let[n]=Za(a);if(!this.graph.nodes[n])throw new Error(`The output '${a}' is not found in the graph`)})}},Rz=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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yW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n;Ie(r,"argMin");let i=v.parseAxisParam(s,r.shape),o=I.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Va({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=I.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],I.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[d,c]=I.computeOutAndReduceShapes(l.shape,i),p=v.sizeFromShape(d),h=v.makeZerosTypedArray(p,"int32"),m=v.sizeFromShape(c),f=a.data.get(l.dataId).values;for(let g=0;ga.disposeIntermediateTensorInfo(g)),a.makeTensorInfo(d,"int32",h)}var xW={kernelName:mu,backendName:"cpu",kernelFunc:yW},AW=ct(zi,e=>Math.asin(e)),bW={kernelName:zi,backendName:"cpu",kernelFunc:AW},vW=ct(Li,e=>Math.asinh(e)),wW={kernelName:Li,backendName:"cpu",kernelFunc:vW},kW=ct(Wi,e=>Math.atan(e)),IW={kernelName:Wi,backendName:"cpu",kernelFunc:kW},SW=Pt((e,t)=>Math.atan2(e,t)),TW=Kt(Vi,SW),CW={kernelName:Vi,backendName:"cpu",kernelFunc:TW},NW=ct(Bi,e=>Math.atanh(e)),RW={kernelName:Bi,backendName:"cpu",kernelFunc:NW};function $3(e,t,a,n,r,s){let i=r.strideHeight,o=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,d=r.effectiveFilterHeight,c=r.effectiveFilterWidth,p=r.padInfo.top,h=r.padInfo.left,m=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=Te(r.outShape,a),g=f.values,y=r.outShape[1]*r.outShape[2]*r.outShape[3],x=r.outShape[2]*r.outShape[3],A=r.outShape[3];for(let b=0;bU?U=ee:s==="avg"&&(G+=ee,q++)}if(isNaN(U))break}let H=T+D*A+C;g[H]=s==="avg"?G/q:U}}}return f}function Sv(e,t,a,n,r=!1,s=!1){let i=Te(n.outShape,"int32"),o=n.strideHeight,l=n.strideWidth,u=n.dilationHeight,d=n.dilationWidth,c=n.effectiveFilterHeight,p=n.effectiveFilterWidth,h=n.padInfo.top,m=n.padInfo.left,f=Te(t,a,e);for(let g=0;gF&&(F=$,r?E=s?((g*n.inHeight+T)*n.inWidth+O)*n.inChannels+y:(T*n.inWidth+O)*n.inChannels+y:E=D*p+W)}}i.set(E,g,x,S,y)}}return i}function Tv(e,t,a,n,r,s){let i=r.strideDepth,o=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,d=r.dilationHeight,c=r.dilationWidth,p=r.effectiveFilterDepth,h=r.effectiveFilterHeight,m=r.effectiveFilterWidth,f=r.padInfo.front,g=r.padInfo.top,y=r.padInfo.left,x=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,A=Te(r.outShape,a),b=A.values,w=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],S=r.outShape[2]*r.outShape[3]*r.outShape[4],C=r.outShape[3]*r.outShape[4],N=r.outShape[4];for(let M=0;Mbe?be=xt:s==="avg"&&(Ce+=xt,Ee++),isNaN(be))break}if(isNaN(be))break}if(isNaN(be))break}let Le=ie+T;b[Le]=s==="avg"?Ce/Math.max(Ee,1):be}}}}return 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OW(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;Ie([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,d=I.computePool2DInfo(i.shape,o,l,1,u),c=d.strideHeight,p=d.strideWidth,h=d.filterHeight,m=d.filterWidth,f=d.dilationHeight,g=d.dilationWidth,y=d.effectiveFilterHeight,x=d.effectiveFilterWidth,A=x-1-d.padInfo.left,b=y-1-d.padInfo.top,w=Te(i.shape,"float32"),S=1/(h*m),C=a.data.get(r.dataId).values,N=Te(r.shape,"float32",C);for(let M=0;M=d.outHeight||Math.floor(U)!==U))for(let G=0;G=d.outWidth||Math.floor(q)!==q)continue;let H=N.get(M,U,q,F);W+=H}}w.set(W*S,M,E,T,F)}return a.makeTensorInfo(w.shape,w.dtype,w.values)}var zW={kernelName:gp,backendName:"cpu",kernelFunc:OW};function LW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,scale:s,offset:i,mean:o,variance:l}=t;v.assert(o.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(s==null||o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),Ie([r,o,l,s,i],"batchNorm");let{varianceEpsilon:u}=n;u==null&&(u=.001);let d=a.data.get(r.dataId).values,c=a.data.get(o.dataId).values,p=a.data.get(l.dataId).values,h=s?a.data.get(s.dataId).values:new Float32Array([1]),m=i?a.data.get(i.dataId).values:new Float32Array([0]),f=new Float32Array(d.length),g=m.length,y=h.length,x=p.length,A=c.length,b=0,w=0,S=0,C=0;for(let N=0;N=g&&(b=0),w>=A&&(w=0),S>=y&&(S=0),C>=x&&(C=0);return a.makeTensorInfo(r.shape,r.dtype,f)}var WW={kernelName:po,backendName:"cpu",kernelFunc:LW};function BW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;Ie([r],"batchToSpaceND");let o=s.reduce((y,x)=>y*x),l=I.getReshaped(r.shape,s,o),u=I.getPermuted(l.length,s.length),d=I.getReshapedPermuted(r.shape,s,o),c=I.getSliceBeginCoords(i,s.length),p=I.getSliceSize(d,i,s.length),h=bt({inputs:{x:r},backend:a,attrs:{shape:l}}),m=Va({inputs:{x:h},backend:a,attrs:{perm:u}}),f=bt({inputs:{x:m},backend:a,attrs:{shape:d}}),g=Ci({inputs:{x:f},backend:a,attrs:{begin:c,size:p}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),g}var VW={kernelName:gu,backendName:"cpu",kernelFunc:BW};function UW(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=a.data.get(r.dataId).values,l=a.data.get(s.dataId).values,u=w3(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var GW={kernelName:Hi,backendName:"cpu",kernelFunc:UW};function HW(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.data.get(n.dataId).values,i=a.data.get(r.dataId).values,o=I.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var jW={kernelName:yu,backendName:"cpu",kernelFunc:HW},qW=ct(hs,(e,t)=>{let a=t;return e>a.clipValueMax?a.clipValueMax:e{let{x:t}=e.inputs,a=e.backend,n=new Float32Array(v.sizeFromShape(t.shape)),r=a.data.get(t.dataId),s=r.complexTensorInfos.real,i=r.complexTensorInfos.imag,o=a.data.get(s.dataId).values,l=a.data.get(i.dataId).values;for(let u=0;uf.shape);I.assertParamsConsistent(i,s);let o=I.computeOutShape(t.map(f=>f.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(f=>v.sizeFromShape(f.shape)>0);if(l.length===1)return sr({inputs:{x:l[0]},backend:a});if(l[0].dtype==="complex64"){let f=l.map(b=>Ti({inputs:{input:b},backend:a})),g=l.map(b=>iu({inputs:{input:b},backend:a})),y=ou({inputs:f,backend:a,attrs:{axis:s}}),x=ou({inputs:g,backend:a,attrs:{axis:s}}),A=Qa({inputs:{real:y,imag:x},backend:a});return f.forEach(b=>a.disposeIntermediateTensorInfo(b)),g.forEach(b=>a.disposeIntermediateTensorInfo(b)),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(x),A}let u=l.map(f=>{let g=[-1,v.sizeFromShape(f.shape.slice(s))];return bt({inputs:{x:f},backend:a,attrs:{shape:g}})}),d=u.map(f=>({vals:a.data.get(f.dataId).values,shape:f.shape}));o=I.computeOutShape(u.map(f=>f.shape),1);let c=u[0].shape[0]===1,p=k3(d,o,t[0].dtype,c),h=I.computeOutShape(l.map(f=>f.shape),s),m=a.makeTensorInfo(h,t[0].dtype,p);return u.forEach(f=>a.disposeIntermediateTensorInfo(f)),m}var JW={kernelName:xu,backendName:"cpu",kernelFunc:ou};function Cv(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:d}=n;Ie([r,s],"conv2d");let c=I.convertConv2DDataFormat(l),p=I.computeConv2DInfo(r.shape,s.shape,i,u,o,d,!1,c),h=p.filterHeight,m=p.filterWidth,f=p.dilationHeight,g=p.dilationWidth,y=p.padInfo.left,x=p.padInfo.top,A=p.dataFormat==="channelsLast",b=new Rt(p.outShape,r.dtype),w=v.computeStrides(r.shape),S=v.computeStrides(s.shape),C=w[0],N=A?w[1]:w[2],M=A?w[2]:1,F=A?1:w[1],E=b.strides[0],T=A?b.strides[1]:b.strides[2],D=A?b.strides[2]:1,O=A?1:b.strides[1],W=a.data.get(r.dataId).values,$=a.data.get(s.dataId).values,U=b.values;for(let G=0;G=p.inHeight)continue;let ge=re*S[0],ie=q+ee*N;for(let be=0;be=p.inWidth)continue;let gt=ge+Le*S[1],dt=ie+qe*M,st=gt;for(let it=0;it=u.inDepth)continue;let G=$*M[0],q=E+U*N[1];for(let H=0;H=u.inHeight)continue;let ee=G+X*M[1],ge=q+re*N[2];for(let ie=0;ie=u.inWidth)continue;let qe=ee+Ee*M[2],gt=ge+Le*u.inChannels,dt=qe;for(let st=0;stMath.cos(e)),pB={kernelName:Ji,backendName:"cpu",kernelFunc:dB},cB=ct(Qi,e=>Math.cosh(e)),hB={kernelName:Qi,backendName:"cpu",kernelFunc:cB};function mB(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,[d,c,p,h]=r.shape,m=s.shape[0],[f,g]=o,y=Te([m,f,g,h],"float32"),x=a.data.get(s.dataId).values,A=a.data.get(i.dataId).values,b=a.data.get(r.dataId).values,w=v.computeStrides(r.shape),S=v.computeStrides(y.shape);for(let C=0;C=d)continue;let O=f>1?(E-M)*(c-1)/(f-1):0,W=g>1?(T-F)*(p-1)/(g-1):0;for(let $=0;$1?M*(c-1)+$*O:.5*(M+E)*(c-1);if(U<0||U>c-1){for(let G=0;G1?F*(p-1)+V*W:.5*(F+T)*(p-1);if(Z<0||Z>p-1){for(let ge=0;ge1?F*(p-1)+G*W:.5*(F+T)*(p-1);if(q<0||q>p-1){for(let Z=0;Zy+m-x-1:(y,x)=>y+x;for(let y=0;yy+m-x-1:(y,x)=>y+x;for(let y=0;y`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${i}`);let o=r.shape[0],l=r.shape[1],u=r.shape[2],d=r.shape[3],c=l*s,p=u*s,h=d/(s*s),m=a.data.get(r.dataId).values,f=new Float32Array(o*c*p*h),g=0;for(let y=0;y`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let h=I.computeConv2DInfo(r.shape,s.shape,i,p,o,u,!0),{filterHeight:m,filterWidth:f,dilationHeight:g,dilationWidth:y,padInfo:x}=h,A=x.left,b=x.top,w=h.outChannels/h.inChannels,S=new Rt(h.outShape,r.dtype),C=a.data.get(r.dataId).values,N=a.data.get(s.dataId).values,M=S.values;for(let F=0;F=h.inHeight)continue;let G=$*c[0],q=E+U*d[1];for(let H=0;H=h.inWidth)continue;let ee=G+X*c[1],ge=q+re*h.inChannels,ie=V,be=ee;for(let Ce=0;Ce{let{x:n,filter:r}=e,{strides:s,pad:i,dilations:o}=a,l=t,u=l.data.get(n.dataId).values,d=n.shape.length,c=l.data.get(r.dataId).values,p=r.shape.length,{batchSize:h,inHeight:m,inWidth:f,inChannels:g,outHeight:y,outWidth:x,padInfo:A,strideHeight:b,strideWidth:w,filterHeight:S,filterWidth:C,dilationHeight:N,dilationWidth:M,outShape:F}=I.computeDilation2DInfo(n.shape,r.shape,s,i,"NHWC",o),E=v.sizeFromShape(F),T=F.length,D=v.getArrayFromDType(n.dtype,E);for(let O=0;O=0&&X=0&&eeH&&(H=be)}}}let V=v.locToIndex([O,W,U,q],T,v.computeStrides(F));D[V]=H}}}return{dataId:l.write(v.toTypedArray(D,n.dtype),F,n.dtype),shape:F,dtype:n.dtype}}},FB={kernelName:Ql,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:a})=>{let{x:n,filter:r,dy:s}=e,{strides:i,pad:o,dilations:l}=a,u=t,d=v.toNestedArray(n.shape,u.data.get(n.dataId).values),c=v.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:p,inHeight:h,inWidth:m,inChannels:f,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:w,filterWidth:S,dilationHeight:C,dilationWidth:N,outShape:M}=I.computeDilation2DInfo(n.shape,r.shape,i,o,"NHWC",l);v.assert(s.rank===M.length,()=>`Error in ${Ql}, dy must have the same rank as output ${M.length}, but got ${s.rank}`);let F=v.toNestedArray(M,u.data.get(s.dataId).values),E=v.makeZerosNestedTypedArray(r.shape,r.dtype);for(let T=0;T=0&&Z=0&&reG&&(G=ee,q=V,H=X)}}}E[q][H][U]+=F[T][D][W][U]}}}return{dataId:u.write(v.toTypedArray(E,n.dtype),r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},$B={kernelName:Jl,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:a})=>{let{x:n,filter:r,dy:s}=e,{strides:i,pad:o,dilations:l}=a,u=t,d=v.toNestedArray(n.shape,u.data.get(n.dataId).values),c=v.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:p,inHeight:h,inWidth:m,inChannels:f,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:w,filterWidth:S,dilationHeight:C,dilationWidth:N,outShape:M}=I.computeDilation2DInfo(n.shape,r.shape,i,o,"NHWC",l);v.assert(s.rank===M.length,()=>`Error in ${Jl}, dy must have the same rank as output ${M.length}, but got ${s.rank}`);let F=v.toNestedArray(M,u.data.get(s.dataId).values),E=v.makeZerosNestedTypedArray(n.shape,n.dtype);for(let T=0;T=0&&Z=0&&reG&&(G=ee,q=Z,H=re)}}}E[T][q][H][U]+=F[T][D][W][U]}}}return{dataId:u.write(v.toTypedArray(E,n.dtype),n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}};function DB(e){let{inputs:t,backend:a,attrs:n}=e,{image:r}=t,{canvas:s,options:i}=n,{contextOptions:o,imageOptions:l}=i||{},u=(l==null?void 0:l.alpha)||1,d=(o==null?void 0:o.contextType)||"2d";if(d!=="2d")throw new Error(`Context type ${o.contextType} is not supported by the CPU backend.`);let c=s.getContext(d,(o==null?void 0:o.contextAttributes)||{});if(c==null)throw new Error(`Could not get the context with ${d} type.`);let[p,h]=r.shape.slice(0,2),m=r.shape.length===2?1:r.shape[2],f=a.data.get(r.dataId).values,g=r.dtype==="float32"?255:1,y=new Uint8ClampedArray(h*p*4);for(let A=0;A1)throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${C}.`)}else if(r.dtype==="int32"&&(C<0||C>255))throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${C}.`);m===1?(b[0]=C*g,b[1]=C*g,b[2]=C*g):b[S]=C*g}let w=A*4;y[w+0]=Math.round(b[0]),y[w+1]=Math.round(b[1]),y[w+2]=Math.round(b[2]),y[w+3]=Math.round(b[3])}s.width=h,s.height=p;let x=new ImageData(y,h,p);return c.putImageData(x,0,0),r}var PB={kernelName:kp,backendName:"cpu",kernelFunc:DB};function tc(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"sum");let o;r.dtype==="bool"?o=ds({inputs:{x:r},backend:a,attrs:{dtype:"int32"}}):o=sr({inputs:{x:r},backend:a});let l=o.shape.length,u=v.parseAxisParam(s,o.shape),d=I.getAxesPermutation(u,l),c=u,p=o;d!=null&&(p=Va({inputs:{x:o},backend:a,attrs:{perm:d}}),c=I.getInnerMostAxes(c.length,l)),I.assertAxesAreInnerMostDims("sum",c,p.shape.length);let[h,m]=I.computeOutAndReduceShapes(p.shape,c),f=I.upcastType(p.dtype,"int32"),g=Ih(a,h,f),y=v.sizeFromShape(m),x=a.data.get(g.dataId).values,A=a.data.get(p.dataId).values;for(let b=0;b=0&&(p=tc({inputs:{x:p},backend:a,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(p)),h--)}for(let f of m)f!==p&&a.disposeIntermediateTensorInfo(f);return p}var zB={kernelName:Ip,backendName:"cpu",kernelFunc:OB};function LB(e){let{inputs:t,backend:a}=e,{dy:n,y:r}=t;Ie([n,r],"eluGrad");let s=new Float32Array(v.sizeFromShape(r.shape)),i=a.data.get(r.dataId).values,o=a.data.get(n.dataId).values;for(let l=0;l=0?s[l]=o[l]:s[l]=o[l]*(u+1)}return a.makeTensorInfo(r.shape,"float32",s)}var WB={kernelName:wu,backendName:"cpu",kernelFunc:LB},BB=I.ERF_P,VB=I.ERF_A1,UB=I.ERF_A2,GB=I.ERF_A3,HB=I.ERF_A4,jB=I.ERF_A5,qB=ct(lo,e=>{let t=Math.sign(e),a=Math.abs(e),n=1/(1+BB*a);return t*(1-((((jB*n+HB)*n+GB)*n+UB)*n+VB)*n*Math.exp(-a*a))}),XB={kernelName:lo,backendName:"cpu",kernelFunc:qB};function Ch(e){let{inputs:t,backend:a,attrs:n}=e,{input:r}=t,{dim:s}=n,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),bt({inputs:{x:r},backend:a,attrs:{shape:o}})}var KB={kernelName:ku,backendName:"cpu",kernelFunc:Ch},YB=Pt((e,t)=>e/t),D3=Kt(io,YB),L1={kernelName:io,backendName:"cpu",kernelFunc:D3};function Rv(e,t,a){let n=e.shape,r=n[0],s=n[1],i=a.data.get(e.dataId),o=i.complexTensorInfos.real,l=i.complexTensorInfos.imag,u=[r,s],d=v.sizeFromShape(u),c=v.getTypedArrayFromDType("float32",d),p=v.getTypedArrayFromDType("float32",d);for(let g=0;g{let{image:n}=e,r=a,s=v.getTypedArrayFromDType(n.dtype,v.sizeFromShape(n.shape)),[i,o,l,u]=n.shape,d=r.data.get(n.dataId).values;for(let c=0;c=0&&x=0,()=>`GatherV2: the index value ${w} is not in [0, ${d-1}]`)}let c=o;o==null&&(c=0);let p=v.sizeFromShape(s.shape),h=I.segment_util.collectGatherOpShapeInfo(r,s,l,c),m=bt({inputs:{x:r},backend:a,attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]}}),f=bt({inputs:{x:s},backend:a,attrs:{shape:[h.batchSize,p/h.batchSize]}}),g=[h.batchSize,h.outerSize,p/h.batchSize,h.sliceSize],y=a.bufferSync(f),x=a.bufferSync(m),A=j6(x,y,g);return a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),a.makeTensorInfo(h.outputShape,A.dtype,A.values)}var cV={kernelName:Su,backendName:"cpu",kernelFunc:pV};function hV(e){let{inputs:t,backend:a}=e,{input:n}=t,r=v.sizeFromShape(n.shape),s=n.shape[n.shape.length-1],i=r/s,o=bt({inputs:{x:n},backend:a,attrs:{shape:[i,s]}}),l=Rv(o,!0,a),u=bt({inputs:{x:l},backend:a,attrs:{shape:n.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(l),u}var mV={kernelName:Tp,backendName:"cpu",kernelFunc:hV},fV=ct(mo,e=>Number.isFinite(e)?1:0,"bool"),gV={kernelName:mo,backendName:"cpu",kernelFunc:fV},yV=ct(fo,e=>Math.abs(e)===1/0?1:0,"bool"),xV={kernelName:fo,backendName:"cpu",kernelFunc:yV},AV=ct(go,e=>Number.isNaN(e)?1:0,"bool"),bV={kernelName:go,backendName:"cpu",kernelFunc:AV};function vV(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=Z6(n,r,s);return t.makeTensorInfo([i.length],"float32",i)}var wV={kernelName:xo,backendName:"cpu",kernelFunc:vV},kV=ct(Ao,e=>Math.log1p(e)),IV={kernelName:Ao,backendName:"cpu",kernelFunc:kV},SV=Pt((e,t)=>e&&t),TV=Kt(bo,SV,null,"bool"),CV={kernelName:bo,backendName:"cpu",kernelFunc:TV},NV=ct(vo,e=>e?0:1,"bool"),RV={kernelName:vo,backendName:"cpu",kernelFunc:NV},EV=Pt((e,t)=>e||t),MV=Kt(wo,EV,null,"bool"),FV={kernelName:wo,backendName:"cpu",kernelFunc:MV};function $V(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;Ie(r,"LRN");let u=r.shape[3],d=u-1,c=a.data.get(r.dataId).values,p=v.sizeFromShape(r.shape),h=new Float32Array(p);function m(f){let g=f%u,y=f-g+Math.max(0,g-s),x=f-g+Math.min(g+s,d),A=0;for(;y<=x;y++){let b=c[y];A+=b*b}return A}for(let f=0;f`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let d=I.computePool2DInfo(r.shape,s,i,u,o,l),c;if(d.filterWidth===1&&d.filterHeight===1&&v.arraysEqual(d.inShape,d.outShape))c=sr({inputs:{x:r},backend:a});else{let p=a.data.get(r.dataId).values,h=v.computeStrides(r.shape),m=$3(p,r.shape,r.dtype,h,d,"max");c=a.makeTensorInfo(d.outShape,r.dtype,m.values)}return c}var LV={kernelName:So,backendName:"cpu",kernelFunc:zV};function WV(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n;Ie(r,"maxPool3d");let d=I.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.data.get(r.dataId).values,p=Tv(c,r.shape,r.dtype,v.computeStrides(r.shape),d,"max");return a.makeTensorInfo(p.shape,"float32",p.values)}var BV={kernelName:Cu,backendName:"cpu",kernelFunc:WV};function VV(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n;Ie([r,s],"maxPool3DGrad");let d=I.computePool3DInfo(s.shape,i,o,1,l,u),c=a.bufferSync(s),p=EW(c,d),h=d.strideDepth,m=d.strideHeight,f=d.strideWidth,g=d.dilationDepth,y=d.dilationHeight,x=d.dilationWidth,A=d.effectiveFilterDepth,b=d.effectiveFilterHeight,w=d.effectiveFilterWidth,S=A-1-d.padInfo.front,C=w-1-d.padInfo.left,N=b-1-d.padInfo.top,M=Te(s.shape,"float32"),F=a.bufferSync(r);for(let E=0;E=d.outDepth||Math.floor(V)!==V))for(let Z=0;Z=d.outHeight||Math.floor(X)!==X))for(let re=0;re=d.outWidth||Math.floor(ee)!==ee)continue;let ge=A*b*w-1-p.get(E,V,X,ee,T),ie=H*b*w+Z*w+re,be=ge===ie?1:0;if(be===0)continue;let Ce=F.get(E,V,X,ee,T);q+=Ce*be}}}M.set(q,E,D,O,W,T)}return a.makeTensorInfo(M.shape,M.dtype,M.values)}var UV={kernelName:Rp,backendName:"cpu",kernelFunc:VV};function GV(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;Ie([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:d,dimRoundingMode:c}=n,p=I.computePool2DInfo(o.shape,l,u,1,d,c),h=a.data.get(o.dataId).values,m=Te(p.outShape,o.dtype,Sv(h,o.shape,o.dtype,p).values),f=p.strideHeight,g=p.strideWidth,y=p.dilationHeight,x=p.dilationWidth,A=p.effectiveFilterHeight,b=p.effectiveFilterWidth,w=b-1-p.padInfo.left,S=A-1-p.padInfo.top,C=Te(o.shape,"float32"),N=a.data.get(r.dataId).values,M=Te(r.shape,"float32",N);for(let F=0;F=p.outHeight||Math.floor(G)!==G))for(let q=0;q=p.outWidth||Math.floor(H)!==H)continue;let V=A*b-1-m.get(F,G,H,E),Z=U*b+q,X=V===Z?1:0;if(X===0)continue;let re=M.get(F,G,H,E);$+=re*X}}C.set($,F,T,D,E)}return a.makeTensorInfo(C.shape,C.dtype,C.values)}var HV={kernelName:Np,backendName:"cpu",kernelFunc:GV};function jV(e,t,a,n,r){let s=v.computeStrides(t),i=$3(e,t,a,s,r,"max"),o=Sv(e,t,a,r,!0,n);return[i.values,o.values]}var qV={kernelName:Nu,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=a;Ie(n,"MaxPoolWithArgmax");let u=l.data.get(n.dataId).values,d=I.computePool2DInfo(n.shape,r,s,[1,1],i),[c,p]=jV(u,n.shape,n.dtype,o,d),h=l.write(c,d.outShape,n.dtype),m=l.write(p,d.outShape,n.dtype);return[{dataId:h,shape:d.outShape,dtype:n.dtype},{dataId:m,shape:d.outShape,dtype:"int32"}]}};function XV(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=v.parseAxisParam(s,r.shape),l=I.computeOutAndReduceShapes(r.shape,o)[1],u=v.sizeFromShape(l),d=[],c=a.makeTensorInfo([],"float32",new Float32Array([u]));d.push(c);let p=ds({inputs:{x:r},backend:a,attrs:{dtype:"float32"}});d.push(p);let h=D3({inputs:{a:p,b:c},backend:a});d.push(h);let m=tc({inputs:{x:h},backend:a,attrs:{axis:s,keepDims:i}});return d.forEach(f=>a.disposeIntermediateTensorInfo(f)),m}var KV={kernelName:To,backendName:"cpu",kernelFunc:XV};function YV(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;Ie(r,"min");let o=v.parseAxisParam(s,r.shape),l=o,u=I.getAxesPermutation(l,r.shape.length),d=r;u!=null&&(d=Va({inputs:{x:r},backend:a,attrs:{perm:u}}),l=I.getInnerMostAxes(l.length,r.shape.length)),I.assertAxesAreInnerMostDims("min",l,d.shape.length);let[c,p]=I.computeOutAndReduceShapes(d.shape,l),h=v.sizeFromShape(p),m=v.makeZerosTypedArray(v.sizeFromShape(c),d.dtype),f=a.data.get(d.dataId).values;for(let y=0;yx[0]+r.shape[A]+x[1]),l=s.map(x=>x[0]),u=s.map((x,A)=>x[0]+r.shape[A]),d=i==="reflect"?0:1,c=a.data.get(r.dataId).values,p=r.shape.length,h=v.computeStrides(r.shape),m=v.sizeFromShape(o),f=o.length,g=v.computeStrides(o),y=v.getTypedArrayFromDType(r.dtype,m);for(let x=0;x=u[w]&&(A[w]=(u[w]-1)*2-A[w]+d);A=A.map((w,S)=>w-l[S]);let b=v.locToIndex(A,p,h);y[x]=c[b]}return{dataId:a.write(y,o,r.dtype),shape:o,dtype:r.dtype}}var QV={kernelName:No,backendName:"cpu",kernelFunc:JV},eU=Pt((e,t)=>{let a=e%t;return e<0&&t<0||e>=0&&t>=0?a:(a+t)%t}),tU=Kt(Ro,eU),aU={kernelName:Ro,backendName:"cpu",kernelFunc:tU},nU=uu(EA());function Mv(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=r.shape.length,o=s;if(o===-1&&(o=i-1),o!==i-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${i} and dim was ${o}`);let l=v.parseAxisParam([o],r.shape),u=Ev({inputs:{x:r},backend:a,attrs:{reductionIndices:l,keepDims:!1}}),d=I.expandShapeToKeepDim(u.shape,l),c=bt({inputs:{x:u},backend:a,attrs:{shape:d}}),p=M3({inputs:{a:r,b:c},backend:a}),h=B6({inputs:{x:p},backend:a}),m=tc({inputs:{x:h},backend:a,attrs:{axis:l,keepDims:!1}}),f=bt({inputs:{x:m},backend:a,attrs:{shape:d}}),g=D3({inputs:{a:h,b:f},backend:a});return a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),g}var rU={kernelName:el,backendName:"cpu",kernelFunc:Mv};function sU(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n;Ie(r,"multinomial");let l=o?r:Mv({inputs:{logits:r},backend:a,attrs:{dim:-1}}),u=l.shape[0],d=l.shape[1],c=a.data.get(l.dataId).values,p=[u,s],h=v.makeZerosTypedArray(v.sizeFromShape(p),"int32");for(let m=0;m=0&&c[p]{v.assertShapesMatch(s,d.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===d.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(d=>{let c=Ch({inputs:{input:d},backend:a,attrs:{dim:r}});return o.push(c),c}),u=ou({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(d=>a.disposeIntermediateTensorInfo(d)),u}var bU={kernelName:Fu,backendName:"cpu",kernelFunc:$v};function vU(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;Ie(r,"pad");let o=s.map((y,x)=>y[0]+r.shape[x]+y[1]),l=s.map(y=>y[0]),u=a.data.get(r.dataId).values,d=v.sizeFromShape(r.shape),c=r.shape.length,p=v.computeStrides(r.shape),h=v.sizeFromShape(o),m=o.length,f=v.computeStrides(o),g=v.getTypedArrayFromDType(r.dtype,h);i!==0&&g.fill(i);for(let 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w=v.computeStrides(d);m=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let f=i.shape.length,g=d.length===2&&v.arraysEqual(i.shape,l),y=v.sizeFromShape(i.shape)===1,x=I.getBroadcastDims(i.shape,a.shape),A=!e.packedInputs&&f===a.shape.length&&v.arraysEqual(l,a.texData.texShape),b=e.packedInputs||d.length>2?"":`${l[0]>1}_${l[1]>1}`;n+=`${f}_${A}_${u?c:""}_${d.length}_${y}_${x}_${g}_${p}_${h}_${m}_${b}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${l}_${o}`}});let r=e.userCode,s=e.constructor.name;return s+="_"+n+"_"+r+`${B().getNumber("WEBGL_VERSION")}`,s}function ga(e){return B().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var hj=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=sp.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Ra();this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length),this.userCode=` ivec3 outCoordsFromFlatIndex(int index) { 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s="";for(let i=0;ibw,createBufferFromOutputTexture:()=>kw,createFloat16MatrixTexture:()=>gw,createFloat16PackedMatrixTexture:()=>Aw,createFloat32MatrixTexture:()=>fw,createIndexBuffer:()=>mw,createPackedMatrixTexture:()=>xw,createUnsignedBytesMatrixTexture:()=>yw,createVertexBuffer:()=>hw,createVertexShader:()=>cw,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Sw,downloadFloat32MatrixFromBuffer:()=>Iw,downloadMatrixFromPackedOutputTexture:()=>Cw,downloadPackedMatrixFromBuffer:()=>Tw,getInternalFormatForFloat16MatrixTexture:()=>V3,getInternalFormatForFloat16PackedMatrixTexture:()=>H3,getInternalFormatForFloat32MatrixTexture:()=>B3,getInternalFormatForPackedMatrixTexture:()=>G3,getInternalFormatForUnsignedBytesMatrixTexture:()=>U3,uploadDenseMatrixToTexture:()=>vw,uploadPixelDataToTexture:()=>ww});function cw(e){let t=Ra(),a=`${t.version} precision highp float; ${t.attribute} vec3 clipSpacePos; ${t.attribute} vec2 uv; ${t.varyingVs} vec2 resultUV; void main() { gl_Position = 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nc(e,r,s,V3(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function U3(e){return e.downloadTextureFormat}function yw(e,t,a,n){let[r,s]=ac(t,a);return nc(e,r,s,U3(n),e.RGBA,e.UNSIGNED_BYTE)}function G3(e){return e.internalFormatPackedFloat}function xw(e,t,a,n){let[r,s]=Zu(t,a);return nc(e,r,s,G3(n),e.RGBA,e.FLOAT)}function H3(e){return e.internalFormatPackedHalfFloat}function Aw(e,t,a,n){let[r,s]=Zu(t,a);return nc(e,r,s,H3(n),e.RGBA,n.textureTypeHalfFloat)}function bw(e,t,a){return ce(e,()=>e.bindBuffer(e.ARRAY_BUFFER,a)),B1(e,t,"clipSpacePos",a,3,20,0)&&B1(e,t,"uv",a,2,20,12)}function vw(e,t,a,n,r,s){ce(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;r instanceof Uint8Array?(i=new Uint8Array(a*n*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(a*n*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(r),B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a,n,e.RGBA,o,i)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,a,n,0,e.RGBA,o,i)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function ww(e,t,a){ce(e,()=>e.bindTexture(e.TEXTURE_2D,t)),a.data instanceof Uint8Array?B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,a.width,a.height,e.RGBA,e.UNSIGNED_BYTE,a.data)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,a.width,a.height,0,e.RGBA,e.UNSIGNED_BYTE,a.data)):B().getNumber("WEBGL_VERSION")===2?ce(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,a)):ce(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,a)),ce(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function kw(e,t,a,n){let r=e.createBuffer();ce(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let s=4*4*t*a;return ce(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),ce(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,0)),ce(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function Iw(e,t,a){let n=e,r=new Float32Array(a);return n.bindBuffer(n.PIXEL_PACK_BUFFER,t),n.getBufferSubData(n.PIXEL_PACK_BUFFER,0,r),n.bindBuffer(n.PIXEL_PACK_BUFFER,null),r}function Sw(e,t,a,n){let[r,s]=ac(t,a),i=4,o=new Uint8Array(mH(t*a,i));return ce(e,()=>e.readPixels(0,0,r,s,n.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function Tw(e,t,a,n,r,s,i,o){let l=e,u=new Float32Array(fH(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function Cw(e,t,a){let n=new Float32Array(t*a*4);return ce(e,()=>e.readPixels(0,0,a,t,e.RGBA,e.FLOAT,n)),n}var Yl=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let t=B().getNumber("WEBGL_VERSION");if(e!=null?(this.gl=e,u0(t,e)):this.gl=Un(t),e=this.gl,B().getNumber("WEBGL_VERSION")===2){let r=e;this.createVertexArray=()=>ce(r,()=>r.createVertexArray()),this.bindVertexArray=s=>ce(r,()=>r.bindVertexArray(s)),this.deleteVertexArray=s=>ce(r,()=>r.deleteVertexArray(s)),this.getVertexArray=()=>ce(r,()=>r.getParameter(r.VERTEX_ARRAY_BINDING))}else if(e!=null){let r=e.getExtension("OES_vertex_array_object");if(r==null)throw new Error("All WebGL1 implementations are expected to offer OES_vertex_array_object.");this.createVertexArray=()=>ce(e,()=>r.createVertexArrayOES()),this.bindVertexArray=s=>ce(e,()=>r.bindVertexArrayOES(s)),this.deleteVertexArray=s=>ce(e,()=>r.deleteVertexArrayOES(s)),this.getVertexArray=()=>ce(e,()=>e.getParameter(r.VERTEX_ARRAY_BINDING_OES))}let a="WEBGL_color_buffer_float",n="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),B().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=Dd(this.gl,r),yn(this.gl,s))this.textureHalfFloatExtension=Dd(this.gl,s);else if(B().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(a),yn(this.gl,n))this.colorBufferHalfFloatExtension=Dd(this.gl,n);else if(B().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(a="EXT_color_buffer_float",yn(this.gl,a))this.colorBufferFloatExtension=this.gl.getExtension(a);else if(yn(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=hw(this.gl),this.indexBuffer=mw(this.gl),this.framebuffer=jv(this.gl),this.textureConfig=_3(this.gl,this.textureHalfFloatExtension)}get debug(){return B().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. 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this.throwIfDisposed(),Aw(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),xw(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(V1(this.gl,this.framebuffer),this.outputTexture=null),ce(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,a){return this.downloadMatrixDriver(e,()=>Sw(this.gl,t,a,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,a,n,r,s){return Tw(this.gl,e,t,a,n,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return Iw(this.gl,e,t)}createBufferFromTexture(e,t,a){this.bindTextureToFrameBuffer(e);let n=kw(this.gl,t,a,this.textureConfig);return this.unbindTextureToFrameBuffer(),n}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,a;if(B().getBool("WEBGL_FENCE_API_ENABLED")){let n=e,r=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),a=()=>{let 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t=this.gl;ce(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),bw(t,e,this.vertexBuffer)}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(ce(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&uh(this.gl,this.program),ce(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,a=!0){return this.throwIfDisposed(),a?Xv(this.gl,e,t):Kv(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),ce(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,a){this.throwIfDisposed(),this.throwIfNoProgram(),Yv(this.gl,e,t,a)}setOutputMatrixTexture(e,t,a){this.setOutputMatrixTextureDriver(e,a,t)}setOutputPackedMatrixTexture(e,t,a){this.throwIfDisposed();let[n,r]=Zu(t,a);this.setOutputMatrixTextureDriver(e,n,r)}setOutputMatrixWriteRegion(e,t,a,n){this.setOutputMatrixWriteRegionDriver(a,e,n,t)}setOutputPackedMatrixWriteRegion(e,t,a,n){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&uh(this.gl,this.program),Pd(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;if(this.debug){let t=this.getVertexArray();console.assert(t===this.program.vao,"VAO changed between setProgram and executeProgram!"),this.debugValidate()}ce(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),ce(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=Dd(this.gl,B().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(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let a=this.gl,n=this.getQueryTimerExtensionWebGL2(),r=a.createQuery();return a.beginQuery(n.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,a=this.getQueryTimerExtensionWebGL2();t.endQuery(a.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let a=this.gl;return a.getQueryParameter(e,a.QUERY_RESULT)/1e6}else{let a=this.getQueryTimerExtensionWebGL1();return a.getQueryObjectEXT(e,a.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let a=this.gl,n=this.getQueryTimerExtensionWebGL2(),r=a.getQueryParameter(e,a.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let a=this.getQueryTimerExtensionWebGL1(),n=a.getQueryObjectEXT(e,a.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(a.GPU_DISJOINT_EXT)),n&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=Aj(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:a}=this.itemsToPoll[t];a()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){if(this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1)return;let a;"setTimeoutCustom"in B().platform&&(a=B().platform.setTimeoutCustom.bind(B().platform)),v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,a)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),dh(this.gl,e,this.framebuffer),this.debug&&Pd(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(dh(this.gl,this.outputTexture,this.framebuffer),this.debug&&Pd(this.gl)):V1(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let a=t();return this.unbindTextureToFrameBuffer(),a}setOutputMatrixTextureDriver(e,t,a){this.throwIfDisposed();let n=this.gl;dh(n,e,this.framebuffer),this.debug&&Pd(n),this.outputTexture=e,ce(n,()=>n.viewport(0,0,t,a)),ce(n,()=>n.scissor(0,0,t,a))}setOutputMatrixWriteRegionDriver(e,t,a,n){this.throwIfDisposed(),ce(this.gl,()=>this.gl.scissor(e,t,a,n))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function Aj(e){let t=0;for(;t`${e}.${a}`)}function ka(e,t){return t===1?[e]:Mw(e,t)}function pq(e,t){if(e===1)return"rc";let a="";for(let n=0;n ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let a=this.rank-2;a= ${this.enableShapeUniforms?`outShape[${a}]`:this.outputShape[a]}`,a= ${a}; bool rEdge = rp1 >= ${n}; `}getOutput(e){let t=this.getSourceCoordsArr(e);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${t[0]}), cEdge ? 0. : getA(${t[1]}), rEdge ? 0. : getA(${t[2]}), rEdge || cEdge ? 0. : getA(${t[3]})`}},Fw=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length);let a="";for(let n=0;n<4;n++){let r="thisRC = rc;";n%2===1&&(r+="thisRC.z += 1;"),n>1&&(r+="thisRC.y += 1;"),a+=` ${r} ${n>0?"if(thisRC.y < rows && thisRC.z < cols){":""} int flatIndex = getFlatIndex(thisRC); ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex); vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z)); result[${n}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims); ${n>0?"}":""} `}this.userCode=` ${hq(t,this.enableShapeUniforms)} ${this.enableShapeUniforms?L3():z3(e)} void main() { ivec3 rc = getOutputCoords(); vec4 result = vec4(0.); ivec3 thisRC; int rows = ${this.enableShapeUniforms?"outShape[1]":e[1]}; int cols = ${this.enableShapeUniforms?"outShape[2]":e[2]}; ${a} setOutput(result); } `}};function hq(e,t){return` ivec3 inputCoordsFromReshapedOutCoords(int index) { ${t?CH(["r","c","d"],"inputShape"):dl(["r","c","d"],e)} return ivec3(r, c, d); } `}var mq=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.usedTextures={},this.logEnabled=!1}acquireTexture(e,t,a){let n=L5(t,a),r=W5(e,n,a);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=z5(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,a);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].pop();return this.usedTextures[r].push(o),o}let i;return n===pa.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===pa.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===pa.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===pa.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===pa.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,a,n){if(this.freeTextures==null)return;let r=L5(a,n),s=W5(t,r,n);s in this.freeTextures||(this.freeTextures[s]=[]);let i=z5(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,n),o=B().getNumber("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l&&l.indexOf(e);if(u==null||u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l[u]=l[l.length-1],l.pop(),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function fq(e,t){let a=e;if(t===a.R32F)return 4;if(t===a.R16F)return 2;if(t===a.RGBA32F||t===e.RGBA)return 16;if(t===a.RGBA16F)return 8;if(t===a.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function z5(e,t,a,n,r){let s=gq(t,n),i;if(r){let[l,u]=Zu(e[0],e[1]);i=l*u}else{let[l,u]=ac(e[0],e[1]);i=l*u}let o=fq(a,s);return i*o}function gq(e,t){switch(e){case pa.PACKED_2X2_FLOAT32:return G3(t);case pa.PACKED_2X2_FLOAT16:return H3(t);case pa.UNPACKED_FLOAT32:return B3(t);case pa.UNPACKED_FLOAT16:return V3(t);case pa.PACKED_4X1_UNSIGNED_BYTE:return U3(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function yq(e){return B().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?pa.PACKED_2X2_FLOAT32:pa.UNPACKED_FLOAT32:e?pa.PACKED_2X2_FLOAT16:pa.UNPACKED_FLOAT16}function L5(e,t){if(e===gn.UPLOAD)return pa.PACKED_2X2_FLOAT32;if(e===gn.RENDER||e==null)return yq(t);if(e===gn.DOWNLOAD||e===gn.PIXELS)return pa.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function W5(e,t,a){return`${e[0]}_${e[1]}_${t}_${a}`}var Qn=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length),this.userCode=` float unaryOperation(float x) { ${t} } void main() { float x = getAAtOutCoords(); float y = unaryOperation(x); setOutput(y); } `}},$n="if (isnan(x)) return x;",xq="return x;",B5="return abs(x);",Aq="return (x >= 0.0) ? x : (exp(x) - 1.0);",bq=$n+` return (x < 0.0) ? 0.0 : x; `,vq=$n+` return (x < 0.0) ? 0.0 : min(6.0, x); `,jr="return x;",wq="return 1.0 / (1.0 + exp(-1.0 * x));",kq="return x;",Iq=` 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; `,Sq=` 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; `,Tq=` 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; `,Cq="return 1.0 / (1.0 + exp(-1.0 * x));",Zr=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length),this.userCode=` vec4 unaryOperation(vec4 x) { ${t} } void main() { vec4 x = getAAtOutCoords(); vec4 y = unaryOperation(x); setOutput(y); } `}},Nq=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=ga(this.outputShape.length);let t=e.length,a=ka("rc",t),n=ft(t),r=pq(t,a),s=a.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=` void main() { ${n} rc = getOutputCoords(); vec4 packedInput = getA(${r}); setOutput(getChannel(packedInput, ${i})); } `}},Rq=Fn.whereImpl,Eq=1e-7,Mq=1e-4,r1={};function Fq(e){return e in r1||(r1[e]={}),r1[e]}var $q=B().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),Dq=600;function Pq(){return B().global.screen==null?1024:B().global.screen.height*B().global.screen.width*window.devicePixelRatio*Dq/1024/1024}var rc=class $w extends du{nextDataId(){return $w.nextDataId++}constructor(t){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!B().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let a;if(t!=null){if(t instanceof Yl)a=t;else{let n=Un(B().getNumber("WEBGL_VERSION"),t);a=new Yl(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Un(B().getNumber("WEBGL_VERSION"));a=new Yl(n),this.binaryCache=Fq(B().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=a,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new mq(this.gpgpu),this.numMBBeforeWarning=Pq(),this.texData=new hp(this,St())}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(t,a,n,r,s,i){let o=this.makeTensorInfo(a,n),l=this.texData.get(o.dataId);l.isPacked=!1,l.texture={texture:t,texShape:[r,s]},l.texShape=[r,s];let u=_d(a),d=new O5(u,!1,i),c=this.runWebGLProgram(d,[o],n,[[r,s]]);return c.shape=a,l.texture=null,this.disposeIntermediateTensorInfo(o),c.dataId}write(t,a,n){if((B().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||B().getBool("DEBUG"))&&this.checkNumericalProblems(t),n==="complex64"&&t!=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:a,dtype:n,values:t,usage:gn.UPLOAD,refCount:1}),r}refCount(t){return this.texData.has(t)?this.texData.get(t).refCount:0}incRef(t){let a=this.texData.get(t);a.refCount++}decRef(t){if(this.texData.has(t)){let a=this.texData.get(t);a.refCount--}}move(t,a,n,r,s){if(B().getBool("DEBUG")&&this.checkNumericalProblems(a),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:r,values:a,usage:gn.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let a=this.texData.get(t),{values:n,dtype:r,complexTensorInfos:s,slice:i,shape:o,isPacked:l}=a;if(i!=null){let p;l?p=new Zr(o,jr):p=new Qn(o,jr);let h=this.runWebGLProgram(p,[{dataId:t,shape:o,dtype:r}],r),m=this.readSync(h.dataId);return this.disposeIntermediateTensorInfo(h),m}if(n!=null)return this.convertAndCacheOnCPU(t);if(r==="string")return n;let u=this.activeTimers!=null,d;u&&(d=v.now());let c;if(r==="complex64"){let p=this.readSync(s.real.dataId),h=this.readSync(s.imag.dataId);c=I.mergeRealAndImagArrays(p,h)}else c=this.getValuesFromTexture(t);return u&&(this.downloadWaitMs+=v.now()-d),this.convertAndCacheOnCPU(t,c)}async read(t){if(this.pendingRead.has(t)){let m=this.pendingRead.get(t);return new Promise(f=>m.push(f))}let a=this.texData.get(t),{values:n,shape:r,slice:s,dtype:i,complexTensorInfos:o,isPacked:l}=a;if(s!=null){let m;l?m=new Zr(r,jr):m=new Qn(r,jr);let f=this.runWebGLProgram(m,[{dataId:t,shape:r,dtype:i}],i),g=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),g}if(n!=null)return this.convertAndCacheOnCPU(t);if(B().getBool("DEBUG")&&!B().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&B().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let u=null,d;if(i!=="complex64"&&B().get("WEBGL_BUFFER_SUPPORTED")){d=this.decode(t);let m=this.texData.get(d.dataId);u=this.gpgpu.createBufferFromTexture(m.texture.texture,...nh(r))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(i==="complex64"){let m=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),f=m[0],g=m[1];c=I.mergeRealAndImagArrays(f,g)}else if(u==null)c=this.getValuesFromTexture(t);else{let m=v.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(u,m)}if(d!=null&&this.disposeIntermediateTensorInfo(d),u!=null){let m=this.gpgpu.gl;ce(m,()=>m.deleteBuffer(u))}let p=this.convertAndCacheOnCPU(t,c),h=this.pendingRead.get(t);return this.pendingRead.delete(t),h.forEach(m=>m(p)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&St().removeDataId(t,this),this.pendingDeletes--),p}readToGPU(t,a={}){let n=this.texData.get(t),{values:r,shape:s,slice:i,dtype:o,isPacked:l,texture:u}=n;if(o==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let h;l?h=new Zr(s,jr):h=new Qn(s,jr);let m=this.runWebGLProgram(h,[{dataId:t,shape:s,dtype:o}],o),f=this.readToGPU(m,a);return this.disposeIntermediateTensorInfo(m),f}if(u==null)throw r!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let d=this.decode(t,a.customTexShape),c=St().makeTensorFromTensorInfo(d),p=this.texData.get(d.dataId);return Object.assign({tensorRef:c},p.texture)}bufferSync(t){let a=this.readSync(t.dataId);if(t.dtype==="string")try{let n=a.map(r=>v.decodeString(r));return Te(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Te(t.shape,t.dtype,a)}checkNumericalProblems(t){if(t!=null)for(let a=0;a0}time(t){let a=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),i=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=a,r&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);o.kernelMs=v.sum(l),o.getExtraProfileInfo=()=>l.map((u,d)=>({name:i[d],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(t){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=v.now(),t)}async getQueryTime(t){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(t);let a=t;return a.endMs-a.startMs}disposeData(t,a=!1){if(this.pendingDisposal.has(t))return!1;if(!this.texData.has(t))return!0;if(a?this.texData.get(t).refCount=0:this.texData.get(t).refCount--,!a&&this.texData.get(t).refCount>0)return!1;if(this.pendingRead.has(t))return this.pendingDisposal.add(t),this.pendingDeletes++,!1;this.releaseGPUData(t);let{complexTensorInfos:n}=this.texData.get(t);return n!=null&&(this.disposeData(n.real.dataId,a),this.disposeData(n.imag.dataId,a)),this.texData.delete(t),!0}releaseGPUData(t){let{texture:a,dtype:n,texShape:r,usage:s,isPacked:i,slice:o}=this.texData.get(t),l=o&&o.origDataId||t,u=this.dataRefCount.get(l);u>1?this.dataRefCount.set(l,u-1):(this.dataRefCount.delete(l),a!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(a,r,s,i)));let d=this.texData.get(t);d.texture=null,d.texShape=null,d.isPacked=!1,d.slice=null}getTexture(t){return this.uploadToGPU(t),this.texData.get(t).texture.texture}getDataInfo(t){return this.texData.get(t)}shouldExecuteOnCPU(t,a=$q){return B().getBool("WEBGL_CPU_FORWARD")&&t.every(n=>this.texData.get(n.dataId).texture==null&&v.sizeFromShape(n.shape)0&&v.isString(n[0])){let s=n.map(i=>v.encodeString(i));r=this.write(s,t,a)}else r=this.write(n,t,a);return this.texData.get(r).usage=null,{dataId:r,shape:t,dtype:a}}makeOutput(t,a,n){return St().makeTensorFromTensorInfo(this.makeTensorInfo(t,a,n),this)}unpackTensor(t){let a=new Nq(t.shape);return this.runWebGLProgram(a,[t],t.dtype)}packTensor(t){let a=new cq(t.shape);return this.runWebGLProgram(a,[t],t.dtype,null,!0)}packedReshape(t,a){let n=[Ni(t.shape),...Ri(t.shape)],r={dtype:t.dtype,shape:n,dataId:t.dataId},s=[Ni(a),...Ri(a)],i=new Fw(s,n),o=!0,l=[n],u=this.runWebGLProgram(i,[r],t.dtype,l,o);return{dataId:u.dataId,shape:a,dtype:u.dtype}}decode(t,a){let n=this.texData.get(t),{isPacked:r,shape:s,dtype:i}=n;if(a!=null){let p=v.sizeFromShape(s),h=a[0]*a[1]*4;v.assert(p<=h,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let o=_d(s),l;r?l=new mj(o):l=new hj(o);let u=!0,d=[a!=null?a:nh(o)],c=this.runWebGLProgram(l,[{shape:o,dtype:i,dataId:t}],i,d,u,a);return{dtype:i,shape:s,dataId:c.dataId}}runWebGLProgram(t,a,n,r,s=!1,i){let o=this.makeTensorInfo(t.outputShape,n),l=this.texData.get(o.dataId);if(t.packedOutput&&(l.isPacked=!0),t.outPackingScheme===sp.DENSE){let y=i!=null?i:nh(t.outputShape);l.texShape=y.map(x=>x*2)}if(t.outTexUsage!=null&&(l.usage=t.outTexUsage),v.sizeFromShape(o.shape)===0)return l.values=v.getTypedArrayFromDType(o.dtype,0),o;let u=[],d=a.map(y=>{if(y.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let x=this.texData.get(y.dataId);if(x.texture==null){if(!t.packedInputs&&v.sizeFromShape(y.shape)<=B().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:y.shape,texData:null,isUniform:!0,uniformValues:x.values};t.packedInputs&&(x.isPacked=!0,x.shape=y.shape)}if(this.uploadToGPU(y.dataId),!!x.isPacked!=!!t.packedInputs)y=x.isPacked?this.unpackTensor(y):this.packTensor(y),u.push(y),x=this.texData.get(y.dataId);else if(x.isPacked&&!ip(x.shape,y.shape)){let A=y,b=y.shape;y.shape=x.shape,y=this.packedReshape(y,b),u.push(y),x=this.texData.get(y.dataId),A.shape=b}return{shape:y.shape,texData:x,isUniform:!1}});this.uploadToGPU(o.dataId);let c={shape:o.shape,texData:l,isUniform:!1},p=cj(t,d,c),h=this.getAndSaveBinary(p,()=>dj(this.gpgpu,t,d,c)),m=this.activeTimers!=null,f;m&&(f=this.startTimer()),B().get("ENGINE_COMPILE_ONLY")||pj(this.gpgpu,h,d,c,r),u.forEach(y=>this.disposeIntermediateTensorInfo(y)),m&&(f=this.endTimer(f),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(f)}));let g=B().getNumber("WEBGL_FLUSH_THRESHOLD");if(g>0){let y=v.now();y-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=y)}if(!B().getBool("WEBGL_LAZILY_UNPACK")&&l.isPacked&&s===!1){let y=this.unpackTensor(o);return this.disposeIntermediateTensorInfo(o),y}return o}compileAndRun(t,a,n,r,s=!1){return n=n||a[0].dtype,this.runWebGLProgram(t,a,n,r,s)}getAndSaveBinary(t,a){return t in this.binaryCache||(this.binaryCache[t]=a()),this.binaryCache[t]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(B().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),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=Pe(()=>{if(!B().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=B().getBool("DEBUG");B().set("DEBUG",!1);let a=this.abs(Ge(1e-8)).dataSync()[0];if(B().set("DEBUG",t),a>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?Eq:Mq}uploadToGPU(t){let a=this.texData.get(t),{shape:n,dtype:r,values:s,texture:i,usage:o,isPacked:l}=a;if(i!=null)return;let u=this.activeTimers!=null,d;u&&(d=v.now());let c=a.texShape;if(c==null&&(c=Qv(n,l),a.texShape=c),s!=null){let p=_d(n),h,m=c[1],f=c[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(l||!g)&&([m,f]=Zu(c[0],c[1])),l?h=new xj(p,g):h=new O5(p,g);let y=g?[f,m]:c,x=this.makeTensorInfo(y,r),A=this.texData.get(x.dataId);g?A.usage=gn.PIXELS:A.usage=gn.UPLOAD,A.texShape=y,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(x.dataId),m,f,s);let b=[[f,m]],w=this.runWebGLProgram(h,[x],r,b,!0),S=this.texData.get(w.dataId);a.texShape=S.texShape,a.isPacked=S.isPacked,a.usage=S.usage,B().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(a.texture=S.texture,a.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(x),u&&(this.uploadWaitMs+=v.now()-d)}else{let p=this.acquireTexture(c,o,r,l);a.texture=p}}convertAndCacheOnCPU(t,a){let n=this.texData.get(t),{dtype:r}=n;return a!=null&&(n.values=_q(a,r)),n.values}acquireTexture(t,a,n,r){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(t,a,r)}computeBytes(t,a){return t[0]*t[1]*v.bytesPerElement(a)}checkCompileCompletion(){for(let[,t]of Object.entries(this.binaryCache))this.checkCompletion_(t)}async checkCompileCompletionAsync(){let t=[];if(this.gpgpu.parallelCompilationExtension){for(let[,a]of Object.entries(this.binaryCache))t.push(this.checkCompletionAsync_(a));return Promise.all(t)}else{for(let[,a]of Object.entries(this.binaryCache)){let n=new Promise(r=>{try{this.checkCompletion_(a),r(!0)}catch(s){throw s}});t.push(n)}return Promise.all(t)}}async checkCompletionAsync_(t){return this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(t):(await i6(),this.checkCompletionAsync_(t))}checkCompletion_(t){if(this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(t.webGLProgram)),this.gpgpu.gl.getShaderParameter(t.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(O3(t.source,this.gpgpu.gl.getShaderInfoLog(t.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let t of Object.values(this.binaryCache)){this.gpgpu.buildVao(t.webGLProgram);let{variablesLocations:a,customUniformLocations:n,infLoc:r,nanLoc:s,outShapeLocation:i,outShapeStridesLocation:o,outTexShapeLocation:l}=dw(this.gpgpu,t.program,t.webGLProgram);t.variablesLocations=a,t.customUniformLocations=n,t.infLoc=r,t.nanLoc=s,t.outShapeLocation=i,t.outShapeStridesLocation=o,t.outTexShapeLocation=l}}createTensorFromGPUData(t,a,n){t.channels=t.channels||"RGBA";let{texture:r,height:s,width:i,channels:o}=t,l=St().backend;if(!l.gpgpu.gl.isTexture(r))throw new Error("The texture is invalid. 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NAN : result.r; result.g = isNaN.g ? NAN : result.g; result.b = isNaN.b ? NAN : result.b; result.a = isNaN.a ? NAN : result.a; `,nd=class{constructor(e,t,a,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=I.assertAndGetBroadcastShape(t,a);let r=this.outputShape.length;this.enableShapeUniforms=ga(r);let s="";if(n)if(r===0||v.sizeFromShape(this.outputShape)===1)s=` result.y = 0.; result.z = 0.; result.w = 0.; `;else if(s=` ${ft(r)} coords = getOutputCoords(); `,r===1)this.enableShapeUniforms?s+=` result.y = (coords + 1) >= outShape ? 0. : result.y; result.z = 0.; result.w = 0.; `:s+=` result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y; result.z = 0.; result.w = 0.; `;else{let i=ka("coords",r);this.enableShapeUniforms?s+=` bool nextRowOutOfBounds = (${i[r-2]} + 1) >= outShape[${r} - 2]; bool nextColOutOfBounds = (${i[r-1]} + 1) >= outShape[${r} - 1]; result.y = nextColOutOfBounds ? 0. : result.y; result.z = nextRowOutOfBounds ? 0. : result.z; result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w; `:s+=` bool nextRowOutOfBounds = (${i[r-2]} + 1) >= ${this.outputShape[r-2]}; bool nextColOutOfBounds = (${i[r-1]} + 1) >= ${this.outputShape[r-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); ${s} setOutput(result); } `}};function tn(e){let{inputs:t,backend:a}=e,{x:n}=t;return a.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var Lq={kernelName:ho,backendName:"webgl",kernelFunc:tn};function zs(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.makeTensorInfo(n.shape,"complex64"),i=a.texData.get(s.dataId),o=tn({inputs:{x:n},backend:a}),l=tn({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var Wq={kernelName:xp,backendName:"webgl",kernelFunc:zs},Pw="return (a < 0.) ? b * a : a;",_w=` vec4 aLessThanZero = vec4(lessThan(a, vec4(0.))); return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a); `;function Bq(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=a.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new nd(_w,r.shape,i.shape):new Ei(Pw,r.shape,i.shape),l=a.runWebGLProgram(o,[r,i],"float32");return a.disposeIntermediateTensorInfo(i),l}var Vq={kernelName:yo,backendName:"webgl",kernelFunc:Bq},Ow="return (a < 0.) ? 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${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); ${l} } setOutput(sumValue); } `}},Xq=class{constructor(e,t){this.variableNames=["x"];let{windowSize:a,batchSize:n,inSize:r,outSize:s}=e;this.outputShape=[n,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${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 u=Math.floor(a/4)*4,d=a%4,c=` 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 = ${o}(values, minMaxValue); if (${t==="min"} || ${t==="max"}) { minMaxValue = ${o}(values, minMaxValue); bvec4 isNaN = isnan(values); if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) { minMaxValue = vec4(NAN); } } } `,p="vec4";t==="all"?(i="1.0",c=` bool reducedAllValue = all(values); float floatedReducedAllValue = float(reducedAllValue); allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0); `,p="bvec4"):t==="any"&&(i="0.0",c=` bool reducedAnyValue = any(values); float floatedReducedAnyValue = float(reducedAnyValue); anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0); `,p="bvec4");let h="";r%a>0&&(h=` if (inIdx < 0 || inIdx >= ${r}) { 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) { ${h} return getX(batch, inIdx); } void main() { ivec2 coords = getOutputCoords(); int batch = coords[0]; int outIdx = coords[1]; int inOffset = outIdx * ${a}; vec4 minMaxValue = vec4(${i}); float prodValue = 1.0; float sumValue = 0.0; float allValue = 1.0; float anyValue = 0.0; for (int i = 0; i < ${u}; i += 4) { int inIdx = inOffset + i; ${p} values = ${p}( getValue(batch, inIdx), getValue(batch, inIdx + 1), getValue(batch, inIdx + 2), getValue(batch, inIdx + 3) ); ${c} } int inIdx = inOffset + ${u}; if (${d===1}) { ${p} values = ${p}( getValue(batch, inIdx), initializationValue, initializationValue, initializationValue ); ${c} } else if (${d===2}) { ${p} values = ${p}( getValue(batch, inIdx), getValue(batch, inIdx + 1), initializationValue, initializationValue ); ${c} } else if (${d===3}) { ${p} values = ${p}( getValue(batch, inIdx), getValue(batch, inIdx + 1), getValue(batch, inIdx + 2), initializationValue ); ${c} } setOutput(${l}); } `}};function Kq(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let a=t.length?t[t.length-1].outSize:e[1],n=I.computeOptimalWindowSize(a);t.push({inSize:a,windowSize:n,outSize:Math.ceil(a/n)})}return t}function hl(e,t,a,n){let r=Kq(e.shape),s=e;for(let i=0;i6)throw Error(`Transpose for rank ${t} is not yet supported`);let a=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(t);for(let r=0;r6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=ft(this.rank),r=Mw("rc",this.rank),s=new Array(this.rank);for(let u=0;u`Error in matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[y,c,h]:[y,h,c],w=n?[x,m,p]:[x,p,m],S=pe({inputs:{x:e},backend:r,attrs:{shape:b}}),C=pe({inputs:{x:t},backend:r,attrs:{shape:w}}),N=[S,C],M=Math.max(y,x),F=a?S.shape[1]:S.shape[2],E=s!=null,T=i!=null,D=l==="leakyrelu",O=l!=null?op(l,!0):null,W=E||T||D||O!=null,$;if((h===1||m===1)&&F>Ww&&W===!1){let G=S,q=C;a&&(G=Ta({inputs:{x:S},backend:r,attrs:{perm:[0,2,1]}}),N.push(G)),n&&(q=Ta({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),N.push(q));let H=m!==1,V=m===1,Z=G;H&&(Z=pe({inputs:{x:G},backend:r,attrs:{shape:[M,F,1]}}),N.push(Z));let X=m===1?2:1,re=q;V&&(re=pe({inputs:{x:q},backend:r,attrs:{shape:[M,1,F]}}),N.push(re));let ee=X3({inputs:{a:Z,b:re},backend:r});$=c0({inputs:{x:ee},backend:r,attrs:{axis:X,keepDims:!0}}),N.push(ee)}else{let G=Qt(e.dtype,t.dtype),q=new Lw(b,w,[M,h,m],a,n,E,O,T,D),H=[S,C];if(s!=null&&H.push(s),T&&H.push(i),D){let V=r.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));H.push(V),N.push(V)}$=r.runWebGLProgram(q,H,G)}let U=pe({inputs:{x:$},backend:r,attrs:{shape:A}});N.push($);for(let G of N)r.disposeIntermediateTensorInfo(G);return U}function aX(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:d,leakyreluAlpha:c}=n;return Rh({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:d})}var nX={kernelName:ts,backendName:"webgl",kernelFunc:aX},j5="return abs(x);";function rX(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=a.texData.get(n.dataId),i=Rw(s.values);return a.makeTensorInfo(n.shape,n.dtype,i)}let r;return B().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Zr(n.shape,j5):r=new Qn(n.shape,j5),a.runWebGLProgram(r,[n],n.dtype)}var sX={kernelName:cu,backendName:"webgl",kernelFunc:rX},iX=$n+` if (abs(x) > 1.) { return NAN; } return acos(x); `,oX=tt({opSnippet:iX}),lX={kernelName:$i,backendName:"webgl",kernelFunc:oX},uX=$n+` if (x < 1.0) return NAN; return log(x + sqrt(x * x - 1.0));`,dX=tt({opSnippet:uX}),pX={kernelName:Di,backendName:"webgl",kernelFunc:dX},q5="return a + b;",cX=ha({opSnippet:q5,packedOpSnippet:q5,supportsComplex:!0,cpuKernelImpl:bj}),hX={kernelName:Mr,backendName:"webgl",kernelFunc:cX},mX=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let a=[];this.variableNames.forEach(r=>{a.push(`float v${r} = get${r}AtOutCoords();`)});let n=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=` void main() { ${a.join(` `)} float result = ${n}; setOutput(result); } `}},fX=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let a=[];this.variableNames.forEach(r=>{a.push(`vec4 v${r} = get${r}AtOutCoords();`)});let n=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=` void main() { ${a.join(` `)} vec4 result = ${n}; setOutput(result); } `}};function hh(e){let{inputs:t,backend:a}=e,n=t;if(n.length===1)return tn({inputs:{x:n[0]},backend:a});if(n.length>B().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(n.length/2),l=hh({inputs:n.slice(0,o),backend:a}),u=hh({inputs:n.slice(o),backend:a});return hh({inputs:[l,u],backend:a})}let r=n.map(o=>o.dtype).reduce((o,l)=>Qt(o,l)),s=n.map(o=>o.shape),i=B().getBool("WEBGL_PACK")?new fX(n[0].shape,s):new mX(n[0].shape,s);return a.runWebGLProgram(i,n,r)}var gX={kernelName:Pi,backendName:"webgl",kernelFunc:hh};function yX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,d=I.getAxesPermutation(u,o),c=r;d!=null&&(c=Ta({inputs:{x:r},backend:a,attrs:{perm:d}}),u=I.getInnerMostAxes(u.length,o)),I.assertAxesAreInnerMostDims("all",u,o);let[p,h]=I.computeOutAndReduceShapes(c.shape,u),m=v.sizeFromShape(h),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,m]}}),g=hl(f,f.dtype,"all",a),y;if(i){let x=I.expandShapeToKeepDim(p,l);y=pe({inputs:{x:g},backend:a,attrs:{shape:x}})}else y=pe({inputs:{x:g},backend:a,attrs:{shape:p}});return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),d!=null&&a.disposeIntermediateTensorInfo(c),y}var xX={kernelName:_i,backendName:"webgl",kernelFunc:yX};function AX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,d=I.getAxesPermutation(u,o),c=r;d!=null&&(c=Ta({inputs:{x:r},backend:a,attrs:{perm:d}}),u=I.getInnerMostAxes(u.length,o)),I.assertAxesAreInnerMostDims("any",u,o);let[p,h]=I.computeOutAndReduceShapes(c.shape,u),m=v.sizeFromShape(h),f=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,m]}}),g=hl(f,f.dtype,"any",a),y;if(i){let x=I.expandShapeToKeepDim(p,l);y=pe({inputs:{x:g},backend:a,attrs:{shape:x}})}else y=pe({inputs:{x:g},backend:a,attrs:{shape:p}});return a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),d!=null&&a.disposeIntermediateTensorInfo(c),y}var bX={kernelName:Oi,backendName:"webgl",kernelFunc:AX},vX=class{constructor(e,t,a){this.variableNames=["A"];let{windowSize:n,batchSize:r,outSize:s}=e;a||this.variableNames.push("bestIndicesA"),this.outputShape=[r,s];let i=t==="max"?">":"<",o=a?"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 * ${n}; int bestIndex = inOffset; float bestValue = getA(batch, bestIndex); for (int i = 0; i < ${n}; i++) { int inIdx = ${o}; float candidate = getA(batch, inIdx); if (candidate ${i} bestValue) { bestValue = candidate; bestIndex = inIdx; } } setOutput(float(bestIndex)); } `}},wX=class{constructor(e,t,a,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${a.charAt(0).toUpperCase()+a.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],s=Math.ceil(r/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ft(o),u=ka("coords",o),d,c;if(s===1){c=o+1;let C=ft(c);d=` ${C} sourceLocR = ${C}(${u.join()}, 0); ++${u[o-1]}; ${C} sourceLocG = ${C}(${u.join()}, 0); ++${u[o-2]}; ${C} sourceLocA = ${C}(${u.join()}, 0); --${u[o-1]}; ${C} sourceLocB = ${C}(${u.join()}, 0); --${u[o-2]};`}else c=o,d=` ${l} sourceLocR = coords; ++${u[o-1]}; ${l} sourceLocG = coords; ++${u[o-2]}; ${l} sourceLocA = coords; --${u[o-1]}; ${l} sourceLocB = coords; --${u[o-2]};`;let p=["x","y","z","w","u","v"].slice(0,c),h="."+p[c-1],m=p.map(C=>"int "+C),f=ka("sourceLocR",c-1).concat("inIdx.r"),g=ka("sourceLocG",c-1).concat("inIdx.g"),y=ka("sourceLocB",c-1).concat("inIdx.b"),x=ka("sourceLocA",c-1).concat("inIdx.a"),A=a==="max"?"greaterThan":"lessThan",b=n?"":` inIdx = round(vec4(getBestIndicesAChannel(${f.join()}), getBestIndicesAChannel(${g.join()}), getBestIndicesAChannel(${y.join()}), getBestIndicesAChannel(${x.join()})));`,w=`vec4( getAChannel(${f.join()}), hasNextCol ? getAChannel(${g.join()}) : 0., hasNextRow ? getAChannel(${y.join()}) : 0., hasNextRow && hasNextCol ? getAChannel(${x.join()}) : 0.)`,S=n?"":` float getBestIndicesAChannel(${m.join()}) { return getChannel(getBestIndicesA(${p.join()}), vec2(${p.slice(-2).join()})); }`;this.userCode=` float getAChannel(${m.join()}) { return getChannel(getA(${p.join()}), vec2(${p.slice(-2).join()})); } ${S} void main() { ${l} coords = getOutputCoords(); bool hasNextCol = ${u[o-1]} < ${i[o-1]-1}; bool hasNextRow = ${u[o-2]} < ${i[o-2]-1}; ${d} ivec4 srcIdx = ivec4(sourceLocR${h}, sourceLocG${h}, sourceLocB${h}, sourceLocA${h}) * ${t}; ivec4 inIdx = srcIdx; vec4 bestIndex = vec4(inIdx); vec4 bestValue = ${w}; for (int i = 0; i < ${t}; i++) { inIdx = srcIdx; ${b} vec4 candidate = ${w}; bvec4 nan = isnan(candidate); bvec4 replace = bvec4( vec4(${A}(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 Bw(e,t,a,n=null){let r=t.shape[0],s=t.shape[1];n!=null&&(r=n.shape[0],s=n.shape[1]);let i=I.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:r,outSize:Math.ceil(s/i)},l=new vX(o,a,n==null),u=[t];n!=null&&u.push(n);let d=e.runWebGLProgram(l,u,"int32");if(d.shape[1]===1)return d;let c=Bw(e,t,a,d);return e.disposeIntermediateTensorInfo(d),c}function Vw(e,t,a,n=null){let r=n!=null?n.shape:t.shape,s=r[r.length-1],i=I.computeOptimalWindowSize(s),o=new wX(r,i,a,n==null),l=n==null?[t]:[t,n],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let d=Vw(e,t,a,u);return e.disposeIntermediateTensorInfo(u),d}return u}function Uw(e,t,a,n){let r=[a];if(I.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.shape.length),!B().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=e.texData.get(t.dataId),o=i!==null&&i.isPacked,l=t;o&&(l=e.unpackTensor(t),s.push(l));let[u,d]=I.computeOutAndReduceShapes(l.shape,r),c=v.sizeFromShape(d),p=pe({inputs:{x:l},backend:e,attrs:{shape:[-1,c]}});s.push(p);let h=Bw(e,p,n);s.push(h);let m=pe({inputs:{x:h},backend:e,attrs:{shape:u}});return s.forEach(f=>e.disposeIntermediateTensorInfo(f)),m}return Vw(e,t,n)}function kX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=I.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ta({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=I.getInnerMostAxes(i.length,l.shape.length)),I.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let d=Uw(a,l,i[0],"max");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),d}var IX={kernelName:hu,backendName:"webgl",kernelFunc:kX};function SX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=I.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Ta({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=I.getInnerMostAxes(i.length,l.shape.length)),I.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let d=Uw(a,l,i[0],"min");return u.forEach(c=>a.disposeIntermediateTensorInfo(c)),d}var TX={kernelName:mu,backendName:"webgl",kernelFunc:SX},CX=$n+` if (abs(x) > 1.) { return NAN; } return asin(x); `,NX=tt({opSnippet:CX}),RX={kernelName:zi,backendName:"webgl",kernelFunc:NX},EX=$n+"return log(x + sqrt(x * x + 1.0));",MX=tt({opSnippet:EX}),FX={kernelName:Li,backendName:"webgl",kernelFunc:MX},$X=$n+` return atan(x); `,DX=tt({opSnippet:$X}),PX={kernelName:Wi,backendName:"webgl",kernelFunc:DX},_X=q3+` return atan(a, b); `,OX=` vec4 result = atan(a, b); bvec4 isNaNA = isnan(a); bvec4 isNaNB = isnan(b); bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w); `+cl+` return result; `,zX=ha({opSnippet:_X,packedOpSnippet:OX}),LX={kernelName:Vi,backendName:"webgl",kernelFunc:zX},WX=$n+` if ((x < -1.0) || (x > 1.0)) return NAN; return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,BX=tt({opSnippet:WX}),VX={kernelName:Bi,backendName:"webgl",kernelFunc:BX},lp=class{constructor(e,t,a,n=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,d=e.effectiveFilterHeight,c=e.effectiveFilterWidth,p=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let m=t==="avg",f=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(m||(y="-1.0 / 1e-20"),a){let C=">=";this.userCode=` const ivec2 strides = ivec2(${i}, ${o}); const ivec2 pads = ivec2(${p}, ${h}); 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 < ${d}; wR += ${l}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${c}; wC += ${u}) { 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 ${C} currMinMaxValue) { minMaxValue = value; minMaxValueFound = 1.0; minMaxPosition = ${n?r?f:g:`wR * ${c} + wC`}; } } } setOutput(float(minMaxPosition)); } `;return}let x="max",A=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(A="avgValue / max(count, 1.0)");let b=Math.floor(s/4)*4,w=s%4,S=` if (${m}) { avgValue += dot(values, ones); } else { minMaxValue = ${x}(values, minMaxValue); } `;this.userCode=` const ivec2 strides = ivec2(${i}, ${o}); const ivec2 pads = ivec2(${p}, ${h}); 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 < ${d}; wR += ${l}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${b}; wC += 4) { int xC = xCCorner + wC * ${u}; vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${u}, d), getValue(batch, xR, xC + 2 * ${u}, d), getValue(batch, xR, xC + 3 * ${u}, d) ); ${S} } int xC = xCCorner + ${b}; if (${w===1}) { vec4 values = vec4( getValue(batch, xR, xC, d), initializationValue, initializationValue, initializationValue ); ${S} } else if (${w===2}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${u}, d), initializationValue, initializationValue ); ${S} } else if (${w===3}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${u}, d), getValue(batch, xR, xC + 2 * ${u}, d), initializationValue ); ${S} } } setOutput(${A}); } `}},K3=class{constructor(e,t,a,n=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,d=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterDepth,h=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.front,g=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let x=t==="avg",A="0.0";if(x||(A="-1.0 / 1e-20"),a){let M=">=";this.userCode=` const ivec3 strides = ivec3(${i}, ${o}, ${l}); const ivec3 pads = ivec3(${f}, ${g}, ${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 < ${p}; wD += ${u}) { int xD = xDCorner + wD; if (xD < 0 || xD >= ${e.inDepth}) { continue; } for (int wR = 0; wR < ${h}; wR += ${d}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${m}; wC += ${c}) { 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 ${M} currMinMaxValue) { minMaxValue = value; minMaxValueFound = 1.0; minMaxPosition = ${n?r?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${h} * ${m} + wR * ${m} + wC`}; } } } } setOutput(float(minMaxPosition)); } `;return}let b="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / max(count, 1.0)");let S=Math.floor(s/4)*4,C=s%4,N=` if (${x}) { avgValue += dot(values, ones); } else { minMaxValue = ${b}(values, minMaxValue); } `;this.userCode=` const ivec3 strides = ivec3(${i}, ${o}, ${l}); const ivec3 pads = ivec3(${f}, ${g}, ${y}); const float initializationValue = ${A}; 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 >= ${e.inWidth}) { return initializationValue; } count += 1.0; return getX(batch, xD, xR, xC, ch); } void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int ch = coords.u; ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads; int xDCorner = xCorner.x; int xRCorner = xCorner.y; int xCCorner = xCorner.z; // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch). // ? = to be determined vec4 minMaxValue = vec4(${A}); float avgValue = 0.0; count = 0.0; for (int wD = 0; wD < ${p}; wD += ${u}) { int xD = xDCorner + wD; if (xD < 0 || xD >= ${e.inDepth}) { continue; } for (int wR = 0; wR < ${h}; wR += ${d}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${S}; wC += 4) { int xC = xCCorner + wC * ${c}; vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${c}, ch), getValue(batch, xD, xR, xC + 2 * ${c}, ch), getValue(batch, xD, xR, xC + 3 * ${c}, ch) ); ${N} } int xC = xCCorner + ${S}; if (${C===1}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), initializationValue, initializationValue, initializationValue ); ${N} } else if (${C===2}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${c}, ch), initializationValue, initializationValue ); ${N} } else if (${C===3}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${c}, ch), getValue(batch, xD, xR, xC + 2 * ${c}, ch), initializationValue ); ${N} } } } setOutput(${w}); } `}};function UX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;Ju(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1;v.assert(I.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let d=I.computePool2DInfo(r.shape,s,i,u,o,l);if(d.filterWidth===1&&d.filterHeight===1&&v.arraysEqual(d.inShape,d.outShape))return tn({inputs:{x:r},backend:a});let c=new lp(d,"avg",!1);return a.runWebGLProgram(c,[r],"float32")}var GX={kernelName:Ui,backendName:"webgl",kernelFunc:UX};function HX(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,d=[1,1,1],c=I.computePool3DInfo(r.shape,s,i,d,o,l,u),p=new K3(c,"avg",!1);return a.runWebGLProgram(p,[r],"float32")}var jX={kernelName:fu,backendName:"webgl",kernelFunc:HX},qX=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,d=l-1-e.padInfo.left,c=1/(t*a);this.userCode=` const ivec2 pads = ivec2(${u}, ${d}); const float avgMultiplier = float(${c}); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; ivec2 dyRCCorner = coords.yz - pads; int dyRCorner = dyRCCorner.x; int dyCCorner = dyRCCorner.y; // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wR = 0; wR < ${o}; 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 < ${l}; wC+= ${i}) { float dyC = float(dyCCorner + wC) / ${r}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(b, idyR, idyC, d); dotProd += dyValue * avgMultiplier; } } setOutput(dotProd); } `}},XX=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,d=e.effectiveFilterDepth,c=e.effectiveFilterHeight,p=e.effectiveFilterWidth,h=d-1-e.padInfo.front,m=c-1-e.padInfo.top,f=p-1-e.padInfo.left,g=1/(t*a*n);this.userCode=` const ivec3 pads = ivec3(${h}, ${m}, ${f}); const float avgMultiplier = float(${g}); 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 < ${d}; wD += ${o}) { float dyD = float(dyDCorner + wD) / ${r}.0; if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) { continue; } int idyD = int(dyD); for (int wR = 0; wR < ${c}; 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 < ${p}; wC += ${u}) { 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 KX(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:d}=n,c=[1,1,1],p=I.computePool3DInfo(i.shape,o,l,c,u,d),h=new XX(p);return a.runWebGLProgram(h,[r],i.dtype)}var YX={kernelName:yp,backendName:"webgl",kernelFunc:KX};function ZX(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;Ju([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,d=I.computePool2DInfo(i.shape,o,l,1,u),c=new qX(d);return a.runWebGLProgram(c,[r],i.dtype)}var JX={kernelName:gp,backendName:"webgl",kernelFunc:ZX};function QX(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return Rh({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var eK={kernelName:Gi,backendName:"webgl",kernelFunc:QX},tK=class{constructor(e,t,a,n,r,s){this.outputShape=[],this.variableNames=["x","mean","variance"],I.assertAndGetBroadcastShape(e,t),I.assertAndGetBroadcastShape(e,a);let i="0.0";n!=null&&(I.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";r!=null&&(I.assertAndGetBroadcastShape(e,r),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))); } `}},aK=class{constructor(e,t,a,n,r,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],I.assertAndGetBroadcastShape(e,t),I.assertAndGetBroadcastShape(e,a);let i="vec4(0.0)";n!=null&&(I.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";r!=null&&(I.assertAndGetBroadcastShape(e,r),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); } `}},nK=({inputs:e,backend:t,attrs:a})=>{let{x:n,mean:r,variance:s,offset:i,scale:o}=e;v.assert(r.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=a;l==null&&(l=.001);let u=[n,r,s],d=null;i!=null&&(d=i.shape,u.push(i));let c=null;o!=null&&(c=o.shape,u.push(o));let p=B().getBool("WEBGL_PACK_NORMALIZATION")?new aK(n.shape,r.shape,s.shape,d,c,l):new tK(n.shape,r.shape,s.shape,d,c,l);return t.runWebGLProgram(p,u,u[0].dtype)},rK={kernelName:po,backendName:"webgl",kernelFunc:nK},sK=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ft(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let a=iK(this.rank),n,r=e.map((s,i)=>`sourceLoc.${H1[i]} = start[${i}] + coords.${H1[i]};`);n=` ${t} sourceLoc; ${t} coords = getOutputCoords(); ${r.join(` `)} `,this.userCode=` void main() { ${n} setOutput(getSource(${a})); } `}},H1=["x","y","z","w","u","v"];function iK(e){if(e===1)return"sourceLoc";if(e<=6)return H1.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var oK=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=ft(this.rank),a=ka("coords",this.rank),n=ka("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,s=`getChannel(getSource(${n.join()}), ${r})`,i=` result.x = ${s}; if (++${a[this.rank-1]} < ${e[this.rank-1]}) { ++${n[this.rank-1]}; result.y = ${s}; --${n[this.rank-1]}; } `,o=this.rank===1?"":` --${a[this.rank-1]}; if (++${a[this.rank-2]} < ${e[this.rank-2]}) { ++${n[this.rank-2]}; result.z = ${s}; if (++${a[this.rank-1]} < ${e[this.rank-1]}) { ++${n[this.rank-1]}; result.w = ${s}; } } `,l=this.rank<=4?`sourceLoc = coords + ${t}(${e.map((u,d)=>`start[${d}]`).join()});`:e.map((u,d)=>`${n[d]} = ${a[d]} + start[${d}];`).join(` `);this.userCode=` void main() { ${t} coords = getOutputCoords(); ${t} sourceLoc; ${l} vec4 result = vec4(0.); ${i} ${o} setOutput(result); } `}};function lK(e,t,a,n){let r=n.texData.get(e.dataId),s=n.makeTensorInfo(a,e.dtype),i=n.texData.get(s.dataId);Object.assign(i,r),i.refCount=1,i.shape=a,i.dtype=e.dtype;let o=wt.computeFlatOffset(t,v.computeStrides(e.shape));r.slice&&(o+=r.slice.flatOffset),i.slice={flatOffset:o,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=n.dataRefCount.get(i.slice.origDataId)||1;return n.dataRefCount.set(i.slice.origDataId,l+1),s}function sd(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=wt.parseSliceParams(r,s,i);if(wt.assertParamsValid(r,o,l),v.sizeFromShape(l)===0)return a.makeTensorInfo(l,r.dtype,[]);if(a.shouldExecuteOnCPU([r])||r.dtype==="string"){let c=a.texData.get(r.dataId),p=Jj(c.values,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,p)}let{isPacked:u}=a.texData.get(r.dataId),d=wt.isSliceContinous(r.shape,o,l);if(u||!d){let c=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new oK(l):new sK(l),p=[o];return a.runWebGLProgram(c,[r],r.dtype,p)}return a.uploadToGPU(r.dataId),lK(r,o,l,a)}var uK={kernelName:zu,backendName:"webgl",kernelFunc:sd},dK=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((x,A)=>x*A),l=I.getReshaped(r.shape,s,o),u=I.getPermuted(l.length,s.length),d=I.getReshapedPermuted(r.shape,s,o),c=I.getSliceBeginCoords(i,s.length),p=I.getSliceSize(d,i,s.length),h=[],m=pe({inputs:{x:r},backend:a,attrs:{shape:l}}),f=Ta({inputs:{x:m},backend:a,attrs:{perm:u}}),g=pe({inputs:{x:f},backend:a,attrs:{shape:d}}),y=sd({inputs:{x:g},backend:a,attrs:{begin:c,size:p}});return h.push(m),h.push(f),h.push(g),h.forEach(x=>a.disposeIntermediateTensorInfo(x)),y},pK={kernelName:gu,backendName:"webgl",kernelFunc:dK};function cK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=a.readSync(r.dataId),l=a.readSync(s.dataId),u=Nw(o,l,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,u)}var hK={kernelName:Hi,backendName:"webgl",kernelFunc:cK},mK=` int r = int(a.r) & int(b.r); int g = int(a.g) & int(b.g); int rb = int(a.b) & int(b.b); int ra = int(a.a) & int(b.a); return vec4(r, g, rb, ra); `,fK=` return float(int(a.r) & int(b.r)); `;function gK(e){let{inputs:t,backend:a}=e,{a:n,b:r}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS"),i=B().getNumber("WEBGL_VERSION");if(a.shouldExecuteOnCPU([n,r])||i===1){let l=a.texData.get(n.dataId).values,u=a.texData.get(r.dataId).values,[d,c]=wj(n.shape,r.shape,l,u,n.dtype),p=a.makeTensorInfo(c,n.dtype),h=a.texData.get(p.dataId);return h.values=d,p}let o;return s?o=new nd(mK,n.shape,r.shape,!1):o=new Ei(fK,n.shape,r.shape),a.runWebGLProgram(o,[n,r],n.dtype)}var yK={kernelName:ji,backendName:"webgl",kernelFunc:gK};function xK(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.readSync(n.dataId),i=a.readSync(r.dataId),o=I.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var AK={kernelName:yu,backendName:"webgl",kernelFunc:xK},bK="return float(a != b);",Gw=ha({opSnippet:bK,cpuKernelImpl:Uj,dtype:"bool"}),vK={kernelName:Cs,backendName:"webgl",kernelFunc:Gw};function sc(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return tn({inputs:{x:r.complexTensorInfos.real},backend:a})}var wK={kernelName:Ep,backendName:"webgl",kernelFunc:sc},kK="return float(int(x));";function IK(e,t){let a=new Qn(e.shape,kK),n=t.runWebGLProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function j1(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return tn({inputs:{x:r},backend:a});let i=An(r.shape),o=j1({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=zs({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=sc({inputs:{input:r},backend:a}),o=j1({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=tn({inputs:{x:r},backend:a});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(a.shouldExecuteOnCPU([r])){let i=a.texData.get(r.dataId).values,[o,l,u]=kj(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return IK(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=Gw({inputs:{a:r,b:i},backend:a});return a.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var SK={kernelName:qi,backendName:"webgl",kernelFunc:j1},X5="return ceil(x);",TK=tt({opSnippet:X5,packedOpSnippet:X5,cpuKernelImpl:Ij}),CK={kernelName:cs,backendName:"webgl",kernelFunc:TK},NK=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=` void main() { float value = getAAtOutCoords(); if (isnan(value)) { setOutput(value); return; } setOutput(clamp(value, minVal, maxVal)); } `}},RK=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=` void main() { vec4 value = getAAtOutCoords(); if (any(isnan(value))) { setOutput(value); return; } setOutput(clamp(value, vec4(minVal), vec4(maxVal))); } `}};function EK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o;B().getBool("WEBGL_PACK_CLIP")?o=new RK(r.shape):o=new NK(r.shape);let l=[[s],[i]];return a.runWebGLProgram(o,[r],r.dtype,l)}var MK={kernelName:hs,backendName:"webgl",kernelFunc:EK},FK=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 K5(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function $K(e){let{inputs:t,backend:a}=e,{x:n}=t,r=a.texData.get(n.dataId),s=new FK(n.shape),i=[K5(n,r.complexTensorInfos.real),K5(n,r.complexTensorInfos.imag)];return a.runWebGLProgram(s,i,i[0].dtype)}var DK={kernelName:Ap,backendName:"webgl",kernelFunc:$K},PK=class{constructor(e){this.outputShape=[],this.outputShape=I.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s`T${f}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let m=1;m= ${o[m-1]}) { return getChannel( getT${m}(${sh(i,l,f)}), vec2(${sh(u,l,f)})); }`}let p=o.length,h=o[o.length-1];c+=` return getChannel( getT${p}(${sh(i,l,h)}), vec2(${sh(u,l,h)}));`,this.userCode=` float getValue(${i.map(m=>"int "+m)}) { ${c} } void main() { ${r} coords = getOutputCoords(); vec4 result = vec4(getValue(${s}), 0., 0., 0.); ${s[n-1]} = ${s[n-1]} + 1; if (${s[n-1]} < ${a[n-1]}) { result.g = getValue(${s}); } ${s[n-2]} = ${s[n-2]} + 1; if (${s[n-2]} < ${a[n-2]}) { result.a = getValue(${s}); } ${s[n-1]} = ${s[n-1]} - 1; if (${s[n-2]} < ${a[n-2]} && ${s[n-1]} < ${a[n-1]}) { result.b = getValue(${s}); } setOutput(result); } `}};function sh(e,t,a){let n=e.indexOf(t);return e.map((r,s)=>s===n?`${r} - ${a}`:r).join()}function h0(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.texData.get(n.dataId);return tn({inputs:{x:r.complexTensorInfos.imag},backend:a})}var OK={kernelName:Cp,backendName:"webgl",kernelFunc:h0};function Od(e,t,a){let n=e[0].dtype;if(n==="complex64"){let h=e.map(x=>sc({inputs:{input:x},backend:a})),m=e.map(x=>h0({inputs:{input:x},backend:a})),f=Od(h,t,a),g=Od(m,t,a),y=zs({inputs:{real:f,imag:g},backend:a});return h.forEach(x=>a.disposeIntermediateTensorInfo(x)),m.forEach(x=>a.disposeIntermediateTensorInfo(x)),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(g),y}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let h=e.map(b=>{let w=[-1,v.sizeFromShape(b.shape.slice(t))];return pe({inputs:{x:b},backend:a,attrs:{shape:w}})}),m=h.map(b=>({vals:a.readSync(b.dataId),shape:b.shape})),f=I.computeOutShape(h.map(b=>b.shape),1),g=h[0].shape[0]===1,y=Sj(m,f,n,g),x=I.computeOutShape(e.map(b=>b.shape),t),A=a.makeTensorInfo(x,n,y);return h.forEach(b=>a.disposeIntermediateTensorInfo(b)),A}let s=e.filter(h=>v.sizeFromShape(h.shape)>0),i=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let h=i?new Qn(e[0].shape,jr):new Zr(e[0].shape,jr);return a.runWebGLProgram(h,e,n)}let o=B().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let h=[];for(let f=0;fm.shape),t);return a.runWebGLProgram(h,s,n)}let{tensors2D:l,outShape:u}=zK(s,t,a),d=new PK(l.map(h=>h.shape)),c=a.runWebGLProgram(d,l,n);l.forEach(h=>a.disposeIntermediateTensorInfo(h));let p=pe({inputs:{x:c},attrs:{shape:u},backend:a});return a.disposeIntermediateTensorInfo(c),p}function zK(e,t,a){let n=I.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>pe({inputs:{x:r},attrs:{shape:[-1,v.sizeFromShape(r.shape.slice(t))]},backend:a})),outShape:n}}function Hw(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);I.assertParamsConsistent(i,s);let o=I.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?tn({inputs:{x:l[0]},backend:a}):Od(l,s,a)}var LK={kernelName:xu,backendName:"webgl",kernelFunc:Hw},jw=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,d=e.dilationWidth,c=e.filterHeight,p=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4,f=e.dataFormat==="channelsLast",g=f?1:2,y=f?2:3,x=f?3:1,A="",b="";a&&(n?A=`float activation(float a) { float b = getPreluActivationWeightsAtOutCoords(); ${a} }`:r?A=`float activation(float a) { float b = getLeakyreluAlphaAtOutCoords(); ${a} }`:A=` float activation(float x) { ${a} } `,b="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${A} const ivec2 strides = ivec2(${o}, ${l}); const ivec2 pads = ivec2(${s}, ${i}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d2 = coords[${x}]; ivec2 xRCCorner = ivec2(coords[${g}], coords[${y}]) * strides - pads; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wR = 0; wR < ${c}; wR++) { int xR = xRCorner + wR * ${u}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${p}; wC++) { int xC = xCCorner + wC * ${d}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } for (int d1 = 0; d1 < ${h}; d1 += 4) { vec4 wValues = vec4( getW(wR, wC, d1, d2), getW(wR, wC, d1 + 1, d2), getW(wR, wC, d1 + 2, d2), getW(wR, wC, d1 + 3, d2) ); if (${f}) { 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 (${m===1}) { if (${f}) { dotProd += getX(batch, xR, xC, ${h}) * getW(wR, wC, ${h}, d2); } else { dotProd += getX(batch, ${h}, xR, xC) * getW(wR, wC, ${h}, d2); } } else if (${m===2}) { vec2 wValues = vec2( getW(wR, wC, ${h}, d2), getW(wR, wC, ${h} + 1, d2) ); if (${f}) { vec2 xValues = vec2( getX(batch, xR, xC, ${h}), getX(batch, xR, xC, ${h} + 1) ); dotProd += dot(xValues, wValues); } else { vec2 xValues = vec2( getX(batch, ${h}, xR, xC), getX(batch, ${h} + 1, xR, xC) ); dotProd += dot(xValues, wValues); } } else if (${m===3}) { vec3 wValues = vec3( getW(wR, wC, ${h}, d2), getW(wR, wC, ${h} + 1, d2), getW(wR, wC, ${h} + 2, d2) ); if (${f}) { vec3 xValues = vec3( getX(batch, xR, xC, ${h}), getX(batch, xR, xC, ${h} + 1), getX(batch, xR, xC, ${h} + 2) ); dotProd += dot(xValues, wValues); } else { vec3 xValues = vec3( getX(batch, ${h}, xR, xC), getX(batch, ${h} + 1, xR, xC), getX(batch, ${h} + 2, xR, xC) ); dotProd += dot(xValues, wValues); } } } } float result = dotProd; ${w} ${b} setOutput(result); } `}},WK=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,a=e.padInfo.top,n=e.padInfo.left,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,d=e.filterDepth,c=e.filterHeight,p=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4;this.userCode=` const ivec3 strides = ivec3(${r}, ${s}, ${i}); const ivec3 pads = ivec3(${t}, ${a}, ${n}); 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 < ${d}; wF++) { int xF = xFCorner + wF * ${o}; if (xF < 0 || xF >= ${e.inDepth}) { continue; } for (int wR = 0; wR < ${c}; wR++) { int xR = xRCorner + wR * ${l}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${p}; wC++) { int xC = xCCorner + wC * ${u}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } for (int d1 = 0; d1 < ${h}; d1 += 4) { vec4 xValues = vec4( getX(batch, xF, xR, xC, d1), getX(batch, xF, xR, xC, d1 + 1), getX(batch, xF, xR, xC, d1 + 2), getX(batch, xF, xR, xC, d1 + 3) ); vec4 wValues = vec4( getW(wF, wR, wC, d1, d2), getW(wF, wR, wC, d1 + 1, d2), getW(wF, wR, wC, d1 + 2, d2), getW(wF, wR, wC, d1 + 3, d2) ); dotProd += dot(xValues, wValues); } if (${m===1}) { dotProd += getX(batch, xF, xR, xC, ${h}) * getW(wF, wR, wC, ${h}, d2); } else if (${m===2}) { vec2 xValues = vec2( getX(batch, xF, xR, xC, ${h}), getX(batch, xF, xR, xC, ${h} + 1) ); vec2 wValues = vec2( getW(wF, wR, wC, ${h}, d2), getW(wF, wR, wC, ${h} + 1, d2) ); dotProd += dot(xValues, wValues); } else if (${m===3}) { vec3 xValues = vec3( getX(batch, xF, xR, xC, ${h}), getX(batch, xF, xR, xC, ${h} + 1), getX(batch, xF, xR, xC, ${h} + 2) ); vec3 wValues = vec3( getW(wF, wR, wC, ${h}, d2), getW(wF, wR, wC, ${h} + 1, d2), getW(wF, wR, wC, ${h} + 2, d2) ); dotProd += dot(xValues, wValues); } } } } setOutput(dotProd); } `}},qw=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ga(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,d=u,c=` int xR; int xC; int xCOffset; vec4 wTexel; vec4 previous; vec4 final;`;for(let f=0;f=0 && xR < inDims[0]) { `;for(let f=0;f<(d+1)/2;f++){let g=f*2;if(c+=` xC = xCCorner + ${g*o}; `,i===1){if(g= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) { xTexelC${g} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${g}.zw = vec2(0.0); } xTexelC${g}Ready = 1; } `,o===1&&g>0?c+=` xC${g} = vec4(xTexelC${g-2}.zw, xTexelC${g}.xy); `:c+=` xCOffset = xC + 1 - 2; if (xCOffset >= 0 && xCOffset < inDims[1]) { previous = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { previous.zw = vec2(0.0); } xC${g} = vec4(previous.zw, xTexelC${g}.xy); } else { xC${g} = vec4(0.0, 0.0, xTexelC${g}.xy); } `):c+=` if (xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) { xTexelC${g} = getX(batch, xR, xC, d1); if (xC + 1 >= inDims[1]) { xTexelC${g}.zw = vec2(0.0); } xTexelC${g}Ready = 1; } xC${g} = xTexelC${g}; `,g+1= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) { xTexelC${g+1} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${g+1}.zw = vec2(0.0); } xTexelC${g+1}Ready = 1; } `,o>1?c+=` xCOffset -= 2; if (xCOffset >= 0 && xCOffset < inDims[1]) { previous = getX(batch, xR, xCOffset, d1); xC${g+1} = vec4(previous.zw, xTexelC${g+1}.xy); } else { xC${g+1} = vec4(0.0, 0.0, xTexelC${g+1}.xy); } `:c+=` xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.xy); `):y===1?c+=` xC${g+1} = xTexelC${g}; `:c+=` xCOffset = xC + ${y}; if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) { xTexelC${g+1} = getX(batch, xR, xCOffset, d1); if (xCOffset + 1 >= inDims[1]) { xTexelC${g+1}.zw = vec2(0.0); } xTexelC${g+1}Ready = 1; } xC${g+1} = xTexelC${g+1}; `}}else g= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) { xTexelC${g} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${g}.zw = vec2(0.0); } xTexelC${g}Ready = 1; } if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${g+1}Ready == 0) { xTexelC${g+1} = getX(batch, xR, xC + 1, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xC + 2 >= inDims[1]) { xTexelC${g+1}.zw = vec2(0.0); } xTexelC${g+1}Ready = 1; } xC${g} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw); `,g+1= 0 && xCOffset < inDims[1]) { final = getX(batch, xR, xCOffset, d1); } xC${g+1} = vec4(xTexelC${g+1}.xy, final.xy); `)):(c+=` if(xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) { xTexelC${g} = getX(batch, xR, xC, d1); if (xC + 1 >= inDims[1]) { xTexelC${g}.zw = vec2(0.0); } xTexelC${g}Ready = 1; } xCOffset = xC + strides[1]; if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) { xTexelC${g+1} = getX(batch, xR, xCOffset, d1); if (xCOffset + 1 >= inDims[1]) { xTexelC${g+1}.zw = vec2(0.); } xTexelC${g+1}Ready = 1; } xC${g} = vec4( xTexelC${g}.xy, xTexelC${g+1}.xy); `,g+1= 0) { // Use custom imod instead mod. On Intel GPU, mod may generate // unexpected value. // https://github.com/tensorflow/tfjs/issues/5447 offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1]; d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) / inChannels); if(d1 < inputShape[${i}] && d1 >= 0) { ch = imod(pos, inChannels); if (${r}) { innerDims = vec2(d1, ch); result[${u*2+d}] = getChannel( getA(rc.x, d0, int(innerDims.x), int(innerDims.y)), innerDims); } else { innerDims = vec2(d0, d1); result[${u*2+d}] = getChannel( getA(rc.x, ch, int(innerDims.x), int(innerDims.y)), innerDims); } } } } `;this.userCode=` void main() { ivec3 rc = getOutputCoords(); vec4 result = vec4(0); int blockIndex, pos, offsetY, d0, offsetX, d1, ch; vec2 innerDims; ${l} ${n.output} = result; } `}};function Eh(e,t){let a=e.length;return a>=3?t?[...e.slice(0,-3),e[a-3]*e[a-2],e[a-1]]:[...e.slice(0,-3),e[a-3],e[a-2]*e[a-1]]:!t&&a===1&&e[0]>1?[e[0],1]:null}function Xw({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=n.texData.get(e.dataId),d=a.inChannels,c=l[0]*l[1]*l[2],p=a.outChannels,h=a.dataFormat==="channelsLast",m=!1,f=!1,g,y=[];if(s!=null){let x=Eh(s.shape,h);x!=null&&(s=pe({inputs:{x:s},backend:n,attrs:{shape:x}}),y.push(s))}if(r!=null){let x=Eh(r.shape,h);x!=null&&(r=pe({inputs:{x:r},backend:n,attrs:{shape:x}}),y.push(r))}if(!((c===1||p===1)&&d>Ww)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let x=l[0]*l[1]*(l[2]+1),A={dataId:e.dataId,shape:[1,x,a.inChannels],dtype:e.dtype},b=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(ip(u.shape,A.shape),()=>`packed reshape ${u.shape} to ${A.shape} isn't free`);let w=pe({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});y.push(w);let S=Rh({a:A,b:w,backend:n,transposeA:m,transposeB:f,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),C=n.texData.get(S.dataId);v.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=b,C.shape=a.outShape,g=tn({inputs:{x:S},backend:n}),g.shape=a.outShape,y.push(S)}else{let x=a.outHeight*a.outWidth,A=pe({inputs:{x:e},backend:n,attrs:{shape:h?[a.batchSize,x,a.inChannels]:[a.batchSize,a.inChannels,x]}}),b=pe({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}}),w=Rh({a:h?A:b,b:h?b:A,transposeA:!h,transposeB:f,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=pe({inputs:{x:w},backend:n,attrs:{shape:a.outShape}}),y.push(A),y.push(b),y.push(w)}for(let x of y)n.disposeIntermediateTensorInfo(x);return g}function Kw({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:d,outWidth:c,outHeight:p,dataFormat:h}=a,m=h==="channelsLast",f=l*u*d,g=p*c,y=[a.batchSize,f,g],x=!0,A=!1,b=[];if(s!=null){let G=Eh(s.shape,m);G!=null&&(s=pe({inputs:{x:s},backend:n,attrs:{shape:G}}),b.push(s))}if(r!=null){let G=Eh(r.shape,m);G!=null&&(r=pe({inputs:{x:r},backend:n,attrs:{shape:G}}),b.push(r))}let w=pe({inputs:{x:t},backend:n,attrs:{shape:[1,f,v.sizeFromShape(t.shape)/f]}});b.push(w);let S=new BK(y,a),C=[e.shape,[a.padInfo.top,a.padInfo.left],[a.strideHeight,a.strideWidth],[a.dilationHeight,a.dilationWidth],[a.inChannels],[a.filterWidth*a.inChannels],[a.outWidth]],N=n.runWebGLProgram(S,[e],"float32",C),M=pe({inputs:{x:N},backend:n,attrs:{shape:y}});b.push(N),b.push(M);let F=r!=null,E=s!=null,T=o==="leakyrelu",D=o?op(o,!0):null,O=new Lw(m?M.shape:w.shape,m?w.shape:M.shape,m?[a.batchSize,g,a.outChannels]:[a.batchSize,a.outChannels,g],x,A,F,D,E,T),W=m?[M,w]:[w,M];if(r&&W.push(r),E&&W.push(s),T){let G=n.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));W.push(G),b.push(G)}let $=n.runWebGLProgram(O,W,"float32"),U=pe({inputs:{x:$},backend:n,attrs:{shape:a.outShape}});b.push($);for(let G of b)n.disposeIntermediateTensorInfo(G);return U}function VK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:d}=n,c=I.convertConv2DDataFormat(l),p=I.computeConv2DInfo(r.shape,s.shape,i,u,o,d,!1,c),h;if(p.filterHeight===1&&p.filterWidth===1&&p.dilationHeight===1&&p.dilationWidth===1&&p.strideHeight===1&&p.strideWidth===1&&(p.padInfo.type==="SAME"||p.padInfo.type==="VALID"))h=Xw({x:r,filter:s,convInfo:p,backend:a});else if(p.strideWidth<=2&&c==="channelsLast"&&B().getBool("WEBGL_EXP_CONV")){let f=new qw(p),g=[[p.padInfo.top,p.padInfo.left],[p.strideHeight,p.strideWidth],[p.dilationHeight,p.dilationWidth],[p.inHeight,p.inWidth]];h=a.runWebGLProgram(f,[r,s],"float32",g)}else if(B().getBool("WEBGL_CONV_IM2COL"))h=Kw({x:r,filter:s,convInfo:p,backend:a});else{let f=new jw(p);h=a.runWebGLProgram(f,[r,s],"float32")}let m=pe({inputs:{x:h},backend:a,attrs:{shape:p.outShape}});return a.disposeIntermediateTensorInfo(h),m}var UK={kernelName:Xi,backendName:"webgl",kernelFunc:VK},GK=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,a=e.strideWidth,n=e.padInfo.top,r=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} - ${n}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC < ${e.outWidth}; yC++) { int xC = wC + yC * ${a} - ${r}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } ${s?`float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue);`:`float dyValue = getDy(b, d2, yR, yC); float xValue = getX(b, d1, xR, xC); dotProd += (xValue * dyValue);`} } } } setOutput(dotProd); } `}},HK=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=a-1-e.padInfo.left,l=s?1:2,u=s?2:3,d=s?3:1;this.userCode=` const ivec2 pads = ivec2(${i}, ${o}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d1 = coords[${d}]; ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads; int dyRCorner = dyCorner.x; int dyCCorner = dyCorner.y; // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wR = 0; wR < ${t}; wR++) { float dyR = float(dyRCorner + wR) / ${n}.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 < ${a}; wC++) { float dyC = float(dyCCorner + wC) / ${r}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); int wCPerm = ${a} - 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); } `}},jK=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,a=e.strideHeight,n=e.strideWidth,r=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} - ${r}; if (xF < 0 || xF >= ${e.inDepth}) { continue; } for (int yR = 0; yR < ${e.outHeight}; yR++) { int xR = wR + yR * ${a} - ${s}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC < ${e.outWidth}; yC++) { int xC = wC + yC * ${n} - ${i}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yF, yR, yC, d2); float xValue = getX(b, xF, xR, xC, d1); dotProd += (xValue * dyValue); } } } } setOutput(dotProd); } `}},qK=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,a=e.filterHeight,n=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=a-1-e.padInfo.top,u=n-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${o}, ${l}, ${u}); void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int d1 = coords.u; ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads; int dyFCorner = dyCorner.x; int dyRCorner = dyCorner.y; int dyCCorner = dyCorner.z; float dotProd = 0.0; for (int wF = 0; wF < ${t}; wF++) { float dyF = float(dyFCorner + wF) / ${r}.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 < ${a}; 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 = ${a} - 1 - wR; for (int wC = 0; wC < ${n}; 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 = ${n} - 1 - wC; for (int d2 = 0; d2 < ${e.outChannels}; d2++) { float xValue = getDy(batch, idyF, idyR, idyC, d2); float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2); dotProd += xValue * wValue; } } } } setOutput(dotProd); } `}};function XK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:d}=n,c=I.convertConv2DDataFormat(l),p=I.computeConv2DInfo(r.shape,d,i,1,o,u,!1,c),h=new GK(p);return a.runWebGLProgram(h,[r,s],"float32")}var KK={kernelName:bp,backendName:"webgl",kernelFunc:XK},YK=class{constructor(e){this.variableNames=["dy","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"strides",type:"vec2"}],this.outputShape=e.inShape,this.enableShapeUniforms=ga(this.outputShape.length);let t=e.filterHeight,a=e.filterWidth,n=t-1-e.padInfo.top,r=a-1-e.padInfo.left;this.userCode=` const ivec2 pads = ivec2(${n}, ${r}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d1 = coords[3]; ivec2 dyCorner = ivec2(coords[1], coords[2]) - pads; int dyRCorner = dyCorner.x; int dyCCorner = dyCorner.y; vec4 result = vec4(0.); for (int wR = 0; wR < ${t}; wR++) { float dyR = float(dyRCorner + wR) / strides[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 < ${a}; wC++) { int wCPerm = ${a} - 1 - wC; float dyC = float(dyCCorner + wC) / strides[1]; bool idyCVal = (dyC >= 0.0) && (dyC < ${e.outWidth}.0) && (fract(dyC) == 0.0); int idyC = int(dyC); float dyC2 = float(dyCCorner + wC + 1) / strides[1]; bool idyCVal2 = (dyC2 >= 0.0) && (dyC2 < ${e.outWidth}.0) && (fract(dyC2) == 0.0); int idyC2 = int(dyC2); if (idyCVal && idyCVal2) { for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) { vec4 wValue = getW(wRPerm, wCPerm, d1, d2); vec4 dySample = getDy(batch, idyR, idyC, d2); vec4 dySample2 = (idyC / 2 == idyC2 / 2) ? dySample : getDy(batch, idyR, idyC2, d2); vec2 dyValue = mod(float(idyC), 2.) == 0. ? dySample.xy : dySample.zw; result.xy += vec2(dot(dyValue, wValue.xy), dot(dyValue, wValue.zw)); dyValue = mod(float(idyC2), 2.) == 0. ? dySample2.xy : dySample2.zw; result.zw += vec2(dot(dyValue, wValue.xy), dot(dyValue, wValue.zw)); } } else if (idyCVal) { for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) { vec4 wValue = getW(wRPerm, wCPerm, d1, d2); vec4 dySample = getDy(batch, idyR, idyC, d2); vec2 dyValue = mod(float(idyC), 2.) == 0. ? dySample.xy : dySample.zw; result.xy += vec2(dot(dyValue, wValue.xy), dot(dyValue, wValue.zw)); } } else if (idyCVal2) { for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) { vec4 wValue = getW(wRPerm, wCPerm, d1, d2); vec4 dySample = getDy(batch, idyR, idyC2, d2); vec2 dyValue = mod(float(idyC2), 2.) == 0. ? dySample.xy : dySample.zw; result.zw += vec2(dot(dyValue, wValue.xy), dot(dyValue, wValue.zw)); } } } } setOutput(result); } `}};function ZK(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:d}=n,c=I.convertConv2DDataFormat(u),p=I.computeConv2DInfo(i,s.shape,o,1,l,d,!1,c);if(B().getBool("WEBGL_PACK_CONV2DTRANSPOSE")&&c==="channelsLast"){let h=[[p.strideHeight,p.strideWidth]],m=new YK(p);return a.runWebGLProgram(m,[r,s],"float32",h)}else{let h=new HK(p);return a.runWebGLProgram(h,[r,s],"float32")}}var JK={kernelName:Ki,backendName:"webgl",kernelFunc:ZK};function QK(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=I.computeConv3DInfo(r.shape,s.shape,i,l,o),d=new WK(u);return a.runWebGLProgram(d,[r,s],"float32")}var eY={kernelName:Yi,backendName:"webgl",kernelFunc:QK};function tY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=I.computeConv3DInfo(r.shape,l,i,1,o),d=new jK(u);return a.runWebGLProgram(d,[r,s],"float32")}var aY={kernelName:Au,backendName:"webgl",kernelFunc:tY};function nY(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=n,u=I.computeConv3DInfo(l,s.shape,o,1,i),d=new qK(u);return a.runWebGLProgram(d,[r,s],"float32")}var rY={kernelName:Zi,backendName:"webgl",kernelFunc:nY},sY=rd+` return cos(x); `,iY=` vec4 result = cos(x); bvec4 isNaN = isnan(x); ${cl} return result; `,oY=tt({opSnippet:sY,packedOpSnippet:iY}),lY={kernelName:Ji,backendName:"webgl",kernelFunc:oY},uY=` float e2x = exp(-x); return (e2x + 1.0 / e2x) / 2.0; `,dY=tt({opSnippet:uY}),pY={kernelName:Qi,backendName:"webgl",kernelFunc:dY},cY=class{constructor(e,t,a,n,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[d,c]=a;this.outputShape=[u,d,c,l];let p=n==="bilinear"?1:0,[h,m]=[`${i-1}.0`,`${o-1}.0`],[f,g,y]=d>1?[`${(i-1)/(d-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[x,A,b]=c>1?[`${(o-1)/(c-1)}`,"(x2-x1) * width_ratio",`x1*${m} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${m}`];this.userCode=` const float height_ratio = float(${f}); const float width_ratio = float(${x}); 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 = ${g}; float width_scale = ${A}; float in_y = ${y}; if( in_y < 0.0 || in_y > ${h} ) { setOutput(float(${r})); return; } float in_x = ${b}; if( in_x < 0.0 || in_x > ${m} ) { setOutput(float(${r})); return; } vec2 sourceFracIndexCR = vec2(in_x,in_y); if(${p} == 1) { // Compute the four integer indices. ivec2 sourceFloorCR = ivec2(sourceFracIndexCR); ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR)); float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d); float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d); float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d); float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d); vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR); float top = topLeft + (topRight - topLeft) * fracCR.x; float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x; float newValue = top + (bottom - top) * fracCR.y; setOutput(newValue); } else { // Compute the coordinators of nearest neighbor point. ivec2 sourceNearestCR = ivec2(floor( sourceFracIndexCR + vec2(0.5,0.5))); float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d); setOutput(newValue); } } `}},hY=e=>{let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,d=new cY(r.shape,s.shape,o,l,u);return a.runWebGLProgram(d,[r,s,i],"float32")},mY={kernelName:ao,backendName:"webgl",kernelFunc:hY},up;(function(e){e.Prod="*",e.Sum="+"})(up||(up={}));var Y5=class{constructor(e,t,a,n){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,s=this.op===up.Prod?"1.0":"0.0",i=a?s:`getX(${Z5(r,"coords",this.op)})`,o=this.outputShape[this.outputShape.length-1],l="",u="";a?(l=n?`end != ${o-1}`:"end != 0",u=n?"end + 1":"end - 1"):(l=n?`end + pow2 < ${o}`:"end >= pow2",u=n?"end + pow2":"end - pow2"),this.userCode=` void main() { ${ft(r)} coords = getOutputCoords(); int end = ${J5(r,"coords",this.op)}; float val = ${i}; int pow2 = int(pow(2.0, index)); if (${l}) { int idx = ${u}; ${J5(r,"coords",this.op)} = idx; val ${this.op}= getX(${Z5(r,"coords",this.op)}); } setOutput(val); } `}};function Z5(e,t,a){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 new Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function J5(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function Yw(e,t,a,n,r,s){let i=t.shape.length,o=I.getAxesPermutation([n],i),l=t;o!=null&&(l=Ta({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=I.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let d=l.shape[u],c=tn({inputs:{x:l},backend:a});for(let p=0;p<=Math.ceil(Math.log2(d))-1;p++){let h=new Y5(e,l.shape,!1,s),m=[[p]],f=c;c=a.runWebGLProgram(h,[c],c.dtype,m),a.disposeIntermediateTensorInfo(f)}if(r){let p=new Y5(e,l.shape,r,s),h=c;c=a.runWebGLProgram(p,[c],c.dtype),a.disposeIntermediateTensorInfo(h)}if(o!=null){let p=I.getUndoAxesPermutation(o),h=Ta({inputs:{x:c},backend:a,attrs:{perm:p}});return a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(l),h}return c}function fY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return Yw(up.Prod,r,a,s,i,o)}var gY={kernelName:eo,backendName:"webgl",kernelFunc:fY};function yY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return Yw(up.Sum,r,a,s,i,o)}var xY={kernelName:to,backendName:"webgl",kernelFunc:yY};function AY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n;if(r.shape.length===1){let l=a.readSync(r.dataId),u=a.readSync(s.dataId),d=Nw(l,u,s.dtype,s.shape,i);return a.makeTensorInfo([i],s.dtype,d)}else if(r.shape.length===2){let l=a.bufferSync(r),u=a.bufferSync(s),d=vj(l,u,i,o);return a.makeTensorInfo(d.shape,s.dtype,d.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var bY={kernelName:bu,backendName:"webgl",kernelFunc:AY},vY=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=a,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 wY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],d=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,p=u*s,h=d/(s*s),m=i==="NHWC"?[o,c,p,h]:[o,h,c,p],f=new vY(m,s,i);return a.runWebGLProgram(f,[r],r.dtype)}var kY={kernelName:no,backendName:"webgl",kernelFunc:wY},Zw=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ga(this.outputShape.length);let s=e.filterHeight,i=e.filterWidth,o=e.outChannels/e.inChannels,l="",u="";a&&(n?l=`float activation(float a) { float b = getPreluActivationWeightsAtOutCoords(); ${a} }`:r?l=`float activation(float a) { float b = getLeakyreluAlphaAtOutCoords(); ${a} }`:l=` float activation(float x) { ${a} } `,u="result = activation(result);");let d=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${l} void main() { ivec4 coords = getOutputCoords(); int batch = coords.x; ivec2 xRCCorner = coords.yz * strides - pads; int d2 = coords.w; int d1 = d2 / ${o}; int q = d2 - d1 * ${o}; 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 < ${s}; wR++) { int xR = xRCorner + wR * dilations[0]; if (xR < 0 || xR >= inDims[0]) { continue; } for (int wC = 0; wC < ${i}; wC++) { int xC = xCCorner + wC * dilations[1]; if (xC < 0 || xC >= inDims[1]) { continue; } float xVal = getX(batch, xR, xC, d1); float wVal = getW(wR, wC, d1, q); dotProd += xVal * wVal; } } float result = dotProd; ${d} ${u} setOutput(result); } `}},Jw=class{constructor(e,t=!1,a=null,n=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ga(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,d=e.filterWidth,c=d,p=` int xR; int xC; int xCOffset; vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g=0 && xR < inDims[0]) { `;for(let g=0;g<(c+1)/2;g++){let y=g*2;if(p+=` xC = xCCorner + ${y*l}; `,o===1){if(y= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) { xTexelC${y} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${y}.zw = vec2(0.0); } xTexelC${y}Ready = 1; } `,l===1&&y>0?p+=` xC${y} = vec4(xTexelC${y-2}.zw, xTexelC${y}.xy); `:p+=` xCOffset = xC + 1 - 2; if (xCOffset >= 0 && xCOffset < inDims[1]) { previous = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { previous.zw = vec2(0.0); } xC${y} = vec4(previous.zw, xTexelC${y}.xy); } else { xC${y} = vec4(0.0, 0.0, xTexelC${y}.xy); } `):p+=` if (xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) { xTexelC${y} = getX(batch, xR, xC, d1); if (xC + 1 >= inDims[1]) { xTexelC${y}.zw = vec2(0.0); } xTexelC${y}Ready = 1; } xC${y} = xTexelC${y}; `,y+1= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) { xTexelC${y+1} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${y+1}.zw = vec2(0.0); } xTexelC${y+1}Ready = 1; } `,l>1?p+=` xCOffset -= 2; if (xCOffset >= 0 && xCOffset < inDims[1]) { previous = getX(batch, xR, xCOffset, d1); xC${y+1} = vec4(previous.zw, xTexelC${y+1}.xy); } else { xC${y+1} = vec4(0.0, 0.0, xTexelC${y+1}.xy); } `:p+=` xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.xy); `):x===1?p+=` xC${y+1} = xTexelC${y}; `:p+=` xCOffset = xC + ${x}; if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) { xTexelC${y+1} = getX(batch, xR, xCOffset, d1); if (xCOffset + 1 >= inDims[1]) { xTexelC${y+1}.zw = vec2(0.0); } xTexelC${y+1}Ready = 1; } xC${y+1} = xTexelC${y+1}; `}}else y= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) { xTexelC${y} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${y}.zw = vec2(0.0); } xTexelC${y}Ready = 1; } if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${y+1}Ready == 0) { xTexelC${y+1} = getX(batch, xR, xC + 1, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xC + 2 >= inDims[1]) { xTexelC${y+1}.zw = vec2(0.0); } xTexelC${y+1}Ready = 1; } xC${y} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw); `,y+1= 0 && xCOffset < inDims[1]) { final = getX(batch, xR, xCOffset, d1); } xC${y+1} = vec4(xTexelC${y+1}.xy, final.xy); `)):(p+=` if(xC >= 0 && xC < inDims[1] && xTexelC${y}Ready == 0) { xTexelC${y} = getX(batch, xR, xC, d1); if (xC + 1 >= inDims[1]) { xTexelC${y}.zw = vec2(0.0); } xTexelC${y}Ready = 1; } xCOffset = xC + strides[1]; if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y+1}Ready == 0) { xTexelC${y+1} = getX(batch, xR, xCOffset, d1); if (xCOffset + 1 >= inDims[1]) { xTexelC${y+1}.zw = vec2(0.); } xTexelC${y+1}Ready = 1; } xC${y} = vec4( xTexelC${y}.xy, xTexelC${y+1}.xy); `,y+1`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${d}'`);let c=I.computeConv2DInfo(r.shape,s.shape,i,d,o,u,!0),p;B().getBool("WEBGL_PACK_DEPTHWISECONV")&&c.strideWidth<=2&&c.outChannels/c.inChannels===1?p=new Jw(c):p=new Zw(c);let h=[[c.padInfo.top,c.padInfo.left],[c.strideHeight,c.strideWidth],[c.dilationHeight,c.dilationWidth],[c.inHeight,c.inWidth]];return a.runWebGLProgram(p,[r,s],"float32",h)}var SY={kernelName:ro,backendName:"webgl",kernelFunc:IY},TY=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,a=e.strideWidth,n=e.padInfo.top,r=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} - ${n}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC < ${e.outWidth}; yC++) { int xC = wC + yC * ${a} - ${r}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue); } } } setOutput(dotProd); } `}},CY=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,a=e.filterWidth,n=e.strideHeight,r=e.strideWidth,s=t-1-e.padInfo.top,i=a-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=` const ivec2 pads = ivec2(${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) / ${n}.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 < ${a}; wC++) { float dyC = float(dyCCorner + wC) / ${r}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); int wCPerm = ${a} - 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 NY(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:d}=n,c=I.computeConv2DInfo(r.shape,d,i,o,l,u,!0),p=new TY(c);return a.runWebGLProgram(p,[r,s],"float32")}var RY={kernelName:vp,backendName:"webgl",kernelFunc:NY};function EY(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:d}=n,c=I.computeConv2DInfo(d,s.shape,i,o,l,u,!0),p=new CY(c);return a.runWebGLProgram(p,[r,s],"float32")}var MY={kernelName:wp,backendName:"webgl",kernelFunc:EY},FY=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 $Y(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=pe({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new FY(s),l=a.runWebGLProgram(o,[i],i.dtype),u=pe({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(l),u}var DY={kernelName:vu,backendName:"webgl",kernelFunc:$Y},PY=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:a,padInfo:n,strideHeight:r,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:d,left:c}=n;this.userCode=` const ivec2 strides = ivec2(${r}, ${s}); const ivec2 pads = ivec2(${d}, ${c}); 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 * ${u}; if (wIn >= 0 && wIn < ${a}) { 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 _Y(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=I.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),d,c=new PY(u);d=a.runWebGLProgram(c,[r,s],"float32");let p=pe({inputs:{x:d},backend:a,attrs:{shape:u.outShape}});return a.disposeIntermediateTensorInfo(d),p}var OY={kernelName:so,backendName:"webgl",kernelFunc:_Y};function zY(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=I.decodeEinsumEquation(r,s.length);I.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:d}=I.getEinsumComputePath(o,l),c=d.length,p=null,h=i.length,m=[];for(let f=0;f=0&&(p=c0({inputs:{x:p},backend:a,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(p)),h--)}for(let f of m)f!==p&&a.disposeIntermediateTensorInfo(f);return p}var LY={kernelName:Ip,backendName:"webgl",kernelFunc:zY},WY="return (x >= 0.0) ? x : (exp(x) - 1.0);",BY=` 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; `,VY=tt({opSnippet:WY,packedOpSnippet:BY}),UY={kernelName:oo,backendName:"webgl",kernelFunc:VY},GY="return (b >= 0.0) ? a : a * (b + 1.0);",HY=` vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.))); return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0)))); `,jY=e=>{let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new nd(HY,n.shape,r.shape):new Ei(GY,n.shape,r.shape);return a.runWebGLProgram(s,[n,r],n.dtype)},qY={kernelName:wu,backendName:"webgl",kernelFunc:jY},XY=` return vec4(equal(a, b)); `,KY="return float(a == b);",YY=ha({opSnippet:KY,packedOpSnippet:XY,dtype:"bool",cpuKernelImpl:Tj}),ZY={kernelName:ms,backendName:"webgl",kernelFunc:YY},JY=` // Error function is calculated approximately with elementary function. // See "Handbook of Mathematical Functions with Formulas, // Graphs, and Mathematical Tables", Abramowitz and Stegun. float p = ${I.ERF_P}; float a1 = ${I.ERF_A1}; float a2 = ${I.ERF_A2}; float a3 = ${I.ERF_A3}; float a4 = ${I.ERF_A4}; float a5 = ${I.ERF_A5}; float sign = sign(x); x = abs(x); float t = 1.0 / (1.0 + p * x); return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x)); `,QY=tt({opSnippet:JY}),eZ={kernelName:lo,backendName:"webgl",kernelFunc:QY},tZ=rd+` return exp(x); `,aZ=` vec4 result = exp(x); bvec4 isNaN = isnan(x); result.r = isNaN.r ? x.r : result.r; result.g = isNaN.g ? x.g : result.g; result.b = isNaN.b ? x.b : result.b; result.a = isNaN.a ? x.a : result.a; return result; `,Qw=tt({opSnippet:tZ,packedOpSnippet:aZ,cpuKernelImpl:Cj,dtype:"float32"}),nZ={kernelName:fs,backendName:"webgl",kernelFunc:Qw};function q1(e){let{inputs:t,attrs:a,backend:n}=e,{dim:r}=a,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),pe({inputs:{x:s},backend:n,attrs:{shape:o}})}var rZ={kernelName:ku,backendName:"webgl",kernelFunc:q1},Q5="return exp(x) - 1.0;",sZ=tt({opSnippet:Q5,packedOpSnippet:Q5,cpuKernelImpl:Nj}),iZ={kernelName:gs,backendName:"webgl",kernelFunc:sZ},eA=class{constructor(e,t,a){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let r=a?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=a?`${n}.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 = ${r}; float unaryOpComplex(float real, float expR, float imag, float expI) { ${i} } float mulMatDFT(int batch, int index) { float indexRatio = float(index) / float(${n}); float exponentMultiplierTimesIndexRatio = exponentMultiplier * indexRatio; float result = 0.0; for (int i = 0; i < ${n}; 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 e8(e,t,a){let n=a.texData.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=pe({inputs:{x:e},backend:a,attrs:{shape:[i,s]}}),l=o.shape,u=new eA("real",l,t),d=new eA("imag",l,t),c=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:l},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:l}],p=a.runWebGLProgram(u,c,"float32"),h=a.runWebGLProgram(d,c,"float32"),m=zs({inputs:{real:p,imag:h},backend:a});a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(h);let f=pe({inputs:{x:m},backend:a,attrs:{shape:e.shape}});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(m),f}function oZ(e){let{inputs:t,backend:a}=e,{input:n}=t;return e8(n,!1,a)}var lZ={kernelName:Sp,backendName:"webgl",kernelFunc:oZ},uZ=class{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode=` void main() { // Input can be obtained from uniform value. setOutput(value); 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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); } `}},NJ=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u=B().getBool("WEBGL_PACK_NORMALIZATION")?new CJ(r.shape,s,i,o,l):new TJ(r.shape,s,i,o,l);return a.runWebGLProgram(u,[r],r.dtype)},RJ={kernelName:ko,backendName:"webgl",kernelFunc:NJ},EJ=class{constructor(e,t,a,n,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=a,this.alpha=n,this.beta=r,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 = ${this.depth}; float norm = 0.0; for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) { if (k < depthBegin){ continue; } else if (k >= depthBegin && k < depthEnd) { norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k); } else { break; } } norm = float(${n}) * norm + float(${a}); for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){ if (k < depthBegin){ continue; } else if (k >= depthBegin && k < depthEnd){ float dyi = -2.0 * float(${n}) * float(${r}) * getInputImage(b, r, c, k) * getOutputImage(b, r, c, d) / norm; if (k == d) { dyi += pow(norm, -1.0 * ${r}); } if (k == coords[3]) { dyi *= getDy(b, r, c, d); result += dyi; } } else { break; } } } setOutput(result); } `}},MJ=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:d}=n,c=new EJ(r.shape,o,l,u,d);return a.runWebGLProgram(c,[r,s,i],r.dtype)},FJ={kernelName:Tu,backendName:"webgl",kernelFunc:MJ};function $J(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=pe({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=hl(i,e.dtype,"max",n),l=pe({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}function a8(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,d=I.getAxesPermutation(u,o),c=d!=null,p=a.shouldExecuteOnCPU([r]),h=r;if(c){if(p){let x=a.texData.get(h.dataId).values,A=new Array(o);for(let S=0;S`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let d=I.computePool2DInfo(r.shape,s,i,u,o,l);if(d.filterWidth===1&&d.filterHeight===1&&v.arraysEqual(d.inShape,d.outShape))return tn({inputs:{x:r},backend:a});let c=new lp(d,"max",!1);return a.runWebGLProgram(c,[r],r.dtype)}var WJ={kernelName:So,backendName:"webgl",kernelFunc:LJ};function BJ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=n,d=[1,1,1],c=I.computePool3DInfo(r.shape,s,i,d,o,u,l),p=new K3(c,"max",!1);return a.runWebGLProgram(p,[r],r.dtype)}var VJ={kernelName:Cu,backendName:"webgl",kernelFunc:BJ},UJ=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,a=e.strideWidth,n=e.dilationHeight,r=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=r-1-e.padInfo.top,o=s-1-e.padInfo.left,l=r*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 < ${r}; wR += ${n}) { 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) / ${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); 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 * ${s} + wC; float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0); dotProd += dyValue * mask; } } setOutput(dotProd); } `}},GJ=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,a=e.strideHeight,n=e.strideWidth,r=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,d=o-1-e.padInfo.front,c=l-1-e.padInfo.top,p=u-1-e.padInfo.left,h=o*l*u-1;this.userCode=` const ivec3 pads = ivec3(${d}, ${c}, ${p}); void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int ch = coords.u; ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads; int dyDCorner = dyCorner.x; int dyRCorner = dyCorner.y; int dyCCorner = dyCorner.z; // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get // dx(xD, xR, xC, ch). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wD = 0; wD < ${o}; wD += ${r}) { 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) / ${a}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); for (int wC = 0; wC < ${u}; wC += ${i}) { 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(batch, idyD, idyR, idyC, ch); int maxPosValue = ${h} - int(getMaxPos(batch, idyD, idyR, idyC, ch)); // Get the current value, check it against the value from the // position matrix. int curPosValue = wD * ${l} * ${u} + wR * ${u} + wC; float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0); dotProd += dyValue * mask; } } } setOutput(dotProd); } `}};function HJ(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:d}=n,c=[1,1,1],p=I.computePool3DInfo(i.shape,o,l,c,u,d),h=new K3(p,"max",!0),m=a.runWebGLProgram(h,[i],i.dtype),f=new GJ(p),g=a.runWebGLProgram(f,[r,m],i.dtype);return a.disposeIntermediateTensorInfo(m),g}var jJ={kernelName:Rp,backendName:"webgl",kernelFunc:HJ};function qJ(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;Ju([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:d,dimRoundingMode:c}=n,p=I.computePool2DInfo(o.shape,l,u,1,d,c),h=!0,m=new lp(p,"max",h),f=a.runWebGLProgram(m,[o],o.dtype),g=new UJ(p),y=a.runWebGLProgram(g,[r,f],o.dtype);return a.disposeIntermediateTensorInfo(f),y}var XJ={kernelName:Np,backendName:"webgl",kernelFunc:qJ};function KJ(e,t,a,n){let r=new lp(a,"max",!1),s=n.runWebGLProgram(r,[e],"float32");r=new lp(a,"max",!0,!0,t);let i=n.runWebGLProgram(r,[e],"float32");return[s,i]}var YJ={kernelName:Nu,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=a;v.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let u=[1,1];v.assert(I.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let d=I.computePool2DInfo(n.shape,r,s,u,i),[c,p]=KJ(n,o,d,l);return[c,p]}};function ZJ(e,t,a,n){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=pe({inputs:{x:e},attrs:{shape:[s,r]},backend:n}),o=hl(i,"float32","mean",n),l=pe({inputs:{x:o},attrs:{shape:a},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}var JJ={kernelName:To,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{keepDims:r,axis:s}=t,i=a,o=n.shape.length,l=v.parseAxisParam(s,n.shape),u=l,d=I.getAxesPermutation(u,o),c=d!=null,p=i.shouldExecuteOnCPU([n]),h=[],m=n;if(c){if(p){let A=i.texData.get(m.dataId).values,b=new Array(o);for(let C=0;Cu[0]+e[d]+u[1]);let n=e.length,r=ft(n),s=t.map(u=>u[0]).join(","),i=t.map((u,d)=>u[0]+e[d]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),l=a==="reflect"?0:1;if(n===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=` ${r} start = ${r}(${s}); ${r} end = ${r}(${i}); void main() { ${r} outC = getOutputCoords(); for (int i = 0; i < ${n}; 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}; } } ${r} coords = outC - start; setOutput(getX(${o})); } `}},iQ=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,m)=>h[0]+e[m]+h[1]);let n=e.length,r=ft(n),s=t.map(h=>h[0]).join(","),i=t.map((h,m)=>h[0]+e[m]).join(","),o=ka("rc",n),l=ka("source",n),u=`${o[n-1]} < ${this.outputShape[n-1]}`,d=n===1?"source":`vec2(${l.slice(-2).join()})`,c=a==="reflect"?0:1,p="";if(n===1){let h=` ${r} source = rc; if (source < start) { source = start * 2 - source - ${c}; } else if (source >= end) { source = (end - 1) * 2 - source + ${c}; } source -= start; `;p=` ${r} rc = outputLoc; ${h} result[0] = getChannel(getX(${l.join()}), ${d}); ${o[n-1]} += 1; if(${u}) { ${h} result[1] = getChannel(getX(${l.join()}), ${d}); } `}else{let h=` ${r} source = rc; ${r} lt = ${r}(lessThan(source, start)); ${r} gte = ${r}(greaterThanEqual(source, end)); ${r} orig = 1 - (lt + gte); source = orig * source + lt * (start * 2 - source - ${c}) + gte * ((end - 1) * 2 - source + ${c}); source -= start; `;p=` ${r} rc = outputLoc; ${h} result[0] = getChannel(getX(${l.join()}), ${d}); ${o[n-1]} += 1; if(${u}) { ${h} result[1] = getChannel(getX(${l.join()}), ${d}); } rc = outputLoc; ${o[n-2]} += 1; if(${o[n-2]} < ${this.outputShape[n-2]}) { ${h} result[2] = getChannel(getX(${l.join()}), ${d}); ${o[n-1]} += 1; if(${u}) { ${h} result[3] = getChannel(getX(${l.join()}), ${d}); } } `}this.userCode=` const ${r} start = ${r}(${s}); const ${r} end = ${r}(${i}); void main() { ${r} outputLoc = getOutputCoords(); vec4 result = vec4(0.); ${p} setOutput(result); } `}},oQ=({inputs:e,backend:t,attrs:a})=>{let{x:n}=e,{paddings:r,mode:s}=a,i=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new iQ(n.shape,r,s):new sQ(n.shape,r,s);return t.runWebGLProgram(i,[n],n.dtype)},lQ={kernelName:No,backendName:"webgl",kernelFunc:oQ},uQ=`if (b == 0.0) return NAN; return mod(a, b);`,dQ=` vec4 result = mod(a, b); bvec4 isNaN = equal(b, vec4(0.0)); `+cl+` return result; `,pQ=ha({opSnippet:uQ,packedOpSnippet:dQ}),cQ={kernelName:Ro,backendName:"webgl",kernelFunc:pQ},hQ=class{constructor(e,t,a){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,a],this.userCode=` 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})); } `}},mQ=` if (a == b) { return 1.0; }; return a / b;`,fQ=` // 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; `,n8=ha({opSnippet:mQ,packedOpSnippet:fQ,checkOutOfBounds:!0}),gQ={kernelName:io,backendName:"webgl",kernelFunc:n8},aA="return a - b;",r8=ha({opSnippet:aA,packedOpSnippet:aA,supportsComplex:!0,cpuKernelImpl:oq}),yQ={kernelName:Fs,backendName:"webgl",kernelFunc:r8};function s8(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=v.parseAxisParam([s],r.shape),o=a8({inputs:{x:r},backend:a,attrs:{reductionIndices:i,keepDims:!1}}),l=I.expandShapeToKeepDim(o.shape,i),u=pe({inputs:{x:o},backend:a,attrs:{shape:l}}),d=r8({inputs:{a:r,b:u},backend:a}),c=Qw({inputs:{x:d},backend:a}),p=c0({inputs:{x:c},backend:a,attrs:{axis:i,keepDims:!1}}),h=pe({inputs:{x:p},backend:a,attrs:{shape:l}}),m=n8({inputs:{a:c,b:h},backend:a});return a.disposeIntermediateTensorInfo(o),a.disposeIntermediateTensorInfo(u),a.disposeIntermediateTensorInfo(d),a.disposeIntermediateTensorInfo(c),a.disposeIntermediateTensorInfo(p),a.disposeIntermediateTensorInfo(h),m}var xQ={kernelName:el,backendName:"webgl",kernelFunc:s8};function AQ(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?r:s8({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),u=l.shape[0],d=l.shape[1],c=new hQ(u,d,s),p=[[i]],h=a.runWebGLProgram(c,[l],"int32",p);return o||a.disposeIntermediateTensorInfo(l),h}var bQ={kernelName:Eo,backendName:"webgl",kernelFunc:AQ},vQ=$n+` return -x; `,wQ=` vec4 result = -x; 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; `;function kQ(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.texData.get(n.dataId),[i,o]=Vj(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r;return B().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Zr(n.shape,wQ):r=new Qn(n.shape,vQ),a.runWebGLProgram(r,[n],n.dtype)}var IQ={kernelName:Ru,backendName:"webgl",kernelFunc:kQ},SQ=Fn.nonMaxSuppressionV3Impl;function TQ(e){I.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,u=a.readSync(r.dataId),d=a.readSync(s.dataId),{selectedIndices:c}=SQ(u,d,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var CQ={kernelName:Mo,backendName:"webgl",kernelFunc:TQ},NQ=Fn.nonMaxSuppressionV4Impl;function RQ(e){I.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=n,d=a.readSync(r.dataId),c=a.readSync(s.dataId),{selectedIndices:p,validOutputs:h}=NQ(d,c,i,o,l,u);return[a.makeTensorInfo([p.length],"int32",new Int32Array(p)),a.makeTensorInfo([],"int32",new Int32Array([h]))]}var EQ={kernelName:Eu,backendName:"webgl",kernelFunc:RQ},MQ=Fn.nonMaxSuppressionV5Impl;function FQ(e){I.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n,d=a.readSync(r.dataId),c=a.readSync(s.dataId),p=i,h=o,m=l,f=u,{selectedIndices:g,selectedScores:y}=MQ(d,c,p,h,m,f);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var $Q={kernelName:Fo,backendName:"webgl",kernelFunc:FQ},DQ=class{constructor(e,t,a,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=` void main() { ivec2 coords = getOutputCoords(); int index = round(getIndices(coords.x)); setOutput(mix(float(${n}), float(${a}), float(index == coords.y))); } `}},PQ=e=>{let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=v.sizeFromShape(r.shape),d=new DQ(u,i,o,l),c=pe({inputs:{x:r},backend:a,attrs:{shape:[u]}}),p=a.runWebGLProgram(d,[c],s);a.disposeIntermediateTensorInfo(c);let h=[...r.shape,i],m=pe({inputs:{x:p},backend:a,attrs:{shape:h}});return a.disposeIntermediateTensorInfo(p),m},_Q={kernelName:$o,backendName:"webgl",kernelFunc:PQ};function Mh(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=sc({inputs:{input:n},backend:a}),s=Mh({inputs:{x:r},backend:a}),i=h0({inputs:{input:n},backend:a}),o=Mh({inputs:{x:i},backend:a}),l=zs({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return ic({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var OQ={kernelName:qu,backendName:"webgl",kernelFunc:Mh};function i8(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let r=sc({inputs:{input:n},backend:a}),s=i8({inputs:{x:r},backend:a}),i=h0({inputs:{input:n},backend:a}),o=Mh({inputs:{x:i},backend:a}),l=zs({inputs:{real:s,imag:o},backend:a});return a.disposeIntermediateTensorInfo(r),a.disposeIntermediateTensorInfo(s),a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}else return ic({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var zQ={kernelName:Mu,backendName:"webgl",kernelFunc:i8};function LQ(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return q1({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(d=>{v.assertShapesMatch(s,d.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===d.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(d=>{let c=q1({inputs:{input:d},backend:a,attrs:{dim:r}});return o.push(c),c}),u=Hw({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(d=>a.disposeIntermediateTensorInfo(d)),u}var WQ={kernelName:Fu,backendName:"webgl",kernelFunc:LQ},BQ=class{constructor(e,t,a){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let n=e.length,r=ft(n),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(n===1){this.userCode=` int start = ${s}; int end = ${i}; void main() { int outC = getOutputCoords(); if (outC < start || outC >= end) { setOutput(value); } else { setOutput(getX(outC - start)); } } `;return}this.userCode=` ${r} start = ${r}(${s}); ${r} end = ${r}(${i}); void main() { ${r} outC = getOutputCoords(); if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) { setOutput(value); } else { ${r} coords = outC - start; setOutput(getX(${o})); } } `}},VQ=class{constructor(e,t,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((m,f)=>m[0]+e[f]+m[1]);let n=e.length,r=ft(n),s=t.map(m=>m[0]).join(","),i=t.map((m,f)=>m[0]+e[f]).join(","),o=ka("rc",n),l=ka("source",n),u=`${o[n-1]} < ${this.outputShape[n-1]}`,d=n===1?"source":`vec2(${l.slice(-2).join()})`,c=[`${r} rc = outputLoc;`,`${o[n-1]} += 1; if(${u}) { `,n===1?"":`} rc = outputLoc; ${o[n-2]} += 1; if(${o[n-2]} < ${this.outputShape[n-2]}) {`,n===1?"":` ${o[n-1]} += 1; if(${u}) {`],p=n===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",h="";for(let m=0,f=n===1?2:4;m{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;if(v.sizeFromShape(r.shape)===0){let u=s.map((d,c)=>d[0]+r.shape[c]+d[1]);return ic({backend:a,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new VQ(r.shape,s,i):new BQ(r.shape,s,i),l=[[i]];return a.runWebGLProgram(o,[r],r.dtype,l)},UQ={kernelName:Do,backendName:"webgl",kernelFunc:o8},GQ=` 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); `,HQ=` // 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; bvec4 isNaN1 = lessThan(a, vec4(0.0)); bvec4 isNaN2 = lessThan(floor(b), b); bvec4 isNaN = bvec4(isNaN1.x && isNaN2.x, isNaN1.y && isNaN2.y, isNaN1.z && isNaN2.z, isNaN1.w && isNaN2.w); `+cl+` return result; `,jQ=ha({opSnippet:GQ,packedOpSnippet:HQ}),qQ={kernelName:Po,backendName:"webgl",kernelFunc:jQ};function XQ(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n,o=r.shape.length,l=[],u=v.parseAxisParam(s,r.shape),d=u,c=I.getAxesPermutation(d,o),p=r;c!=null&&(p=Ta({inputs:{x:r},backend:a,attrs:{perm:c}}),d=I.getInnerMostAxes(d.length,o),l.push(p)),I.assertAxesAreInnerMostDims("prod",d,o);let h;if(a.shouldExecuteOnCPU([p])){let m=a.texData.get(p.dataId).values,{outVals:f,outShape:g,outDtype:y}=Gj(p.shape,p.dtype,m,d);h=a.makeTensorInfo(g,y,f)}else{let[m,f]=I.computeOutAndReduceShapes(p.shape,d),g=v.sizeFromShape(f),y=pe({inputs:{x:p},backend:a,attrs:{shape:[-1,g]}}),x=Lp(r.dtype),A=hl(y,x,"prod",a);h=pe({inputs:{x:A},backend:a,attrs:{shape:m}}),l.push(y),l.push(A)}if(i){l.push(h);let m=I.expandShapeToKeepDim(h.shape,u);h=pe({inputs:{x:h},backend:a,attrs:{shape:m}})}return l.forEach(m=>a.disposeIntermediateTensorInfo(m)),h}var KQ={kernelName:Oo,backendName:"webgl",kernelFunc:XQ};function YQ(e){let{inputs:t,backend:a,attrs:n}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=n,l=r.map(y=>a.readSync(y.dataId)),u=r.map(y=>y.shape),d=a.readSync(s.dataId),c=a.readSync(i.dataId),[p,h,m]=Hj(l,u,d,s.shape,s.dtype,c,i.shape,o),f=p.map(y=>a.makeTensorInfo([y.length],"int32",y)),g=a.makeTensorInfo(m,s.dtype,h);return f.concat([g])}var ZQ={kernelName:Lh,backendName:"webgl",kernelFunc:YQ};function JQ(e){let{inputs:t,backend:a}=e,{starts:n,limits:r,deltas:s}=t,i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,d]=jj(i,n.shape,n.dtype,o,r.shape,l,s.shape),c=a.makeTensorInfo([u.length],"int32",u),p=a.makeTensorInfo([d.length],n.dtype,d);return[c,p]}var QQ={kernelName:Wh,backendName:"webgl",kernelFunc:JQ};function eee(e){let{inputs:t,backend:a,attrs:n}=e,{shape:r,values:s,defaultValue:i,rowPartitionTensors:o}=t,{rowPartitionTypes:l}=n,u=a.readSync(r.dataId),d=a.readSync(s.dataId),c=a.readSync(i.dataId),p=o.map(g=>a.readSync(g.dataId)),h=o.map(g=>g.shape),[m,f]=qj(u,r.shape,d,s.shape,s.dtype,c,i.shape,p,h,l);return a.makeTensorInfo(m,s.dtype,f)}var tee={kernelName:Bh,backendName:"webgl",kernelFunc:eee},l8=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=Xj(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},aee={kernelName:$u,backendName:"webgl",kernelFunc:l8},nee="return 1.0 / x;",ree=tt({opSnippet:nee}),see={kernelName:zo,backendName:"webgl",kernelFunc:ree},iee=$n+` return (x < 0.0) ? 0.0 : x; `,oee=` 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; `,lee=tt({opSnippet:iee,packedOpSnippet:oee}),uee={kernelName:Lo,backendName:"webgl",kernelFunc:lee},dee=$n+` return (x < 0.0) ? 0.0 : min(6.0, x); `,pee=` 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; `,cee=tt({opSnippet:dee,packedOpSnippet:pee}),hee={kernelName:Vo,backendName:"webgl",kernelFunc:cee},mee=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],d=[n&&t>1?t-1:t,n&&a>1?a-1:a],c;r?c="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":c="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=` const vec2 effectiveInputOverOutputRatioRC = vec2( ${u[0]/d[0]}, ${u[1]/d[1]}); const vec2 inputShapeRC = vec2(${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 = ${c}; // 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); } `}},fee=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],d=[n&&t>1?t-1:t,n&&a>1?a-1:a],c;r?c="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":c="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=` const vec3 effectiveInputOverOutputRatioRC = vec3( ${u[0]/d[0]}, ${u[1]/d[1]}, ${u[1]/d[1]}); const vec3 inputShapeRC = vec3(${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 = ${c}; // 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 < ${a-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 gee(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,d=B().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new fee(r.shape,l,u,s,i):new mee(r.shape,l,u,s,i);return a.runWebGLProgram(d,[r],"float32")}var yee={kernelName:Bo,backendName:"webgl",kernelFunc:gee},xee=class{constructor(e,t,a){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,r]=t,[,s,i]=e,o=[a&&s>1?n-1:n,a&&i>1?r-1:r],l=[a&&s>1?s-1:s,a&&i>1?i-1:i],u=o[0]/l[0],d=o[1]/l[1],c=1/u,p=1/d,h=Math.ceil(c)*2+2,m=Math.ceil(p)*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(${u}); const float widthScale = float(${d}); const float invHeightScale = float(${c}); const float invWidthScale = float(${p}); const int winHeight = int(${h}); const int winWidth = int(${m}); // 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), ${n-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), ${r-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 Aee(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new xee(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var bee={kernelName:_u,backendName:"webgl",kernelFunc:Aee},vee=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],d=[n&&t>1?t-1:t,n&&a>1?a-1:a],c=n?"0.5":"0.0",p;r?p="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":p="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=` const vec2 effectiveInputOverOutputRatioRC = vec2( ${u[0]/d[0]}, ${u[1]/d[1]}); const vec2 inputShapeRC = vec2(${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 = ${p}; // Compute the coordinators of nearest neighbor point. ivec2 sourceNearestRC = ivec2( min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${c}))); float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d); setOutput(newValue); } `}},wee=class{constructor(e,t,a,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,a,l];let u=[n&&t>1?i-1:i,n&&a>1?o-1:o],d=[n&&t>1?t-1:t,n&&a>1?a-1:a],c=n?"0.5":"0.0",p;r?p="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":p="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=` const vec3 effectiveInputOverOutputRatioRC = vec3( ${u[0]/d[0]}, ${u[1]/d[1]}, ${u[1]/d[1]}); const vec3 inputShapeRC = vec3(${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 = ${p}; // Compute the coordinators of nearest neighbor point. ivec3 sourceNearestRC = ivec3( min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${c}))); // Should we calculate next column and row elements in 2x2 packed cell. bool hasNextCol = d < ${l-1}; bool hasNextRow = coords.z < ${a-1}; vec4 newValue = vec4( getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d), hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1) : 0.0, hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d) : 0.0, (hasNextRow && hasNextCol) ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0); setOutput(newValue); } `}};function kee(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,d=B().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new wee(r.shape,l,u,s,i):new vee(r.shape,l,u,s,i);return a.runWebGLProgram(d,[r],r.dtype)}var Iee={kernelName:Wo,backendName:"webgl",kernelFunc:kee},See=class{constructor(e,t,a){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,r]=t,[,s,i]=e,o=[a&&s>1?n-1:n,a&&i>1?r-1:r],l=[a&&s>1?s-1:s,a&&i>1?i-1:i],u=o[0]/l[0],d=o[1]/l[1],c=1/u,p=1/d,h=Math.ceil(c)*2+2,m=Math.ceil(p)*2+2;this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; int r = coords[1]; int c = coords[2]; float accumulator = 0.0; const float heightScale = float(${u}); const float widthScale = float(${d}); const float invHeightScale = float(${c}); const float invWidthScale = float(${p}); const int winHeight = int(${h}); const int winWidth = int(${m}); // 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(${l[1]})); int sourceNearestRow = int(min( float(int(${n}) - 1), ${a} ? float(round(sourceFracRow)) : float(floor(sourceFracRow)))); int sourceNearestCol = int(min( float(int(${r}) - 1), ${a} ? float(round(sourceFracCol)) : float(floor(sourceFracCol)))); if (r == sourceNearestRow && c == sourceNearestCol) { accumulator += getDy(b, dyR, dyC, d); } } } // End loop over dy setOutput(accumulator); } `}};function Tee(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=new See(s.shape,r.shape,i);return a.runWebGLProgram(o,[s],s.dtype)}var Cee={kernelName:Pu,backendName:"webgl",kernelFunc:Tee},Nee=class{constructor(e,t){this.variableNames=["x"];let a=e.length;if(a>4)throw new Error(`WebGL backend: Reverse of rank-${a} tensor is not yet supported`);if(this.outputShape=e,a===1){this.userCode=` void main() { int coord = getOutputCoords(); setOutput(getX(${e[0]} - coord - 1)); } `;return}let n=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,r=e.map((i,o)=>n(o)).join(","),s=ft(a);this.userCode=` void main() { ${s} coords = getOutputCoords(); setOutput(getX(${r})); } `}},Ree=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let a=e.length;if(a>4)throw new Error(`WebGL backend: Reverse of rank-${a} tensor is not yet supported`);this.outputShape=e;let n=ka("rc",a),r=`${n[a-1]} + 1 < ${this.outputShape[a-1]}`,s=`${n[a-2]} + 1 < ${this.outputShape[a-2]}`,i=ft(a);a===1?this.userCode=` void main(){ int rc = getOutputCoords(); vec4 result = vec4(0.); result.r = getChannel(getX(${e[0]} - rc - 1), ${e[0]} - rc - 1); if(${r}){ 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 = ${o(n.slice())}; if(${r}){ result.g = ${l(n.slice())}; } if(${s}) { result.b = ${u(n.slice())}; if(${r}) { result.a = ${d(n.slice())}; } } setOutput(result); } `;function o(h){return c(h)}function l(h){return h[a-1]="("+h[a-1]+" + 1)",c(h)}function u(h){return h[a-2]="("+h[a-2]+" + 1)",c(h)}function d(h){return h[a-1]="("+h[a-1]+" + 1)",h[a-2]="("+h[a-2]+" + 1)",c(h)}function c(h){let m=e.map((y,x)=>p(x,h)),f=m.join(","),g=m.slice(-2).join(",");return`getChannel(getX(${f}), vec2(${g}))`}function p(h,m){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${m[h]} - 1`:`${m[h]}`}}};function Eee(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=r.shape.length,o=v.parseAxisParam(s,r.shape);if(i===0)return tn({inputs:{x:r},backend:a});let l=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ree(r.shape,o):new Nee(r.shape,o);return a.runWebGLProgram(l,[r],r.dtype)}var Mee={kernelName:Uo,backendName:"webgl",kernelFunc:Eee},Fee=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let a=e[1],n=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=` vec3 fill = vec3(${t.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) - params[0]) * params[3] - (float(y) - params[1]) * params[2]; float coordYFloat = (float(x) - params[0]) * params[2] + (float(y) - params[1]) * params[3]; int coordX = int(round(coordXFloat + params[0])); int coordY = int(round(coordYFloat + params[1])); ${r} if(coordX >= 0 && coordX < ${n} && coordY >= 0 && coordY < ${a}) { outputValue = getImage(coords[0], coordY, coordX, coords[3]); } setOutput(outputValue); } `}},$ee={kernelName:ol,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new Fee(n.shape,s),[u,d]=I.getImageCenter(i,n.shape[1],n.shape[2]),c=[[u,d,Math.sin(r),Math.cos(r)]];return o.runWebGLProgram(l,[n],n.dtype,c)}},Dee=` // 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; } } `,Pee=tt({opSnippet:Dee}),_ee={kernelName:Go,backendName:"webgl",kernelFunc:Pee},Oee="return inversesqrt(x);",zee=tt({opSnippet:Oee,cpuKernelImpl:Kj}),Lee={kernelName:Ns,backendName:"webgl",kernelFunc:zee},Y3=class{constructor(e,t,a,n,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let l=ft(r.length),u=ft(s.length),d="";a===1?d="i":a===2&&(d="i, j");let c=`getIndices(${d})`,p="";n===1?p="i":n===2&&(p="i, coords[1]");let h=`getUpdates(${p})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides";this.userCode=` ${l} strides = ${l}(${r}); void main() { ${u} coords = getOutputCoords(); float sum = 0.0; bool found = false; for (int i = 0; i < ${e}; i++) { int flattenedIndex = 0; for (int j = 0; j < ${t}; j++) { int index = round(${c}); flattenedIndex += index * ${g}; } if (flattenedIndex == coords[0]) { sum += ${h}; found = true; } } setOutput(mix(${f}, sum, float(found))); } `}},Wee=class{constructor(e,t,a,n,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=s;let l=ft(r.length),u=ft(s.length),d="";a===1?d="i":a===2&&(d="i, j");let c=`getIndices(${d})`,p="";n===1?p="i":n===2&&(p="i, coords[1]");let h=`getUpdates(${p})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides",y=t>1?"strides[j + 1]":"strides";this.userCode=` ${l} strides = ${l}(${r}); void main() { ${u} coords = getOutputCoords(); vec4 sum = vec4(0.); vec4 found = vec4(0.); for (int i = 0; i < ${e}; i+=2) { ivec2 flattenedIndex = ivec2(0); for (int j = 0; j < ${t}; j+=2) { ivec4 index = round(${c}); flattenedIndex += index.xz * ${g}; if (j + 1 < ${t}) { flattenedIndex += index.yw * ${y}; } } if (flattenedIndex[0] == coords[0] || flattenedIndex[1] == coords[0] || flattenedIndex[0] == coords[0] + 1 || flattenedIndex[1] == coords[0] + 1) { vec4 updVals = ${h}; if (flattenedIndex[0] == coords[0]) { sum.xy += updVals.xy; found.xy = vec2(1.); } else if (flattenedIndex[0] == coords[0] + 1) { sum.zw += updVals.xy; found.zw = vec2(1.); } if (flattenedIndex[1] == coords[0]) { sum.xy += updVals.zw; found.xy = vec2(1.); } else if (flattenedIndex[1] == coords[0] + 1) { sum.zw += updVals.zw; found.zw = vec2(1.); } } } setOutput(mix(${f}, sum, found)); } `}};function Bee(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:d,outputSize:c}=I.calculateShapes(s,r,i),p=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=pe({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),m=pe({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),f=a.makeTensorInfo([],"float32",new Float32Array([0])),g;B().getBool("WEBGL_PACK")?g=new Wee(l,o,h.shape.length,m.shape.length,d,p):g=new Y3(l,o,h.shape.length,m.shape.length,d,p);let y=a.runWebGLProgram(g,[m,h,f],m.dtype),x=pe({inputs:{x:y},backend:a,attrs:{shape:i}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(y),a.disposeIntermediateTensorInfo(f),x}var Vee={kernelName:Ho,backendName:"webgl",kernelFunc:Bee},Uee=class{constructor(e,t,a,n){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,a];let r="while (left < right) {",s=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=B().getNumber("WEBGL_VERSION")===2?r:s,o=n==="left"?"<":"<=";this.userCode=` int findBound(int batch, float value) { int left = 0; int right = numInputs; int mid; ${i} mid = (left + right) / 2; if (getSortedSequence(batch, mid) ${o} value) { left = mid + 1; } else { right = mid; } } return right; } void main() { ivec2 coords = getOutputCoords(); int batch = coords[0]; int valueIndex = coords[1]; float value = getValues(batch, valueIndex); setOutput(float(findBound(batch, value))); } `}};function Gee(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new Uee(r.shape[0],r.shape[1],s.shape[1],i),l=[[r.shape[1]]];return a.runWebGLProgram(o,[r,s],"int32",l)}var Hee={kernelName:qo,backendName:"webgl",kernelFunc:Gee},jee=class{constructor(e,t,a){this.variableNames=["c","a","b"],this.outputShape=t;let n,r;if(a>4)throw Error(`Where for rank ${a} is not yet supported`);if(a===1)r="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u= 1.0) { setOutput(getA(${r})); } else { setOutput(getB(${r})); } } `}};function qee(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new jee(n.shape.length,r.shape,r.shape.length);return a.runWebGLProgram(i,[n,r,s],Qt(r.dtype,s.dtype))}var Xee={kernelName:Ou,backendName:"webgl",kernelFunc:qee},Kee=` // Stable and Attracting Fixed Point (0, 1) for Normalized Weights. // see: https://arxiv.org/abs/1706.02515 float scaleAlpha = ${I.SELU_SCALEALPHA}; float scale = ${I.SELU_SCALE}; return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0); `,Yee=tt({opSnippet:Kee}),Zee={kernelName:Xo,backendName:"webgl",kernelFunc:Yee},Jee=rd+` return 1.0 / (1.0 + exp(-1.0 * x)); `,Qee=` vec4 result = 1.0 / (1.0 + exp(-1.0 * x)); 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; `,ete=tt({opSnippet:Jee,packedOpSnippet:Qee,cpuKernelImpl:Zj}),tte={kernelName:Rs,backendName:"webgl",kernelFunc:ete},ate=` if (isnan(x)) { return 0.0; } return sign(x); `,nte=tt({opSnippet:ate}),rte={kernelName:Zo,backendName:"webgl",kernelFunc:nte},ste=rd+` return sin(x); `,ite=` vec4 result = sin(x); bvec4 isNaN = isnan(x); ${cl} return result; `,ote=tt({opSnippet:ste,packedOpSnippet:ite}),lte={kernelName:Ko,backendName:"webgl",kernelFunc:ote},ute=` float e2x = exp(x); return (e2x - 1.0 / e2x) / 2.0; `,dte=tt({opSnippet:ute}),pte={kernelName:Yo,backendName:"webgl",kernelFunc:dte},cte=` 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; `,hte=tt({opSnippet:cte}),mte={kernelName:Jo,backendName:"webgl",kernelFunc:hte},fte=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,x)=>y*x),l=[[0,0]];l.push(...i);for(let y=1+s.length;ya.disposeIntermediateTensorInfo(y)),g},gte={kernelName:Lu,backendName:"webgl",kernelFunc:fte};function yte(e){let{inputs:t,backend:a}=e,{indices:n,values:r,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw: ${s.shape}`);if(n.shape.length!==2)throw new Error(`Indices must be a matrix, saw: ${n.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw: ${r.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw: ${i.shape}`);let o=a.readSync(n.dataId),l=a.readSync(r.dataId),u=a.readSync(s.dataId),d=a.readSync(i.dataId)[0],[c,p,h,m,f]=Qj(o,n.shape,n.dtype,l,r.dtype,u,d);return[a.makeTensorInfo(p,n.dtype,c),a.makeTensorInfo([p[0]],r.dtype,h),a.makeTensorInfo([m.length],"bool",new Uint8Array(m.map(g=>Number(g)))),a.makeTensorInfo([f.length],n.dtype,new Int32Array(f))]}var xte={kernelName:Mp,backendName:"webgl",kernelFunc:yte};function Ate(e){let{inputs:t,backend:a}=e,{inputIndices:n,inputShape:r,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${n.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(a.readSync(r.dataId)),o=a.readSync(n.dataId),l=Array.from(a.readSync(s.dataId)),[u,d,c]=eq(o,n.shape,n.dtype,i,l);return[a.makeTensorInfo(d,n.dtype,u),a.makeTensorInfo([c.length],s.dtype,new Int32Array(c))]}var bte={kernelName:Bu,backendName:"webgl",kernelFunc:Ate};function vte(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape ${s.shape}`);let i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,d]=Ew(i,n.shape,n.dtype,o,l,!0);return a.makeTensorInfo(d,n.dtype,u)}var wte={kernelName:Vu,backendName:"webgl",kernelFunc:vte};function kte(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape ${s.shape}`);let i=a.readSync(n.dataId),o=a.readSync(r.dataId),l=a.readSync(s.dataId),[u,d]=Ew(i,n.shape,n.dtype,o,l);return a.makeTensorInfo(d,n.dtype,u)}var Ite={kernelName:Uu,backendName:"webgl",kernelFunc:kte};function Ste(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:d,strides:c,outputSize:p}=I.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let y=a.bufferSync(r),x=a.bufferSync(s),A=v.decodeString(a.readSync(i.dataId)[0]),b=Yj(y,x,o,p,d,u,l,c,A,h);return a.makeTensorInfo(o,b.dtype,b.values)}let m=new Y3(u,l,r.shape.length,s.shape.length,c,[p,1],h),f=a.runWebGLProgram(m,[s,r,i],s.dtype),g=pe({inputs:{x:f},backend:a,attrs:{shape:o}});return a.disposeIntermediateTensorInfo(f),g}var Tte={kernelName:tl,backendName:"webgl",kernelFunc:Ste};function Cte(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=I.prepareSplitSize(r,s,o),u=r.shape.length,d=new Array(u).fill(0),c=r.shape.slice();return l.map(p=>{let h=[...c];h[o]=p;let m=sd({inputs:{x:r},backend:a,attrs:{begin:d,size:h}});return d[o]+=p,m})}var Nte={kernelName:Wu,backendName:"webgl",kernelFunc:Cte},nA="return sqrt(x);",Rte=tt({opSnippet:nA,packedOpSnippet:nA,cpuKernelImpl:tq}),Ete={kernelName:Es,backendName:"webgl",kernelFunc:Rte},Mte="return x * x;",Fte=tt({opSnippet:Mte}),$te={kernelName:Fp,backendName:"webgl",kernelFunc:Fte},rA="return (a - b) * (a - b);",Dte=ha({opSnippet:rA,packedOpSnippet:rA}),Pte={kernelName:Ms,backendName:"webgl",kernelFunc:Dte};function _te(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t;if(r.dtype!=="string")throw new Error("Input must be of datatype string");let s=a.readSync(r.dataId),i=I.fromUint8ToStringArray(s),o=aq(i,"string",n);return a.makeTensorInfo(r.shape,"string",o)}var Ote={kernelName:Gu,backendName:"webgl",kernelFunc:_te};function zte({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=$n+` return x > 0.0 ? 1.0 : float(${t.alpha}); `,s=new Qn(n.shape,r);return a.runWebGLProgram(s,[n],n.dtype)}var Lte={kernelName:Ds,backendName:"webgl",kernelFunc:zte},Wte=class{constructor(e,t,a){this.variableNames=["x"],this.outputShape=a;let n=a.length,r=ft(a.length),s=ft(a.length),i="";if(n===1)i="coords * strides + begin";else{let o=0;i=a.map((l,u)=>(o++,a.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=` ${r} begin = ${r}(${e}); ${r} strides = ${r}(${t}); void main() { ${s} coords = getOutputCoords(); setOutput(getX(${i})); } `}};function Bte(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:d,newAxisMask:c,shrinkAxisMask:p}=n,{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=wt.sliceInfo(r.shape,s,i,o,l,u,d,c,p),w;if(f)w=pe({inputs:{x:r},backend:a,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let C=wt.computeOutShape(x,A,b),N=sd({inputs:{x:r},backend:a,attrs:{begin:x,size:C}});w=pe({inputs:{x:N},backend:a,attrs:{shape:m}}),a.disposeIntermediateTensorInfo(N)}else if(a.shouldExecuteOnCPU([r])){let C=a.readSync(r.dataId),N=Te(r.shape,r.dtype,C),M=nq(h,N,b,x);w=a.makeTensorInfo(m,r.dtype,M.values)}else{let C=new Wte(x,b,h);w=a.runWebGLProgram(C,[r],r.dtype)}let S=pe({inputs:{x:w},backend:a,attrs:{shape:m}});return a.disposeIntermediateTensorInfo(w),S}var Vte={kernelName:al,backendName:"webgl",kernelFunc:Bte};function Ute(e){let{inputs:t,backend:a,attrs:n}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:d,dataSplits:c}=t,p=a.readSync(d.dataId),h=a.readSync(c.dataId),[m,f]=rq(p,h,r,s,i,o,l,u);return[a.makeTensorInfo([m.length],"string",m),a.makeTensorInfo(c.shape,"int32",f)]}var Gte={kernelName:Hu,backendName:"webgl",kernelFunc:Ute};function Hte(e){let{inputs:t,backend:a,attrs:n}=e,{skipEmpty:r}=n,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let o=a.readSync(s.dataId),l=a.readSync(i.dataId)[0],[u,d,c]=sq(o,l,r),p=d.length;return[a.makeTensorInfo([p,2],"int32",u),a.makeTensorInfo([p],"string",d),a.makeTensorInfo([2],"int32",new Int32Array(c))]}var jte={kernelName:$p,backendName:"webgl",kernelFunc:Hte};function qte(e){let{inputs:t,backend:a,attrs:n}=e,{numBuckets:r}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let i=a.readSync(s.dataId),o=iq(i,r);return a.makeTensorInfo(s.shape,"int32",o)}var Xte={kernelName:Dp,backendName:"webgl",kernelFunc:qte},Kte="return tan(x);",Yte=tt({opSnippet:Kte}),Zte={kernelName:nl,backendName:"webgl",kernelFunc:Yte},Jte=` float e2x = exp(-2.0 * abs(x)); return sign(x) * (1.0 - e2x) / (1.0 + e2x); `,Qte=tt({opSnippet:Jte}),eae={kernelName:rl,backendName:"webgl",kernelFunc:Qte};function tae(e){let{inputs:t,backend:a,attrs:n}=e,{tensor:r,indices:s,updates:i}=t,{}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:d,outputSize:c}=I.calculateShapes(i,s,r.shape),p=[c/u,u];if(c===0)return a.makeTensorInfo(r.shape,s.dtype);let h=pe({inputs:{x:s},backend:a,attrs:{shape:[l,o]}}),m=pe({inputs:{x:i},backend:a,attrs:{shape:[l,u]}}),f=pe({inputs:{x:r},backend:a,attrs:{shape:p}}),g=new Y3(l,o,h.shape.length,m.shape.length,d,p,!1,!0),y=a.runWebGLProgram(g,[m,h,f],f.dtype),x=pe({inputs:{x:y},backend:a,attrs:{shape:r.shape}});return a.disposeIntermediateTensorInfo(h),a.disposeIntermediateTensorInfo(m),a.disposeIntermediateTensorInfo(f),a.disposeIntermediateTensorInfo(y),x}var aae={kernelName:jo,backendName:"webgl",kernelFunc:tae},nae=class{constructor(e,t){this.variableNames=["A"];let a=new Array(e.length);for(let s=0;s5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let a=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let r=0;r5){let o=a.readSync(r.dataId),l=r.dtype==="string"?o.map(c=>v.decodeString(c)):o,u=Te(r.shape,r.dtype,l),d=lq(u,s);return a.makeTensorInfo(d.shape,d.dtype,d.values)}let i=new nae(r.shape,s);return a.runWebGLProgram(i,[r],r.dtype)}var sae={kernelName:$s,backendName:"webgl",kernelFunc:u8},iae=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=` void main() { ivec2 coords = getOutputCoords(); int batch = coords[0]; int elemIdx = coords[1]; // We compare elements pair-wise within a group of size 2 * inc. // The comparing rule for each group alternates between ascending // and descending. Within each group, we compare each pair at // positions i and i+inc. To decide whether an element at position i // is x0 or x1, we mod it by 2 * inc, if the result is smaller than // inc, it is in the first half of the group, we denote it as x0, // otherwise we denote it as x1. // For example, as shown in the Bitonic top K paper referenced above, // Figure5(a) shows that element[1] is in the // second half of the group when group size is 2, but it is in the // first half of the group when group size is 4. bool isFirstInPair = imod(elemIdx, 2 * inc) < inc; int i = isFirstInPair ? elemIdx : elemIdx - inc; int i0 = firstPass == 1 ? i : int(getIndices(batch, i)); int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc)); float x0 = i0 < n ? getX(batch, i0) : negativeInf; float x1 = i1 < n ? getX(batch, i1) : negativeInf; // Denotes which direction indices are in (ascending or descending). bool reverse = imod(elemIdx, 2 * dir) >= dir; bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0); if (reverse == isGreater) { // Elements in opposite order of direction int iTemp = i0; i0 = i1; i1 = iTemp; } if (isFirstInPair) { setOutput(float(i0)); } else { setOutput(float(i1)); } } `}},oae=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=e,this.userCode=` void main() { // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ... ivec2 coords = getOutputCoords(); int batch = coords[0]; int elemIdx = coords[1]; // The output size is half of the previous size. // If the previous sequence is | | | | _ _ _ _ | | | | _ _ _ _ (k=4), // we only need to output the indices at positions |, the indices at // positions _ can be thrown away, see Figure5(b) After Phase 2 // (Merge phase) in the Bitonic Top K paper referenced above. // For example, the paper shows we only need to output the orange bars. // The output sequence should look like this | | | | | | | |. // Because the sequence is halved, to map the output index back // to the previous sequence to find the corresponding value, // we need to double the index. When we double the index, // we basically interpolate a position, so 2i looks like // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position // of each 2k positions by - elemIdx % k. E.g. for output at // index 4,5,6,7, we want to get the corresponding element at // original index 8,9,10,11, for output at index 8,9,10,11, // we want to get the corresponding element at original index // 16,17,18,19, so on and so forth. int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k)); int i0 = firstPass == 1 ? i : int(getIndices(batch, i)); int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k)); float x0 = getX(batch, i0); float x1 = i1 < n ? getX(batch, i1) : x0; setOutput(x0 >= x1 ? float(i0) : float(i1)); } `}};function ui(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function sA(e){let t=1;for(;tl){let M=a.readSync(r.dataId),[F,E]=uq(M,u,r.dtype,s,i);return[a.makeTensorInfo(F.shape,F.dtype,F.values),a.makeTensorInfo(E.shape,E.dtype,E.values)]}if(s===0)return u[u.length-1]=0,[a.makeTensorInfo(u,r.dtype,[]),a.makeTensorInfo(u,"int32",[])];if(d===1)return[r,ic({attrs:{shape:u,dtype:"int32",value:0},backend:a})];let c=a.texData.get(r.dataId),p=c!==null&&c.isPacked,h=p?a.unpackTensor(r):r,m=v.sizeFromShape(u)/d,f=pe({inputs:{x:h},attrs:{shape:[m,d]},backend:a});p&&ui(a,h);let g=sA(s),y=sA(d),x=null,A=()=>x===null?[f,f]:[f,x],b=(M,F,E)=>{let T=A(),D=new iae(E),O=[[d],[x===null?1:0],[Number.NEGATIVE_INFINITY],[M],[F]],W=x;x=a.runWebGLProgram(D,T,"int32",O),ui(a,W)};for(let M=1;M=1;E/=2)b(F,E,[m,y])}for(let M=y;M>g;M/=2){let F=A(),E=new oae([m,M/2]),T=[[d],[x===null?1:0],[g]],D=x;x=a.runWebGLProgram(E,F,"int32",T),ui(a,D);let O=g/2,W=O*2;for(let $=O;$>=1;$/=2)b(W,$,x.shape)}let w=x;x=sd({inputs:{x},backend:a,attrs:{begin:0,size:[m,s]}}),ui(a,w);let S=t8({inputs:{x:f,indices:x},backend:a,attrs:{axis:1,batchDims:1}});ui(a,f);let C=u.slice(0,-1);C.push(s),w=x,x=pe({inputs:{x},attrs:{shape:C},backend:a}),ui(a,w);let N=S;return S=pe({inputs:{x:S},attrs:{shape:C},backend:a}),ui(a,N),[S,x]}var uae={kernelName:sl,backendName:"webgl",kernelFunc:lae},dae=class{constructor(e,t,a,n,r,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=a==="nearest"?1:2,o;switch(n){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=` float mapCoord(float outCoord, float len) { float inCoord = outCoord; if(${o} == 2) { if (inCoord < 0.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz2 = 2.0 * len; if (inCoord < sz2) { inCoord = sz2 * float(int(float(-inCoord / sz2))) + inCoord; } inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0; } } else if (inCoord > len - 1.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz2 = 2.0 * len; inCoord -= sz2 * float(int(float(inCoord / sz2))); if (inCoord >= len) { inCoord = sz2 - inCoord - 1.0; } } } return clamp(inCoord, 0.0, len - 1.0); } else if (${o} == 3) { if (inCoord < 0.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz = len - 1.0; inCoord += len * (float(int(float(-inCoord / sz))) + 1.0); } } else if (inCoord > len - 1.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz = len - 1.0; inCoord -= len * float(int(float(inCoord / sz))); } } return clamp(inCoord, 0.0, len - 1.0); } else if (${o} == 4) { return clamp(outCoord, 0.0, len - 1.0); } else { return outCoord; } } float readWithFillValue(int batch, int coordY, int coordX, int channel) { float outputValue; if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) { outputValue = getImage(batch, coordY, coordX, channel); } else { outputValue = float(${r}); } return outputValue; } void main() { ivec4 coords = getOutputCoords(); float outputValue; int batch = coords[0]; int x = coords[2]; int y = coords[1]; int channel = coords[3]; float xf = float(x); float yf = float(y); float a1 = getTransforms(batch, 0); float a2 = getTransforms(batch, 1); float a3 = getTransforms(batch, 2); float b1 = getTransforms(batch, 3); float b2 = getTransforms(batch, 4); float b3 = getTransforms(batch, 5); float c1 = getTransforms(batch, 6); float c2 = getTransforms(batch, 7); float projection = c1 * xf + c2 * yf + 1.0; if (projection == 0.0) { outputValue = float(${r}); } else { float inX = (a1 * xf + a2 * yf + a3) / projection; float inY = (b1 * xf + b2 * yf + b3) / projection; float mapX = mapCoord(inX, float(${t})); float mapY = mapCoord(inY, float(${e})); if (${i} == 1) { int coordY = int(round(mapY)); int coordX = int(round(mapX)); outputValue = readWithFillValue(batch, coordY, coordX, channel); } else { float yFloor = floor(mapY); float xFloor = floor(mapX); float yCeil = yFloor + 1.0; float xCeil = xFloor + 1.0; float valueYFloor = (xCeil - mapX) * readWithFillValue(batch, int(yFloor), int(xFloor), channel) + (mapX - xFloor) * readWithFillValue(batch, int(yFloor), int(xCeil), channel); float valueYCeil = (xCeil - mapX) * readWithFillValue(batch, int(yCeil), int(xFloor), channel) + (mapX - xFloor) * readWithFillValue(batch, int(yCeil), int(xCeil), channel); outputValue = (yCeil - mapY) * valueYFloor + (mapY - yFloor) * valueYCeil; } } setOutput(outputValue); } `}};function pae(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[d,c,p,h]=r.shape,[m,f]=u!=null?u:[c,p],g=[d,m,f,h],y=new dae(c,p,i,o,l,g);return a.runWebGLProgram(y,[r,s],"float32")}var cae={kernelName:il,backendName:"webgl",kernelFunc:pae};function hae(e){let{inputs:t,attrs:a,backend:n}=e,{axis:r}=a,{x:s}=t;Ju(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=n.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=dq(i,r,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([u.length],"int32",u)]}var mae={kernelName:Pp,backendName:"webgl",kernelFunc:hae};function fae(e){let{inputs:t,backend:a,attrs:n}=e,{value:r}=t,{axis:s}=n;s<0&&(s+=r.shape.length);let i=r,o=i.shape.length,l=r.shape[s],u=new Array(o-1),d=0;for(let f=0;fa.disposeIntermediateTensorInfo(f)),m}var gae={kernelName:ju,backendName:"webgl",kernelFunc:fae},yae=class{constructor(e,t){this.variableNames=["x","segmentIds"];let a=e.windowSize,n=e.batchSize,r=e.inSize,s=e.numSegments,i=s*Math.ceil(r/a);this.outputShape=[n,i];let o="0.0",l="sumValue",u=Math.floor(a/4)*4,d=a%4,c=` sumValue += dot(values, segFilter); `,p="";r%a>0&&(p=` if (inIdx < 0 || inIdx >= ${r}) { return initializationValue; } `);let h="";r%a>0&&(h=` if (inIdx < 0 || inIdx >= ${r}) { return -1.0; } `),this.userCode=` const float initializationValue = ${o}; float getValue(int batch, int inIdx) { ${p} return getX(batch, inIdx); } float getSegmentIdAtIndex(int inIdx) { ${h} return getSegmentIds(inIdx); } void main() { ivec2 coords = getOutputCoords(); int batch = coords[0]; int outIdx = coords[1]; int inOffset = int(floor(float(outIdx) / float( ${s})) * float(${a})); int currentSeg = int(mod(float(outIdx), float(${s}))); float sumValue = 0.0; for (int i = 0; i < ${u}; i += 4) { int inIdx = inOffset + i; vec4 values = vec4( getValue(batch, inIdx), getValue(batch, inIdx + 1), getValue(batch, inIdx + 2), getValue(batch, inIdx + 3) ); vec4 segFilter = vec4( int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0, int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0, int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0, int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0 ); ${c} } int inIdx = inOffset + ${u}; if (${d===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 ); ${c} } else if (${d===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 ); ${c} } else if (${d===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 ); ${c} } setOutput(${l}); } `}};function xae(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,segmentIds:s}=t,{numSegments:i}=n,o=r.shape.length,l=[],u=0,d=I.getAxesPermutation([u],o),c=r;d!=null&&(c=Ta({inputs:{x:r},backend:a,attrs:{perm:d}}),l.push(c),u=I.getInnerMostAxes(1,o)[0]);let p=I.segment_util.computeOutShape(c.shape,u,i),h=v.sizeFromShape([c.shape[u]]),m=pe({inputs:{x:c},backend:a,attrs:{shape:[-1,h]}});l.push(m);let f=Lp(r.dtype),g=(b,w,S,C,N)=>{let M=b.shape[0],F=b.shape[1],E=I.segment_util.segOpComputeOptimalWindowSize(F,N),T={windowSize:E,inSize:F,batchSize:M,numSegments:N},D=new yae(T,w),O=a.compileAndRun(D,[b,S],C);if(l.push(O),O.shape[1]===N)return O;let W=l8({backend:a,attrs:{start:0,stop:N,step:1,dtype:"float32"}}),$=u8({inputs:{x:W},backend:a,attrs:{reps:[F/E]}});return l.push(W),l.push($),g(O,w,$,C,N)},y=g(m,"unsortedSegmentSum",s,f,i),x=pe({inputs:{x:y},backend:a,attrs:{shape:p}}),A=x;if(d!=null){l.push(x);let b=I.getUndoAxesPermutation(d);A=Ta({inputs:{x:A},backend:a,attrs:{perm:b}})}return l.forEach(b=>a.disposeIntermediateTensorInfo(b)),A}var Aae={kernelName:_p,backendName:"webgl",kernelFunc:xae},bae=[nX,sX,lX,pX,hX,gX,xX,bX,IX,TX,RX,FX,PX,LX,VX,GX,jX,YX,JX,eK,rK,pK,hK,yK,AK,SK,CK,MK,Wq,DK,LK,UK,KK,JK,eY,aY,rY,lY,pY,mY,gY,xY,bY,kY,SY,RY,MY,DY,OY,LY,UY,qY,ZY,eZ,nZ,rZ,iZ,lZ,dZ,cZ,mZ,xZ,vZ,IZ,TZ,RZ,FZ,_Z,WZ,Lq,VZ,OK,HZ,XZ,ZZ,Vq,tJ,sJ,oJ,pJ,mJ,xJ,vJ,SJ,RJ,FJ,DJ,zJ,WJ,VJ,jJ,XJ,YJ,JJ,eQ,rQ,lQ,cQ,bQ,Hq,IQ,CQ,EQ,$Q,vK,_Q,zQ,WQ,UQ,qQ,Gq,KQ,ZQ,QQ,tee,aee,wK,gQ,see,uee,hee,qq,yee,bee,Iee,Cee,Mee,$ee,_ee,Lee,Vee,Hee,Xee,Zee,tte,rte,lte,pte,uK,xQ,mte,gte,xte,bte,wte,Ite,Tte,Nte,Ete,$te,Pte,Ote,Lte,Vte,Gte,jte,Xte,yQ,eX,Zte,eae,aae,sae,uae,cae,tX,mae,gae,Aae,OQ];for(let e of bae)bn(e);var nt;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(nt||(nt={}));var dp;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(dp||(dp={}));var d8;function vae(e){d8=e.wasm.cwrap(ts,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function wae(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:d,leakyreluAlpha:c}=n,p=a.dataIdMap.get(r.dataId).id,h=a.dataIdMap.get(s.dataId).id,m=0;if(i!=null){let N=a.dataIdMap.get(i.dataId);if(N.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${N.shape.length}.`);m=N.id}let f=o==null?0:a.dataIdMap.get(o.dataId).id,g=dp[d];if(g==null)throw new Error(`${d} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?r.shape[2]:r.shape[1],x=u?s.shape[1]:s.shape[2],A=ul.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),b=a.makeOutput([...A,y,x],r.dtype),w=a.dataIdMap.get(b.dataId).id,S=new Uint8Array(new Int32Array(r.shape).buffer),C=new Uint8Array(new Int32Array(s.shape).buffer);return d8(p,S,r.shape.length,h,C,s.shape.length,l,u,g,m,f,c||0,w),b}var kae={kernelName:ts,backendName:"wasm",setupFunc:vae,kernelFunc:wae};function Qe(e,t){let a;function n(s){a=s.wasm.cwrap(e,null,["number","number","number"])}function r(s){let{backend:i,inputs:{x:o}}=s,l=i.dataIdMap.get(o.dataId).id,u=i.makeOutput(o.shape,t||o.dtype),d=i.dataIdMap.get(u.dataId).id;return v.sizeFromShape(u.shape)===0||a(l,nt[o.dtype],d),u}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var Iae=Qe(cu),Sae=Qe($i),Tae=Qe(Di);function Gt(e,t,a){let n;function r(i){n=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:d}=l,c=o.dataIdMap.get(u.dataId).id,p=o.dataIdMap.get(d.dataId).id,h=a!=null?a:u.dtype,m=I.assertAndGetBroadcastShape(u.shape,d.shape),f=o.makeOutput(m,h);if(v.sizeFromShape(m)===0)return f;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(d.shape).buffer),x=o.dataIdMap.get(f.dataId).id;return n(c,g,u.shape.length,p,y,d.shape.length,nt[u.dtype],x),f}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var Cae=!0,Nae=Gt(Mr,Cae),p8;function Rae(e){p8=e.wasm.cwrap(Pi,null,["array","number","number","number"])}function Eae(e){let{inputs:t,backend:a}=e,n=a.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(n.shape)===0)return n;let r=t.map(o=>a.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(r).buffer),i=a.dataIdMap.get(n.dataId).id;return p8(s,r.length,nt[n.dtype],i),n}var Mae={kernelName:Pi,backendName:"wasm",setupFunc:Rae,kernelFunc:Eae};function m0(e){let{inputs:{x:t},backend:a}=e;if(t.dtype==="string")return Ve(a.readSync(t.dataId),t.shape,t.dtype);let n=a.makeOutput(t.shape,t.dtype),r=a.typedArrayFromHeap(t);return a.typedArrayFromHeap(n).set(r),n}var Fae={kernelName:ho,backendName:"wasm",kernelFunc:m0},c8;function $ae(e){c8=e.wasm.cwrap(Tr,null,["number","array","number","number","number","array","number"])}function ps(e){let{inputs:t,backend:a,attrs:n}=e,[r,s]=Pae(t.x.shape,n.perm),i=!0;for(let m=0;m=r&&(s===-1||n[s]>n[i])&&(s=i);n[s]=r}return[a,n]}var _ae={kernelName:Tr,backendName:"wasm",kernelFunc:ps,setupFunc:$ae};function Ls(e,t,a){let n=e.shape,r=e.shape.length,s=v.parseAxisParam(t,n),i=s,o=I.getAxesPermutation(i,r),l=null,u=!1;if(o!=null){let d=new Array(r);for(let p=0;p`new shape: ${i}, old shape: ${n.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var lne={kernelName:Du,backendName:"wasm",kernelFunc:La},b8;function une(e){b8=e.wasm.cwrap(Gi,null,["number","array","number","number","array","number","number","number","number"])}function dne(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=s.shape.length,d=i?r.shape[l-2]:r.shape[l-1],c=o?s.shape[u-1]:s.shape[u-2],p=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],m=r.shape.slice(0,-2),f=s.shape.slice(0,-2),g=v.sizeFromShape(m),y=v.sizeFromShape(f),x=ul.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([p,h]);v.assert(d===c,()=>`Error in matMul: inner shapes (${d}) and (${c}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let A=i?[g,d,p]:[g,p,d],b=o?[y,h,c]:[y,c,h],w=La({inputs:{x:r},backend:a,attrs:{shape:A}}),S=La({inputs:{x:s},backend:a,attrs:{shape:b}}),C=a.dataIdMap.get(w.dataId).id,N=a.dataIdMap.get(S.dataId).id,M=i?w.shape[2]:w.shape[1],F=o?S.shape[1]:S.shape[2],E=Math.max(g,y),T=a.makeOutput([E,M,F],w.dtype),D=a.dataIdMap.get(T.dataId).id,O=new Uint8Array(new Int32Array(w.shape).buffer),W=new Uint8Array(new Int32Array(S.shape).buffer);return b8(C,O,w.shape.length,N,W,S.shape.length,i,o,D),a.disposeData(w.dataId),a.disposeData(S.dataId),T.shape=x,T}var pne={kernelName:Gi,backendName:"wasm",setupFunc:une,kernelFunc:dne};function Mi(e){let{inputs:{x:t},attrs:{begin:a,size:n},backend:r}=e,[s,i]=wt.parseSliceParams(t,a,n),o=wt.isSliceContinous(t.shape,s,i),l=r.readSync(t.dataId),u=r.makeOutput(i,t.dtype),d=v.computeStrides(t.shape),c=r.dataIdMap.get(u.dataId);if(o){let m=wt.computeFlatOffset(s,d);return t.dtype==="string"?c.stringBytes=l.slice(m,m+v.sizeFromShape(i)):r.typedArrayFromHeap(u).set(l.subarray(m,m+v.sizeFromShape(i))),u}if(t.dtype==="string"){let m=Sh(l,s,i,t.shape,t.dtype);return c.stringBytes=m,u}let p=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)cne(l,d[0],p,s,i);else if(h===3)hne(l,d[0],d[1],p,s,i);else if(h===4)mne(l,d[0],d[1],d[2],p,s,i);else{let m=Sh(l,s,i,t.shape,t.dtype);p.set(m)}return u}function cne(e,t,a,n,r){let s=0,i=n[0],o=n[1],l=i+r[0];for(let u=i;uy*x),l=I.getReshaped(r.shape,s,o),u=I.getPermuted(l.length,s.length),d=I.getReshapedPermuted(r.shape,s,o),c=I.getSliceBeginCoords(i,s.length),p=I.getSliceSize(d,i,s.length),h=La({inputs:{x:r},backend:a,attrs:{shape:l}}),m=ps({inputs:{x:h},backend:a,attrs:{perm:u}}),f=La({inputs:{x:m},backend:a,attrs:{shape:d}}),g=Mi({inputs:{x:f},backend:a,attrs:{begin:c,size:p}});return a.disposeData(h.dataId),a.disposeData(m.dataId),a.disposeData(f.dataId),g}var yne={kernelName:gu,backendName:"wasm",kernelFunc:gne},v8;function xne(e){v8=e.wasm.cwrap(Hi,null,["number","number","boolean","number","number","number"])}function Ane(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,weights:s}=a,{size:i}=n,o=s.shape.reduce((c,p)=>c*p,1)!==0,l=r.shape.length===1?[i]:[r.shape[0],i],u=t.makeOutput(l,s.dtype);function d(c){return t.dataIdMap.get(c.dataId).id}return v8(d(r),i,o,d(s),nt[s.dtype],d(u)),u}var bne={kernelName:Hi,backendName:"wasm",setupFunc:xne,kernelFunc:Ane},vne=!0,wne=Gt(ji,vne);function kne(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t,s=a.typedArrayFromHeap(n),i=a.typedArrayFromHeap(r),o=I.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return a.makeOutput([o.length],"int32",void 0,new Int32Array(o))}var Ine={kernelName:yu,backendName:"wasm",kernelFunc:kne};function Ws(e){let{inputs:{x:t},attrs:{dtype:a},backend:n}=e,r=n.makeOutput(t.shape,a),s=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(r).set(s),r}var Sne={kernelName:qi,backendName:"wasm",kernelFunc:Ws},Tne=Qe(cs),w8;function Cne(e){w8=e.wasm.cwrap(hs,null,["number","number","number","number"])}function Nne(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o=a.dataIdMap.get(r.dataId).id,l=a.makeOutput(r.shape,r.dtype),u=a.dataIdMap.get(l.dataId).id;return w8(o,s,i,u),l}var Rne={kernelName:hs,backendName:"wasm",setupFunc:Cne,kernelFunc:Nne};function k8(e){let{inputs:t,backend:a}=e,n=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=t.map(h=>h.shape);I.assertParamsConsistent(r,n);let s=I.computeOutShape(t.map(h=>h.shape),n),i=t.filter(h=>v.sizeFromShape(h.shape)>0);if(i.length===1)return m0({inputs:{x:i[0]},backend:a});let o=a.makeOutput(s,t[0].dtype);if(v.sizeFromShape(s)===0)return o;if(i[0].dtype==="string"){let h=i.map(A=>{let b=[-1,v.sizeFromShape(A.shape.slice(n))];return La({inputs:{x:A},backend:a,attrs:{shape:b}})}),m=h.map(A=>({vals:a.readSync(A.dataId),shape:A.shape}));s=I.computeOutShape(h.map(A=>A.shape),1);let f=h[0].shape[0]===1,g=k3(m,s,t[0].dtype,f),y=I.computeOutShape(i.map(A=>A.shape),n);o.shape=y;let x=a.dataIdMap.get(o.dataId);return x.stringBytes=I.fromStringArrayToUint8(g),h.forEach(A=>a.disposeData(A.dataId)),o}let l=v.sizeFromShape(i[0].shape.slice(0,n)),u=0,d=i.map(h=>{let m=v.sizeFromShape(h.shape.slice(n));return u+=m,m}),c=i.map(h=>a.typedArrayFromHeap(h)),p=a.typedArrayFromHeap(o);for(let h=0;h`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=I.getAxesPermutation([s],l),d=r;u!==null&&(d=ps({inputs:{x:r},attrs:{perm:u},backend:a}));let c=I.getInnerMostAxes(1,l)[0];I.assertAxesAreInnerMostDims("cumprod",[c],l);let p=a.makeOutput(d.shape,d.dtype),h=d.shape[c],m=a.dataIdMap.get(d.dataId).id,f=a.dataIdMap.get(p.dataId).id;E8(m,i?1:0,o?1:0,h,f,nt[r.dtype]);let g=p;if(u!==null){let y=I.getUndoAxesPermutation(u);g=ps({inputs:{x:p},attrs:{perm:y},backend:a}),a.disposeData(d.dataId),a.disposeData(p.dataId)}return g}var Qne={kernelName:eo,backendName:"wasm",setupFunc:Zne,kernelFunc:Jne},M8;function ere(e){M8=e.wasm.cwrap(to,null,["number","number","number","number","number","number"])}function tre(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=I.getAxesPermutation([s],l),d=r;u!==null&&(d=ps({inputs:{x:r},attrs:{perm:u},backend:a}));let c=I.getInnerMostAxes(1,l)[0];I.assertAxesAreInnerMostDims("cumsum",[c],l);let p=a.makeOutput(d.shape,d.dtype),h=d.shape[c],m=a.dataIdMap.get(d.dataId).id,f=a.dataIdMap.get(p.dataId).id;M8(m,i?1:0,o?1:0,h,f,nt[r.dtype]);let g=p;if(u!==null){let y=I.getUndoAxesPermutation(u);g=ps({inputs:{x:p},attrs:{perm:y},backend:a}),a.disposeData(d.dataId),a.disposeData(p.dataId)}return g}var are={kernelName:to,backendName:"wasm",setupFunc:ere,kernelFunc:tre},F8;function nre(e){F8=e.wasm.cwrap("DenseBincount",null,["number","array","number","number","boolean","number","number","boolean","number"])}function rre(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,weights:s}=a,{size:i,binaryOutput:o}=n,l=s.shape.reduce((p,h)=>p*h,1)!==0,u=r.shape.length===1?[i]:[r.shape[0],i],d=t.makeOutput(u,s.dtype);function c(p){return t.dataIdMap.get(p.dataId).id}return F8(c(r),new Uint8Array(new Int32Array(r.shape).buffer),r.shape.length,i,l,c(s),nt[s.dtype],o,c(d)),d}var sre={kernelName:bu,backendName:"wasm",setupFunc:nre,kernelFunc:rre},$8;function ire(e){$8=e.wasm.cwrap(no,null,["number","number","number","array","number","array","array","number","number"])}function ore(e){let{backend:t,inputs:a,attrs:n}=e,{x:r}=a,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],d=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,p=u*s,h=d/(s*s),m=i==="NHWC"?[o,c,p,h]:[o,h,c,p],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,y=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),x=new Uint8Array(new Int32Array(m).buffer),A=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer),b=t.dataIdMap.get(f.dataId).id;return $8(g,s,i==="NHWC"?1:0,y,r.shape.length-1,x,A,m.length,b),f}var lre={kernelName:no,backendName:"wasm",setupFunc:ire,kernelFunc:ore},D8;function ure(e){D8=e.wasm.cwrap(ro,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function dre(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s}=t,i=n.dataIdMap.get(r.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:d,dimRoundingMode:c}=a,p=u==null?[1,1]:u,h=I.computeConv2DInfo(r.shape,s.shape,l,p,d,c,!0),m=h.filterHeight,f=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,x=h.padInfo.bottom,A=h.padInfo.left,b=h.dilationHeight,w=h.dilationWidth,S=h.strideHeight,C=h.strideWidth,N=h.inChannels,M=h.outChannels,F=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let E=n.makeOutput(h.outShape,"float32"),T=n.dataIdMap.get(E.dataId).id;return D8(i,r.shape[0],r.shape[1],r.shape[2],o,m,f,g,y,x,A,F,b,w,S,C,N,M,T),E}var pre={kernelName:ro,backendName:"wasm",setupFunc:ure,kernelFunc:dre},P8;function cre(e){P8=e.wasm.cwrap("Diag",null,["number","number","number","number"])}function hre(e){let{inputs:t,backend:a}=e,{x:n}=t,r=v.sizeFromShape(n.shape),s=a.makeOutput([...n.shape,...n.shape],n.dtype);return P8(a.dataIdMap.get(n.dataId).id,nt[n.dtype],r,a.dataIdMap.get(s.dataId).id),s}var mre={kernelName:vu,backendName:"wasm",setupFunc:cre,kernelFunc:hre},_8;function fre(e){_8=e.wasm.cwrap(so,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function gre(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n;if(r.dtype!==s.dtype)throw new Error(`Dilation2D error: x must have the same dtype as filter. Got ${r.dtype} and ${s.dtype}`);let u=I.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),d=a.makeOutput(u.outShape,r.dtype);return _8(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(d.dataId).id,nt[r.dtype],u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.filterHeight,u.filterWidth,u.padInfo.top,u.padInfo.left),d}var yre={kernelName:so,backendName:"wasm",setupFunc:fre,kernelFunc:gre},O8;function xre(e){O8=e.wasm.cwrap(Ql,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Are(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropFilter error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let d=I.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=a.makeOutput(s.shape,s.dtype);return O8(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,nt[r.dtype],d.batchSize,d.inChannels,d.inHeight,d.inWidth,d.outHeight,d.outWidth,d.strideHeight,d.strideWidth,d.dilationHeight,d.dilationWidth,d.filterHeight,d.filterWidth,d.padInfo.top,d.padInfo.left),c}var bre={kernelName:Ql,backendName:"wasm",setupFunc:xre,kernelFunc:Are},z8;function vre(e){z8=e.wasm.cwrap(Jl,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function wre(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropInput error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let d=I.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=a.makeOutput(r.shape,r.dtype);return z8(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,nt[r.dtype],d.batchSize,d.inChannels,d.inHeight,d.inWidth,d.outHeight,d.outWidth,d.strideHeight,d.strideWidth,d.dilationHeight,d.dilationWidth,d.filterHeight,d.filterWidth,d.padInfo.top,d.padInfo.left),c}var kre={kernelName:Jl,backendName:"wasm",setupFunc:vre,kernelFunc:wre},Ire=Qe(oo),L8;function Sre(e){L8=e.wasm.cwrap(wu,null,["number","number","number"])}function Tre(e){let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=a.makeOutput(r.shape,"float32"),i=o=>a.dataIdMap.get(o.dataId).id;return L8(i(r),i(n),i(s)),s}var Cre={kernelName:wu,backendName:"wasm",setupFunc:Sre,kernelFunc:Tre},Nre=!1,Rre=Gt(ms,Nre,"bool"),Ere=Qe(lo),Mre=Qe(fs,"float32");function K1(e){let{inputs:t,attrs:a,backend:n}=e,{input:r}=t,{dim:s}=a,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),La({inputs:{x:r},backend:n,attrs:{shape:o}})}var Fre={kernelName:ku,backendName:"wasm",kernelFunc:K1},$re=Qe(gs,"float32");function W8(e){let{attrs:{shape:t,value:a},backend:n}=e,{attrs:{dtype:r}}=e;r=r||v.inferDtype(a);let s=n.makeOutput(t,r);return n.typedArrayFromHeap(s).fill(a),s}var Dre={kernelName:Iu,backendName:"wasm",kernelFunc:W8},B8;function Pre(e){B8=e.wasm.cwrap(uo,null,["number","number","number","number","number","number"])}function _re(e){let{inputs:t,backend:a}=e,{image:n}=t,r=a.makeOutput(n.shape,n.dtype),s=a.dataIdMap.get(n.dataId).id,i=a.dataIdMap.get(r.dataId).id,[o,l,u,d]=n.shape;return B8(s,o,l,u,d,i),r}var Ore={kernelName:uo,backendName:"wasm",kernelFunc:_re,setupFunc:Pre},zre=Qe(ys),Lre=!1,Wre=Gt(xs,Lre),V8;function Bre(e){V8=e.wasm.cwrap(po,null,["number","number","number","number","number","number","number"])}function Vre(e){let{backend:t,inputs:a,attrs:n}=e,{varianceEpsilon:r}=n,{x:s,mean:i,variance:o,offset:l,scale:u}=a,d=t.dataIdMap.get(s.dataId).id,c=t.dataIdMap.get(i.dataId).id,p=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return V8(d,c,p,h,m,r,g),f}var Ure={kernelName:po,backendName:"wasm",setupFunc:Bre,kernelFunc:Vre},U8;function Gre(e){U8=e.wasm.cwrap(as,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Hre(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:d,dataFormat:c,dimRoundingMode:p,activation:h,leakyreluAlpha:m}=a,f=I.computeConv2DInfo(r.shape,s.shape,l,d,u,p),g=dp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let y=n.dataIdMap.get(r.dataId).id,x=n.dataIdMap.get(s.dataId).id,A=f.outChannels,b=0;if(i!=null){let X=n.dataIdMap.get(i.dataId);if(X.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${X.shape.length}.`);if(X.shape[0]!==A)throw new Error(`FusedConv2D bias shape (${X.shape}) does not match the number of output channels (${A})`);b=X.id}let w=f.filterHeight,S=f.filterWidth,C=f.padInfo.top,N=f.padInfo.right,M=f.padInfo.bottom,F=f.padInfo.left,E=f.dilationHeight,T=f.dilationWidth,D=f.strideHeight,O=f.strideWidth,W=f.inChannels,$=f.padInfo.type==="SAME"?1:0,U=f.batchSize,G=f.inHeight,q=f.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${c}'. Please use 'NHWC'.`);let H=n.makeOutput(f.outShape,"float32"),V=n.dataIdMap.get(H.dataId).id,Z=o==null?0:n.dataIdMap.get(o.dataId).id;return U8(y,U,G,q,x,w,S,b,C,N,M,F,$,E,T,D,O,W,A,g,Z,m||0,V),H}var jre={kernelName:as,backendName:"wasm",setupFunc:Gre,kernelFunc:Hre},G8;function qre(e){G8=e.wasm.cwrap(ns,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Xre(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:d,dataFormat:c,dimRoundingMode:p,activation:h,leakyreluAlpha:m}=a,f=I.computeConv2DInfo(r.shape,s.shape,l,d,u,p,!0),g=dp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=n.dataIdMap.get(r.dataId).id,x=n.dataIdMap.get(s.dataId).id,A=f.outChannels,b=0;if(i!=null){let X=n.dataIdMap.get(i.dataId);if(X.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${X.shape.length}.`);if(X.shape[0]!==A)throw new Error(`FusedDepthwiseConv2D bias shape (${X.shape}) does not match the number of output channels (${A})`);b=X.id}let w=f.filterHeight,S=f.filterWidth,C=f.padInfo.top,N=f.padInfo.right,M=f.padInfo.bottom,F=f.padInfo.left,E=f.dilationHeight,T=f.dilationWidth,D=f.strideHeight,O=f.strideWidth,W=f.inChannels,$=f.padInfo.type==="SAME"?1:0,U=f.batchSize,G=f.inHeight,q=f.inWidth;if(c!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${c}'. Please use 'NHWC'.`);let H=n.makeOutput(f.outShape,"float32"),V=n.dataIdMap.get(H.dataId).id,Z=o==null?0:n.dataIdMap.get(o.dataId).id;return G8(y,U,G,q,x,w,S,b,C,N,M,F,$,E,T,D,O,W,A,g,Z,m||0,V),H}var Kre={kernelName:ns,backendName:"wasm",setupFunc:qre,kernelFunc:Xre},H8;function Yre(e){H8=e.wasm.cwrap(co,null,["number","number","number","number","number","number","array","number"])}function Zre(e){let{backend:t,inputs:a}=e,{params:n,indices:r}=a,[s,i,o,l]=h3.prepareAndValidate(n,r),u=t.makeOutput(s,n.dtype);if(i===0)return u;let d=r.shape,c=d[d.length-1],p=t.dataIdMap.get(n.dataId).id,h=t.dataIdMap.get(r.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return H8(p,nt[n.dtype],h,i,c,o,m,f),u}var Jre={kernelName:co,backendName:"wasm",setupFunc:Yre,kernelFunc:Zre},j8;function Qre(e){j8=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function ese(e){let{backend:t,inputs:a,attrs:n}=e,{x:r,indices:s}=a,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,r.shape)[0],u=t.readSync(s.dataId),d=r.shape[l];for(let C=0;C=0,()=>`GatherV2: the index value ${N} is not in [0, ${d-1}]`)}let c=I.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=La({inputs:{x:r},attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),m=La({inputs:{x:s},attrs:{shape:[c.batchSize,h/c.batchSize]},backend:t}),f=[c.batchSize,c.outerSize,h/c.batchSize,c.sliceSize],g=t.makeOutput(f,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let y=p.shape.length-1,x=t.dataIdMap.get(p.dataId).id,A=t.dataIdMap.get(m.dataId).id,b=t.dataIdMap.get(g.dataId).id,w=new Uint8Array(new Int32Array(v.computeStrides(p.shape)).buffer),S=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer);return j8(x,nt[r.dtype],w,y,A,c.batchSize,S,b),t.disposeData(p.dataId),t.disposeData(m.dataId),g.shape=c.outputShape,g}var tse={kernelName:Su,backendName:"wasm",setupFunc:Qre,kernelFunc:ese},ase=!1,nse=Gt(As,ase,"bool"),rse=!1,sse=Gt(bs,rse,"bool"),ise=Qe(mo,"bool"),ose=Qe(fo,"bool"),lse=Qe(go,"bool"),q8;function use(e){q8=e.wasm.cwrap(yo,null,["number","number","number","number"])}function dse(e){let{inputs:{x:t},attrs:{alpha:a},backend:n}=e,r=n.dataIdMap.get(t.dataId).id,s=n.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let i=n.dataIdMap.get(s.dataId).id;q8(r,nt[t.dtype],a,i)}return s}var pse={kernelName:yo,backendName:"wasm",setupFunc:use,kernelFunc:dse},cse=!1,hse=Gt(vs,cse,"bool"),mse=!1,fse=Gt(ws,mse,"bool"),X8;function gse(e){X8=e.wasm.cwrap(xo,null,["number","number","number","number"])}function yse(e){let{attrs:t,backend:a}=e,{start:n,stop:r,num:s}=t,i=Math.floor(s),o=a.makeOutput([i],"float32");return X8(a.dataIdMap.get(o.dataId).id,n,r,i),o}var xse={kernelName:xo,backendName:"wasm",setupFunc:gse,kernelFunc:yse},Ase=Qe(ks),bse=Qe(Ao),vse=!1,wse=Gt(bo,vse,"bool"),kse=Qe(vo),Ise=!1,Sse=Gt(wo,Ise,"bool"),Tse=!1,Cse=Gt(HA,Tse,"bool"),K8;function Nse(e){K8=e.wasm.cwrap(ko,null,["number","number","number","number","number","number","number"])}function Rse(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n;if(r.dtype!=="float32")throw new Error("LRN error: x must have dtype float32");let u=a.makeOutput(r.shape,r.dtype);return K8(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(u.dataId).id,r.shape[3],s,i,o,l),u}var Ese={kernelName:ko,backendName:"wasm",setupFunc:Nse,kernelFunc:Rse},Y8;function Mse(e){Y8=e.wasm.cwrap(Tu,null,["number","number","number","number","number","number","number","number","number"])}function Fse(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:d}=n;if(r.dtype!=="float32"||s.dtype!=="float32"||i.dtype!=="float32")throw new Error("LRNGrad error: x, y, and dy must have dtype float32");let c=a.makeOutput(r.shape,r.dtype);return Y8(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(i.dataId).id,a.dataIdMap.get(c.dataId).id,i.shape[3],o,l,u,d),c}var $se={kernelName:Tu,backendName:"wasm",setupFunc:Mse,kernelFunc:Fse},Z8;function Dse(e){Z8=e.wasm.cwrap(Io,null,["number","number","number","number"])}function Pse(e){let{backend:t,inputs:a,attrs:n}=e,{reductionIndices:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:d,originalAxes:c,inputWasTransposed:p}=Ls(i,r,t);if(p){let x=t.dataIdMap.get(u.dataId).id;l=u,o=x}let h=l.shape.length;I.assertAxesAreInnerMostDims("max",d,h);let[m,f]=I.computeOutAndReduceShapes(l.shape,d),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;Z8(o,nt[i.dtype],g,x)}if(p&&t.disposeData(u.dataId),s){let x=I.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var _se={kernelName:Io,backendName:"wasm",setupFunc:Dse,kernelFunc:Pse},Ose=!1,zse=Gt(Is,Ose),J8;function Lse(e){J8=e.wasm.cwrap(So,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Wse(e){let{inputs:t,attrs:a,backend:n}=e,r=t.x,s=n.dataIdMap.get(r.dataId).id;v.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,d=I.computePool2DInfo(r.shape,i,o,1,l,u),c=d.filterHeight,p=d.filterWidth,h=d.padInfo.top,m=d.padInfo.right,f=d.padInfo.bottom,g=d.padInfo.left,y=d.dilationHeight,x=d.dilationWidth,A=d.strideHeight,b=d.strideWidth,w=d.inChannels,S=d.outChannels;if(d.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${d.dataFormat}'. Please use 'channelsLast'.`);let C=n.makeOutput(d.outShape,"float32"),N=n.dataIdMap.get(C.dataId).id;return J8(s,r.shape[0],r.shape[1],r.shape[2],c,p,h,m,f,g,y,x,A,b,w,S,N),C}var Bse={kernelName:So,backendName:"wasm",setupFunc:Lse,kernelFunc:Wse},Q8;function Vse(e){Q8=e.wasm.cwrap("MaxPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Use(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,d=I.computePool3DInfo(r.shape,s,i,1,o,l,u),c=a.makeOutput(d.outShape,r.dtype);return Q8(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,d.batchSize,d.inChannels,d.inDepth,d.inHeight,d.inWidth,d.outDepth,d.outHeight,d.outWidth,d.strideDepth,d.strideHeight,d.strideWidth,d.dilationDepth,d.dilationHeight,d.dilationWidth,d.effectiveFilterDepth,d.effectiveFilterHeight,d.effectiveFilterWidth,d.padInfo.front,d.padInfo.top,d.padInfo.left),c}var Gse={kernelName:Cu,backendName:"wasm",setupFunc:Vse,kernelFunc:Use},ek;function Hse(e){ek=e.wasm.cwrap("MaxPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function jse(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,d=I.computePool3DInfo(s.shape,i,o,1,l,u),c=a.makeOutput(s.shape,s.dtype);return ek(a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,d.batchSize,d.inChannels,d.inDepth,d.inHeight,d.inWidth,d.outDepth,d.outHeight,d.outWidth,d.strideDepth,d.strideHeight,d.strideWidth,d.dilationDepth,d.dilationHeight,d.dilationWidth,d.effectiveFilterDepth,d.effectiveFilterHeight,d.effectiveFilterWidth,d.padInfo.front,d.padInfo.top,d.padInfo.left),c}var qse={kernelName:Rp,backendName:"wasm",setupFunc:Hse,kernelFunc:jse},tk;function Xse(e){tk=e.wasm.cwrap("MaxPoolGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Kse(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,d=I.computePool2DInfo(s.shape,i,o,1,l,u),c=a.makeOutput(s.shape,s.dtype);return tk(a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,d.batchSize,d.inChannels,d.inHeight,d.inWidth,d.outHeight,d.outWidth,d.strideHeight,d.strideWidth,d.dilationHeight,d.dilationWidth,d.effectiveFilterHeight,d.effectiveFilterWidth,d.padInfo.top,d.padInfo.left),c}var Yse={kernelName:Np,backendName:"wasm",setupFunc:Xse,kernelFunc:Kse},ak;function Zse(e){ak=e.wasm.cwrap("MaxPoolWithArgmax",null,["number","number","number","number","boolean","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Jse(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,includeBatchInIndex:l}=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(I.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let d=I.computePool2DInfo(r.shape,s,i,[1,1],o),c=a.makeOutput(d.outShape,r.dtype),p=a.makeOutput(d.outShape,"int32");return ak(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(c.dataId).id,a.dataIdMap.get(p.dataId).id,nt[r.dtype],l,d.batchSize,d.inChannels,d.inHeight,d.inWidth,d.outHeight,d.outWidth,d.strideHeight,d.strideWidth,d.dilationHeight,d.dilationWidth,d.effectiveFilterHeight,d.effectiveFilterWidth,d.padInfo.top,d.padInfo.left),[c,p]}var Qse={kernelName:Nu,backendName:"wasm",setupFunc:Zse,kernelFunc:Jse},nk;function eie(e){nk=e.wasm.cwrap(To,null,["number, number, number"])}function tie(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:d,axes:c,originalAxes:p,inputWasTransposed:h}=Ls(i,r,t),m=c;if(h){let b=t.dataIdMap.get(d.dataId).id;b!==o&&(u=d,l=b,m=I.getInnerMostAxes(m.length,u.shape.length))}I.assertAxesAreInnerMostDims("mean",m,u.shape.length);let[f,g]=I.computeOutAndReduceShapes(u.shape,m),y=v.sizeFromShape(g),x=u;u.dtype!=="float32"&&(x=Ws({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(x.dataId).id);let A=t.makeOutput(f,"float32");if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(A.dataId).id;nk(l,y,b)}if(h&&t.disposeData(d.dataId),s){let b=I.expandShapeToKeepDim(A.shape,p);A.shape=b}return u.dtype!=="float32"&&t.disposeData(x.dataId),A}var aie={kernelName:To,backendName:"wasm",setupFunc:eie,kernelFunc:tie},rk;function nie(e){rk=e.wasm.cwrap(Co,null,["number","number","number","number"])}function rie(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:d,axes:c,originalAxes:p,inputWasTransposed:h}=Ls(i,r,t);if(h){let A=t.dataIdMap.get(d.dataId).id;A!==o&&(u=d,l=A)}let m=u.shape.length;I.assertAxesAreInnerMostDims("min",c,m);let[f,g]=I.computeOutAndReduceShapes(u.shape,c),y=v.sizeFromShape(g),x=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;rk(l,nt[i.dtype],y,A)}if(h&&t.disposeData(d.dataId),s){let A=I.expandShapeToKeepDim(x.shape,p);x.shape=A}return x}var sie={kernelName:Co,backendName:"wasm",setupFunc:nie,kernelFunc:rie},iie=!1,oie=Gt(Ss,iie),Y1;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(Y1||(Y1={}));var sk;function lie(e){sk=e.wasm.cwrap(No,null,["number","array","number","number","array","array","number","number"])}function uie(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,mode:r}}=e,s=n.map((m,f)=>m[0]+t.shape[f]+m[1]),i=a.dataIdMap.get(t.dataId).id,o=a.makeOutput(s,t.dtype),l=a.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),d=n.map(m=>m[0]),c=n.map(m=>m[1]),p=new Uint8Array(new Int32Array(d).buffer),h=new Uint8Array(new Int32Array(c).buffer);return sk(i,u,t.shape.length,nt[t.dtype],p,h,Y1[r],l),o}var die={kernelName:No,backendName:"wasm",kernelFunc:uie,setupFunc:lie},ik;function pie(e){ik=e.wasm.cwrap(el,null,["number","number","number","number"])}function ok(e){let{backend:t,inputs:{logits:a},attrs:{dim:n}}=e,r=t.dataIdMap.get(a.dataId).id,s=t.makeOutput(a.shape,a.dtype),i=t.dataIdMap.get(s.dataId).id,o=a.shape[n],l=v.sizeFromShape(a.shape)/o;return v.sizeFromShape(s.shape)===0||ik(r,i,o,l),s}var cie={kernelName:el,backendName:"wasm",setupFunc:pie,kernelFunc:ok},lk;function hie(e){lk=e.wasm.cwrap(Eo,null,["number","number","number","number","number","number"])}function mie(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n;if(r.dtype!=="float32")throw new Error(`Tensor logits must have dtype float32, got ${r.dtype}`);let l=o?r:ok({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),[u,d]=l.shape,c=a.makeOutput([u,s],"int32");return lk(a.dataIdMap.get(l.dataId).id,u,d,s,i,a.dataIdMap.get(c.dataId).id),o||a.disposeData(l.dataId),c}var fie={kernelName:Eo,backendName:"wasm",setupFunc:hie,kernelFunc:mie},gie=Gt(Ro,!0),yie=!0,xie=Gt(Ts,yie),Aie=Qe(Ru);function Z3(e,t){let a=new Int32Array(e.wasm.HEAPU8.buffer,t,4),n=a[0],r=a[1],s=a[2],i=a[3];return e.wasm._free(t),{pSelectedIndices:n,selectedSize:r,pSelectedScores:s,pValidOutputs:i}}var uk;function bie(e){uk=e.wasm.cwrap(Mo,"number",["number","number","number","number","number"])}function vie(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i}=n,{boxes:o,scores:l}=a,u=t.dataIdMap.get(o.dataId).id,d=t.dataIdMap.get(l.dataId).id,c=uk(u,d,s,r,i),{pSelectedIndices:p,selectedSize:h,pSelectedScores:m,pValidOutputs:f}=Z3(t,c);return t.wasm._free(m),t.wasm._free(f),t.makeOutput([h],"int32",p)}var wie={kernelName:Mo,backendName:"wasm",setupFunc:bie,kernelFunc:vie},dk;function kie(e){dk=e.wasm.cwrap(Eu,"number",["number","number","number","number","number","bool"])}function Iie(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=n,{boxes:l,scores:u}=a,d=t.dataIdMap.get(l.dataId).id,c=t.dataIdMap.get(u.dataId).id,p=dk(d,c,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=Z3(t,p);t.wasm._free(f);let y=t.makeOutput([m],"int32",h),x=t.makeOutput([],"int32",g);return[y,x]}var Sie={kernelName:Eu,backendName:"wasm",setupFunc:kie,kernelFunc:Iie},pk;function Tie(e){pk=e.wasm.cwrap(Fo,"number",["number","number","number","number","number","number"])}function Cie(e){let{backend:t,inputs:a,attrs:n}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=n,{boxes:l,scores:u}=a,d=t.dataIdMap.get(l.dataId).id,c=t.dataIdMap.get(u.dataId).id,p=pk(d,c,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=Z3(t,p);t.wasm._free(g);let y=t.makeOutput([m],"int32",h),x=t.makeOutput([m],"float32",f);return[y,x]}var Nie={kernelName:Fo,backendName:"wasm",setupFunc:Tie,kernelFunc:Cie},Rie=!1,Eie=Gt(Cs,Rie,"bool"),ck;function Mie(e){ck=e.wasm.cwrap($o,null,["number","number","number","number","number"])}function Fie(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=a.makeOutput([...r.shape,i],s),d=a.dataIdMap.get(u.dataId).id,c=a.dataIdMap.get(r.dataId).id;return ck(c,i,o,l,d),u}var $ie={kernelName:$o,backendName:"wasm",setupFunc:Mie,kernelFunc:Fie};function Die(e){let{inputs:{x:t},backend:a}=e,n=a.makeOutput(t.shape,t.dtype);return a.typedArrayFromHeap(n).fill(1),n}var Pie={kernelName:Mu,backendName:"wasm",kernelFunc:Die};function _ie(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return K1({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(d=>{v.assertShapesMatch(s,d.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===d.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(d=>{let c=K1({inputs:{input:d},backend:a,attrs:{dim:r}});return o.push(c),c}),u=k8({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(d=>a.disposeData(d.dataId)),u}var Oie={kernelName:Fu,backendName:"wasm",kernelFunc:_ie},hk;function zie(e){hk=e.wasm.cwrap(Do,null,["number","array","number","number","array","array","number","number"])}function Lie(e){let{inputs:{x:t},backend:a,attrs:{paddings:n,constantValue:r}}=e,s=n.map((m,f)=>m[0]+t.shape[f]+m[1]);if(v.sizeFromShape(t.shape)===0)return W8({backend:a,attrs:{shape:s,value:r,dtype:t.dtype}});let i=a.dataIdMap.get(t.dataId).id,o=a.makeOutput(s,t.dtype),l=a.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),d=n.map(m=>m[0]),c=n.map(m=>m[1]),p=new Uint8Array(new Int32Array(d).buffer),h=new Uint8Array(new Int32Array(c).buffer);return hk(i,u,t.shape.length,nt[t.dtype],p,h,r,l),o}var mk={kernelName:Do,backendName:"wasm",kernelFunc:Lie,setupFunc:zie},Wie=!1,Bie=Gt(Po,Wie),fk;function Vie(e){fk=e.wasm.cwrap(_o,null,["number","number","number"])}function Uie(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=a.dataIdMap.get(n.dataId).id,i=a.dataIdMap.get(r.dataId).id,o=s,l=n,u=l;l.dtype!=="float32"&&(u=Ws({backend:a,inputs:{x:n},attrs:{dtype:"float32"}}),o=a.dataIdMap.get(u.dataId).id);let d=a.makeOutput(n.shape,"float32"),c=a.dataIdMap.get(d.dataId).id;return fk(o,i,c),l.dtype!=="float32"&&a.disposeData(u.dataId),d}var Gie={kernelName:_o,backendName:"wasm",setupFunc:Vie,kernelFunc:Uie},gk;function Hie(e){gk=e.wasm.cwrap(Oo,null,["number","number","number","number"])}function jie(e){let{backend:t,inputs:a,attrs:n}=e,{axis:r,keepDims:s}=n,{x:i}=a,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:d,axes:c,originalAxes:p,inputWasTransposed:h}=Ls(i,r,t),m=c;if(h){let A=t.dataIdMap.get(d.dataId).id;A!==o&&(u=d,l=A,m=I.getInnerMostAxes(m.length,u.shape.length))}I.assertAxesAreInnerMostDims("prod",m,u.shape.length);let[f,g]=I.computeOutAndReduceShapes(u.shape,m),y=v.sizeFromShape(g),x=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;gk(l,y,nt[x.dtype],A)}if(h&&t.disposeData(d.dataId),s){let A=I.expandShapeToKeepDim(x.shape,p);x.shape=A}return x}var qie={kernelName:Oo,backendName:"wasm",setupFunc:Hie,kernelFunc:jie},Xie=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=T3(n,r,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},Kie={kernelName:$u,backendName:"wasm",kernelFunc:Xie},Yie=!0,Zie=Gt(io,Yie),Jie=Qe(zo),Qie=Qe(Lo),eoe=Qe(Vo),yk;function toe(e){yk=e.wasm.cwrap(Bo,null,["number","number","number","number","number","number","number","number","number","number"])}function aoe(e){let{backend:t,inputs:a,attrs:n}=e,{images:r}=a,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,[d,c,p,h]=r.shape,m=[d,l,u,h],f=t.dataIdMap.get(r.dataId),g;f.dtype!=="float32"&&(g=Ws({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(g.dataId));let y=f.id,x=t.makeOutput(m,"float32");if(v.sizeFromShape(r.shape)===0)return x;let A=t.dataIdMap.get(x.dataId).id;return yk(y,d,c,p,h,l,u,s?1:0,i?1:0,A),g!=null&&t.disposeData(g.dataId),x}var noe={kernelName:Bo,backendName:"wasm",setupFunc:toe,kernelFunc:aoe},xk;function roe(e){xk=e.wasm.cwrap(_u,null,["number","number","number","array","array","boolean"])}function soe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=a.makeOutput(r.shape,"float32"),l=a.dataIdMap.get(r.dataId),u;return l.dtype!=="float32"&&(u=Ws({backend:a,inputs:{x:r},attrs:{dtype:"float32"}}),l=a.dataIdMap.get(u.dataId)),xk(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(o.dataId).id,new Uint8Array(new Int32Array(r.shape).buffer),new Uint8Array(new Int32Array(s.shape).buffer),i),u!=null&&a.disposeData(u.dataId),o}var ioe={kernelName:_u,backendName:"wasm",setupFunc:roe,kernelFunc:soe},Ak;function ooe(e){Ak=e.wasm.cwrap(Wo,null,["number","number","number","number","number","number","number","number","number","number"])}function loe(e){let{backend:t,inputs:a,attrs:n}=e,{images:r}=a,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,[d,c,p,h]=r.shape,m=[d,l,u,h],f=t.makeOutput(m,"float32");if(v.sizeFromShape(r.shape)===0)return f;let g=t.dataIdMap.get(r.dataId),y;g.dtype!=="float32"&&(y=Ws({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),g=t.dataIdMap.get(y.dataId));let x=g.id,A=t.dataIdMap.get(f.dataId).id;return Ak(x,d,c,p,h,l,u,s?1:0,i?1:0,A),y!=null&&t.disposeData(y.dataId),f}var uoe={kernelName:Wo,backendName:"wasm",setupFunc:ooe,kernelFunc:loe},bk;function doe(e){bk=e.wasm.cwrap(Pu,null,["number","number","number","array","array","boolean"])}function poe(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,o=a.makeOutput(r.shape,"float32"),l=a.dataIdMap.get(r.dataId),u;return l.dtype!=="float32"&&(u=Ws({backend:a,inputs:{x:r},attrs:{dtype:"float32"}}),l=a.dataIdMap.get(u.dataId)),bk(a.dataIdMap.get(r.dataId).id,a.dataIdMap.get(s.dataId).id,a.dataIdMap.get(o.dataId).id,new Uint8Array(new Int32Array(r.shape).buffer),new Uint8Array(new Int32Array(s.shape).buffer),i),u!=null&&a.disposeData(u.dataId),o}var coe={kernelName:Pu,backendName:"wasm",setupFunc:doe,kernelFunc:poe},vk;function hoe(e){vk=e.wasm.cwrap(Uo,null,["number","array","number","array","number","number"])}function moe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=v.parseAxisParam(s,r.shape);if(r.shape.length===0)return m0({inputs:{x:r},backend:a});let o=a.makeOutput(r.shape,r.dtype),l=a.dataIdMap.get(r.dataId).id,u=a.dataIdMap.get(o.dataId).id,d=new Uint8Array(new Int32Array(i).buffer),c=new Uint8Array(new Int32Array(r.shape).buffer);vk(l,d,i.length,c,r.shape.length,u);let p=La({inputs:{x:o},attrs:{shape:r.shape},backend:a});return a.disposeData(o.dataId),p}var foe={kernelName:Uo,backendName:"wasm",kernelFunc:moe,setupFunc:hoe},wk;function goe(e){wk=e.wasm.cwrap(ol,null,["number","number","number","number","number","number","number","number","array","number","number"])}function yoe(e){let{inputs:t,backend:a,attrs:n}=e,{image:r}=t,{radians:s,fillValue:i,center:o}=n,l=a.makeOutput(r.shape,r.dtype),u=a.dataIdMap.get(r.dataId).id,d=a.dataIdMap.get(l.dataId).id,[c,p,h,m]=r.shape,[f,g]=I.getImageCenter(o,p,h),y=i===0,x=255,A=typeof i=="number"?[i,i,i,y?0:x]:[...i,x],b=new Uint8Array(new Int32Array(A).buffer);return wk(u,c,p,h,m,s,f,g,b,A.length,d),l}var xoe={kernelName:ol,backendName:"wasm",kernelFunc:yoe,setupFunc:goe},Aoe=Qe(Go),boe=Qe(Ns),kk;function voe(e){kk=e.wasm.cwrap(Ho,null,["number","number","number","number","number","number","array","number","number"])}function woe(e){let{backend:t,inputs:a,attrs:n}=e,{indices:r,updates:s}=a,{shape:i}=n,o=t.makeOutput(i,s.dtype);if(v.sizeFromShape(i)===0)return o;let{sliceRank:l,numUpdates:u,sliceSize:d,strides:c,outputSize:p}=Qh.calculateShapes(s,r,i),h=t.dataIdMap.get(r.dataId).id,m=t.dataIdMap.get(s.dataId).id,f=new Uint8Array(new Int32Array(c).buffer),g=t.dataIdMap.get(o.dataId).id;return kk(h,m,nt[s.dtype],l,u,d,f,p,g),o}var koe={kernelName:Ho,backendName:"wasm",setupFunc:voe,kernelFunc:woe},Ik;function Ioe(e){Ik=e.wasm.cwrap(qo,null,["number","number","number","number","number","number","bool","number"])}function Soe(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n;if(r.dtype!==s.dtype)throw new Error(`SearchSorted error: sorted_sequence must have the same dtype as values. 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Foe(e){let{backend:t,inputs:{x:a}}=e,n=t.dataIdMap.get(a.dataId).id,r=t.makeOutput(a.shape,a.dtype),s=t.dataIdMap.get(r.dataId).id;return v.sizeFromShape(r.shape)===0||Tk(n,s),r}var $oe={kernelName:"Sigmoid",backendName:"wasm",setupFunc:Moe,kernelFunc:Foe},Doe=Qe(Zo),Poe=Qe(Ko),_oe=Qe(Yo),Ooe=Qe(Jo);function zoe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n,o=v.sizeFromShape(s),l=[[0,0]];l.push(...i);for(let g=1+s.length;g0?l+1:0;if(u<0)throw new Error(I.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let d=r.shape.slice();d[0]=u;let c=a.dataIdMap.get(r.dataId).id,p=a.dataIdMap.get(s.dataId).id,h=a.dataIdMap.get(i.dataId).id,m=a.makeOutput(d,r.dtype),f=a.dataIdMap.get(m.dataId).id,g=a.makeOutput([4],"int32"),y=a.dataIdMap.get(g.dataId).id;Rk(c,nt[r.dtype],r.shape[0],p,h,f,y,t,0);let x=a.readSync(g.dataId),A;switch(x[0]){case 0:{A=I.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();break}case 1:{A=I.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();break}case 2:A=I.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(x[1],x[2]);break;case 3:A=I.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(x[1],x[2],x[3]);break;default:A=""}if(a.disposeData(g.dataId),A)throw a.disposeData(m.dataId),new Error(A);return m}function joe(e){return Mk(e,!0)}var qoe={kernelName:Vu,backendName:"wasm",setupFunc:Ek,kernelFunc:joe};function Xoe(e){return Mk(e,!1)}var Koe={kernelName:Uu,backendName:"wasm",setupFunc:Ek,kernelFunc:Xoe},Fk;function Yoe(e){Fk=e.wasm.cwrap(tl,null,["number","number","number","number","number","number","number","number","array","number","number"])}function Zoe(e){let{backend:t,inputs:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=a,{outputShape:o}=n,l=t.makeOutput(o,i.dtype);if(v.sizeFromShape(o)===0)return l;let{sliceRank:u,numUpdates:d,sliceSize:c,strides:p,outputSize:h}=I.calculateShapes(s,r,o),m=t.dataIdMap.get(r.dataId).id,f=t.dataIdMap.get(s.dataId).id,g=t.dataIdMap.get(i.dataId).id,y=new Uint8Array(new Int32Array(p).buffer),x=t.dataIdMap.get(l.dataId).id;return Fk(m,f,s.shape.length,g,nt[i.dtype],u,d,c,y,h,x),l}var Joe={kernelName:tl,backendName:"wasm",setupFunc:Yoe,kernelFunc:Zoe};function Qoe(e){let{inputs:t,attrs:a,backend:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=a,o=v.parseAxisParam(i,r.shape)[0],l=I.prepareSplitSize(r,s,o),u=new Array(r.shape.length).fill(0),d=r.shape.slice();return l.map(c=>{let p=[...d];p[o]=c;let h=Mi({inputs:{x:r},attrs:{begin:u,size:p},backend:n});return u[o]+=c,h})}var ele={kernelName:Wu,backendName:"wasm",kernelFunc:Qoe},tle=Qe(Es),ale=Qe(Fp),nle=!0,rle=Gt(Ms,nle),$k;function sle(e){$k=e.wasm.cwrap(Ds,null,["number","number","number","number"])}function 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Number(this.architecture.match(/\d+/));if(this.architecture.startsWith("xe"))return 12}return 0}isIntel(){return this.vendor==="intel"}},tue=class{constructor(e){this.device=e,this.numUsedBuffers=0,this.numFreeBuffers=0,this.freeBuffers=new Map,this.usedBuffers=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireBuffer(e,t,a=!1,n=!0){let r,s=dA(e,t);return n?(this.freeBuffers.has(s)||this.freeBuffers.set(s,[]),this.freeBuffers.get(s).length>0?(r=this.freeBuffers.get(s).pop(),this.numFreeBuffers--):(r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:a}),this.numBytesAllocated+=e)):(r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:a}),this.numBytesAllocated+=e),this.usedBuffers.has(s)||this.usedBuffers.set(s,[]),this.usedBuffers.get(s).push(r),this.numUsedBuffers++,this.numBytesUsed+=e,r}releaseBuffer(e,t=!0){if(this.freeBuffers.size===0)return;let a=e.size,n=e.usage,r=dA(a,n),s=this.usedBuffers.get(r),i=s.indexOf(e);if(i<0)throw new Error("Cannot find the 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r=cA(a),s=e*t*r,i=pA(e,t,a,n);if(this.freeTextures.has(i)||this.freeTextures.set(i,[]),this.usedTextures.has(i)||this.usedTextures.set(i,[]),this.numBytesUsed+=s,this.numUsedTextures++,this.freeTextures.get(i).length>0){this.numFreeTextures--;let l=this.freeTextures.get(i).shift();return this.usedTextures.get(i).push(l),l}this.numBytesAllocated+=s;let o=this.device.createTexture({size:[e,t],format:a,usage:n});return this.usedTextures.get(i).push(o),o}releaseTexture(e){if(this.freeTextures.size===0)return;let t=e.width,a=e.height,n=e.format,r=e.usage,s=pA(t,a,n,r);this.freeTextures.has(s)||this.freeTextures.set(s,[]),this.freeTextures.get(s).push(e),this.numFreeTextures++,this.numUsedTextures--;let i=this.usedTextures.get(s),o=i.indexOf(e);if(o<0)throw new Error("Cannot release a texture that was never provided by this texture manager");i.splice(o,1);let l=cA(n),u=t*a*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(a=>{a.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function pA(e,t,a,n){return`${e}_${t}_${a}_${n}`}function cA(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}function nue(e,t){if(Math.max(...e)>5)throw new Error("Cannot symbolically compute strides for rank > 6 tensor.");let a=e.length,n="xyzwuv",r=e.map(i=>`${t}.${n[i]}`),s=new Array(a-1);s[a-2]=r[a-1];for(let i=a-3;i>=0;--i)s[i]=`(${s[i+1]} * ${r[i+1]})`;return s}var Bs=(e,t,a)=>a==="int32"?`atomicAdd(${e}, bitcast(${t}));`:` { var oldValue = 0; loop { let newValueF32 = bitcast(oldValue) + (${t}); let newValue = bitcast(newValueF32); let res = atomicCompareExchangeWeak(${e}, oldValue, newValue); if res.exchanged { break; } oldValue = res.old_value; } }`,lu;(function(e){e[e.FROM_PIXELS=0]="FROM_PIXELS",e[e.DRAW=1]="DRAW"})(lu||(lu={}));var rue=(e,t,a,n,r)=>{let s={dtype:n.dtype,shape:n.shape},i=iue(a,s,t),o=e.createShaderModule({code:i,label:t.constructor.name}),l=B().get("WEBGPU_PRINT_SHADER");if(l!==""){l=l.toLowerCase();let u=l.split(",");(l==="all"||u.some(d=>t.shaderKey.toLowerCase().includes(d)))&&(console.group(t.shaderKey),console.debug(i),console.groupEnd())}return r?e.createComputePipelineAsync({compute:{module:o,entryPoint:"_start"},label:t.constructor.name,layout:"auto"}):e.createComputePipeline({compute:{module:o,entryPoint:"_start"},label:t.constructor.name,layout:"auto"})},Xe=(e,t="f32")=>{switch(e){case 1:return`${t}`;case 2:return`vec2<${t}>`;case 3:return`vec3<${t}>`;case 4:return`vec4<${t}>`;default:throw new Error(`${e}-component ${t} is not supported.`)}};function Dt(e){if(e<=1)return"i32";if(e===2)return"vec2";if(e===3)return"vec3";if(e===4)return"vec4";if(e===5)return"vec5";if(e===6)return"vec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Nr(e){if(e===0)return"x";if(e===1)return"y";if(e===2)return"z";if(e===3)return"w";if(e===4)return"u";if(e===5)return"v";throw Error(`Index ${e} is not yet supported`)}function ue(...e){let t;switch(e.length){case 0:t=` fn main() `;break;case 1:t=` fn main(${e[0]} : i32) `;break;default:throw Error("Unreachable")}return t}function hA(e,t){let a;return a=` ${sue(t)} fn _start(@builtin(local_invocation_id) LocalId : vec3, @builtin(global_invocation_id) GlobalId : vec3, @builtin(local_invocation_index) LocalIndex: u32, @builtin(workgroup_id) WorkgroupId : vec3, @builtin(num_workgroups) NumWorkgroups : vec3) { localId = LocalId; localIndex = LocalIndex; globalId = GlobalId; numWorkgroups = NumWorkgroups; workgroupId = WorkgroupId; ${e?"main(getGlobalIndex());":"main();"}; } `,a}function sue(e){return` @compute @workgroup_size(${e.workgroupSize[0]}, ${e.workgroupSize[1]}, ${e.workgroupSize[2]}) `}function iue(e,t,a){let n=[],r=a.workgroupSize[0]*a.workgroupSize[1]*a.workgroupSize[2];if(a.outputComponent=a.outputComponent?a.outputComponent:1,n.push(` var localId: vec3; var localIndex: u32; var globalId: vec3; var numWorkgroups: vec3; var workgroupId: vec3; // Only used when the y/z dimension of workgroup size is 1. fn getGlobalIndex() -> i32 { ${Vk(a)?" return i32(globalId.x);":` return i32((workgroupId.z * numWorkgroups.x * numWorkgroups.y + workgroupId.y * numWorkgroups.x + workgroupId.x) * ${r}u + localIndex); `} } `),a.pixelsOpType!=null){let h=a.pixelsOpType===lu.FROM_PIXELS?`@group(0) @binding(0) var result: array<${gi(t.dtype,a.outputComponent)}>;`:`@group(0) @binding(1) var inBuf : array<${gi(e[0].dtype,a.outputComponent)}>;`,m=t.shape.length===3?"vec2":"i32";n.push(` struct Uniform { outShapeStrides : ${m}, size : i32, numChannels : i32, alpha : f32, }; ${h} @group(0) @binding(2) var uniforms: Uniform; `);let f=fA(a);return[mA,n.join(` `),mh(t.shape),a.getUserCode(),hA(f,a)].join(` `)}let s,i,o="struct Uniforms { NAN : f32, INFINITY : f32, ";a.variableNames.forEach((h,m)=>{let f=Dt(e[m].shape.length);o+=`${h.charAt(0).toLowerCase()+h.slice(1)}Shape : ${f}, `,s=e[m].shape.length-1,i=Dt(s),o+=`${h.charAt(0).toLowerCase()+h.slice(1)}ShapeStrides: ${i}, `});let l=Dt(t.shape.length);o+=`outShape : ${l}, `,s=t.shape.length-1,i=Dt(s),o+=` outShapeStrides: ${i}, `,a.size&&(o+="size : i32, "),a.uniforms&&(o+=a.uniforms),o+="};",o=fue(o),n.push(o),a.atomic?n.push(` @group(0) @binding(0) var result: array>; `):n.push(` @group(0) @binding(0) var result: array<${gi(t.dtype,a.outputComponent)}>; `),a.variableNames.forEach((h,m)=>{n.push(` @group(0) @binding(${1+m}) var ${h}: array<${a.variableComponents?gi(e[m].dtype,a.variableComponents[m]):gi(e[m].dtype,a.outputComponent)}>; `)}),o!==""&&n.push(` @group(0) @binding(${1+a.variableNames.length}) var uniforms: Uniforms; `);let u=cue(t.shape,a.dispatchLayout),d=[mA,n.join(` `)+lue,mh(t.shape),u,hue(t.shape.length)];a.atomic||d.push(mue(t.shape,t.dtype,a.outputComponent)),a.variableNames.forEach((h,m)=>{d.push(`${mh(e[m].shape,h)}`)});let c=e.map((h,m)=>pue(h,t.shape,a.variableComponents?a.variableComponents[m]:a.outputComponent,a.dispatchLayout.x.length===t.shape.length)).join(` `);d.push(c),d.push(a.getUserCode());let p=fA(a);return d.push(hA(p,a)),d.join(` `)}function oue(e,t,a){let n=e.shaderKey;if(e.pixelsOpType!=null)return n;let r=[],s=[];t.forEach(d=>{r.push(d.shape),s.push(d.dtype)}),r.push(a.shape),s.push(a.dtype);let i=t.map(d=>I.getBroadcastDims(d.shape,a.shape)),o=t.map(d=>v.arraysEqual(d.shape,a.shape)).join("_"),l=i.map(d=>d.join("_")).join(";"),u=Vk(e)?"flatDispatch":"";return n+="_"+(e.workgroupSize?e.workgroupSize.join(","):"")+r.map(d=>d.length).join(",")+s.join(",")+e.variableNames.join(",")+l+o+u,n}var mA=` struct vec5 {x: i32, y: i32, z: i32, w: i32, u: i32}; struct vec6 {x: i32, y: i32, z: i32, w: i32, u: i32, v: i32}; // Checks whether coordinates lie within the bounds of the shape. fn coordsInBounds2D(coord : vec2, shape : vec2) -> bool { return all(coord >= vec2(0)) && all(coord < shape); } fn coordsInBounds3D(coord : vec3, shape : vec3) -> bool { return all(coord >= vec3(0)) && all(coord < shape); } fn coordsInBounds4D(coord : vec4, shape : vec4) -> bool { return all(coord >= vec4(0)) && all(coord < shape); } fn getIndexFromCoords1D(coord : i32, shape : i32) -> i32 { return coord; } fn getIndexFromCoords2D(coords : vec2, shape : vec2) -> i32 { return dot(coords, vec2(shape.y, 1)); } fn getIndexFromCoords3D(coords : vec3, shape : vec3) -> i32 { return dot(coords, vec3(shape.y * shape.z, shape.z, 1)); } fn getIndexFromCoords4D(coords : vec4, shape : vec4) -> i32 { return dot(coords, vec4( shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1)); } fn getIndexFromCoords5D(coords : vec5, shape : vec5) -> i32 { let shapeStrides: vec5 = vec5(shape.y * shape.z * shape.w * shape.u, shape.z * shape.w * shape.u, shape.w * shape.u, shape.u, 1); return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u; } fn getIndexFromCoords6D(coords : vec6, shape : vec6) -> i32 { let shapeStrides: vec6 = vec6(shape.y * shape.z * shape.w * shape.u * shape.v, shape.z * shape.w * shape.u * shape.v, shape.w * shape.u * shape.v, shape.u * shape.v, shape.v, 1); return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u + coords.v*shapeStrides.v; } // NaN defination in IEEE 754-1985 is : // - sign = either 0 or 1. // - biased exponent = all 1 bits. // - fraction = anything except all 0 bits (since all 0 bits represents infinity). // https://en.wikipedia.org/wiki/IEEE_754-1985#Representation_of_non-numbers fn isnan(val: f32) -> bool { let floatToUint: u32 = bitcast(val); return (floatToUint & 0x7fffffffu) > 0x7f800000u; } fn isnanVec4(val : vec4) -> vec4 { let floatToUint: vec4 = bitcast>(val); return (floatToUint & vec4(0x7fffffffu)) > vec4(0x7f800000u); } `,lue=` fn isinf(val: f32) -> bool { return abs(val) == uniforms.INFINITY; } `;function mh(e,t=""){let a=e.length,n=t!==""?`get${t.charAt(0).toUpperCase()+t.slice(1)}CoordsFromIndex`:"getCoordsFromIndex",r=t!==""?`${t.charAt(0).toLowerCase()+t.slice(1)}ShapeStrides`:"outShapeStrides";if(a<=1)return`fn ${n}(index : i32) -> i32 { return index; }`;let s=v.computeStrides(e),i=Dt(a),o=[];for(let u=0;u vec2 { let d0 = index / uniforms.${r}; let d1 = index - d0 * uniforms.${r}; return vec2(d0, d1); }`;let l;return l="var index2 = index;"+s.map((u,d)=>{let c=`let ${o[d]} = index2 / uniforms.${r}.${Nr(d)}`,p=d===s.length-1?`let ${o[d+1]} = index2 - ${o[d]} * uniforms.${r}.${Nr(d)}`:`index2 = index2 - ${o[d]} * uniforms.${r}.${Nr(d)}`;return`${c}; ${p};`}).join(""),` fn ${n}(index : i32) -> ${i} { ${l} return ${i}(${o.join(",")}); } `}function uue(e,t){let a=e.name,n=e.shape.length,r=Dt(n),s="get"+a.charAt(0).toUpperCase()+a.slice(1),i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=i.map(d=>`${d} : i32`).join(", ");if(n<1)return` fn ${s}() -> ${Xe(t)} { return ${Xe(t)}(${a}[0]); } `;let l=`uniforms.${a.charAt(0).toLowerCase()+a.slice(1)}Shape`,u=`${n}D`;return n===0&&(u="1D"),` fn ${s}(${o}) -> ${Xe(t)} { return ${Xe(t)}(${a}[getIndexFromCoords${u}(${r}(${i.join(",")}), ${l})${t===1?"":` / ${t}`}]); } `}function due(e,t,a,n){let r=e.name,s=r.charAt(0).toUpperCase()+r.slice(1),i="get"+s+"ByOutput",o=e.shape.length,l=t.length,u=Dt(l);if(v.arraysEqual(e.shape,t)&&n)return` fn ${i}Index(globalIndex : i32) -> ${Xe(a)} { return ${Xe(a)}(${r}[globalIndex]); } fn ${i}Coords(coords : ${u}) -> ${Xe(a)} { return ${Xe(a)}(${r}[${l>1?"getOutputIndexFromCoords(coords)":"coords"}${a===1?"":` / ${a}`}]); } `;let d=I.getBroadcastDims(e.shape,t),c=l-o,p="";if(o===0)return` fn ${i}Index(globalIndex : i32) -> ${Xe(a)}{ return get${s}(); } fn ${i}Coords(coords : ${u}) -> ${Xe(a)}{ return get${s}(); } `;l<2&&d.length>=1?p="coords = 0;":p=d.map(g=>`coords.${Nr(g+c)} = 0;`).join(` `);let h="";if(l<2&&o>0)h="coords";else if(l>1){let g=Dt(o),y=e.shape.map((x,A)=>`coords.${Nr(A+c)}`).join(", ");h=`${g}(${y})`}else h="coords";let m=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,f=`${o}D`;return` fn ${i}Index(globalIndex : i32) -> ${Xe(a)} { var coords = getCoordsFromIndex(globalIndex); ${p} return ${Xe(a)}(${r}[getIndexFromCoords${f}(${h}, ${m})${a===1?"":` / ${a}`}]); } fn ${i}Coords(coordsIn : ${u}) -> ${Xe(a)} { var coords = coordsIn; ${p} return ${Xe(a)}(${r}[getIndexFromCoords${f}(${h}, ${m})${a===1?"":` / ${a}`}]); } `}function pue(e,t,a,n){let r=uue(e,a);return e.shape.length<=t.length&&(r+=due(e,t,a,n)),r}function cue(e,t){let{x:a,y:n=[],z:r=[]}=t,s=e.length,i=a.length+n.length+r.length;if(i!==s)return"";if(a.length===s)return`fn getOutputCoords() -> ${Dt(s)}{ let globalIndex = getGlobalIndex(); return getCoordsFromIndex(globalIndex); } `;let o="",l=[a,n,r];for(let p=0;p ${d} { ${o} `;return u.length===0?c+=`return ${d}(0); }`:c+=`return ${d}(${u.join(",")}); }`,c}function hue(e){let t="";switch(e){case 0:case 1:t+=` fn getOutputIndexFromCoords(coords : i32) -> i32 { return coords; } `;break;case 2:t+=` fn getOutputIndexFromCoords(coords : vec2) -> i32 { return dot(coords, vec2(uniforms.outShapeStrides, 1)); } `;break;case 3:t+=` fn getOutputIndexFromCoords(coords : vec3) -> i32 { return dot(coords, vec3(uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, 1)); } `;break;case 4:t+=` fn getOutputIndexFromCoords(coords : vec4) -> i32 { return dot(coords, vec4( uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, uniforms.outShapeStrides.z, 1)); } `;break;case 5:t+=` fn getOutputIndexFromCoords(coords : vec5) -> i32 { return coords.x * uniforms.outShapeStrides.x + coords.y * uniforms.outShapeStrides.y + coords.z * uniforms.outShapeStrides.z + coords.w * uniforms.outShapeStrides.w + coords.u; } `;break;case 6:t+=` fn getOutputIndexFromCoords(coords : vec6) -> i32 { return coords.x * uniforms.outShapeStrides.x + coords.y * uniforms.outShapeStrides.y + coords.z * uniforms.outShapeStrides.z + coords.w * uniforms.outShapeStrides.w + coords.u * uniforms.outShapeStrides.u + coords.v; } `;break;default:v.assert(!1,()=>`Unsupported ${e}D shape`);break}return t}function Vk(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function gi(e,t=1){if(e==="float32")return Xe(t,"f32");if(e==="int32"||e==="bool")return Xe(t,"i32");throw new Error(`type ${e} is not supported.`)}function mue(e,t,a){let n=e.length,r=gi(t,a),s=`fn setOutputAtIndex(flatIndex : i32, value : ${Xe(a)}) { result[flatIndex] = ${r}(value); } fn setOutputAtIndexI32(flatIndex : i32, value : ${Xe(a,"i32")}) { result[flatIndex] = ${r}(value); } `;if(n>=2){let i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=Dt(n);s+=` fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : ${Xe(a)}) { let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")})); setOutputAtIndex(flatIndex${a===1?"":` / ${a}`}, value); } fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : ${Xe(a,"i32")}) { let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")})); setOutputAtIndexI32(flatIndex${a===1?"":` / ${a}`}, value); } `}return s}function fue(e){let t=/(\w+)\s*:\s*vec(5|6)/g;e=e.replace(t,n=>"@align(16) "+n);let a=/vec(5|6)\s*,\s*(\w+)/g;return e=e.replace(a,(n,r,s)=>`vec${r}, @align(16) ${s}`),e}function fA(e){return!(e.dispatchLayout.hasOwnProperty("y")&&e.dispatchLayout.y.length!==0||e.dispatchLayout.hasOwnProperty("z")&&e.dispatchLayout.z.length!==0)}var Uk={};Ke(Uk,{GPUBytesPerElement:()=>Q1,MatMulProgramType:()=>Ln,assertNotComplex:()=>ay,computeDispatch:()=>de,computeWorkPerThreadForConv2d:()=>ey,computeWorkgroupInfoForMatMul:()=>Gk,computeWorkgroupSizeForConv2d:()=>Q3,flatDispatchLayout:()=>me,isWebGPUSupported:()=>ty,tilesFitEvenlyIntoShape:()=>gue});var bi=e=>{let t=1;for(let a=0;aa%e[n]===0)}function de(e,t,a=[1,1,1],n=[1,1,1]){let[r,s,i]=[Math.ceil(bi(e.x.map(o=>t[o]))/(a[0]*n[0])),e.y?Math.ceil(bi(e.y.map(o=>t[o]))/(a[1]*n[1])):1,e.z?Math.ceil(bi(e.z.map(o=>t[o]))/(a[2]*n[2])):1];return[r,s,i]}function Gk(e,t,a,n=!1){let r=[8,8,1],s=[4,4,1];return n||(e<=8&&(s[1]=1),t<=16&&a<=16&&(r[0]=4)),{workgroupSize:r,elementsPerThread:s}}function Q3(e,t,a=!1){if(a)return[8,8,1];let n=bi(e.x.map(s=>t[s])),r=bi(e.y.map(s=>t[s]));return n<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function ey(e,t,a=!1){if(a)return[4,4,1];let n=bi(e.x.map(s=>t[s])),r=bi(e.y.map(s=>t[s]));return n<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function me(e){return{x:e.map((t,a)=>a)}}function Q1(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function ty(){return!!(globalThis&&globalThis.navigator&&globalThis.navigator.gpu)}function ay(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGPU backend.`)})}var Ln;(function(e){e[e.MatMulReduceProgram=0]="MatMulReduceProgram",e[e.MatMulSplitKProgram=1]="MatMulSplitKProgram",e[e.MatMulSmallOutputSizeProgram=2]="MatMulSmallOutputSizeProgram",e[e.MatMulPackedProgram=3]="MatMulPackedProgram",e[e.MatMulMax=4]="MatMulMax"})(Ln||(Ln={}));var yue=B().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),xue=(e,t)=>{let a=e.limits.maxComputeWorkgroupsPerDimension,n=t.dispatchLayout,r=t.dispatch;if(r.every(i=>i<=a))return r;v.assert(r[0]>a&&n.y===void 0&&n.z===void 0,()=>"Dispatch size exceeds WebGPU limits in Y or Z dimension.");let s=Math.ceil(Math.sqrt(r[0]));return s>a?(s=Math.ceil(Math.cbrt(r[0])),v.assert(s<=a,()=>"Total dispatch size exceeds WebGPU maximum."),[s,s,s]):[s,s,1]},ny=class Hk extends du{nextDataId(){return Hk.nextDataId++}constructor(t,a){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchCountInPass=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.queryResolveBuffer=null,this.querySet=null,this.querySetCount=2,this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,this.hasReadSyncWarned=!1,this.hasTimestampQueryWarned=!1,!ty())throw new Error("WebGPU is not supported on this device");this.pipelineCache={},this.device=t,this.queue=t.queue,this.commandEncoder=null,this.computePassEncoder=null,this.adapterInfo=new eue(a),this.supportTimestampQuery=this.device.features.has("timestamp-query"),this.thresholdToIncreaseWorkgroups=this.adapterInfo.intelGPUGeneration>=12?16:8,this.bufferManager=new tue(this.device),this.textureManager=new aue(this.device),this.tensorMap=new hp(this,St()),B().getBool("WEBGPU_USE_PROFILE_TOOL")&&(this.dummyCanvas=document.createElement("canvas"),this.dummyCanvas.width=1,this.dummyCanvas.height=1,this.dummyContext=this.dummyCanvas.getContext("webgpu"),this.dummyContext.configure({device:t,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}floatPrecision(){return 32}disposeData(t,a=!1){if(!this.tensorMap.has(t))return!0;let n=this.tensorMap.get(t);return a?n.refCount=0:n.refCount--,n.refCount>0?!1:(n.complexTensorInfos!=null&&(this.disposeData(n.complexTensorInfos.real.dataId),this.disposeData(n.complexTensorInfos.imag.dataId)),this.commandQueueOwnedIds.has(t)?(this.tensorDataPendingDisposal.push(t),!0):(this.releaseResource(t),this.tensorMap.delete(t),!0))}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}releaseResource(t){let a=this.tensorMap.get(t);if(!(!a||!a.resource)){if(a.external){a.resource=null;return}a.resource instanceof GPUBuffer?this.bufferManager.releaseBuffer(a.resource):a.resource instanceof GPUTexture&&this.textureManager.releaseTexture(a.resource),a.resource=null}}refCount(t){return this.tensorMap.has(t)?this.tensorMap.get(t).refCount:0}incRef(t){let a=this.tensorMap.get(t);a.refCount++}decRef(t){if(this.tensorMap.has(t)){let a=this.tensorMap.get(t);a.refCount--}}write(t,a,n){if(n==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={id:this.nextDataId()};return this.tensorMap.set(r,{dtype:n,shape:a,values:t,refCount:1}),r}move(t,a,n,r,s){if(r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.tensorMap.set(t,{dtype:r,shape:n,values:a,refCount:s})}submitQueue(){this.queue.submit([this.commandEncoder.finish()]),this.commandEncoder=null,this.dispatchCountInPass=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(t=>{this.releaseResource(t),this.tensorMap.delete(t)}),this.uniformPendingDisposal.forEach(t=>this.bufferManager.releaseBuffer(t)),this.stagingPendingDisposal.forEach(t=>this.bufferManager.releaseBuffer(t,!1)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.commandEncoder||(this.commandEncoder=this.device.createCommandEncoder())}endComputePassEncoder(){this.computePassEncoder&&(this.computePassEncoder.end(),this.computePassEncoder=null)}async checkCompileCompletionAsync(){let t;try{t=await Promise.all(Object.values(this.pipelineCache))}catch(a){throw new Error(a.message)}Object.keys(this.pipelineCache).map((a,n)=>{this.pipelineCache[a]=t[n]})}async getBufferData(t){if(B().getBool("WEBGPU_ENGINE_COMPILE_ONLY"))return console.warn("The data may be invalid since WEBGPU_ENGINE_COMPILE_ONLY is true, this can only be called when WEBGPU_ENGINE_COMPILE_ONLY is false"),null;let a=t.size,n=this.bufferManager.acquireBuffer(a,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(t,0,n,0,a),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let r=n.getMappedRange().slice(0);return n.unmap(),n!=null&&this.bufferManager.releaseBuffer(n),B().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),r}convertAndCacheOnCPU(t,a){let n=this.tensorMap.get(t);return n.values=a,n.values}readSync(t){let a=this.tensorMap.get(t),{values:n,complexTensorInfos:r}=a;if(n!=null||a.dtype==="string")return n;if(a.dtype==="complex64"){let f=this.readSync(r.real.dataId),g=this.readSync(r.imag.dataId),y=v.convertBackendValuesAndArrayBuffer(I.mergeRealAndImagArrays(f,g).buffer,"float32");return this.convertAndCacheOnCPU(t,y),y}this.hasReadSyncWarned||(this.hasReadSyncWarned=!0,console.warn("The performance of synchronously reading data from GPU to CPU is poor on the webgpu backend, please use asynchronous APIs instead."));let s=["opaque","premultiplied"],i=a.resource,o=i.size;v.assert(o%4===0,()=>"Because there is 4 bytes for one pixel, buffer size must be multiple of 4.");let l=o/4,u=new ArrayBuffer(o),d=256,c=256,p=s.map(f=>new OffscreenCanvas(d,c)),h=new OffscreenCanvas(d,c);this.endComputePassEncoder(),p.map((f,g)=>{let y=f.getContext("webgpu");return y.configure({device:this.device,format:"bgra8unorm",usage:GPUTextureUsage.COPY_DST,alphaMode:s[g]}),y.getCurrentTexture()}).map((f,g)=>{let y=d*4,x=(N,M,F)=>{this.ensureCommandEncoderReady(),this.commandEncoder.copyBufferToTexture({buffer:i,bytesPerRow:y,offset:F},{texture:f},{width:N,height:M}),this.submitQueue();let E=h.getContext("2d",{willReadFrequently:!0});E.clearRect(0,0,N,M),E.drawImage(p[g],0,0);let T=E.getImageData(0,0,N,M).data,D=s[g],O=new Uint8ClampedArray(u,F,N*M*4);for(let W=0;W0&&(x(b,w,S),S+=w*(d*4)),b=C%d,b>0&&x(b,1,S)});let m=v.convertBackendValuesAndArrayBuffer(u,a.dtype);return this.convertAndCacheOnCPU(t,m),m}async read(t){if(!this.tensorMap.has(t))throw new Error(`Tensor ${t} was not registered!`);let a=this.tensorMap.get(t),{values:n}=a;if(n!=null)return n;let r;if(a.dtype==="complex64"){let s=await Promise.all([this.read(a.complexTensorInfos.real.dataId),this.read(a.complexTensorInfos.imag.dataId)]),i=s[0],o=s[1];r=I.mergeRealAndImagArrays(i,o)}else{let s=await this.getBufferData(a.resource);r=v.convertBackendValuesAndArrayBuffer(s,a.dtype)}return this.convertAndCacheOnCPU(t,r),r}copyBuffer(t){let a=t.size,n=t.usage,r=this.bufferManager.acquireBuffer(a,n);return this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(t,0,r,0,a),this.submitQueue(),r}createTensorFromGPUData(t,a,n){let r=t.buffer;if(n==="complex64")throw new Error("Cannot write to a complex64 dtype. ");let s={id:this.nextDataId()};this.tensorMap.set(s,{dtype:n,shape:a,values:null,refCount:1,external:t.zeroCopy});let i=this.tensorMap.get(s),o=Q1(i.dtype)*v.sizeFromShape(i.shape);if(t.buffer.sizev.decodeString(r));return Te(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Te(t.shape,t.dtype,a)}async time(t){!this.supportTimestampQuery&&!this.hasTimestampQueryWarned&&(console.warn("This device doesn't support timestamp-query extension. Start Chrome browser with flag --enable-dawn-features=allow_unsafe_apis to try it again. Otherwise, zero will be shown for the kernel time when profiling mode is enabled."),this.hasTimestampQueryWarned=!0);let a=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=v.flatten(this.activeTimers.map(u=>u.query)).filter(u=>u!=null),i=v.flatten(this.activeTimers.map(u=>u.name)).filter(u=>u!=null);this.activeTimers=a,r&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},l=await Promise.all(s);return o.kernelMs=v.sum(l),o.getExtraProfileInfo=()=>l.map((u,d)=>({name:i[d],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,o}makeTensorInfo(t,a,n){return a==="string"&&n!=null&&n.length>0&&v.isString(n[0])&&(n=n.map(r=>v.encodeString(r))),{dataId:this.write(n,t,a),shape:t,dtype:a}}tensorToBinding(t){if(!t)return null;let a=this.tensorMap.get(t.dataId).resource;return a instanceof GPUBuffer?{buffer:a}:a instanceof GPUTexture?a.createView():a}uploadToGPU(t){let a=this.tensorMap.get(t);if(a.resource!=null)return;let n=Q1(a.dtype)*v.sizeFromShape(a.shape),r,s=GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST;if(a.values){if(r=this.bufferManager.acquireBuffer(n,s,!0),r.mapState==="unmapped"){let i=this.bufferManager.acquireBuffer(n,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,!0,!1),o=i.getMappedRange();a.dtype==="int32"||a.dtype==="bool"?new Int32Array(o).set(a.values):new Float32Array(o).set(a.values),i.unmap(),this.ensureCommandEncoderReady(),this.endComputePassEncoder(),this.commandEncoder.copyBufferToBuffer(i,0,r,0,n),this.stagingPendingDisposal.push(i)}else{let i=r.getMappedRange();a.dtype==="int32"||a.dtype==="bool"?new Int32Array(i).set(a.values):new Float32Array(i).set(a.values),r.unmap()}a.values=null}else r=this.bufferManager.acquireBuffer(n,s);a.resource=r}makeUniforms(t){let a=0,n=0,r=[],s=1;t.forEach(l=>{l.data.length===0&&(l.data=[1]);let u;switch(l.data.length){case 1:u=4;break;case 2:u=8;break;case 3:u=16;break;case 4:u=16;break;case 5:u=16;break;case 6:u=16;break;default:v.assert(!1,()=>`Unsupported ${l.data.length}D shape`)}(n===5||n===6)&&(u=16),u>s&&(s=u),a=Math.ceil(a/u)*u,n=l.data.length,r.push(a),a+=l.data.length*4}),a=Math.ceil(a/s)*s;let i=new ArrayBuffer(a);t.forEach((l,u)=>{let d=r[u];l.type==="int32"?new Int32Array(i,d,l.data.length).set(l.data):l.type==="uint32"?new Uint32Array(i,d,l.data.length).set(l.data):new Float32Array(i,d,l.data.length).set(l.data)});let o=this.bufferManager.acquireBuffer(a,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);return this.queue.writeBuffer(o,0,i,0,a),this.uniformPendingDisposal.push(o),{offset:0,size:a,buffer:o}}runWebGPUProgram(t,a,n,r,s){if(s||(s=this.makeTensorInfo(t.outputShape,n)),v.sizeFromShape(s.shape)===0)return this.tensorMap.get(s.dataId).values=v.getTypedArrayFromDType(s.dtype,0),s;this.uploadToGPU(s.dataId),t.dispatch=xue(this.device,t);let i=a.map((l,u)=>{if(l.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");return this.uploadToGPU(l.dataId),{dtype:this.tensorMap.get(l.dataId).dtype,shape:l.shape,name:t.variableNames[u]}});t.shaderKey=oue(t,i,s);let o=B().getBool("WEBGPU_ENGINE_COMPILE_ONLY");return t.shaderKey in this.pipelineCache||(this.pipelineCache[t.shaderKey]=rue(this.device,t,i,s,o)),t.pipeline=this.pipelineCache[t.shaderKey],o||this.recordAndSubmit(t,s,a,r),s}recordAndSubmit(t,a,n,r){if(t.pipeline instanceof Promise)throw new Error("Please call checkCompileCompletionAsync to ensure parallel compilation is done!");let s=[],i=[],o="int32";if(t.pixelsOpType==null){s.push({type:"float32",data:[NaN]},{type:"float32",data:[1/0]}),i=n.concat(a).map(h=>h.shape);let p="int32";i.map(h=>{s.push({type:p,data:h});let m=v.computeStrides(h);s.push({type:p,data:m})})}else{let p=v.computeStrides(a.shape);s.push({type:o,data:p})}if(t.size){let p=v.sizeFromShape(t.outputShape);s.push({type:o,data:[t.outputComponent?p/t.outputComponent:p]})}r&&(s=[...s,...r]);let l=[this.tensorToBinding(a),...n.map(p=>this.tensorToBinding(p)),this.makeUniforms(s)];n.forEach(p=>{this.commandQueueOwnedIds.add(p.dataId)}),this.commandQueueOwnedIds.add(a.dataId);let u=this.device.createBindGroup({layout:t.pipeline.getBindGroupLayout(0),entries:l.map((p,h)=>({binding:h,resource:p}))}),d=this.activeTimers!=null;this.ensureCommandEncoderReady();let c={};d&&this.supportTimestampQuery?(this.endComputePassEncoder(),this.querySet==null&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:this.querySetCount})),c.timestampWrites={querySet:this.querySet,beginningOfPassWriteIndex:0,endOfPassWriteIndex:1},this.computePassEncoder=this.commandEncoder.beginComputePass(c)):this.computePassEncoder||(this.computePassEncoder=this.commandEncoder.beginComputePass(c)),this.computePassEncoder.setPipeline(t.pipeline),this.computePassEncoder.setBindGroup(0,u),this.computePassEncoder.dispatchWorkgroups(t.dispatch[0],t.dispatch[1],t.dispatch[2]),this.dispatchCountInPass++,(d||B().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchCountInPass||t.pixelsOpType===lu.DRAW)&&(this.endComputePassEncoder(),d?this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime()}):this.submitQueue())}async getQueryTime(){if(!this.supportTimestampQuery)return 0;this.queryResolveBuffer==null&&(this.queryResolveBuffer=this.bufferManager.acquireBuffer(this.querySetCount*8,GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST|GPUBufferUsage.QUERY_RESOLVE)),this.commandEncoder.resolveQuerySet(this.querySet,0,this.querySetCount,this.queryResolveBuffer,0);let t=this.bufferManager.acquireBuffer(this.querySetCount*8,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.commandEncoder.copyBufferToBuffer(this.queryResolveBuffer,0,t,0,this.querySetCount*8),this.submitQueue(),await t.mapAsync(GPUMapMode.READ);let a=new BigUint64Array(t.getMappedRange()),n=Number(a[1]-a[0])/1e6;return t.unmap(),this.bufferManager.releaseBuffer(t),n}shouldExecuteOnCPU(t,a=yue){return B().getBool("WEBGPU_CPU_FORWARD")&&t.every(n=>this.tensorMap.get(n.dataId).resource==null&&v.sizeFromShape(n.shape){let e={powerPreference:B().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),a={},n=[];t.features.has("timestamp-query")&&n.push("timestamp-query"),t.features.has("bgra8unorm-storage")&&n.push(["bgra8unorm-storage"]),a.requiredFeatures=n;let r=t.limits;a.requiredLimits={maxComputeWorkgroupStorageSize:r.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:r.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:r.maxStorageBufferBindingSize,maxBufferSize:r.maxBufferSize,maxComputeWorkgroupSizeX:r.maxComputeWorkgroupSizeX,maxComputeInvocationsPerWorkgroup:r.maxComputeInvocationsPerWorkgroup};let s=await t.requestDevice(a),i=await t.requestAdapterInfo();return new ny(s,i)},3);var De;(function(e){e[e.ADD=0]="ADD",e[e.ATAN2=1]="ATAN2",e[e.COMPLEX_MULTIPLY_IMAG=2]="COMPLEX_MULTIPLY_IMAG",e[e.COMPLEX_MULTIPLY_REAL=3]="COMPLEX_MULTIPLY_REAL",e[e.DIV=4]="DIV",e[e.ELU_DER=5]="ELU_DER",e[e.EQUAL=6]="EQUAL",e[e.FLOOR_DIV=7]="FLOOR_DIV",e[e.GREATER=8]="GREATER",e[e.GREATER_EQUAL=9]="GREATER_EQUAL",e[e.LESS=10]="LESS",e[e.LESS_EQUAL=11]="LESS_EQUAL",e[e.LOGICAL_AND=12]="LOGICAL_AND",e[e.LOGICAL_OR=13]="LOGICAL_OR",e[e.MAX=14]="MAX",e[e.MIN=15]="MIN",e[e.MOD=16]="MOD",e[e.MUL=17]="MUL",e[e.NOT_EQUAL=18]="NOT_EQUAL",e[e.POW=19]="POW",e[e.PRELU=20]="PRELU",e[e.SQUARED_DIFFERENCE=21]="SQUARED_DIFFERENCE",e[e.SUB=22]="SUB"})(De||(De={}));var Aue="let resultTemp = a + b;",bue="let resultTemp = atan2(a, b);",vue="let resultTemp = areal * breal - aimag * bimag;",wue="let resultTemp = areal * bimag + aimag * breal;",kue="let resultTemp = a / b;",Iue="let resultTemp = select(a * (b + 1.0), a, b >= b - b);",Sue=` let zero = sign(a) * 0 + 0; let one = sign(b) * 0 + 1; let resultTemp = select(zero, one, a == b); `,Tue=` let remainder = select(a % b, round(a % b), (round(a) == a) & (round(b) == b)); let quotient = (a - remainder) / b; let resultTemp = round(select(quotient, quotient - 1, sign(remainder) == -sign(b))); `,Cue=` let zero = sign(a) * 0 + 0; let one = sign(b) * 0 + 1; let resultTemp = select(zero, one, a > b); `,Nue=` let zero = sign(a) * 0 + 0; let one = sign(b) * 0 + 1; let resultTemp = select(zero, one, a >= b); `,Rue=` let zero = sign(a) * 0 + 0; let one = sign(b) * 0 + 1; let resultTemp = select(zero, one, a < b); `,Eue=` let zero = sign(a) * 0 + 0; let one = sign(b) * 0 + 1; let resultTemp = select(zero, one, a <= b); `,Mue="return f32(a >= 1.0 && b >= 1.0);",Fue=`return (vec4(a >= vec4(1.0)) * vec4(b >= vec4(1.0)));`,$ue="return f32(a >= 1.0 || b >= 1.0);",Due=`return min(vec4(a >= vec4(1.0)) + vec4(b >= vec4(1.0)), vec4(1.0));`,Pue="let resultTemp = max(a, b);",_ue="let resultTemp = min(a, b);",Oue=` let isNaN = b == 0.; var resultTemp = a % b; resultTemp = select((resultTemp + b) % b, resultTemp, (a < 0. && b < 0.) || (a >= 0. && b > 0.)); `,zue=` let isNaN = !vec4(b); var resultTemp = vec4(a % b); if (!((a[0] < 0. && b[0] < 0.) || (a[0] >= 0. && b[0] > 0.))) { resultTemp[0] = (resultTemp[0] + b[0]) % b[0]; } if (!((a[1] < 0. && b[1] < 0.) || (a[1] >= 0. && b[1] > 0.))) { resultTemp[1] = (resultTemp[1] + b[1]) % b[1]; } if (!((a[2] < 0. && b[2] < 0.) || (a[2] >= 0. && b[2] > 0.))) { resultTemp[2] = (resultTemp[2] + b[2]) % b[2]; } if (!((a[3] < 0. && b[3] < 0.) || (a[3] >= 0. && b[3] > 0.))) { resultTemp[3] = (resultTemp[3] + b[3]) % b[3]; } `,Lue="let resultTemp = a * b;",Wue=` var resultTemp = f32(a != b); let valueForNaN = 1.0; `,Bue=` var resultTemp = vec4(a != b); let valueForNaN = 1.0; `,Vue=` let isNaN = a < 0.0 && floor(b) < b; if (b == 0.0) { return 1.0; } var resultTemp = select(sign(a) * pow(abs(a), b), pow(abs(a), b), round(abs(b) % 2.0) != 1.0); `,Uue=` let isModRound1Bool = vec4(round(abs(b) % vec4(2.0))) == vec4(1); let isModRound1 = vec4(isModRound1Bool); let multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1); var resultTemp = multiplier * pow(abs(a), b); // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS let isExpZero = b == vec4(0.0); if (isExpZero.r) { resultTemp.r = 1.0; } if (isExpZero.g) { resultTemp.g = 1.0; } if (isExpZero.b) { resultTemp.b = 1.0; } if (isExpZero.a) { resultTemp.a = 1.0; } let isNaN = (a < vec4(0.0)) & (floor(b) < b); `,Gue="if (a < 0.0) { return b * a; } return a;",Hue=` let aLessThanZero = vec4(a < vec4(0.0)); return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a); `,jue="let resultTemp = (a - b) * (a - b);",que="let resultTemp = a - b;";function ry(e,t){let a;do{switch(e){case De.ATAN2:a=bue;break;case De.MAX:a=Pue;break;case De.MIN:a=_ue;break;case De.MOD:a=t?zue:Oue;break;case De.NOT_EQUAL:a=t?Bue:Wue;break;case De.POW:a=t?Uue:Vue;break;default:continue}let n,r,s;return t?(n="isnanVec4",r="vec4",s="vec4"):(n="isnan",r="f32",s="bool"),` let aIsNaN = ${n}(a); let aPostLegalization = select(a, ${r}(42), aIsNaN); let bIsNaN = ${n}(b); let bPostLegalization = select(b, ${r}(42), bIsNaN); let isNaN = false; let valueForNaN = uniforms.NAN; { let a = aPostLegalization; let b = bPostLegalization; ${a} return select( resultTemp, ${r}(valueForNaN), ${s}(isNaN) | aIsNaN | bIsNaN); } `}while(!1);switch(e){case De.ADD:a=Aue;break;case De.COMPLEX_MULTIPLY_IMAG:a=wue;break;case De.COMPLEX_MULTIPLY_REAL:a=vue;break;case De.DIV:a=kue;break;case De.ELU_DER:a=Iue;break;case De.EQUAL:a=Sue;break;case De.FLOOR_DIV:a=Tue;break;case De.GREATER:a=Cue;break;case De.GREATER_EQUAL:a=Nue;break;case De.LESS:a=Rue;break;case De.LESS_EQUAL:a=Eue;break;case De.LOGICAL_AND:return t?Fue:Mue;case De.LOGICAL_OR:return t?Due:$ue;case De.MUL:a=Lue;break;case De.PRELU:return t?Hue:Gue;case De.SQUARED_DIFFERENCE:a=jue;break;case De.SUB:a=que;break;default:}return` ${a} return resultTemp; `}var le;(function(e){e[e.ABS=0]="ABS",e[e.ACOS=1]="ACOS",e[e.ACOSH=2]="ACOSH",e[e.ASIN=3]="ASIN",e[e.ASINH=4]="ASINH",e[e.ATAN=5]="ATAN",e[e.ATANH=6]="ATANH",e[e.CEIL=7]="CEIL",e[e.COS=8]="COS",e[e.COSH=9]="COSH",e[e.ELU=10]="ELU",e[e.ERF=11]="ERF",e[e.EXP=12]="EXP",e[e.EXPM1=13]="EXPM1",e[e.FLOOR=14]="FLOOR",e[e.IS_FINITE=15]="IS_FINITE",e[e.IS_INF=16]="IS_INF",e[e.IS_NAN=17]="IS_NAN",e[e.LINEAR=18]="LINEAR",e[e.LOG=19]="LOG",e[e.LOG1P=20]="LOG1P",e[e.LOGICAL_NOT=21]="LOGICAL_NOT",e[e.NEG=22]="NEG",e[e.RELU=23]="RELU",e[e.RELU6=24]="RELU6",e[e.LEAKYRELU=25]="LEAKYRELU",e[e.RECIPROCAL=26]="RECIPROCAL",e[e.ROUND=27]="ROUND",e[e.RSQRT=28]="RSQRT",e[e.SELU=29]="SELU",e[e.SIGMOID=30]="SIGMOID",e[e.SIGN=31]="SIGN",e[e.SIN=32]="SIN",e[e.SINH=33]="SINH",e[e.SOFTPLUS=34]="SOFTPLUS",e[e.SQRT=35]="SQRT",e[e.SQUARE=36]="SQUARE",e[e.STEP=37]="STEP",e[e.TAN=38]="TAN",e[e.TANH=39]="TANH",e[e.TO_INT=40]="TO_INT"})(le||(le={}));var Xue="return abs(a);",Kue=` if (abs(a) > 1.) { return uniforms.NAN; } return acos(a); `,Yue=` if (a < 1.) { return uniforms.NAN; } return acosh(a); `,Zue=` if (abs(a) > 1.) { return uniforms.NAN; } return asin(a); `,Jue="return asinh(a);",Que=` if (isnan(a)) { return uniforms.NAN; } return atan(a); `,ede=` if (abs(a) > 1.) { return uniforms.NAN; } if (a == 1.) { return uniforms.INFINITY; } if (a == -1.) { return -uniforms.INFINITY; } return atanh(a); `,tde="return ceil(a);",ade="return cos(a);",nde=` let e2x = exp(-a); return (e2x + 1.0 / e2x) / 2.0; `,rde="return exp(a) - 1.0;",sde="if (a >= 0.0) { return a; } return (exp(a) - 1.0);",ide=` var resFloat = exp(a) - vec4(1.0); if (a.r >= 0.0) { resFloat.r = a.r; } if (a.g >= 0.0) { resFloat.g = a.g; } if (a.b >= 0.0) { resFloat.b = a.b; } if (a.a >= 0.0) { resFloat.a = a.a; } return resFloat; `,ode=` // Error function is calculated approximately with elementary function. // See "Handbook of Mathematical Functions with Formulas, // Graphs, and Mathematical Tables", Abramowitz and Stegun. let p = ${I.ERF_P}; let a1 = ${I.ERF_A1}; let a2 = ${I.ERF_A2}; let a3 = ${I.ERF_A3}; let a4 = ${I.ERF_A4}; let a5 = ${I.ERF_A5}; let sign = sign(a); let absA = abs(a); let t = 1.0 / (1.0 + p * absA); return sign * (1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * exp(-absA * absA)); `,lde="return exp(a);",ude="return floor(a);",dde="return f32(!isnan(a) && !isinf(a));",pde="return f32(isinf(a));",cde="return f32(isnan(a));",hde="return a;",mde=`if (a < 0.0) { return uniforms.NAN; } return log(a);`,fde=` if (isnan(a)) { return a; } return log(1.0 + a); `,gde="return f32(!(a >= 1.0));",yde="return -a;",xde="if (a < 0.0) { return uniforms.alpha * a; } return a;",Ade=` let aLessThanZero = vec4(a < vec4(0.0)); return (aLessThanZero * (uniforms.alpha * a)) + ((vec4(1.0) - aLessThanZero) * a); `,bde="return 1.0 / a;",vde="return select(a, 0.0, a < 0.0);",wde="return clamp(a, 0.0, 6.0);",kde="return clamp(a, vec4(0.0, 0.0, 0.0, 0.0), vec4(6.0, 6.0, 6.0, 6.0));",Ide=` return select(a, vec4(0.0), a < vec4(0.0)); `,Sde="return round(a);",Tde="return inverseSqrt(a);",Cde=` if (a >= 0.0) { return ${I.SELU_SCALE} * a; } else { return ${I.SELU_SCALEALPHA} * (exp(a) - 1.0); } `,Nde="return 1.0 / (1.0 + exp(-1.0 * a));",Rde="return sign(a);",Ede="return sin(a);",Mde=` let e2x = exp(a); return (e2x - 1.0 / e2x) / 2.0; `,Fde=` let epsilon = 1.1920928955078125e-7; let threshold = log(epsilon) + 2.0; let too_large = a > -threshold; let too_small = a < threshold; let exp_a = exp(a); if (too_large) { return a; } else if (too_small) { return exp_a; } else { return log(exp_a + 1.0); } `,$de="return sqrt(a);",Dde="return a * a;",Pde=` if (isnan(a)) { return a; } return select(uniforms.stepAlpha, 1.0, a > 0.0); `,_de="return tan(a);",Ode=` let e2x = exp(-2.0 * abs(a)); return sign(a) * (1.0 - e2x) / (1.0 + e2x); `,zde="return f32(i32((a)));";function pi(e,t){switch(e){case le.ABS:return Xue;case le.ACOS:return Kue;case le.ACOSH:return Yue;case le.ASIN:return Zue;case le.ASINH:return Jue;case le.ATAN:return Que;case le.ATANH:return ede;case le.COS:return ade;case le.COSH:return nde;case le.CEIL:return tde;case le.ELU:return t?ide:sde;case le.ERF:return ode;case le.EXP:return lde;case le.EXPM1:return rde;case le.FLOOR:return ude;case le.IS_FINITE:return dde;case le.IS_INF:return pde;case le.IS_NAN:return cde;case le.LINEAR:return hde;case le.LOG:return mde;case le.LOG1P:return fde;case le.LOGICAL_NOT:return gde;case le.NEG:return yde;case le.LEAKYRELU:return t?Ade:xde;case le.RECIPROCAL:return bde;case le.RELU:return t?Ide:vde;case le.RELU6:return t?kde:wde;case le.ROUND:return Sde;case le.RSQRT:return Tde;case le.SELU:return Cde;case le.SIGMOID:return Nde;case le.SIGN:return Rde;case le.SIN:return Ede;case le.SINH:return Mde;case le.SOFTPLUS:return Fde;case le.SQRT:return $de;case le.SQUARE:return Dde;case le.STEP:return Pde;case le.TAN:return _de;case le.TANH:return Ode;case le.TO_INT:return zde;default:throw new Error(`BinaryType ${e} is not implemented!`)}}function Or(e,t=!1,a=!1,n=3){if(e===null)return"";let r="";if(e==="linear")r=pi(le.LINEAR);else if(e==="relu")r=pi(le.RELU,a);else if(e==="elu")r=pi(le.ELU,a);else if(e==="relu6")r=pi(le.RELU6,a);else if(e==="prelu")r=ry(De.PRELU,a);else if(e==="sigmoid")r=pi(le.SIGMOID,a);else if(e==="leakyrelu")r=pi(le.LEAKYRELU,a);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let s=Xe(a?4:1),i="";return t?i=` fn activation(a : ${s}, coords : vec${n}) -> ${s} { let b = getPreluActivationWeightsByOutputCoords(coords); ${r} }`:i=` fn activation(a : ${s}, coords : vec${n}) -> ${s} { ${r} }`,i}function ml(e,t){return` ${e?"value = value + getBiasByOutputCoords(coords);":""} ${t?"value = activation(value, coords);":""} `}function jk(e,t,a=!1,n=!1,r=!1,s=1){v.assert(e&&s===1||!e,()=>`transposeA ${e} is not compatible with component size ${s}`);let i=` ${e?"value = getA(batch, col, row);":"value = getA(batch, row, col);"} `,o=t?"value = getB(batch, col, row);":"value = getB(batch, row, col);";return` fn mm_readA(batch: i32, row: i32, col: i32) -> ${Xe(s)} { var value = ${Xe(s)}(0.0); ${a&&r?i:` ${e?"if(row < uniforms.dimAOuter && col < uniforms.dimInner)":"if(row < uniforms.aShape[1] && col < uniforms.aShape[2])"} { ${i} } `} return value; } fn mm_readB(batch: i32, row: i32, col: i32) -> ${Xe(s)} { var value = ${Xe(s)}(0.0); ${o} return value; } `}function sy(e,t,a,n,r=!1,s=!1,i=!1,o=1){return` ${jk(a,n,r,s,i,o)} fn mm_write(batch: i32, row: i32, col: i32, valueIn: ${Xe(o)}) { ${r&&s?"":"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)"} { var value = valueIn; let coords = vec3(batch, row, col); ${ml(e,t)} setOutputAtCoords(coords[0], coords[1], coords[2], value); } } `}var Lde=(e,t)=>e?` mm_Asub[inputRow][inputCol] = mm_readA(batchA, kStart + inputRow, globalRowStart + inputCol * ${t}); `:` mm_Asub[inputRow][inputCol] = mm_readA(batchA, globalRow + innerRow, kStart + inputCol * ${t}); `,Wde=(e,t,a,n)=>{if(e)return` for (var k = 0; k < ${n}; k++) { let BCached0 = mm_Bsub[k][tileCol]; let ACached0 = mm_Asub[k][localRow]; for (var i = 0; i < ${a}; i++) { acc[i] = fma(BCached0, vec4(ACached0[i]), acc[i]); } }`;{let r="",s="";for(let i=0;i(ACached[${i}]), acc[i]);`;return` for (var k = 0; k < ${n/t}; k++) { ${r} for (var i = 0; i < ${a}; i++) { let ACached = mm_Asub[tileRow + i][k]; ${s} } }`}};function g0(e,t,a=!1,n=32,r=!1,s=32,i=!1){let o=t[1]*e[1],l=t[0]*e[0],u=a?o:n,d=a?n:o,c=u/t[0],p=n/t[1],h=e[1],m=e[0];return v.assert((a&&c===4&&e[1]===4||!a&&(c===3||c===4))&&u%t[0]===0&&n%t[1]===0&&e[0]===4,()=>`If transposeA ${a} is true, innerElementSize ${c} and workPerThread[1] ${e[1]} must be 4. Otherwise, innerElementSize ${c} must be 3 or 4. tileAWidth ${u} must be divisible by workgroupSize[0]${t[0]}. tileInner ${n} must be divisible by workgroupSize[1] ${t[1]}. colPerThread ${e[0]} must be 4.`),` var mm_Asub : array, ${u/c}>, ${d}>; var mm_Bsub : array, ${l/e[0]}>, ${n}>; ${ue()} { let localRow = i32(localId.y); let tileRow = localRow * ${h}; let tileCol = i32(localId.x); let globalRow = i32(globalId.y) * ${h}; let globalCol = i32(globalId.x) * ${m}; let batch = ${r?"0":"i32(globalId.z)"}; let batchA = ${r||!i?"batch":"batch % uniforms.aShape[0]"}; let batchB = ${r||!i?"batch":"batch % uniforms.bShape[0]"}; let globalRowStart = i32(workgroupId.y) * ${o}; let numTiles = ${r?`${Math.ceil(s/n)}`:`(uniforms.dimInner - 1) / ${n} + 1`}; var kStart = ${r?`i32(globalId.z) * ${s}`:"0"}; var acc: array, ${h}>; // Loop over shared dimension. let tileRowB = localRow * ${p}; for (var t = 0; t < numTiles; t++) { // Load one tile of A into local memory. for (var innerRow = 0; innerRow < ${h}; innerRow++) { let inputRow = tileRow + innerRow; let inputCol = tileCol; ${Lde(a,c)} } // Load one tile of B into local memory. for (var innerRow = 0; innerRow < ${p}; innerRow++) { let inputRow = tileRowB + innerRow; let inputCol = tileCol; mm_Bsub[inputRow][inputCol] = mm_readB(batchB, kStart + inputRow, globalCol); } kStart = kStart + ${n}; workgroupBarrier(); // Compute acc values for a single thread. ${Wde(a,c,h,n)} workgroupBarrier(); } for (var innerRow = 0; innerRow < ${h}; innerRow++) { mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]); } }`}var gA=e=>e?` mm_Asub[inputRow][inputCol] = mm_readA(batchA, kStart + inputRow, globalRowStart + inputCol); `:` mm_Asub[inputRow][inputCol] = mm_readA(batchA, globalRowStart + inputRow, kStart + inputCol); `,Bde=e=>e?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function y0(e,t,a=!1,n=32,r=!1,s=32,i=!1,o=!1){let l=e[1]*t[1],u=e[0]*t[0],d=a?l:n,c=a?n:l;v.assert(c%t[1]===0&&d%t[0]===0&&n%t[1]===0,()=>`tileAHight ${c} must be divisible by workgroupSize[1]${t[1]}, tileAWidth ${d} must be divisible by workgroupSize[0]${t[0]}, tileInner ${n} must be divisible by workgroupSize[1]${t[1]}`);let p=c/t[1],h=d/t[0],m=n/t[1],f=e[1],g=e[0],y=i?` let localRow = i32(localId.y); let localCol = i32(localId.x); let globalRowStart = i32(workgroupId.y) * ${l}; let globalColStart = i32(workgroupId.x) * ${u}; // Loop over shared dimension. for (var t = 0; t < numTiles; t++) { // Load one tile of A into local memory. for (var inputRow = localRow; inputRow < ${c}; inputRow = inputRow + ${t[1]}) { for (var inputCol = localCol; inputCol < ${d}; inputCol = inputCol + ${t[0]}) { ${gA(a)} } } // Load one tile of B into local memory. for (var inputRow = localRow; inputRow < ${n}; inputRow = inputRow + ${t[1]}) { for (var inputCol = localCol; inputCol < ${u}; inputCol = inputCol + ${t[0]}) { mm_Bsub[inputRow][inputCol] = mm_readB(batchB, kStart + inputRow, globalColStart + inputCol); } } kStart = kStart + ${n}; workgroupBarrier(); // Compute acc values for a single thread. var BCached : array; for (var k = 0; k < ${n}; k++) { for (var inner = 0; inner < ${g}; inner++) { BCached[inner] = mm_Bsub[k][localCol + inner * ${t[0]}]; } for (var innerRow = 0; innerRow < ${f}; innerRow++) { let ACached = ${a?`mm_Asub[k][localRow + innerRow * ${t[1]}];`:`mm_Asub[localRow + innerRow * ${t[1]}][k];`} for (var innerCol = 0; innerCol < ${g}; innerCol++) { acc[innerRow][innerCol] = fma(ACached, BCached[innerCol], acc[innerRow][innerCol]); } } } workgroupBarrier(); } for (var innerRow = 0; innerRow < ${f}; innerRow++) { let gRow = globalRowStart + localRow + innerRow * ${t[1]}; for (var innerCol = 0; innerCol < ${g}; innerCol++) { let gCol = globalColStart + localCol + innerCol * ${t[0]}; mm_write(batch, gRow, gCol, acc[innerRow][innerCol]); } } `:` let tileRow = i32(localId.y) * ${f}; let tileCol = i32(localId.x) * ${g}; let globalRow = i32(globalId.y) * ${f}; let globalCol = i32(globalId.x) * ${g}; let globalRowStart = i32(workgroupId.y) * ${l}; let tileRowA = i32(localId.y) * ${p}; let tileColA = i32(localId.x) * ${h}; let tileRowB = i32(localId.y) * ${m}; // Loop over shared dimension. for (var t = 0; t < numTiles; t++) { // Load one tile of A into local memory. for (var innerRow = 0; innerRow < ${p}; innerRow++) { for (var innerCol = 0; innerCol < ${h}; innerCol++) { let inputRow = tileRowA + innerRow; let inputCol = tileColA + innerCol; ${gA(a)} } } // Load one tile of B into local memory. for (var innerRow = 0; innerRow < ${m}; innerRow++) { for (var innerCol = 0; innerCol < ${g}; innerCol++) { let inputRow = tileRowB + innerRow; let inputCol = tileCol + innerCol; mm_Bsub[inputRow][inputCol] = mm_readB(batchB, kStart + inputRow, globalCol + innerCol); } } kStart = kStart + ${n}; workgroupBarrier(); // Compute acc values for a single thread. var BCached : array; for (var k = 0; k < ${n}; k++) { for (var inner = 0; inner < ${g}; inner++) { BCached[inner] = mm_Bsub[k][tileCol + inner]; } for (var innerRow = 0; innerRow < ${f}; innerRow++) { ${Bde(a)} for (var innerCol = 0; innerCol < ${g}; innerCol++) { acc[innerRow][innerCol] = fma(ACached, BCached[innerCol], acc[innerRow][innerCol]); } } } workgroupBarrier(); } for (var innerRow = 0; innerRow < ${f}; innerRow++) { for (var innerCol = 0; innerCol < ${g}; innerCol++) { mm_write(batch, globalRow + innerRow, globalCol + innerCol, acc[innerRow][innerCol]); } } `;return` var mm_Asub : array, ${c}>; var mm_Bsub : array, ${n}>; ${ue()} { let batch = ${r?"0":"i32(globalId.z)"}; let batchA = ${r||!o?"batch":"batch % uniforms.aShape[0]"}; let batchB = ${r||!o?"batch":"batch % uniforms.bShape[0]"}; let numTiles = ${r?`${Math.ceil(s/n)}`:`(uniforms.dimInner - 1) / ${n} + 1`}; var kStart = ${r?`i32(globalId.z) * ${s}`:"0"}; var acc : array, ${f}>; // Without this initialization strange values show up in acc. for (var innerRow = 0; innerRow < ${f}; innerRow++) { for (var innerCol = 0; innerCol < ${g}; innerCol++) { acc[innerRow][innerCol] = 0.0; } } ${y} } `}var Vde=e=>e?` mm_readA(batchA, colA, globalRow), mm_readA(batchA, colA + 1, globalRow), mm_readA(batchA, colA + 2, globalRow), mm_readA(batchA, colA + 3, globalRow) `:` mm_readA(batchA, globalRow, colA), mm_readA(batchA, globalRow, colA + 1), mm_readA(batchA, globalRow, colA + 2), mm_readA(batchA, globalRow, colA + 3) `;function Ude(e,t=!1){v.assert(e[1]===1&&e[2]===1,()=>`A linear work group size is required. But got ${e}.`);let a=e[0]*4;return` var mm_Asub : array, ${e[0]}>; ${ue()} { let tileCol = i32(localId.x); let globalCol = i32(globalId.x); let globalRow = i32(globalId.y); let numTiles = (uniforms.dimInner - 1) / ${a} + 1; let batch = i32(globalId.z); let batchA = batch % uniforms.aShape[0]; let batchB = batch % uniforms.bShape[0]; // Without this initialization strange values show up in acc. var acc = 0.0; // Loop over shared dimension. for (var t = 0; t < numTiles; t++) { // Load one tile of A into local memory. let colA = t * ${a} + tileCol * 4; mm_Asub[tileCol] = vec4(${Vde(t)}); workgroupBarrier(); // Compute acc values for a single thread. for (var k = 0; k < ${a/4}; k++) { let rowB = t * ${a} + k * 4; let BCached = vec4(mm_readB(batchB, rowB, globalCol), mm_readB(batchB, rowB + 1, globalCol), mm_readB(batchB, rowB + 2, globalCol), mm_readB(batchB, rowB + 3, globalCol)); let ACached = mm_Asub[k]; acc = acc + dot(ACached, BCached); } workgroupBarrier(); } mm_write(batch, globalRow, globalCol, acc); } `}var Gde=class{constructor(e,t,a=!1,n=!1,r=null,s=null,i=null,o=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let l=a?e[1]:e[2];if(this.isVec4=(l%4===0&&!a||t[1]%4===0&&a)&&t[2]%4===0&&!n,this.outputComponent=this.isVec4?4:1,this.isVectorA=t[1]===1&&!a,!this.isVec4&&this.isVectorA)this.elementsPerThread=[1,1,1],this.workgroupSize=[32,1,1];else{let c=Gk(t[1],l,t[2],a);this.workgroupSize=c.workgroupSize,this.elementsPerThread=c.elementsPerThread}this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread);let u=r!=null,d=i!=null;u&&this.variableNames.push("bias"),d&&this.variableNames.push("preluActivationWeights"),this.sequentialAccessByThreads=o,this.transposeA=a,this.transposeB=n,this.addBias=u,this.activation=s,this.hasPreluActivationWeights=d,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],l),this.shaderKey=`matMulPacked_${this.elementsPerThread}_${a}_${n}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.isVectorA}_${this.sequentialAccessByThreads}`}getShapeFit(e,t,a){let n=this.workgroupSize[1]*this.elementsPerThread[1],r=this.workgroupSize[0]*this.elementsPerThread[0];!this.isVec4&&this.isVectorA?this.tileInner=this.workgroupSize[0]*4:this.tileInner=r;let s=e%n===0,i=t%r===0,o=a%this.tileInner===0;return[s,i,o]}getUserCode(){return` ${Or(this.activation,this.hasPreluActivationWeights,this.isVec4)} ${sy(this.addBias,this.activation,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner,this.isVec4?4:1)} ${this.isVec4?g0(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,!0):this.isVectorA?Ude(this.workgroupSize,this.transposeA):y0(this.elementsPerThread,this.workgroupSize,this.transposeA,this.tileInner,!1,null,this.sequentialAccessByThreads,!0)} `}};function Hde(e){return` var sumValues : array; ${ue()} { let coords = getOutputCoords(); let batch = coords[0]; let batchA = batch % uniforms.aShape[0]; let batchB = batch % uniforms.bShape[0]; let row = coords[1]; let col = coords[2]; var sum = 0.0; let Length = uniforms.dimInner; for (var k = i32(localId.x); k < Length; k = k + ${e}) { let dataA = mm_readA(batchA, row, k); let dataB = mm_readB(batchB, k, col); sum = sum + dataA * dataB; } sumValues[localId.x] = sum; workgroupBarrier(); for(var currentSize = ${e/2}u; currentSize > 1u; currentSize = currentSize / 2u) { if (localId.x < currentSize) { sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize]; } workgroupBarrier(); } if (localId.x == 0u) { sum = sumValues[0] + sumValues[1]; mm_write(batch, row, col, sum); } } `}var jde=class{constructor(e,t=!1,a=!1,n=null,r=null,s=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize);let i=n!=null,o=s!=null;i&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),this.transposeA=t,this.transposeB=a,this.addBias=i,this.activation=r,this.hasPreluActivationWeights=o,this.shaderKey=`matMulReduce_${this.activation}_${t}_${a}`}getUserCode(){return` ${Or(this.activation,this.hasPreluActivationWeights)} ${sy(this.addBias,this.activation,this.transposeA,this.transposeB)} ${Hde(this.workgroupSize[0])} `}};function qde(e){let t=e[1],a=e[0],n=t>a?t:a;return` var mm_Asub : array, ${t}>; var mm_Bsub : array, ${n}>; // If the output size is small for matrix multiplication, avoid to use vec4 // and handle some elements per thread to optimally utilize the ALU. // Read data from global memory to registers firstly, then store them into // shared memory, so it is instruction-Level parallelism for arithmetic // operations and others handle IO operations between barrier api, makes ALU // and load/store units work simultaneously, could improves the performance. ${ue()} { let tileRow = i32(localId.y); let tileCol = i32(localId.x); let globalRow = i32(globalId.y); let globalCol = i32(globalId.x); let batch = i32(globalId.z); let batchA = batch % uniforms.aShape[0]; let batchB = batch % uniforms.bShape[0]; // uniforms.dimInner should be greater than 0. let numTiles = (uniforms.dimInner - 1) / ${n} + 1; var acc = 0.0; var globalColA = tileCol; var globalRowB = 0; var regA = mm_readA(batchA, globalRow, globalColA); var regB0 = mm_readB(batchB, globalRowB + 2 * tileRow, globalCol); var regB1 = mm_readB(batchB, globalRowB + 2 * tileRow + 1, globalCol); globalColA = globalColA + ${n}; globalRowB = globalRowB + ${n}; for (var t = 0; t < numTiles; t = t + 1) { mm_Asub[tileRow][tileCol] = regA; mm_Bsub[2 * tileRow][tileCol] = regB0; mm_Bsub[2 * tileRow + 1][tileCol] = regB1; workgroupBarrier(); regA = mm_readA(batchA, globalRow, globalColA); regB0 = mm_readB(batchB, globalRowB + 2 * tileRow, globalCol); regB1 = mm_readB(batchB, globalRowB + 2 * tileRow + 1, globalCol); globalColA = globalColA + ${n}; globalRowB = globalRowB + ${n}; for (var k = 0; k < ${n}; k = k + 1) { acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol]; } workgroupBarrier(); } mm_write(batch, globalRow, globalCol, acc); } `}var Xde=class{constructor(e,t,a,n=!1,r=!1,s=null,i=null,o=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[16,8,1],this.outputShape=a,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(a[2]/this.workgroupSize[0]),Math.ceil(a[1]/this.workgroupSize[1]),a[0]];let l=s!=null;l&&this.variableNames.push("bias");let u=o!=null;u&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=r,this.addBias=l,this.activation=i,this.hasPreluActivationWeights=u,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${n}_${r}`}getUserCode(){return` ${Or(this.activation,this.hasPreluActivationWeights)} ${sy(this.addBias,this.activation,this.transposeA,this.transposeB)} ${qde(this.workgroupSize)} `}},Kde=class{constructor(e,t,a=!1,n=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workgroupSize=[8,8,1],this.atomic=!0,this.splitedDimInner=128,v.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]};let r=(a&&this.outputShape[1]%4===0||!a&&t%4===0)&&this.outputShape[2]%4===0;this.elementsPerThread=[4,4,this.splitedDimInner],this.outputComponent=r?4:1,r||(this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1)),this.dispatch=de(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workgroupSize,this.elementsPerThread),this.transposeA=a,this.transposeB=n,this.shaderKey=`matMulSplitK_${a}_${n}_${this.elementsPerThread}_${this.outputComponent}`}getUserCode(){let e=this.outputComponent;return` ${jk(!1,this.transposeB,!1,!1,!1,e)} fn mm_write(batch: i32, row : i32, col : i32, value : ${Xe(e)}) { if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) { let coords = vec3(batch, row, col); let flatIndex = getOutputIndexFromCoords(coords); // The problem is that we should initialize output to zero before using. // Otherwise, the original value will be added to the result. for (var i = 0; i < ${e}; i = i + 1) { ${Bs("&result[flatIndex + i]",`${e>1?"value[i]":"value"}`,"float32")} } } } ${e===4?g0(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner):y0(this.elementsPerThread,this.workgroupSize,this.transposeA,32,!0,this.splitedDimInner)} `}},Yde=class{constructor(e,t=null,a=null,n=null){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=n!=null,this.activation=a,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${a}`}getUserCode(){return` ${Or(this.activation,this.hasPreluActivationWeights)} ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); var value = getXByOutputIndex(index); ${ml(this.addBias,this.activation)} setOutputAtIndex(index, value); } } `}},Zde=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="fill"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { setOutputAtIndex(index, uniforms.value); } } `}};function Wa(e){let{backend:t,attrs:a}=e,{shape:n,value:r}=a,{dtype:s}=a;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(r),t.makeTensorInfo(n,s,i)}else{let i=new Zde(n),o=[{type:"float32",data:[r]}];return t.runWebGPUProgram(i,[],s,o)}}var Jde={kernelName:Iu,backendName:"webgpu",kernelFunc:Wa};function ke(e){let{inputs:t,attrs:a}=e,{x:n}=t,{shape:r}=a,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(r,s),o=v.sizeFromShape(i);return v.assert(s===o,()=>`The new shape (${i}) has ${o} elements and the old shape (${n.shape}) has ${s} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var Qde={kernelName:Du,backendName:"webgpu",kernelFunc:ke};function x0({a:e,b:t,transposeA:a,transposeB:n,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,d=t.shape.length,c=a?e.shape[u-2]:e.shape[u-1],p=n?t.shape[d-1]:t.shape[d-2],h=a?e.shape[u-1]:e.shape[u-2],m=n?t.shape[d-2]:t.shape[d-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(f),x=v.sizeFromShape(g),A=ul.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,m]);v.assert(c===p,()=>`Error in matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${a} and transposeB=${n} must match.`);let b=a?[y,c,h]:[y,h,c],w=n?[x,m,p]:[x,p,m],S=ke({inputs:{x:e},backend:r,attrs:{shape:b}}),C=ke({inputs:{x:t},backend:r,attrs:{shape:w}}),N=[S,C],M=Math.max(y,x),F=[S,C],E=[{type:"int32",data:[h]},{type:"int32",data:[m]},{type:"int32",data:[c]}],T,D,O=[M,h,m],W=B().get("WEBGPU_MATMUL_PROGRAM_TYPE");if(W<0){let U=B().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),G=U>0?U:r.thresholdToIncreaseWorkgroups,q=M*Math.ceil(h/32)*Math.ceil(m/32);q<=G||h<=8&&q<=G*2?M*h*m<=128?W=Ln.MatMulReduceProgram:M===1&&p>=2e3?W=Ln.MatMulSplitKProgram:W=Ln.MatMulSmallOutputSizeProgram:W=Ln.MatMulPackedProgram}switch(W){case Ln.MatMulReduceProgram:T=new jde(O,a,n,s,l,i);break;case Ln.MatMulSplitKProgram:{if(D=Wa({backend:r,attrs:{shape:O,value:0,dtype:e.dtype}}),T=new Kde(O,p,a,n),s||l){D=r.runWebGPUProgram(T,F,e.dtype,E,D);let G=new Yde(D.shape,s,l,i),q=null,H=[D];s&&H.push(s),i&&H.push(i),l==="leakyrelu"&&(q=[{type:"float32",data:[o]}],G.uniforms+=" alpha : f32,");let V=r.runWebGPUProgram(G,H,D.dtype,q);N.push(D);let Z=ke({inputs:{x:V},backend:r,attrs:{shape:A}});N.push(V);for(let X of N)r.disposeData(X.dataId);return Z}break}case Ln.MatMulSmallOutputSizeProgram:T=new Xde(b,w,O,a,n,s,l,i);break;case Ln.MatMulPackedProgram:let U=r.adapterInfo.isIntel();T=new Gde(b,O,a,n,s,l,i,U);break;default:throw new Error(`Unsupported MatMulProgramType ${W}.`)}s&&F.push(s),i&&F.push(i),l==="leakyrelu"&&(E.push({type:"float32",data:[o]}),T.uniforms+=" alpha : f32,"),D=r.runWebGPUProgram(T,F,e.dtype,E,D);let $=ke({inputs:{x:D},backend:r,attrs:{shape:A}});N.push(D);for(let U of N)r.disposeData(U.dataId);return $}function epe(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:d,leakyreluAlpha:c}=n;return x0({a:r,b:s,transposeA:l,transposeB:u,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:c,activation:d})}var tpe={kernelName:ts,backendName:"webgpu",kernelFunc:epe},yA=class{constructor(e,t,a){this.variableNames=["AReal","AImag","BReal","BImag"],this.workgroupSize=[128,1,1],this.size=!0,this.outputShape=I.assertAndGetBroadcastShape(t,a),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return` fn binaryOpComplex( areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 { ${ry(this.op,!1)} } ${ue("index")} { if(index < uniforms.size) { let areal = getARealByOutputIndex(index); let aimag = getAImagByOutputIndex(index); let breal = getBRealByOutputIndex(index); let bimag = getBImagByOutputIndex(index); setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag)); } } `}},$h=class{constructor(e,t,a){if(this.size=!0,this.variableNames=["A","B"],this.outputShape=I.assertAndGetBroadcastShape(t,a),this.dispatchLayout=me(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length<=1&&a.length>1&&t[0]<128,this.useSharedMemoryWithB=a.length<=1&&t.length>1&&a[0]<128,this.useSharedMemoryWithA||this.useSharedMemoryWithB)this.outputComponent=1,this.variableComponents=[1,1],this.lastDimensionSize=this.useSharedMemoryWithB?a[0]:t[0],this.shaderKey=`binary_${e}_${this.lastDimensionSize}`,this.type="shared",this.workgroupSize=[256,1,1];else{let n=t.length>0&&t[t.length-1]%4===0,r=a.length>0&&a[a.length-1]%4===0;n&&r?(this.outputComponent=4,this.variableComponents=[4,4]):n&&(v.isScalarShape(a)||a[a.length-1]===1)||r&&(v.isScalarShape(t)||t[t.length-1]===1)?(this.outputComponent=4,this.variableComponents=n?[4,1]:[1,4]):(this.outputComponent=1,this.variableComponents=[1,1]),this.type="nonshared",this.shaderKey=`binary_${e}_${this.variableComponents}`,this.workgroupSize=[128,1,1]}this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.outputComponent,1,1])}getUserCode(){let e,t=this.outputComponent===4?"vec4":"f32",a=` fn binaryOperation(a : ${t}, b : ${t}) -> ${t} { ${ry(this.op,this.outputComponent===4)} }; `;if(this.type==="shared"){let n=this.lastDimensionSize>1?`coords[${this.outputShape.length-1}]`:"0",r=this.useSharedMemoryWithB?`let a = getAByOutputIndex(index); let b = sharedBuf[${n}];`:`let a = sharedBuf[${n}]; let b = getBByOutputIndex(index);`;e=` ${a} var sharedBuf : array; ${ue("index")} { // Fill in the shared memory buffer. let localIndex = i32(localId.x); if(localIndex < ${this.lastDimensionSize}) { sharedBuf[localIndex] = f32(${this.useSharedMemoryWithB?"B":"A"}[localIndex]); } workgroupBarrier(); if(index < uniforms.size) { let coords = getCoordsFromIndex(index); ${r} setOutputAtIndex(index, binaryOperation(a, b)); } } `}else e=` ${a} ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index * ${this.outputComponent}); let a = ${t}(getAByOutputCoords(coords)); let b = ${t}(getBByOutputCoords(coords)); setOutputAtIndex(index, binaryOperation(a, b)); } } `;return e}};function an(e){let{inputs:t}=e,{x:a}=t;return e.backend.incRef(a.dataId),{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}var ape={kernelName:ho,backendName:"webgpu",kernelFunc:an};function fl(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.makeTensorInfo(n.shape,"complex64"),i=a.tensorMap.get(s.dataId),o=an({inputs:{x:n},backend:a}),l=an({inputs:{x:r},backend:a});return i.complexTensorInfos={real:o,imag:l},s}var npe={kernelName:xp,backendName:"webgpu",kernelFunc:fl},id=class{constructor(e,t,a=""){this.variableNames=["A"],this.size=!0;let n=128;this.workgroupSize=[n,1,1],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.op=t,a!==""&&(this.uniforms=a),this.shaderKey=`unary_${t}`}getUserCode(){return` fn unaryOperation(a : f32) -> f32 { ${pi(this.op,!1)} } ${ue("index")} { if (index < uniforms.size) { let a = getAByOutputIndex(index); setOutputAtIndex(index, unaryOperation(a)); } } `}};function at({opType:e,cpuKernelImpl:t,dtype:a}){return({inputs:n,backend:r})=>{let{x:s}=n,i=r,o=a||s.dtype;if(i.shouldExecuteOnCPU([s])&&t!=null){let u=i.tensorMap.get(s.dataId),d=t(u.values,o);return i.makeTensorInfo(s.shape,o,d)}let l=new id(s.shape,e);return i.runWebGPUProgram(l,[s],o)}}function aa({opType:e,cpuKernelImpl:t,supportsComplex:a=!1,dtype:n}){return({inputs:r,backend:s})=>{let{a:i,b:o}=r,l=s;if(a&&i.dtype==="complex64"){let c=l.tensorMap.get(i.dataId),p=l.tensorMap.get(o.dataId),h,m;if(e!==De.MUL)[h,m]=[[c.complexTensorInfos.real,p.complexTensorInfos.real],[c.complexTensorInfos.imag,p.complexTensorInfos.imag]].map(g=>{let[y,x]=g,A={dataId:y.dataId,dtype:y.dtype,shape:i.shape},b={dataId:x.dataId,dtype:x.dtype,shape:o.shape},w=new $h(e,i.shape,o.shape);return l.runWebGPUProgram(w,[A,b],Qt(y.dtype,x.dtype))});else{let g=new yA(De.COMPLEX_MULTIPLY_REAL,i.shape,o.shape),y=new yA(De.COMPLEX_MULTIPLY_IMAG,i.shape,o.shape),x=[{dataId:c.complexTensorInfos.real.dataId,dtype:c.complexTensorInfos.real.dtype,shape:i.shape},{dataId:c.complexTensorInfos.imag.dataId,dtype:c.complexTensorInfos.imag.dtype,shape:i.shape},{dataId:p.complexTensorInfos.real.dataId,dtype:p.complexTensorInfos.real.dtype,shape:o.shape},{dataId:p.complexTensorInfos.imag.dataId,dtype:p.complexTensorInfos.imag.dtype,shape:o.shape}];h=l.runWebGPUProgram(g,x,"float32"),m=l.runWebGPUProgram(y,x,"float32")}let f=fl({inputs:{real:h,imag:m},backend:l});return l.disposeData(h.dataId),l.disposeData(m.dataId),f}let u=n||Qt(i.dtype,o.dtype);if((i.dtype==="string"||o.dtype==="string"||l.shouldExecuteOnCPU([i,o]))&&t!=null){let c=l.tensorMap.get(i.dataId).values,p=l.tensorMap.get(o.dataId).values,h=i.dtype==="string"?I.fromUint8ToStringArray(c):c,m=i.dtype==="string"?I.fromUint8ToStringArray(p):p,[f,g]=t(i.shape,o.shape,h,m,u);return l.makeTensorInfo(g,u,f)}let d=new $h(e,i.shape,o.shape);return l.runWebGPUProgram(d,[i,o],u)}}var qk={};Ke(qk,{addImpl:()=>Yk,bincountImpl:()=>ope,bincountReduceImpl:()=>lpe,bitwiseAndImpl:()=>Zk,castImpl:()=>Kk,ceilImpl:()=>Qk,concatImpl:()=>upe,equalImpl:()=>e9,expImpl:()=>t9,expm1Impl:()=>a9,floorDivImpl:()=>r9,floorImpl:()=>n9,gatherNdImpl:()=>dpe,gatherV2Impl:()=>ppe,greaterEqualImpl:()=>i9,greaterImpl:()=>s9,lessEqualImpl:()=>l9,lessImpl:()=>o9,linSpaceImpl:()=>cpe,logImpl:()=>u9,maxImpl:()=>hpe,maximumImpl:()=>d9,minimumImpl:()=>p9,multiplyImpl:()=>ly,negImpl:()=>fpe,notEqualImpl:()=>c9,prodImpl:()=>ype,raggedGatherImpl:()=>Ipe,raggedRangeImpl:()=>Spe,raggedTensorToTensorImpl:()=>Cpe,rangeImpl:()=>Npe,rsqrtImpl:()=>h9,scatterImpl:()=>Rpe,sigmoidImpl:()=>Epe,simpleAbsImpl:()=>rpe,sliceImpl:()=>Mpe,sparseFillEmptyRowsImpl:()=>Fpe,sparseReshapeImpl:()=>$pe,sparseSegmentReductionImpl:()=>Dpe,sqrtImpl:()=>Ppe,squaredDifferenceImpl:()=>m9,staticRegexReplaceImpl:()=>f9,stridedSliceImpl:()=>_pe,stringNGramsImpl:()=>zpe,stringSplitImpl:()=>Wpe,stringToHashBucketFastImpl:()=>Bpe,subImpl:()=>g9,tileImpl:()=>Upe,topKImpl:()=>Gpe,transposeImpl:()=>gpe,uniqueImpl:()=>Hpe});function Xk(e,t){Array.isArray(e)||(e=[e]),e.forEach(a=>{a!=null&&v.assert(a.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}function rpe(e){let t=new Float32Array(e.length);for(let a=0;a{let i=I.assertAndGetBroadcastShape(t,a),o=i.length,l=v.computeStrides(i),u=v.sizeFromShape(i),d=v.getTypedArrayFromDType(s,u),c=t.length,p=a.length,h=v.computeStrides(t),m=v.computeStrides(a),f=I.getBroadcastDims(t,i),g=I.getBroadcastDims(a,i);if(f.length+g.length===0)for(let y=0;yA[C]=0);let b=v.locToIndex(A,c,h),w=x.slice(-p);g.forEach(C=>w[C]=0);let S=v.locToIndex(w,p,m);d[y]=e(n[b],r[S])}return[d,i]}}function iy(e){let{inputs:t,backend:a}=e,{real:n,imag:r}=t,s=a.data.get(n.dataId).values,i=a.data.get(r.dataId).values,o=a.makeTensorInfo(n.shape,"complex64"),l=a.data.get(o.dataId);return l.complexTensorInfos={real:a.makeTensorInfo(n.shape,"float32",s),imag:a.makeTensorInfo(r.shape,"float32",i)},o}function eg(e,t,a="float32"){if(a==="complex64"){let 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WorkPerThread = DIV_CEIL(u32(Length), ${a}u); for (var k = i32(localId.x); k < Length && outputIndex < uniforms.size; k = k + ${a}) { let candidate = f32(x[offset + k]); ${e} } xBestValues[localId.x] = bestValue; workgroupBarrier(); var reduceSize = min(u32(Length), ${a}u); for (var currentSize = reduceSize / 2u; reduceSize > 1u; currentSize = reduceSize / 2u) { let interval = DIV_CEIL(reduceSize, 2u); if (localId.x < currentSize) { let candidate = xBestValues[localId.x + interval]; ${e} xBestValues[localId.x] = bestValue; } reduceSize = interval; workgroupBarrier(); } if (localId.x == 0u && outputIndex < uniforms.size) { ${n} } } `}},Bce={mean:"float32",all:"bool",any:"bool"};function gl(e,t,a,n,r){let s=e.shape.length,i=[],o=v.parseAxisParam(t,e.shape),l=o,u=I.getAxesPermutation(l,s),d=e;u!=null&&(d=ir({inputs:{x:e},attrs:{perm:u},backend:r}),l=I.getInnerMostAxes(l.length,s),i.push(d)),I.assertAxesAreInnerMostDims(n,l,s);let[c,p]=I.computeOutAndReduceShapes(d.shape,l),h=c;a&&(h=I.expandShapeToKeepDim(c,o));let m;if((n==="max"||n==="prod")&&r.shouldExecuteOnCPU([d])){let f=r.tensorMap.get(d.dataId).values;switch(n){case"max":let g=lce(f,v.sizeFromShape(p),h,e.dtype);m=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:y,outShape:x,outDtype:A}=mce(d.shape,d.dtype,f,l);m=r.makeTensorInfo(x,A,y);break;default:throw new Error(`${n} CPU implementation is not yet supported.`)}}else{let f=v.sizeFromShape(p),g=v.sizeFromShape(d.shape)/f,y={windowSize:f,inSize:f,batchSize:g,outSize:1},x=Bce[n]||Lp(e.dtype),A=[{type:"int32",data:[f]}],b=new Wce(y,n,r.device.limits.maxComputeWorkgroupSizeX),w=r.runWebGPUProgram(b,[d],x,A);i.push(w),m=ke({inputs:{x:w},attrs:{shape:h},backend:r})}return i.forEach(f=>r.disposeData(f.dataId)),m}function Vce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return gl(r,i,s,"all",a)}var Uce={kernelName:_i,backendName:"webgpu",kernelFunc:Vce};function Gce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return gl(r,i,s,"any",a)}var Hce={kernelName:Oi,backendName:"webgpu",kernelFunc:Gce},A9=class{constructor(e,t,a){this.workgroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let n=[t];this.op=a==="min"?"<":">";let[r,s]=I.computeOutAndReduceShapes(e,n);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=me(this.outputShape),v.sizeFromShape(s)<32?(this.type="plain",this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize)):(this.type="shared",this.dispatch=de(this.dispatchLayout,this.outputShape,[1,1,1])),this.inputShape=e,this.shaderKey=`argMinMax_${this.op}_${this.type}`}getUserCode(){let e=this.workgroupSize[0],t=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${Nr(this.inputShape.length-1)}`,a=()=>{let n="";if(this.outputShape.length===1)this.inputShape.length!==1&&(n+="outputCoords,");else for(let r=0;r u32 { return ((a - 1u) / b + 1u); } ${` var xBestIndices : array; var xBestValues : array; `} ${ue("index")} { let outputIndex = index / ${e}; let reduceLength = ${t()}; var bestIndex = i32(localId.x); var bestValue = uniforms.infinityValue; let outputCoords = getCoordsFromIndex(outputIndex); for (var k = i32(localId.x); k < reduceLength && outputIndex < uniforms.size; k = k + ${e}) { let candidate = getX(${a()} k); if (!isnan(candidate) && candidate ${this.op} bestValue) { bestValue = candidate; bestIndex = k; } } xBestValues[localId.x] = bestValue; xBestIndices[localId.x] = bestIndex; workgroupBarrier(); var reduceSize = min(u32(reduceLength), ${e}u); for (var currentSize = reduceSize / 2u; reduceSize > 1u; currentSize = reduceSize / 2u) { let interval = DIV_CEIL(reduceSize, 2u); if (localId.x < currentSize) { let candidate = xBestValues[localId.x + interval]; if (candidate ${this.op} bestValue) { bestValue = candidate; xBestValues[localId.x] = bestValue; xBestIndices[localId.x] = xBestIndices[localId.x + interval]; } } reduceSize = interval; workgroupBarrier(); } if (localId.x == 0u && outputIndex < uniforms.size) { setOutputAtIndexI32(outputIndex, xBestIndices[localId.x]); } } `:` ${ue("index")} { if (index < uniforms.size) { let outputCoords = getCoordsFromIndex(index); var bestIndex = 0; var bestValue = getX(${a()} 0); let reduceLength = ${t()}; for (var i = 1; i < reduceLength; i++) { let candidate = getX(${a()} i); if (candidate ${this.op} bestValue) { bestValue = candidate; bestIndex = i; } } setOutputAtIndexI32(index, bestIndex); } } `}};function jce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=I.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=ir({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=I.getInnerMostAxes(i.length,l.shape.length)),I.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let d=new A9(l.shape,i[0],"max"),c=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],p=a.runWebGPUProgram(d,[l],"int32",c);return u.forEach(h=>a.disposeData(h.dataId)),p}var qce={kernelName:hu,backendName:"webgpu",kernelFunc:jce};function Xce(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s}=n,i=v.parseAxisParam(s,r.shape),o=I.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=ir({inputs:{x:r},backend:a,attrs:{perm:o}}),u.push(l),i=I.getInnerMostAxes(i.length,l.shape.length)),I.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let d=new A9(l.shape,i[0],"min"),c=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],p=a.runWebGPUProgram(d,[l],"int32",c);return u.forEach(h=>a.disposeData(h.dataId)),p}var Kce={kernelName:mu,backendName:"webgpu",kernelFunc:Xce},Yce=at({opType:le.ASIN}),Zce={kernelName:zi,backendName:"webgpu",kernelFunc:Yce},Jce=at({opType:le.ASINH}),Qce={kernelName:Li,backendName:"webgpu",kernelFunc:Jce},ehe=at({opType:le.ATAN}),the={kernelName:Wi,backendName:"webgpu",kernelFunc:ehe},ahe=aa({opType:De.ATAN2}),nhe={kernelName:Vi,backendName:"webgpu",kernelFunc:ahe},rhe=at({opType:le.ATANH}),she={kernelName:Bi,backendName:"webgpu",kernelFunc:rhe},ihe=class{constructor(e){this.variableNames=["x"],this.uniforms="strides : vec2,",this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords[0]; let d = coords[3]; let xRCCorner = coords.yz * uniforms.strides; let xRCorner = xRCCorner.x; let xCCorner = xRCCorner.y; let value = getX(batch, xRCorner, xCCorner, d); setOutputAtIndex(index, value); } } `}},pp=class{constructor(e,t,a=!1,n=!1,r=!1){if(this.variableNames=["x"],this.uniforms="strides : vec2, pads : vec2, dilations : vec2, convDims : vec2, filterDims : vec2,",this.workgroupSize=[128,1,1],this.size=!0,t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.poolType=t,this.computePositions=a,this.flattenPositions=n,this.includeBatchIndex=r,this.shaderKey=`pool2D_${t}_${a}_${n}_${r}`}getUserCode(){let e;this.poolType==="avg"?e="resultValue = resultValue + value; count = count + 1.0;":this.computePositions?e=`let currMaxValue = mix(value, maxValue, maxValueFound); if (value >= currMaxValue) { maxValue = value; maxValueFound = 1.0; maxPosition = ${this.flattenPositions?this.includeBatchIndex?"((batch * uniforms.xShape[1] + xR) * uniforms.xShape[2] + xC) * uniforms.xShape[3] + d":"(xR * uniforms.xShape[2] + xC) * uniforms.xShape[3] + d":"wR * uniforms.filterDims.y + wC"}; }`:e="resultValue = max(value, resultValue);";let t="resultValue";return this.poolType==="avg"&&(t="resultValue / max(count, 1.0)"),` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords[0]; let d = coords[3]; let xRCCorner = vec2(coords.yz) * uniforms.strides - uniforms.pads; let xRCorner = xRCCorner.x; let xCCorner = xRCCorner.y; ${this.computePositions?`var maxValue = 0.0; var maxValueFound = 0.0; var maxPosition = 0;`:`var resultValue = ${this.poolType==="avg"?"0.0":"-1.0 / pow(10.0, -20.0)"};`} var count = 0.0; for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + uniforms.dilations.x) { let xR = xRCorner + wR; if (xR < 0 || xR >= uniforms.convDims.x) { continue; } for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilations.y) { let xC = xCCorner + wC; if (xC < 0 || xC >= uniforms.convDims.y) { continue; } let value = getX(batch, xR, xC, d); ${e} } } ${this.computePositions?"setOutputAtIndexI32(index, maxPosition);":`setOutputAtIndex(index, ${t});`} } } `}},uy=class{constructor(e,t,a=!1,n=!1,r=!1){if(this.variableNames=["x"],this.uniforms="strides : vec3, pads : vec3, convDims : vec3, filterDims : vec3,",this.workgroupSize=[128,1,1],this.size=!0,t==="avg"&&a)throw new Error("Cannot compute positions for average pool.");this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.poolType=t,this.computePositions=a,this.flattenPositions=n,this.includeBatchIndex=r,this.shaderKey=`pool3D_${t}_${a}_${n}_${r}`}getUserCode(){let e;this.poolType==="avg"?e="resultValue += value; count += 1.0;":this.computePositions?e=`let currMaxValue = mix(value, maxValue, maxValueFound); if (value >= currMaxValue) { maxValue = value; maxValueFound = 1.0; maxPosition = ${this.flattenPositions?this.includeBatchIndex?"(((batch * uniforms.xShape.y + xD) * uniforms.xShape.z + xR) * uniforms.xShape.w + xC) * uniforms.xShape.u + ch":"((xD * uniforms.xShape.z + xR) * uniforms.xShape.w + xC) * uniforms.xShape.u + ch":"wD * uniforms.filterDims.y * uniforms.filterDims.y + wR * uniforms.filterDims.z + wC"}; }`:e="resultValue = max(value, resultValue);";let t="resultValue";return this.poolType==="avg"&&(t="resultValue / max(count, 1.0)"),` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords.x; let ch = coords.u; let xCorner = vec3(coords.y, coords.z, coords.w) * uniforms.strides - uniforms.pads; let xDCorner = xCorner.x; let xRCorner = xCorner.y; let xCCorner = xCorner.z; ${this.computePositions?`var maxValue = 0.0; var maxValueFound = 0.0; var maxPosition = 0;`:`var resultValue = ${this.poolType==="avg"?"0.0":"-1.0 / pow(10.0, -20.0)"};`} var count = 0.0; for (var wD = 0; wD < uniforms.filterDims.x; wD++) { let xD = xDCorner + wD; if (xD < 0 || xD >= uniforms.convDims.x) { continue; } for (var wR = 0; wR < uniforms.filterDims.y; wR++) { let xR = xRCorner + wR; if (xR < 0 || xR >= uniforms.convDims.y) { continue; } for (var wC = 0; wC < uniforms.filterDims.z; wC++) { let xC = xCCorner + wC; if (xC < 0 || xC >= uniforms.convDims.z) { continue; } let value = getX(batch, xD, xR, xC, ch); ${e} } } } ${this.computePositions?"setOutputAtIndexI32(index, maxPosition);":`setOutputAtIndex(index, ${t});`} } } `}};function b9(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=n;return gl(r,s,i,"max",a)}var ohe={kernelName:Io,backendName:"webgpu",kernelFunc:b9};function v9(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{keepDims:s,axis:i}=n;return gl(r,i,s,"mean",a)}var lhe={kernelName:To,backendName:"webgpu",kernelFunc:v9};function w9(e,t,a,n){if(t.filterWidth===1&&t.filterHeight===1&&v.arraysEqual(t.inShape,t.outShape))return an({inputs:{x:e},backend:n});if(t.filterWidth===t.inWidth&&t.filterHeight===t.inHeight&&t.batchSize===1&&t.padInfo.type==="VALID"){let i=e.shape.length,o=ke({inputs:{x:e},backend:n,attrs:{shape:[e.shape[i-3]*e.shape[i-2],e.shape[i-1]]}}),l;a==="avg"?l=v9({inputs:{x:o},backend:n,attrs:{axis:0,keepDims:!1}}):(v.assert(a==="max",()=>`Invalid pool type ${a}`),l=b9({inputs:{x:o},backend:n,attrs:{reductionIndices:0,keepDims:!1}}));let u=ke({inputs:{x:l},backend:n,attrs:{shape:t.outShape}});return n.disposeData(o.dataId),n.disposeData(l.dataId),u}let r,s=[{type:"int32",data:[t.strideHeight,t.strideWidth]}];return t.filterHeight===1&&t.filterWidth===1?r=new ihe(t):(a==="avg"?r=new pp(t,"avg"):(v.assert(a==="max",()=>`Invalid pool type ${a}`),r=new pp(t,"max")),s.push({type:"int32",data:[t.padInfo.top,t.padInfo.left]},{type:"int32",data:[t.dilationHeight,t.dilationWidth]},{type:"int32",data:[t.inHeight,t.inWidth]},{type:"int32",data:[t.effectiveFilterHeight,t.effectiveFilterWidth]})),n.runWebGPUProgram(r,[e],e.dtype,s)}function uhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=I.computePool2DInfo(r.shape,s,i,1,o,l);return w9(r,u,"avg",a)}var dhe={kernelName:Ui,backendName:"webgpu",kernelFunc:uhe};function phe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=n,d=[1,1,1],c=I.computePool3DInfo(r.shape,s,i,d,o,u,l),p=new uy(c,"avg"),h=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.front,c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.inDepth,c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]}];return a.runWebGPUProgram(p,[r],r.dtype,h)}var che={kernelName:fu,backendName:"webgpu",kernelFunc:phe},hhe=class{constructor(e){this.variableNames=["dy"],this.uniforms=`strides : vec2, pads : vec2, dilations : vec2, filterDims : vec2, outHeight : i32, outWidth : i32, avgMultiplier : f32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="avgPool2DBackprop"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords[0]; let d = coords[3]; let dyRCCorner = vec2(coords.yz) - uniforms.pads; let dyRCorner = dyRCCorner.x; let 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. var dotProd = 0.0; for (var wR = 0; wR < uniforms.filterDims[0]; wR = wR + uniforms.dilations[0]) { let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]); if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) { continue; } let idyR = i32(dyR); for (var wC = 0; wC < uniforms.filterDims[1]; wC = wC + uniforms.dilations[1]) { let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]); if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) { continue; } let idyC = i32(dyC); let dyValue = getDy(batch, idyR, idyC, d); dotProd = dotProd + dyValue * uniforms.avgMultiplier; } } setOutputAtIndex(index, dotProd); } } `}},mhe=class{constructor(e){this.variableNames=["dy"],this.uniforms=`strides : vec3, pads : vec3, filterDims : vec3, outDepth : i32, outHeight : i32, outWidth : i32, avgMultiplier : f32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="avgPool3DBackprop"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords.x; let ch = coords.u; let dyCorner = vec3(coords.y, coords.z, coords.w) - uniforms.pads; let dyDCorner = dyCorner.x; let dyRCorner = dyCorner.y; let 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. var dotProd = 0.0; for (var wD = 0; wD < uniforms.filterDims[0]; wD++) { let dyD = f32(dyDCorner + wD) / f32(uniforms.strides[0]); if (dyD < 0.0 || dyD >= f32(uniforms.outDepth) || fract(dyD) > 0.0) { continue; } let idyD = i32(dyD); for (var wR = 0; wR < uniforms.filterDims[1]; wR++) { let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]); if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) { continue; } let idyR = i32(dyR); for (var wC = 0; wC < uniforms.filterDims[2]; wC++) { let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]); if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) { continue; } let idyC = i32(dyC); let dyValue = getDy(batch, idyD, idyR, idyC, ch); dotProd += dyValue * uniforms.avgMultiplier; } } } setOutputAtIndex(index, dotProd); } } `}};function fhe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:d}=n,c=I.computePool3DInfo(i.shape,o,l,1,u,d),p=new mhe(c),h=1/(c.filterDepth*c.filterHeight*c.filterWidth),m=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.effectiveFilterDepth-1-c.padInfo.front,c.effectiveFilterHeight-1-c.padInfo.top,c.effectiveFilterWidth-1-c.padInfo.left]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]},{type:"int32",data:[c.outDepth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"float32",data:[h]}];return a.runWebGPUProgram(p,[r],i.dtype,m)}var ghe={kernelName:yp,backendName:"webgpu",kernelFunc:fhe};function yhe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s;ay([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,d=I.computePool2DInfo(i.shape,o,l,1,u),c=new hhe(d),p=1/(d.filterHeight*d.filterWidth),h=[{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.effectiveFilterHeight-1-d.padInfo.top,d.effectiveFilterWidth-1-d.padInfo.left]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[d.effectiveFilterHeight,d.effectiveFilterWidth]},{type:"int32",data:[d.outHeight]},{type:"int32",data:[d.outWidth]},{type:"float32",data:[p]}];return a.runWebGPUProgram(c,[r],i.dtype,h)}var xhe={kernelName:gp,backendName:"webgpu",kernelFunc:yhe};function Ahe(e){let{inputs:t,backend:a,attrs:n}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=n;return x0({a:r,b:s,transposeA:i,transposeB:o,backend:a})}var bhe={kernelName:Gi,backendName:"webgpu",kernelFunc:Ahe},vhe=class{constructor(e,t){this.variableNames=["source"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.rank=t.length,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Dt(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Dt(this.rank),t=whe(this.rank),a;return this.start.length===1?a=this.outputShape.map((n,r)=>"sourceLoc = uniforms.start + coords;"):a=this.outputShape.map((n,r)=>`sourceLoc.${ag[r]} = uniforms.start.${Nr(r)} + coords.${ag[r]};`),` ${ue("index")} { if (index < uniforms.size) { var sourceLoc : ${e}; let coords = getCoordsFromIndex(index); ${a.join(` `)} setOutputAtIndex(index, getSource(${t})); } } `}},ag=["x","y","z","w","u","v"];function whe(e){if(e===1)return"sourceLoc";if(e<=6)return ag.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function od(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,size:i}=n,[o,l]=wt.parseSliceParams(r,s,i);if(wt.assertParamsValid(r,o,l),a.shouldExecuteOnCPU([r])||r.dtype==="string"){let c=a.tensorMap.get(r.dataId),p=Ace(c.values,o,l,r.shape,r.dtype);return a.makeTensorInfo(l,r.dtype,p)}if(v.sizeFromShape(l)===0)return a.makeTensorInfo(l,r.dtype,[]);let u=new vhe(o,l),d=[{type:"int32",data:o}];return a.runWebGPUProgram(u,[r],r.dtype,d)}var khe={kernelName:zu,backendName:"webgpu",kernelFunc:od},Ihe=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,crops:i}=n;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet");let o=s.reduce((x,A)=>x*A),l=I.getReshaped(r.shape,s,o),u=I.getPermuted(l.length,s.length),d=I.getReshapedPermuted(r.shape,s,o),c=I.getSliceBeginCoords(i,s.length),p=I.getSliceSize(d,i,s.length),h=[],m=ke({inputs:{x:r},backend:a,attrs:{shape:l}}),f=ir({inputs:{x:m},backend:a,attrs:{perm:u}}),g=ke({inputs:{x:f},backend:a,attrs:{shape:d}}),y=od({inputs:{x:g},backend:a,attrs:{begin:c,size:p}});return h.push(m),h.push(f),h.push(g),h.forEach(x=>a.disposeData(x.dataId)),y},She={kernelName:gu,backendName:"webgpu",kernelFunc:Ihe},The=` fn bincount_write(index: i32, value: f32) { ${Bs("&result[index]","value","float32")} } `,Che=` fn bincount_write(index: i32, value: f32) { atomicStore(&result[index], bitcast(value)); } `,k9=class{constructor(e,t,a=!1){this.outputShape=[],this.variableNames=["x"],this.uniforms="binCountSize : i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.hasWeights=!0,this.binaryOutput=!1,this.outputShape=e,this.rank=e.length,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.binaryOutput=a,a&&(this.atomic=!1),this.hasWeights=t,this.hasWeights&&this.variableNames.push("w"),this.shaderKey=`bincount_${this.hasWeights}_${this.binaryOutput}_${this.rank}`}getUserCode(){return` ${this.binaryOutput?Che:The} ${ue("index")} { ${this.rank===1?`if (index < uniforms.xShape) { let indexVal = i32(getX(index)); if (indexVal < uniforms.binCountSize) { let value = ${this.binaryOutput?1:this.hasWeights?"getW(index)":"1."}; bincount_write(indexVal, value); } }`:`let coord = getCoordsFromIndex(index); if (coordsInBounds2D(coord, uniforms.xShape)) { let indexVal = i32(getX(coord[0], coord[1])); if (indexVal < uniforms.binCountSize) { let value = ${this.binaryOutput?1:this.hasWeights?"getW(coord[0], coord[1])":"1."}; bincount_write(coord.x * uniforms.binCountSize + indexVal, value); } }`} } `}};function Nhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i}=n,o=v.sizeFromShape(r.shape),l=v.sizeFromShape(s.shape)>0,u=[i],d=s.dtype,c=Wa({backend:a,attrs:{shape:u,value:0,dtype:d}}),p=new k9([o],l),h=[{type:"int32",data:[i]}],m=l?[r,s]:[r];return a.runWebGPUProgram(p,m,d,h,c)}var Rhe={kernelName:Hi,backendName:"webgpu",kernelFunc:Nhe},Ehe=class{constructor(e){this.outputShape=[],this.variableNames=["s0","s1"],this.uniforms="s0Size : i32, s1Size : i32, ",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="broadcastArgs"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { var s0 = 1.0; var s1 = 1.0; let indexS0 = index - uniforms.size + uniforms.s0Size; let indexS1 = index - uniforms.size + uniforms.s1Size; if (indexS0 >= 0) { s0 = getS0(indexS0); } if (indexS1 >= 0) { s1 = getS1(indexS1); } if (s0 == 1.0) { setOutputAtIndex(index, s1); } else if (s1 == 1.0) { setOutputAtIndex(index, s0); } else if (s0 != s1) { setOutputAtIndex(index, uniforms.NAN); } else { setOutputAtIndex(index, s0); } } } `}};function Mhe(e){let{inputs:t,backend:a}=e,{s0:n,s1:r}=t;if(a.shouldExecuteOnCPU([n,r])){let d=a.tensorMap.get(n.dataId),c=a.tensorMap.get(r.dataId),p=d.values,h=c.values,m=I.assertAndGetBroadcastShape(Array.from(p),Array.from(h));return a.makeTensorInfo([m.length],"int32",Int32Array.from(m))}let s=v.sizeFromShape(n.shape),i=v.sizeFromShape(r.shape),o=Math.max(s,i),l=new Ehe(o),u=[{type:"int32",data:[s]},{type:"int32",data:[i]}];return a.runWebGPUProgram(l,[n,r],"int32",u)}var Fhe={kernelName:yu,backendName:"webgpu",kernelFunc:Mhe},I9=aa({opType:De.NOT_EQUAL,dtype:"bool",cpuKernelImpl:hce}),$he={kernelName:Cs,backendName:"webgpu",kernelFunc:I9};function oc(e){let{inputs:t,backend:a}=e,{input:n}=t,r=a.tensorMap.get(n.dataId);return an({inputs:{x:r.complexTensorInfos.real},backend:a})}var Dhe={kernelName:Ep,backendName:"webgpu",kernelFunc:oc};function Phe(e,t){let a=new id(e.shape,le.TO_INT),n=t.runWebGPUProgram(a,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function ng(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dtype:s}=n;if(s==="complex64"){if(r.dtype==="complex64")return an({inputs:{x:r},backend:a});let i=An(r.shape),o=ng({inputs:{x:r},backend:a,attrs:{dtype:"float32"}}),l=fl({inputs:{real:o,imag:i},backend:a});return i.dispose(),a.disposeData(o.dataId),l}if(r.dtype==="complex64"){let i=oc({inputs:{input:r},backend:a}),o=ng({inputs:{x:i},backend:a,attrs:{dtype:s}});return a.disposeData(i.dataId),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=an({inputs:{x:r},backend:a});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(a.shouldExecuteOnCPU([r])){let i=a.tensorMap.get(r.dataId).values,[o,l,u]=qpe(i,r.shape,r.dtype,s);return a.makeTensorInfo(o,l,u)}if(s==="int32")return Phe(r,a);if(s==="bool"){let i=a.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=I9({inputs:{a:r,b:i},backend:a});return a.disposeData(i.dataId),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var _he={kernelName:qi,backendName:"webgpu",kernelFunc:ng},Ohe=at({opType:le.CEIL,cpuKernelImpl:Xpe}),zhe={kernelName:cs,backendName:"webgpu",kernelFunc:Ohe},Lhe=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workgroupSize=[64,1,1],this.outputComponent=4,this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return` ${ue("index")} { if(index < uniforms.size) { let value = getAByOutputIndex(index); var clampedValue = clamp( value, vec4(uniforms.minVal), vec4(uniforms.maxVal)); clampedValue = select(clampedValue, value, isnanVec4(value)); setOutputAtIndex(index, clampedValue); } } `}},Whe=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="clip"}getUserCode(){return` ${ue("index")} { if(index < uniforms.size) { let value = getAByOutputIndex(index); if (isnan(value)) { setOutputAtIndex(index, value); return; } setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal)); } } `}};function Bhe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=n,o,l=[{type:"float32",data:[s]},{type:"float32",data:[i]}];return v.sizeFromShape(r.shape)%4===0?o=new Lhe(r.shape):o=new Whe(r.shape),a.runWebGPUProgram(o,[r],r.dtype,l)}var Vhe={kernelName:hs,backendName:"webgpu",kernelFunc:Bhe},Uhe=class{constructor(e){this.outputShape=[],this.variableNames=["real","imag"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="complexAbs"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let re = abs(getRealByOutputIndex(index)); let im = abs(getImagByOutputIndex(index)); let mx = max(re, im); // The length function in wgsl may be not underflow-safe on some GPUs. // So the safe solution is to ensure underflow-safety in all cases. setOutputAtIndex(index, select(mx * length(vec2(1, min(re, im)/mx)), 0.0, mx == 0.0)); } } `}};function kA(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function Ghe(e){let{inputs:t,backend:a}=e,{x:n}=t,r=a.tensorMap.get(n.dataId),s=new Uhe(n.shape),i=[kA(n,r.complexTensorInfos.real),kA(n,r.complexTensorInfos.imag)];return a.runWebGPUProgram(s,i,i[0].dtype)}var Hhe={kernelName:Ap,backendName:"webgpu",kernelFunc:Ghe},jhe=class{constructor(e){this.uniforms="",this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=I.computeOutShape(e,1),this.variableNames=e.map((t,a)=>`T${a}`),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]),this.offsetLength=e.length-1;for(let t=0;t0){e.push("if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }");for(let n=1;noc({inputs:{input:A},backend:a})),f=e.map(A=>A0({inputs:{input:A},backend:a})),g=Wd(m,t,a),y=Wd(f,t,a),x=fl({inputs:{real:g,imag:y},backend:a});return m.forEach(A=>a.disposeData(A.dataId)),f.forEach(A=>a.disposeData(A.dataId)),a.disposeData(g.dataId),a.disposeData(y.dataId),x}let r=a.shouldExecuteOnCPU(e);if(n==="string"&&(r=!0),r){let m=e.map(w=>{let S=[-1,v.sizeFromShape(w.shape.slice(t))];return ke({inputs:{x:w},backend:a,attrs:{shape:S}})}),f=m.map(w=>({vals:a.readSync(w.dataId),shape:w.shape})),g=I.computeOutShape(m.map(w=>w.shape),1),y=m[0].shape[0]===1,x=Kpe(f,g,n,y),A=I.computeOutShape(e.map(w=>w.shape),t),b=a.makeTensorInfo(A,n,x);return m.forEach(w=>a.disposeData(w.dataId)),b}let s=a.device.limits.maxStorageBuffersPerShaderStage-1;if(e.length>s){let m=[];for(let g=0;gm.shape),u=new jhe(l),d=[],c=new Array(l.length-1);if(c.length>0){c[0]=l[0][1],d.push({type:"int32",data:[c[0]]});for(let m=1;ma.disposeData(m.dataId));let h=ke({inputs:{x:p},backend:a,attrs:{shape:o}});return a.disposeData(p.dataId),h}function Xhe(e,t,a){let n=I.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>ke({inputs:{x:r},backend:a,attrs:{shape:[v.sizeFromShape(r.shape.slice(0,t)),v.sizeFromShape(r.shape.slice(t))]}})),outShape:n}}function S9(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);I.assertParamsConsistent(i,s);let o=I.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return a.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?an({inputs:{x:l[0]},backend:a}):Wd(l,s,a)}var Khe={kernelName:xu,backendName:"webgpu",kernelFunc:S9};function Yhe(e,t,a,n,r=!1,s=null,i=!1,o=4,l=4,u=4){let d=N=>{switch(N){case 1:return"resData = f32(x[xIndex]);";case 3:return"resData = vec3(x[xIndex], x[xIndex + 1], x[xIndex + 2]);";case 4:return"resData = vec4(x[xIndex / 4]);";default:throw new Error(`innerElementSize ${N} is not supported.`)}},c=N=>{switch(N){case 1:return"return f32(W[row * uniforms.wShape[3] + col]);";case 4:return"return vec4(W[(row * uniforms.wShape[3] + col) / 4]);";default:throw new Error(`innerElementSize ${N} is not supported.`)}},p=e?` let coord = vec4(batch, xRow, xCol, xCh); `:` let coord = vec4(batch, xCh, xRow, xCol); `,h=e?` let coords = vec4( batch, row / outWidth, row % outWidth, col); `:` let coords = vec4( batch, row, col / outWidth, col % outWidth); `,m=e?"uniforms.xShape[1]":"uniforms.xShape[2]",f=e?"uniforms.xShape[2]":"uniforms.xShape[3]",g=e?"row":"col",y=e?"col":"row",x=` let inChannels = uniforms.wShape[2]; let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"}; let outRow = ${g} / outWidth; let outCol = ${g} % outWidth; let WRow = ${y} / (uniforms.filterDims[1] * inChannels); let WCol = ${y} / inChannels % uniforms.filterDims[1]; let xRow = outRow * uniforms.strides[0] + uniforms.dilations[0] * WRow - uniforms.pads[0]; let xCol = outCol * uniforms.strides[1] + uniforms.dilations[1] * WCol - uniforms.pads[1]; let xCh = ${y} % inChannels; var resData = ${Xe(o)}(0.0); // The bounds checking is always needed since we use it to pad zero for // the 'same' padding type. if (xRow >= 0 && xRow < ${m} && xCol >= 0 && xCol < ${f}) { ${p} let xIndex = getIndexFromCoords4D(coord, uniforms.xShape); ${d(o)} } return resData;`,A=e?t&&n?` ${x}`:` if (row < uniforms.dimAOuter && col < uniforms.dimInner) { ${x} } return ${Xe(o)}(0.0);`:n&&a?` ${x}`:` if (row < uniforms.dimInner && col < uniforms.dimBOuter) { ${x} } return ${Xe(o)}(0.0);`,b=`${c(l)}`,w=Xe(u),S=Xe(e?o:l),C=Xe(e?l:o);return` ${Or(s,i,u===4,4)} fn mm_readA(batch: i32, row : i32, col : i32) -> ${S} { ${e?A:b} } fn mm_readB(batch: i32, row : i32, col : i32) -> ${C} { ${e?b:A} } fn mm_write(batch: i32, row : i32, col : i32, valueIn : ${w}) { if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) { var value = valueIn; let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"}; ${h} ${ml(r,s)} setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value); } }`}var Zhe=class{constructor(e,t,a,n,r=!1,s=null,i=!1,o=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2, pads : vec2, strides : vec2, dilations : vec2, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workgroupSize=Q3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=ey(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4?(this.outputComponent=4,this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableComponents=[1,4]):(this.innerElementSize=4,this.variableComponents=[4,4]),r&&(this.variableNames.push("bias"),this.variableComponents.push(4)),i&&(this.variableNames.push("preluActivationWeights"),this.variableComponents.push(4))):(this.innerElementSize=this.elementsPerThread[0],r&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights")),this.sequentialAccessByThreads=o,this.addBias=r,this.activation=s,this.hasPreluActivationWeights=i,this.tileAOuter=this.workgroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workgroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workgroupSize[0]*this.innerElementSize,this.workgroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=a%this.tileBOuter===0,this.fitInner=n%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}_${this.sequentialAccessByThreads}`}getUserCode(){let e=this.isVec4?g0(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner):y0(this.elementsPerThread,this.workgroupSize,!this.isChannelsLast,this.tileInner,!1,null,this.sequentialAccessByThreads),t=this.isVec4?[this.innerElementSize,4,4]:[1,1,1];return` ${Yhe(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])} ${e} `}},Jhe=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms="filterDims: vec2, pads: vec2, strides: vec2, dilations: vec2,",this.workgroupSize=[4,4,8],this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.dispatchLayout=this.isChannelsLast?{x:[2],y:[1],z:[0,3]}:{x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.addBias=t,this.activation=a,this.hasPreluActivationWeights=n,t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`conv2dnaive_${this.activation}_${this.isChannelsLast}`}getUserCode(){return` ${Or(this.activation,this.hasPreluActivationWeights,!1,4)} fn readInp(batch : i32, row : i32, col : i32, chan : i32) -> f32{ let coords = vec4(batch, row, col, chan); if (coordsInBounds4D(coords, uniforms.xShape)) { return getX(batch, row, col, chan); } else { return 0.0; } } fn readFilt(row : i32, col : i32, xChannel : i32, outChannel : i32) -> f32{ let coords = vec4(row, col, xChannel, outChannel); if(coordsInBounds4D(coords, uniforms.wShape)) { return getW(row, col, xChannel, outChannel); } else { return 0.0; } } fn writeResult(batch : i32, row : i32, col : i32, chan : i32, valueIn : f32) { let coords = ${this.isChannelsLast?"vec4(batch, row, col, chan);":"vec4(batch, chan, row, col);"} if (coordsInBounds4D(coords, uniforms.outShape)) { var value = valueIn; ${ml(this.addBias,this.activation)} setOutputAtCoords(coords.x, coords.y, coords.z, coords.w, value); } } ${ue("index")} { let coords = getOutputCoords(); let batch = coords[0]; let outChannel = ${this.isChannelsLast?"coords[3];":"coords[1];"} let outRow = ${this.isChannelsLast?"coords[1];":"coords[2];"} let outCol = ${this.isChannelsLast?"coords[2];":"coords[3];"} var acc : f32 = 0.0; for (var row = 0; row < uniforms.filterDims[0]; row = row + 1) { for (var col = 0; col < uniforms.filterDims[1]; col = col + 1) { let xRow = outRow * uniforms.strides[0] + uniforms.dilations[0] * row - uniforms.pads[0]; let xCol = outCol * uniforms.strides[1] + uniforms.dilations[1] * col - uniforms.pads[1]; for (var xChannel = 0; xChannel < ${this.isChannelsLast?"uniforms.xShape[3];":"uniforms.xShape[1];"} xChannel = xChannel + 1) { ${this.isChannelsLast?"let v = readInp(batch, xRow, xCol, xChannel);":"let v = readInp(batch, xChannel, xRow, xCol);"} let f = readFilt(row, col, xChannel, outChannel); acc = acc + v * f; } } } writeResult(batch, outRow, outCol, outChannel, acc); } `}},Qhe=class{constructor(e,t){this.variableNames=["x"],this.uniforms=`pads : vec2, strides : vec2, dilations : vec2, outWidth : i32, itemsPerBlockRow : i32, inChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=t,this.shaderKey=`im2col_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,a=this.isChannelsLast?"coords[1]":"coords[2]",n=this.isChannelsLast?"coords[2]":"coords[1]",r=this.isChannelsLast?"getX(batch, xRow, xCol, ch)":"getX(batch, ch, xRow, xCol)";return` ${ue("index")} { let coords = getCoordsFromIndex(index); if(index < uniforms.size) { let batch = coords[0]; let row = ${a}; let col = ${n}; let offsetY = (row / uniforms.outWidth) * uniforms.strides[0] - uniforms.pads[0]; let xRow = offsetY + uniforms.dilations[0] * (col / uniforms.itemsPerBlockRow); var value = 0.0; if(xRow < uniforms.xShape[${e}] && xRow >= 0) { let offsetX = (row % uniforms.outWidth) * uniforms.strides[1] - uniforms.pads[1]; let xCol = offsetX + uniforms.dilations[1] * ((col % uniforms.itemsPerBlockRow) / uniforms.inChannels); let ch = col % uniforms.inChannels; if(xCol < uniforms.xShape[${t}] && xCol >= 0) { value = ${r}; } } setOutputAtIndex(index, value); } } `}};function Ph(e,t){let a=e.length;return a>=3?t?[...e.slice(0,-3),e[a-3]*e[a-2],e[a-1]]:[...e.slice(0,-3),e[a-3],e[a-2]*e[a-1]]:!t&&a===1&&e[0]>1?[e[0],1]:null}function e0e({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=a.dataFormat==="channelsLast",u=!l,d=!1,c=l&&a.filterHeight===a.inHeight&&a.filterWidth===a.inWidth&&a.padInfo.type==="VALID",p=[],h,m;if(c){let y=a.inHeight*a.inWidth*a.inChannels;h=ke({inputs:{x:e},backend:n,attrs:{shape:[1,a.batchSize,y]}}),m=ke({inputs:{x:t},backend:n,attrs:{shape:[1,y,a.outChannels]}})}else h=ke({inputs:{x:e},backend:n,attrs:{shape:l?[a.batchSize,a.inHeight*a.inWidth,a.inChannels]:[a.batchSize,a.inChannels,a.inHeight*a.inWidth]}}),m=ke({inputs:{x:t},backend:n,attrs:{shape:[1,a.inChannels,a.outChannels]}});if(p.push(h),p.push(m),s!=null){let y=Ph(s.shape,l);y!=null&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:y}}),p.push(s))}if(r!=null){let y=Ph(r.shape,l);y!=null&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:y}}),p.push(r))}let f=x0({a:l?h:m,b:l?m:h,transposeA:u,transposeB:d,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),g=ke({inputs:{x:f},backend:n,attrs:{shape:a.outShape}});p.push(f);for(let y of p)n.disposeData(y.dataId);return g}function t0e({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:d,strideWidth:c,strideHeight:p,padInfo:h,outWidth:m,outHeight:f,dilationWidth:g,dilationHeight:y,dataFormat:x}=a,A=x==="channelsLast",b=l*u*d,w=f*m,S=A?[a.batchSize,w,b]:[a.batchSize,b,w],C=new Qhe(S,A),N=[{type:"int32",data:[h.top,h.left]},{type:"int32",data:[p,c]},{type:"int32",data:[y,g]},{type:"int32",data:[m]},{type:"int32",data:[d*l]},{type:"int32",data:[d]}],M=n.runWebGPUProgram(C,[e],e.dtype,N),F=[];F.push(M);let E=ke({inputs:{x:t},backend:n,attrs:{shape:[1,b,-1]}});if(F.push(E),s!=null){let O=Ph(s.shape,A);O!=null&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:O}}),F.push(s))}if(r!=null){let O=Ph(r.shape,A);O!=null&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:O}}),F.push(r))}let T=x0({a:A?M:E,b:A?E:M,transposeA:!A,transposeB:!1,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),D=ke({inputs:{x:T},backend:n,attrs:{shape:a.outShape}});F.push(T);for(let O of F)n.disposeData(O.dataId);return D}function T9({x:e,filter:t,convInfo:a,backend:n,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=r!=null,u=s!=null,d=a.dataFormat==="channelsLast",c=d&&a.filterHeight===a.inHeight&&a.filterWidth===a.inWidth&&a.padInfo.type==="VALID",p=B().getBool("WEBGPU_USE_NAIVE_CONV2D_DEBUG");if(!p&&(c||a.filterHeight===1&&a.filterWidth===1&&a.dilationHeight===1&&a.dilationWidth===1&&a.strideHeight===1&&a.strideWidth===1&&(a.padInfo.type==="SAME"||a.padInfo.type==="VALID")))return e0e({x:e,filter:t,convInfo:a,backend:n,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});let h=B().getNumber("WEBGPU_THRESHOLD_TO_INCREASE_WORKGROUPS_FOR_MATMUL"),m=h>-1?h:n.thresholdToIncreaseWorkgroups,f=a.batchSize*Math.ceil(a.outHeight*a.outWidth/32)*Math.ceil(a.outChannels/32);if(B().getBool("WEBGPU_CONV_SEPARATE_IM2COL_SHADER")||f<=m)return t0e({x:e,filter:t,convInfo:a,backend:n,bias:r,preluActivationWeights:s,leakyreluAlpha:i,activation:o});let g,y=[a.padInfo.top,a.padInfo.left],x=[{type:"int32",data:[a.filterHeight,a.filterWidth]},{type:"int32",data:[...y]},{type:"int32",data:[a.strideHeight,a.strideWidth]},{type:"int32",data:[a.dilationHeight,a.dilationWidth]}];if(p)g=new Jhe(a,l,o,u);else{let S=d?a.outHeight*a.outWidth:a.outChannels,C=d?a.outChannels:a.outHeight*a.outWidth,N=a.filterHeight*a.filterWidth*a.inChannels;x.push({type:"int32",data:[S]},{type:"int32",data:[C]},{type:"int32",data:[N]});let M=n.adapterInfo.isIntel();g=new Zhe(a,S,C,N,l,o,u,M)}let A=[],b=[e,t];l&&(!d&&r.shape.length===1&&(r=ke({inputs:{x:r},backend:n,attrs:{shape:[r.shape[0],1,1]}}),A.push(r)),b.push(r)),u&&(!d&&s.shape.length===1&&(s=ke({inputs:{x:s},backend:n,attrs:{shape:[s.shape[0],1,1]}}),A.push(s)),b.push(s)),o==="leakyrelu"&&(x.push({type:"float32",data:[i]}),g.uniforms+=" alpha : f32,");let w=n.runWebGPUProgram(g,b,e.dtype,x);for(let S of A)n.disposeData(S.dataId);return w}function a0e(e){let{inputs:t,attrs:a,backend:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:d}=a,c=I.convertConv2DDataFormat(l),p=I.computeConv2DInfo(r.shape,s.shape,i,u,o,d,!1,c);return T9({x:r,filter:s,convInfo:p,backend:n})}var n0e={kernelName:Xi,backendName:"webgpu",kernelFunc:a0e},r0e=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2, pads : vec2, strides : vec2, outBackprop : vec4,",this.workgroupSize=[64,1,1],this.size=!1,this.isVec4=!1,this.workPerThread=1,this.outputShape=e.inShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=this.isChannelsLast&&e.outChannels%4===0&&e.inChannels%4===0,this.isVec4?(this.workPerThread=2,this.outputComponent=4,this.workgroupSize=[4,4,4],this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[4,this.workPerThread,1])):(this.size=!0,this.workPerThread=1,this.workgroupSize=[64,1,1],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize)),this.shaderKey=`conv2DDerInput_${this.isChannelsLast}_${this.isVec4}_${this.workPerThread}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,a=this.isChannelsLast?3:1,n=` ${ue()} { let batch = i32(globalId.z) / uniforms.outShape[1]; let r = i32(globalId.z) % uniforms.outShape[1]; let c = i32(globalId.y) * ${this.workPerThread}; let d1 = i32(globalId.x) * 4; let dyCorner = vec2(r, c) - uniforms.pads; // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1). // ? = to be determined. : = across all values in that axis. var dotProd: array, ${this.workPerThread}>; for (var i = 0; i < ${this.workPerThread}; i++) { dotProd[i] = vec4(0.0); } for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) { let dyR = f32(dyCorner.x + wR) / f32(uniforms.strides.x); let wRPerm = uniforms.filterDims.x - 1 - wR; if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) || fract(dyR) > 0.0) { continue; } let idyR = i32(dyR); for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) { let dyC = f32(dyCorner.y + wC) / f32(uniforms.strides.y); let dyC2 = f32(dyCorner.y + 1 + wC) / f32(uniforms.strides.y); let wCPerm = uniforms.filterDims.y - 1 - wC; var bDyCVal = true; var bDyCVal2 = true; if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) || fract(dyC) > 0.0) { bDyCVal = false; } if (dyC2 < 0.0 || dyC2 >= f32(uniforms.outBackprop[2]) || fract(dyC2) > 0.0) { bDyCVal2 = false; } let idyC = i32(dyC); let idyC2 = i32(dyC2); if (bDyCVal && bDyCVal2) { let d2Length = uniforms.outBackprop[3]; for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) { let wValue0 = getW(wRPerm, wCPerm, d1, d2); let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2); let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2); let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2); var xValue = getDy(batch, idyR, idyC, d2); let tmpval = vec4(dot(xValue, wValue0), dot(xValue, wValue1), dot(xValue, wValue2), dot(xValue, wValue3)); dotProd[0] = dotProd[0] + tmpval; xValue = getDy(batch, idyR, idyC2, d2); dotProd[1] = dotProd[1] + vec4(dot(xValue, wValue0), dot(xValue, wValue1), dot(xValue, wValue2), dot(xValue, wValue3)); } } else if (bDyCVal) { let d2Length = uniforms.outBackprop[3]; for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) { let wValue0 = getW(wRPerm, wCPerm, d1, d2); let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2); let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2); let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2); var xValue = getDy(batch, idyR, idyC, d2); let tmpval = vec4(dot(xValue, wValue0), dot(xValue, wValue1), dot(xValue, wValue2), dot(xValue, wValue3)); dotProd[0] = dotProd[0] + tmpval; } } else if (bDyCVal2) { let d2Length = uniforms.outBackprop[3]; for (var d2 = 0; d2 < d2Length; d2 = d2 + 4) { let wValue0 = getW(wRPerm, wCPerm, d1, d2); let wValue1 = getW(wRPerm, wCPerm, d1 + 1, d2); let wValue2 = getW(wRPerm, wCPerm, d1 + 2, d2); let wValue3 = getW(wRPerm, wCPerm, d1 + 3, d2); var xValue = getDy(batch, idyR, idyC2, d2); let tmpval = vec4(dot(xValue, wValue0), dot(xValue, wValue1), dot(xValue, wValue2), dot(xValue, wValue3)); dotProd[1] = dotProd[1] + tmpval; } } } } for (var i = 0; i < ${this.workPerThread}; i = i + 1) { let coords = vec4(batch, r, c + i, d1); if (coordsInBounds4D(coords, uniforms.outShape)) { setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], dotProd[i]); } } } `;return this.isVec4?` ${n} `:` ${ue("index")} { if(index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords[0]; let d1 = coords[${a}]; let dyCorner = vec2(coords[${e}], coords[${t}]) - uniforms.pads; let dyRCorner = dyCorner.x; let 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. var dotProd = 0.0; for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) { let dyR = (f32(dyRCorner) + f32(wR)) / f32(uniforms.strides.x); let wRPerm = uniforms.filterDims.x - 1 - wR; if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) || fract(dyR) > 0.0 || wRPerm < 0) { continue; } let idyR = i32(dyR); for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) { let dyC = (f32(dyCCorner) + f32(wC)) / f32(uniforms.strides.y); let wCPerm = uniforms.filterDims.y - 1 - wC; if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) || fract(dyC) > 0.0 || wCPerm < 0) { continue; } let idyC = i32(dyC); for (var d2 = 0; d2 < uniforms.outBackprop[3]; d2 = d2 + 1) { let xValue = ${this.isChannelsLast?"getDy(batch, idyR, idyC, d2)":"getDy(batch, d2, idyR, idyC)"}; let wValue = getW(wRPerm, wCPerm, d1, d2); dotProd = dotProd + xValue * wValue; } } } setOutputAtIndex(index, dotProd); } } `}},s0e=class{constructor(e){this.variableNames=["x","dy"],this.uniforms="pads : vec2, strides : vec2, batchSize : i32, outHeight : i32, outWidth : i32, inHeight : i32, inWidth : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerFilter_${this.isChannelsLast}`}getUserCode(){return` ${ue("index")} { if(index < uniforms.size) { let coords = getCoordsFromIndex(index); let wR = coords[0]; let wC = coords[1]; let d1 = coords[2]; let d2 = coords[3]; // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2). // ? = to be determined. : = across all values in that axis. var dotProd = 0.0; for (var b = 0; b < uniforms.batchSize; b = b + 1) { for (var yR = 0; yR < uniforms.outHeight; yR = yR + 1) { let xR = wR + yR * uniforms.strides[0] - uniforms.pads[0]; if (xR < 0 || xR >= uniforms.inHeight) { continue; } for (var yC = 0; yC < uniforms.outWidth; yC = yC + 1) { let xC = wC + yC * uniforms.strides[1] - uniforms.pads[1]; if (xC < 0 || xC >= uniforms.inWidth) { continue; } if (${this.isChannelsLast}) { let dyValue = getDy(b, yR, yC, d2); let xValue = getX(b, xR, xC, d1); dotProd = dotProd + xValue * dyValue; } else { let dyValue = getDy(b, d2, yR, yC); let xValue = getX(b, d1, xR, xC); dotProd = dotProd + xValue * dyValue; } } } } setOutputAtIndex(index, dotProd); } } `}},i0e=class{constructor(e){this.variableNames=["x","dy"],this.uniforms=`pads : vec3, strides : vec3, batchSize : i32, outDepth : i32, outHeight : i32, outWidth : i32, inDepth : i32, inHeight : i32, inWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3DDerFilter"}getUserCode(){return` ${ue("index")} { if(index < uniforms.size) { let coords = getCoordsFromIndex(index); let wF = coords.x; let wR = coords.y; let wC = coords.z; let d1 = coords.w; let d2 = coords.u; var dotProd = 0.0; for (var b = 0; b < uniforms.batchSize; b++) { for (var yF = 0; yF < uniforms.outDepth; yF++) { let xF = wF + yF * uniforms.strides[0] - uniforms.pads[0]; if (xF < 0 || xF >= uniforms.inDepth) { continue; } for (var yR = 0; yR < uniforms.outHeight; yR++) { let xR = wR + yR * uniforms.strides[1] - uniforms.pads[1]; if (xR < 0 || xR >= uniforms.inHeight) { continue; } for (var yC = 0; yC < uniforms.outWidth; yC++) { let xC = wC + yC * uniforms.strides[2] - uniforms.pads[2]; if (xC < 0 || xC >= uniforms.inWidth) { continue; } let dyValue = getDy(b, yF, yR, yC, d2); let xValue = getX(b, xF, xR, xC, d1); dotProd += xValue * dyValue; } } } } setOutputAtIndex(index, dotProd); } } `}},o0e=class{constructor(e){this.variableNames=["dy","W"],this.uniforms=`filterDims : vec3, pads : vec3, strides : vec3, outDepth : i32, outHeight : i32, outWidth : i32, outChannels : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3DDerInput"}getUserCode(){return` ${ue("index")} { if(index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords.x; let d1 = coords.u; let dyCorner = vec3(coords.y, coords.z, coords.w) - uniforms.pads; let dyFCorner = dyCorner.x; let dyRCorner = dyCorner.y; let dyCCorner = dyCorner.z; var dotProd = 0.0; for (var wF = 0; wF < uniforms.filterDims[0]; wF++) { let dyF = f32(dyFCorner + wF) / f32(uniforms.strides[0]); if (dyF < 0.0 || dyF >= f32(uniforms.outDepth) || fract(dyF) > 0.0) { continue; } let idyF = i32(dyF); let wFPerm = uniforms.filterDims[0] - 1 - wF; for (var wR = 0; wR < uniforms.filterDims[1]; wR++) { let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]); if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) { continue; } let idyR = i32(dyR); let wRPerm = uniforms.filterDims[1] - 1 - wR; for (var wC = 0; wC < uniforms.filterDims[2]; wC++) { let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]); if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) { continue; } let idyC = i32(dyC); let wCPerm = uniforms.filterDims[2] - 1 - wC; for (var d2 = 0; d2 < uniforms.outChannels; d2++) { let xValue = getDy(batch, idyF, idyR, idyC, d2); let wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2); dotProd += xValue * wValue; } } } } setOutputAtIndex(index, dotProd); } } `}};function l0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:d}=n,c=I.convertConv2DDataFormat(l),p=I.computeConv2DInfo(r.shape,d,i,1,o,u,!1,c),h=new s0e(p),m=[{type:"int32",data:[p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.batchSize]},{type:"int32",data:[p.outHeight]},{type:"int32",data:[p.outWidth]},{type:"int32",data:[p.inHeight]},{type:"int32",data:[p.inWidth]}];return a.runWebGPUProgram(h,[r,s],r.dtype,m)}var u0e={kernelName:bp,backendName:"webgpu",kernelFunc:l0e};function d0e(e=4){let t=n=>{switch(n){case 1:return"return W[getIndexFromCoords4D(coord, uniforms.wShape)];";case 4:return` let coord1 = vec4(coordX, coordY, col + 1, rowInner); let coord2 = vec4(coordX, coordY, col + 2, rowInner); let coord3 = vec4(coordX, coordY, col + 3, rowInner); let v0 = W[getIndexFromCoords4D(coord, uniforms.wShape)]; let v1 = W[getIndexFromCoords4D(coord1, uniforms.wShape)]; let v2 = W[getIndexFromCoords4D(coord2, uniforms.wShape)]; let v3 = W[getIndexFromCoords4D(coord3, uniforms.wShape)]; return vec4(v0, v1, v2, v3); `;default:throw new Error(`innerElementSize ${n} is not supported.`)}},a=`if (row < uniforms.dimAOuter && col < uniforms.dimInner) { ${` let outRow = row / uniforms.outShape[2]; let outCol = row % uniforms.outShape[2]; let WRow = col / (uniforms.filterDims[1] * uniforms.outBackprop[3]); let WCol = col / uniforms.outBackprop[3] % uniforms.filterDims[1]; let xR = f32(outRow - uniforms.pads[0] + WRow) / f32(uniforms.strides[0]); let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.strides[1]); if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) { return ${Xe(e)}(0.0); } if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) { return ${Xe(e)}(0.0); } let coord = vec4( batch, i32(xR), i32(xC), col % uniforms.outBackprop[3]); return x[getIndexFromCoords4D(coord, uniforms.xShape)/${e}];`} } return ${Xe(e)}(0.0);`;return` fn mm_readA(batch: i32, row : i32, col : i32) -> ${Xe(e)} { ${a} } fn mm_readB(batch: i32, row : i32, col : i32) -> ${Xe(e)} { let coordX = uniforms.filterDims.x - 1 - row / (uniforms.filterDims[1] * uniforms.outBackprop[3]); let coordY = uniforms.filterDims.y - 1 - (row / uniforms.outBackprop[3]) % uniforms.filterDims[1]; if (row < uniforms.dimInner && col < uniforms.dimBOuter && coordX >= 0 && coordY >= 0) { let rowInner = row % uniforms.outBackprop[3]; let coord = vec4(coordX, coordY, col, rowInner); ${t(e)} } return ${Xe(e)}(0.0); } fn mm_write(batch: i32, row : i32, col : i32, valueInput : ${Xe(e)}) { if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) { var value = valueInput; let outCoord = vec4( batch, row / uniforms.outShape[2], row % uniforms.outShape[2], col); result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${e}] = value; } }`}var p0e=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims : vec2, pads : vec2, strides : vec2, outBackprop : vec4, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.inShape,v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),this.isVec4=e.inChannels%4===0&&e.outChannels%4===0,this.dispatchLayout={x:[3],y:[1,2],z:[0]},this.workgroupSize=Q3(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=ey(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,this.elementsPerThread),this.isVec4&&(this.outputComponent=4,this.variableComponents=[4,1]),this.shaderKey=`conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}`}getUserCode(){let e=this.isVec4?g0(this.elementsPerThread,this.workgroupSize):y0(this.elementsPerThread,this.workgroupSize);return` ${d0e(this.isVec4?4:1)} ${e} `}};function c0e(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:d}=n,c=I.convertConv2DDataFormat(u),p=I.computeConv2DInfo(i,s.shape,o,1,l,d,!1,c),h=[{type:"int32",data:[p.filterHeight,p.filterWidth]},{type:"int32",data:[p.filterHeight-1-p.padInfo.top,p.filterWidth-1-p.padInfo.left]},{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.batchSize,p.outHeight,p.outWidth,p.outChannels]}],m;if(B().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE")||p.dataFormat!=="channelsLast")m=new r0e(p);else{m=new p0e(p);let f=p.inHeight*p.inWidth,g=p.inChannels,y=p.filterHeight*p.filterWidth*p.outChannels;h.push({type:"uint32",data:[f]},{type:"uint32",data:[g]},{type:"uint32",data:[y]})}return a.runWebGPUProgram(m,[r,s],"float32",h)}var h0e={kernelName:Ki,backendName:"webgpu",kernelFunc:c0e},m0e=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims: vec3, pads: vec3, strides: vec3, dilations: vec3,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="conv3dnaive"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); let batch = coords.x; let d2 = coords.u; let xFRCCorner = vec3(coords.y, coords.z, coords.w) * uniforms.strides - uniforms.pads; let xFCorner = xFRCCorner.x; let xRCorner = xFRCCorner.y; let xCCorner = xFRCCorner.z; let inputDepthNearestVec4 = (uniforms.xShape.u / 4) * 4; let inputDepthVec4Remainder = uniforms.xShape.u % 4; var dotProd = 0.0; for (var wF = 0; wF < uniforms.filterDims[0]; wF++) { let xF = xFCorner + wF * uniforms.dilations[0]; if (xF < 0 || xF >= uniforms.xShape.y) { continue; } for (var wR = 0; wR < uniforms.filterDims[1]; wR++) { let xR = xRCorner + wR * uniforms.dilations[1]; if (xR < 0 || xR >= uniforms.xShape.z) { continue; } for (var wC = 0; wC < uniforms.filterDims[2]; wC++) { let xC = xCCorner + wC * uniforms.dilations[2]; if (xC < 0 || xC >= uniforms.xShape.w) { continue; } for (var d1 = 0; d1 < inputDepthNearestVec4; d1 += 4) { let 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) ); let 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 (inputDepthVec4Remainder == 1) { dotProd += getX(batch, xF, xR, xC, inputDepthNearestVec4) * getW(wF, wR, wC, inputDepthNearestVec4, d2); } else if (inputDepthVec4Remainder == 2) { let xValues = vec2( getX(batch, xF, xR, xC, inputDepthNearestVec4), getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1) ); let wValues = vec2( getW(wF, wR, wC, inputDepthNearestVec4, d2), getW(wF, wR, wC, inputDepthNearestVec4 + 1, d2) ); dotProd += dot(xValues, wValues); } else if (inputDepthVec4Remainder == 3) { let xValues = vec3( getX(batch, xF, xR, xC, inputDepthNearestVec4), getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1), getX(batch, xF, xR, xC, inputDepthNearestVec4 + 2) ); let wValues = vec3( getW(wF, wR, wC, inputDepthNearestVec4, d2), getW(wF, wR, wC, inputDepthNearestVec4 + 1, d2), getW(wF, wR, wC, inputDepthNearestVec4 + 2, d2) ); dotProd += dot(xValues, wValues); } } } } setOutputAtIndex(index, dotProd); } }`}};function f0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=I.computeConv3DInfo(r.shape,s.shape,i,l,o),d=[u.padInfo.front,u.padInfo.top,u.padInfo.left],c=[{type:"int32",data:[u.filterDepth,u.filterHeight,u.filterWidth]},{type:"int32",data:[...d]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.dilationDepth,u.dilationHeight,u.dilationWidth]}],p=new m0e(u),h=Qt(r.dtype,s.dtype);return a.runWebGPUProgram(p,[r,s],h,c)}var g0e={kernelName:Yi,backendName:"webgpu",kernelFunc:f0e};function y0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=I.computeConv3DInfo(r.shape,l,i,1,o),d=new i0e(u),c=[{type:"int32",data:[u.padInfo.front,u.padInfo.top,u.padInfo.left]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.batchSize]},{type:"int32",data:[u.outDepth]},{type:"int32",data:[u.outHeight]},{type:"int32",data:[u.outWidth]},{type:"int32",data:[u.inDepth]},{type:"int32",data:[u.inHeight]},{type:"int32",data:[u.inWidth]}];return a.runWebGPUProgram(d,[r,s],s.dtype,c)}var x0e={kernelName:Au,backendName:"webgpu",kernelFunc:y0e};function A0e(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,pad:o,inputShape:l}=n,u=I.computeConv3DInfo(l,s.shape,i,1,o),d=new o0e(u),c=[{type:"int32",data:[u.filterDepth,u.filterHeight,u.filterWidth]},{type:"int32",data:[u.filterDepth-1-u.padInfo.front,u.filterHeight-1-u.padInfo.top,u.filterWidth-1-u.padInfo.left]},{type:"int32",data:[u.strideDepth,u.strideHeight,u.strideWidth]},{type:"int32",data:[u.outDepth]},{type:"int32",data:[u.outHeight]},{type:"int32",data:[u.outWidth]},{type:"int32",data:[u.outChannels]}];return a.runWebGPUProgram(d,[r,s],r.dtype,c)}var b0e={kernelName:Zi,backendName:"webgpu",kernelFunc:A0e},v0e=at({opType:le.COS}),w0e={kernelName:Ji,backendName:"webgpu",kernelFunc:v0e},k0e=at({opType:le.COSH}),I0e={kernelName:Qi,backendName:"webgpu",kernelFunc:k0e},S0e=class{constructor(e,t,a,n){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workgroupSize=[64,1,1],this.size=!0;let[r]=t;this.outputShape=[r,a[0],a[1],e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.methodId=n==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`}getUserCode(){let[e,t]=["f32(uniforms.imageShape[1] - 1)","f32(uniforms.imageShape[2] - 1)"],[a,n,r]=this.cropHeightBiggerThan1?[`(${e} / f32(uniforms.outShape[1] - 1))`,"(y2-y1) * height_ratio",`y1*${e} + f32(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${e}`],[s,i,o]=this.cropWidthBiggerThan1?[`(${t} / f32(uniforms.outShape[2] - 1))`,"(x2-x1) * width_ratio",`x1*${t} + f32(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${t}`];return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let height_ratio = f32(${a}); let width_ratio = f32(${s}); let b = coords[0]; let y = coords[1]; let x = coords[2]; let d = coords[3]; // get box vals let y1 = getBoxes(b, 0); let x1 = getBoxes(b, 1); let y2 = getBoxes(b, 2); let x2 = getBoxes(b, 3); // get image in batch index let bInd = i32(round(getBoxInd(b))); if(bInd < 0 || bInd >= uniforms.outShape[0]) { return; } let height_scale = ${n}; let width_scale = ${i}; let in_y = ${r}; if( in_y < 0.0 || in_y > ${e} ) { setOutputAtIndex(index, uniforms.extrapolationValue); return; } let in_x = ${o}; if( in_x < 0.0 || in_x > ${t} ) { setOutputAtIndex(index, uniforms.extrapolationValue); return; } let sourceFracIndexCR = vec2(in_x,in_y); if(${this.methodId} == 1) { // Compute the four integer indices. let sourceFloorCR = vec2(sourceFracIndexCR); let sourceCeilCR = vec2(ceil(sourceFracIndexCR)); let topLeft = getImage(bInd, sourceFloorCR.y, sourceFloorCR.x, d); let bottomLeft = getImage(bInd, sourceCeilCR.y, sourceFloorCR.x, d); let topRight = getImage(bInd, sourceFloorCR.y, sourceCeilCR.x, d); let bottomRight = getImage(bInd, sourceCeilCR.y, sourceCeilCR.x, d); let fracCR = sourceFracIndexCR - vec2(sourceFloorCR); let top = topLeft + (topRight - topLeft) * fracCR.x; let bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x; let newValue = top + (bottom - top) * fracCR.y; setOutputAtIndex(index, newValue); } else { // Compute the coordinators of nearest neighbor point. let sourceNearestCR = vec2(floor( sourceFracIndexCR + vec2(0.5,0.5))); let newValue = getImage( bInd, sourceNearestCR.y, sourceNearestCR.x, d); setOutputAtIndex(index, newValue); } } } `}},T0e=e=>{let{inputs:t,backend:a,attrs:n}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,d=new S0e(r.shape[3],s.shape,o,l),c=[{type:"float32",data:[u]}];return a.runWebGPUProgram(d,[r,s,i],"float32",c)},C0e={kernelName:ao,backendName:"webgpu",kernelFunc:T0e},cp;(function(e){e.Prod="*",e.Sum="+"})(cp||(cp={}));var IA=class{constructor(e,t,a,n){this.variableNames=["x"],this.uniforms="index : f32,",this.size=!0,this.workgroupSize=[128,1,1],this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.exclusive=a,this.reverse=n,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===cp.Prod?"1.0":"0.0",a=this.exclusive?t:`getX(${SA(e,"coords",this.op)})`,n=this.outputShape[this.outputShape.length-1],r="",s="";return this.exclusive?(r=this.reverse?`end != ${n-1}`:"end != 0",s=this.reverse?"end + 1":"end - 1"):(r=this.reverse?`end + pow2 < ${n}`:"end >= pow2",s=this.reverse?"end + pow2":"end - pow2"),` ${ue("index")} { if (index < uniforms.size) { var coords = getCoordsFromIndex(index); let end = ${TA(e,"coords",this.op)}; var val = ${a}; let pow2 = i32(pow(2.0, uniforms.index)); if (${r}) { let idx = ${s}; ${TA(e,"coords",this.op)} = idx; val ${this.op}= getX(${SA(e,"coords",this.op)}); } setOutputAtIndex(index, val); } } `}};function SA(e,t,a){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 ${a} for rank ${e} is not yet supported`)}function TA(e,t,a){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative ${a} for rank ${e} is not yet supported`)}function C9(e,t,a,n,r,s){let i=t.shape.length,o=I.getAxesPermutation([n],i),l=t;o!=null&&(l=ir({inputs:{x:t},backend:a,attrs:{perm:o}}));let u=I.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let d=l.shape[u],c=an({inputs:{x:l},backend:a});for(let p=0;p<=Math.ceil(Math.log2(d))-1;p++){let h=new IA(e,l.shape,!1,s),m=c,f=[{type:"float32",data:[p]}];c=a.runWebGPUProgram(h,[c],c.dtype,f),a.disposeData(m.dataId)}if(r){let p=new IA(e,l.shape,r,s),h=c,m=[{type:"float32",data:[0]}];c=a.runWebGPUProgram(p,[c],c.dtype,m),a.disposeData(h.dataId)}if(o!=null){let p=I.getUndoAxesPermutation(o),h=ir({inputs:{x:c},backend:a,attrs:{perm:p}});return a.disposeData(c.dataId),a.disposeData(l.dataId),h}return c}function N0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return C9(cp.Prod,r,a,s,i,o)}var R0e={kernelName:eo,backendName:"webgpu",kernelFunc:N0e};function E0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=n;return C9(cp.Sum,r,a,s,i,o)}var M0e={kernelName:to,backendName:"webgpu",kernelFunc:E0e};function F0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=n,l=r.shape.length===1,u=v.sizeFromShape(s.shape)>0,d=s.dtype,c=l?[r.shape[0]]:[r.shape[0],r.shape[1]],p=l?[i]:[r.shape[0],i],h=Wa({backend:a,attrs:{shape:p,value:0,dtype:d}}),m=new k9(c,u,o),f=[{type:"int32",data:[i]}],g=u?[r,s]:[r];return a.runWebGPUProgram(m,g,d,f,h)}var $0e={kernelName:bu,backendName:"webgpu",kernelFunc:F0e},D0e=class{constructor(e,t){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let b = coords[0]; let h = ${this.getHeightCoordString()}; let w = ${this.getWidthCoordString()}; let d = ${this.getDepthCoordString()}; let in_h = h / uniforms.blockSize; let offset_h = h % uniforms.blockSize; let in_w = w / uniforms.blockSize; let offset_w = w % uniforms.blockSize; let offset_d = (offset_h * uniforms.blockSize + offset_w) * ${this.getOutputDepthSize()}; let in_d = d + offset_d; let rlt = ${this.getInputSamplingString()}; setOutputAtIndex(index, rlt); } }`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function P0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockSize:s,dataFormat:i}=n,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],d=i==="NHWC"?r.shape[3]:r.shape[1],c=l*s,p=u*s,h=d/(s*s),m=i==="NHWC"?[o,c,p,h]:[o,h,c,p],f=[{type:"int32",data:[s]}],g=new D0e(m,i);return a.runWebGPUProgram(g,[r],r.dtype,f)}var _0e={kernelName:no,backendName:"webgpu",kernelFunc:P0e},O0e=class{constructor(e,t,a,n=!1,r=null,s=!1){this.variableNames=["x","W"],this.uniforms="pads : vec2, inDims : vec2,",this.workgroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),n&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.addBias=n,this.activation=r,this.hasPreluActivation=s,this.filterHeight=t,this.filterWidth=a,this.shaderKey=`depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`}getUserCode(){let e=this.filterWidth*this.filterHeight,t=this.workgroupSize[0]*this.workgroupSize[1]*this.workgroupSize[2],a=this.workgroupSize[1]+this.filterHeight-1,n=this.workgroupSize[0]+this.filterWidth-1;return` ${Or(this.activation,this.hasPreluActivation,!1,4)} var mm_Asub : array, ${a}>; var mm_Bsub : array, ${this.filterHeight}>; fn readX(batch : i32, channel : i32, row : i32, col : i32) -> f32 { var value = 0.0; if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1]) { value = getX(batch, channel, row, col); } return value; } ${ue()} { let coords = getOutputCoords(); let batch = coords[0]; let xRCCorner = vec2(coords.zw) - uniforms.pads; let channelMul = uniforms.wShape[3]; let d1 = coords[1] / channelMul; let q = coords[1] % channelMul; let inputRowStart = xRCCorner.x; let inputColStart = xRCCorner.y; let localRow = i32(localId.y); let localCol = i32(localId.x); // Load one tile of X into local memory. for (var inputRow = localRow; inputRow < ${a}; inputRow = inputRow + ${this.workgroupSize[1]}) { for (var inputCol = localCol; inputCol < ${n}; inputCol = inputCol + ${this.workgroupSize[0]}) { let rowOffset = inputRow - localRow; let colOffset = inputCol - localCol; mm_Asub[inputRow][inputCol] = readX(batch, d1, inputRowStart + rowOffset, inputColStart + colOffset); } } // Load one tile of W into local memory. var wIndex = i32(localIndex); ${e, inDims : vec2, virtualWidth : i32,",this.workgroupSize=[64,1,1],this.workPerThread=4,this.outputComponent=4,this.outputShape=e.outShape,this.virtualWidth=Math.ceil(this.outputShape[2]/this.workPerThread)*this.workPerThread;let r=[this.outputShape[0],this.outputShape[1],this.virtualWidth,this.outputShape[3]];this.dispatchLayout=me(r),this.dispatch=de(this.dispatchLayout,r,this.workgroupSize,[this.outputComponent*this.workPerThread,1,1]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwiseVec4_${a}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}_${this.convInfo.strideHeight}_${this.convInfo.strideWidth}_${this.workPerThread}`}getUserCode(){let e=(this.workPerThread-1)*this.convInfo.strideWidth+this.convInfo.filterWidth,t=this.convInfo.strideHeight,a=this.convInfo.strideWidth;return` ${Or(this.activation,this.hasPreluActivation,!0,4)} fn readX(batch : i32, row : i32, col : i32, channel : i32) -> vec4 { var value = vec4(0.0); if (col >=0 && col < uniforms.inDims[1]) { value = getX(batch, row, col, channel); } return value; } ${ue("index")} { let width0 = uniforms.outShape[3] / ${this.outputComponent}; let d1 = (index % width0) * ${this.outputComponent}; var index1 = index / width0; let width1 = uniforms.virtualWidth / ${this.workPerThread}; let c = (index1 % width1) * ${this.workPerThread}; index1 = index1 / width1; let r = index1 % uniforms.outShape[1]; let batch = index1 / uniforms.outShape[1]; let xRCCorner = vec2(r, c) * vec2(${t}, ${a}) - uniforms.pads; let xRCorner = xRCCorner.x; let xCCorner = xRCCorner.y; var xVals : array, ${e}>; var dotProd : array, ${this.workPerThread}>; for (var i = 0; i < ${this.workPerThread}; i++) { dotProd[i] = vec4(0.0); } // Use constant instead of uniform can give better performance. for (var wR = 0; wR < ${this.convInfo.filterHeight}; wR = wR + 1) { let xR = xRCorner + wR; if (xR >=0 && xR < uniforms.inDims[0]) { for (var i = 0; i < ${e}; i++) { xVals[i] = readX(batch, xR, xCCorner + i, d1); } for (var wC = 0; wC < ${this.convInfo.filterWidth}; wC = wC + 1) { let wValue = getW(wR, wC, d1, 0); for (var i = 0; i < ${this.workPerThread}; i++) { dotProd[i] = fma(xVals[i * ${a} + wC], wValue, dotProd[i]); } } } } for (var i = 0; i < ${this.workPerThread}; i = i + 1) { let coords = vec4(batch, r, c + i, d1); if (coordsInBounds4D(coords, uniforms.outShape)) { var value = dotProd[i]; ${ml(this.addBias,this.activation)} setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value); } } } `}},R9=class{constructor(e,t=!1,a=null,n=!1){this.variableNames=["x","W"],this.uniforms=`pads : vec2, inDims : vec2, filterHeight : i32, filterWidth : i32, strides : vec2, dilations : vec2,`,this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=a,this.hasPreluActivation=n,this.shaderKey=`depthwise_${this.activation}_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?"getX(batch, xR, xC, d1);":"getX(batch, d1, xR, xC);";return` ${Or(this.activation,this.hasPreluActivation,!1,4)} ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); let batch = coords[0]; let xRCCorner = vec2(coords.${this.isChannelsLast?"yz":"zw"}) * uniforms.strides - uniforms.pads; let d2 = coords[${this.isChannelsLast?3:1}]; let channelMul = uniforms.wShape[3]; let d1 = d2 / channelMul; let q = d2 % channelMul; let inputRowStart = xRCCorner.x; let inputColStart = xRCCorner.y; let inputRowEnd = inputRowStart + uniforms.filterHeight * uniforms.dilations[0]; let inputColEnd = inputColStart + uniforms.filterWidth * uniforms.dilations[1]; // Convolve x(?, ?, d1)|x(d1, ?, ?) with w(:, :, d1, q) to get // y(yR, yC, d2)|y(d2, yR, yC). ? = to be determined. : = across all // values in that axis. x(?, ?, d1) and y(yR, yC, d2) is for NHWC. // x(d1, ?, ?) and y(d2, yR, yC) is for NCHW. var value = 0.0; // Extract if checking out of for loop for performance. if (inputRowStart >= 0 && inputColStart >= 0 && inputRowEnd < uniforms.inDims[0] && inputColEnd < uniforms.inDims[1]) { for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) { let xR = inputRowStart + wR * uniforms.dilations[0]; for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) { let xC = inputColStart + wC * uniforms.dilations[1]; let xVal = ${e}; let wVal = getW(wR, wC, d1, q); value = value + xVal * wVal; } } } else { for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) { let xR = inputRowStart + wR * uniforms.dilations[0]; if (xR < 0 || xR >= uniforms.inDims[0]) { continue; } for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) { let xC = inputColStart + wC * uniforms.dilations[1]; if (xC < 0 || xC >= uniforms.inDims[1]) { continue; } let xVal = ${e}; let wVal = getW(wR, wC, d1, q); value = value + xVal * wVal; } } } ${ml(this.addBias,this.activation)} setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value); } } `}};function z0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:d}=n,c=I.convertConv2DDataFormat(l),p=u;p==null&&(p=[1,1]);let h=I.computeConv2DInfo(r.shape,s.shape,i,p,o,d,!0,c),m=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],f=h.dataFormat==="channelsLast",g;return!f&&h.inHeight>16&&h.inWidth>16&&h.strideHeight===1&&h.strideWidth===1&&h.dilationWidth===1&&h.dilationHeight===1&&h.inChannels===h.outChannels?g=new O0e(h.outShape,h.filterHeight,h.filterWidth):f&&h.outHeight>4&&h.outWidth>4&&h.strideWidth<=2&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?(g=new N9(h),m.push({type:"int32",data:[g.virtualWidth]})):(g=new R9(h),m.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),a.runWebGPUProgram(g,[r,s],r.dtype,m)}var L0e={kernelName:ro,backendName:"webgpu",kernelFunc:z0e},W0e=class{constructor(e){this.variableNames=["x","dy"],this.uniforms=`strides : vec2, pads : vec2, filterDims : vec2, outHeight : i32, outWidth : i32, inHeight : i32, inWidth : i32, batchSize : i32, channelMul : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="depthwise_conv2d_backprop_filter"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let wR = coords[0]; let wC = coords[1]; let d1 = coords[2]; let dm = coords[3]; let d2 = d1 * uniforms.channelMul + dm; var dotProd = 0.0; for (var b = 0; b < uniforms.batchSize; b++) { for (var yR = 0; yR < uniforms.outHeight; yR++) { let xR = wR + yR * uniforms.strides[0] - uniforms.pads[0]; if (xR < 0 || xR >= uniforms.inHeight) { continue; } for (var yC = 0; yC < uniforms.outWidth; yC++) { let xC = wC + yC * uniforms.strides[1] - uniforms.pads[1]; if (xC < 0 || xC >= uniforms.inWidth) { continue; } let dyValue = getDy(b, yR, yC, d2); let xValue = getX(b, xR, xC, d1); dotProd += xValue * dyValue; } } } setOutputAtIndex(index, dotProd); } } `}},B0e=class{constructor(e){this.variableNames=["dy","W"],this.uniforms=`strides : vec2, pads : vec2, filterDims : vec2, outHeight : i32, outWidth : i32, channelMul : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="depthwise_conv2d_backprop_input"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords[0]; let d1 = coords[3]; let dyCorner = coords.yz - uniforms.pads; let dyRCorner = dyCorner.x; let dyCCorner = dyCorner.y; var dotProd = 0.0; for (var wR = 0; wR < uniforms.filterDims[0]; wR++) { let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]); if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) { continue; } let idyR = i32(dyR); let wRPerm = uniforms.filterDims[0] - 1 - wR; for (var wC = 0; wC < uniforms.filterDims[1]; wC++) { let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]); if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) { continue; } let idyC = i32(dyC); let wCPerm = uniforms.filterDims[1] - 1 - wC; for (var dm = 0; dm < uniforms.channelMul; dm++) { let d2 = d1 * uniforms.channelMul + dm; let xValue = getDy(batch, idyR, idyC, d2); let wValue = getW(wRPerm, wCPerm, d1, dm); dotProd += xValue * wValue; } } } setOutputAtIndex(index, dotProd); } } `}};function V0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:d}=n,c=I.computeConv2DInfo(r.shape,d,i,o,l,u,!0),p=new W0e(c),h=[{type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.filterHeight,c.filterWidth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"int32",data:[c.inHeight]},{type:"int32",data:[c.inWidth]},{type:"int32",data:[c.batchSize]},{type:"int32",data:[c.outChannels/c.inChannels]}];return a.runWebGPUProgram(p,[r,s],"float32",h)}var U0e={kernelName:vp,backendName:"webgpu",kernelFunc:V0e};function G0e(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:d}=n,c=I.computeConv2DInfo(d,s.shape,i,o,l,u,!0),p=new B0e(c),h=[{type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.filterHeight-1-c.padInfo.top,c.filterWidth-1-c.padInfo.left]},{type:"int32",data:[c.filterHeight,c.filterWidth]},{type:"int32",data:[c.outHeight]},{type:"int32",data:[c.outWidth]},{type:"int32",data:[c.outChannels/c.inChannels]}];return a.runWebGPUProgram(p,[r,s],r.dtype,h)}var H0e={kernelName:wp,backendName:"webgpu",kernelFunc:G0e},j0e=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="diag"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); let value = select(0.0, getX(coords[0]), coords[0] == coords[1]); setOutputAtIndex(index, value); } } `}};function q0e(e){let{inputs:t,backend:a}=e,{x:n}=t,r=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=ke({inputs:{x:n},backend:a,attrs:{shape:[s]}}),o=new j0e(s),l=a.runWebGPUProgram(o,[i],i.dtype),u=ke({inputs:{x:l},backend:a,attrs:{shape:r}});return a.disposeData(i.dataId),a.disposeData(l.dataId),u}var X0e={kernelName:vu,backendName:"webgpu",kernelFunc:q0e},K0e=class{constructor(e){this.variableNames=["x","w"],this.uniforms="filterDims: vec2, pads: vec2, strides: vec2, dilations: vec2",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="dilation2d"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let neg_infinity = -3.4e38; let coords = getOutputCoords(); let batch = coords.x; let d1 = coords.w; let outTopLeftCorner = coords.yz * uniforms.strides - uniforms.pads; let hBeg = outTopLeftCorner.x; let wBeg = outTopLeftCorner.y; var curVal = neg_infinity; for (var h = 0; h < uniforms.filterDims[0]; h = h + 1) { let hIn = hBeg + h * uniforms.dilations[0]; if (hIn >= 0 && hIn < uniforms.xShape[1]) { for (var w = 0; w < uniforms.filterDims[1]; w = w + 1) { let wIn = wBeg + w * uniforms.dilations[1]; if (wIn >= 0 && wIn < uniforms.xShape[2]) { let val = getX(batch, hIn, wIn, d1) + getW(h, w, d1); if (val > curVal) { curVal = val; } } } } } setOutputAtIndex(index, curVal); } } `}};function Y0e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=I.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),d=[u.padInfo.top,u.padInfo.left],c=[{type:"int32",data:[u.filterHeight,u.filterWidth]},{type:"int32",data:[...d]},{type:"int32",data:[u.strideHeight,u.strideWidth]},{type:"int32",data:[u.dilationHeight,u.dilationWidth]}],p=new K0e(u);return a.runWebGPUProgram(p,[r,s],r.dtype,c)}var Z0e={kernelName:so,backendName:"webgpu",kernelFunc:Y0e},J0e=class{constructor(e,t){if(this.variableNames=["x","w","dy"],this.uniforms="filterDims: vec2, pads: vec2, strides: vec2, dilations: vec2, dySize: i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e.inShape,this.dispatchLayout=me(e.outShape),this.dispatch=de(this.dispatchLayout,e.outShape,this.workgroupSize),t!=="float32"&&t!=="int32")throw new Error(`Dilation2DBackpropInput only supports float32 and int32 types, does not support ${t} type.`);this.type=t,this.shaderKey="dilation2DBackpropInput"}getUserCode(){return` ${ue("index")} { if (index < uniforms.dySize) { let coords = getDyCoordsFromIndex(index); let b = coords[0]; let r = coords[1]; let c = coords[2]; let d = coords[3]; let dyCorner = vec2(r, c) * uniforms.strides - uniforms.pads; var curVal = -3.4e38; // neg_infinity var xRMax = 0; var xCMax = 0; // In the case of multiple argmax branches, we only back-propagate // along the last branch, i.e., the one with largest value of // 'wR * uniforms.filterDims[1] + wC', similarly to the max-pooling // backward routines. for (var wR = 0; wR < uniforms.filterDims[0]; wR++) { let xR = dyCorner.x + wR * uniforms.dilations[0]; if (xR >= 0 && xR < uniforms.xShape[1]) { for (var wC = 0; wC < uniforms.filterDims[1]; wC++) { let xC = dyCorner.y + wC * uniforms.dilations[1]; if (xC >= 0 && xC < uniforms.xShape[2]) { let val = getX(b, xR, xC, d) + getW(wR, wC, d); if (val > curVal) { curVal = val; xRMax = xR; xCMax = xC; } } } } } let flatIndexIn = d + uniforms.xShape[3] * (xCMax + uniforms.xShape[2] * (xRMax + uniforms.xShape[1] * b)); let value = getDy(b, r, c, d); ${Bs("&result[flatIndexIn]","value",this.type)} } } `}},Q0e=class{constructor(e,t,a){if(this.variableNames=["x","w","dy"],this.uniforms="filterDims: vec2, pads: vec2, strides: vec2, dilations: vec2, dySize: i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e.filterShape,this.dispatchLayout=me(e.outShape),this.dispatch=de(this.dispatchLayout,e.outShape,this.workgroupSize),a!=="float32"&&a!=="int32")throw new Error(`Dilation2DBackpropFilter only supports float32 and int32 types, does not support ${a} type.`);this.type=a,this.shaderKey="dilation2DBackpropFilter"}getUserCode(){return` ${ue("index")} { if (index < uniforms.dySize) { let coords = getDyCoordsFromIndex(index); let b = coords[0]; let r = coords[1]; let c = coords[2]; let d = coords[3]; let dyCorner = vec2(r, c) * uniforms.strides - uniforms.pads; var curVal = -3.4e38; // neg_infinity var wRMax = 0; var wCMax = 0; // In the case of multiple argmax branches, we only back-propagate // along the last branch, i.e., the one with largest value of // 'wR * uniforms.filterDims[1] + wC', similarly to the max-pooling // backward routines. for (var wR = 0; wR < uniforms.filterDims[0]; wR++) { let xR = dyCorner.x + wR * uniforms.dilations[0]; if (xR >= 0 && xR < uniforms.xShape[1]) { for (var wC = 0; wC < uniforms.filterDims[1]; wC++) { let xC = dyCorner.y + wC * uniforms.dilations[1]; if (xC >= 0 && xC < uniforms.xShape[2]) { let val = getX(b, xR, xC, d) + getW(wR, wC, d); if (val > curVal) { curVal = val; wRMax = wR; wCMax = wC; } } } } } let flatIndexIn = d + uniforms.wShape[2] * (wCMax + wRMax * uniforms.wShape[1]); let value = getDy(b, r, c, d); ${Bs("&result[flatIndexIn]","value",this.type)} } } `}};function eme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n,d=I.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=s.dtype,p=new Q0e(d,s.shape,c),h=[{type:"int32",data:[d.filterHeight,d.filterWidth]},{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[v.sizeFromShape(d.outShape)]}],m=Wa({backend:a,attrs:{shape:s.shape,value:0,dtype:c}});return a.runWebGPUProgram(p,[r,s,i],c,h,m)}var tme={kernelName:Ql,backendName:"webgpu",kernelFunc:eme};function ame(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=n,d=I.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),c=r.dtype,p=new J0e(d,c),h=[{type:"int32",data:[d.filterHeight,d.filterWidth]},{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[v.sizeFromShape(d.outShape)]}],m=Wa({backend:a,attrs:{shape:d.inShape,value:0,dtype:c}});return a.runWebGPUProgram(p,[r,s,i],c,h,m)}var nme={kernelName:Jl,backendName:"webgpu",kernelFunc:ame},rme=class{constructor(e,t,a){this.variableNames=["Image"],this.uniforms="alpha: f32,",this.workgroupSize=[64,1,1],this.pixelsOpType=lu.DRAW,this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.type=t,this.textureFormat=a,this.shaderKey=`draw_${t}_${a}`}getUserCode(){let e,t=this.type==="float32"?"value":"value / 255.0";return e=` if (uniforms.numChannels == 1) { rgba[0] = ${t}; rgba[1] = ${t}; rgba[2] = ${t}; } else { rgba[d] = ${t}; }`,` @group(0) @binding(0) var outImage : texture_storage_2d<${this.textureFormat}, write>; ${ue("index")} { if (index < uniforms.size) { var rgba = vec4(0.0, 0.0, 0.0, uniforms.alpha); for (var d = 0; d < uniforms.numChannels; d = d + 1) { let value = f32(inBuf[index * uniforms.numChannels + d]); ${e} } rgba.x = rgba.x * rgba.w; rgba.y = rgba.y * rgba.w; rgba.z = rgba.z * rgba.w; let coords = getCoordsFromIndex(index); textureStore(outImage, vec2(coords.yx), rgba); } } `}};function sme(e){let{inputs:t,backend:a,attrs:n}=e,{image:r}=t,{canvas:s,options:i}=n,[o,l]=r.shape.slice(0,2),{imageOptions:u}=i||{},d=(u==null?void 0:u.alpha)||1,c=a.device.features.has("bgra8unorm-storage")?"bgra8unorm":"rgba8unorm",p=[o,l],h=new rme(p,r.dtype,c);s.width=l,s.height=o;let m="webgpu",f=s.getContext(m),g;f||(g=new OffscreenCanvas(l,o),f=g.getContext(m));let y=r.shape.length===3?r.shape[2]:1;f.configure({device:a.device,format:c,usage:GPUTextureUsage.STORAGE_BINDING,alphaMode:"premultiplied"});let x="int32",A=a.makeTensorInfo(p,x),b=a.tensorMap.get(A.dataId);b.resource=f.getCurrentTexture(),b.external=!0;let w=[{type:"uint32",data:[y]},{type:"float32",data:[d]}];if(a.runWebGPUProgram(h,[r],x,w,A),g){let S=s.getContext("2d");if(!S)throw new Error("Please make sure this canvas has only been used for 2d or webgpu context!");S.drawImage(g,0,0)}return a.disposeData(A.dataId),r}var ime={kernelName:kp,backendName:"webgpu",kernelFunc:sme},E9=aa({opType:De.MUL,cpuKernelImpl:pce,supportsComplex:!0}),ome={kernelName:Ts,backendName:"webgpu",kernelFunc:E9};function M9(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return gl(r,s,i,"sum",a)}var lme={kernelName:Qo,backendName:"webgpu",kernelFunc:M9};function ume(e){let{inputs:t,backend:a,attrs:n}=e,{equation:r}=n,s=t,{allDims:i,summedDims:o,idDims:l}=I.decodeEinsumEquation(r,s.length);I.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:d}=I.getEinsumComputePath(o,l),c=d.length,p=null,h=i.length,m=[];for(let f=0;f=0&&(p=M9({inputs:{x:p},backend:a,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(p)),h--)}for(let f of m)f!==p&&a.disposeData(f.dataId);return p}var dme={kernelName:Ip,backendName:"webgpu",kernelFunc:ume},pme=at({opType:le.ELU}),cme={kernelName:oo,backendName:"webgpu",kernelFunc:pme},hme=e=>{let{inputs:t,backend:a}=e,{dy:n,y:r}=t,s=new $h(De.ELU_DER,n.shape,r.shape);return a.runWebGPUProgram(s,[n,r],n.dtype)},mme={kernelName:wu,backendName:"webgpu",kernelFunc:hme},fme=aa({opType:De.EQUAL,dtype:"bool",cpuKernelImpl:Ype}),gme={kernelName:ms,backendName:"webgpu",kernelFunc:fme},yme=at({opType:le.ERF}),xme={kernelName:lo,backendName:"webgpu",kernelFunc:yme},Ame=at({opType:le.EXP,cpuKernelImpl:Zpe,dtype:"float32"}),bme={kernelName:fs,backendName:"webgpu",kernelFunc:Ame};function rg(e){let{inputs:t,attrs:a,backend:n}=e,{dim:r}=a,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),ke({inputs:{x:s},backend:n,attrs:{shape:o}})}var vme={kernelName:ku,backendName:"webgpu",kernelFunc:rg},wme=at({opType:le.EXPM1,cpuKernelImpl:Jpe}),kme={kernelName:gs,backendName:"webgpu",kernelFunc:wme},CA=class{constructor(e,t){this.variableNames=["real","imag"],this.outputShape=[],this.uniforms="exponentMultiplier : f32, denominator: f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.component=e,this.shaderKey=`fft_${e}`}getUserCode(){return` fn unaryOpComplex(real: f32, expR: f32, imag: f32, expI: f32) -> f32 { ${this.component==="real"?"return real * expR - imag * expI;":"return real * expI + imag * expR;"} } fn mulMatDFT(batch: i32, index: i32) -> f32 { let indexRatio = f32(index) / f32(uniforms.realShape[1]); let exponentMultiplierTimesIndexRatio = uniforms.exponentMultiplier * indexRatio; var result = 0.0; for (var i = 0; i < uniforms.realShape[1]; i = i + 1) { // x = (-2|2 * PI / N) * index * i; let x = exponentMultiplierTimesIndexRatio * f32(i); let expR = cos(x); let expI = sin(x); let real = getReal(batch, i); let imag = getImag(batch, i); result = result + unaryOpComplex(real, expR, imag, expI) / uniforms.denominator; } return result; } ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); setOutputAtIndex(index, mulMatDFT(coords[0], coords[1])); } } `}};function F9(e,t,a){let n=a.tensorMap.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=[],l=ke({inputs:{x:e},backend:a,attrs:{shape:[i,s]}});o.push(l);let u=l.shape,d=new CA("real",u),c=new CA("imag",u),p=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:u},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:u}],h=t?2*Math.PI:-2*Math.PI,m=t?u[1]:1,f=[{type:"float32",data:[h]},{type:"float32",data:[m]}],g=a.runWebGPUProgram(d,p,"float32",f);o.push(g);let y=a.runWebGPUProgram(c,p,"float32",f);o.push(y);let x=fl({inputs:{real:g,imag:y},backend:a});o.push(x);let A=ke({inputs:{x},backend:a,attrs:{shape:e.shape}});return o.forEach(b=>a.disposeData(b.dataId)),A}function Ime(e){let{inputs:t,backend:a}=e,{input:n}=t;return F9(n,!1,a)}var Sme={kernelName:Sp,backendName:"webgpu",kernelFunc:Ime},Tme=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let coordX = uniforms.xShape[2] - coords[2] - 1; let outputValue = getX(coords[0], coords[1], coordX, coords[3]); setOutputAtIndex(index, outputValue); } } `}},Cme={kernelName:uo,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:a}=e,n=t,r=new Tme(a.shape);return n.runWebGPUProgram(r,[a],a.dtype)}},Nme=at({opType:le.FLOOR,cpuKernelImpl:Qpe}),Rme={kernelName:ys,backendName:"webgpu",kernelFunc:Nme},Eme=aa({opType:De.FLOOR_DIV,cpuKernelImpl:ece,dtype:"int32"}),Mme={kernelName:xs,backendName:"webgpu",kernelFunc:Eme},Fme=class{constructor(e,t,a=!1){this.pixelsOpType=lu.FROM_PIXELS,this.outputShape=[0],this.variableNames=[],this.workgroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[t,1,1]),this.importVideo=a,this.shaderKey=`fromPixels_${this.importVideo}`}getUserCode(){let e=this.importVideo?"textureLoad(src, vec2(coords.yx));":"textureLoad(src, vec2(coords.yx), 0)";return` @binding(1) @group(0) var src: ${this.importVideo?"texture_external":"texture_2d"}; ${ue("index")} { let flatIndex = index * uniforms.numChannels; if (flatIndex < uniforms.size) { let coords = getCoordsFromIndex(flatIndex); let values = ${e}; for (var i = 0; i < uniforms.numChannels; i = i + 1) { result[flatIndex + i] = i32(floor(255.0 * values[i])); } } } `}},$me={kernelName:jd,backendName:"webgpu",kernelFunc:Dme},Vl,i1=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function Dme(e){let{inputs:t,backend:a,attrs:n}=e,{pixels:r}=t,{numChannels:s}=n;if(r==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,l=typeof HTMLCanvasElement!="undefined"&&r instanceof HTMLCanvasElement||typeof OffscreenCanvas!="undefined"&&r instanceof OffscreenCanvas,u=typeof ImageBitmap!="undefined"&&r instanceof ImageBitmap,[d,c]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],p=[c,d,s],h=B().getBool("WEBGPU_IMPORT_EXTERNAL_TEXTURE")&&i,m=i||o;if(u||l||m){let x;if(h)x=a.device.importExternalTexture({source:r});else{if(m){let T=B().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Vl==null||T!==i1)&&(i1=T,Vl=document.createElement("canvas").getContext("2d",{willReadFrequently:i1})),Vl.canvas.width=d,Vl.canvas.height=c,Vl.drawImage(r,0,0,d,c),r=Vl.canvas}let F=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,E=a.textureManager.acquireTexture(p[1],p[0],"rgba8unorm",F);a.queue.copyExternalImageToTexture({source:r},{texture:E},[p[1],p[0]]),x=E}let A=v.sizeFromShape(p),b=v.computeStrides(p),w=new Fme(p,s,h),S=[{type:"uint32",data:[A]},{type:"uint32",data:[s]},{type:"uint32",data:[...b]}],C=a.makeTensorInfo([c,d],"int32"),N=a.tensorMap.get(C.dataId);N.resource=x;let M=a.runWebGPUProgram(w,[C],"int32",S);return a.disposeData(C.dataId),M}let f=r.data,g=f;if(s!=null&&s!==4){g=new Uint8Array(r.width*r.height*s);let x=f.length,A=0;for(let b=0;b(xValue, -meanValue, offsetValue), vec3(inv, inv, 1.0))); } } `}},_me={kernelName:po,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n,scale:r,offset:s,mean:i,variance:o}=e,{varianceEpsilon:l}=t,u=a,d=[n,i,o],c=null;s!=null&&(c=s.shape,d.push(s));let p=null;r!=null&&(p=r.shape,d.push(r));let h=new Pme(n.shape,i.shape,o.shape,c,p),m=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,d,n.dtype,m)}};function Ome(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:d,dilations:c,dimRoundingMode:p,activation:h,leakyreluAlpha:m}=n,f=I.convertConv2DDataFormat(d),g=I.computeConv2DInfo(r.shape,s.shape,l,c,u,p,!1,f);return T9({x:r,filter:s,convInfo:g,backend:a,bias:i,preluActivationWeights:o,leakyreluAlpha:m,activation:h})}var zme={kernelName:as,backendName:"webgpu",kernelFunc:Ome};function Lme(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:d,dimRoundingMode:c,activation:p,leakyreluAlpha:h}=n,m=d;m==null&&(m=[1,1]),v.assert(I.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let f=I.computeConv2DInfo(r.shape,s.shape,l,m,u,c,!0),g=[r,s],y=i!=null,x=o!=null;y&&g.push(i),x&&g.push(o);let A=[{type:"int32",data:[f.padInfo.top,f.padInfo.left]},{type:"int32",data:[f.inHeight,f.inWidth]}],b;return f.outHeight>4&&f.outWidth>4&&f.strideWidth<=2&&f.inChannels===f.outChannels&&f.dilationHeight===1&&f.dilationWidth===1&&f.inChannels%4===0?(b=new N9(f,y,p,x),A.push({type:"int32",data:[b.virtualWidth]})):(b=new R9(f,y,p,x),A.push({type:"int32",data:[f.filterHeight]},{type:"int32",data:[f.filterWidth]},{type:"int32",data:[f.strideHeight,f.strideWidth]},{type:"int32",data:[f.dilationHeight,f.dilationWidth]})),p==="leakyrelu"&&(A.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),a.runWebGPUProgram(b,g,"float32",A)}var Wme={kernelName:ns,backendName:"webgpu",kernelFunc:Lme},Bme=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Dt(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); var flattenIndex = 0; for (var j = 0; j < uniforms.sliceDim; j = j + 1) { let indexTemp = i32(round(getIndices(coords[0], j))); let strideNum = ${e}; flattenIndex = flattenIndex + indexTemp * strideNum; } setOutputAtIndex(index, getA(flattenIndex, coords[1])); } } `}};function Vme(e){let{inputs:t,backend:a}=e,{params:n,indices:r}=t,s=r.shape,i=s[s.length-1],o=v.sizeFromShape(n.shape),[l,u,d,c]=I.prepareAndValidate(n,r),p=ke({inputs:{x:r},backend:a,attrs:{shape:[u,i]}}),h=ke({inputs:{x:n},backend:a,attrs:{shape:[v.sizeFromShape(n.shape)/d,d]}});if(a.shouldExecuteOnCPU([n,r])||n.dtype==="string"){let x=a.readSync(r.dataId),A=a.bufferSync(n),b=tce(x,A,n.dtype,u,i,d,c,n.shape,o);return a.makeTensorInfo(l,n.dtype,b.values)}let m=new Bme(i,[u,d]),f=[{type:"int32",data:[i]},{type:"int32",data:c}],g=a.runWebGPUProgram(m,[h,p],h.dtype,f),y=ke({inputs:{x:g},backend:a,attrs:{shape:l}});return a.disposeData(p.dataId),a.disposeData(h.dataId),a.disposeData(g.dataId),y}var Ume={kernelName:co,backendName:"webgpu",kernelFunc:Vme},Gme=class{constructor(e,t){this.variableNames=["A","indices"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.slice(),this.aShape=e,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="gather"}getUserCode(){let e=Hme(this.aShape);return` ${ue("index")} { if (index < uniforms.size) { let resRC = getCoordsFromIndex(index); let indexZ = i32(getIndices(resRC.x, resRC.z)); let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]); setOutputAtIndex(index, inBounds * getA(${e})); } } `}};function Hme(e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[];for(let n=0;na.disposeData(C.dataId)),a.makeTensorInfo(u.outputShape,S.dtype,S.values)}let f=new Gme(p.shape,m),g=a.runWebGPUProgram(f,[p,h],p.dtype);c.push(g);let y=ke({inputs:{x:g},backend:a,attrs:{shape:u.outputShape}});return c.forEach(x=>a.disposeData(x.dataId)),y}var jme={kernelName:Su,backendName:"webgpu",kernelFunc:$9},qme=aa({opType:De.GREATER,cpuKernelImpl:rce,dtype:"bool"}),Xme={kernelName:As,backendName:"webgpu",kernelFunc:qme},Kme=aa({opType:De.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:nce}),Yme={kernelName:bs,backendName:"webgpu",kernelFunc:Kme};function Zme(e){let{inputs:t,backend:a}=e,{input:n}=t;return F9(n,!0,a)}var Jme={kernelName:Tp,backendName:"webgpu",kernelFunc:Zme},Qme=at({opType:le.IS_FINITE,dtype:"bool"}),efe={kernelName:mo,backendName:"webgpu",kernelFunc:Qme},tfe=at({opType:le.IS_INF,dtype:"bool"}),afe={kernelName:fo,backendName:"webgpu",kernelFunc:tfe},nfe=at({opType:le.IS_NAN,dtype:"bool"}),rfe={kernelName:go,backendName:"webgpu",kernelFunc:nfe};function sfe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{alpha:s}=n,i=[{type:"float32",data:[s]}],o=new id(r.shape,le.LEAKYRELU,"alpha : f32,");return a.runWebGPUProgram(o,[r],"float32",i)}var ife={kernelName:yo,backendName:"webgpu",kernelFunc:sfe},ofe=aa({opType:De.LESS,dtype:"bool",cpuKernelImpl:ice}),lfe={kernelName:vs,backendName:"webgpu",kernelFunc:ofe},ufe=aa({opType:De.LESS_EQUAL,dtype:"bool",cpuKernelImpl:sce}),dfe={kernelName:ws,backendName:"webgpu",kernelFunc:ufe},pfe=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="start : f32, step : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="linSpace"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { setOutputAtIndex(index, uniforms.start + f32(index) * uniforms.step); } } `}};function cfe(e){let{backend:t,attrs:a}=e,{start:n,stop:r,num:s}=a,i=(r-n)/(s-1),o=new pfe(s),l=[{type:"float32",data:[n]},{type:"float32",data:[i]}];return t.runWebGPUProgram(o,[],"float32",l)}var hfe={kernelName:xo,backendName:"webgpu",kernelFunc:cfe},mfe=at({opType:le.LOG,cpuKernelImpl:oce}),ffe={kernelName:ks,backendName:"webgpu",kernelFunc:mfe},gfe=at({opType:le.LOG1P}),yfe={kernelName:Ao,backendName:"webgpu",kernelFunc:gfe},xfe=aa({opType:De.LOGICAL_AND,dtype:"bool"}),Afe={kernelName:bo,backendName:"webgpu",kernelFunc:xfe},bfe=at({opType:le.LOGICAL_NOT}),vfe={kernelName:vo,backendName:"webgpu",kernelFunc:bfe},wfe=aa({opType:De.LOGICAL_OR}),kfe={kernelName:wo,backendName:"webgpu",kernelFunc:wfe},D9=` var powValue = 0.0; let basis = uniforms.bias + uniforms.alpha * sum; if (uniforms.beta == 0.5) { powValue = inverseSqrt(basis); } else if (uniforms.beta == 1.0) { powValue = 1.0 / basis; } else { powValue = exp(log(basis) * (-uniforms.beta)); } `,Ife=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.uniforms="radius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="lrn"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); let b = coords[0]; let r = coords[1]; let c = coords[2]; let d = coords[3]; let x = getX(b, r, c, d); var sum = 0.0; for (var i = -uniforms.radius; i <= uniforms.radius; i = i + 1) { let idx = d + i; if (idx >= 0 && idx < uniforms.xShape[3]) { let z = getX(b, r, c, idx); sum = sum + z * z; } } ${D9} setOutputAtIndex(index, x * powValue); } } `}},Sfe=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.uniforms="radius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[256,1,1],this.maxAllowRadius=16,v.assert(t<=this.maxAllowRadius,()=>`Radius must be less than or equal to ${this.maxAllowRadius}, current radius is ${t}`),this.outputShape=e,this.elementsPerWorkgroup=this.workgroupSize[0]-2*this.maxAllowRadius,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=de(this.dispatchLayout,this.outputShape,[this.elementsPerWorkgroup,this.workgroupSize[1],this.workgroupSize[2]]),this.shaderKey="lrn_shared"}getUserCode(){return` var lrnSub: array; const elementsPerWorkgroup = ${this.elementsPerWorkgroup}; const maxAllowRadius = ${this.maxAllowRadius}; ${ue()} { let localDepth = i32(localId.x); let workgroupDepth = i32(workgroupId.x) * elementsPerWorkgroup; let xDepth = workgroupDepth + localDepth - maxAllowRadius; let b = i32(globalId.z) / uniforms.xShape[1]; let r = i32(globalId.z) - b * uniforms.xShape[1]; let c = i32(globalId.y); let d = workgroupDepth + localDepth; var x = 0.0; if (xDepth >= 0 && xDepth < uniforms.xShape[3]) { x = getX(b, r, c, xDepth); } lrnSub[localDepth] = x; workgroupBarrier(); if (localDepth < elementsPerWorkgroup && d < uniforms.outShape[3]) { var sum = 0.0; let index = localDepth + maxAllowRadius; for (var i = -uniforms.radius; i <= uniforms.radius; i = i + 1) { let z = lrnSub[index + i]; sum = sum + z * z; } ${D9} setOutputAtCoords(b, r, c, d, lrnSub[index] * powValue); } } `}};function Tfe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u;s>16?u=new Ife(r.shape):u=new Sfe(r.shape,s);let d=[{type:"int32",data:[s]},{type:"float32",data:[i]},{type:"float32",data:[o]},{type:"float32",data:[l]}];return a.runWebGPUProgram(u,[r],r.dtype,d)}var Cfe={kernelName:ko,backendName:"webgpu",kernelFunc:Tfe},Nfe=class{constructor(e){this.outputShape=[],this.variableNames=["inputImage","outputImage","dy"],this.uniforms="depthRadius : i32, bias : f32, alpha : f32, beta : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="lrn_grad"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); let b = coords[0]; let r = coords[1]; let c = coords[2]; let MIN_DEPTH_BEGIN = 0; let MAX_DEPTH_END = uniforms.outShape[3]; var result = 0.0; for (var d = MIN_DEPTH_BEGIN; d < MAX_DEPTH_END; d++) { let depthBegin = max(MIN_DEPTH_BEGIN, d - uniforms.depthRadius); let depthEnd = min(MAX_DEPTH_END, d + uniforms.depthRadius + 1); var norm = 0.0; for (var 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 = uniforms.alpha * norm + uniforms.bias; for (var k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; k++) { if (k < depthBegin) { continue; } else if (k >= depthBegin && k < depthEnd) { var dyi = -2.0 * uniforms.alpha * uniforms.beta * getInputImage(b, r, c, k) * getOutputImage(b, r, c, d) / norm; if (k == d) { dyi += pow(norm, -1.0 * uniforms.beta); } if (k == coords[3]) { dyi *= getDy(b, r, c, d); result += dyi; } } else { break; } } } setOutputAtIndex(index, result); } } `}};function Rfe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:d}=n,c=new Nfe(r.shape),p=[{type:"int32",data:[o]},{type:"float32",data:[l]},{type:"float32",data:[u]},{type:"float32",data:[d]}];return a.runWebGPUProgram(c,[r,s,i],r.dtype,p)}var Efe={kernelName:Tu,backendName:"webgpu",kernelFunc:Rfe},Mfe=aa({opType:De.MAX,cpuKernelImpl:uce}),Ffe={kernelName:Is,backendName:"webgpu",kernelFunc:Mfe};function $fe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=I.computePool2DInfo(r.shape,s,i,1,o,l);return w9(r,u,"max",a)}var Dfe={kernelName:So,backendName:"webgpu",kernelFunc:$fe};function Pfe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=n,d=[1,1,1],c=I.computePool3DInfo(r.shape,s,i,d,o,u,l),p=new uy(c,"max"),h=[{type:"int32",data:[c.strideDepth,c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.front,c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.inDepth,c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterDepth,c.effectiveFilterHeight,c.effectiveFilterWidth]}];return a.runWebGPUProgram(p,[r],r.dtype,h)}var _fe={kernelName:Cu,backendName:"webgpu",kernelFunc:Pfe},Ofe=class{constructor(e){this.variableNames=["dy","maxPos"],this.uniforms=`strides : vec2, pads : vec2, dilations : vec2, filterDims : vec2, outHeight : i32, outWidth : i32`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="maxPool2DBackprop"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords[0]; let d = coords[3]; let dyRCCorner = vec2(coords.yz) - uniforms.pads; let dyRCorner = dyRCCorner.x; let 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. var dotProd = 0.0; let lastIndex = uniforms.filterDims[0] * uniforms.filterDims[1] - 1; for (var wR = 0; wR < uniforms.filterDims[0]; wR += uniforms.dilations[0]) { let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[0]); if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) { continue; } let idyR = i32(dyR); for (var wC = 0; wC < uniforms.filterDims[1]; wC += uniforms.dilations[1]) { let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[1]); if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) { continue; } let idyC = i32(dyC); let dyValue = getDy(batch, idyR, idyC, d); let maxPosValue = lastIndex - i32(getMaxPos(batch, idyR, idyC, d)); // Get the current value, check it against the value from the // position matrix. let curPosValue = wR * uniforms.filterDims[1] + wC; let mask = select(0.0, 1.0, maxPosValue == curPosValue); dotProd += dyValue * mask; } } setOutputAtIndex(index, dotProd); } } `}},zfe=class{constructor(e){this.variableNames=["dy","maxPos"],this.uniforms=`strides : vec3, pads : vec3, filterDims : vec3, outDepth : i32, outHeight : i32, outWidth : i32`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="maxPool3DBackprop"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let batch = coords.x; let ch = coords.u; let dyCorner = vec3(coords.y, coords.z, coords.w) - uniforms.pads; let dyDCorner = dyCorner.x; let dyRCorner = dyCorner.y; let 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. var dotProd = 0.0; let lastIndex = uniforms.filterDims[0] * uniforms.filterDims[1] * uniforms.filterDims[2] - 1; for (var wD = 0; wD < uniforms.filterDims[0]; wD++) { let dyD = f32(dyDCorner + wD) / f32(uniforms.strides[0]); if (dyD < 0.0 || dyD >= f32(uniforms.outDepth) || fract(dyD) > 0.0) { continue; } let idyD = i32(dyD); for (var wR = 0; wR < uniforms.filterDims[1]; wR++) { let dyR = f32(dyRCorner + wR) / f32(uniforms.strides[1]); if (dyR < 0.0 || dyR >= f32(uniforms.outHeight) || fract(dyR) > 0.0) { continue; } let idyR = i32(dyR); for (var wC = 0; wC < uniforms.filterDims[2]; wC++) { let dyC = f32(dyCCorner + wC) / f32(uniforms.strides[2]); if (dyC < 0.0 || dyC >= f32(uniforms.outWidth) || fract(dyC) > 0.0) { continue; } let idyC = i32(dyC); let dyValue = getDy(batch, idyD, idyR, idyC, ch); let maxPosValue = lastIndex - i32(getMaxPos(batch, idyD, idyR, idyC, ch)); // Get the current value, check it against the value from the // position matrix. let curPosValue = wD * uniforms.filterDims[1] * uniforms.filterDims[2] + wR * uniforms.filterDims[2] + wC; let mask = select(0.0, 1.0, maxPosValue == curPosValue); dotProd += dyValue * mask; } } } setOutputAtIndex(index, dotProd); } } `}};function Lfe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:d}=n,c=[1,1,1],p=I.computePool3DInfo(i.shape,o,l,c,u,d),h=new uy(p,"max",!0),m=[{type:"int32",data:[p.strideDepth,p.strideHeight,p.strideWidth]},{type:"int32",data:[p.padInfo.front,p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.inDepth,p.inHeight,p.inWidth]},{type:"int32",data:[p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth]}],f=a.runWebGPUProgram(h,[i],"int32",m),g=new zfe(p);m=[{type:"int32",data:[p.strideDepth,p.strideHeight,p.strideWidth]},{type:"int32",data:[p.effectiveFilterDepth-1-p.padInfo.front,p.effectiveFilterHeight-1-p.padInfo.top,p.effectiveFilterWidth-1-p.padInfo.left]},{type:"int32",data:[p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth]},{type:"int32",data:[p.outDepth]},{type:"int32",data:[p.outHeight]},{type:"int32",data:[p.outWidth]}];let y=a.runWebGPUProgram(g,[r,f],i.dtype,m);return a.disposeData(f.dataId),y}var Wfe={kernelName:Rp,backendName:"webgpu",kernelFunc:Lfe};function Bfe(e){let{inputs:t,backend:a,attrs:n}=e,{dy:r,input:s,output:i}=t,o=s;ay([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:d,dimRoundingMode:c}=n,p=I.computePool2DInfo(o.shape,l,u,1,d,c),h=new pp(p,"max",!0),m=[{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.padInfo.top,p.padInfo.left]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[p.inHeight,p.inWidth]},{type:"int32",data:[p.effectiveFilterHeight,p.effectiveFilterWidth]}],f=a.runWebGPUProgram(h,[o],"int32",m),g=new Ofe(p);m=[{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.effectiveFilterHeight-1-p.padInfo.top,p.effectiveFilterWidth-1-p.padInfo.left]},{type:"int32",data:[p.dilationHeight,p.dilationWidth]},{type:"int32",data:[p.effectiveFilterHeight,p.effectiveFilterWidth]},{type:"int32",data:[p.outHeight]},{type:"int32",data:[p.outWidth]}];let y=a.runWebGPUProgram(g,[r,f],o.dtype,m);return a.disposeData(f.dataId),y}var Vfe={kernelName:Np,backendName:"webgpu",kernelFunc:Bfe};function Ufe(e){let{inputs:t,backend:a,attrs:n}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=n,{x:l}=t;v.assert(l.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${l.shape.length}.`);let u=[1,1];v.assert(I.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let d=I.computePool2DInfo(l.shape,r,s,u,i),c=[{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[d.inHeight,d.inWidth]},{type:"int32",data:[d.effectiveFilterHeight,d.effectiveFilterWidth]}],p=new pp(d,"max",!1),h=a.runWebGPUProgram(p,[l],l.dtype,c);p=new pp(d,"max",!0,!0,o);let m=a.runWebGPUProgram(p,[l],"int32",c);return[h,m]}var Gfe={kernelName:Nu,backendName:"webgpu",kernelFunc:Ufe};function Hfe(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return gl(r,s,i,"min",a)}var jfe={kernelName:Co,backendName:"webgpu",kernelFunc:Hfe},qfe=aa({opType:De.MIN,cpuKernelImpl:dce}),Xfe={kernelName:Ss,backendName:"webgpu",kernelFunc:qfe},Kfe=class{constructor(e,t,a){this.uniforms="",this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,r)=>n[0]+e[r]+n[1]),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.xShape=e,t.map((n,r)=>{this.uniforms+=` pad${r} : vec2,`}),this.offset=a==="reflect"?0:1,this.shaderKey=`mirrorPad_${a}`}getUserCode(){let e=this.xShape.length,t=this.xShape.map((l,u)=>`uniforms.pad${u}[0]`).join(","),a=this.xShape.map((l,u)=>`uniforms.pad${u}[0] + uniforms.xShape${e>1?`[${u}]`:""}`).join(","),n=e===1?"start":"start[i]",r=e===1?"end":"end[i]",s=e===1?"outC":"outC[i]",i=Dt(e),o=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return` ${ue("index")} { if (index < uniforms.size) { let start = ${i}(${t}); let end = ${i}(${a}); var outC = getCoordsFromIndex(index); for (var i = 0; i < ${e}; i = i + 1) { if (${s} < ${n}) { ${s} = ${n} * 2 - ${s} - ${this.offset}; } else if(${s} >= ${r}) { ${s} = (${r} - 1) * 2 - ${s} + ${this.offset}; } } let coords = outC - start; setOutputAtIndex(index, getX(${o})); } } `}},Yfe={kernelName:No,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{x:n}=e,{paddings:r,mode:s}=t,i=a,o=r.map(u=>({type:"int32",data:[u[0],u[1]]})),l=new Kfe(n.shape,r,s);return i.runWebGPUProgram(l,[n],n.dtype,o)}},Zfe=aa({opType:De.MOD}),Jfe={kernelName:Ro,backendName:"webgpu",kernelFunc:Zfe},Qfe=class{constructor(e,t){this.variableNames=["probs"],this.outputShape=[],this.uniforms="seed : f32, numOutcomes: i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,t],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="multinomial"}getUserCode(){return` //Based on the work of Dave Hoskins //https://www.shadertoy.com/view/4djSRW fn random (seed : f32, resultUV : vec2) -> f32 { let HASHSCALE1 = 443.8975; let p = resultUV * seed; var p3 = fract(vec3(p.xyx) * HASHSCALE1); p3 = p3 + dot(p3, p3.yzx + 19.19); return fract((p3.x + p3.y) * p3.z); } ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); let batch = coords[0]; let resUV = vec2(f32(coords[1]) / f32(uniforms.outShape[1]), f32(coords[0]) / f32(uniforms.outShape[0])); let r = random(uniforms.seed, resUV); var cdf = 0.0; for (var i = 0; i < uniforms.numOutcomes - 1; i = i + 1) { cdf = cdf + getProbs(batch, i); if (r < cdf) { setOutputAtIndexI32(index, i); return; } } // If no other event happened, last event happened. setOutputAtIndexI32(index, uniforms.numOutcomes - 1); } } `}},e2e=class{constructor(e){this.variableNames=["logits"],this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=[this.outputShape[0],1,1],this.outputShape[1]>=4096?this.workgroupSize=[256,1,1]:this.workgroupSize=[64,1,1],this.shaderKey="softmax"}getUserCode(){return` var buf : array; var rowMaxShared : f32; var rowSumShared : f32; const blockSize = ${this.workgroupSize[0]}; ${ue("index")} { let row = index / blockSize; let tid = i32(localId.x); let cols = uniforms.outShape[1]; var threadMax = -3.402823e+38f; for (var col = tid; col < cols; col += blockSize) { let value = getLogits(row, col); threadMax = max(threadMax, value); } if (tid < cols) { buf[tid] = threadMax; } workgroupBarrier(); var reduceSize = min(cols, blockSize); for (var currSize = reduceSize >> 1; currSize > 0; currSize = reduceSize >> 1) { reduceSize = currSize + (reduceSize & 1); if (tid < currSize) { buf[tid] = max(buf[tid], buf[tid + reduceSize]); } workgroupBarrier(); } if (tid == 0) { rowMaxShared = buf[0]; } workgroupBarrier(); var threadSum = 0.0; for (var col = tid; col < cols; col += blockSize) { let subExp = exp(getLogits(row, col) - rowMaxShared); threadSum += subExp; } buf[tid] = threadSum; workgroupBarrier(); for (var currSize = blockSize >> 1; currSize > 0; currSize = currSize >> 1) { if (tid < currSize) { buf[tid] = buf[tid] + buf[tid + currSize]; } workgroupBarrier(); } if (tid == 0) { rowSumShared = buf[0]; } workgroupBarrier(); for (var col = tid; col < cols; col += blockSize) { let value = exp(getLogits(row, col) - rowMaxShared) / rowSumShared; setOutputAtCoords(row, col, value); } } `}};function P9(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{dim:s}=n,i=ke({inputs:{x:r},backend:a,attrs:{shape:[v.sizeFromShape(r.shape)/r.shape[s],r.shape[s]]}}),o=new e2e(i.shape),l=a.runWebGPUProgram(o,[i],r.dtype),u=ke({inputs:{x:l},backend:a,attrs:{shape:r.shape}});return a.disposeData(i.dataId),a.disposeData(l.dataId),u}var t2e={kernelName:el,backendName:"webgpu",kernelFunc:P9};function a2e(e){let{inputs:t,backend:a,attrs:n}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?r:P9({inputs:{logits:r},backend:a,attrs:{dim:r.shape.length-1}}),u=l.shape[0],d=l.shape[1],c=new Qfe(u,s),p=[{type:"float32",data:[i]},{type:"int32",data:[d]}],h=a.runWebGPUProgram(c,[l],"int32",p);return o||a.disposeData(l.dataId),h}var n2e={kernelName:Eo,backendName:"webgpu",kernelFunc:a2e};function r2e(e){let{inputs:t,backend:a}=e,{x:n}=t;if(a.shouldExecuteOnCPU([n])){let s=a.tensorMap.get(n.dataId),[i,o]=cce(s.values,n.shape,n.dtype);return a.makeTensorInfo(o,n.dtype,i)}let r=new id(n.shape,le.NEG);return a.runWebGPUProgram(r,[n],n.dtype)}var s2e={kernelName:Ru,backendName:"webgpu",kernelFunc:r2e};function i2e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,u=a.readSync(r.dataId),d=a.readSync(s.dataId),{selectedIndices:c}=Fn.nonMaxSuppressionV3Impl(u,d,i,o,l);return a.makeTensorInfo([c.length],"int32",new Int32Array(c))}var o2e={kernelName:Mo,backendName:"webgpu",kernelFunc:i2e};function l2e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:a,attrs:n}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n,d=a.readSync(r.dataId),c=a.readSync(s.dataId),p=i,h=o,m=l,f=u,{selectedIndices:g,selectedScores:y}=Fn.nonMaxSuppressionV5Impl(d,c,p,h,m,f);return[a.makeTensorInfo([g.length],"int32",new Int32Array(g)),a.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var u2e={kernelName:Fo,backendName:"webgpu",kernelFunc:l2e},d2e=class{constructor(e,t){this.variableNames=["x"],this.uniforms="onValue : f32, offValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e,t],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="onehot"}getUserCode(){return` ${ue("index")} { if(index < uniforms.size) { let coords = getCoordsFromIndex(index); setOutputAtIndex(index, mix(uniforms.offValue, uniforms.onValue, f32(i32(round(getX(coords.x))) == coords.y))); } } `}};function p2e(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=n,u=v.sizeFromShape(r.shape),d=new d2e(u,i),c=ke({inputs:{x:r},backend:a,attrs:{shape:[u]}}),p=[{type:"float32",data:[o]},{type:"float32",data:[l]}],h=a.runWebGPUProgram(d,[c],s,p);a.disposeData(c.dataId);let m=[...r.shape,i],f=ke({inputs:{x:h},backend:a,attrs:{shape:m}});return a.disposeData(h.dataId),f}var c2e={kernelName:$o,backendName:"webgpu",kernelFunc:p2e};function _h(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="complex64"){let r=oc({inputs:{input:n},backend:a}),s=_h({inputs:{x:r},backend:a}),i=A0({inputs:{input:n},backend:a}),o=_h({inputs:{x:i},backend:a}),l=fl({inputs:{real:s,imag:o},backend:a});return a.disposeData(r.dataId),a.disposeData(s.dataId),a.disposeData(i.dataId),a.disposeData(o.dataId),l}else return Wa({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:a})}var h2e={kernelName:qu,backendName:"webgpu",kernelFunc:_h};function _9(e){let{inputs:t,backend:a}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let r=oc({inputs:{input:n},backend:a}),s=_9({inputs:{x:r},backend:a}),i=A0({inputs:{input:n},backend:a}),o=_h({inputs:{x:i},backend:a}),l=fl({inputs:{real:s,imag:o},backend:a});return a.disposeData(r.dataId),a.disposeData(s.dataId),a.disposeData(i.dataId),a.disposeData(o.dataId),l}else return Wa({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:a})}var m2e={kernelName:Mu,backendName:"webgpu",kernelFunc:_9};function f2e(e){let{inputs:t,backend:a,attrs:n}=e,{axis:r}=n;if(t.length===1)return rg({inputs:{input:t[0]},backend:a,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(d=>{v.assertShapesMatch(s,d.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===d.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(d=>{let c=rg({inputs:{input:d},backend:a,attrs:{dim:r}});return o.push(c),c}),u=S9({inputs:l,backend:a,attrs:{axis:r}});return o.forEach(d=>a.disposeData(d.dataId)),u}var g2e={kernelName:Fu,backendName:"webgpu",kernelFunc:f2e};function O9(e,t=!1){let a=e.length,n=Dt(a),r=e.map((c,p)=>`uniforms.pad${p}[0]`).join(","),s=e.map((c,p)=>`uniforms.pad${p}[0] + uniforms.xShape${a>1?`[${p}]`:""}`).join(","),i=a>1?`${n}(${r})`:`${r}`,o=a>1?`${n}(${s})`:`${s}`,l=a>1?"any(paddedCoords < start)":"paddedCoords < start",u=a>1?"any(paddedCoords >= end)":"paddedCoords >= end",d=a>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a):"coords";return` let start = ${i}; let end = ${o}; if (${l} || ${u}) { setOutputAtIndex(index, ${t?0:"uniforms.constantValue"}); } else { let coords = paddedCoords - start; setOutputAtIndex(index, getX(${d})); } `}var y2e=class{constructor(e,t){this.variableNames=["x"],this.uniforms="constantValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((a,n)=>a[0]+e[n]+a[1]),this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),t.map((a,n)=>{this.uniforms+=` pad${n} : vec2,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let paddedCoords = getCoordsFromIndex(index); ${O9(this.xShape)} } } `}},x2e=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{paddings:s,constantValue:i}=n;if(s.every(u=>v.arraysEqual(u,[0,0])))return an({inputs:{x:r},backend:a});if(v.sizeFromShape(r.shape)===0){let u=s.map((d,c)=>d[0]+r.shape[c]+d[1]);return Wa({backend:a,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=[{type:"float32",data:[i]}];s.map(u=>o.push({type:"int32",data:[u[0],u[1]]}));let l=new y2e(r.shape,s);return a.runWebGPUProgram(l,[r],r.dtype,o)},A2e={kernelName:Do,backendName:"webgpu",kernelFunc:x2e},b2e=aa({opType:De.POW}),v2e={kernelName:Po,backendName:"webgpu",kernelFunc:b2e};function w2e(e){let{inputs:t,backend:a}=e,{x:n,alpha:r}=t,s=new $h(De.PRELU,n.shape,r.shape);return a.runWebGPUProgram(s,[n,r],"float32")}var k2e={kernelName:_o,backendName:"webgpu",kernelFunc:w2e};function I2e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{axis:s,keepDims:i}=n;return gl(r,s,i,"prod",a)}var S2e={kernelName:Oo,backendName:"webgpu",kernelFunc:I2e},T2e=e=>{let{backend:t,attrs:a}=e,{start:n,stop:r,step:s,dtype:i}=a,o=fce(n,r,s,i);return t.makeTensorInfo([o.length],i,o)},C2e={kernelName:$u,backendName:"webgpu",kernelFunc:T2e},N2e=aa({opType:De.DIV}),R2e={kernelName:io,backendName:"webgpu",kernelFunc:N2e},E2e=at({opType:le.RECIPROCAL}),M2e={kernelName:zo,backendName:"webgpu",kernelFunc:E2e},F2e=at({opType:le.RELU}),$2e={kernelName:Lo,backendName:"webgpu",kernelFunc:F2e},D2e=at({opType:le.RELU6}),P2e={kernelName:Vo,backendName:"webgpu",kernelFunc:D2e},_2e=class{constructor(e,t,a){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2, halfPixelCenters : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,a,e[3]],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let b = coords[0]; let d = coords[3]; let rc = coords.yz; let effectiveInSize = vec2( f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0], f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]); let effectiveOutSize = vec2( f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0], f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]); let effectiveInputOverOutputRatioRC = effectiveInSize / effectiveOutSize; // Fractional source index let sourceFracIndexRC = (vec2(rc) + vec2(uniforms.halfPixelCenters)) * effectiveInputOverOutputRatioRC - vec2(uniforms.halfPixelCenters); // Compute the four integer indices. let sourceFloorRC = vec2(sourceFracIndexRC); let sourceCeilRC = vec2( min(vec2(uniforms.xShape.yz) - vec2(1.0), ceil(sourceFracIndexRC))); let topLeft = getX(b, sourceFloorRC.x, sourceFloorRC.y, d); let bottomLeft = getX(b, sourceCeilRC.x, sourceFloorRC.y, d); let topRight = getX(b, sourceFloorRC.x, sourceCeilRC.y, d); let bottomRight = getX(b, sourceCeilRC.x, sourceCeilRC.y, d); let fracRC = sourceFracIndexRC - vec2(sourceFloorRC); let top = topLeft + (topRight - topLeft) * fracRC.y; let bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y; let newValue = top + (bottom - top) * fracRC.x; setOutputAtIndex(index, newValue); } } `}};function O2e(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,size:i,halfPixelCenters:o}=n,[l,u]=i,d=s&&l>1?1:0,c=s&&u>1?1:0,p=[{type:"float32",data:[d,c]},{type:"float32",data:[o?.5:0]}],h=new _2e(r.shape,l,u);return a.runWebGPUProgram(h,[r],"float32",p)}var z2e={kernelName:Bo,backendName:"webgpu",kernelFunc:O2e},L2e=class{constructor(e,t){this.variableNames=["dy"],this.uniforms=`effectiveXSize : vec2, effectiveYSize : vec2, heightScale : f32, widthScale : f32, invHeightScale : f32, invWidthScale : f32, winHeight : i32, winWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.alignCorners=t,this.shaderKey=`resizeBilinearBackprop_${t}`}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); let b = coords[0]; let d = coords[3]; let r = coords[1]; let c = coords[2]; var accumulator = 0.0; // Compute bounds for where in dy we will look let startRLerp = floor(f32(r) * uniforms.invHeightScale); let startDyR = i32(startRLerp - f32(uniforms.winHeight / 2)); let startCLerp = floor(f32(c) * uniforms.invWidthScale); let startDyC = i32(startCLerp - f32(uniforms.winWidth / 2)); // Loop over dy for (var dyROffset = 0; dyROffset < uniforms.winHeight; dyROffset++) { let dyR = startDyR + dyROffset; // Guard against the window exceeding the bounds of dy if (dyR < 0 || dyR >= uniforms.dyShape[1]) { continue; } for (var dyCOffset = 0; dyCOffset < uniforms.winWidth; dyCOffset++) { let dyC = startDyC + dyCOffset; // Guard against the window exceeding the bounds of dy if (dyC < 0 || dyC >= uniforms.dyShape[2]) { continue; } let dxR = f32(dyR) * uniforms.heightScale; let topDxRIndex = i32(floor(dxR)); let bottomDxRIndex = i32(min(ceil(dxR), f32(uniforms.outShape[1] - 1))); let dxRLerp = dxR - f32(topDxRIndex); let inverseDxRLerp = 1.0 - dxRLerp; let dxC = f32(dyC) * uniforms.widthScale; let leftDxCIndex = i32(floor(dxC)); let rightDxCIndex = i32(min(ceil(dxC), f32(uniforms.outShape[2] - 1))); let dxCLerp = dxC - f32(leftDxCIndex); let 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 setOutputAtIndex(index, accumulator); } } `}};function W2e(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,[,o,l]=r.shape,[,u,d]=s.shape,c=[i&&u>1?o-1:o,i&&d>1?l-1:l],p=[i&&u>1?u-1:u,i&&d>1?d-1:d],h=c[0]/p[0],m=c[1]/p[1],f=1/h,g=1/m,y=Math.ceil(f)*2+2,x=Math.ceil(g)*2+2,A=new L2e(r.shape,i),b=[{type:"int32",data:c},{type:"int32",data:p},{type:"float32",data:[h]},{type:"float32",data:[m]},{type:"float32",data:[f]},{type:"float32",data:[g]},{type:"int32",data:[y]},{type:"int32",data:[x]}];return a.runWebGPUProgram(A,[s],s.dtype,b)}var B2e={kernelName:_u,backendName:"webgpu",kernelFunc:W2e},V2e=class{constructor(e,t,a,n){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2, roundBase : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,a,e[3]],this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.halfPixelCenters=n,this.shaderKey=`resizeNearest_${n}`}getUserCode(){let e;return this.halfPixelCenters?e="max((vec2(rc) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":e="vec2(rc) * effectiveInputOverOutputRatioRC",` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let b = coords[0]; let d = coords[3]; let rc = coords.yz; let effectiveInSize = vec2( f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0], f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]); let effectiveOutSize = vec2( f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0], f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]); let effectiveInputOverOutputRatioRC = effectiveInSize / effectiveOutSize; // Fractional source index let sourceFracIndexRC = ${e}; // Compute the coordinators of nearest neighbor point. let inputShapeRC = vec2(f32(uniforms.xShape.y), f32(uniforms.xShape.z)); let sourceNearestRC = vec2( min(inputShapeRC - 1.0, floor(sourceFracIndexRC + uniforms.roundBase))); let newValue = getX(b, sourceNearestRC.x, sourceNearestRC.y, d); setOutputAtIndex(index, newValue); } } `}};function U2e(e){let{inputs:t,backend:a,attrs:n}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,d=s&&l>1?1:0,c=s&&u>1?1:0,p=[{type:"float32",data:[d,c]},{type:"float32",data:[s?.5:0]}],h=new V2e(r.shape,l,u,i);return a.runWebGPUProgram(h,[r],r.dtype,p)}var G2e={kernelName:Wo,backendName:"webgpu",kernelFunc:U2e},H2e=class{constructor(e,t){this.variableNames=["dy"],this.uniforms=`effectiveXSize : vec2, effectiveYSize : vec2, invHeightScale : f32, invWidthScale : f32, winHeight : i32, winWidth : i32,`,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.alignCorners=t,this.shaderKey=`resizeNearestNeigborBackprop_${t}`}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getOutputCoords(); let b = coords[0]; let d = coords[3]; let r = coords[1]; let c = coords[2]; var accumulator = 0.0; // Compute bounds for where in dy we will look let startRLerp = floor(f32(r) * uniforms.invHeightScale); let startDyR = i32(floor(startRLerp - f32(uniforms.winHeight / 2))); let startCLerp = floor(f32(c) * uniforms.invWidthScale); let startDyC = i32(floor(startCLerp - f32(uniforms.winWidth / 2))); // Loop over dy for (var dyROffset = 0; dyROffset < uniforms.winHeight; dyROffset++) { let dyR = startDyR + dyROffset; // Guard against the window exceeding the bounds of dy if (dyR < 0 || dyR >= uniforms.dyShape[1]) { continue; } for (var dyCOffset = 0; dyCOffset < uniforms.winWidth; dyCOffset++) { let dyC = startDyC + dyCOffset; // Guard against the window exceeding the bounds of dy if (dyC < 0 || dyC >= uniforms.dyShape[2]) { continue; } let sourceFracRow = f32(uniforms.effectiveXSize[0]) * (f32(dyR) / f32(uniforms.effectiveYSize[0])); let sourceFracCol = f32(uniforms.effectiveXSize[1]) * (f32(dyC) / f32(uniforms.effectiveYSize[1])); let sourceNearestRow = i32(min(f32(uniforms.outShape[1] - 1), ${this.alignCorners?"floor(sourceFracRow + 0.5)":"floor(sourceFracRow)"})); let sourceNearestCol = i32(min(f32(uniforms.outShape[2] - 1), ${this.alignCorners?"floor(sourceFracCol + 0.5)":"floor(sourceFracCol)"})); if (r == sourceNearestRow && c == sourceNearestCol) { accumulator += getDy(b, dyR, dyC, d); } } } // End loop over dy setOutputAtIndex(index, accumulator); } } `}};function j2e(e){let{inputs:t,backend:a,attrs:n}=e,{images:r,dy:s}=t,{alignCorners:i}=n,[,o,l]=r.shape,[,u,d]=s.shape,c=[i&&u>1?o-1:o,i&&d>1?l-1:l],p=[i&&u>1?u-1:u,i&&d>1?d-1:d],h=c[0]/p[0],m=c[1]/p[1],f=1/h,g=1/m,y=Math.ceil(f)*2+2,x=Math.ceil(g)*2+2,A=new H2e(r.shape,i),b=[{type:"int32",data:c},{type:"int32",data:p},{type:"float32",data:[f]},{type:"float32",data:[g]},{type:"int32",data:[y]},{type:"int32",data:[x]}];return a.runWebGPUProgram(A,[s],s.dtype,b)}var q2e={kernelName:Pu,backendName:"webgpu",kernelFunc:j2e},X2e=class{constructor(e){this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=" axis : vec4,",this.shaderKey="reverse"}getUserCode(){return` // Using uniform variables as judging conditions, so the function has // coherent execution within all threads. fn getReverseCoords(coords : vec4) -> vec4 { var reverseCoords = coords; if (uniforms.axis[0] == 1) { reverseCoords[0] = uniforms.xShape[0] - coords[0] - 1; } if (uniforms.axis[1] == 1) { reverseCoords[1] = uniforms.xShape[1] - coords[1] - 1; } if (uniforms.axis[2] == 1) { reverseCoords[2] = uniforms.xShape[2] - coords[2] - 1; } if (uniforms.axis[3] == 1) { reverseCoords[3] = uniforms.xShape[3] - coords[3] - 1; } return reverseCoords; } ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let reverseCoords = getReverseCoords(coords); setOutputAtIndex(index, getX(reverseCoords[0], reverseCoords[1], reverseCoords[2], reverseCoords[3])); } } `}};function K2e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{dims:s}=n,i=r.shape.length;if(i===0)return an({inputs:{x:r},backend:a});let o=r.shape,l=[1,1,1,1];o.forEach((g,y)=>{let x=y+4-i;l[x]=g});let u=v.parseAxisParam(s,r.shape),d=[0,0,0,0];u.forEach(g=>{let y=g+4-i;d[y]=1});let c=[{type:"int32",data:d}],p=ke({inputs:{x:r},backend:a,attrs:{shape:l}}),h=new X2e(l),m=a.runWebGPUProgram(h,[p],p.dtype,c);a.disposeData(p.dataId);let f=ke({inputs:{x:m},backend:a,attrs:{shape:o}});return a.disposeData(m.dataId),f}var Y2e={kernelName:Uo,backendName:"webgpu",kernelFunc:K2e},Z2e=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`centerX : f32, centerY : f32, sinRadians : f32, cosRadians : f32,`,this.shaderKey="rotate",this.outputShape=e,typeof t=="number"?(this.uniforms+=" fillValue : f32,",this.fillSnippet="var outputValue = uniforms.fillValue;",this.shaderKey+="_float"):(this.uniforms+=" fillValue : vec3,",this.fillSnippet="var outputValue = uniforms.fillValue[coords[3]];",this.shaderKey+="_vec3")}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let coordXFloat = (f32(coords[2]) - uniforms.centerX) * uniforms.cosRadians - (f32(coords[1]) - uniforms.centerY) * uniforms.sinRadians; let coordYFloat = (f32(coords[2]) - uniforms.centerX) * uniforms.sinRadians + (f32(coords[1]) - uniforms.centerY) * uniforms.cosRadians; let coordX = i32(round(coordXFloat + uniforms.centerX)); let coordY = i32(round(coordYFloat + uniforms.centerY)); ${this.fillSnippet} if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 && coordY < uniforms.xShape[1]) { outputValue = getX(coords[0], coordY, coordX, coords[3]); } setOutputAtIndex(index, outputValue); } } `}},J2e={kernelName:ol,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:a})=>{let{image:n}=e,{radians:r,fillValue:s,center:i}=t,o=a,l=new Z2e(n.shape,s),[u,d]=I.getImageCenter(i,n.shape[1],n.shape[2]),c=[{type:"float32",data:[u]},{type:"float32",data:[d]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof s=="number"?c.push({type:"float32",data:[Number.parseFloat(s.toFixed(2))]}):c.push({type:"float32",data:s}),o.runWebGPUProgram(l,[n],n.dtype,c)}},Q2e=at({opType:le.ROUND}),e1e={kernelName:Go,backendName:"webgpu",kernelFunc:Q2e},t1e=at({opType:le.RSQRT,cpuKernelImpl:gce}),a1e={kernelName:Ns,backendName:"webgpu",kernelFunc:t1e},Gd=class{constructor(e,t,a,n,r,s,i,o=!0){this.variableNames=["updates","indices"],this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=s,this.type=i,this.sumDupeIndices=o,this.dispatchLayout=me(e),this.dispatch=de(this.dispatchLayout,e,this.workgroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${a}_${n}_${this.sliceDimGreaterThanOne}_${i}_${o}_${r.length}`;let l=Dt(r.length);this.uniforms=`sliceDim : i32, strides: ${l}, updatesSize: i32,`,this.updatesRank=n,this.indicesRank=a}getUserCode(){let e="";this.indicesRank===1?e="coords[0]":this.indicesRank===2&&(e="coords[0], j");let t=`getIndices(${e})`,a=this.sliceDimGreaterThanOne?"uniforms.strides[j]":"uniforms.strides",n="",r="";this.dispatchLayout.x.length===1?(n="flattenedIndex",r=` fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 { return index; } `):this.dispatchLayout.x.length===2&&(n="vec2(flattenedIndex, coords[1])",r=` fn getUpdatesCoordsFromFlatIndex(index : i32) -> vec2 { // N.B. |updates| could be a scalar tensor, conceptually representing a // 2D tensor with all values equal to that. By design, its size must be // the same as |outShape[1]| in one dimension, and |indicesShape[0]| // gives the other. let sliceSize = uniforms.outShape[1]; let d0 = index / sliceSize; let d1 = index - d0 * sliceSize; return vec2(d0, d1); } `);let s=`getUpdates(${Array.from({length:this.updatesRank},(i,o)=>`coords[${o}]`).join(", ")})`;return` ${r} ${ue("index")} { if (index < uniforms.updatesSize) { let coords = getUpdatesCoordsFromFlatIndex(index); var flattenedIndex = 0; for (var j = 0; j < uniforms.sliceDim; j = j + 1) { let indexInside = i32(round(${t})); flattenedIndex = flattenedIndex + indexInside * ${a}; } let updateValue = ${gi(this.type)}(${s}); let flatIndex = getOutputIndexFromCoords(${n}); ${this.sumDupeIndices?Bs("&result[flatIndex]","updateValue",this.type):"atomicStore(&result[flatIndex], bitcast(updateValue));"} } }`}};function n1e(e){let{inputs:t,backend:a,attrs:n}=e,{indices:r,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:d,outputSize:c}=I.calculateShapes(s,r,i),p=[c/u,u];if(c===0)return a.makeTensorInfo(i,r.dtype);let h=ke({inputs:{x:r},backend:a,attrs:{shape:[l,o]}}),m=ke({inputs:{x:s},backend:a,attrs:{shape:[l,u]}}),f=m.dtype,g=Wa({backend:a,attrs:{shape:p,value:0,dtype:f}}),y=v.sizeFromShape(m.shape),x=[{type:"int32",data:[o]},{type:"int32",data:d},{type:"int32",data:[y]}],A=new Gd(m.shape,o,h.shape.length,m.shape.length,d,p,f),b=a.runWebGPUProgram(A,[m,h],f,x,g),w=ke({inputs:{x:b},backend:a,attrs:{shape:i}});return a.disposeData(h.dataId),a.disposeData(m.dataId),a.disposeData(b.dataId),w}var r1e={kernelName:Ho,backendName:"webgpu",kernelFunc:n1e},s1e=class{constructor(e,t){this.outputShape=[],this.variableNames=["sortedSequence","values"],this.uniforms="numInputs : i32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.side=t,this.shaderKey=`search_sorted_${t}`}getUserCode(){return` fn findBound(batch: i32, value: f32) -> i32 { var left = i32(0); var right = uniforms.numInputs; while (left < right) { var mid = (left + right) / 2; if (getSortedSequence(batch, mid) ${this.side==="left"?"<":"<="} value) { left = mid + 1; } else { right = mid; } } return right; } ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); let value = getValuesByOutputIndex(index); setOutputAtIndexI32(index, findBound(coords[0], value)); } } `}};function i1e(e){let{inputs:t,backend:a,attrs:n}=e,{sortedSequence:r,values:s}=t,{side:i}=n,o=new s1e([s.shape[0],s.shape[1]],i),l=[{type:"int32",data:[r.shape[1]]}];return a.runWebGPUProgram(o,[r,s],"int32",l)}var o1e={kernelName:qo,backendName:"webgpu",kernelFunc:i1e},l1e=class{constructor(e,t,a){this.variableNames=["c","a","b"],this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.cRank=e,this.rank=a,this.shaderKey="select"}getUserCode(){let e,t;if(this.rank>4)throw Error(`Where for rank ${this.rank} is not yet supported`);if(this.rank===1)t="resRC",e="resRC";else{let a=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[],r=[];for(let s=0;s= 1.0) { setOutputAtIndex(index, getA(${t})); } else { setOutputAtIndex(index, getB(${t})); } } } `}};function u1e(e){let{inputs:t,backend:a}=e,{condition:n,t:r,e:s}=t,i=new l1e(n.shape.length,r.shape,r.shape.length);return a.runWebGPUProgram(i,[n,r,s],Qt(r.dtype,s.dtype))}var d1e={kernelName:Ou,backendName:"webgpu",kernelFunc:u1e},p1e=at({opType:le.SELU}),c1e={kernelName:Xo,backendName:"webgpu",kernelFunc:p1e},h1e=at({opType:le.SIGMOID}),m1e={kernelName:Rs,backendName:"webgpu",kernelFunc:h1e},f1e=at({opType:le.SIGN}),g1e={kernelName:Zo,backendName:"webgpu",kernelFunc:f1e},y1e=at({opType:le.SIN}),x1e={kernelName:Ko,backendName:"webgpu",kernelFunc:y1e},A1e=at({opType:le.SINH}),b1e={kernelName:Yo,backendName:"webgpu",kernelFunc:A1e},v1e=at({opType:le.SOFTPLUS}),w1e={kernelName:Jo,backendName:"webgpu",kernelFunc:v1e},k1e=class{constructor(e,t,a,n,r,s){this.variableNames=["x"],this.outputShape=[],this.uniforms="",this.workgroupSize=[64,1,1],this.size=!0;let i=new Array(n.length);for(let o=0;o{this.uniforms+=` pad${l} : vec2,`}),this.shaderKey=`spaceToBatchND_${r}`}getUserCode(){let e=Dt(this.outputShape.length),t=x9(this.newDim);return` ${mh(this.paddedXShape,"PaddedX")} ${ue("index")} { if(index < uniforms.size) { let coords = getCoordsFromIndex(index); let switchedIndex = getIndexFromCoords${this.outputShape.length}D(${e}(${t}), uniforms.reshapedPaddedXShape); let paddedCoords = getPaddedXCoordsFromIndex(switchedIndex); ${O9(this.xShape,!0)} } } `}},I1e=e=>{let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{blockShape:s,paddings:i}=n;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet");let o=s.reduce((x,A)=>x*A),l=[[0,0]];l.push(...i);for(let x=1+s.length;xx[0]+r.shape[A]+x[1]),d=I.getReshaped(u,s,o,!1),c=I.getPermuted(d.length,s.length,!1),p=I.getReshapedPermuted(u,s,o,!1),h=v.computeStrides(u),m=new k1e(r.shape,u,l,d,c,h.length),f=[{type:"int32",data:d},{type:"int32",data:h}];l.map(x=>f.push({type:"int32",data:[x[0],x[1]]}));let g=a.runWebGPUProgram(m,[r],r.dtype,f),y=ke({inputs:{x:g},backend:a,attrs:{shape:p}});return a.disposeData(g.dataId),y},S1e={kernelName:Lu,backendName:"webgpu",kernelFunc:I1e},T1e=class{constructor(e,t,a){this.variableNames=["input","indices","segmentIds"],this.outputShape=[],this.uniforms="segmentSize : i32, sparseSize : i32,",this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=e,this.type=a,this.dispatchLayout=me([t]),this.dispatch=de(this.dispatchLayout,[t],this.workgroupSize),this.shaderKey="sparseSegmentSum"}getUserCode(){return` ${ue("index")} { if (index < uniforms.sparseSize) { let indexInSegmentIds = index / uniforms.segmentSize; let indexInSegment = index % uniforms.segmentSize; let indexInInput = indices[indexInSegmentIds]; let segmentId = segmentIds[indexInSegmentIds]; let value = input[indexInInput * uniforms.segmentSize + indexInSegment]; let outIndex = segmentId * uniforms.segmentSize + indexInSegment; ${Bs("&result[outIndex]","value",this.type)} } } `}},C1e=class{constructor(e,t){this.variableNames=["segmentIds"],this.outputShape=[],this.workgroupSize=[64,1,1],this.atomic=!0,this.outputShape=[e],this.dispatchLayout=me(t),this.dispatch=de(this.dispatchLayout,t,this.workgroupSize),this.shaderKey="sparseSegmentIdCountProgram"}getUserCode(){return` ${ue("index")} { if (index < uniforms.segmentIdsShape) { let segmentId = segmentIds[index]; ${Bs("&result[segmentId]","1","int32")} } } `}},N1e=class{constructor(e,t){this.variableNames=["segmentSum","sameSegmentIdCount"],this.outputShape=[],this.uniforms="segmentSize : i32",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.type=t,this.dispatchLayout=me(e),this.dispatch=de(this.dispatchLayout,e,this.workgroupSize),this.shaderKey="sparseSegmentMean"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let segmentId = index / uniforms.segmentSize; let count = sameSegmentIdCount[segmentId]; if (count != 0) { ${this.type==="float32"?"setOutputAtIndex(index, segmentSum[index] / f32(count));":"setOutputAtIndexI32(index, segmentSum[index] / count);"} } } } `}};function z9(e,t,a,n=!1,r){let s=v.sizeFromShape(e.shape)/e.shape[0],i=e.dtype,o=v.sizeFromShape(t.shape),l=r.readSync(a.dataId),u=o>0?l[o-1]+1:0,d,c=e.shape.slice();c[0]=u;let p=o*s,h=Wa({backend:r,attrs:{shape:c,value:0,dtype:i}});d=new T1e(c,p,i);let m=[{type:"int32",data:[s]},{type:"int32",data:[p]}],f=r.runWebGPUProgram(d,[e,t,a],i,m,h);if(n)return f;let g=Wa({backend:r,attrs:{shape:[u],value:0,dtype:"int32"}});d=new C1e(u,a.shape);let y=r.runWebGPUProgram(d,[a],"int32",null,g),x=Wa({backend:r,attrs:{shape:c,value:0,dtype:i}});d=new N1e(c,i),m=[{type:"int32",data:[s]}];let A=r.runWebGPUProgram(d,[f,y],i,m,x);return r.disposeData(f.dataId),r.disposeData(y.dataId),A}function R1e(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;return z9(n,r,s,!1,a)}var E1e={kernelName:Vu,backendName:"webgpu",kernelFunc:R1e};function M1e(e){let{inputs:t,backend:a}=e,{data:n,indices:r,segmentIds:s}=t;return z9(n,r,s,!0,a)}var F1e={kernelName:Uu,backendName:"webgpu",kernelFunc:M1e},$1e=class{constructor(e,t){this.variableNames=["A"],this.workgroupSize=[64,1,1],this.size=!0;let a=new Array(e.length);for(let n=0;n=5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`(resRC % ${t}aShape)`;let a=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let r=0;r=5){let o=a.readSync(r.dataId),l=r.dtype==="string"?o.map(c=>v.decodeString(c)):o,u=Te(r.shape,r.dtype,l),d=kce(u,s);return a.makeTensorInfo(d.shape,d.dtype,d.values)}let i=new $1e(r.shape,s);return a.runWebGPUProgram(i,[r],r.dtype)}var P1e={kernelName:$s,backendName:"webgpu",kernelFunc:dy};function _1e(e){let{inputs:t,backend:a,attrs:n}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:d,strides:c,outputSize:p}=I.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let N=a.bufferSync(r),M=a.bufferSync(s),F=v.decodeString(a.readSync(i.dataId)[0]),E=yce(N,M,o,p,d,u,l,c,F,h);return a.makeTensorInfo(o,E.dtype,E.values)}let m=[p/d,d],f=ke({inputs:{x:r},backend:a,attrs:{shape:[u,l]}}),g=s.shape.length?ke({inputs:{x:s},backend:a,attrs:{shape:[u,d]}}):an({inputs:{x:s},backend:a}),y=g.dtype,x=a.makeTensorInfo([],y,v.makeZerosTypedArray(1,y)),A=ke({inputs:{x:i},backend:a,attrs:{shape:Array(m.length).fill(1)}}),b=dy({inputs:{x:A},backend:a,attrs:{reps:m}}),w=v.sizeFromShape([u,d]),S=[{type:"int32",data:[l]},{type:"int32",data:c},{type:"int32",data:[w]}];switch(u){case 0:break;case 1:{let N=new Gd([u,d],l,f.shape.length,g.shape.length,c,m,y,h);a.runWebGPUProgram(N,[g,f],y,S,b)}break;default:{let N=new Gd([u,d],l,f.shape.length,x.shape.length,c,m,y,h);a.runWebGPUProgram(N,[x,f],y,S,b)}{let N=new Gd([u,d],l,f.shape.length,g.shape.length,c,m,y);a.runWebGPUProgram(N,[g,f],y,S,b)}}let C=ke({inputs:{x:b},backend:a,attrs:{shape:o}});return a.disposeData(f.dataId),a.disposeData(g.dataId),a.disposeData(A.dataId),a.disposeData(x.dataId),a.disposeData(b.dataId),C}var O1e={kernelName:tl,backendName:"webgpu",kernelFunc:_1e};function z1e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,r.shape)[0],l=I.prepareSplitSize(r,s,o),u=r.shape.length,d=new Array(u).fill(0),c=r.shape.slice();return l.map(p=>{let h=[...c];h[o]=p;let m=od({inputs:{x:r},backend:a,attrs:{begin:d,size:h}});return d[o]+=p,m})}var L1e={kernelName:Wu,backendName:"webgpu",kernelFunc:z1e},W1e=at({opType:le.SQRT}),B1e={kernelName:Es,backendName:"webgpu",kernelFunc:W1e},V1e={kernelName:Fp,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:a}=e,n=t,r=new id(a.shape,le.SQUARE);return n.runWebGPUProgram(r,[a],a.dtype)}},U1e=aa({opType:De.SQUARED_DIFFERENCE}),G1e={kernelName:Ms,backendName:"webgpu",kernelFunc:U1e};function H1e({inputs:e,attrs:t,backend:a}){let{x:n}=e,r=new id(n.shape,le.STEP,"stepAlpha : f32,"),s=[{type:"float32",data:[t.alpha]}];return a.runWebGPUProgram(r,[n],n.dtype,s)}var j1e={kernelName:Ds,backendName:"webgpu",kernelFunc:H1e},q1e=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize,[this.workPerThread,1,1]);let t=Dt(this.outputShape.length);this.uniforms=`begin : ${t}, strides : ${t}, `,this.shaderKey="stridedSlice"}getUserCode(){let e=this.outputShape.length,t="";if(e===1)t="coords * uniforms.strides + uniforms.begin";else{let a=0;t=this.outputShape.map((n,r)=>(a++,this.outputShape.length===1?`coords * uniforms.strides[${r}] + uniforms.begin[${r}]`:`coords[${a-1}] * uniforms.strides[${r}] + uniforms.begin[${r}]`)).join(",")}return` ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); setOutputAtIndex(index, getX(${t})); } } `}};function X1e(e){let{inputs:t,backend:a,attrs:n}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:d,newAxisMask:c,shrinkAxisMask:p}=n,{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=wt.sliceInfo(r.shape,s,i,o,l,u,d,c,p),w;if(f)w=ke({inputs:{x:r},backend:a,attrs:{shape:m}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let S=wt.computeOutShape(x,A,b),C=od({inputs:{x:r},backend:a,attrs:{begin:x,size:S}});w=ke({inputs:{x:C},backend:a,attrs:{shape:m}}),a.disposeData(C.dataId)}else if(a.shouldExecuteOnCPU([r])){let S=a.readSync(r.dataId),C=Te(r.shape,r.dtype,S),N=bce(h,C,b,x);w=a.makeTensorInfo(m,r.dtype,N.values)}else{let S=new q1e(h),C=[{type:"int32",data:x},{type:"int32",data:b}],N=a.runWebGPUProgram(S,[r],r.dtype,C);w=ke({inputs:{x:N},backend:a,attrs:{shape:m}}),a.disposeData(N.dataId)}return w}var K1e={kernelName:al,backendName:"webgpu",kernelFunc:X1e};function Y1e(e){let{inputs:t,backend:a,attrs:n}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:d,dataSplits:c}=t,p=a.readSync(d.dataId),h=a.readSync(c.dataId),[m,f]=vce(p,h,r,s,i,o,l,u);return[a.makeTensorInfo([m.length],"string",m),a.makeTensorInfo(c.shape,"int32",f)]}var Z1e={kernelName:Hu,backendName:"webgpu",kernelFunc:Y1e},J1e=aa({opType:De.SUB,cpuKernelImpl:wce,supportsComplex:!0}),Q1e={kernelName:Fs,backendName:"webgpu",kernelFunc:J1e},ege=at({opType:le.TAN}),tge={kernelName:nl,backendName:"webgpu",kernelFunc:ege},age=at({opType:le.TANH}),nge={kernelName:rl,backendName:"webgpu",kernelFunc:age};function rge(e){let{inputs:t,backend:a,attrs:n}=e,{tensor:r,indices:s,updates:i}=t,{}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:d,outputSize:c}=I.calculateShapes(i,s,r.shape),p=[c/u,u];if(c===0)return a.makeTensorInfo(r.shape,s.dtype);let h=[],m=ke({inputs:{x:s},backend:a,attrs:{shape:[l,o]}});h.push(m);let f=ke({inputs:{x:i},backend:a,attrs:{shape:[l,u]}});h.push(f);let g=ke({inputs:{x:r},backend:a,attrs:{shape:p}});h.push(g);let y=dy({inputs:{x:g},backend:a,attrs:{reps:Array(p.length).fill(1)}}),x=new Gd([l,u],o,m.shape.length,f.shape.length,d,p,r.dtype,!1),A=v.sizeFromShape([l,u]),b=[{type:"int32",data:[o]},{type:"int32",data:d},{type:"int32",data:[A]}],w=a.runWebGPUProgram(x,[f,m],g.dtype,b,y);h.push(w);let S=ke({inputs:{x:w},backend:a,attrs:{shape:r.shape}});return h.forEach(C=>a.disposeData(C.dataId)),S}var sge={kernelName:jo,backendName:"webgpu",kernelFunc:rge},ige=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32, dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let outC = getCoordsFromIndex(index); let batch = outC[0]; let elemIdx = outC[1]; // We compare elements pair-wise within a group of size 2 * inc. // The comparing rule for each group alternates between ascending // and descending. Within each group, we compare each pair at // positions i and i+inc. To decide whether an element at position i // is x0 or x1, we mod it by 2 * inc, if the result is smaller than // inc, it is in the first half of the group, we denote it as x0, // otherwise we denote it as x1. // For example, as shown in the Bitonic top K paper referenced // above, Figure5(a) shows that element[1] is in the second half of // the group when group size is 2, but it is in the first half of // the group when group size is 4. let isFirstInPair = elemIdx % (2 * uniforms.inc) < uniforms.inc; var i = 0; if (isFirstInPair) { i = elemIdx; } else { i = elemIdx - uniforms.inc; } var i0 = 0; if (uniforms.firstPass == 1) { i0 = i; } else { i0 = i32(getIndices(batch, i)); } var i1 = 0; if (uniforms.firstPass == 1) { i1 = i + uniforms.inc; } else { i1 = i32(getIndices(batch, i + uniforms.inc)); } var x0 = f32(0.0); var x1 = f32(0.0); if (i0 < uniforms.inputSize) { x0 = getX(batch, i0); } else { x0 = uniforms.negativeInf; } if (i1 < uniforms.inputSize) { x1 = getX(batch, i1); } else { x1 = uniforms.negativeInf; } let reverse = elemIdx % (2 * uniforms.dir) >= uniforms.dir; let isGreater = x0 > x1 || (x0 == x1 && i1 > i0); if (reverse == isGreater) { // Elements in opposite order of direction let iTemp = i0; i0 = i1; i1 = iTemp; } if (isFirstInPair) { setOutputAtIndex(index, f32(i0)); } else { setOutputAtIndex(index, f32(i1)); } } } `}},oge=class{constructor(e){this.variableNames=["x","indices"],this.workgroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return` ${ue("index")} { if (index < uniforms.size) { let outC = getCoordsFromIndex(index); let batch = outC[0]; let elemIdx = outC[1]; // The output size is half of the previous size. // If the previous sequence is | | | | _ _ _ _ | | | | _ _ _ _ // (k=4), we only need to output the indices at positions |, the // indices at positions _ can be thrown away, see Figure5(b) After // Phase 2 (Merge phase) in the Bitonic Top K paper referenced // above. // For example, the paper shows we only need to output the orange // bars. The output sequence should look like this | | | | | | | |. // Because the sequence is halved, to map the output index back to // the previous sequence to find the corresponding value, we need // to double the index. When we double the index, we basically // interpolate a position, so 2i looks like // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k // position of each 2k positions by - elemIdx % k. E.g. for output // at index 4,5,6,7, we want to get the corresponding element at // original index 8,9,10,11, for output at index 8,9,10,11, // we want to get the corresponding element at original index // 16,17,18,19, so on and so forth. var i = 0; if (elemIdx < uniforms.k) { i = elemIdx; } else { i = elemIdx * 2 - elemIdx % uniforms.k; } var i0 = 0; if (uniforms.firstPass == 1) { i0 = i; } else { i0 = i32(getIndices(batch, i)); } var i1 = 0; if (uniforms.firstPass == 1) { i1 = i + uniforms.k; } else { i1 = i32(getIndices(batch, i + uniforms.k)); } let x0 = getX(batch, i0); var x1 = f32(0.0); if (i1 < uniforms.inputSize) { x1 = getX(batch, i1); } else { x1 = x0; } if (x0 >= x1) { setOutputAtIndex(index, f32(i0)); } else { setOutputAtIndex(index, f32(i1)); } } } `}};function Ul(e,t){t!==null&&e.disposeData(t.dataId)}function NA(e){let t=1;for(;th===null?[d,d]:[d,h],f=(b,w,S)=>{let C=m(),N=new ige(S),M=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[b]},{type:"int32",data:[w]}],F=h;h=a.runWebGPUProgram(N,C,"int32",M),Ul(a,F)};for(let b=1;b=1;S/=2)f(w,S,[u,p])}for(let b=p;b>c;b/=2){let w=m(),S=new oge([u,b/2]),C=[{type:"int32",data:[l]},{type:"int32",data:[h===null?1:0]},{type:"int32",data:[c]}],N=h;h=a.runWebGPUProgram(S,w,"int32",C),Ul(a,N);let M=c/2,F=M*2;for(let E=M;E>=1;E/=2)f(F,E,h.shape)}let g=h;h=od({inputs:{x:h},backend:a,attrs:{begin:0,size:[u,s]}}),Ul(a,g);let y=$9({inputs:{x:d,indices:h},backend:a,attrs:{axis:1,batchDims:1}});Ul(a,d);let x=o.slice(0,-1);x.push(s),g=h,h=ke({inputs:{x:h},attrs:{shape:x},backend:a}),Ul(a,g);let A=y;return y=ke({inputs:{x:y},attrs:{shape:x},backend:a}),Ul(a,A),[y,h]}var uge={kernelName:sl,backendName:"webgpu",kernelFunc:lge},dge=class{constructor(e){this.variableNames=["Image","Transforms"],this.uniforms="interpolationModeId : i32, fillModeId : i32, fillValue : f32,",this.workgroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=me(this.outputShape),this.dispatch=de(this.dispatchLayout,this.outputShape,this.workgroupSize),this.shaderKey="transform"}getUserCode(){return` fn mapCoord(outCoord : f32, len : f32) -> f32{ var inCoord = outCoord; if(uniforms.fillModeId == 2) { if (inCoord < 0.0) { if (len <= 1.0) { inCoord = 0.0; } else { let sz2 = 2.0 * len; if (inCoord < sz2) { inCoord = sz2 * f32(i32(f32(-inCoord / sz2))) + inCoord; } if (inCoord < -len) { inCoord = inCoord + sz2; } else { inCoord = -inCoord - 1.0; } } } else if (inCoord > len - 1.0) { if (len <= 1.0) { inCoord = 0.0; } else { let sz2 = 2.0 * len; inCoord = inCoord - sz2 * f32(i32(f32(inCoord / sz2))); if (inCoord >= len) { inCoord = sz2 - inCoord - 1.0; } } } return clamp(inCoord, 0.0, len - 1.0); } else if (uniforms.fillModeId == 3) { if (inCoord < 0.0) { if (len <= 1.0) { inCoord = 0.0; } else { let sz = len - 1.0; inCoord = inCoord + len * (f32(i32(f32(-inCoord / sz))) + 1.0); } } else if (inCoord > len - 1.0) { if (len <= 1.0) { inCoord = 0.0; } else { let sz = len - 1.0; inCoord = inCoord - len * f32(i32(f32(inCoord / sz))); } } return clamp(inCoord, 0.0, len - 1.0); } else if (uniforms.fillModeId == 4) { return clamp(outCoord, 0.0, len - 1.0); } return outCoord; } fn readWithFillValue(batch : i32, coordY : i32, coordX : i32, channel : i32) -> f32 { var outputValue : f32; if (0 <= coordY && coordY < uniforms.imageShape[1] && 0 <= coordX && coordX < uniforms.imageShape[2]) { outputValue = getImage(batch, coordY, coordX, channel); } else { outputValue = uniforms.fillValue; } return outputValue; } ${ue("index")} { if (index < uniforms.size) { let coords = getCoordsFromIndex(index); var outputValue : f32; let batch = coords[0]; let x = coords[2]; let y = coords[1]; let channel = coords[3]; let xf = f32(x); let yf = f32(y); let a1 = getTransforms(batch, 0); let a2 = getTransforms(batch, 1); let a3 = getTransforms(batch, 2); let b1 = getTransforms(batch, 3); let b2 = getTransforms(batch, 4); let b3 = getTransforms(batch, 5); let c1 = getTransforms(batch, 6); let c2 = getTransforms(batch, 7); let projection = c1 * xf + c2 * yf + 1.0; if (projection == 0.0) { outputValue = uniforms.fillValue; } else { let inX = (a1 * xf + a2 * yf + a3) / projection; let inY = (b1 * xf + b2 * yf + b3) / projection; let mapX = mapCoord(inX, f32(uniforms.imageShape[2])); let mapY = mapCoord(inY, f32(uniforms.imageShape[1])); if (uniforms.interpolationModeId == 1) { let coordY = i32(round(mapY)); let coordX = i32(round(mapX)); outputValue = readWithFillValue(batch, coordY, coordX, channel); } else { let yFloor = floor(mapY); let xFloor = floor(mapX); let yCeil = yFloor + 1.0; let xCeil = xFloor + 1.0; let valueYFloor = (xCeil - mapX) * readWithFillValue(batch, i32(yFloor), i32(xFloor), channel) + (mapX - xFloor) * readWithFillValue(batch, i32(yFloor), i32(xCeil), channel); let valueYCeil = (xCeil - mapX) * readWithFillValue(batch, i32(yCeil), i32(xFloor), channel) + (mapX - xFloor) * readWithFillValue(batch, i32(yCeil), i32(xCeil), channel); outputValue = (yCeil - mapY) * valueYFloor + (mapY - yFloor) * valueYCeil; } } setOutputAtIndex(index, outputValue); } } `}};function pge(e){let{inputs:t,backend:a,attrs:n}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[d,c,p,h]=r.shape,[m,f]=u!=null?u:[c,p],g=[d,m,f,h],y=new dge(g),x=i==="nearest"?1:2,A;switch(o){case"constant":A=1;break;case"reflect":A=2;break;case"wrap":A=3;break;case"nearest":A=4;break;default:A=1;break}let b=[{type:"int32",data:[x]},{type:"int32",data:[A]},{type:"float32",data:[l]}];return a.runWebGPUProgram(y,[r,s],"float32",b)}var cge={kernelName:il,backendName:"webgpu",kernelFunc:pge};function hge(e){let{inputs:t,backend:a,attrs:n}=e,{value:r}=t,{axis:s}=n;s<0&&(s+=r.shape.length);let i=r,o=i.shape.length,l=r.shape[s],u=new Array(o-1),d=0;for(let f=0;fa.disposeData(f.dataId)),m}var 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S0=class{constructor(){he(this,"config");he(this,"element");he(this,"stream");he(this,"devices",[]);he(this,"enumerate",async()=>{try{let t=await navigator.mediaDevices.enumerateDevices();this.devices=t.filter(a=>a.kind==="videoinput")}catch(t){this.devices=[]}return this.devices});he(this,"start",async t=>{var r,s;if(t!=null&&t.debug&&(this.config.debug=t==null?void 0:t.debug),t!=null&&t.crop&&(this.config.crop=t==null?void 0:t.crop),t!=null&&t.mode&&(this.config.mode=t==null?void 0:t.mode),t!=null&&t.width&&(this.config.width=t==null?void 0:t.width),t!=null&&t.height&&(this.config.height=t==null?void 0:t.height),t!=null&&t.id&&(this.config.id=t==null?void 0:t.id),t!=null&&t.element)if(typeof t.element=="string"){let i=document.getElementById(t.element);if(i&&i instanceof HTMLVideoElement)this.element=i;else return this.config.debug&&K("webcam","cannot get dom element",t.element),`webcam error: cannot get dom element: ${t.element}`}else if(t.element instanceof 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a;if(rt.drawGaze&&((a=e.rotation)!=null&&a.gaze.strength)&&e.rotation.gaze.bearing&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let n=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];Ay(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[n[0],n[1]],4);let r=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];Ay(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[r[0],r[1]],4)}}function pye(e,t){if(rt.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let a=0;ae.mesh[r]);xy(t,n,rt)}lye(e,t)}}function 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Sn,Il=224,nI,yye=5,D0=[8,16,32,32,32];function xye(){let e=[],t=0;for(;ta.x)),y:Vt(e.map(a=>a.y))}}async function rI(e){if(ne.initial&&(Sn=null),!Sn&&e.body.detector&&e.body.detector.modelPath){Sn=await $e(e.body.detector.modelPath);let t=Sn!=null&&Sn.executor?Object.values(Sn.modelSignature.inputs):void 0;Il=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0}else e.debug&&Sn&&K("cached model:",Sn.modelUrl);return xye(),Sn}var aI=[5,5];function Aye(e,t){return Pe(()=>{let a=Sa(e,12,1),n=Oe(a[0]),r=Oe(a[1]),s=Oe(a[2]),i=Oe(a[3]);n=we(ve(n,Il),t.x),r=we(ve(r,Il),t.y),s=te(ve(s,Il),aI[0]),i=te(ve(i,Il),aI[1]);let o=xe(n,ve(s,2)),l=xe(r,ve(i,2)),u=we(o,s),d=we(l,i);return ca([o,l,u,d],1)})}async function bye(e,t,a,n){var u,d;let r=[],s={};s.boxes=Aye(e,nI),s.scores=za(t),s.nms=await fe.nonMaxSuppressionAsync(s.boxes,s.scores,1,((u=a.body.detector)==null?void 0:u.minConfidence)||.1,((d=a.body.detector)==null?void 0:d.iouThreshold)||.1);let i=await s.nms.data(),o=await 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_y(e,t){if(!(Ft!=null&&Ft.executor)||!(Ft!=null&&Ft.inputs[0].shape))return[];let a=(t.body.skipTime||0)>ae()-gI,n=Py<(t.body.skipFrames||0);return t.skipAllowed&&a&&n&&Object.keys(Ma.keypoints).length>0?(Py++,[Ma]):(Py=0,new Promise(async r=>{let s=Pe(()=>{var m,f;let c=fe.resizeBilinear(e,[((m=Ft==null?void 0:Ft.inputs[0].shape)==null?void 0:m[2])||0,((f=Ft==null?void 0:Ft.inputs[0].shape)==null?void 0:f[1])||0],!1),p=te(c,ze.tf2);return xe(p,ze.tf1)}),i;if(t.body.enabled&&(i=Ft==null?void 0:Ft.execute(s)),gI=ae(),J(s),i){Ma.keypoints.length=0;let c=Oe(i);J(i);let p=Na(c,2);J(c);for(let h=0;h(t.body.minConfidence||0)&&Ma.keypoints.push({score:Math.round(100*g)/100,part:$y[h],positionRaw:[m/Ft.inputs[0].shape[2],f/Ft.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/Ft.inputs[0].shape[2]),Math.round(e.shape[1]*f/Ft.inputs[0].shape[1])]})}p.forEach(h=>J(h))}Ma.score=Ma.keypoints.reduce((c,p)=>p.score>c?p.score:c,0);let o=Ma.keypoints.map(c=>c.position[0]),l=Ma.keypoints.map(c=>c.position[1]);Ma.box=[Math.min(...o),Math.min(...l),Math.max(...o)-Math.min(...o),Math.max(...l)-Math.min(...l)];let u=Ma.keypoints.map(c=>c.positionRaw[0]),d=Ma.keypoints.map(c=>c.positionRaw[1]);Ma.boxRaw=[Math.min(...u),Math.min(...d),Math.max(...u)-Math.min(...u),Math.max(...d)-Math.min(...d)];for(let[c,p]of Object.entries(Dy)){let h=[];for(let m=0;my.part===p[m]),g=Ma.keypoints.find(y=>y.part===p[m+1]);f&&g&&f.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&h.push([f.position,g.position])}Ma.annotations[c]=h}r([Ma])}))}var dd=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],L0=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],W0=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],B0=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],vI=(e,t,a)=>{let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],r=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],s=e.landmarks.map(i=>[(i[0]+a[0])*t[0],(i[1]+a[1])*t[1]]);return{startPoint:n,endPoint:r,landmarks:s,confidence:e.confidence}},Oy=(e,t,a)=>{let n=t.shape[1],r=t.shape[2],s=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],i=fe.cropAndResize(t,[s],[0],a),o=ve(i,ze.tf255);return J(i),o},V0=(e,t)=>{let a=L0(e),n=dd(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[a[0]-r[0],a[1]-r[1]],endPoint:[a[0]+r[0],a[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence,size:n}},U0=e=>{let t=L0(e),a=dd(e),n=Math.max(...a)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence,size:[Math.round(a[0]),Math.round(a[1])]}},wI=e=>{let t=e.map(n=>n[0]),a=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...a)],endPoint:[Math.max(...t),Math.max(...a)],landmarks:e}},zy=[[1,0,0],[0,1,0],[0,0,1]],Cye=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),Nye=(e,t)=>Cye(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var AI=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Tl=(e,t)=>{let a=0;for(let n=0;n{let a=[];for(let n=0;n{let 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u=L0(t),d=[u[0]/a.shape[2],u[1]/a.shape[1]],c=fe.rotateWithOffset(a,s,0,[d[0],d[1]]);i=kI(-s,u),o=Oy(t,c,[n,n]),J(c)}else o=Oy(t,a,[n,n]);else o=Oy(t,a,[n,n]);return[s,i,o]}var Fye=e=>{let t=e.map(n=>n[0]),a=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...a)+(Math.max(...a)-Math.min(...a))/2]},CI=(e,t)=>{let a=Fye(e),n=dd(t);return{startPoint:[a[0]-n[0]/2,a[1]-n[1]/2],endPoint:[a[0]+n[0]/2,a[1]+n[1]/2]}};var NI=6,Hn,G0=null,Xs=0,pd=null,RI=()=>Xs;async function EI(e){var t;return ne.initial&&(Hn=null),Hn?e.debug&&K("cached model:",Hn.modelUrl):Hn=await $e((t=e.face.detector)==null?void 0:t.modelPath),Xs=Hn.executor&&Hn.inputs[0].shape?Hn.inputs[0].shape[2]:256,pd=Ge(Xs,"int32"),G0=er(II(Xs)),Hn}function $ye(e){if(!G0||!pd)return An([0,0]);let t={};t.boxStarts=_e(e,[0,1],[-1,2]),t.centers=we(t.boxStarts,G0),t.boxSizes=_e(e,[0,3],[-1,2]),t.boxSizesNormalized=ve(t.boxSizes,pd),t.centersNormalized=ve(t.centers,pd),t.halfBoxSize=ve(t.boxSizesNormalized,ze.tf2),t.starts=xe(t.centersNormalized,t.halfBoxSize),t.ends=we(t.centersNormalized,t.halfBoxSize),t.startNormalized=te(t.starts,pd),t.endNormalized=te(t.ends,pd);let a=Xu([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>J(t[n])),a}async function MI(e,t){var o,l,u,d,c,p,h;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let a={};a.resized=fe.resizeBilinear(e,[Xs,Xs]),a.div=ve(a.resized,ze.tf127),a.normalized=xe(a.div,ze.tf05);let n=Hn==null?void 0:Hn.execute(a.normalized);if(Array.isArray(n)&&n.length>2){let m=n.sort((f,g)=>f.size-g.size);a.concat384=lt([m[0],m[2]],2),a.concat512=lt([m[1],m[3]],2),a.concat=lt([a.concat512,a.concat384],1),a.batch=Oe(a.concat,[0])}else Array.isArray(n)?a.batch=Oe(n[0]):a.batch=Oe(n);J(n),a.boxes=$ye(a.batch),a.logits=_e(a.batch,[0,0],[-1,1]),a.sigmoid=za(a.logits),a.scores=Oe(a.sigmoid),a.nms=await fe.nonMaxSuppressionAsync(a.boxes,a.scores,((o=t.face.detector)==null?void 0:o.maxDetected)||0,((l=t.face.detector)==null?void 0:l.iouThreshold)||0,((u=t.face.detector)==null?void 0:u.minConfidence)||0);let r=await a.nms.array(),s=[],i=await a.scores.data();for(let m=0;m(((d=t.face.detector)==null?void 0:d.minConfidence)||0)){let g={};g.bbox=_e(a.boxes,[r[m],0],[1,-1]),g.slice=_e(a.batch,[r[m],NI-1],[1,-1]),g.squeeze=Oe(g.slice),g.landmarks=Q(g.squeeze,[NI,-1]);let y=await g.bbox.data(),x={startPoint:[y[0],y[1]],endPoint:[y[2],y[3]],landmarks:await g.landmarks.array(),confidence:f};g.anchor=_e(G0,[r[m],0],[1,2]);let A=await g.anchor.data(),b=vI(x,[(e.shape[2]||0)/Xs,(e.shape[1]||0)/Xs],A),w=V0(b,((c=t.face.detector)==null?void 0:c.scale)||1.4),S=U0(w);S.size[0]>(((p=t.face.detector)==null?void 0:p.minSize)||0)&&S.size[1]>(((h=t.face.detector)==null?void 0:h.minSize)||0)&&s.push(S),Object.keys(g).forEach(C=>J(g[C]))}}return Object.keys(a).forEach(m=>J(a[m])),s}var sn,Ks=0,Wy=Pn.leftEyeLower0,By=Pn.rightEyeLower0,cd={leftBounds:[Wy[0],Wy[Wy.length-1]],rightBounds:[By[0],By[By.length-1]]},hd={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function _I(e){var t,a;return ne.initial&&(sn=null),sn?e.debug&&K("cached model:",sn.modelUrl):sn=await $e((t=e.face.iris)==null?void 0:t.modelPath),Ks=sn!=null&&sn.executor&&((a=sn.inputs)!=null&&a[0].shape)?sn.inputs[0].shape[2]:0,Ks===-1&&(Ks=64),sn}function H0(e,t,a,n){for(let r=0;r{let t=e[cd.leftBounds[0]][2],a=e[cd.rightBounds[0]][2];return t-a},$I=(e,t,a,n,r,s=!1,i=2.3)=>{let o=U0(V0(wI([e[a],e[n]]),i)),l=dd(o),u=fe.cropAndResize(t,[[o.startPoint[1]/r,o.startPoint[0]/r,o.endPoint[1]/r,o.endPoint[0]/r]],[0],[Ks,Ks]);if(s&&ne.kernels.includes("flipleftright")){let d=fe.flipLeftRight(u);J(u),u=d}return{box:o,boxSize:l,crop:u}},DI=(e,t,a,n=!1)=>{let r=[];for(let s=0;s{let n=e[Pn[`${a}EyeUpper0`][hd.upperCenter]][2],r=e[Pn[`${a}EyeLower0`][hd.lowerCenter]][2],s=(n+r)/2;return t.map((i,o)=>{let l=s;return o===2?l=n:o===4&&(l=r),[i[0],i[1],l]})};async function OI(e,t,a,n){var C,N;if(!(sn!=null&&sn.executor))return e;let{box:r,boxSize:s,crop:i}=$I(e,t,cd.leftBounds[0],cd.leftBounds[1],a,!0,((C=n.face.iris)==null?void 0:C.scale)||2.3),{box:o,boxSize:l,crop:u}=$I(e,t,cd.rightBounds[0],cd.rightBounds[1],a,!0,((N=n.face.iris)==null?void 0:N.scale)||2.3),d=lt([i,u]);J(i),J(u);let c=sn.execute(d);J(d);let p=await c.data();J(c);let h=p.slice(0,hd.numCoordinates*3),{rawCoords:m,iris:f}=DI(h,r,s,!0),g=p.slice(hd.numCoordinates*3),{rawCoords:y,iris:x}=DI(g,o,l,!1),A=Dye(e);Math.abs(A)<30?(H0(e,m,"left",null),H0(e,y,"right",null)):A<1?H0(e,m,"left",["EyeUpper0","EyeLower0"]):H0(e,y,"right",["EyeUpper0","EyeLower0"]);let b=PI(e,f,"left"),w=PI(e,x,"right");return e.concat(b).concat(w)}async function LI(e,t){var s,i,o,l,u,d,c,p,h,m;let a={lips:await((i=(s=t.filter(f=>f.size===160))==null?void 0:s[0])==null?void 0:i.data()),irisL:await((l=(o=t.filter(f=>f.size===10))==null?void 0:o[0])==null?void 0:l.data()),eyeL:await((d=(u=t.filter(f=>f.size===142))==null?void 0:u[0])==null?void 0:d.data()),irisR:await((p=(c=t.filter(f=>f.size===10))==null?void 0:c[1])==null?void 0:p.data()),eyeR:await((m=(h=t.filter(f=>f.size===142))==null?void 0:h[1])==null?void 0:m.data())};for(let f of Object.values(a))if(!f)return e;let n=wl.reduce((f,g)=>f+=e[g][2],0)/wl.length;for(let f=0;ff+=e[g][2],0)/kl.length;for(let f=0;fae()-mr.timestamp,n=mr.skipped<(((u=t.face.detector)==null?void 0:u.skipFrames)||0);!t.skipAllowed||!a||!n||mr.boxes.length===0?(mr.boxes=await MI(e,t),mr.timestamp=ae(),mr.skipped=0):mr.skipped++;let r=[],s=[],i=0,o=gc;for(let x=0;x[C[0]/(e.shape[2]||0),C[1]/(e.shape[1]||0),(C[2]||0)/o]);for(let C of Object.keys(bl))S.annotations[C]=[S.mesh[bl[C]]]}else if(!Ct)t.debug&&K("face mesh detection requested, but model is not loaded");else{if((h=t.face.attention)!=null&&h.enabled&&!ne.kernels.includes("atan2"))return t.face.attention.enabled=!1,J(S.tensor),r;let C=Ct.execute(S.tensor),M=await C.find(F=>F.shape[F.shape.length-1]===1).data();if(S.faceScore=Math.round(100*M[0])/100,S.faceScore<(((m=t.face.detector)==null?void 0:m.minConfidence)||1)){if(A.confidence=S.faceScore,t.face.mesh.keepInvalid){S.box=W0(A,e),S.boxRaw=B0(A,e),S.size=A.size,S.score=S.boxScore,S.mesh=A.landmarks,S.meshRaw=S.mesh.map(F=>[F[0]/(e.shape[2]||1),F[1]/(e.shape[1]||1),(F[2]||0)/o]);for(let F of Object.keys(bl))S.annotations[F]=[S.mesh[bl[F]]]}}else{let F=C.find(O=>O.shape[O.shape.length-1]===1404),E=Q(F,[-1,3]),T=await E.array();J(E),(f=t.face.attention)!=null&&f.enabled?T=await LI(T,C):(g=t.face.iris)!=null&&g.enabled&&(T=await OI(T,S.tensor,gc,t)),S.mesh=SI(T,A,b,w,gc),S.meshRaw=S.mesh.map(O=>[O[0]/(e.shape[2]||0),O[1]/(e.shape[1]||0),(O[2]||0)/o]);for(let O of Object.keys(Pn))S.annotations[O]=Pn[O].map(W=>S.mesh[W]);S.score=S.faceScore;let D={...CI(S.mesh,A),confidence:A.confidence,landmarks:A.landmarks,size:A.size};S.box=W0(D,e),S.boxRaw=B0(D,e),S.size=D.size,s.push(D)}J(C)}S.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?r.push(S):J(S.tensor)}return mr.boxes=s,r}async function BI(e){var t,a,n,r,s,i;return ne.initial&&(Ct=null),(t=e.face.attention)!=null&&t.enabled&&(Ct!=null&&Ct.signature)&&Object.keys(((a=Ct==null?void 0:Ct.signature)==null?void 0:a.outputs)||{}).length<6&&(Ct=null),Ct?e.debug&&K("cached model:",Ct.modelUrl):(n=e.face.attention)!=null&&n.enabled?Ct=await $e(e.face.attention.modelPath):Ct=await $e((r=e.face.mesh)==null?void 0:r.modelPath),gc=Ct.executor&&((s=Ct==null?void 0:Ct.inputs)!=null&&s[0].shape)?(i=Ct==null?void 0:Ct.inputs)==null?void 0:i[0].shape[2]:256,Ct}var VI=vl,UI=mc;var Gy=[],sa,j0=[],GI=0,HI=0,Uy=Number.MAX_SAFE_INTEGER,Hy=!1;async function jI(e){var t,a,n;return ne.initial&&(sa=null),sa?e.debug&&K("cached model:",sa.modelUrl):(sa=await $e((t=e.face.emotion)==null?void 0:t.modelPath),Hy=((n=(a=sa==null?void 0:sa.inputs)==null?void 0:a[0].shape)==null?void 0:n[3])===3,Hy?Gy=["angry","disgust","fear","happy","neutral","sad","surprise"]:Gy=["angry","disgust","fear","happy","sad","surprise","neutral"]),sa}async function jy(e,t,a,n){var i,o;if(!sa)return[];let r=Uy<(((i=t.face.emotion)==null?void 0:i.skipFrames)||0),s=(((o=t.face.emotion)==null?void 0:o.skipTime)||0)>ae()-HI;return t.skipAllowed&&s&&r&&GI===n&&j0[a]&&j0[a].length>0?(Uy++,j0[a]):(Uy=0,new Promise(async l=>{var d,c,p;let u=[];if((d=t.face.emotion)!=null&&d.enabled){let h={},m=sa!=null&&sa.inputs[0].shape?sa.inputs[0].shape[2]:0;if(((c=t.face.emotion)==null?void 0:c.crop)>0){let g=(p=t.face.emotion)==null?void 0:p.crop,y=[[g,g,1-g,1-g]];h.resize=fe.cropAndResize(e,y,[0],[m,m])}else h.resize=fe.resizeBilinear(e,[m,m],!1);Hy?(h.mul=te(h.resize,255),h.normalize=xe(h.mul,[103.939,116.779,123.68]),h.emotion=sa==null?void 0:sa.execute(h.normalize)):(h.channels=te(h.resize,ze.rgb),h.grayscale=ot(h.channels,3,!0),h.grayscaleSub=xe(h.grayscale,ze.tf05),h.grayscaleMul=te(h.grayscaleSub,ze.tf2),h.emotion=sa==null?void 0:sa.execute(h.grayscaleMul)),HI=ae();let f=await h.emotion.data();for(let g=0;g(t.face.emotion.minConfidence||0)&&u.push({score:Math.min(.99,Math.trunc(100*f[g])/100),emotion:Gy[g]});u.sort((g,y)=>y.score-g.score),Object.keys(h).forEach(g=>J(h[g]))}j0[a]=u,GI=n,l(u)}))}var ia,Ys=[],XI=0,KI=0,qy=Number.MAX_SAFE_INTEGER;async function YI(e){var t;return ne.initial&&(ia=null),ia?e.debug&&K("cached model:",ia.modelUrl):ia=await $e((t=e.face.description)==null?void 0:t.modelPath),ia}function _ye(e,t){var s,i;let a=e.image||e.tensor||e;if(!(ia!=null&&ia.inputs[0].shape))return a;let n;if(((s=t.face.description)==null?void 0:s.crop)>0){let o=(i=t.face.description)==null?void 0:i.crop,l=[[o,o,1-o,1-o]];n=fe.cropAndResize(a,l,[0],[ia.inputs[0].shape[2],ia.inputs[0].shape[1]])}else n=fe.resizeBilinear(a,[ia.inputs[0].shape[2],ia.inputs[0].shape[1]],!1);let r=te(n,ze.tf255);return J(n),r}async function Xy(e,t,a,n){var o,l,u,d;let r={age:0,gender:"unknown",genderScore:0,descriptor:[]};if(!(ia!=null&&ia.executor))return r;let s=qy<(((o=t.face.description)==null?void 0:o.skipFrames)||0),i=(((l=t.face.description)==null?void 0:l.skipTime)||0)>ae()-XI;return t.skipAllowed&&s&&i&&KI===n&&((u=Ys==null?void 0:Ys[a])==null?void 0:u.age)>0&&((d=Ys==null?void 0:Ys[a])==null?void 0:d.genderScore)>0?(qy++,Ys[a]):(qy=0,new Promise(async c=>{var p;if((p=t.face.description)!=null&&p.enabled){let h=_ye(e,t),m=ia==null?void 0:ia.execute(h);XI=ae(),J(h);let g=await m.find(N=>N.shape[1]===1).data(),y=Math.trunc(200*Math.abs(g[0]-.5))/100;y>(t.face.description.minConfidence||0)&&(r.gender=g[0]<=.5?"female":"male",r.genderScore=Math.min(.99,y));let x=or(m.find(N=>N.shape[1]===100),1),A=(await x.data())[0];J(x);let w=await m.find(N=>N.shape[1]===100).data();r.age=Math.round(w[A-1]>w[A+1]?10*A-100*w[A-1]:10*A+100*w[A+1])/10,(Number.isNaN(g[0])||Number.isNaN(w[0]))&&K("faceres error:",{model:ia,result:m});let S=m.find(N=>N.shape[1]===1024),C=S?await S.data():[];r.descriptor=Array.from(C),m.forEach(N=>J(N))}Ys[a]=r,KI=n,c(r)}))}var md=.1,Ky=.5;function Oye(e,t,a){let n=!1,r=a.length-1;for(let s=0;st!=a[r].y>t&&e<(a[r].x-a[s].x)*(t-a[s].y)/(a[r].y-a[s].y)+a[s].x&&(n=!n);return n}async function JI(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,a=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let i of Pn.silhouette)r.push({x:(e.mesh[i][0]-e.box[0])/e.box[2],y:(e.mesh[i][1]-e.box[1])/e.box[3]});md&&md>0&&(r=r.map(i=>({x:i.x>.5?i.x+md:i.x-md,y:i.y>.5?i.y+md:i.y-md})));for(let i=0;iae()-eS,s=Yy<(((o=t.face.antispoof)==null?void 0:o.skipFrames)||0);return t.skipAllowed&&r&&s&&QI===n&&q0[a]?(Yy++,q0[a]):(Yy=0,new Promise(async l=>{let u=fe.resizeBilinear(e,[oa!=null&&oa.inputs[0].shape?oa.inputs[0].shape[2]:0,oa!=null&&oa.inputs[0].shape?oa.inputs[0].shape[1]:0],!1),d=oa==null?void 0:oa.execute(u),c=(await d.data())[0];q0[a]=Math.round(100*c)/100,QI=n,eS=ae(),J([u,d]),l(q0[a])}))}var la,X0=[],Jy=Number.MAX_SAFE_INTEGER,nS=0,rS=0;async function sS(e){var t;return ne.initial&&(la=null),la?e.debug&&K("cached model:",la.modelUrl):la=await $e((t=e.face.liveness)==null?void 0:t.modelPath),la}async function Qy(e,t,a,n){var i,o;if(!(la!=null&&la.executor))return 0;let r=(((i=t.face.liveness)==null?void 0:i.skipTime)||0)>ae()-rS,s=Jy<(((o=t.face.liveness)==null?void 0:o.skipFrames)||0);return t.skipAllowed&&r&&s&&nS===n&&X0[a]?(Jy++,X0[a]):(Jy=0,new Promise(async l=>{let u=fe.resizeBilinear(e,[la!=null&&la.inputs[0].shape?la.inputs[0].shape[2]:0,la!=null&&la.inputs[0].shape?la.inputs[0].shape[1]:0],!1),d=la==null?void 0:la.execute(u),c=(await d.data())[0];X0[a]=Math.round(100*c)/100,nS=n,rS=ae(),J([u,d]),l(X0[a])}))}var _n,ex=[],Lye=["white","black","asian","indian","other"],Wye=[15,23,28,35.5,45.5,55.5,65],oS=0,lS=0,tx=Number.MAX_SAFE_INTEGER;async function uS(e){var t;return ne.initial&&(_n=null),_n?e.debug&&K("cached model:",_n.modelUrl):_n=await $e((t=e.face.gear)==null?void 0:t.modelPath),_n}async function ax(e,t,a,n){var i,o;if(!_n)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=tx<(((i=t.face.gear)==null?void 0:i.skipFrames)||0),s=(((o=t.face.gear)==null?void 0:o.skipTime)||0)>ae()-lS;return t.skipAllowed&&s&&r&&oS===n&&ex[a]?(tx++,ex[a]):(tx=0,new Promise(async l=>{var y,x,A,b;if(!(_n!=null&&_n.inputs[0].shape))return;let u={},d=[[0,.1,.9,.9]];if(((y=t.face.gear)==null?void 0:y.crop)>0){let w=(x=t.face.gear)==null?void 0:x.crop;d=[[w,w,1-w,1-w]]}u.resize=fe.cropAndResize(e,d,[0],[_n.inputs[0].shape[2],_n.inputs[0].shape[1]]);let c={age:0,gender:"unknown",genderScore:0,race:[]};(A=t.face.gear)!=null&&A.enabled&&([u.age,u.gender,u.race]=_n.execute(u.resize,["age_output","gender_output","race_output"]));let p=await u.gender.data();c.gender=p[0]>p[1]?"male":"female",c.genderScore=Math.round(100*(p[0]>p[1]?p[0]:p[1]))/100;let h=await u.race.data();for(let w=0;w(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&c.race.push({score:Math.round(100*h[w])/100,race:Lye[w]});c.race.sort((w,S)=>S.score-w.score);let f=Array.from(await u.age.data()).map((w,S)=>[Wye[S],w]).sort((w,S)=>S[1]-w[1]),g=f[0][0];for(let w=1;wJ(u[w])),ex[a]=c,oS=n,lS=ae(),l(c)}))}var Fa,K0=[],pS=0,cS=0,nx=Number.MAX_SAFE_INTEGER;async function hS(e){return ne.initial&&(Fa=null),Fa?e.debug&&K("cached model:",Fa.modelUrl):Fa=await $e(e.face.ssrnet.modelPathAge),Fa}async function rx(e,t,a,n){var i,o,l,u;if(!Fa)return{age:0};let r=nx<(((i=t.face.ssrnet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.ssrnet)==null?void 0:o.skipTime)||0)>ae()-cS;return t.skipAllowed&&r&&s&&pS===n&&((l=K0[a])!=null&&l.age)&&((u=K0[a])==null?void 0:u.age)>0?(nx++,K0[a]):(nx=0,new Promise(async d=>{var h,m,f;if(!(Fa!=null&&Fa.inputs)||!Fa.inputs[0]||!Fa.inputs[0].shape)return;let c={};if(((h=t.face.ssrnet)==null?void 0:h.crop)>0){let g=(m=t.face.ssrnet)==null?void 0:m.crop,y=[[g,g,1-g,1-g]];c.resize=fe.cropAndResize(e,y,[0],[Fa.inputs[0].shape[2],Fa.inputs[0].shape[1]])}else c.resize=fe.resizeBilinear(e,[Fa.inputs[0].shape[2],Fa.inputs[0].shape[1]],!1);c.enhance=te(c.resize,ze.tf255);let p={age:0};if((f=t.face.ssrnet)!=null&&f.enabled&&(c.age=Fa.execute(c.enhance)),c.age){let g=await c.age.data();p.age=Math.trunc(10*g[0])/10}Object.keys(c).forEach(g=>J(c[g])),K0[a]=p,pS=n,cS=ae(),d(p)}))}var xa,Y0=[],fS=0,gS=0,sx=Number.MAX_SAFE_INTEGER,ix=[.2989,.587,.114];async function yS(e){var t;return ne.initial&&(xa=null),xa?e.debug&&K("cached model:",xa.modelUrl):xa=await $e((t=e.face.ssrnet)==null?void 0:t.modelPathGender),xa}async function ox(e,t,a,n){var i,o,l,u;if(!xa)return{gender:"unknown",genderScore:0};let r=sx<(((i=t.face.ssrnet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.ssrnet)==null?void 0:o.skipTime)||0)>ae()-gS;return t.skipAllowed&&r&&s&&fS===n&&((l=Y0[a])!=null&&l.gender)&&((u=Y0[a])==null?void 0:u.genderScore)>0?(sx++,Y0[a]):(sx=0,new Promise(async d=>{var m,f,g;if(!(xa!=null&&xa.inputs[0].shape))return;let c={};if(((m=t.face.ssrnet)==null?void 0:m.crop)>0){let y=(f=t.face.ssrnet)==null?void 0:f.crop,x=[[y,y,1-y,1-y]];c.resize=fe.cropAndResize(e,x,[0],[xa.inputs[0].shape[2],xa.inputs[0].shape[1]])}else c.resize=fe.resizeBilinear(e,[xa.inputs[0].shape[2],xa.inputs[0].shape[1]],!1);c.enhance=Pe(()=>{var x,A;let y;if(((A=(x=xa==null?void 0:xa.inputs)==null?void 0:x[0].shape)==null?void 0:A[3])===1){let[b,w,S]=Sa(c.resize,3,3),C=te(b,ix[0]),N=te(w,ix[1]),M=te(S,ix[2]),F=Uh([C,N,M]);y=te(xe(F,ze.tf05),2)}else y=te(xe(c.resize,ze.tf05),2);return y});let p={gender:"unknown",genderScore:0};(g=t.face.ssrnet)!=null&&g.enabled&&(c.gender=xa.execute(c.enhance));let h=await c.gender.data();p.gender=h[0]>h[1]?"female":"male",p.genderScore=h[0]>h[1]?Math.trunc(100*h[0])/100:Math.trunc(100*h[1])/100,Object.keys(c).forEach(y=>J(c[y])),Y0[a]=p,fS=n,gS=ae(),d(p)}))}var on,lx=[],AS=0,bS=0,vS=Number.MAX_SAFE_INTEGER;async function wS(e){var t;return ne.initial&&(on=null),on?e.debug&&K("cached model:",on.modelUrl):on=await $e((t=e.face.mobilefacenet)==null?void 0:t.modelPath),on}async function ux(e,t,a,n){var i,o;if(!(on!=null&&on.executor))return[];let r=vS<(((i=t.face.mobilefacenet)==null?void 0:i.skipFrames)||0),s=(((o=t.face.mobilefacenet)==null?void 0:o.skipTime)||0)>ae()-bS;return t.skipAllowed&&s&&r&&AS===n&&lx[a]?(vS++,lx[a]):new Promise(async l=>{var d;let u=[];if((d=t.face.mobilefacenet)!=null&&d.enabled&&(on!=null&&on.inputs[0].shape)){let c={};c.crop=fe.resizeBilinear(e,[on.inputs[0].shape[2],on.inputs[0].shape[1]],!1),c.data=on.execute(c.crop);let p=await c.data.data();u=Array.from(p),Object.keys(c).forEach(h=>J(c[h]))}lx[a]=u,AS=n,bS=ae(),l(u)})}var ln,dx=[],IS=0,SS=0,TS=Number.MAX_SAFE_INTEGER;async function CS(e){return ne.initial&&(ln=null),ln?e.debug&&K("cached model:",ln.modelUrl):ln=await $e(e.face.insightface.modelPath),ln}async function px(e,t,a,n){var i,o;if(!(ln!=null&&ln.executor))return[];let r=TS<(((i=t.face.insightface)==null?void 0:i.skipFrames)||0),s=(((o=t.face.insightface)==null?void 0:o.skipTime)||0)>ae()-SS;return t.skipAllowed&&s&&r&&IS===n&&dx[a]?(TS++,dx[a]):new Promise(async l=>{var d;let u=[];if((d=t.face.insightface)!=null&&d.enabled&&(ln!=null&&ln.inputs[0].shape)){let c={};c.crop=fe.resizeBilinear(e,[ln.inputs[0].shape[2],ln.inputs[0].shape[1]],!1),c.data=ln.execute(c.crop);let p=await 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y=f[1]*g[2]-f[2]*g[1],x=f[2]*g[0]-f[0]*g[2],A=f[0]*g[1]-f[1]*g[0];return[y,x,A]},s=f=>{let[g,y,x,A,b,w,S,C,N]=f,M,F,E;return A<1?A>-1?(E=Math.asin(A),F=Math.atan2(-S,g),M=Math.atan2(-w,b)):(E=-Math.PI/2,F=-Math.atan2(C,N),M=0):(E=Math.PI/2,F=Math.atan2(C,N),M=0),Number.isNaN(M)&&(M=0),Number.isNaN(F)&&(F=0),Number.isNaN(E)&&(E=0),{pitch:2*-M,yaw:2*-F,roll:2*-E}},i=e.meshRaw;if(!i||i.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let o=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[i[10],i[152],i[234],i[454]].map(f=>[f[0]*t[0]/o,f[1]*t[1]/o,f[2]]),u=a(n(l[1],l[0])),d=a(n(l[3],l[2])),c=a(r(d,u));d=r(u,c);let p=[d[0],d[1],d[2],u[0],u[1],u[2],c[0],c[1],c[2]],h=s(p),m=i.length===478?Bye(e):{bearing:0,strength:0};return{angle:h,matrix:p,gaze:m}};function ES(e,t){let a=e==null?void 0:e.annotations;if(!(a!=null&&a.leftEyeIris)||!(a!=null&&a.rightEyeIris))return 0;let 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u={};u.box=_e(n.norm,[l,0],[1,-1]),u.slice=_e(n.predictions,[l,5],[1,14]),u.norm=this.normalizeLandmarks(u.slice,l),u.palmLandmarks=Q(u.norm,[-1,2]);let d=await u.box.data(),c=d.slice(0,2),p=d.slice(2,4),h=await u.palmLandmarks.array(),m={startPoint:c,endPoint:p,palmLandmarks:h,confidence:r[l]},f=jS(m,[(t.shape[2]||1)/this.inputSize,(t.shape[1]||0)/this.inputSize]);i.push(f),Object.keys(u).forEach(g=>J(u[g]))}return Object.keys(n).forEach(l=>J(n[l])),i}};var txe=5,ZS=1.65,JS=[0,5,9,13,17,1,2],axe=0,nxe=2,QS=0,am=class{constructor(t,a){he(this,"handDetector");he(this,"handPoseModel");he(this,"inputSize");he(this,"storedBoxes");he(this,"skipped");he(this,"detectedHands");var n,r,s;this.handDetector=t,this.handPoseModel=a,this.inputSize=((s=(r=(n=this.handPoseModel)==null?void 0:n.inputs)==null?void 0:r[0].shape)==null?void 0:s[2])||0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let a=t.map(i=>i[0]),n=t.map(i=>i[1]),r=[Math.min(...a),Math.min(...n)],s=[Math.max(...a),Math.max(...n)];return{startPoint:r,endPoint:s}}getBoxForPalmLandmarks(t,a){let n=t.map(s=>gx([...s,1],a)),r=this.calculateLandmarksBoundingBox(n);return Q0(em(r),txe)}getBoxForHandLandmarks(t){let a=this.calculateLandmarksBoundingBox(t),n=Q0(em(a),ZS);n.palmLandmarks=[];for(let r=0;r[i[0]*(h[0]-this.inputSize/2),i[1]*(h[1]-this.inputSize/2),i[2]*h[2]]),l=fx(n,[0,0]),u=o.map(h=>[...gx(h,l),h[2]]),d=XS(r),c=[...yc(a),1],p=[ai(c,d[0]),ai(c,d[1])];return u.map(h=>[Math.trunc(h[0]+p[0]),Math.trunc(h[1]+p[1]),Math.trunc(h[2])])}async estimateHands(t,a){let n=!1,r,s=(a.hand.skipTime||0)>ae()-QS,i=this.skipped<(a.hand.skipFrames||0);a.skipAllowed&&s&&i?this.skipped++:(r=await this.handDetector.predict(t,a),this.skipped=0),r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==a.hand.maxDetected||!a.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let o=[];for(let l=0;l=a.hand.minConfidence/4){let w=Q(A,[-1,3]),S=await w.array();J(A),J(w);let C=this.transformRawCoords(S,f,d,m),N=this.getBoxForHandLandmarks(C);this.storedBoxes[l]={...N,confidence:b};let M={landmarks:C,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:N.startPoint,bottomRight:N.endPoint}};o.push(M)}else this.storedBoxes[l]=null;J(A)}else{let d=Q0(em(u),ZS),c={confidence:u.confidence,boxConfidence:u.confidence,fingerConfidence:0,box:{topLeft:d.startPoint,bottomRight:d.endPoint},landmarks:[]};o.push(c)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=o.length,o.length>a.hand.maxDetected&&(o.length=a.hand.maxDetected),o}};var eT={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},El,Ml,yx;function sxe(){let e=El?new tm(El):void 0;e&&Ml&&(yx=new am(e,Ml))}async function xx(e,t){yx||sxe();let a=await yx.estimateHands(e,t);if(!a)return[];let n=[];for(let r=0;ra[r].landmarks[c]);let i=a[r].landmarks,o=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(i&&i.length>0){for(let d of i)d[0]o[2]&&(o[2]=d[0]),d[1]>o[3]&&(o[3]=d[1]);o[2]-=o[0],o[3]-=o[1],l=[o[0]/(e.shape[2]||0),o[1]/(e.shape[1]||0),o[2]/(e.shape[2]||0),o[3]/(e.shape[1]||0)]}else o=a[r].box?[Math.trunc(Math.max(0,a[r].box.topLeft[0])),Math.trunc(Math.max(0,a[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,a[r].box.bottomRight[0])-Math.max(0,a[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,a[r].box.bottomRight[1])-Math.max(0,a[r].box.topLeft[1]))]:[0,0,0,0],l=[a[r].box.topLeft[0]/(e.shape[2]||0),a[r].box.topLeft[1]/(e.shape[1]||0),(a[r].box.bottomRight[0]-a[r].box.topLeft[0])/(e.shape[2]||0),(a[r].box.bottomRight[1]-a[r].box.topLeft[1])/(e.shape[1]||0)];let u=Z0(i);n.push({id:r,score:Math.round(100*a[r].confidence)/100,boxScore:Math.round(100*a[r].boxConfidence)/100,fingerScore:Math.round(100*a[r].fingerConfidence)/100,label:"hand",box:o,boxRaw:l,keypoints:i,annotations:s,landmarks:u})}return n}async function tT(e){var t;return ne.initial&&(El=null),El?e.debug&&K("cached model:",El.modelUrl):El=await $e((t=e.hand.detector)==null?void 0:t.modelPath),El}async function aT(e){var t;return ne.initial&&(Ml=null),Ml?e.debug&&K("cached model:",Ml.modelUrl):Ml=await $e((t=e.hand.skeleton)==null?void 0:t.modelPath),Ml}var zt=[null,null],ixe=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],ni=[[0,0],[0,0]],oxe=["hand","fist","pinch","point","face","tip","pinchtip"],rT=4,sT=1.6,lxe=512,uxe=1.4,nm=Number.MAX_SAFE_INTEGER,Ax=0,Wr=[0,0],Ot={boxes:[],hands:[]},iT={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function oT(e){var t;if(ne.initial&&(zt[0]=null),zt[0])e.debug&&K("cached model:",zt[0].modelUrl);else{T0(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),zt[0]=await $e((t=e.hand.detector)==null?void 0:t.modelPath);let a=zt[0].executor?Object.values(zt[0].modelSignature.inputs):void 0;ni[0][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,ni[0][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return zt[0]}async function lT(e){var t;if(ne.initial&&(zt[1]=null),zt[1])e.debug&&K("cached model:",zt[1].modelUrl);else{zt[1]=await $e((t=e.hand.skeleton)==null?void 0:t.modelPath);let a=zt[1].executor?Object.values(zt[1].modelSignature.inputs):void 0;ni[1][0]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[1].size):0,ni[1][1]=Array.isArray(a)?parseInt(a[0].tensorShape.dim[2].size):0}return zt[1]}async function dxe(e,t){let a=[];if(!e||!zt[0])return a;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),s=Math.min(Math.round((e.shape[1]||0)/8)*8,lxe),i=Math.round(s*r/8)*8;n.resize=fe.resizeBilinear(e,[s,i]),n.cast=Ue(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await zt[0].executeAsync(n.cast,ixe),n.boxes=Oe(n.rawBoxes,[0,2]),n.scores=Oe(n.rawScores,[0]);let o=Na(n.scores,1);J(o[rT]),o.splice(rT,1),n.filtered=ca(o,1),J(o),n.max=fa(n.filtered,1),n.argmax=or(n.filtered,1);let l=0;n.nms=await fe.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let u=await n.nms.data(),d=await n.max.data(),c=await n.argmax.data();for(let p of Array.from(u)){let h=_e(n.boxes,p,1),m=await h.data();J(h);let f=[m[1],m[0],m[3]-m[1],m[2]-m[0]],g=P0(f,uxe),y=[Math.trunc(f[0]*Wr[0]),Math.trunc(f[1]*Wr[1]),Math.trunc(f[2]*Wr[0]),Math.trunc(f[3]*Wr[1])],x=d[p],A=oxe[c[p]],b={id:l++,score:x,box:y,boxRaw:g,label:A};a.push(b)}return Object.keys(n).forEach(p=>J(n[p])),a.sort((p,h)=>h.score-p.score),a.length>(t.hand.maxDetected||1)&&(a.length=t.hand.maxDetected||1),a}async function bx(e,t,a){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&zt[1]&&a.hand.landmarks&&t.score>(a.hand.minConfidence||0)){let r={},s=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=fe.cropAndResize(e,[s],[0],[ni[1][0],ni[1][1]],"bilinear"),r.div=ve(r.crop,ze.tf255),[r.score,r.keypoints]=zt[1].execute(r.div,["Identity_1","Identity"]);let i=(await r.score.data())[0],o=(100-Math.trunc(100/(1+Math.exp(i))))/100;if(o>=(a.hand.minConfidence||0)){n.fingerScore=o,r.reshaped=Q(r.keypoints,[-1,3]);let d=(await r.reshaped.array()).map(c=>[c[0]/ni[1][1],c[1]/ni[1][0],c[2]||0]).map(c=>[c[0]*t.boxRaw[2],c[1]*t.boxRaw[3],c[2]||0]);n.keypoints=d.map(c=>[Wr[0]*(c[0]+t.boxRaw[0]),Wr[1]*(c[1]+t.boxRaw[1]),c[2]||0]),n.landmarks=Z0(n.keypoints);for(let c of Object.keys(iT))n.annotations[c]=iT[c].map(p=>n.landmarks&&n.keypoints[p]?n.keypoints[p]:null)}Object.keys(r).forEach(l=>J(r[l]))}return n}async function vx(e,t){var r,s;if(!((r=zt[0])!=null&&r.executor)||!((s=zt[1])!=null&&s.executor)||!zt[0].inputs[0].shape||!zt[1].inputs[0].shape)return[];Wr=[e.shape[2]||0,e.shape[1]||0],nm++;let a=(t.hand.skipTime||0)>ae()-Ax,n=nm<(t.hand.skipFrames||0);return t.skipAllowed&&a&&n?Ot.hands:new Promise(async i=>{let o=3*(t.hand.skipTime||0)>ae()-Ax,l=nm<3*(t.hand.skipFrames||0);t.skipAllowed&&Ot.hands.length===t.hand.maxDetected?Ot.hands=await Promise.all(Ot.boxes.map(d=>bx(e,d,t))):t.skipAllowed&&o&&l&&Ot.hands.length>0?Ot.hands=await Promise.all(Ot.boxes.map(d=>bx(e,d,t))):(Ot.boxes=await dxe(e,t),Ax=ae(),Ot.hands=await Promise.all(Ot.boxes.map(d=>bx(e,d,t))),nm=0);let u=[...Ot.boxes];if(Ot.boxes.length=0,t.cacheSensitivity>0)for(let d=0;d.05&&c.box[3]/(e.shape[1]||1)>.05&&Ot.hands[d].fingerScore&&Ot.hands[d].fingerScore>(t.hand.minConfidence||0)){let p=P0(c.box,sT),h=P0(c.boxRaw,sT);Ot.boxes.push({...u[d],box:p,boxRaw:h})}}for(let d=0;d({face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,width:0,height:0,error:e});var xc={};vr(xc,{connected:()=>sm,horizontal:()=>wx,kpt:()=>rm,relative:()=>Ix,vertical:()=>kx});var rm=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],wx=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],kx=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],Ix=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],sm={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ae=fr(),Sx=0;function dT(e,t){var i,o,l,u,d,c,p,h,m,f,g,y,x,A,b,w,S,C,N,M,F,E,T,D,O,W;let a=ae();if(!e)return fr();let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(Ae.canvas=e.canvas),e.error&&(Ae.error=e.error),!Ae.body||e.body.length!==Ae.body.length)Ae.body=JSON.parse(JSON.stringify(e.body));else for(let $=0;$((r-1)*Ae.body[$].box[X]+Z)/r),G=e.body[$].boxRaw.map((Z,X)=>((r-1)*Ae.body[$].boxRaw[X]+Z)/r),q=e.body[$].keypoints.map((Z,X)=>{var re,ee,ge,ie,be,Ce,Ee,Le,qe;return{score:Z.score,part:Z.part,position:[Ae.body[$].keypoints[X]?((r-1)*(Ae.body[$].keypoints[X].position[0]||0)+(Z.position[0]||0))/r:Z.position[0],Ae.body[$].keypoints[X]?((r-1)*(Ae.body[$].keypoints[X].position[1]||0)+(Z.position[1]||0))/r:Z.position[1],Ae.body[$].keypoints[X]?((r-1)*(Ae.body[$].keypoints[X].position[2]||0)+(Z.position[2]||0))/r:Z.position[2]],positionRaw:[Ae.body[$].keypoints[X]?((r-1)*(Ae.body[$].keypoints[X].positionRaw[0]||0)+(Z.positionRaw[0]||0))/r:Z.positionRaw[0],Ae.body[$].keypoints[X]?((r-1)*(Ae.body[$].keypoints[X].positionRaw[1]||0)+(Z.positionRaw[1]||0))/r:Z.positionRaw[1],Ae.body[$].keypoints[X]?((r-1)*(Ae.body[$].keypoints[X].positionRaw[2]||0)+(Z.positionRaw[2]||0))/r:Z.positionRaw[2]],distance:[Ae.body[$].keypoints[X]?((r-1)*(((re=Ae.body[$].keypoints[X].distance)==null?void 0:re[0])||0)+(((ee=Z.distance)==null?void 0:ee[0])||0))/r:(ge=Z.distance)==null?void 0:ge[0],Ae.body[$].keypoints[X]?((r-1)*(((ie=Ae.body[$].keypoints[X].distance)==null?void 0:ie[1])||0)+(((be=Z.distance)==null?void 0:be[1])||0))/r:(Ce=Z.distance)==null?void 0:Ce[1],Ae.body[$].keypoints[X]?((r-1)*(((Ee=Ae.body[$].keypoints[X].distance)==null?void 0:Ee[2])||0)+(((Le=Z.distance)==null?void 0:Le[2])||0))/r:(qe=Z.distance)==null?void 0:qe[2]]}}),H={},V={connected:{}};(i=t.body.modelPath)!=null&&i.includes("efficientpose")?V=z0:(o=t.body.modelPath)!=null&&o.includes("blazepose")?V=$0:(l=t.body.modelPath)!=null&&l.includes("movenet")&&(V=xc);for(let[Z,X]of Object.entries(V.connected)){let re=[];for(let ee=0;eebe.part===X[ee]),ie=q.find(be=>be.part===X[ee+1]);ge&&ie&&re.push([ge.position,ie.position])}H[Z]=re}Ae.body[$]={...e.body[$],box:U,boxRaw:G,keypoints:q,annotations:H}}if(!Ae.hand||e.hand.length!==Ae.hand.length)Ae.hand=JSON.parse(JSON.stringify(e.hand));else for(let $=0;$((r-1)*Ae.hand[$].box[Z]+V)/r),G=e.hand[$].boxRaw.map((V,Z)=>((r-1)*Ae.hand[$].boxRaw[Z]+V)/r);Ae.hand[$].keypoints.length!==e.hand[$].keypoints.length&&(Ae.hand[$].keypoints=e.hand[$].keypoints);let q=e.hand[$].keypoints&&e.hand[$].keypoints.length>0?e.hand[$].keypoints.map((V,Z)=>V.map((X,re)=>((r-1)*(Ae.hand[$].keypoints[Z][re]||1)+(X||0))/r)):[],H={};if(Object.keys(Ae.hand[$].annotations).length!==Object.keys(e.hand[$].annotations).length)Ae.hand[$].annotations=e.hand[$].annotations,H=Ae.hand[$].annotations;else if(e.hand[$].annotations)for(let V of Object.keys(e.hand[$].annotations))H[V]=(c=(d=(u=e.hand[$])==null?void 0:u.annotations)==null?void 0:d[V])!=null&&c[0]?e.hand[$].annotations[V].map((Z,X)=>Z.map((re,ee)=>((r-1)*Ae.hand[$].annotations[V][X][ee]+re)/r)):null;Ae.hand[$]={...e.hand[$],box:U,boxRaw:G,keypoints:q,annotations:H}}if(!Ae.face||e.face.length!==Ae.face.length)Ae.face=JSON.parse(JSON.stringify(e.face));else for(let $=0;$((r-1)*Ae.face[$].box[V]+H)/r),G=e.face[$].boxRaw.map((H,V)=>((r-1)*Ae.face[$].boxRaw[V]+H)/r),q=e.face[$].annotations;if(Object.keys(Ae.face[$].annotations).length!==Object.keys(e.face[$].annotations).length)Ae.face[$].annotations=e.face[$].annotations,q=Ae.face[$].annotations;else if(e.face[$].annotations)for(let H of Object.keys(e.face[$].annotations))q[H]=(m=(h=(p=e.face[$])==null?void 0:p.annotations)==null?void 0:h[H])!=null&&m[0]?e.face[$].annotations[H].map((V,Z)=>V.map((X,re)=>((r-1)*Ae.face[$].annotations[H][Z][re]+X)/r)):null;if(e.face[$].rotation){let H={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};H.matrix=(f=e.face[$].rotation)==null?void 0:f.matrix,H.angle={roll:((r-1)*(((y=(g=Ae.face[$].rotation)==null?void 0:g.angle)==null?void 0:y.roll)||0)+(((A=(x=e.face[$].rotation)==null?void 0:x.angle)==null?void 0:A.roll)||0))/r,yaw:((r-1)*(((w=(b=Ae.face[$].rotation)==null?void 0:b.angle)==null?void 0:w.yaw)||0)+(((C=(S=e.face[$].rotation)==null?void 0:S.angle)==null?void 0:C.yaw)||0))/r,pitch:((r-1)*(((M=(N=Ae.face[$].rotation)==null?void 0:N.angle)==null?void 0:M.pitch)||0)+(((E=(F=e.face[$].rotation)==null?void 0:F.angle)==null?void 0:E.pitch)||0))/r},H.gaze={bearing:((r-1)*(((T=Ae.face[$].rotation)==null?void 0:T.gaze.bearing)||0)+(((D=e.face[$].rotation)==null?void 0:D.gaze.bearing)||0))/r,strength:((r-1)*(((O=Ae.face[$].rotation)==null?void 0:O.gaze.strength)||0)+(((W=e.face[$].rotation)==null?void 0:W.gaze.strength)||0))/r},Ae.face[$]={...e.face[$],rotation:H,box:U,boxRaw:G,annotations:q}}else Ae.face[$]={...e.face[$],box:U,boxRaw:G,annotations:q}}if(!Ae.object||e.object.length!==Ae.object.length)Ae.object=JSON.parse(JSON.stringify(e.object));else for(let $=0;$((r-1)*Ae.object[$].box[H]+q)/r),G=e.object[$].boxRaw.map((q,H)=>((r-1)*Ae.object[$].boxRaw[H]+q)/r);Ae.object[$]={...e.object[$],box:U,boxRaw:G}}if(e.persons){let 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a={};a.resize=fe.resizeBilinear(e,[Aa.inputs[0].shape?Aa.inputs[0].shape[1]:0,Aa.inputs[0].shape?Aa.inputs[0].shape[2]:0],!1),a.norm=ve(a.resize,ze.tf255),a.res=Aa.execute(a.norm),a.squeeze=Oe(a.res,[0]),[a.bgRaw,a.fgRaw]=Na(a.squeeze,2),a.fg=Yh(a.fgRaw),a.mul=te(a.fg,ze.tf255),a.expand=Bt(a.mul,2),a.output=fe.resizeBilinear(a.expand,[e.shape[1]||0,e.shape[2]||0]);let n;switch(t.segmentation.mode||"default"){case"default":a.input=Oe(e),a.concat=lt([a.input,a.output],-1),n=Ue(a.concat,"int32");break;case"alpha":n=Ue(a.output,"int32");break;default:n=Ve(0)}return Object.keys(a).forEach(s=>J(a[s])),n}var im={};vr(im,{distance:()=>Cx,find:()=>hxe,similarity:()=>cxe});function Cx(e,t,a={order:2,multiplier:25}){if(!e||!e)return Number.MAX_SAFE_INTEGER;let n=0;for(let r=0;r{if(e===0)return 1;let s=(1-(t===2?Math.sqrt(e):e**(1/t))/100-a)/(n-a);return Math.max(Math.min(s,1),0)};function cxe(e,t,a={order:2,multiplier:25,min:.2,max:.8}){let n=Cx(e,t,a);return 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state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models.models).filter(i=>i).length!==n&&(this.models.validate(),this.emit("load"));let s=Math.trunc(ae()-a);s>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+s:s)}next(t=this.result){return dT(t,this.config)}async warmup(t){let a=ae(),n=await zT(this,t),r=ae();return this.performance.warmup=Math.trunc(r-a),n}async profile(t,a){let n=await this.tf.profile(()=>this.detect(t,a)),r={},s=0;for(let o of n.kernels){let l=Number(o.kernelTimeMs)||0;r[o.name]?r[o.name]+=l:r[o.name]=l,s+=l}let i=[];Object.entries(r).forEach(o=>i.push({kernel:o[0],time:o[1],perc:0}));for(let o of i)o.perc=Math.round(1e3*o.time/s)/1e3,o.time=Math.round(1e3*o.time)/1e3;return i.sort((o,l)=>l.time-o.time),i.length=20,i}async detect(t,a){return this.state="detect",new Promise(async n=>{var g,y,x,A,b,w,S,C,N,M,F,E,T,D,O,W,$,U,G,q,H;this.state="config";let r;this.config=Mt(this.config,a),this.state="check";let s=Xa(this,gm).call(this,t);s&&(K(s,t),this.emit("error"),n(fr(s)));let i=ae();await this.load(),r=ae(),this.state="image";let o=await k0(t,this.config);if(this.process=o,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(ae()-r):Math.trunc(ae()-r),this.analyze("Get Image:"),!o.tensor){this.config.debug&&K("could not convert input to tensor"),this.emit("error"),n(fr("could not convert input to tensor"));return}this.emit("image"),r=ae(),this.config.skipAllowed=await q9(this.config,o.tensor),this.config.filter.autoBrightness=(this.config.filter.autoBrightness||!1)&&this.config.skipAllowed,this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(ae()-r):Math.trunc(ae()-r),this.analyze("Check Changed:");let l=[],u=[],d=[],c=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?cx(this,o.tensor):[],this.performance.face&&delete this.performance.face):(r=ae(),l=this.config.face.enabled?await cx(this,o.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(l=await l),this.analyze("Start Body:"),this.state="detect:body";let p=this.config.body.maxDetected===-1?Mt(this.config,{body:{maxDetected:this.config.face.enabled?1*l.length:1}}):this.config;this.config.async?((g=this.config.body.modelPath)!=null&&g.includes("posenet")?u=this.config.body.enabled?Ox(o.tensor,p):[]:(y=this.config.body.modelPath)!=null&&y.includes("blazepose")?u=this.config.body.enabled?Ry(o.tensor,p):[]:(x=this.config.body.modelPath)!=null&&x.includes("efficientpose")?u=this.config.body.enabled?_y(o.tensor,p):[]:(A=this.config.body.modelPath)!=null&&A.includes("movenet")&&(u=this.config.body.enabled?Ex(o.tensor,p):[]),this.performance.body&&delete this.performance.body):(r=ae(),(b=this.config.body.modelPath)!=null&&b.includes("posenet")?u=this.config.body.enabled?await Ox(o.tensor,p):[]:(w=this.config.body.modelPath)!=null&&w.includes("blazepose")?u=this.config.body.enabled?await Ry(o.tensor,p):[]:(S=this.config.body.modelPath)!=null&&S.includes("efficientpose")?u=this.config.body.enabled?await _y(o.tensor,p):[]:(C=this.config.body.modelPath)!=null&&C.includes("movenet")&&(u=this.config.body.enabled?await Ex(o.tensor,p):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let h=this.config.hand.maxDetected===-1?Mt(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((M=(N=this.config.hand.detector)==null?void 0:N.modelPath)!=null&&M.includes("handdetect")?d=this.config.hand.enabled?xx(o.tensor,h):[]:(E=(F=this.config.hand.detector)==null?void 0:F.modelPath)!=null&&E.includes("handtrack")&&(d=this.config.hand.enabled?vx(o.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=ae(),(D=(T=this.config.hand.detector)==null?void 0:T.modelPath)!=null&&D.includes("handdetect")?d=this.config.hand.enabled?await xx(o.tensor,h):[]:(W=(O=this.config.hand.detector)==null?void 0:O.modelPath)!=null&&W.includes("handtrack")&&(d=this.config.hand.enabled?await vx(o.tensor,h):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?(($=this.config.object.modelPath)!=null&&$.includes("nanodet")?c=this.config.object.enabled?Fx(o.tensor,this.config):[]:(U=this.config.object.modelPath)!=null&&U.includes("centernet")&&(c=this.config.object.enabled?Fy(o.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=ae(),(G=this.config.object.modelPath)!=null&&G.includes("nanodet")?c=this.config.object.enabled?await Fx(o.tensor,this.config):[]:(q=this.config.object.modelPath)!=null&&q.includes("centernet")&&(c=this.config.object.enabled?await Fy(o.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,u,d,c]=await Promise.all([l,u,d,c])),this.state="detect:gesture";let m=[];this.config.gesture.enabled&&(r=ae(),m=[...WS(l),...LS(u),...VS(d),...BS(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(ae()-r):Math.trunc(ae()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(ae()-i):Math.trunc(ae()-i);let f=((H=this.process.tensor)==null?void 0:H.shape)||[0,0,0,0];this.result={face:l,body:u,hand:d,gesture:m,object:c,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,width:f[2],height:f[1],get persons(){return OT(l,u,d,m,f)}},J(o.tensor),this.emit("detect"),this.state="idle",n(this.result)})}async sleep(t){return new Promise(a=>{setTimeout(a,t)})}async video(t,a=!0,n=0){a?(Xa(this,ri)[t.id]||(this.config.debug&&K("video start",t.id),Xa(this,ri)[t.id]=!0),!t.paused&&Xa(this,ri)[t.id]&&t.readyState>=2&&await this.detect(t),n>0&&await this.sleep(n),Xa(this,ri)[t.id]&&requestAnimationFrame(()=>this.video(t,a,n))):(this.config.debug&&K("video stop",t.id),Xa(this,ri)[t.id]=!1)}};Ad=new WeakMap,wc=new WeakMap,kc=new WeakMap,gm=new WeakMap,ri=new WeakMap;return kC(zxe);})();