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vendor: 9,231 bytes, line 2
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2s.forEach(e=>{e.kept||-1!==i.indexOf(e.id)||e.dispose()});let c=o;for(;u[0];){const e=c;c=await n.functionMap[r].executeFunctionAsync(c,n.tensorArrayMap,n.tensorListMap);const t=c.map(e=>e.id);e.forEach(e=>{e.kept||-1!==i.indexOf(e.id)||-1!==t.indexOf(e.id)||e.dispose()});const o=await n.functionMap[a].executeFunctionAsync(c,n.tensorArrayMap,n.tensorListMap);u=await o[0].data(),o.forEach(e=>{e.kept||-1!==i.indexOf(e.id)||-1!==t.indexOf(e.id)||e.dispose()})}return c}case"LoopCond":return[F(N("pred",e,t,n))];case"Switch":{const r=N("pred",e,t,n);let a=N("data",e,t,n);return a.kept||(a=F(a)),(await r.data())[0]?[void 0,a]:[a,void 0]}case"Merge":{const r=e.inputNames.find(e=>void 0!==I(e,t,n));if(r){return[F(I(r,t,n))]}return}case"Enter":{const r=N("frameName",e,t,n),a=N("tensor",e,t,n);return n.enterFrame(r),[F(a)]}case"Exit":{const r=N("tensor",e,t,n);return n.exitFrame(),[F(r)]}case"NextIteration":{const r=N("tensor",e,t,n);return n.nextIteration(),[F(r)]}case"TensorArrayV3":{const r=N("size",e,t,n),a=N("dtype",e,t,n),o=N("elementShape",e,t,n),s=N("dynamicSize",e,t,n),i=N("clearAfterRead",e,t,n),u=N("identicalElementShapes",e,t,n),c=N("name",e,t,n),l=new we(c,a,r,o,u,s,i);return n.addTensorArray(l),[l.idTensor,(0,S.d_2)(1)]}case"TensorArrayWriteV3":{const r=N("tensorArrayId",e,t,n),a=N("index",e,t,n),o=N("tensor",e,t,n),s=n.getTensorArray(r.id);return s.write(a,o),[s.idTensor]}case"TensorArrayReadV3":{const r=N("tensorArrayId",e,t,n),a=N("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{const r=N("tensorArrayId",e,t,n),a=N("indices",e,t,n),o=N("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,o)]}case"TensorArrayScatterV3":{const r=N("tensorArrayId",e,t,n),a=N("indices",e,t,n),o=N("tensor",e,t,n),s=n.getTensorArray(r.id);return s.scatter(a,o),[s.idTensor]}case"TensorArrayConcatV3":{const r=N("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),o=N("dtype",e,t,n);return[a.concat(o)]}case"TensorArraySplitV3":{const r=N("tensorArrayId",e,t,n),a=N("tensor",e,t,n),o=N("lengths",e,t,n),s=n.getTensorArray(r.id);return s.split(o,a),[s.idTensor]}case"TensorArraySizeV3":{const r=N("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return[(0,S.d_2)(a.size(),"int32")]}case"TensorArrayCloseV3":{const r=N("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{const r=N("tensorListId",e,t,n),a=N("index",e,t,n),o=N("tensor",e,t,n),s=n.getTensorList(r.id);return s.setItem(a,o),[s.idTensor]}case"TensorListGetItem":{const r=N("tensorListId",e,t,n),a=N("index",e,t,n),o=N("elementShape",e,t,n),s=N("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,o,s)]}case"TensorListScatterV2":case"TensorListScatter":{const r=N("indices",e,t,n),a=function(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);const a=Math.max(...t);if(null!=r&&-1!==r&&a>=r)throw new Error(`Max index must be < array size (${a}  vs. ${r})`);const o=new Te([],n,e.dtype,r),s=(0,S.K$i)(e,0);return t.forEach((e,t)=>{o.setItem(e,s[t])}),o}(N("tensor",e,t,n),r,N("elementShape",e,t,n),N("numElements",e,t,n));return n.addTensorList(a),[a.idTensor]}case"TensorListReserve":case"EmptyTensorList":{const r=N("elementShape",e,t,n),a=N("elementDType",e,t,n);let o;o="TensorListReserve"===e.op?"numElements":"maxNumElements";const s=N(o,e,t,n),i=function(e,t,n,r){return new Te([],e,t,r)}(r,a,0,"TensorListReserve"===e.op?-1:s);return n.addTensorList(i),[i.idTensor]}case"TensorListGather":{const r=N("tensorListId",e,t,n),a=N("indices",e,t,n),o=N("elementShape",e,t,n),s=N("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,s,o)]}case"TensorListStack":{const r=N("tensorListId",e,t,n),a=N("elementShape",e,t,n),o=N("elementDType",e,t,n),s=N("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,o,s)]}case"TensorListFromTensor":{const r=function(e,t,n){const r=e.dtype;if(e.shape.length<1)throw new Error(`Tensor must be at least a vector, but saw shape: ${e.shape}`);if(e.dtype!==n)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${n}`);ye(e.shape.slice(1),t,"TensorList shape mismatch: ");const a=(0,S.K$i)(e);return new Te(a,t,r)}(N("tensor",e,t,n),N("elementShape",e,t,n),N("elementDType",e,t,n));return n.addTensorList(r),[r.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{const r=N("tensorListId",e,t,n),a=n.getTensorList(r.id),o=N("dtype",e,t,n),s=N("elementShape",e,t,n);return[a.concat(o,s)]}case"TensorListPushBack":{const r=N("tensorListId",e,t,n),a=N("tensor",e,t,n),o=n.getTensorList(r.id);return o.pushBack(a),[o.idTensor]}case"TensorListPopBack":{const r=N("tensorListId",e,t,n),a=N("elementShape",e,t,n),o=N("elementDType",e,t,n);return[n.getTensorList(r.id).popBack(a,o)]}case"TensorListSplit":{const r=N("tensor",e,t,n),a=N("elementShape",e,t,n),o=function(e,t,n){let r=0;const a=t.map(e=>(r+=e,r));if(r!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        ${r}, and tensor's shape is: ${e.shape}`);const o=ve(e.shape.slice(1),n),s=0===r?0:e.size/r,i=(0,S.DZQ)(()=>{const n=[];e=(0,S.tQQ)(e,[1,r,s]);for(let r=0;r<t.length;++r){const i=[0,0===r?0:a[r-1],0],u=[1,t[r],s];n[r]=(0,S.tQQ)((0,S.dik)(e,i,u),o)}return e.dispose(),n}),u=new Te([],n,e.dtype,t.length);for(let e=0;e<i.length;e++)u.setItem(e,i[e]);return u}(r,N("lengths",e,t,n),a);return n.addTensorList(o),[o.idTensor]}case"TensorListLength":{const r=N("tensorListId",e,t,n),a=n.getTensorList(r.id);return[(0,S.d_2)(a.size(),"int32")]}case"TensorListResize":{const r=N("tensorListId",e,t,n),a=N("size",e,t,n),o=n.getTensorList(r.id).resize(a);return n.addTensorList(o),[o.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Ce(e,t,n){const[r,a]=N("fusedOps",e,t,n),o="biasadd"===r,s=!o,i="prelu"===a,u="fusedbatchnorm"===r,c=N("numArgs",e,t,n);if(o){if(i&&2!==c)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&o&&1!==c)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(u)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported");const l=N("strides",e,t,n),p=O(e,t,n),h=N("dataFormat",e,t,n).toUpperCase(),d=N("dilations",e,t,n);let[f,m]=N("args",e,t,n);s&&(m=f,f=void 0);return{stride:l,pad:p,dataFormat:h,dilations:d,biasArg:f,preluArg:m,activationFunc:a,leakyreluAlpha:N("leakyreluAlpha",e,t,n)}}function ke(e,t,n){return{boxes:N("boxes",e,t,n),scores:N("scores",e,t,n),maxOutputSize:N("maxOutputSize",e,t,n),iouThreshold:N("iouThreshold",e,t,n),scoreThreshold:N("scoreThreshold",e,t,n),softNmsSigma:N("softNmsSigma",e,t,n)}}var Ee=n(45702);class $e{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=(0,S.d_2)(0),this.tensorMap=new Map,(0,S.aCs)(this.handle)}get id(){return this.handle.id}
vendor: 13,718 bytes, line 2
2clearAndClose(){this.tensorMap.forEach(e=>e.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return Ee.d(this.size(),"int32")}async import(e,t){this.checkKeyAndValueTensor(e,t);const n=await e.data();return this.tensorMap.forEach(e=>e.dispose()),this.tensorMap.clear(),(0,S.DZQ)(()=>{const e=(0,S.K$i)(t),r=n.length,a=e.length;S.ZSL.assert(r===a,()=>`The number of elements doesn't match, keys has ${r} elements, the values has ${a} elements.`);for(let t=0;t<r;t++){const r=n[t],a=e[t];(0,S.aCs)(a),this.tensorMap.set(r,a)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);const n=await e.data();return(0,S.DZQ)(()=>{const e=[];for(let r=0;r<n.length;r++){const a=n[r],o=this.findWithDefault(a,t);e.push(o)}return(0,S.t$z)(e)})}findWithDefault(e,t){const n=this.tensorMap.get(e);return null!=n?n:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got 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a=N("axis",e,t,n);return[r.argMax(N("x",e,t,n),a)]}case"ArgMin":{const a=N("axis",e,t,n);return[r.argMin(N("x",e,t,n),a)]}case"Prod":{const a=N("axis",e,t,n),o=N("keepDims",e,t,n);return[r.prod(N("x",e,t,n),a,o)]}case"Cumprod":{const a=N("axis",e,t,n),o=N("exclusive",e,t,n),s=N("reverse",e,t,n);return[r.cumprod(N("x",e,t,n),a,o,s)]}case"Cumsum":{const a=N("axis",e,t,n),o=N("exclusive",e,t,n),s=N("reverse",e,t,n);return[r.cumsum(N("x",e,t,n),a,o,s)]}case"Bincount":const a=N("x",e,t,n),o=N("weights",e,t,n),s=N("size",e,t,n);return[r.bincount(a,o,s)];case"DenseBincount":{const a=N("x",e,t,n),o=N("weights",e,t,n),s=N("size",e,t,n),i=N("binaryOutput",e,t,n);return[r.denseBincount(a,o,s,i)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n));case"slice_join":return a(()=>((e,t,n,r=T)=>{switch(e.op){case"ConcatV2":case"Concat":{const a=N("n",e,t,n),o=N("axis",e,t,n);let s=N("tensors",e,t,n);return s=s.slice(0,a),[r.concat(s,o)]}case"Gather":{const a=N("x",e,t,n),o=N("indices",e,t,n);return[r.gather(a,r.cast(o,"int32"),0)]}case"GatherV2":{const a=N("axis",e,t,n),o=N("batchDims",e,t,n),s=N("x",e,t,n),i=N("indices",e,t,n);return[r.gather(s,r.cast(i,"int32"),a,o)]}case"Reverse":{const a=N("dims",e,t,n),o=[];for(let e=0;e<a.length;e++)a[e]&&o.push(e);const s=N("x",e,t,n);return[r.reverse(s,o)]}case"ReverseV2":{const a=N("axis",e,t,n),o=N("x",e,t,n);return[r.reverse(o,a)]}case"Slice":{const a=N("begin",e,t,n),o=N("size",e,t,n);return[r.slice(N("x",e,t,n),a,o)]}case"StridedSlice":{const a=N("begin",e,t,n),o=N("end",e,t,n),s=N("strides",e,t,n),i=N("beginMask",e,t,n),u=N("endMask",e,t,n),c=N("ellipsisMask",e,t,n),l=N("newAxisMask",e,t,n),p=N("shrinkAxisMask",e,t,n),h=N("x",e,t,n);return[r.stridedSlice(h,a,o,s,i,u,c,l,p)]}case"Pack":return(0,S.DZQ)(()=>{const a=N("axis",e,t,n),o=N("tensors",e,t,n),s=o[0].shape,i=r.squeeze(o[0]).shape,u=o.map(e=>{const t=S.ZSL.arraysEqual(e.shape,s);if(!t&&!S.ZSL.arraysEqual(r.squeeze(e).shape,i))throw new Error("the input tensors shape does not match");return t?e:r.reshape(e,s)});return[r.stack(u,a)]});case"Unpack":{const a=N("axis",e,t,n),o=N("tensor",e,t,n);return r.unstack(o,a)}case"Tile":{const a=N("reps",e,t,n);return[r.tile(N("x",e,t,n),a)]}case"Split":case"SplitV":{const a=N("axis",e,t,n),o=N("numOrSizeSplits",e,t,n),s=N("x",e,t,n);return r.split(s,o,a)}case"ScatterNd":{const a=N("indices",e,t,n),o=N("values",e,t,n),s=N("shape",e,t,n);return[r.scatterND(a,o,s)]}case"GatherNd":{const a=N("x",e,t,n),o=N("indices",e,t,n);return[r.gatherND(a,o)]}case"SparseToDense":{const a=N("sparseIndices",e,t,n),o=N("outputShape",e,t,n),s=N("sparseValues",e,t,n),i=N("defaultValue",e,t,n);return[r.sparseToDense(a,s,o,s.dtype===i.dtype?i:r.cast(i,s.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n));case"sparse":return a(()=>((e,t,n,r=T)=>{switch(e.op){case"SparseFillEmptyRows":{const{outputIndices:a,outputValues:o,emptyRowIndicator:s,reverseIndexMap:i}=r.sparse.sparseFillEmptyRows(N("indices",e,t,n),N("values",e,t,n),N("denseShape",e,t,n),N("defaultValue",e,t,n));return[a,o,s,i]}case"SparseReshape":{const{outputIndices:a,outputShape:o}=r.sparse.sparseReshape(N("inputIndices",e,t,n),N("inputShape",e,t,n),N("newShape",e,t,n));return[a,o]}case"SparseSegmentMean":return[r.sparse.sparseSegmentMean(N("data",e,t,n),N("indices",e,t,n),N("segmentIds",e,t,n))];case"SparseSegmentSum":return[r.sparse.sparseSegmentSum(N("data",e,t,n),N("indices",e,t,n),N("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n));case"spectral":return a(()=>((e,t,n,r=T)=>{switch(e.op){case"FFT":return[r.fft(N("x",e,t,n))];case"IFFT":return[r.ifft(N("x",e,t,n))];case"RFFT":return[r.rfft(N("x",e,t,n))];case"IRFFT":return[r.irfft(N("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n));case"string":return a(()=>((e,t,n,r=T)=>{switch(e.op){case"StringNGrams":{const{nGrams:a,nGramsSplits:o}=r.string.stringNGrams(N("data",e,t,n),N("dataSplits",e,t,n),N("separator",e,t,n),N("nGramWidths",e,t,n),N("leftPad",e,t,n),N("rightPad",e,t,n),N("padWidth",e,t,n),N("preserveShortSequences",e,t,n));return[a,o]}case"StringSplit":{const{indices:a,values:o,shape:s}=r.string.stringSplit(N("input",e,t,n),N("delimiter",e,t,n),N("skipEmpty",e,t,n));return[a,o,s]}case"StringToHashBucketFast":return[r.string.stringToHashBucketFast(N("input",e,t,n),N("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n));case"transformation":return a(()=>((e,t,n,r=T)=>{switch(e.op){case"Cast":return[r.cast(N("x",e,t,n),N("dtype",e,t,n))];case"ExpandDims":{const a=N("axis",e,t,n);return[r.expandDims(N("x",e,t,n),a)]}case"Squeeze":{const a=N("axis",e,t,n);return[r.squeeze(N("x",e,t,n),a)]}case"Reshape":return[r.reshape(N("x",e,t,n),N("shape",e,t,n))];case"MirrorPad":return[r.mirrorPad(N("x",e,t,n),N("padding",e,t,n),N("mode",e,t,n))];case"PadV2":case"Pad":return[r.pad(N("x",e,t,n),N("padding",e,t,n),N("constantValue",e,t,n))];

2case"SpaceToBatchND":{const a=N("blockShape",e,t,n),o=N("paddings",e,t,n);return[r.spaceToBatchND(N("x",e,t,n),a,o)]}case"BatchToSpaceND":{const a=N("blockShape",e,t,n),o=N("crops",e,t,n);return[r.batchToSpaceND(N("x",e,t,n),a,o)]}case"DepthToSpace":{const a=N("blockSize",e,t,n),o=N("dataFormat",e,t,n).toUpperCase();return[r.depthToSpace(N("x",e,t,n),a,o)]}case"BroadcastTo":return[r.broadcastTo(N("x",e,t,n),N("shape",e,t,n))];case"BroadcastArgs":return[r.broadcastArgs(N("s0",e,t,n),N("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n));case"hash_table":return(async(e,t,n,r)=>{switch(e.op){case"HashTable":case"HashTableV2":{const a=N("keyDType",e,t,n),o=N("valueDType",e,t,n),s=new $e(a,o);return r.addHashTable(e.name,s),[s.handle]}case"LookupTableImport":case"LookupTableImportV2":{const a=N("tableHandle",e,t,n,r),o=N("keys",e,t,n),s=N("values",e,t,n),i=r.getHashTableById(a.id);return[await i.import(o,s)]}case"LookupTableFind":case"LookupTableFindV2":{const a=N("tableHandle",e,t,n,r),o=N("keys",e,t,n),s=N("defaultValue",e,t,n),i=r.getHashTableById(a.id);return[await i.find(o,s)]}case"LookupTableSize":case"LookupTableSizeV2":{const a=N("tableHandle",e,t,n,r);return[r.getHashTableById(a.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n,r);case"custom":const o=$(e.op);if(o&&o.customExecutor)return o.customExecutor(new me(e,t,n));throw TypeError(`Custom op ${e.op} is not registered.`);default:throw TypeError(`Unknown op '${e.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,n);return S.ZSL.isPromise(o)?o.then(e=>[].concat(e)):[].concat(o)}class Ie{constructor(e={},t={},n={},r={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=r,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){const e=[];for(let t=0;t<this.contexts.length-1;t++){const n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(e=>0===e.id&&0===e.iterationId?"":`${e.frameName}-${e.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(!(this.contexts&&this.contexts.length>1))throw new Error("Cannot exit frame, the context is empty");this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift()}nextIteration(){if(!(this.contexts&&this.contexts.length>0))throw new Error("Cannot increase frame iteration, the context is empty");{this.contexts=this.contexts.slice(),this.lastId++;const e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(const t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(const t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}}function Ae(e,t,n,r){const a=new Set,o=[];let s=null,i=null;const u=new Set,c=Object.keys(e).map(e=>_(e)[0]);let l=[];null!=r&&(l=r.map(e=>_(e.name)[0]));const p=[...t];for(;p.length>0;){const e=p.pop();(Fe(e)||De(e)||Le(e))&&null==s&&(s=e,i=s.children.map(e=>e.name).filter(e=>a.has(e))),a.add(e.name),null==n[e.name]&&(-1===c.indexOf(e.name)&&-1===l.indexOf(e.name)&&(0!==e.inputs.length?e.inputs.forEac

2h(e=>{u.has(e.name)||(u.add(e.name),p.push(e))}):o.push(e.name)))}return{inputs:e,outputs:t,usedNodes:a,missingInputs:o,dynamicNode:s,syncInputs:i}}const Re=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],_e=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],Oe=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function Fe(e){return Re.indexOf(e.op)>=0}function De(e){return _e.indexOf(e.op)>=0}function Le(e){return Oe.indexOf(e.op)>=0}class Me{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,null!=e.functions&&Object.keys(e.functions).forEach(t=>{this._functionExecutorMap[t]=new Me(e.functions[t],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){const t=Object.keys(e).map(t=>e[t].map(e=>e.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{const t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){const n=e.map(e=>e.name).sort(),r=t.map(e=>e.name).sort();return n.join(this.SEPERATOR)+"--"+r.join(this.SEPERATOR)}compile(e,t){const n=Ae(e,t,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:a,syncInputs:o}=n;if(null!=a)throw new Error(`This execution contains the node '${a.name}', which has the dynamic op '${a.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${o}]`);if(r.length>0){const n=t.map(e=>e.name),a=Object.keys(e);throw new Error(`Cannot compute the outputs [${n}] from the provided inputs [${a}]. Missing the following inputs: [${r}]`)}return function(e,t,n){const{usedNodes:r,inputs:a}=n,o=[],s=Object.keys(a).map(e=>_(e)[0]).map(t=>e.nodes[t]),i=e.initNodes;s.forEach(e=>{r.has(e.name)&&o.push(e)}),e.weights.forEach(e=>{r.has(e.name)&&o.push(e)}),null!=i&&i.forEach(e=>{r.has(e.name)&&o.push(e)});const u=new Set,c=[];for(;o.length>0;){const e=o.pop();u.add(e.name),t[e.name]||c.push(e),e.children.forEach(e=>{!u.has(e.name)&&r.has(e.name)&&e.inputs.every(e=>u.has(e.name))&&o.push(e)})}return c}(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);const n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);const r=n.map(e=>this.graph.nodes[_(e)[0]]),a=t.map(e=>_(e)[0]);let o=a.map(e=>this.graph.nodes[e]);this.resetIntermediateTensors(),0===o.length&&(o=this._outputs);const s=this.getCompilationKey(r,o);let i=this.compiledMap.get(s);null==i&&(i=this.compile(e,o),this.compiledMap.set(s,i));const u={},c={};return(0,S.DZQ)(()=>{const n=new Ie(this.weightMap,u,c,this.functionExecutorMap),r=Object.assign({},this.weightMap);Object.keys(e).forEach(t=>{const[n,a]=_(t),o=[];o[a]=e[t],r[n]=o});const o=this.getFrozenTensorIds(r),s={};for(let e=0;e<i.length;e++){const t=i[e];if(!r[t.name]){const e=Ne(t,r,n,this._resourceManager);if(S.ZSL.isPromise(e))throw new Error(`The execution of the op '${t.op}' returned a promise. Please use model.executeAsync() instead.`);r[t.name]=e,this.checkTensorForDisposal(t.name,t,r,n,o,a,s)}}return null==this.parent&&n.dispose(o),t.map(e=>I(e,r,n))})}getFrozenTensorIds(e){const t=[].concat.apply([],Object.keys(e).map(t=>e[t]).map(e=>e.map(e=>e.id)));return new Set(t)}checkTensorForDisposal(e,t,n,r,a,o,s){"control"!==t.category&&-1===o.indexOf(e)&&(n[e].forEach(e

2=>{null!=e&&(s[e.id]=(s[e.id]||0)+t.children.length)}),t.inputs.forEach(e=>{if("control"!==e.category){const o=function(e,t,n){return t[R(e,n.currentContextId)]}(e.name,n,r);null!=o&&o.forEach(e=>{if(e&&!e.kept&&!a.has(e.id)){const n=s[e.id];if(1===n){if(this.keepTensorForDebug){const[n,a]=A(t.name,r);this.intermediateTensors[n]||(this.intermediateTensors[n]=[]),this.intermediateTensors[n][a]=e}else e.dispose();delete s[e.id]}else null!=n&&s[e.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){this.intermediateTensors&&(Object.keys(this.intermediateTensors).forEach(e=>this.intermediateTensors[e].forEach(e=>e.dispose())),this.disposeTensorsMap())}disposeTensorsMap(){this.tensorsMap&&Object.keys(this.tensorsMap).forEach(e=>{this.tensorsMap[e].forEach(e=>{!e||e.kept||e.isDisposed||this.keepIds.has(e.id)||e.dispose()})})}getIntermediateTensors(){return this.tensorsMap}resetIntermediateTensors(){for(const e in this.intermediateTensors)this.intermediateTensors[e].forEach(e=>e.dispose()),delete this.intermediateTensors[e]}async _executeAsync(e,t,n=!1,r={},a={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepTensorForDebug=(0,S._K2)().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){}this.resetIntermediateTensors();const o=new Ie(this.weightMap,r,a,this.functionExecutorMap);this.tensorsMap=await this.executeWithControlFlow(e,o,t,n);const s=t.map(e=>I(e,this.tensorsMap,o)),i=s.map(e=>e.id),u=Object.keys(e).map(t=>e[t].id);return this.keepIds=new Set([...i,...u,...this.weightIds]),this.keepTensorForDebug||this.disposeTensorsMap(),null==this.parent&&o.dispose(this.keepIds),s}async executeFunctionAsync(e,t,n){const r=e.reduce((e,t,n)=>(e[this.inputs[n].name]=t,e),{});return this._executeAsync(r,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,r){const a=Object.keys(e),o=a.map(e=>this.graph.nodes[_(e)[0]]),s=n.map(e=>_(e)[0]);let i=s.map(e=>this.graph.nodes[e]);0===i.length&&(i=this._outputs);const{usedNodes:u,missingInputs:c,dynamicNode:l,syncInputs:p}=Ae(e,i,this.weightMap,this._initNodes),h=[...o,...this.graph.weights,...this._initNodes||[]].map(e=>({node:e,contexts:t.currentContext})),d=Object.assign({},this.weightMap);Object.keys(e).forEach(t=>{const[n,r]=_(t),a=[];a[r]=e[t],d[n]=a});const f={},m=this.getFrozenTensorIds(d),g={};for(;h.length>0;){const e=this.processStack(o,h,t,d,g,m,s,f,u);await Promise.all(e)}const y=i.filter(e=>!Fe(e)&&!I(e.name,d,t)).map(e=>e.name);if(y.length>0){let e="";throw null!=l&&(e=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${p}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${a}]. Consider providing the following inputs: [${c}]. ${e}`)}return d}processStack(e,t,n,r,a,o,s,i,u){const c=[];for(;t.length>0;){const e=t.pop();n.currentContext=e.contexts;let l="";if("Enter"===e.node.op&&N("isConstant",e.node,r,n)&&([l]=A(e.node.name,n)),null==r[e.node.name]){const p=Ne(e.node,r,n,this._resourceManager);l||([l]=A(e.node.name,n));const h=n.currentContext;S.ZSL.isPromise(p)?c.push(p.then(c=>(r[l]=c,n.currentContext=h,this.checkTensorForDisposal(l,e.node,r,n,o,s,i),this.processChildNodes(e.node,t,n,r,a,u),c))):(r[l]=p,this.checkTensorForDisposal(l,e.node,r,n,o,s,i),this.processChildNodes(e.node,t,n,r,a,u))}else this.processChildNodes(e.node,t,n,r,a,u)}return c}processChildNodes(e,t,n,r,a,o){e.children.forEach(e=>{const[s]=A(e.name,n);!a[s]&&o.has(e.name)&&("Merge"===e.op?e.inputNames.some(e=>!!I(e,r,n))&&(a[s]=!0,t.push({contexts:n.currentContext,node:e})):e.inputNames.every(e=>!!I(e,r,n))&&(a[s]=!0,t.push({contexts:n.currentContext,node:e})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(e=>e.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{const n=e[t],[r]=_(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){const e=a.attrParams.shape.value,t=e.length===n.shape.length&&n.shape.every((t,n)=>-1===e[n]||e[n]===t);S.ZSL.assert(t,()=>`The shape of dict['${a.name}'] provided in model.execute(dict) must be [${e}], but was [${n.shape}]`)}a.attrParams.dtype&&a.attrParams.dtype.value&&S.ZSL.assert(n.dtype===a.attrParams.dtype.value,()=>`The dtype of dict['${a.name}'] provided in model.execute(dict) must be ${a.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){const t={};for(const n in e)if(null!=this._signature&&null!=this._signature.inputs&&null!=this._signature.inputs[n]){t[this._signature.inputs[n].name]=e[n]}else t[n]=e[n];return t}checkInputs(e){const t=Object.keys(e).filter(e=>{const[t]=_(e);return null==this.graph.nodes[t]});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(e=>{if(null!=this._signature&&null!=this._signature.outputs&&null!=this._signature.outputs[e]){return this._signature.outputs[e].name}return e},{})}

2checkOutputs(e){e.forEach(e=>{const[t]=_(e);if(!this.graph.nodes[t])throw new Error(`The output '${e}' is not found in the graph`)})}}class Pe{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(const e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(const e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}}const Be="?tfjs-format=file",Ve="model.json";class ze{constructor(e,t={},n=S.io){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=n,null==t&&(this.loadOptions={}),this.resourceManager=new Pe}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){const e=this.modelUrl;if(null!=e.load)this.handler=e;else if(null!=this.loadOptions.requestInit)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{const t=this.io.getLoadHandlers(e,this.loadOptions);if(0===t.length)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),null==this.handler.load)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");const e=this.handler.load();return S.ZSL.isPromise(e)?e.then(e=>this.loadSync(e)):this.loadSync(e)}loadSync(e){this.artifacts=e;const t=this.artifacts.modelTopology;let n=this.artifacts.signature;if(null!=this.artifacts.userDefinedMetadata){const e=this.artifacts.userDefinedMetadata;null!=e.signature&&(n=e.signature),null!=e.structuredOutputKeys&&(this.structuredOutputKeys=e.structuredOutputKeys)}this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;const r=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new Me(ee.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,null!=e.modelInitializer&&null!=e.modelInitializer.node){const t=ee.Instance.transformGraph(e.modelInitializer);this.initializer=new Me(t),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if("string"==typeof e){const t=this.io.getSaveHandlers(e);if(0===t.length)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(t.length>1)throw new Error(`Found more than one (${t.length}) save handlers for URL '${e}'`);e=t[0]}if(null==e.save)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){const n=this.execute(e,this.outputNodes);if(this.structuredOutputKeys){const e=n instanceof S.qYS?[n]:n,t={};return e.forEach((e,n)=>t[this.structuredOutputKeys[n]]=e),t}return n}normalizeInputs(e){if(!(e instanceof S.qYS||Array.isArray(e)))return e;if((e=Array.isArray(e)?e:[e]).length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);const n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);const n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}}async function Ue(e,t={},n=S.io){if(null==e)throw new Error("modelUrl in loadGraphModel() cannot be null. 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e&&"boolean"!=typeof e&&"string"!=typeof e){const r=null==e?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${r}'`)}const p=u(e,c);(0,s.iu)(e)||Array.isArray(e)||(e=[e]);const h="string"!==c?(0,i.toTypedArray)(e,c):(0,s.Bq)(e,[],!0);return r.T2.makeTensor(h,p,c)}function h(e,t,n,r="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((e,a)=>p(e,`${t}[${a}]`,n,r))}},28570:function(e){e.exports=n;var t=null;try{t=new WebAssembly.Instance(new WebAssembly.Module(new 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2h(e=>{r.push(`uniform ${e.type} ${e.name}${e.arrayIndex?`[${e.arrayIndex}]`:""};`)});const o=r.join("\n"),s=e.map(e=>function(e,t,n=!1,r){let o="";o+=n?X(e,r):Z(e,r);const s=e.shapeInfo.logicalShape,i=t.logicalShape;s.length<=i.length&&(o+=n?function(e,t){const n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),o="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,u=H(e.shapeInfo.logicalShape,t.logicalShape),c=ae(i),l=i-s;let p;const h=["x","y","z","w","u","v"];p=0===s?"":i<2&&u.length>=1?"coords = 0;":u.map(e=>`coords.${h[e+l]} = 0;`).join("\n");let d="";d=i<2&&s>0?"coords":e.shapeInfo.logicalShape.map((e,t)=>`coords.${h[t+l]}`).join(", ");let f="return outputValue;";const m=1===a.ZSL.sizeFromShape(e.shapeInfo.logicalShape),g=a.ZSL.sizeFromShape(t.logicalShape),y=1===g;if(1!==s||m||y){if(m&&!y)f=1===i?"\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      ":"\n        return vec4(outputValue.x);\n      ";else if(u.length){const e=s-2,t=s-1;u.indexOf(e)>-1&&u.indexOf(t)>-1?f="return vec4(outputValue.x);":u.indexOf(e)>-1?f="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":u.indexOf(t)>-1&&(f="return vec4(outputValue.xx, outputValue.zz);")}}else f="\n      return vec4(outputValue.xy, outputValue.xy);\n    ";return`\n    vec4 ${o}() {\n      ${c} coords = getOutputCoords();\n      ${p}\n      vec4 outputValue = get${r}(${d});\n      ${f}\n    }\n  `}(e,t):function(e,t){const n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),o="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,u=e.shapeInfo.logicalShape.length,c=t.logicalShape.length;if(!e.shapeInfo.isUniform&&u===c&&null==e.shapeInfo.flatOffset&&a.ZSL.arraysEqual(i,s))return`\n      float ${o}() {\n        return sampleTexture(${n}, resultUV);\n      }\n    `;const l=ae(c),p=H(e.shapeInfo.logicalShape,t.logicalShape),h=c-u;let d;const f=["x","y","z","w","u","v"];d=0===u?"":c<2&&p.length>=1?"coords = 0;":p.map(e=>`coords.${f[e+h]} = 0;`).join("\n");let m="";m=c<2&&u>0?"coords":e.shapeInfo.logicalShape.map((e,t)=>`coords.${f[t+h]}`).join(", ");return`\n    float ${o}() {\n      ${l} coords = getOutputCoords();\n      ${d}\n      return get${r}(${m});\n    }\n  `}(e,t));return o}(e,t,n.packedInputs,n.enableShapeUniforms)).join("\n"),i=t.texShape,u=z(),c=function(e){return`\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return ${e.texture2D}(textureSampler, uv).r;\n    }\n  `}(u);let l,p,h=function(e){const t=`${e.version}\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    ${e.varyingFs} vec2 resultUV;\n    ${e.defineOutput}\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    ${e.defineSpecialNaN}\n    ${e.defineSpecialInf}\n    ${e.defineRound}\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    ${q}\n    ${Q}\n    ${J}\n  `;return t}(u);t.isPacked?(l=function(e,t,n){switch(e.length){case 0:return te();case 1:return function(e,t,n){const r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(1===r[0])return n?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));\n      }\n    ":`\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * ${r[1]}.0);\n      }\n    `;if(1===r[1])return n?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));\n      }\n    ":`\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * ${r[0]}.0);\n      }\n    `;if(n)return"\n    int getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));

2\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);\n    }\n  ";return`\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${r[0]}, ${r[1]}));\n      return 2 * (resTexRC.x * ${r[1]} + resTexRC.y);\n    }\n  `}(0,t,n);case 2:return function(e,t,n){const r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(a.ZSL.arraysEqual(e,t))return n?"\n      ivec2 getOutputCoords() {\n        ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n        return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));\n      }\n    ":`\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2(${r[0]}, ${r[1]}));\n      }\n    `;const o=Math.ceil(e[1]/2);if(n)return"\n    ivec2 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec2(r, c);\n    }\n  ";return`\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${r[0]}, ${r[1]}));\n\n      int index = resTexRC.x * ${r[1]} + resTexRC.y;\n      int r = 2 * (index / ${o});\n      int c = imod(index, ${o}) * 2;\n\n      return ivec2(r, c);\n    }\n  `}(e,t,n);case 3:return function(e,t,n){if(n)return"\n    ivec3 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));\n      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n      int b = index / texelsInBatch;\n      index -= b * texelsInBatch;\n\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec3(b, r, c);\n    }\n  ";const r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[2]/2),o=a*Math.ceil(e[1]/2);return`\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${r[0]}, ${r[1]}));\n      int index = resTexRC.x * ${r[1]} + resTexRC.y;\n\n      int b = index / ${o};\n      index -= b * ${o};\n\n      int r = 2 * (index / ${a});\n      int c = imod(index, ${a}) * 2;\n\n      return ivec3(b, r, c);\n    }\n  `}(e,t,n);default:return function(e,t,n){if(n)return"\n    ivec4 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n      int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));\n      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));\n      int texelsInBatchN = texelsInBatch * outShape[1];\n\n      int b2 = index / texelsInBatchN;\n      index -= b2 * texelsInBatchN;\n\n      int b = index / texelsInBatch;\n      index -= b * texelsInBatch;\n\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec4(b2, b, r, c);\n    }\n  ";const r=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[e.length-1]/2),o=a*Math.ceil(e[e.length-2]/2);let s=o,i="",u="b, r, c";for(let t=2;t<e.length-1;t++)s*=e[e.length-t-1],i=`\n      int b${t} = index / ${s};\n      index -= b${t} * ${s};\n    `+i,u=`b${t}, `+u;return`\n    ivec${e.length}

2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${r[0]}, ${r[1]}));\n      int index = resTexRC.x * ${r[1]} + resTexRC.y;\n\n      ${i}\n\n      int b = index / ${o};\n      index -= b * ${o};\n\n      int r = 2 * (index / ${a});\n      int c = imod(index, ${a}) * 2;\n\n      return ivec${e.length}(${u});\n    }\n  `}(e,t,n)}}(t.logicalShape,i,n.enableShapeUniforms),p=function(e){return`\n    void setOutput(vec4 val) {\n      ${e.output} = val;\n    }\n  `}(u)):(l=function(e,t,n){switch(e.length){case 0:return te();case 1:return function(e,t,n){if(1===t[0])return n?"\n      int getOutputCoords() {\n        return int(resultUV.x * float(outTexShape[1]));\n      }\n    ":`\n      int getOutputCoords() {\n        return int(resultUV.x * ${t[1]}.0);\n      }\n    `;if(1===t[1])return n?"\n      int getOutputCoords() {\n        return int(resultUV.y * float(outTexShape[0]));\n      }\n    ":`\n      int getOutputCoords() {\n        return int(resultUV.y * ${t[0]}.0);\n      }\n    `;if(n)return"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(outTexShape[0], outTexShape[1]));\n      return resTexRC.x * outTexShape[1] + resTexRC.y;\n    }\n  ";return`\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${t[0]}, ${t[1]}));\n      return resTexRC.x * ${t[1]} + resTexRC.y;\n    }\n  `}(0,t,n);case 2:return function(e,t,n){if(a.ZSL.arraysEqual(e,t))return n?"\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));\n      }\n    ":`\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));\n      }\n    `;if(1===e[1])return n?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(outTexShape[0], outTexShape[1]));\n        int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ":`\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(${t[0]}, ${t[1]}));\n        int index = resTexRC.x * ${t[1]} + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    `;if(1===e[0])return n?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(outTexShape[0], outTexShape[1]));\n        int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ":`\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(${t[0]}, ${t[1]}));\n        int index = resTexRC.x * ${t[1]} + resTexRC.y;\n        return ivec2(0, index);\n      }\n    `;if(n)return"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(outTexShape[0], outTexShape[1]));\n      int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n      int r = index / outShape[1];\n      int c = index - r * outShape[1];\n      return ivec2(r, c);\n    }\n  ";return`\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${t[0]}, ${t[1]}));\n      int index = resTexRC.x * ${t[1]} + resTexRC.y;\n      int r = index / ${e[1]};\n      int c = index - r * ${e[1]};\n      return ivec2(r, c);\n    }\n  `}(e,t,n);case 3:return function(e,t,n){if(n){return`\n  ivec3 getOutputCoords() {\n    ivec2 resTexRC = ivec2(resultUV.yx *\n                           vec2(outTexShape[0], outTexShape[1]));\n    int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n    ${W(["r","c","d"],e)}\n    return ivec3(r, c, d);\n  }\n`}const r=U(["r","c","d"],e);return`\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${t[0]}, ${t[1]}));\n      int index = resTexRC.x * ${t[1]} + resTexRC.y;\n      ${r}\n      return ivec3(r, c, d);\n    }\n  `}(e,t,n);case 4:return function(e,t,n){if(n){return`\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ive

2c2(resultUV.yx *\n        vec2(outTexShape[0], outTexShape[1]));\n      int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n      ${W(["r","c","d","d2"],e)}\n      return ivec4(r, c, d, d2);\n    }\n  `}const r=U(["r","c","d","d2"],e);return`\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(${t[0]}, ${t[1]}));\n      int index = resTexRC.x * ${t[1]} + resTexRC.y;\n      ${r}\n      return ivec4(r, c, d, d2);\n    }\n  `}(e,t,n);case 5:return function(e,t){const n=U(["r","c","d","d2","d3"],e);return`\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},\n                             ${t[1]}));\n\n      int index = resTexRC.x * ${t[1]} + resTexRC.y;\n\n      ${n}\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  `}(e,t);case 6:return function(e,t){const n=U(["r","c","d","d2","d3","d4"],e);return`\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(${t[0]}, ${t[1]}));\n      int index = resTexRC.x * ${t[1]} + resTexRC.y;\n\n      ${n}\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  `}(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}(t.logicalShape,i,n.enableShapeUniforms),p=function(e){return`\n    void setOutput(float val) {\n      ${e.output} = vec4(val, 0, 0, 0);\n    }\n  `}(u)),n.packedInputs&&(h+=ee);return[h,c,p,o,l,s,n.userCode].join("\n")}function Z(e,t=!1){const n=e.shapeInfo.logicalShape;switch(n.length){case 0:return function(e,t){const n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`float ${r}() {return ${n};}`;const[a,o]=e.shapeInfo.texShape;if(1===a&&1===o)return`\n      float ${r}() {\n        return sampleTexture(${n}, halfCR);\n      }\n    `;const s=ne(n);if(t)return`\n    float ${r}() {\n      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], ${s});\n      return sampleTexture(${n}, uv);\n    }\n  `;const[i,u]=e.shapeInfo.texShape;return`\n    float ${r}() {\n      vec2 uv = uvFromFlat(${i}, ${u}, ${s});\n      return sampleTexture(${n}, uv);\n    }\n  `}(e,t);case 1:return function(e,t){const n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`\n      float ${r}(int index) {\n        ${re(e)}\n      }\n    `;const a=e.shapeInfo.texShape,o=a[0],s=a[1];if(1===s&&1===o)return`\n      float ${r}(int index) {\n        return sampleTexture(${n}, halfCR);\n      }\n    `;const i=ne(n);if(1===s)return t?`\n      float ${r}(int index) {\n        vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / float(${n}TexShape[0]));\n        return sampleTexture(${n}, uv);\n      }\n    `:`\n      float ${r}(int index) {\n        vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${o}.0);\n        return sampleTexture(${n}, uv);\n      }\n    `;if(1===o)return t?`\n      float ${r}(int index) {\n        vec2 uv = vec2((float(index + ${i}) + 0.5) / float(${n}TexShape[1]), 0.5);\n        return sampleTexture(${n}, uv);\n      }\n    `:`\n      float ${r}(int index) {\n        vec2 uv = vec2((float(index + ${i}) + 0.5) / ${s}.0, 0.5);\n        return sampleTexture(${n}, uv);\n      }\n    `;if(t)return`\n    float ${r}(int index) {\n      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${i});\n      return sampleTexture(${n}, uv);\n    }\n  `;return`\n    float ${r}(int index) {\n      vec2 uv = uvFromFlat(${o}, ${s}, index + ${i});\n      return sampleTexture(${n}, uv);\n    }\n  `}(e,t);case 2:return function(e,t){const n=e.shapeInfo.logicalShape,r=e.name,o="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape;if(null!=s&&a.ZSL.arraysEqual(n,s)){if(t)return`\n      float ${o}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${r}TexShape[1], ${r}TexShape[0]);\n        return sampleTexture(${r}, uv);\n      }\n    `;const e=s[0];return`\n    float ${o}(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2(${s[1]}.0, ${e}.0);\n      return sampleTexture(${r}, uv);\n    }\n  `}const{newShape:i,keptDims:u}=a.ZSL.squeezeShape(n),c=i;
vendor: 4,352 bytes, line 2
2if(c.length<n.length){const n=["row","col"];return`\n      ${Z(se(e,c),t)}\n      float ${o}(int row, int col) {\n        return ${o}(${ie(n,u)});\n      }\n    `}if(e.shapeInfo.isUniform)return`\n      float ${o}(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));\n        ${re(e)}\n      }\n    `;const l=s[0],p=s[1],h=ne(r);if(1===p)return t?`\n      float ${o}(int row, int col) {\n        float index = dot(vec3(row, col, ${h}), vec3(${r}Shape[1], 1, 1));\n        vec2 uv = vec2(0.5, (index + 0.5) / float(${r}TexShape[0]));\n        return sampleTexture(${r}, uv);\n      }\n    `:`\n    float ${o}(int row, int col) {\n      float index = dot(vec3(row, col, ${h}), vec3(${n[1]}, 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);\n      return sampleTexture(${r}, uv);\n    }\n  `;if(1===l)return t?`\n      float ${o}(int row, int col) {\n        float index = dot(vec3(row, col, ${h}), vec3(${r}Shape[1], 1, 1));\n        vec2 uv = vec2((index + 0.5) / float(${r}TexShape[1]), 0.5);\n        return sampleTexture(${r}, uv);\n      }\n    `:`\n    float ${o}(int row, int col) {\n      float index = dot(vec3(row, col, ${h}), vec3(${n[1]}, 1, 1));\n      vec2 uv = vec2((index + 0.5) / ${p}.0, 0.5);\n      return sampleTexture(${r}, uv);\n    }\n  `;if(t)return`\n      float ${o}(int row, int col) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * ${r}Shape[1] + col + ${h};\n        vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], index);\n        return sampleTexture(${r}, uv);\n      }\n    `;return`\n  float ${o}(int row, int col) {\n    // Explicitly use integer operations as dot() only works on floats.\n    int index = row * ${n[1]} + col + ${h};\n    vec2 uv = uvFromFlat(${l}, ${p}, index);\n    return sampleTexture(${r}, uv);\n  }\n`}(e,t);case 3:return function(e,t){const n=e.shapeInfo.logicalShape,r=e.name,o="get"+r.charAt(0).toUpperCase()+r.slice(1),s=n[1]*n[2],i=n[2],{newShape:u,keptDims:c}=a.ZSL.squeezeShape(n),l=u;if(l.length<n.length){const n=["row","col","depth"];return`\n        ${Z(se(e,l),t)}\n        float ${o}(int row, int col, int depth) {\n          return ${o}(${ie(n,c)});\n        }\n      `}if(e.shapeInfo.isUniform)return`\n      float ${o}(int row, int col, int depth) {\n        int index = round(dot(vec3(row, col, depth),\n                          vec3(${s}, ${i}, 1)));\n        ${re(e)}\n      }\n    `;const p=e.shapeInfo.texShape,h=p[0],d=p[1],f=e.shapeInfo.flatOffset;if(d===s&&null==f)return t?`\n      float ${o}(int row, int col, int depth) {\n        int stride1 = ${r}Shape[2];\n        float texR = float(row);\n        float texC = dot(vec2(col, depth), vec2(stride1, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${r}TexShape[1], ${r}TexShape[0]);\n        return sampleTexture(${r}, uv);\n      }\n    `:`\n        float ${o}(int row, int col, int depth) {\n          float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2(${i}, 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2(${d}.0, ${h}.0);\n          return sampleTexture(${r}, uv);\n        }\n      `;if(d===i&&null==f)return t?`\n      float ${o}(int row, int col, int depth) {\n        float texR = dot(vec2(row, col), vec2(${r}Shape[1], 1));\n        float texC = float(depth);\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${r}TexShape[1], ${r}TexShape[0]);\n        return sampleTexture(${r}, uv);\n      }\n    `:`\n    float ${o}(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2(${n[1]}, 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${d}.0, ${h}.0);\n      return sampleTexture(${r}, uv);\n    }\n  `;const m=ne(r);if(t)return`\n    float ${o}(int row, int col, int depth) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int stride0 = ${r}Shape[1] * ${r}Shape[2];\n      int stride1 = ${r}Shape[2];\n      int index = row * stride0 + col * stride1 + depth + ${m};\n      vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], index);\n      return sampleTexture(${r}, uv);\n    }\n    `;return`\n      float ${o}(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only w

2orks on floats.\n        int index = row * ${s} + col * ${i} + depth + ${m};\n        vec2 uv = uvFromFlat(${h}, ${d}, index);\n        return sampleTexture(${r}, uv);\n      }\n  `}(e,t);case 4:return function(e,t){const n=e.shapeInfo.logicalShape,r=e.name,o="get"+r.charAt(0).toUpperCase()+r.slice(1),s=n[3],i=n[2]*s,u=n[1]*i,{newShape:c,keptDims:l}=a.ZSL.squeezeShape(n);if(c.length<n.length){const n=["row","col","depth","depth2"];return`\n      ${Z(se(e,c),t)}\n      float ${o}(int row, int col, int depth, int depth2) {\n        return ${o}(${ie(n,l)});\n      }\n    `}if(e.shapeInfo.isUniform)return`\n      float ${o}(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4(${u}, ${i}, ${s}, 1)));\n        ${re(e)}\n      }\n    `;const p=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],f=h[1],m=`int stride2 = ${r}Shape[3];`,g=`int stride1 = ${r}Shape[2] * stride2;`,y=`int stride0 = ${r}Shape[1] * stride1;`;if(f===u&&null==p)return t?`\n      float ${o}(int row, int col, int depth, int depth2) {\n        ${m}\n        ${g}\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3(stride1, stride2, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${r}TexShape[1], ${r}TexShape[0]);\n        return sampleTexture(${r}, uv);\n      }\n    `:`\n      float ${o}(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3(${i}, ${s}, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${f}.0, ${d}.0);\n        return sampleTexture(${r}, uv);\n      }\n    `;if(f===s&&null==p)return t?`\n      float ${o}(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3(${r}Shape[1] * ${r}Shape[2], ${r}Shape[2], 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${r}TexShape[1], ${r}TexShape[0]);\n        return sampleTexture(${r}, uv);\n      }\n    `:`\n      float ${o}(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3(${n[1]*n[2]}, ${n[2]}, 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${f}.0, ${d}.0);\n        return sampleTexture(${r}, uv);\n      }\n    `;const x=ne(r);if(t)return`\n    float ${o}(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      ${m}\n      ${g}\n      ${y}\n      int index = row * stride0 + col * stride1 +\n          depth * stride2 + depth2;\n      vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], index + ${x});\n      return sampleTexture(${r}, uv);\n    }\n  `;return`\n    float ${o}(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${u} + col * ${i} +\n          depth * ${s} + depth2;\n      vec2 uv = uvFromFlat(${d}, ${f}, index + ${x});\n      return sampleTexture(${r}, uv);\n    }\n  `}(e,t);case 5:return function(e){const t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t[4],s=t[3]*o,i=t[2]*s,u=t[1]*i,{newShape:c,keptDims:l}=a.ZSL.squeezeShape(t);if(c.length<t.length){const t=["row","col","depth","depth2","depth3"];return`\n      ${Z(se(e,c))}\n      float ${r}(int row, int col, int depth, int depth2, int depth3) {\n        return ${r}(${ie(t,l)});\n      }\n    `}if(e.shapeInfo.isUniform)return`\n      float ${r}(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4(${u}, ${i}, ${s}, ${o})) +\n          depth3;\n        ${re(e)}\n      }\n    `;const p=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],f=h[1];if(f===u&&null==p)return`\n      float ${r}(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4(${i}, ${s}, ${o}, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${f}.0, ${d}.0);\n        return sampleTexture(${n}, uv);\n      }\n    `;if(f===o&&null==p)return`\n      float ${r}(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot

2(\n          vec4(row, col, depth, depth2),\n          vec4(${t[1]*t[2]*t[3]},\n               ${t[2]*t[3]}, ${t[3]}, 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${f}.0, ${d}.0);\n        return sampleTexture(${n}, uv);\n      }\n    `;const m=ne(n);return`\n    float ${r}(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${u} + col * ${i} + depth * ${s} +\n          depth2 * ${o} + depth3 + ${m};\n      vec2 uv = uvFromFlat(${d}, ${f}, index);\n      return sampleTexture(${n}, uv);\n    }\n  `}(e);case 6:return function(e){const t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:o,keptDims:s}=a.ZSL.squeezeShape(t);if(o.length<t.length){const t=["row","col","depth","depth2","depth3","depth4"];return`\n      ${Z(se(e,o))}\n      float ${r}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return ${r}(${ie(t,s)});\n      }\n    `}const i=t[5],u=t[4]*i,c=t[3]*u,l=t[2]*c,p=t[1]*l;if(e.shapeInfo.isUniform)return`\n      float ${r}(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4(${p}, ${l}, ${c}, ${u})) +\n          dot(\n            vec2(depth3, depth4),\n            vec2(${i}, 1)));\n        ${re(e)}\n      }\n    `;const h=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,f=d[0],m=d[1];if(m===p&&null==h)return`\n      float ${r}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4(${l}, ${c}, ${u}, ${i})) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${m}.0, ${f}.0);\n        return sampleTexture(${n}, uv);\n      }\n    `;if(m===i&&null==h)return`\n      float ${r}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4(${t[1]*t[2]*t[3]*t[4]},\n               ${t[2]*t[3]*t[4]},\n               ${t[3]*t[4]},\n               ${t[4]})) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${m}.0, ${f}.0);\n        return sampleTexture(${n}, uv);\n      }\n    `;const g=ne(n);return`\n    float ${r}(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${p} + col * ${l} + depth * ${c} +\n          depth2 * ${u} + depth3 * ${i} + depth4 + ${g};\n      vec2 uv = uvFromFlat(${f}, ${m}, index);\n      return sampleTexture(${n}, uv);\n    }\n  `}(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function X(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return function(e){const t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=z();return`\n    vec4 ${n}() {\n      return ${r.texture2D}(${t}, halfCR);\n    }\n  `}(e);case 1:return function(e,t){const n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,o=z();if(t)return`\n    vec4 ${r}(int index) {\n      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));\n      vec2 uv = packedUVfrom1D(\n        packedTexShape[0], packedTexShape[1], index);\n      return ${o.texture2D}(${n}, uv);\n    }\n  `;const s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];return`\n    vec4 ${r}(int index) {\n      vec2 uv = packedUVfrom1D(\n        ${s[0]}, ${s[1]}, index);\n      return ${o.texture2D}(${n}, uv);\n    }\n  `}(e,t);case 2:return function(e,t){const n=e.shapeInfo.logicalShape,r=e.name,o="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=s[0],u=s[1],c=z();if(null!=s&&a.ZSL.arraysEqual(n,s))return t?`\n      vec4 ${o}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${r}TexShape[1], ${r}TexShape[0]);\n\n        return ${c.texture2D}(${r}, uv);\n      }\n    `:`\n      vec4 ${o}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${u}.0, ${i}.0);\n\n        return ${c.texture2D}(${r}, uv);\n      }\n    `;if(t)return`\n    vec4 ${o}(int row, int col) {\n      ivec2 packedTexShape = ivec2(ceil(float(${r}TexShape[0]) / 2.0), ceil(float(${r}TexShape[1]) / 2.0));\n      int valuesPerRow = int(ceil(float(${r}Shape[1]) / 2.0));\n      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, c

2ol);\n      return ${c.texture2D}(${r}, uv);\n    }\n  `;const l=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],p=Math.ceil(n[1]/2);return`\n    vec4 ${o}(int row, int col) {\n      vec2 uv = packedUVfrom2D(${p}, ${l[0]}, ${l[1]}, row, col);\n      return ${c.texture2D}(${r}, uv);\n    }\n  `}(e,t);case 3:return function(e,t){const n=e.shapeInfo.logicalShape,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),o=e.shapeInfo.texShape,s=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];if(1===n[0]){const r=[1,2],o=["b","row","col"];return`\n        ${X(se(e,n.slice(1)),t)}\n        vec4 ${a}(int b, int row, int col) {\n          return ${a}(${ie(o,r)});\n        }\n      `}const i=z();if(t)return`\n    vec4 ${a}(int b, int row, int col) {\n      ivec2 packedTexShape = ivec2(ceil(float(${r}TexShape[0]) / 2.0), ceil(float(${r}TexShape[1]) / 2.0));\n      int valuesPerRow = int(ceil(float(${r}Shape[2]) / 2.0));\n      int texelsInBatch = valuesPerRow * int(ceil(float(${r}Shape[1]) / 2.0));\n      vec2 uv = packedUVfrom3D(\n        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);\n      return ${i.texture2D}(${r}, uv);\n    }\n  `;const u=s[0],c=s[1],l=Math.ceil(n[2]/2),p=l*Math.ceil(n[1]/2);return`\n    vec4 ${a}(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        ${u}, ${c}, ${p}, ${l}, b, row, col);\n      return ${i.texture2D}(${r}, uv);\n    }\n  `}(e,t);default:return function(e,t){const n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=z();if(t)return`\n    vec4 ${r}(int b2, int b, int row, int col) {\n      int valuesPerRow = int(ceil(float(${n}Shape[3]) / 2.0));\n      int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[2]) / 2.0));\n      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);\n      texelsInBatch *= ${n}Shape[1];\n      index = b2 * texelsInBatch + index;\n      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));\n      int texR = index / packedTexShape[1];\n      int texC = index - texR * packedTexShape[1];\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${a.texture2D}(${n}, uv);\n    }\n  `;const o=e.shapeInfo.logicalShape,s=o.length,i=e.shapeInfo.texShape,u=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],c=u[0],l=u[1],p=Math.ceil(o[s-1]/2);let h=p*Math.ceil(o[s-2]/2),d="int b, int row, int col",f=`b * ${h} + (row / 2) * ${p} + (col / 2)`;for(let e=2;e<s-1;e++)d=`int b${e}, `+d,h*=o[s-e-1],f=`b${e} * ${h} + `+f;return`\n    vec4 ${r}(${d}) {\n      int index = ${f};\n      int texR = index / ${l};\n      int texC = index - texR * ${l};\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${c});\n      return ${a.texture2D}(${n}, uv);\n    }\n  `}(e,t)}}const q="\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",Q="\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",J="\nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",ee="\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n";function te(){return"\n    int getOutputCoords() {\n      return 0;\n    }\n  "}function ne(e){return`offset${e}`}function re(e){const t=e.name,n=a.ZSL.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`\n    for (int i = 0; i < ${n};

2 i++) {\n      if (i == index) {\n        return ${t}[i];\n      }\n    }\n  `}function ae(e){if(e<=1)return"int";if(2===e)return"ivec2";if(3===e)return"ivec3";if(4===e)return"ivec4";if(5===e)return"ivec5";if(6===e)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function oe(e,t,n){const{newShape:r,keptDims:o}=a.ZSL.squeezeShape(t),s=t.length,i=e&&3===s&&1===t[0],u=i?t.slice(1):r,c=!e&&s>1&&!a.ZSL.arraysEqual(t,n)&&r.length<s||i;return{useSqueezeShape:c,uniformShape:c?u:t,keptDims:o}}function se(e,t){const n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function ie(e,t){return t.map(t=>e[t]).join(", ")}function ue(e,t,n,r){const o=n.map((e,n)=>{const r={logicalShape:e.shape,texShape:e.isUniform?null:e.texData.texShape,isUniform:e.isUniform,isPacked:!e.isUniform&&e.texData.isPacked,flatOffset:null};return null!=e.texData&&null!=e.texData.slice&&e.texData.slice.flatOffset>0&&(r.flatOffset=e.texData.slice.flatOffset),{name:t.variableNames[n],shapeInfo:r}}),s=o.map(e=>e.shapeInfo),i={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},u=Y(o,i,t),c=function(e,t){const n=E(e,()=>e.createShader(e.FRAGMENT_SHADER),"Unable to create fragment WebGLShader.");if(m(e,()=>e.shaderSource(n,t)),m(e,()=>e.compileShader(n)),(0,a._K2)().get("ENGINE_COMPILE_ONLY"))return n;if(!1===e.getShaderParameter(n,e.COMPILE_STATUS))throw b(t,e.getShaderInfoLog(n)),new Error("Failed to compile fragment shader.");return n}(e.gl,u),l=e.createProgram(c);return(0,a._K2)().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:c,source:u,webGLProgram:l,inShapeInfos:s,outShapeInfo:i,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:c,source:u,webGLProgram:l,inShapeInfos:s,outShapeInfo:i},ce(e,t,l))}function ce(e,t,n){const r={},o={},s={},i=[];let u,c,l,p=null,h=null;h=e.getUniformLocation(n,"NAN",!1),1===(0,a._K2)().getNumber("WEBGL_VERSION")&&(p=e.getUniformLocation(n,"INFINITY",!1));const d=!1;for(let a=0;a<t.variableNames.length;a++){const i=t.variableNames[a];r[i]=e.getUniformLocation(n,i,d),r[`offset${i}`]=e.getUniformLocation(n,`offset${i}`,d),t.enableShapeUniforms&&(o[`${i}Shape`]=e.getUniformLocation(n,`${i}Shape`,d),s[`${i}TexShape`]=e.getUniformLocation(n,`${i}TexShape`,d))}return t.enableShapeUniforms&&(u=e.getUniformLocation(n,"outShape",d),l=e.getUniformLocation(n,"outShapeStrides",d),c=e.getUniformLocation(n,"outTexShape",d)),t.customUniforms&&t.customUniforms.forEac

2h((t,r)=>{i[r]=e.getUniformLocation(n,t.name,d)}),{uniformLocations:r,customUniformLocations:i,infLoc:p,nanLoc:h,inShapesLocations:o,inTexShapesLocations:s,outShapeLocation:u,outShapeStridesLocation:l,outTexShapeLocation:c}}function le(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((e,n)=>{const r=e.logicalShape,o=t[n],s=o.shape;if(!a.ZSL.arraysEqual(r,s))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${s} must match`);if(e.isUniform&&o.isUniform)return;const i=e.texShape,u=o.isUniform?null:o.texData.texShape;if(!a.ZSL.arraysEqual(i,u))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${u} must match`)})}function pe(e){return(0,a._K2)().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}class he{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=u.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];const t=z();this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length),this.userCode=`\n      ivec3 outCoordsFromFlatIndex(int index) {\n        ${this.enableShapeUniforms?W(["r","c","d"],e):U(["r","c","d"],e)}\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));\n        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        ${t.output} = result;\n      }\n    `}}class de{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=u.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];const t=z();this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length),this.userCode=`\n      ivec3 outCoordsFromFlatIndex(int index) {\n        ${this.enableShapeUniforms?W(["r","c","d"],e):U(["r","c","d"],e)}\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));\n        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        ${t.output} = result;\n      }\n    `}}class fe{constructor(e){this.variableNames=["A"],this.outTexUsage=c.DOWNLOAD;const t=z();this.outputShape=e,this.userCode=`\n      ${K}\n\n      void main() {\n        float x = getAAtOutCoords();\n        ${t.output} = encode_float(x);\n      }\n    `}}class me{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=c.DOWNLOAD;const t=z();this.outputShape=e,this.userCode=`\n      ${K}\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        ${t.output} = encode_float(x);\n      }\n    `}}class ge{constructor(e,t=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];const n=z();this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length);let r="result";t&&(r="floor(result * 255. + 0.5)"),this.userCode=`\n      ${this.enableShapeUniforms?"\n  int getFlatIndex(ivec3 coords) {\n    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;\n  }\n":j(e)}\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n\n        int r = flatIndex / texShape[1];\n        int c = imod(flatIndex, texShape[1]);\n        vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);\n        vec4 values = ${n.texture2D}(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        ${n.output} = vec4(${r}, 0., 0., 0.);\n      }\n    `}}class ye{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];const n=z();this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length);let r="",a="result";t&&(a="floor(result * 255. + 0.5)");for(let t=0;t<=1;t++)for(let a=0;a<=1;a++){const o=2*t+a;r+=`\n          localCoords = coords;\n          if(localCoords[2] + ${a} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}

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create WebGLBuffer");return m(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),m(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),n}(e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function ve(e){return function(e,t){const n=E(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return m(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,n)),m(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),n}(e,new Uint16Array([0,1,2,2,1,3]))}function we(e,t,n,r,o,s){!function(e,t){const n=(0,a._K2)().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0)throw new Error(`Requested texture size [${e}x${t}] is invalid.`);if(e>n||t>n)throw new Error(`Requested texture size [${e}x${t}] greater than WebGL maximum on this browser / GPU [${n}x${n}].`)}(t,n);const i=function(e){return E(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}(e),u=e.TEXTURE_2D;return 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renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",D(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else{if(!D(this.gl,r))throw new Error("GL context does not support color renderable floats");this.colorBufferHalfFloatExtension=this.gl.getExtension(r)}this.vertexBuffer=be(this.gl),this.indexBuffer=ve(this.gl),this.framebuffer=function(e){return E(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}(this.gl),this.textureConfig=f(this.gl,this.textureHalfFloatExtension)}get debug(){return(0,a._K2)().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program,this.outputTexture;const 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e=0;e<t.length-1;++e){u*=t[e];const n=t[e+1];for(let t=1;t<u+1;++t)i[e].push(t*n)}for(let r=0;r<e.length;++r){let s=e[r],u=e[r]+1;for(let e=0;e<n.length;++e){const r=n[e],a=e+t.length-1;if(a>=0){const e=i[a],t=e[e.length-1]-r[s];for(let e=s;e<u;++e)i[a].push(r[e+1]+t)}s=r[s],u=r[u]}u!==s&&(a.push([s,u]),o+=u-s)}return{outSplits:i,valueSlices:a,numValues:o}}function yt(e,t){const n=e.slice(0,t);for(;n.length<t;)n.push(1);for(let r=t;r<e.length;r++)n[t-1]*=e[r];return n}function xt(e,t,n,r,o){const s=t.slice();s[0]=o;const i=a.ZSL.getArrayFromDType(n,a.ZSL.sizeFromShape(s)),u=e.length;return function(e,t,n,r,a,o){const s=yt(t,2)[1],i=yt(o,2)[1];let u=0;for(const t of n)for(let n=t[0];n<t[1];++n){for(let t=0;t<r;++t)a[u*i+t]=e[n*s+t];++u}}(e,t,r,0===u?0:u/t[0],i,s),[i,s]}function bt(e,t,n,r,o,s,i,u){if(0===e.length)throw new Error("paramsNestedSplits must be non empty");if(0===t[0].length)throw new Error("Split tensors must not be 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this.rowPartitionTypes[0]===vt.FIRST_DIM_SIZE?this.rowPartitionTypes[e+1]:this.rowPartitionTypes[e]}getRowPartitionTensor(e){return this.rowPartitionTypes[0]===vt.FIRST_DIM_SIZE?this.rowPartitionValues[e+1]:this.rowPartitionValues[e]}getMaxWidth(e){const t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case vt.VALUE_ROWIDS:return wt.getMaxWidthValueRowID(t);case vt.ROW_SPLITS:return wt.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${vt[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){const t=e.length;if(0===t||1===t)return 0;let n=0;for(let r=0;r<t-1;++r){const t=e[r+1]-e[r];t>n&&(n=t)}return n}static getMaxWidthValueRowID(e){const t=e.length;if(0===t)return 0;let n=0,r=e[0],a=0;for(let o=1;o<t;++o){const t=e[o];t!==r&&(r=t,a=Math.max(o-n,a),n=o)}return Math.max(t-n,a)}tensorShapeFromTensor(e,t,n=!0){if(0===t.length){if(-1===e[0])return[];throw new Error("The only valid scalar shape tensor is 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vendor: 8,869 bytes, line 2
2ineRaggedTensorToTensorShapes(this.raggedRank,r,t);o[0]<0&&(o[0]=e);for(let e=1;e<=this.raggedRank;++e)o[e]<0&&(o[e]=this.getMaxWidth(e));return o}calculateFirstParentOutputIndex(e,t,n){const r=Math.min(e,n),o=[];let s=0;for(let e=0;e<r;++e,s+=t)o.push(s);for(let t=r;t<e;++t)o.push(-1);return a.ZSL.assert(o.length===e,()=>"Final length of result must be equal to firstDimension."),o}calculateOutputIndexRowSplit(e,t,n,r){const a=e.length,o=[];for(let s=0;s<a-1;++s){const a=e[s+1]-e[s];let i=Math.min(r,a),u=t[s];-1===u&&(i=0);for(let e=0;e<i;++e)o.push(u),u+=n;for(let e=0;e<a-i;++e)o.push(-1)}if(a>0&&o.length!==e[a-1])throw new Error("Invalid row split size.");return o}calculateOutputIndexValueRowID(e,t,n,r){const a=e.length,o=[];if(0===a)return[];let s=0,i=e[0];if(i>=t.length)throw new Error(`Got currentValueRowId=${i}, which is not less than ${t.length}`);let u=t[i];o.push(u);for(let c=1;c<a;++c){const a=e[c];if(a===i)u>=0&&(++s,s<r?u+=n:u=-1);else{if(s=0,i=a,a>=t.length)throw new Error(`Got nextValueRowId=${a} which is not less than ${t.length}`);u=t[a]}o.push(u)}if(o.length!==e.length)throw new Error("Invalid row ids.");return o}calculateOutputIndex(e,t,n,r){const a=this.getRowPartitionTensor(e),o=this.getRowPartitionTypeByDimension(e);switch(o){case vt.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(a,t,n,r);case vt.ROW_SPLITS:if(a.length-1>t.length)throw new Error(`Row partition size is greater than output size: ${a.length-1} > ${t.length}`);return this.calculateOutputIndexRowSplit(a,t,n,r);default:throw new Error(`Unsupported partition type: ${vt[o]}`)}}getFirstDimensionSize(){const e=this.rowPartitionValues[0];if(0===this.rowPartitionTypes.length)throw new Error("No row_partition_types given.");const t=this.rowPartitionTypes[0];switch(t){case vt.FIRST_DIM_SIZE:return e[0];case vt.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case vt.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${vt[t]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. 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e=n.length;r=Math.floor(e/u)}if(r>d)if(1===this.defaultValue.length)s.subarray(d*u,r*u).fill(this.defaultValue[0]),d=r;else for(;r>d;){Tt(s.slice(d*u),l,u),++d}r<0?(p=e+1,h=d):(p=e,h=d,d=h+1)}else++d}}}function Tt(e,t,n){for(let r=0;r<n;r++)e[r]=t[r]}function St(e,t){const n=[];for(let r of e){if(r<0){if(!t)throw new Error(`Dimension ${r} must be >= 0`);if(r<-1)throw new Error(`Dimension ${r} must be >= -1`);r=-1}n.push(r)}return n}function Ct(e,t,n,r,a,o,s,i,u,c){return new wt(e,t,n,r,a,o,s,i,u,c).compute()}function kt(e,t,n,r){if(e===t||e<t&&n<0||t<e&&n>1)return a.ZSL.makeZerosTypedArray(0,r);const o=Math.abs(Math.ceil((t-e)/n)),s=a.ZSL.makeZerosTypedArray(o,r);t<e&&1===n&&(n=-1),s[0]=e;for(let e=1;e<s.length;e++)s[e]=s[e-1]+n;return s}const Et=Ge(e=>1/Math.sqrt(e));Ke(a.TOR,Et),a.TOR;function $t(e,t,n,r,o,s,i,u,c,l){const p=[r/o,o],h=e.values,d=t.values;if(0===r)return(0,a.ra8)(n,t.dtype);const f=(0,a.ra8)(p,t.dtype);"string"==typeof c||"number"==typeof 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       setOutput(vec4(0));\n          } else {\n            ${r}\n\n            setOutput(vec4(${a}));\n          }\n        }\n      `}}getSourceCoordsArr(e){const t=[];for(let n=0;n<=1;n++)for(let r=0;r<=1;r++){let a=`${0===n?"r":"rp1"}, ${0===r?"c":"cp1"}`;for(let t=2;t<this.rank;t++)a=`${e[e.length-1-t]},`+a;t.push(a)}return t}getOutOfBoundsCondition(e){if(1===this.rank)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let n=this.rank-2;n<this.rank;n++)t+=`${e[n]} >= ${this.enableShapeUniforms?`outShape[${n}]`:this.outputShape[n]}`,n<this.rank-1&&(t+="||");return t}getSetup(e){if(1===this.rank)return"";const t=e.slice(-2),n=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],r=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`\n      int r = ${t[0]};\n      int c = ${t[1]};\n      int rp1 = r + 1;\n      int cp1 = c + 1;\n\n      bool cEdge = cp1 >= ${n};\n      bool rEdge = rp1 >= ${r};\n    `}getOutput(e){const t=this.getSourceCoordsArr(e);if(1===this.rank){return`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`}return`getA(${t[0]}),\n            cEdge ? 0. : getA(${t[1]}

2),\n            rEdge ? 0. : getA(${t[2]}),\n            rEdge || cEdge ? 0. : getA(${t[3]})`}}class Wn{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length);let n="";for(let e=0;e<4;e++){let t="thisRC = rc;";e%2==1&&(t+="thisRC.z += 1;"),e>1&&(t+="thisRC.y += 1;"),n+=`\n        ${t}\n        ${e>0?"if(thisRC.y < rows && thisRC.z < cols){":""}\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result[${e}] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        ${e>0?"}":""}\n      `}var r,a;this.userCode=`\n      ${r=t,a=this.enableShapeUniforms,`\n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      ${a?G(["r","c","d"],"inputShape"):U(["r","c","d"],r)}\n      return ivec3(r, c, d);\n    }\n  `}\n      ${this.enableShapeUniforms?"\n  int getFlatIndex(ivec3 coords) {\n    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;\n  }\n":j(e)}\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = ${this.enableShapeUniforms?"outShape[1]":e[1]};\n        int cols = ${this.enableShapeUniforms?"outShape[2]":e[2]};\n\n        ${n}\n\n        setOutput(result);\n      }\n    `}}class Gn{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){const r=Kn(t,n),a=Hn(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);const o=jn(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=o,this.log();const e=this.freeTextures[a].shift();return this.usedTextures[a].push(e),e}let s;return r===l.PACKED_2X2_FLOAT32?s=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===l.PACKED_2X2_FLOAT16?s=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===l.UNPACKED_FLOAT32?s=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===l.UNPACKED_FLOAT16?s=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===l.PACKED_4X1_UNSIGNED_BYTE&&(s=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(s),this.numUsedTextures++,this._numBytesAllocated+=o,this.log(),s}releaseTexture(e,t,n,r){if(null==this.freeTextures)return;const o=Kn(n,r),s=Hn(t,o,r);s in this.freeTextures||(this.freeTextures[s]=[]);const i=jn(t,o,this.gpgpu.gl,this.gpgpu.textureConfig,r),u=(0,a._K2)().get("WEBGL_DELETE_TEXTURE_THRESHOLD");-1!==u&&this._numBytesAllocated>u?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;const c=this.usedTextures[s],l=c.indexOf(e);if(l<0)throw new Error("Cannot release a texture that was never provided by this texture manager");c.splice(l,1),this.log()}log(){if(!this.logEnabled)return;this.numFreeTextures,this.numUsedTextures,this._numBytesFree,this._numBytesAllocated}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(null!=this.freeTextures){for(const e in this.freeTextures)this.freeTextures[e].forEach(e=>{this.gpgpu.deleteMatrixTexture(e.texture)});for(const e in this.usedTextures)this.usedTextures[e].forEach(e=>{this.gpgpu.deleteMatrixTexture(e.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}}function jn(e,t,n,r,a){const o=function(e,t){switch(e){case l.PACKED_2X2_FLOAT32:return ke(t);case l.PACKED_2X2_FLOAT16:return Ee(t);case l.UNPACKED_FLOAT32:return Te(t);case l.UNPACKED_FLOAT16:return Se(t);case l.PACKED_4X1_UNSIGNED_BYTE:return Ce(t);default:throw new Error(`Unknown physical texture type ${e}`)}}(t,r);let s;if(a){const[t,n]=d(e[0],e[1]);s=t*n}else{const[t,n]=p(e[0],e[1]);s=t*n}const i=function(e,t){const n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F)return 16;if(t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}(n,o);return s*i}function Kn(e,t){if(e===c.UPLOAD)return l.PACKED_2X2_FLOAT32;if(e===c.RENDER||null==e)return function(e){return(0,a._K2)().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?l.PACKED_2X2_FLOAT32:l.UNPACKED_FLOAT32:e?l.PACKED_2X2_FLOAT16:l.UNPACKED_FLOAT16}(t);

2if(e===c.DOWNLOAD||e===c.PIXELS)return l.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function Hn(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}class Yn{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length),this.userCode=`\n      float unaryOperation(float x) {\n        ${t}\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    `}}const Zn="if (isnan(x)) return x;",Xn="return abs(x);";const qn=Zn+"\n  return (x < 0.0) ? 0.0 : x;\n",Qn=Zn+"\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n",Jn="return x;";class er{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length),this.userCode=`\n      vec4 unaryOperation(vec4 x) {\n        ${t}\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    `}}class tr{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length);const t=e.length,n=zn("rc",t),r=ae(t),a=function(e,t){if(1===e)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}(t,n),o=n.slice(-2),s=t<=1?"rc":`vec2(${o.join(",")})`;this.userCode=`\n      void main() {\n        ${r} rc = getOutputCoords();\n        vec4 packedInput = getA(${a});\n\n        setOutput(getChannel(packedInput, ${s}));\n      }\n    `}}const nr=a.kpo.YO,rr={};const ar=(0,a._K2)().getNumber("CPU_HANDOFF_SIZE_THRESHOLD");class or extends a.uI_{constructor(e){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,!(0,a._K2)().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(null!=e){if(e instanceof Ne)t=e;else{const n=i((0,a._K2)().getNumber("WEBGL_VERSION"),e);t=new Ne(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{const e=i((0,a._K2)().getNumber("WEBGL_VERSION"));t=new Ne(e),this.binaryCache=((n=(0,a._K2)().getNumber("WEBGL_VERSION"))in rr||(rr[n]={}),rr[n]),this.gpgpuCreatedLocally=!0}var n;this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new Gn(this.gpgpu),this.numMBBeforeWarning=null==(0,a._K2)().global.screen?1024:(0,a._K2)().global.screen.height*(0,a._K2)().global.screen.width*window.devicePixelRatio*600/1024/1024,this.texData=new a.GJx(this,(0,a.Hi9)())}nextDataId(){return or.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,n){if(((0,a._K2)().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||(0,a._K2)().getBool("DEBUG"))&&this.checkNumericalProblems(e),"complex64"===n&&null!=e)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");const r={id:this.nextDataId()};return this.texData.set(r,{shape:t,dtype:n,values:e,usage:c.UPLOAD,refCount:1}),r}refCount(e){if(this.texData.has(e)){return this.texData.get(e).refCount}return 0}incRef(e){this.texData.get(e).refCount++}decRef(e){if(this.texData.has(e)){this.texData.get(e).refCount--}}move(e,t,n,r,o){if((0,a._K2)().getBool("DEBUG")&&this.checkNumericalProblems(t),"complex64"===r)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:r,values:t,usage:c.UPLOAD,refCount:o})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){const t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:o,slice:s,shape:i,isPacked:u}=t;if(null!=s){let t;t=u?new er(i,Jn):new Yn(i,Jn);const n=this.runWebGLProgram(t,[{dataId:e,shape:i,dtype:r}],r),a=this.readSync(n.dataId);return this.disposeIntermediateTensorInfo(n),a}if(null!=n)return this.convertAndCacheOnCPU(e);if("string"===r)return n;const c=null!=this.activeTimers;let l,p;if(c&&(l=a.ZSL.now()),"complex64"===r){const e=this.readSync(o.real.dataId),t=this.readSync(o.imag.dataId);p=a.C0T.mergeRealAndImagArrays(e,t)}else p=this.getValuesFromTexture(e);return c&&(this.downloadWaitMs+=a.ZSL.now()-l),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){const t=this.pendingRead.get(e);return new Promise(e=>t.push(e))}const t=this.texData.get(e),{values:n,shape:r,slice:o,dtype:s,complexTensorInfos:i,isPacked:u}=t;if(null!=o){let t;t=u?new er(r,Jn):new Yn(r,Jn);const n=this.runWebGLProgram(t,[{dataId:e,shape:r,dtype:s}],s),a=this.read(n.dataId);return this.disposeIntermediateTensorInfo(n),a}if(null!=n)return this.convertAndCacheOnCPU(e);if((0,a._K2)().getBool("DEBUG")&&!(0,a._K2)().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&2===(0,a._K2)().getNumber("WEBGL_VERSION"))throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let c,l,p=null;if("complex64"!==s&&(0,a._K2)().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);const t=this.texData.get(c.dataId);p=this.gpgpu.createBufferFromTexture(t.texture.texture,...h(r))}if(this.pendingRead.set(e,[]),"complex64"!==s&&await this.gpgpu.createAndWaitForFence(),"complex64"===s){const e=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),t=e[0],n=e[1];l=a.C0T.mergeRealAndImagArrays(t,n)}else if(null==p)l=this.getValuesFromTexture(e);else{const e=a.ZSL.sizeFromShape(r);l=this.gpgpu.downloadFloat32MatrixFromBuffer(p,e)}if(null!=c&&this.disposeIntermediateTensorInfo(c),null!=p){const e=this.gpgpu.gl;m(e,()=>e.deleteBuffer(p))}const d=this.convertAndCacheOnCPU(e,l),f=this.pendingRead.get(e);

2return this.pendingRead.delete(e),f.forEach(e=>e(d)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&(0,a.Hi9)().removeDataId(e,this),this.pendingDeletes--),d}readToGPU(e,t={}){const n=this.texData.get(e),{values:r,shape:o,slice:s,dtype:i,isPacked:u,texture:c}=n;if("complex64"===i)throw new Error("Does not support reading texture for complex64 dtype.");if(null!=s){let n;n=u?new er(o,Jn):new Yn(o,Jn);const r=this.runWebGLProgram(n,[{dataId:e,shape:o,dtype:i}],i),a=this.readToGPU(r,t);return this.disposeIntermediateTensorInfo(r),a}if(null==c)throw null!=r?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");const l=this.decode(e,t.customTexShape),p=(0,a.Hi9)().makeTensorFromTensorInfo(l),h=this.texData.get(l.dataId);return Object.assign({tensorRef:p},h.texture)}bufferSync(e){const t=this.readSync(e.dataId);if("string"===e.dtype)try{const n=t.map(e=>a.ZSL.decodeString(e));return(0,a.ra8)(e.shape,e.dtype,n)}catch(e){throw new Error("Failed to decode encoded string bytes into utf-8")}return(0,a.ra8)(e.shape,e.dtype,t)}checkNumericalProblems(e){if(null!=e)for(let t=0;t<e.length;t++){const n=e[t];if(!g(n)){if((0,a._K2)().getBool("WEBGL_RENDER_FLOAT32_CAPABLE"))throw Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`);throw Error(`The value ${n} cannot be represented on this device.`)}}}getValuesFromTexture(e){const{shape:t,dtype:n,isPacked:r}=this.texData.get(e),o=a.ZSL.sizeFromShape(t);if((0,a._K2)().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){const n=this.decode(e),r=this.texData.get(n.dataId),a=this.gpgpu.downloadMatrixFromPackedTexture(r.texture.texture,...h(t)).subarray(0,o);return this.disposeIntermediateTensorInfo(n),a}const s=(0,a._K2)().getBool("WEBGL_PACK")&&!0===r,i=s?A(t):t,u=s?new me(i):new fe(i),c=this.runWebGLProgram(u,[{shape:i,dtype:n,dataId:e}],"float32"),l=this.texData.get(c.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(l.texture.texture,l.texShape[0],l.texShape[1]).subarray(0,o);return this.disposeIntermediateTensorInfo(c),p}timerAvailable(){return(0,a._K2)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){const t=this.activeTimers,n=[];let r=!1;null==this.programTimersStack?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();const o=a.ZSL.flatten(this.activeTimers.map(e=>e.query)).filter(e=>null!=e),s=a.ZSL.flatten(this.activeTimers.map(e=>e.name)).filter(e=>null!=e);this.activeTimers=t,r&&(this.programTimersStack=null);const i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if((0,a._K2)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){const e=await Promise.all(o);i.kernelMs=a.ZSL.sum(e),i.getExtraProfileInfo=()=>e.map((e,t)=>({name:s[t],ms:e})).map(e=>`${e.name}: ${e.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return(0,a._K2)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:a.ZSL.now(),endMs:null}}endTimer(e){return(0,a._K2)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=a.ZSL.now(),e)}async getQueryTime(e){if((0,a._K2)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);const t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);const{complexTensorInfos:n}=this.texData.get(e);return null!=n&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){const{texture:t,dtype:n,texShape:r,usage:a,isPacked:o,slice:s}=this.texData.get(e),i=s&&s.origDataId||e,u=this.dataRefCount.get(i);u>1?this.dataRefCount.set(i,u-1):(this.dataRefCount.delete(i),null!=t&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,o)));const c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=ar){return(0,a._K2)().getBool("WEBGL_CPU_FORWARD")&&e.every(e=>null==this.texData.get(e.dataId).texture&&a.ZSL.sizeFromShape(e.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){a.C0T.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");const t=e.dataSync();return nr(e.shape,t)}packedUnaryOp(e,t,n){const r=new er(e.shape,t),o=this.compileAndRun(r,[e],n);return(0,a.Hi9)().makeTensorFromTensorInfo(o)}abs(e){if(this.shouldExecuteOnCPU([e])&&"complex64"!==e.dtype){const t=kn(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,t)}if((0,a._K2)().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Xn,e.dtype);const t=new Yn(e.shape,Xn),n=this.compileAndRun(t,[e]);return(0,a.Hi9)().makeTensorFromTensorInfo(n)}makeTensorInfo(e,t,n){let r;if("string"===t&&null!=n&&n.length>0&&a.ZSL.isString(n[0])){const o=n.map(e=>a.ZSL.encodeString(e));r=this.write(o,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){return(0,a.Hi9)().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,n),this)}unpackTensor(e){const t=new tr(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){const t=new Un(e.shape);return this.runWebGLProgram(t,[e],e.dtype,null,!0)}packedReshape(e,t){const n=[N(e.shape),...I(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[N(t),...I(t)],o=new Wn(a,n),s=[n],i=this.runWebGLProgram(o,[r],e.dtype,s,!0);return{dataId:i.dataId,shape:t,dtype:i.dtype}}decode(e,t){const n=this.texData.get(e),{isPacked:r,shape:o,dtype:s}=n;if(null!=t){const e=a.ZSL.sizeFromShape(o),n=t[0]*t[1]*4;a.ZSL.assert(e<=n,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}const i=A(o);let u;u=r?new de(i):new he(i);const c=[null!=t?t:h(i)];return{dtype:s,shape:o,dataId:this.runWebGLProgram(u,[{shape:i,dtype:s,dataId:e}],s,c,!0,t).dataId}}runWebGLProgram(e,t,n,r,o=!1,s){const i=this.makeTensorInfo(e.outputShape,n),c=this.texData.get(i.dataId);if(e.packedOutput&&(c.isPacked=!0),e.outPackingScheme===u.DENSE){const t=null!=s?s:h(e.outputShape);c.texShape=t.map(e=>2*e)}if(null!=e.outTexUsage&&(c.usage=e.outTexUsage),0===a.ZSL.sizeFromShape(i.shape))return c.values=a.ZSL.getTypedArrayFromDType(i.dtype,0),i;const l=[],p=t.map(t=>{if("complex64"===t.dtype)throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let n=this.texData.get(t.dataId);

2if(null==n.texture){if(!e.packedInputs&&a.ZSL.sizeFromShape(t.shape)<=(0,a._K2)().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:t.shape,texData:null,isUniform:!0,uniformValues:n.values};e.packedInputs&&(n.isPacked=!0,n.shape=t.shape)}if(this.uploadToGPU(t.dataId),!!n.isPacked!=!!e.packedInputs)t=n.isPacked?this.unpackTensor(t):this.packTensor(t),l.push(t),n=this.texData.get(t.dataId);else if(n.isPacked&&!_(n.shape,t.shape)){const e=t,r=t.shape;t.shape=n.shape,t=this.packedReshape(t,r),l.push(t),n=this.texData.get(t.dataId),e.shape=r}return{shape:t.shape,texData:n,isUniform:!1}});this.uploadToGPU(i.dataId);const d={shape:i.shape,texData:c,isUniform:!1},f=function(e,t,n){let r="";t.concat(n).forEach(t=>{const o=null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!t.isUniform){const s=t.texData.texShape,{useSqueezeShape:i,uniformShape:u,keptDims:c}=oe(e.packedInputs,t.shape,s);let l="",p="",h="";if(1===u.length&&e.packedInputs){const e=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];l=`${e[0]>1}_${e[1]>1}`}else if(2!==u.length||e.packedInputs){if(u.length>2&&!e.packedInputs){const e=a.ZSL.computeStrides(u);h=`${e[0]===s[1]}_${e[e.length-1]===s[1]}`}}else p=`${u[0]>1}_${u[1]>1}`;const d=t.shape.length,f=2===u.length&&a.ZSL.arraysEqual(t.shape,s),m=1===a.ZSL.sizeFromShape(t.shape),g=a.C0T.getBroadcastDims(t.shape,n.shape),y=!e.packedInputs&&d===n.shape.length&&a.ZSL.arraysEqual(s,n.texData.texShape),x=e.packedInputs||u.length>2?"":`${s[0]>1}_${s[1]>1}`;r+=`${d}_${y}_${i?c:""}_${u.length}_${m}_${g}_${f}_${l}_${p}_${h}_${x}_${o}`}else{const e=t.isUniform?"uniform":t.texData.texShape;r+=`${t.shape}_${e}_${o}`}});const o=e.userCode;let s=e.constructor.name;return s+="_"+r+"_"+o+`${(0,a._K2)().getNumber("WEBGL_VERSION")}`,s}(e,p,d),m=this.getAndSaveBinary(f,()=>ue(this.gpgpu,e,p,d)),g=null!=this.activeTimers;let y;g&&(y=this.startTimer()),(0,a._K2)().get("ENGINE_COMPILE_ONLY")||function(e,t,n,r,o){t.program.enableShapeUniforms||(le(t.inShapeInfos,n),le([t.outShapeInfo],[r]));const s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),1===(0,a._K2)().getNumber("WEBGL_VERSION")&&null!==t.infLoc&&e.gl.uniform1f(t.infLoc,1/0),null!==t.nanLoc&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((n,r)=>{const o=t.program.variableNames[r],s=t.uniformLocations[o],i=t.uniformLocations[`offset${o}`],u=t.inShapesLocations[`${o}Shape`],c=t.inTexShapesLocations[`${o}TexShape`];if(u){const{uniformShape:r}=oe(t.program.packedInputs,n.shape,n.texData.texShape);switch(r.length){case 1:e.gl.uniform1iv(u,new Int32Array(r));break;case 2:e.gl.uniform2iv(u,new Int32Array(r));break;case 3:e.gl.uniform3iv(u,new Int32Array(r));break;case 4:e.gl.uniform4iv(u,new Int32Array(r))}}if(c&&e.gl.uniform2i(c,n.texData.texShape[0],n.texData.texShape[1]),null!=s)if(n.isUniform)if(a.ZSL.sizeFromShape(n.shape)<2)e.gl.uniform1f(s,n.uniformValues[0]);else{let t=n.uniformValues;t instanceof Float32Array||(t=new Float32Array(t)),e.gl.uniform1fv(s,t)}else null!=n.texData.slice&&null!=i&&e.gl.uniform1i(i,n.texData.slice.flatOffset),e.setInputMatrixTexture(n.texData.texture.texture,s,r)});const u=t.outShapeLocation;if(u)switch(r.shape.length){case 1:e.gl.uniform1iv(u,new Int32Array(r.shape));break;case 2:e.gl.uniform2iv(u,new Int32Array(r.shape));break;case 3:e.gl.uniform3iv(u,new Int32Array(r.shape));break;case 4:e.gl.uniform4iv(u,new Int32Array(r.shape))}if(t.outShapeStridesLocation){const n=a.ZSL.computeStrides(r.shape);switch(r.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(n));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(n));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(n))}}t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,r.texData.texShape[0],r.texData.texShape[1]),t.program.customUniforms&&o&&t.program.customUniforms.forEac

2h((n,r)=>{const a=t.customUniformLocations[r],s=o[r];if("float"===n.type)e.gl.uniform1fv(a,s);else if("vec2"===n.type)e.gl.uniform2fv(a,s);else if("vec3"===n.type)e.gl.uniform3fv(a,s);else if("vec4"===n.type)e.gl.uniform4fv(a,s);else if("int"===n.type)e.gl.uniform1iv(a,s);else if("ivec2"===n.type)e.gl.uniform2iv(a,s);else if("ivec3"===n.type)e.gl.uniform3iv(a,s);else{if("ivec4"!==n.type)throw Error(`uniform type ${n.type} is not supported yet.`);e.gl.uniform4iv(a,s)}}),e.executeProgram()}(this.gpgpu,m,p,d,r),l.forEach(e=>this.disposeIntermediateTensorInfo(e)),g&&(y=this.endTimer(y),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(y)}));const x=(0,a._K2)().get("WEBGL_FLUSH_THRESHOLD");if(x>0){const e=a.ZSL.now();e-this.lastGlFlushTime>x&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=e)}if(!(0,a._K2)().getBool("WEBGL_LAZILY_UNPACK")&&c.isPacked&&!1===o){const e=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),e}return i}compileAndRun(e,t,n,r,a=!1){n=n||t[0].dtype;return this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){if(!this.disposed){if(!(0,a._K2)().getBool("IS_TEST")){Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]})}this.textureManager.dispose(),null!=this.canvas&&"undefined"!=typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0}}floatPrecision(){return null==this.floatPrecisionValue&&(this.floatPrecisionValue=(0,a.DZQ)(()=>{if(!(0,a._K2)().get("WEBGL_RENDER_FLOAT32_ENABLED")){const e=(0,a._K2)().getBool("DEBUG");(0,a._K2)().set("DEBUG",!1);const t=this.abs((0,a.d_2)(1e-8)).dataSync()[0];if((0,a._K2)().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return 32===this.floatPrecision()?1e-7:1e-4}uploadToGPU(e){const t=this.texData.get(e),{shape:n,dtype:r,values:o,texture:s,usage:i,isPacked:u}=t;if(null!=s)return;const l=null!=this.activeTimers;let p;l&&(p=a.ZSL.now());let h=t.texShape;if(null==h&&(h=function(e,t=!1){let n=(0,a._K2)().getNumber("WEBGL_MAX_TEXTURE_SIZE"),r=(0,a._K2)().getNumber("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE");if(r===1/0&&(0,a._K2)().getBool("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE")&&(r=n/2),t&&(n*=2,r*=2,1===(e=e.map((t,n)=>n>=e.length-2?a.ZSL.nearestLargerEven(e[n]):e[n])).length&&(e=[2,e[0]])),2!==e.length){const t=a.ZSL.squeezeShape(e);e=t.newShape}let o=a.ZSL.sizeFromShape(e),s=null;e.length<=1&&o<=n?s=[1,o]:2===e.length&&e[0]<=n&&e[1]<=n?s=e:3===e.length&&e[0]*e[1]<=n&&e[2]<=n?s=[e[0]*e[1],e[2]]:3===e.length&&e[0]<=n&&e[1]*e[2]<=n?s=[e[0],e[1]*e[2]]:4===e.length&&e[0]*e[1]*e[2]<=n&&e[3]<=n?s=[e[0]*e[1]*e[2],e[3]]:4===e.length&&e[0]<=n&&e[1]*e[2]*e[3]<=n&&(s=[e[0],e[1]*e[2]*e[3]]);const i=null!=s&&Math.max(...s)>r&&Math.min(...s)<=(t?2:1)&&Math.min(...s)>0;if(null==s||i)if(t){const t=N(e);let n=2,r=2;e.length&&([n,r]=I(e)),o=t*(n/2)*(r/2),s=a.ZSL.sizeToSquarishShape(o).map(e=>2*e)}else s=a.ZSL.sizeToSquarishShape(o);return s}(n,u),t.texShape=h),null!=o){const e=A(n);let s,i=h[1],f=h[0];const m=o instanceof Uint8Array||o instanceof Uint8ClampedArray;!u&&m||([i,f]=d(h[0],h[1])),s=u?new ye(e,m):new ge(e,m);const g=m?[f,i]:h,y=this.makeTensorInfo(g,r),x=this.texData.get(y.dataId);x.usage=m?c.PIXELS:c.UPLOAD,x.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(y.dataId),i,f,o);const b=[[f,i]],v=!0,w=this.runWebGLProgram(s,[y],r,b,v),T=this.texData.get(w.dataId);t.texShape=T.texShape,t.isPacked=T.isPacked,t.usage=T.usage,(0,a._K2)().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(t.texture=T.texture,t.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(y),l&&(this.uploadWaitMs+=a.ZSL.now()-p)}else{const e=this.acquireTexture(h,i,r,u);t.texture=e}}convertAndCacheOnCPU(e,t){const n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),null!=t&&(n.values=function(e,t){if("float32"===t||"complex64"===t)return e;if("int32"===t||"bool"===t){const n="int32"===t?new Int32Array(e.length):new Uint8Array(e.length);for(let t=0;t<n.length;++t)n[t]=Math.round(e[t]);return n}throw new Error(`Unknown dtype ${t}`)}(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>1024*this.numMBBeforeWarning*1024){(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*a.ZSL.bytesPerElement(t)}checkCompileCompletion(){for(const[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){const e=[];

2if(this.gpgpu.parallelCompilationExtension){for(const[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}for(const[,t]of Object.entries(this.binaryCache)){const n=new Promise(e=>{try{this.checkCompletion_(t),e(!0)}catch(e){throw e}});e.push(n)}return Promise.all(e)}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await(0,a.dA1)(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(!1===this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)){if(!1===this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS))throw b(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.");throw new Error("Failed to link vertex and fragment shaders.")}return!0}getUniformLocations(){for(const[,e]of Object.entries(this.binaryCache)){const{uniformLocations:t,customUniformLocations:n,infLoc:r,nanLoc:a,inShapesLocations:o,inTexShapesLocations:s,outShapeLocation:i,outShapeStridesLocation:u,outTexShapeLocation:c}=ce(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=n,e.infLoc=r,e.nanLoc=a,e.inShapesLocations=o,e.inTexS

2hapesLocations=s,e.outShapeLocation=i,e.outShapeStridesLocation=u,e.outTexShapeLocation=c}}}or.nextDataId=0,a.eMq.isBrowser()&&(0,a.gJX)("webgl",()=>new or,2);const sr="\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n";class ir{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=a.C0T.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=pe(this.outputShape.length),this.userCode=`\n      float binaryOperation(float a, float b) {\n        ${e}\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    `}}const ur="\n  result.r = isNaN.r ? NAN : result.r;\n  result.g = isNaN.g ? NAN : result.g;\n  result.b = isNaN.b ? NAN : result.b;\n  result.a = isNaN.a ? NAN : result.a;\n";class cr{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=a.C0T.assertAndGetBroadcastShape(t,n);const o=this.outputShape.length;this.enableShapeUniforms=pe(o);let s="";if(r)if(0===o||1===a.ZSL.sizeFromShape(this.outputShape))s="\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        ";else{if(s=`\n          ${ae(o)} coords = getOutputCoords();\n        `,1===o)this.enableShapeUniforms?s+="\n            result.y = (coords + 1) >= outShape ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          ":s+=`\n            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          `;else{const e=zn("coords",o);this.enableShapeUniforms?s+=`\n            bool nextRowOutOfBounds =\n              (${e[o-2]} + 1) >= outShape[${o} - 2];\n            bool nextColOutOfBounds =\n              (${e[o-1]} + 1) >= outShape[${o} - 1];\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          `:s+=`\n            bool nextRowOutOfBounds =\n              (${e[o-2]} + 1) >= ${this.outputShape[o-2]};\n            bool nextColOutOfBounds =\n              (${e[o-1]} + 1) >= ${this.outputShape[o-1]};\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          `}}this.userCode=`\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        ${e}\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        ${s}\n\n        setOutput(result);\n      }\n    `}}function lr(e){const{inputs:t,backend:n}=e,{x:r}=t;return n.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}const pr={kernelName:a.lzr,backendName:"webgl",kernelFunc:lr};function hr(e){const{inputs:t,backend:n}=e,{real:r,imag:a}=t,o=n.makeTensorInfo(r.shape,"complex64"),s=n.texData.get(o.dataId),i=lr({inputs:{x:r},backend:n}),u=lr({inputs:{x:a},backend:n});return s.complexTensorInfos={real:i,imag:u},o}const dr={kernelName:a.pr3,backendName:"webgl",kernelFunc:hr},fr="return (a < 0.) ? b * a : a;",mr="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));

2\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n";const gr={kernelName:a.X0$,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",a.ZSL.createScalarValue(s,"float32")),u=(0,a._K2)().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cr(mr,o.shape,i.shape):new ir(fr,o.shape,i.shape),c=n.runWebGLProgram(u,[o,i],"float32");return n.disposeIntermediateTensorInfo(i),c}},yr="return (a < 0.) ? b * a : a;",xr="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n";const br={kernelName:a.Ncv,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{x:r,alpha:o}=t,s=(0,a._K2)().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cr(xr,r.shape,o.shape):new ir(yr,r.shape,o.shape);return n.runWebGLProgram(s,[r,o],"float32")}},vr="if (isnan(x)) return x;";function wr({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:o,backend:s})=>{const{x:i}=o,u=s,c=r||i.dtype;if(u.shouldExecuteOnCPU([i])&&null!=n){const e=u.texData.get(i.dataId),t=n(e.values,c);return u.makeTensorInfo(i.shape,c,t)}let l;return l=(0,a._K2)().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&null!=t?new er(i.shape,t):new Yn(i.shape,e),u.runWebGLProgram(l,[i],c)}}function Tr({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:o,dtype:s}){return({inputs:i,backend:u})=>{const{a:c,b:l}=i,p=u;if(r&&"complex64"===c.dtype){const t=p.texData.get(c.dataId),n=p.texData.get(l.dataId),[r,o]=[[t.complexTensorInfos.real,n.complexTensorInfos.real],[t.complexTensorInfos.imag,n.complexTensorInfos.imag]].map(t=>{const[n,r]=t,o={dataId:n.dataId,dtype:n.dtype,shape:c.shape},s={dataId:r.dataId,dtype:r.dtype,shape:l.shape},i=new ir(e,c.shape,l.shape);return p.runWebGLProgram(i,[o,s],(0,a.TuY)(n.dtype,r.dtype))}),s=hr({inputs:{real:r,imag:o},backend:p});return p.disposeIntermediateTensorInfo(r),p.disposeIntermediateTensorInfo(o),s}const h=s||(0,a.TuY)(c.dtype,l.dtype);if(("string"===c.dtype||"string"===l.dtype||p.shouldExecuteOnCPU([c,l]))&&null!=o){const e=p.texData.get(c.dataId).values,t=p.texData.get(l.dataId).values,n="string"===c.dtype?a.C0T.fromUint8ToStringArray(e):e,r="string"===c.dtype?a.C0T.fromUint8ToStringArray(t):t,[s,i]=o(c.shape,l.shape,n,r,h),u=p.makeTensorInfo(i,h);return p.texData.get(u.dataId).values=s,u}let d;return d=(0,a._K2)().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&null!=t?new cr(t,c.shape,l.shape,n):new ir(e,c.shape,l.shape),p.runWebGLProgram(d,[c,l],h)}}function Sr(e,t=!1){if("linear"===e)return"return x;";if("relu"===e)return t?"\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n":qn;if("elu"===e)return t?"\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n":"return (x >= 0.0) ? x : (exp(x) - 1.0);";if("relu6"===e)return t?"\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n":Qn;if("prelu"===e)return t?xr:yr;if("leakyrelu"===e)return t?mr:fr;if("sigmoid"===e)return"return 1.0 / (1.0 + exp(-1.0 * x));";throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}class Cr{constructor(e,t,n,r=!1,a=!1,o=!1,s=null,i=!1,u=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=pe(this.outputShape.length);const c=r?e[1]:e[2],l=Math.ceil(c/2),p=r?"i * 2, rc.y":"rc.y, i * 2",h=a?"rc.z, i * 2":"i * 2, rc.z",d=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.

2ywyw"]:["b.xyxy","b.zwzw"];let m="",g="";s&&(m=i?`vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          ${s}\n        }`:u?`vec4 activation(vec4 a) {\n          vec4 b = getLeakyreluAlphaAtOutCoords();\n          ${s}\n        }`:`vec4 activation(vec4 x) {\n          ${s}\n        }`,g="result = activation(result);");const y=o?"result += getBiasAtOutCoords();":"";o&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights"),u&&this.variableNames.push("leakyreluAlpha");let x="rc.x",b="rc.x";e[0]<t[0]?x=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(b=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`\n      ${m}\n      // Don't use uniform for sharedDimensionPacked for performance.\n      const float sharedDimension = ${l}.0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < ${l}; i++) {\n          int batchA = ${x};\n          int batchB = ${b};\n          vec4 a = getMatrixA(batchA, ${p});\n          vec4 b = getMatrixB(batchB, ${h});\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += (${d[0]} * ${f[0]});\n          result += (${d[1]} * ${f[1]});\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        ${y}\n\n        ${g}\n\n        setOutput(result);\n      }\n    `}}const kr="return areal * breal - aimag * bimag;",Er="return areal * bimag + aimag * breal;";class $r{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=a.C0T.assertAndGetBroadcastShape(t,n),this.userCode=`\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        ${e}\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    `}}const Nr="return a * b;";function Ir(e){const{inputs:t,backend:n}=e,{a:r,b:o}=t,s=a.C0T.upcastType(r.dtype,o.dtype);if("complex64"===r.dtype){const e=n.texData.get(r.dataId),t=n.texData.get(o.dataId),a=new $r(kr,r.shape,o.shape),s=new $r(Er,r.shape,o.shape),i=[{dataId:e.complexTensorInfos.real.dataId,dtype:e.complexTensorInfos.real.dtype,shape:r.shape},{dataId:e.complexTensorInfos.imag.dataId,dtype:e.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:t.complexTensorInfos.real.dataId,dtype:t.complexTensorInfos.real.dtype,shape:o.shape},{dataId:t.complexTensorInfos.imag.dataId,dtype:t.complexTensorInfos.imag.dtype,shape:o.shape}],u=n.runWebGLProgram(a,i,"float32"),c=n.runWebGLProgram(s,i,"float32"),l=hr({inputs:{real:u,imag:c},backend:n});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),l}if(n.shouldExecuteOnCPU([r,o])){const e=n.texData.get(r.dataId),t=n.texData.get(o.dataId),[a,i]=mn(r.shape,o.shape,e.values,t.values,s),u=n.makeTensorInfo(i,s);return n.texData.get(u.dataId).values=a,u}let i;return i=(0,a._K2)().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cr(Nr,r.shape,o.shape):new ir(Nr,r.shape,o.shape),n.runWebGLProgram(i,[r,o],s)}const Ar={kernelName:a.xu7,backendName:"webgl",kernelFunc:Ir};function Rr(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{shape:s}=r,i=n,u=a.ZSL.sizeFromShape(o.shape),c=a.ZSL.inferFromImplicitShape(s,u),l=a.ZSL.sizeFromShape(c);a.ZSL.assert(u===l,()=>`The new shape (${c}) has ${l} elements and the old shape (${o.shape}) has ${u} elements. The new shape and old shape must have the same number of elements.`);const p=i.texData.get(o.dataId);return!p.isPacked||_(o.shape,c)||null!==p.texture&&_(p.shape,c)?(i.incRef(o.dataId),{dataId:o.dataId,shape:c,dtype:o.dtype}):function(e,t,n){const r=[N(e.shape),...I(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},o=[N(t),...I(t)],s=new Wn(o,r),i=[r],u=n.runWebGLProgram(s,[a],e.dtype,i,!0);return{dataId:u.dataId,shape:t,dtype:u.dtype}}(o,c,i)}const _r={kernelName:a.R23,backendName:"webgl",kernelFunc:Rr};class Or{constructor(e,t){this.variableNames=["x"];const{windowSize:n,batchSize:r,inSize:o,outSize:s}=e;this.outputShape=[r,s];const i=4*Math.floor(n/4),u=n%4;let c="sumValue += dot(values, ones);";if(null!=t){const e=1/t;c=`sumValue += dot(values * ${a.ZSL.isInt(e)?e.toPrecision(2):e}, ones);`}let l="";o%n>0&&(l=`\n        if (inIdx < 0 || inIdx >= ${o}) {\n          return 0.0;\n        }\n      `),this.userCode=`\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        ${l}\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${n};\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < ${i}; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          ${c}\n        }\n\n        int inIdx = inOffset + ${i};\n        if (${1===u}) {\n          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);\n\n          ${c}\n        } else if (${2===u}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1), 0.0, 0.0);\n\n          ${c}\n        } else if (${3===u}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2), 0.0);\n\n          ${c}\n        }\n        setOutput(sumValue);\n      }\n    `}}class Fr{constructor(e,t){this.variableNames=["x"];const{windowSize:n,batchSize:r,inSize:a,outSize:o}=e;this.outputShape=[r,o];let s="0.0",i="";"prod"===t?s="1.0":"min"===t?(s="1.0 / 1e-20",i="min"):"max"===t&&(s="-1.0 / 1e-20",i="max");let u=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;"sum"===t?u="sumValue":"prod"===t?u="prodValue":"all"===t?u="allValue":"any"===t&&(u="anyValue");const c=4*Math.floor(n/4),l=n%4;let p=`\n      if (${"sum"===t}) {\n        sumValue += dot(values, ones);\n      } else if (${"prod"===t}) {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = ${i}(values, minMaxValue);\n        if (${"min"===t} || ${"max"===t}) {\n          minMaxValue = ${i}(values, minMaxValue);\n          bvec4 isNaN = isnan(values);\n          if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {\n            minMaxValue = vec4(NAN);\n          }\n        }\n      }\n    `,h="vec4";"all"===t?(s="1.0",p="\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      ",h="bvec4"):"any"===t&&(s="0.0",p="\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      ",h="bvec4");let d="";a%n>0&&(d=`\n        if (inIdx < 0 || inIdx >= ${a}) {\n          return initializationValue;\n        }\n      `),this.userCode=`\n      const float initializationValue = ${s};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        ${d}\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${n};\n\n        vec4 minMaxValue = vec4(${s});\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < ${c}; i += 4) {\n          int inIdx = inOffset + i;\n          ${h} values = ${h}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          ${p}\n        }\n\n        int inIdx = inOffset + ${c};\n        if (${1===l}) {\n          ${h} values = ${h}(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          ${p}\n        } else if (${2===l}) {\n          ${h} values = ${h}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          ${p}\n        } else if (${3===l}) {\n          ${h} values = ${h}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          ${p}\n        }\n        setOutput(${u});\n      }\n    `}}function Dr(e,t,n,r){const o=function(e){const t=[];for(;0===t.length||1!==t[t.length-1].outSize;){const n=t.length?t[t.length-1].outSize:e[1],r=a.C0T.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}(e.shape);let s=e;for(let a=0;a<o.length;a++){const{inSize:i,windowSize:u,outSize:c}=o[a];let l,p;l="mean"===n?0===a?new Or({windowSize:u,inSize:i,batchSize:e.shape[0],outSize:c},i):new Or({windowSize:u,inSize:i,batchSize:e.shape[0],outSize:c}):new Fr({windowSize:u,inSize:i,batchSize:e.shape[0],outSize:c},n),p=s,s=r.runWebGLProgram(l,[s],t),p.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(p)}return s}class Lr{constructor(e,t){this.variableNames=["A"];const n=new Array(e.length);for(let r=0;r<n.length;r++)n[r]=e[t[r]];this.outputShape=n,this.rank=n.length;const r=ae(this.rank),a=function(e){const t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);const n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let t=0;t<e.length;t++)r[e[t]]=n[t];return r.join()}(t);this.userCode=`\n    void main() {\n      ${r} resRC = getOutputCoords();\n      setOutput(getA(${a}));\n    }\n    `}}class Mr{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;const n=new Array(e.length);for(let r=0;r<n.length;r++)n[r]=e[t[r]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);const r=ae(this.rank),a=Vn("rc",this.rank),o=new Array(this.rank);for(let e=0;e<t.length;e++)o[t[e]]=a[e];const s=`vec2(${o.slice(-2).join()})`,i=`++${a[this.rank-1]} < ${n[this.rank-1]}`,u=`getChannel(getA(${o.join()}), ${s})`;this.userCode=`\n    void main() {\n      ${r} rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = ${u};\n      if(${i}) {\n        result[1] = ${u};\n      }\n      --${a[this.rank-1]};\n      if(++${a[this.rank-2]} < ${n[this.rank-2]}) {\n        result[2] = ${u};\n        if(${i}) {\n          result[3] = ${u};\n        }\n      }\n      setOutput(result);\n    }\n    `}}function Pr(e,t,n){const r=(0,a._K2)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Mr(e.shape,t):new Lr(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function Br(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{axis:s,keepDims:i}=r;return function(e,t,n,r){const o=t,s=e.shape.length,i=a.ZSL.parseAxisParam(o,e.shape);let u=i;const c=a.C0T.getAxesPermutation(u,s),l=null!=c;let p=e;l&&(p=Pr(e,c,r),u=a.C0T.getInnerMostAxes(u.length,s)),a.C0T.assertAxesAreInnerMostDims("sum",u,s);const[h,d]=a.C0T.computeOutAndReduceShapes(p.shape,u);let f=h;n&&(f=a.C0T.expandShapeToKeepDim(h,i));const m=a.ZSL.sizeFromShape(d),g=Rr({inputs:{x:p},attrs:{shape:[a.ZSL.sizeFromShape(e.shape)/m,m]},backend:r}),y=Dr(g,(0,a.chL)(e.dtype),"sum",r),x=Rr({inputs:{x:y},attrs:{shape:f},backend:r});return r.disposeIntermediateTensorInfo(g),r.disposeIntermediateTensorInfo(y),l&&r.disposeIntermediateTensorInfo(p),x}(o,s,i,n)}const Vr={kernelName:a.WuN,backendName:"webgl",kernelFunc:Br};function zr(e){const{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:o}=r,s=n,i=a.shape.length,u=new Array(i);for(let e=0;e<u.length;e++)u[e]=a.shape[o[e]];let c;if(s.shouldExecuteOnCPU([a])){const e=s.texData.get(a.dataId).values,t=Pn(e,a.shape,a.dtype,o,u);c=s.makeTensorInfo(u,a.dtype);s.texData.get(c.dataId).values=t}else c=Pr(a,o,s);return c}const Ur={kernelName:a.wx0,backendName:"webgl",kernelFunc:zr};function Wr({a:e,b:t,transposeA:n,transposeB:r,backend:o,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:u=0,activation:c=null}){const l=e.shape.length,p=t.shape.length,h=n?e.shape[l-2]:e.shape[l-1],d=r?t.shape[p-1]:t.shape[p-2],f=n?e.shape[l-1]:e.shape[l-2],m=r?t.shape[p-2]:t.shape[p-1],g=e.shape.slice(0,-2),y=t.shape.slice(0,-2),x=a.ZSL.sizeFromShape(g),b=

2a.ZSL.sizeFromShape(y),v=a.ZEY.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([f,m]);a.ZSL.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);const w=n?[x,h,f]:[x,f,h],T=r?[b,m,d]:[b,d,m],S=Rr({inputs:{x:e},backend:o,attrs:{shape:w}}),C=Rr({inputs:{x:t},backend:o,attrs:{shape:T}}),k=[S,C],E=Math.max(x,b),$=n?S.shape[1]:S.shape[2],N=null!=s,I=null!=i,A="leakyrelu"===c,R=null!=c?Sr(c,!0):null;let _;if((1===f||1===m)&&$>1e3&&!1===(N||I||A||null!=R)){let e=S,t=C;n&&(e=zr({inputs:{x:S},backend:o,attrs:{perm:[0,2,1]}}),k.push(e)),r&&(t=zr({inputs:{x:C},backend:o,attrs:{perm:[0,2,1]}}),k.push(t));const a=1===m;let s=e;1!==m&&(s=Rr({inputs:{x:e},backend:o,attrs:{shape:[E,$,1]}}),k.push(s));const i=1===m?2:1;let u=t;a&&(u=Rr({inputs:{x:t},backend:o,attrs:{shape:[E,1,$]}}),k.push(u));const c=Ir({inputs:{a:s,b:u},backend:o});_=Br({inputs:{x:c},backend:o,attrs:{axis:i,keepDims:!0}}),k.push(c)}else{const c=(0,a.TuY)(e.dtype,t.dtype),l=new Cr(w,T,[E,f,m],n,r,N,R,I,A),p=[S,C];if(null!=s&&p.push(s),I&&p.push(i),A){const e=o.makeTensorInfo([],"float32",a.ZSL.createScalarValue(u,"float32"));p.push(e),k.push(e)}_=o.runWebGLProgram(l,p,c)}const O=Rr({inputs:{x:_},backend:o,attrs:{shape:v}});k.push(_);for(const e of k)o.disposeIntermediateTensorInfo(e);return O}const Gr={kernelName:a.Dr,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{a:a,b:o,bias:s,preluActivationWeights:i}=t,{transposeA:u,transposeB:c,activation:l,leakyreluAlpha:p}=r;return Wr({a:a,b:o,transposeA:u,transposeB:c,backend:n,bias:s,preluActivationWeights:i,leakyreluAlpha:p,activation:l})}},jr="return abs(x);";const Kr={kernelName:a.ljI,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&"complex64"!==r.dtype){const e=n.texData.get(r.dataId),t=kn(e.values);return n.makeTensorInfo(r.shape,r.dtype,t)}let o;return o=(0,a._K2)().getBool("WEBGL_PACK_UNARY_OPERATIONS")?new er(r.shape,jr):new Yn(r.shape,jr),n.runWebGLProgram(o,[r],r.dtype)}},Hr=wr({opSnippet:Zn+"\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n"}),Yr={kernelName:a.Vvy,backendName:"webgl",kernelFunc:Hr},Zr=wr({opSnippet:Zn+"\n  if (x < 1.0) return NAN;\nreturn log(x + sqrt(x * x - 1.0));"}),Xr={kernelName:a.PH8,backendName:"webgl",kernelFunc:Zr},qr="return a + b;",Qr=Tr({opSnippet:qr,packedOpSnippet:qr,supportsComplex:!0,cpuKernelImpl:Ht}),Jr={kernelName:a.OMN,backendName:"webgl",kernelFunc:Qr};class ea{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((e,t)=>`T${t}`);const n=[];this.variableNames.forEach(e=>{n.push(`float v${e} = get${e}AtOutCoords();`)});const r=this.variableNames.map(e=>`v${e}`).join(" + ");this.userCode=`\n      void main() {\n        ${n.join("\n        ")}\n\n        float result = ${r};\n        setOutput(result);\n      }\n    `}}class ta{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((e,t)=>`T${t}`);const n=[];this.variableNames.forEach(e=>{n.push(`vec4 v${e} = get${e}AtOutCoords();`)});const r=this.variableNames.map(e=>`v${e}`).join(" + ");this.userCode=`\n      void main() {\n        ${n.join("\n        ")}\n\n        vec4 result = ${r};\n        setOutput(result);\n      }\n    `}}const na={kernelName:a.EkD,backendName:"webgl",kernelFunc:function e(t){const{inputs:n,backend:r}=t,o=n;if(1===o.length)return lr({inputs:{x:o[0]},backend:r});if(o.length>(0,a._K2)().get("WEBGL_MAX_TEXTURES_IN_SHADER")){const t=Math.floor(o.length/2),n=e({

2inputs:o.slice(0,t),backend:r}),a=e({inputs:o.slice(t),backend:r});return e({inputs:[n,a],backend:r})}const s=o.map(e=>e.dtype).reduce((e,t)=>(0,a.TuY)(e,t)),i=o.map(e=>e.shape),u=(0,a._K2)().getBool("WEBGL_PACK")?new ta(o[0].shape,i):new ea(o[0].shape,i);return r.runWebGLProgram(u,o,s)}};const ra={kernelName:a.u8Z,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{axis:s,keepDims:i}=r,u=o.shape.length,c=a.ZSL.parseAxisParam(s,o.shape);let l=c;const p=a.C0T.getAxesPermutation(l,u);let h=o;null!=p&&(h=zr({inputs:{x:o},backend:n,attrs:{perm:p}}),l=a.C0T.getInnerMostAxes(l.length,u)),a.C0T.assertAxesAreInnerMostDims("all",l,u);const[d,f]=a.C0T.computeOutAndReduceShapes(h.shape,l),m=Rr({inputs:{x:h},backend:n,attrs:{shape:[-1,a.ZSL.sizeFromShape(f)]}}),g=Dr(m,m.dtype,"all",n);let y;if(i){y=Rr({inputs:{x:g},backend:n,attrs:{shape:a.C0T.expandShapeToKeepDim(d,c)}})}else y=Rr({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),null!=p&&n.disposeIntermediateTensorInfo(h),y}};const aa={kernelName:a.FSt,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{axis:s,keepDims:i}=r,u=o.shape.length,c=a.ZSL.parseAxisParam(s,o.shape);let l=c;const p=a.C0T.getAxesPermutation(l,u);let h=o;null!=p&&(h=zr({inputs:{x:o},backend:n,attrs:{perm:p}}),l=a.C0T.getInnerMostAxes(l.length,u)),a.C0T.assertAxesAreInnerMostDims("any",l,u);const[d,f]=a.C0T.computeOutAndReduceShapes(h.shape,l),m=Rr({inputs:{x:h},backend:n,attrs:{shape:[-1,a.ZSL.sizeFromShape(f)]}}),g=Dr(m,m.dtype,"any",n);let y;if(i){y=Rr({inputs:{x:g},backend:n,attrs:{shape:a.C0T.expandShapeToKeepDim(d,c)}})}else y=Rr({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),null!=p&&n.disposeIntermediateTensorInfo(h),y}};class oa{constructor(e,t,n){this.variableNames=["A"];const{windowSize:r,batchSize:a,outSize:o}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,o];const s="max"===t?">":"<",i=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${r};\n\n        int bestIndex = inOffset;\n        float bestValue = getA(batch, bestIndex);\n\n        for (int i = 0; i < ${r}; i++) {\n          int inIdx = ${i};\n          float candidate = getA(batch, inIdx);\n          if (candidate ${s} bestValue) {\n            bestValue = candidate;\n            bestIndex = inIdx;\n          }\n        }\n        setOutput(float(bestIndex));\n      }\n    `}}class sa{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,a.ZSL.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);const o=e[e.length-1],s=Math.ceil(o/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");const i=this.outputShape,u=i.length,c=ae(u),l=zn("coords",u);let p,h;if(1===s){h=u+1;const e=ae(h);p=`\n        ${e} sourceLocR = ${e}(${l.join()}, 0);\n        ++${l[u-1]};\n        ${e} sourceLocG = ${e}(${l.join()}, 0);\n        ++${l[u-2]};\n        ${e} sourceLocA = ${e}(${l.join()}, 0);\n        --${l[u-1]};\n        ${e} sourceLocB = ${e}(${l.join()}, 0);\n        --${l[u-2]};`}else h=u,p=`\n        ${c} sourceLocR = coords;\n        ++${l[u-1]};\n        ${c} sourceLocG = coords;\n        ++${l[u-2]};\n        ${c} sourceLocA = coords;\n        --${l[u-1]};\n        ${c} sourceLocB = coords;\n        --${l[u-2]};`;const d=["x","y","z","w","u","v"].slice(0,h),f="."+d[h-1],m=d.map(e=>"int "+e),g=zn("sourceLocR",h-1).concat("inIdx.r"),y=zn("sourceLocG",h-1).concat("inIdx.g"),x=zn("sourceLocB",h-1).concat("inIdx.b"),b=zn("sourceLocA",h-1).concat("inIdx.a"),v="max"===n?"greaterThan":"lessThan",w=r?"":`\n          inIdx = round(vec4(getBestIndicesAChannel(${g.join()}),\n                             getBestIndicesAChannel(${y.join()}),\n                             getBestIndicesAChannel(${x.join()}),\n                             getBestIndicesAChannel(${b.join()})));`,T=`vec4(\n            getAChannel(${g.join()}),\n            hasNextCol ? getAChannel(${y.join()}) : 0.,\n            hasNextRow ? getAChannel(${x.join()}) : 0.,\n            hasNextRow && hasNextCol ? getAChannel(${b.join()}) : 0.)`,S=r?"":`\n      float getBestIndicesAChannel(${m.join()}) {\n        return getChannel(getBestIndicesA(${d.join()}),\n                                          vec2(${d.slice(-2).join()}));\n      }`;this.userCode=`\n      float getAChannel(${m.join()}) {\n        return getChannel(getA(${d.join()}),\n                               vec2(${d.slice(-2).join()}));\n      }\n      ${S}\n      void main() {\n        ${c} coords = getOutputCoords();\n        bool hasNextCol = ${l[u-1]} < ${i[u-1]-1};\n        bool hasNextRow = ${l[u-2]} < ${i[u-2]-1};\n        ${p}\n        ivec4 srcIdx = ivec4(sourceLocR${f}, sourceLocG${f},\n          sourceLocB${f}, sourceLocA${f}) * ${t};\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = ${T};\n\n        for (int i = 0; i < ${t};

2 i++) {\n          inIdx = srcIdx;\n          ${w}\n          vec4 candidate = ${T};\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4(${v}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    `}}function ia(e,t,n,r=null){let o=t.shape[0],s=t.shape[1];null!=r&&(o=r.shape[0],s=r.shape[1]);const i=a.C0T.computeOptimalWindowSize(s),u={windowSize:i,inSize:s,batchSize:o,outSize:Math.ceil(s/i)},c=new oa(u,n,null==r),l=[t];null!=r&&l.push(r);const p=e.runWebGLProgram(c,l,"int32");if(1===p.shape[1])return p;const h=ia(e,t,n,p);return e.disposeIntermediateTensorInfo(p),h}function ua(e,t,n,r=null){const o=null!=r?r.shape:t.shape,s=o[o.length-1],i=a.C0T.computeOptimalWindowSize(s),u=new sa(o,i,n,null==r),c=null==r?[t]:[t,r],l=e.runWebGLProgram(u,c,"int32");if(l.shape.length===t.shape.length){const r=ua(e,t,n,l);return e.disposeIntermediateTensorInfo(l),r}return l}function ca(e,t,n,r){const o=[n];if(a.C0T.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),o,t.shape.length),!(0,a._K2)().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){const n=[],s=e.texData.get(t.dataId);let i=t;null!==s&&s.isPacked&&(i=e.unpackTensor(t),n.push(i));const[u,c]=a.C0T.computeOutAndReduceShapes(i.shape,o),l=a.ZSL.sizeFromShape(c),p=Rr({inputs:{x:i},backend:e,attrs:{shape:[-1,l]}});n.push(p);const h=ia(e,p,r);n.push(h);const d=Rr({inputs:{x:h},backend:e,attrs:{shape:u}});return n.forEach(t=>e.disposeIntermediateTensorInfo(t)),d}return ua(e,t,r)}const la={kernelName:a.Jp_,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{axis:s}=r;let i=a.ZSL.parseAxisParam(s,o.shape);const u=a.C0T.getAxesPermutation(i,o.shape.length);let c=o;const l=[];null!=u&&(c=zr({inputs:{x:o},backend:n,attrs:{perm:u}}),l.push(c),i=a.C0T.getInnerMostAxes(i.length,c.shape.length)),a.C0T.assertAxesAreInnerMostDims("argMax",[i[0]],c.shape.length);const p=ca(n,c,i[0],"max");return l.forEach(e=>n.disposeIntermediateTensorInfo(e)),p}};const pa={kernelName:a.p_m,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{axis:s}=r;let i=a.ZSL.parseAxisParam(s,o.shape);const u=a.C0T.getAxesPermutation(i,o.shape.length);let c=o;const l=[];null!=u&&(c=zr({inputs:{x:o},backend:n,attrs:{perm:u}}),l.push(c),i=a.C0T.getInnerMostAxes(i.length,c.shape.length)),a.C0T.assertAxesAreInnerMostDims("argMin",[i[0]],c.shape.length);const p=ca(n,c,i[0],"min");return l.forEach(e=>n.disposeIntermediateTensorInfo(e)),p}},ha=wr({opSnippet:Zn+"\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n"}),da={kernelName:a.QKF,backendName:"webgl",kernelFunc:ha},fa=wr({opSnippet:Zn+"return log(x + sqrt(x * x + 1.0));"}),ma={kernelName:a.epO,backendName:"webgl",kernelFunc:fa},ga=wr({opSnippet:Zn+"\n  return atan(x);\n"}),ya={kernelName:a.TyE,backendName:"webgl",kernelFunc:ga},xa=Tr({opSnippet:sr+"\n  return atan(a, b);\n",packedOpSnippet:"\n  vec4 result = atan(a, b);\n  bvec4 isNaNA = isnan(a);\n  bvec4 isNaNB = isnan(b);\n  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);\n  "+ur+"\n  return result;\n"}),ba={kernelName:a.lxb,backendName:"webgl",kernelFunc:xa},va=wr({opSnippet:Zn+"\n  if ((x < -1.0) || (x > 1.0)) return NAN;\nreturn (log(1.0 + x) - log(1.0 - x)) / 2.0;"}),wa={kernelName:a.zP9,backendName:"webgl",kernelFunc:va};class Ta{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],"avg"===t&&n)throw new Error("Cannot compute positions for average pool.");const o=e.filterWidth,s=e.strideHeight,i=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,l=e.effectiveFilterHeight,p=e.effectiveFilterWidth,h=e.padInfo.top,d=e.padInfo.left;this.outputShape=e.outShape;const f="avg"===t,m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`;let y="0.0";if(f||(y="-1.0 / 1e-20"),n){const t=">=";return void(this.userCode=`\n        const ivec2 strides = ivec2(${s}, ${i});\n        const ivec2 pads = ivec2(${h}, ${d});\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < ${l};\n              wR += ${u}) {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= ${e.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${p};\n                wC += ${c}) {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= ${e.inWidth}) {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value ${t} currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = ${r?a?m:g:`wR * ${p} + wC`};\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      `)}let x=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;"avg"===t&&(x="avgValue / count");const b=4*Math.floor(o/4),v=o%4,w=`\n      if (${f}

2) {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    `;this.userCode=`\n      const ivec2 strides = ivec2(${s}, ${i});\n      const ivec2 pads = ivec2(${h}, ${d});\n      const float initializationValue = ${y};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= ${e.inWidth}) {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(${y});\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < ${l};\n            wR += ${u}) {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= ${e.inHeight}) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${b}; wC += 4) {\n            int xC = xCCorner + wC * ${c};\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${c}, d),\n              getValue(batch, xR, xC + 2 * ${c}, d),\n              getValue(batch, xR, xC + 3 * ${c}, d)\n            );\n\n            ${w}\n          }\n\n          int xC = xCCorner + ${b};\n          if (${1===v}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            ${w}\n          } else if (${2===v}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${c}, d),\n              initializationValue,\n              initializationValue\n            );\n\n            ${w}\n          } else if (${3===v}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${c}, d),\n              getValue(batch, xR, xC + 2 * ${c}, d),\n              initializationValue\n            );\n\n            ${w}\n          }\n        }\n        setOutput(${x});\n      }\n    `}}class Sa{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],"avg"===t&&n)throw new Error("Cannot compute positions for average pool.");const o=e.filterWidth,s=e.strideDepth,i=e.strideHeight,u=e.strideWidth,c=e.dilationDepth,l=e.dilationHeight,p=e.dilationWidth,h=e.effectiveFilterDepth,d=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,g=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;const x="avg"===t;let b="0.0";if(x||(b="-1.0 / 1e-20"),n){const t=">=";return void(this.userCode=`\n        const ivec3 strides =\n            ivec3(${s}, ${i}, ${u});\n        const ivec3 pads = ivec3(${m}, ${g}, ${y});\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < ${h};\n              wD += ${c}) {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= ${e.inDepth}) {\n              continue;\n            }\n\n            for (int wR = 0; wR < ${d};\n                wR += ${l}) {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= ${e.inHeight}) {\n                continue;\n              }\n\n              for (int wC = 0; wC < ${f};\n                  wC += ${p}) {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= ${e.inWidth}) {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value ${t} currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;

2\n                  minMaxPosition = ${r?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${d} * ${f} +\n                      wR * ${f} + wC`};\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      `)}let v=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;"avg"===t&&(v="avgValue / count");const w=4*Math.floor(o/4),T=o%4,S=`\n      if (${x}) {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    `;this.userCode=`\n      const ivec3 strides =\n        ivec3(${s}, ${i}, ${u});\n      const ivec3 pads = ivec3(${m}, ${g}, ${y});\n      const float initializationValue = ${b};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= ${e.inWidth}) {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(${b});\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < ${h};\n            wD += ${c}) {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= ${e.inDepth}) {\n            continue;\n          }\n\n          for (int wR = 0; wR < ${d};\n            wR += ${l}) {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= ${e.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${w}; wC += 4) {\n              int xC = xCCorner + wC * ${p};\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${p}, ch),\n                getValue(batch, xD, xR, xC + 2 * ${p}, ch),\n                getValue(batch, xD, xR, xC + 3 * ${p}, ch)\n              );\n\n              ${S}\n            }\n\n            int xC = xCCorner + ${w};\n            if (${1===T}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              ${S}\n            } else if (${2===T}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${p}, ch),\n                initializationValue,\n                initializationValue\n              );\n\n              ${S}\n            } else if (${3===T}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${p}, ch),\n                getValue(batch, xD, xR, xC + 2 * ${p}, ch),\n                initializationValue\n              );\n\n              ${S}\n            }\n          }\n          setOutput(${v});\n        }\n      }\n    `}}const Ca={kernelName:a.ho8,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t;B(o,"avgPool");const{filterSize:s,strides:i,pad:u,dimRoundingMode:c}=r;a.ZSL.assert(a.C0T.eitherStridesOrDilationsAreOne(i,1),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '1'`);const l=a.C0T.computePool2DInfo(o.shape,s,i,1,u,c);if(1===l.filterWidth&&1===l.filterHeight&&a.ZSL.arraysEqual(l.inShape,l.outShape))return lr({inputs:{x:o},backend:n});const p=new Ta(l,"avg",!1);return n.runWebGLProgram(p,[o],"float32")}};const ka={kernelName:a.cS,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{filterSize:s,strides:i,pad:u,dimRoundingMode:c,dataFormat:l}
vendor: 4,243 bytes, line 2
2=r,p=a.C0T.computePool3DInfo(o.shape,s,i,[1,1,1],u,c,l),h=new Sa(p,"avg",!1);return n.runWebGLProgram(h,[o],"float32")}};class Ea{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;const t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,o=e.dilationHeight,s=e.dilationWidth,i=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=i-1-e.padInfo.top,l=u-1-e.padInfo.left,p=1/(t*n);this.userCode=`\n      const ivec2 pads = ivec2(${c}, ${l});\n      const float avgMultiplier = float(${p});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${i};\n            wR += ${o}) {\n          float dyR = float(dyRCorner + wR) / ${r}.0;\n\n          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < ${u};\n            wC+= ${s}) {\n            float dyC = float(dyCCorner + wC) / ${a}.0;\n\n            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}class $a{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;const t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,o=e.strideHeight,s=e.strideWidth,i=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,l=e.effectiveFilterDepth,p=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=l-1-e.padInfo.front,f=p-1-e.padInfo.top,m=h-1-e.padInfo.left,g=1/(t*n*r);this.userCode=`\n      const ivec3 pads = ivec3(${d}, ${f}, ${m});\n      const float avgMultiplier = float(${g});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < ${l};\n            wD += ${i}) {\n          float dyD = float(dyDCorner + wD) / ${a}.0;\n\n          if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < ${p};\n              wR += ${u}) {\n            float dyR = float(dyRCorner + wR) / ${o}.0;\n\n            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < ${h};\n                wC += ${c}) {\n              float dyC = float(dyCCorner + wC) / ${s}.0;\n\n              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}const Na={kernelName:a.wwC,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:o,input:s}=t,i=s,{filterSize:u,strides:c,pad:l,dimRoundingMode:p}=r,h=a.C0T.computePool3DInfo(i.shape,u,c,[1,1,1],l,p),d=new $a(h);return n.runWebGLProgram(d,[o],i.dtype)}};const Ia={kernelName:a.VCH,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:o,input:s}=t,i=s;B([o,s],"avgPoolGrad");const{filterSize:u,strides:c,pad:l}

2=r,p=a.C0T.computePool2DInfo(i.shape,u,c,1,l),h=new Ea(p);return n.runWebGLProgram(h,[o],i.dtype)}};const Aa={kernelName:a.jAQ,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{a:a,b:o}=t,{transposeA:s,transposeB:i}=r;return Wr({a:a,b:o,transposeA:s,transposeB:i,backend:n})}};class Ra{constructor(e,t,n,r,o,s){this.outputShape=[],this.variableNames=["x","mean","variance"],a.C0T.assertAndGetBroadcastShape(e,t),a.C0T.assertAndGetBroadcastShape(e,n);let i="0.0";null!=r&&(a.C0T.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let u="1.0";null!=o&&(a.C0T.assertAndGetBroadcastShape(e,o),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = ${i};\n        float scale = ${u};\n        float inv = scale * inversesqrt(variance + float(${s}));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    `}}class _a{constructor(e,t,n,r,o,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],a.C0T.assertAndGetBroadcastShape(e,t),a.C0T.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";null!=r&&(a.C0T.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let u="vec4(1.0)";null!=o&&(a.C0T.assertAndGetBroadcastShape(e,o),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`\n      void main() {\n        vec4 offset = ${i};\n        vec4 scale = ${u};\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4(${s}));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    `}}const Oa={kernelName:a.i5R,backendName:"webgl",kernelFunc:({inputs:e,backend:t,attrs:n})=>{const{x:r,mean:o,variance:s,offset:i,scale:u}=e;a.ZSL.assert(o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),a.ZSL.assert(null==i||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),a.ZSL.assert(null==u||o.shape.length===u.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:c}=n;null==c&&(c=.001);const l=[r,o,s];let p=null;null!=i&&(p=i.shape,l.push(i));let h=null;null!=u&&(h=u.shape,l.push(u));const d=(0,a._K2)().getBool("WEBGL_PACK_NORMALIZATION")?new _a(r.shape,o.shape,s.shape,p,h,c):new Ra(r.shape,o.shape,s.shape,p,h,c);return t.runWebGLProgram(d,l,l[0].dtype)}};class Fa{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;const t=ae(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];const n=function(e){if(1===e)return"sourceLoc";if(e<=6)return Da.slice(0,e).map(e=>"sourceLoc."+e).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}(this.rank);let r;r=`\n        ${t} sourceLoc;\n        ${t} coords = getOutputCoords();\n        ${e.map((e,t)=>`sourceLoc.${Da[t]} = start[${t}] + coords.${Da[t]};`).join("\n")}\n      `,this.userCode=`\n      void main() {\n        ${r}\n        setOutput(getSource(${n}));\n      }\n    `}}const Da=["x","y","z","w","u","v"];class La{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"}];const t=ae(this.rank),n=zn("coords",this.rank),r=zn("sourceLoc",this.rank),a=1===this.rank?"sourceLoc":`vec2(${r.slice(-2).join()})`,o=`getChannel(getSource(${r.join()}), ${a})`,s=`\n      result.x = ${o};\n      if (++${n[this.rank-1]} < ${e[this.rank-1]}) {\n        ++${r[this.rank-1]};\n        result.y = ${o};\n        --${r[this.rank-1]};\n      }\n    `,i=1===this.rank?"":`\n      --${n[this.rank-1]};\n      if (++${n[this.rank-2]} < ${e[this.rank-2]}) {\n        ++${r[this.rank-2]};\n        result.z = ${o};\n        if (++${n[this.rank-1]} < ${e[this.rank-1]}) {\n          ++${r[this.rank-1]};\n          result.w = ${o};\n        }\n      }

2\n    `,u=this.rank<=4?`sourceLoc = coords +\n            ${t}(${e.map((e,t)=>`start[${t}]`).join()});`:e.map((e,t)=>`${r[t]} = ${n[t]} + start[${t}];`).join("\n");this.userCode=`\n      void main() {\n        ${t} coords = getOutputCoords();\n        ${t} sourceLoc;\n        ${u}\n        vec4 result = vec4(0.);\n        ${s}\n        ${i}\n        setOutput(result);\n      }\n    `}}function Ma(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{begin:s,size:i}=r,[u,c]=a.Kro.parseSliceParams(o,s,i);if(a.Kro.assertParamsValid(o,u,c),0===a.ZSL.sizeFromShape(c))return n.makeTensorInfo(c,o.dtype,[]);if(n.shouldExecuteOnCPU([o])||"string"===o.dtype){const e=n.texData.get(o.dataId),t=En(e.values,u,c,o.shape,o.dtype);return n.makeTensorInfo(c,o.dtype,t)}const{isPacked:l}=n.texData.get(o.dataId),p=a.Kro.isSliceContinous(o.shape,u,c);if(l||!p){const e=(0,a._K2)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new La(c):new Fa(c),t=[u];return n.runWebGLProgram(e,[o],o.dtype,t)}return n.uploadToGPU(o.dataId),function(e,t,n,r){const o=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,o),i.refCount=1,i.shape=n,i.dtype=e.dtype;let u=a.Kro.computeFlatOffset(t,a.ZSL.computeStrides(e.shape));o.slice&&(u+=o.slice.flatOffset),i.slice={flatOffset:u,origDataId:o.slice&&o.slice.origDataId||e.dataId};const c=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,c+1),s}(o,u,c,n)}const Pa={kernelName:a.JiE,backendName:"webgl",kernelFunc:Ma},Ba={kernelName:a.Ik2,backendName:"webgl",kernelFunc:e=>{const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{blockShape:s,crops:i}=r;a.ZSL.assert(o.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");const u=s.reduce((e,t)=>e*t),c=a.C0T.getReshaped(o.shape,s,u),l=a.C0T.getPermuted(c.length,s.length),p=a.C0T.getReshapedPermuted(o.shape,s,u),h=a.C0T.getSliceBeginCoords(i,s.length),d=a.C0T.getSliceSize(p,i,s.length),f=[],m=Rr({inputs:{x:o},backend:n,attrs:{shape:c}}),g=zr({inputs:{x:m},backend:n,attrs:{perm:l}}),y=Rr({inputs:{x:g},backend:n,attrs:{shape:p}}),x=Ma({inputs:{x:y},backend:n,attrs:{begin:h,size:d}});return f.push(m),f.push(g),f.push(y),f.forEach(e=>n.disposeIntermediateTensorInfo(e)),x}};const Va={kernelName:a.N4F,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a,weights:o}=t,{size:s}=r,i=n.readSync(a.dataId),u=n.readSync(o.dataId),c=Yt(i,u,o.dtype,o.shape,s);return n.makeTensorInfo([s],o.dtype,c)}};const za={kernelName:a.vj7,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{s0:r,s1:o}=t,s=n.readSync(r.dataId),i=n.readSync(o.dataId),u=a.C0T.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([u.length],"int32",Int32Array.from(u))}},Ua=Tr({opSnippet:"return float(a != b);",cpuKernelImpl:yn,dtype:"bool"}),Wa={kernelName:a.ylV,backendName:"webgl",kernelFunc:Ua};function Ga(e){const{inputs:t,backend:n}=e,{input:r}=t;return lr({inputs:{x:n.texData.get(r.dataId).complexTensorInfos.real},backend:n})}const ja={kernelName:a.LRy,backendName:"webgl",kernelFunc:Ga};const Ka={kernelName:a.KXH,backendName:"webgl",kernelFunc:function e(t){const{inputs:n,backend:r,attrs:o}=t,{x:s}=n,{dtype:i}=o;if("complex64"===i){if("complex64"===s.dtype)return lr({inputs:{x:s},backend:r});const t=a.Ul9(s.shape),n=e({inputs:{x:s},backend:r,attrs:{dtype:"float32"}}),o=hr({inputs:{real:n,imag:t},backend:r});return t.dispose(),r.disposeIntermediateTensorInfo(n),o}if("complex64"===s.dtype){const t=Ga({inputs:{input:s},backend:r}),n=e({inputs:{x:t},backend:r,attrs:{dtype:i}});return r.disposeIntermediateTensorInfo(t),n}if(!a.ZSL.hasEncodingLoss(s.dtype,i)){const e=lr({inputs:{x:s},backend:r});return{dataId:e.dataId,shape:e.shape,dtype:i}}if(r.shouldExecuteOnCPU([s])){const e=r.texData.get(s.dataId).values,[t,n,a]=Xt(e,s.shape,s.dtype,i);return r.makeTensorInfo(t,n,a)}if("int32"===i)return function(e,t){const n=new Yn(e.shape,"return float(int(x));"),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}(s,r);if("bool"===i){const e=r.makeTensorInfo([],"bool",a.ZSL.getTypedArrayFromDType("bool",1)),t=Ua({inputs:{a:s,b:e},backend:r});return r.disposeIntermediateTensorInfo(e),t}throw new Error(`Error in Cast: failed to cast ${s.dtype} to ${i}`)}},Ha="return ceil(x);",Ya=wr({opSnippet:Ha,packedOpSnippet:Ha,cpuKernelImpl:qt}),Za={kernelName:a.QDP,backendName:"webgl",kernelFunc:Ya};class Xa{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode="\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    "}}class qa{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode="\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    "}}const Qa={kernelName:a.vaV,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{clipValueMin:s,clipValueMax:i}=r;let u;u=(0,a._K2)().getBool("WEBGL_PACK_CLIP")?new qa(o.shape):new Xa(o.shape);const c=[[s],[i]];return n.runWebGLProgram(u,[o],o.dtype,c)}};class Ja{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode="\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    "}}function eo(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}const to={kernelName:a.$zE,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),o=new Ja(r.shape),s=[eo(r,a.complexTensorInfos.real),eo(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(o,s,s[0].dtype)}};

2class no{constructor(e){this.outputShape=[],this.outputShape=a.C0T.computeOutShape(e,1),this.variableNames=e.map((e,t)=>`T${t}`);const t=new Array(e.length-1);t[0]=e[0][1];for(let n=1;n<t.length;n++)t[n]=t[n-1]+e[n][1];const n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let e=1;e<t.length;e++){const r=t[e-1];n.push(`else if (yC < ${t[e]}) setOutput(getT${e}(yR, yC-${r}));`)}const r=t.length,o=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${o}));`),this.userCode=`\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        ${n.join("\n        ")}\n      }\n    `}}class ro{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=a.C0T.computeOutShape(e,t);const n=this.outputShape,r=n.length,o=ae(r),s=zn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((e,t)=>`T${t}`);const u=new Array(e.length-1);u[0]=e[0][t];for(let n=1;n<u.length;n++)u[n]=u[n-1]+e[n][t];const c=i[t],l=i.slice(-2),p=i.join();let h=`if (${c} < ${u[0]}) {\n        return getChannel(\n            getT0(${p}), vec2(${l.join()}));\n        }`;for(let e=1;e<u.length;e++){const t=u[e-1];h+=`\n        if (${c} < ${u[e]}  && ${c} >= ${u[e-1]}) {\n          return getChannel(\n            getT${e}(${ao(i,c,t)}),\n            vec2(${ao(l,c,t)}));\n        }`}const d=u.length,f=u[u.length-1];h+=`\n        return getChannel(\n          getT${d}(${ao(i,c,f)}),\n          vec2(${ao(l,c,f)}));`,this.userCode=`\n      float getValue(${i.map(e=>"int "+e)}) {\n        ${h}\n      }\n\n      void main() {\n        ${o} coords = getOutputCoords();\n        vec4 result = vec4(getValue(${s}), 0., 0., 0.);\n\n        ${s[r-1]} = ${s[r-1]} + 1;\n        if (${s[r-1]} < ${n[r-1]}) {\n          result.g = getValue(${s});\n        }\n\n        ${s[r-2]} = ${s[r-2]} + 1;\n        if (${s[r-2]} < ${n[r-2]}) {\n          result.a = getValue(${s});\n        }\n\n        ${s[r-1]} = ${s[r-1]} - 1;\n        if (${s[r-2]} < ${n[r-2]} &&\n            ${s[r-1]} < ${n[r-1]}) {\n          result.b = getValue(${s});\n        }\n        setOutput(result);\n      }\n    `}}function ao(e,t,n){const r=e.indexOf(t);return e.map((e,t)=>t===r?`${e} - ${n}`:e).join()}function oo(e){const{inputs:t,backend:n}=e,{input:r}=t;return lr({inputs:{x:n.texData.get(r.dataId).complexTensorInfos.imag},backend:n})}const so={kernelName:a.dv8,backendName:"webgl",kernelFunc:oo};function io(e,t,n){const r=e[0].dtype;if("complex64"===r){const r=e.map(e=>Ga({inputs:{input:e},backend:n})),a=e.map(e=>oo({inputs:{input:e},backend:n})),o=io(r,t,n),s=io(a,t,n),i=hr({inputs:{real:o,imag:s},backend:n});return r.forEach(e=>n.disposeIntermediateTensorInfo(e)),a.forEach(e=>n.disposeIntermediateTensorInfo(e)),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(s),i}let o=n.shouldExecuteOnCPU(e);if("string"===r&&(o=!0),o){const o=e.map(e=>{const r=a.ZSL.sizeFromShape(e.shape.slice(t));return Rr({inputs:{x:e},backend:n,attrs:{shape:[-1,r]}})}),s=o.map(e=>({vals:n.readSync(e.dataId),shape:e.shape})),i=a.C0T.computeOutShape(o.map(e=>e.shape),1),u=1===o[0].shape[0],c=Qt(s,i,r,u),l=a.C0T.computeOutShape(e.map(e=>e.shape),t),p=n.makeTensorInfo(l,r,c);return o.forEach(e=>n.disposeIntermediateTensorInfo(e)),p}const s=(0,a._K2)().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(e.length>s){const r=[];for(let a=0;a<e.length;a+=s){const o=e.slice(a,a+s);r.push(io(o,t,n))}const a=io(r,t,n);for(const e of r)n.disposeIntermediateTensorInfo(e);return a}if((0,a._K2)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){const a=new ro(e.map(e=>e.shape),t);return n.runWebGLProgram(a,e,r)}const{tensors2D:i,outShape:u}=function(e,t,n){const r=a.C0T.computeOutShape(e.map(e=>e.shape),t),o=e.map(e=>Rr({inputs:{x:e},attrs:{shape:[-1,a.ZSL.sizeFromShape(e.shape.slice(t))]},backend:n}));return{tensors2D:o,outShape:r}}(e,t,n),c=new no(i.map(e=>e.shape)),l=n.runWebGLProgram(c,i,r);i.forEach(e=>n.disposeIntermediateTensorInfo(e));const p=Rr({inputs:{x:l},attrs:{shape:u},backend:n});return n.disposeIntermediateTensorInfo(l),p}function uo(e){const{inputs:t,backend:n,attrs:r}=e,{axis:o}=r,s=a.ZSL.parseAxisParam(o,t[0].shape)[0],i=t.map(e=>e.shape);a.C0T.assertParamsConsistent(i,s);const u=a.C0T.computeOutShape(t.map(e=>e.shape),s);if(0===a.ZSL.sizeFromShape(u))return n.makeTensorInfo(u,t[0].dtype,[]);const c=t.filter(e=>a.ZSL.sizeFromShape(e.shape)>0);
vendor: 5,898 bytes, line 2
2return 1===c.length?lr({inputs:{x:c[0]},backend:n}):io(c,s,n)}const co={kernelName:a.$dB,backendName:"webgl",kernelFunc:uo};class lo{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;const o=e.padInfo.top,s=e.padInfo.left,i=e.strideHeight,u=e.strideWidth,c=e.dilationHeight,l=e.dilationWidth,p=e.filterHeight,h=e.filterWidth,d=4*Math.floor(e.inChannels/4),f=e.inChannels%4,m="channelsLast"===e.dataFormat,g=m?1:2,y=m?2:3,x=m?3:1;let b="",v="";n&&(b=r?`float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          ${n}\n        }`:a?`float activation(float a) {\n          float b = getLeakyreluAlphaAtOutCoords();\n          ${n}\n        }`:`\n          float activation(float x) {\n            ${n}\n          }\n        `,v="result = activation(result);");const w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`\n      ${b}\n\n      const ivec2 strides = ivec2(${i}, ${u});\n      const ivec2 pads = ivec2(${o}, ${s});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords[${x}];\n\n        ivec2 xRCCorner =\n            ivec2(coords[${g}], coords[${y}]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${p}; wR++) {\n          int xR = xRCorner + wR * ${c};\n\n          if (xR < 0 || xR >= ${e.inHeight}) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${h}; wC++) {\n            int xC = xCCorner + wC * ${l};\n\n            if (xC < 0 || xC >= ${e.inWidth}) {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < ${d}; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if (${m}) {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if (${1===f}) {\n\n              if (${m}) {\n                dotProd +=\n                    getX(batch, xR, xC, ${d}) *\n                    getW(wR, wC, ${d}, d2);\n              } else {\n                dotProd +=\n                    getX(batch, ${d}, xR, xC) *\n                    getW(wR, wC, ${d}, d2);\n              }\n\n            } else if (${2===f}) {\n              vec2 wValues = vec2(\n                getW(wR, wC, ${d}, d2),\n                getW(wR, wC, ${d} + 1, d2)\n              );\n\n              if (${m}) {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, ${d}),\n                  getX(batch, xR, xC, ${d} + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, ${d}, xR, xC),\n                  getX(batch, ${d} + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if (${3===f}) {\n              vec3 wValues = vec3(\n                getW(wR, wC, ${d}, d2),\n                getW(wR, wC, ${d} + 1, d2),\n                getW(wR, wC, ${d} + 2, d2)\n              );\n\n              if (${m}) {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, ${d}),\n                  getX(batch, xR, xC, ${d} + 1),\n                  getX(batch, xR, xC, ${d} + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, ${d}, xR, xC),\n                  getX(batch, ${d} + 1, xR, xC),\n                  getX(batch, ${d} + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        ${w}\n        ${v}\n        setOutput(result);\n      }\n    `}}class po{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;const t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,o=e.strideHeight,s=e.strideWidth,i=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,l=e.filterDepth,p=e.filterHeight,h=e.filterWidth,d=4*Math.floor(e.inChannels/4),f=e.inChannels%4;this.userCode=`\n      const ivec3 strides = ivec3(${a}, ${o}, ${s});\n      const ivec3 pads = ivec3(${t}, ${n}, ${r});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < ${l};

2 wF++) {\n          int xF = xFCorner + wF * ${i};\n\n          if (xF < 0 || xF >= ${e.inDepth}) {\n            continue;\n          }\n\n          for (int wR = 0; wR < ${p}; wR++) {\n            int xR = xRCorner + wR * ${u};\n\n            if (xR < 0 || xR >= ${e.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${h}; wC++) {\n              int xC = xCCorner + wC * ${c};\n\n              if (xC < 0 || xC >= ${e.inWidth}) {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < ${d}; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if (${1===f}) {\n                dotProd +=\n                  getX(batch, xF, xR, xC, ${d}) *\n                  getW(wF, wR, wC, ${d}, d2);\n              } else if (${2===f}) {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, ${d}),\n                  getX(batch, xF, xR, xC, ${d} + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, ${d}, d2),\n                  getW(wF, wR, wC, ${d} + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if (${3===f}) {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, ${d}),\n                  getX(batch, xF, xR, xC, ${d} + 1),\n                  getX(batch, xF, xR, xC, ${d} + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, ${d}, d2),\n                  getW(wF, wR, wC, ${d} + 1, d2),\n                  getW(wF, wR, wC, ${d} + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}class ho{constructor(e,t=!1,n=null,r=!1,o=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=pe(this.outputShape.length);const s=e.padInfo.left,i=e.strideWidth,u=e.dilationWidth,c=e.filterHeight,l=e.filterWidth,p=l;let h="\n       int xR; int xC; int xCOffset;\n       vec4 wTexel; vec4 previous; vec4 final;";for(let e=0;e<l;e++)h+=`\n           vec4 xTexelC${2*e};\n           int xTexelC${2*e}Ready;\n           vec4 xTexelC${2*e+1};\n           int xTexelC${2*e+1}Ready;\n           vec4 xC${e};`;h+=`\n     for (int r = 0; r < ${c}; r++) {\n      for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {\n       `;for(let e=0;e<l;e++)h+=`\n           xTexelC${2*e} = vec4(0.0);\n           xTexelC${2*e}Ready = 0;\n           xTexelC${2*e+1} = vec4(0.0);\n           xTexelC${2*e+1}Ready = 0;\n           xC${e} = vec4(0.0);`;h+="\n         xR = xRCorner + r * dilations[0];\n         if (xR >=0 && xR < inDims[0]) {\n       ";for(let t=0;t<(p+1)/2;t++){const n=2*t;if(h+=`\n           xC = xCCorner + ${n*u};\n           `,1===i){if(n<l&&(s%2==1?(h+=`\n                 xCOffset = xC + 1;\n                 if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${n}Ready == 0) {\n                   xTexelC${n} = getX(batch, xR, xCOffset, d1);\n\n                   // Need to manually clear unused channels in case\n                   // we're reading from recycled texture.\n                   if (xCOffset + 1 >= inDims[1]) {\n                     xTexelC${n}.zw = vec2(0.0);\n                   }\n                   xTexelC${n}Ready = 1;\n                 }\n               `,h+=1===u&&n>0?`\n                 xC${n} = vec4(xTexelC${n-2}.zw, xTexelC${n}.xy);\n                 `:`\n                   xCOffset = xC + 1 - 2;\n\n                   if (xCOffset >= 0 && xCOffset < inDims[1]) {\n                     previous = getX(batch, xR, xCOffset, d1);\n\n                     // Need to manually clear unused channels in case\n                     // we're reading from recycled texture.\n                     if (xCOffset + 1 >= inDims[1]) {\n                       previous.zw = vec2(0.0);\n                     }\n\n                     xC${n} = vec4(previous.zw, xTexelC${n}.xy);\n                   } else {\n                     xC${n} = vec4(0.0, 0.0, xTexelC${n}.xy);\n                   }\n                   `):h+=`\n                 if (xC >= 0 && xC < inDims[1] && xTexelC${n}Ready == 0) {\n                   xTexelC${n} = getX(batch, xR, xC, d1);\n                   if (xC + 1 >= inDims[1]) {\n                     xTexelC${n}.zw = vec2(0.0);\n                   }\n                   xTexelC${n}Ready = 1;\n                 }\n\n                 xC${n} = xTexelC${n};\n                 `,n+1<l)){const e=s%2==0?a.ZSL.nearestLargerEven(u):u;u%2==0&&s%2==1||u%2!=0&&s%2!=1?(h+=`\n                   xCOffset = xC + imod(pads[1], 2) + ${e};\n\n                   if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${n+1}Ready == 0) {\n                     xTexelC${n+1} = getX(batch, xR, xCOffset, d1);\n\n                     // Need to manually clear unused channels in case\n                     // we're reading from recycled texture.\n                     if (xCOffset + 1 >= inDims[1]) {\n                       xTexelC${n+1}.zw = vec2(0.0);\n                     }\n                     xTexelC${n+1}Ready = 1;\n                   }\n                   `,h+=u>1?`\n                     xCOffset -= 2;\n                     if (xCOffset >= 0 && xCOffset < inDims[1]) {\n                      previous = getX(batch, xR, xCOffset, d1);\n                      xC${n+1} = vec4(previous.zw, xTexelC${n+1}.xy);\n                     } else {\n                      xC${n+1} = vec4(0.0, 0.0, xTexelC${n+1}.xy);\n                     }\n                     `:`\n                     xC${n+1} = vec4(xTexelC${n}.zw, xTexelC${n+1}.xy);

2\n                     `):h+=1===e?`\n                     xC${n+1} = xTexelC${n};\n                     `:`\n                     xCOffset = xC + ${e};\n\n                     if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${n+1}Ready == 0) {\n                       xTexelC${n+1} = getX(batch, xR, xCOffset, d1);\n                       if (xCOffset + 1 >= inDims[1]) {\n                         xTexelC${n+1}.zw = vec2(0.0);\n                       }\n                       xTexelC${n+1}Ready = 1;\n                     }\n\n                     xC${n+1} = xTexelC${n+1};\n                     `}}else n<l&&(s%2==1?(h+=`\n                 xCOffset = xC + 1 - strides[1];\n                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${n}Ready == 0) {\n                   xTexelC${n} = getX(batch, xR, xCOffset, d1);\n                   // Need to manually clear unused channels in case\n                   // we're reading from recycled texture.\n                   if (xCOffset + 1 >= inDims[1]) {\n                     xTexelC${n}.zw = vec2(0.0);\n                   }\n                   xTexelC${n}Ready = 1;\n                 }\n\n                 if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${n+1}Ready == 0) {\n                   xTexelC${n+1} = getX(batch, xR, xC + 1, d1);\n                   // Need to manually clear unused channels in case\n                   // we're reading from recycled texture.\n                   if (xC + 2 >= inDims[1]) {\n                     xTexelC${n+1}.zw = vec2(0.0);\n                   }\n                   xTexelC${n+1}Ready = 1;\n                 }\n\n                 xC${n} = vec4(xTexelC${n}.zw, xTexelC${n+1}.zw);\n               `,n+1<l&&(h+=`\n                   final = vec4(0.0);\n                   xCOffset = xC + 1 + strides[1];\n                   if(xCOffset >= 0 && xCOffset < inDims[1]) {\n                     final = getX(batch, xR, xCOffset, d1);\n                   }\n                   xC${n+1} = vec4(xTexelC${n+1}.xy, final.xy);\n                 `)):(h+=`\n                 if(xC >= 0 && xC < inDims[1] && xTexelC${n}Ready == 0) {\n                   xTexelC${n} = getX(batch, xR, xC, d1);\n                   if (xC + 1 >= inDims[1]) {\n                     xTexelC${n}.zw = vec2(0.0);\n                   }\n                   xTexelC${n}Ready = 1;\n                 }\n\n                 xCOffset = xC + strides[1];\n                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${n+1}Ready == 0) {\n                   xTexelC${n+1} = getX(batch, xR, xCOffset, d1);\n                   if (xCOffset + 1 >= inDims[1]) {\n                     xTexelC${n+1}.zw = vec2(0.);\n                   }\n                   xTexelC${n+1}Ready = 1;\n                 }\n\n                 xC${n} = vec4(\n                   xTexelC${n}.xy, xTexelC${n+1}.xy);\n               `,n+1<l&&(h+=`\n                   xC${n+1} = vec4(xTexelC${n}.zw, xTexelC${n+1}.zw);\n                 `)));n<l&&(h+=`\n             wTexel = getW(r, ${n}, d1, d2);\n             dotProd += xC${n}.xxzz * vec4(wTexel.xy, wTexel.xy);\n             if(d1 + 1 < ${e.inChannels}) {\n               dotProd += xC${n}.yyww * vec4(wTexel.zw, wTexel.zw);\n             }\n           `,n+1<l&&(h+=`\n               wTexel = getW(r, ${n+1}, d1, d2);\n               dotProd += xC${n+1}.xxzz * vec4(wTexel.xy, wTexel.xy);\n               if(d1 + 1 < ${e.inChannels}) {\n                 dotProd += xC${n+1}.yyww * vec4(wTexel.zw, wTexel.zw);\n               }\n             `))}h+="\n     }\n   ",h+="\n     }\n   ",h+="\n     }\n   ";let d="",f="";n&&(d=r?`vec4 activation(vec4 a) {\n           vec4 b = getPreluActivationWeightsAtOutCoords();\n           ${n}\n         }`:o?`vec4 activation(vec4 a) {\n           vec4 b = getLeakyreluAlphaAtOutCoords();\n           ${n}\n         }`:`vec4 activation(vec4 x) {\n           ${n}\n         }`,f="result = activation(result);");const m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),o&&this.variableNames.push("leakyreluAlpha"),this.userCode=`\n       ${d}\n\n       void main() {\n         ivec4 coords = getOutputCoords();\n         int batch = coords.x;\n         ivec2 xRCCorner = coords.yz * strides - pads;\n         int d2 = coords.w;\n         int xRCorner = xRCCorner.x;\n         int xCCorner = xRCCorner.y;\n\n         //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.\n         vec4 dotProd = vec4(0.000000000000001);\n\n         ${h}\n\n         vec4 result = dotProd - vec4(0.000000000000001);\n         ${m}\n         ${f}\n         setOutput(result);\n       }\n     `}}class fo{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec4"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=pe(this.outputShape.length);const{dataFormat:n}=t,r=z(),a="channelsLast"===n,o=a?1:2,s=a?2:3,i=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`;let u="";for(let e=0;e<=1;e++)for(let t=0;t<=1;t++)u+=`\n          blockIndex = rc.z + ${t};\n          pos = rc.y + ${e};\n\n          ${i}\n            offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];\n            d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);\n\n            if(d0 < inputShape[${o}] && d0 >= 0) {\n              // Use custom imod instead mod. On Intel GPU, mod may generate\n              // unexpected value.\n              // https://github.com/tensorflow/tfjs/issues/5447\n              offsetX = imod(blockIndex, outWidth) * stride[1] - pad[

21];\n              d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /\n                  inChannels);\n\n              if(d1 < inputShape[${s}] && d1 >= 0) {\n\n                ch = imod(pos, inChannels);\n\n                if (${a}) {\n                  innerDims = vec2(d1, ch);\n                  result[${2*e+t}] = getChannel(\n                    getA(rc.x, d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result[${2*e+t}] = getChannel(\n                    getA(rc.x, ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        `;this.userCode=`\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        ${u}\n\n        ${r.output} = result;\n      }\n    `}}function mo(e,t){const n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&1===n&&e[0]>1?[e[0],1]:null}function go({x:e,filter:t,convInfo:n,backend:r,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:u=null}){const c=e.shape,l=r.texData.get(e.dataId),p=n.inChannels,h=c[0]*c[1]*c[2],d=n.outChannels,f="channelsLast"===n.dataFormat,m=!1;let g;const y=[];if(null!=s){const e=mo(s.shape,f);null!=e&&(s=Rr({inputs:{x:s},backend:r,attrs:{shape:e}}),y.push(s))}if(null!=o){const e=mo(o.shape,f);null!=e&&(o=Rr({inputs:{x:o},backend:r,attrs:{shape:e}}),y.push(o))}if(!((1===h||1===d)&&p>1e3)&&l.isPacked&&f&&null!=l.texture&&c[2]%2!=0&&a.ZSL.arraysEqual(l.shape.slice(-3),c.slice(-3))){const p=c[0]*c[1]*(c[2]+1),h={dataId:e.dataId,shape:[1,p,n.inChannels],dtype:e.dtype},d=l.shape;l.shape=l.shape.slice(),l.shape[l.shape.length-2]++,a.ZSL.assert(_(l.shape,h.shape),()=>`packed reshape ${l.shape} to ${h.shape} isn't free`);const f=Rr({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(f);const x=Wr({a:h,b:f,backend:r,transposeA:false,transposeB:m,bias:o,activation:u,preluActivationWeights:s,leakyreluAlpha:i}),b=r.texData.get(x.dataId);a.ZSL.assert(b.isPacked,()=>"batchMatMul result is expected to be packed"),l.shape=d,b.shape=n.outShape,g=lr({inputs:{x:x},backend:r}),g.shape=n.outShape,y.push(x)}else{const a=n.outHeight*n.outWidth,c=Rr({inputs:{x:e},backend:r,attrs:{shape:f?[n.batchSize,a,n.inChannels]:[n.batchSize,n.inChannels,a]}}),l=Rr({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),p=Wr({a:f?c:l,b:f?l:c,transposeA:!f,transposeB:m,backend:r,bias:o,activation:u,preluActivationWeights:s,leakyreluAlpha:i});g=Rr({inputs:{x:p},backend:r,attrs:{shape:n.outShape}}),y.push(c),y.push(l),y.push(p)}for(const e of y)r.disposeIntermediateTensorInfo(e);return g}function yo({x:e,filter:t,convInfo:n,backend:r,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:u=null}){const{filterWidth:c,filterHeight:l,inChannels:p,outWidth:h,outHeight:d,dataFormat:f}=n,m="channelsLast"===f,g=c*l*p,y=d*h,x=[n.batchSize,g,y],b=[];if(null!=s){const e=mo(s.shape,m);null!=e&&(s=Rr({inputs:{x:s},backend:r,attrs:{shape:e}}),b.push(s))}if(null!=o){const e=mo(o.shape,m);null!=e&&(o=Rr({inputs:{x:o},backend:r,attrs:{shape:e}}),b.push(o))}const v=Rr({inputs:{x:t},backend:r,attrs:{shape:[1,g,a.ZSL.sizeFromShape(t.shape)/g]}});b.push(v);const w=new fo(x,n),T=[e.shape,[n.padInfo.top,n.padInfo.left],[n.strideHeight,n.strideWidth],[n.dilationHeight,n.dilationWidth],[n.inChannels],[n.filterWidth*n.inChannels],[n.outWidth]],S=r.runWebGLProgram(w,[e],"float32",T),C=Rr({inputs:{x:S},backend:r,attrs:{shape:x}});b.push(S),b.push(C);const k=null!=o,E=null!=s,$="leakyrelu"===u,N=u?Sr(u,!0):null,I=new Cr(m?C.shape:v.shape,m?v.shape:C.shape,m?[n.batchSize,y,n.outChannels]:[n.batchSize,n.outChannels,y],!0,!1,k,N,E,$),A=m?[C,v]:[v,C];if(o&&A.push(o),E&&A.push(s),$){const e=r.makeTensorInfo([],"float32",a.ZSL.createScalarValue(i,"float32"));A.push(e),b.push(e)}
vendor: 5,153 bytes, line 2
2const R=r.runWebGLProgram(I,A,"float32"),_=Rr({inputs:{x:R},backend:r,attrs:{shape:n.outShape}});b.push(R);for(const e of b)r.disposeIntermediateTensorInfo(e);return _}const xo={kernelName:a.p2J,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,filter:s}=t,{strides:i,pad:u,dataFormat:c,dilations:l,dimRoundingMode:p}=r,h=a.C0T.convertConv2DDataFormat(c),d=a.C0T.computeConv2DInfo(o.shape,s.shape,i,l,u,p,!1,h);let f;if(1!==d.filterHeight||1!==d.filterWidth||1!==d.dilationHeight||1!==d.dilationWidth||1!==d.strideHeight||1!==d.strideWidth||"SAME"!==d.padInfo.type&&"VALID"!==d.padInfo.type)if(d.strideWidth<=2&&"channelsLast"===h&&(0,a._K2)().getBool("WEBGL_EXP_CONV")){const e=new ho(d),t=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];f=n.runWebGLProgram(e,[o,s],"float32",t)}else if((0,a._K2)().getBool("WEBGL_CONV_IM2COL"))f=yo({x:o,filter:s,convInfo:d,backend:n});else{const e=new lo(d);f=n.runWebGLProgram(e,[o,s],"float32")}else f=go({x:o,filter:s,convInfo:d,backend:n});const m=Rr({inputs:{x:f},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(f),m}};class bo{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;const t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,o="channelsLast"===e.dataFormat;this.userCode=`\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < ${e.batchSize}; b++) {\n          for (int yR = 0; yR < ${e.outHeight}; yR++) {\n            int xR = wR + yR * ${t} - ${r};\n\n            if (xR < 0 || xR >= ${e.inHeight}) {\n              continue;\n            }\n\n            for (int yC = 0; yC < ${e.outWidth}; yC++) {\n              int xC = wC + yC * ${n} - ${a};\n\n              if (xC < 0 || xC >= ${e.inWidth}) {\n                continue;\n              }\n\n              if (${o}) {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}class vo{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;const t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,o="channelsLast"===e.dataFormat,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,u=o?1:2,c=o?2:3,l=o?3:1;this.userCode=`\n      const ivec2 pads = ivec2(${s}, ${i});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[${l}];\n\n        ivec2 dyCorner = ivec2(coords[${u}], coords[${c}]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${t}; wR++) {\n          float dyR = float(dyRCorner + wR) / ${r}.0;\n\n          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = ${t} - 1 - wR;\n\n          for (int wC = 0; wC < ${n}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${a}.0;\n\n            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = ${n} - 1 - wC;\n\n            for (int d2 = 0; d2 < ${e.outChannels}; d2++) {\n\n              if (${o}) {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}class wo{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;const t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,o=e.padInfo.top,s=e.padInfo.left;this.userCode=`\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < ${e.batchSize}; b++) {\n          for (int yF = 0; yF < ${e.outDepth};

2 yF++) {\n            int xF = wF + yF * ${t} - ${a};\n\n            if (xF < 0 || xF >= ${e.inDepth}) {\n              continue;\n            }\n\n            for (int yR = 0; yR < ${e.outHeight}; yR++) {\n              int xR = wR + yR * ${n} - ${o};\n\n              if (xR < 0 || xR >= ${e.inHeight}) {\n                continue;\n              }\n\n              for (int yC = 0; yC < ${e.outWidth}; yC++) {\n                int xC = wC + yC * ${r} - ${s};\n\n                if (xC < 0 || xC >= ${e.inWidth}) {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}class To{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;const t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,o=e.strideHeight,s=e.strideWidth,i=t-1-e.padInfo.front,u=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`\n      const ivec3 pads = ivec3(${i}, ${u}, ${c});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < ${t}; wF++) {\n          float dyF = float(dyFCorner + wF) / ${a}.0;\n\n          if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = ${t} - 1 - wF;\n\n          for (int wR = 0; wR < ${n}; wR++) {\n            float dyR = float(dyRCorner + wR) / ${o}.0;\n\n            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = ${n} - 1 - wR;\n\n            for (int wC = 0; wC < ${r}; wC++) {\n              float dyC = float(dyCCorner + wC) / ${s}.0;\n\n              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = ${r} - 1 - wC;\n\n              for (int d2 = 0; d2 < ${e.outChannels}; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}const So={kernelName:a.rFm,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,dy:s}=t,{strides:i,pad:u,dataFormat:c,dimRoundingMode:l,filterShape:p}=r,h=a.C0T.convertConv2DDataFormat(c),d=a.C0T.computeConv2DInfo(o.shape,p,i,1,u,l,!1,h),f=new bo(d);return n.runWebGLProgram(f,[o,s],"float32")}};const Co={kernelName:a.jfg,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:o,filter:s}=t,{inputShape:i,strides:u,pad:c,dataFormat:l,dimRoundingMode:p}=r,h=a.C0T.convertConv2DDataFormat(l),d=a.C0T.computeConv2DInfo(i,s.shape,u,1,c,p,!1,h),f=new vo(d);return n.runWebGLProgram(f,[o,s],"float32")}};const ko={kernelName:a.A1h,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,filter:s}=t,{strides:i,pad:u,dilations:c}=r,l=a.C0T.computeConv3DInfo(o.shape,s.shape,i,c,u),p=new po(l);return n.runWebGLProgram(p,[o,s],"float32")}};const Eo={kernelName:a.iGz,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,dy:s}=t,{strides:i,pad:u,filterShape:c}=r,l=a.C0T.computeConv3DInfo(o.shape,c,i,1,u),p=new wo(l);return n.runWebGLProgram(p,[o,s],"float32")}};const $o={kernelName:a.gC7,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:o,filter:s}=t,{pad:i,strides:u,inputShape:c}=r,l=a.C0T.computeConv3DInfo(c,s.shape,u,1,i),p=new To(l);return n.runWebGLProgram(p,[o,s],"float32")}},No=wr({opSnippet:vr+"\n  return cos(x);\n"}),Io={kernelName:a.Mn0,backendName:"webgl",kernelFunc:No},Ao=wr({opSnippet:"\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n"}),Ro={kernelName:a.MnK,backendName:"webgl",kernelFunc:Ao};class _o{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];const[o,s,i,u]=e,[c]=t,[l,p]=n;this.outputShape=[c,l,p,u];const h="bilinear"===r?1:0,[d,f]=[s-1+".0",i-1+".0"],[m,g,y]=l>1?[""+(s-1)/(l-1),"(y2-y1) * height_ratio",`y1*${d} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${d}`],[x,b,v]=p>1?[""+(i-1)/(p-1),"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`\n      const float height_ratio = float(${m});\n      const float width_ratio = float(${x});\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= ${o}) {\n          return;\n        }\n\n        float height_scale = ${g};\n        float width_scale = ${b};\n\n        float in_y = ${y};\n        if( in_y < 0.0 || in_y > ${d} ) {\n          setOutput(float(${a}));\n          return;\n        }\n        float in_x = ${v};\n        if( in_x < 0.0 || in_x > ${f} ) {\n          setOutput(float(${a}));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if(${h} == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    `}}const Oo={kernelName:a.MRQ,backendName:"webgl",kernelFunc:e=>{const{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:o,boxInd:s}=t,{cropSize:i,method:u,extrapolationValue:c}
vendor: 10,711 bytes, line 2
2=r,l=new _o(a.shape,o.shape,i,u,c);return n.runWebGLProgram(l,[a,o,s],"float32")}};var Fo;!function(e){e.Prod="*",e.Sum="+"}(Fo||(Fo={}));class Do{constructor(e,t,n,r){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];const a=this.outputShape.length,o=this.op===Fo.Prod?"1.0":"0.0",s=n?o:`getX(${Lo(a,"coords",this.op)})`,i=this.outputShape[this.outputShape.length-1];let u="",c="";n?(u=r?"end != "+(i-1):"end != 0",c=r?"end + 1":"end - 1"):(u=r?`end + pow2 < ${i}`:"end >= pow2",c=r?"end + pow2":"end - pow2"),this.userCode=`\n      void main() {\n        ${ae(a)} coords = getOutputCoords();\n        int end = ${Mo(a,"coords",this.op)};\n        float val = ${s};\n        int pow2 = int(pow(2.0, index));\n        if (${u}) {\n          int idx = ${c};\n          ${Mo(a,"coords",this.op)} = idx;\n          val ${this.op}= getX(${Lo(a,"coords",this.op)});\n        }\n        setOutput(val);\n      }\n    `}}function Lo(e,t,n){if(1===e)return`${t}`;if(2===e)return`${t}.x, ${t}.y`;if(3===e)return`${t}.x, ${t}.y, ${t}.z`;if(4===e)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function Mo(e,t,n){if(1===e)return`${t}`;if(2===e)return`${t}.y`;if(3===e)return`${t}.z`;if(4===e)return`${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function Po(e,t,n,r,o,s){const i=t.shape.length,u=a.C0T.getAxesPermutation([r],i);let c=t;null!=u&&(c=zr({inputs:{x:t},backend:n,attrs:{perm:u}}));const l=a.C0T.getInnerMostAxes(1,i)[0];if(l!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${r}`);const p=c.shape[l];let h=lr({inputs:{x:c},backend:n});for(let t=0;t<=Math.ceil(Math.log2(p))-1;t++){const r=new Do(e,c.shape,!1,s),a=[[t]],o=h;h=n.runWebGLProgram(r,[h],h.dtype,a),n.disposeIntermediateTensorInfo(o)}if(o){const t=new Do(e,c.shape,o,s),r=h;h=n.runWebGLProgram(t,[h],h.dtype),n.disposeIntermediateTensorInfo(r)}if(null!=u){const e=zr({inputs:{x:h},backend:n,attrs:{perm:a.C0T.getUndoAxesPermutation(u)}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(c),e}return h}const Bo={kernelName:a.jj_,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:o,exclusive:s,reverse:i}=r;return Po(Fo.Prod,a,n,o,s,i)}};const Vo={kernelName:a.nY8,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:o,exclusive:s,reverse:i}=r;return Po(Fo.Sum,a,n,o,s,i)}};const zo={kernelName:a.wNW,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a,weights:o}=t,{size:s,binaryOutput:i}=r;if(1===a.shape.length){const e=n.readSync(a.dataId),t=n.readSync(o.dataId),r=Yt(e,t,o.dtype,o.shape,s);return n.makeTensorInfo([s],o.dtype,r)}if(2===a.shape.length){const e=n.bufferSync(a),t=n.bufferSync(o),r=Zt(e,t,s,i);return n.makeTensorInfo(r.shape,o.dtype,r.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}};class Uo{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = ${this.getHeightCoordString()};\n      int w = ${this.getWidthCoordString()};\n      int d = ${this.getDepthCoordString()};\n\n      int in_h = h / ${t};\n      int offset_h = imod(h, ${t});\n      int in_w = w / ${t};\n      int offset_w = imod(w, ${t});\n      int offset_d = (offset_h * ${t} + offset_w) *\n        ${this.getOutputDepthSize()};\n      int in_d = d + offset_d;\n\n      float result = ${this.getInputSamplingString()};\n      setOutput(result);\n    }\n  `}getHeightCoordString(){return"NHWC"===this.dataFormat?"coords[1]":"coords[2]"}getWidthCoordString(){return"NHWC"===this.dataFormat?"coords[2]":"coords[3]"}getDepthCoordString(){return"NHWC"===this.dataFormat?"coords[3]":"coords[1]"}getOutputDepthSize(){return"NHWC"===this.dataFormat?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return"NHWC"===this.dataFormat?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}}const Wo={kernelName:a.TMz,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:o,dataFormat:s}=r,i=a.shape[0],u=("NHWC"===s?a.shape[1]:a.shape[2])*o,c=("NHWC"===s?a.shape[2]:a.shape[3])*o,l=("NHWC"===s?a.shape[3]:a.shape[1])/(o*o),p=new Uo("NHWC"===s?[i,u,c,l]:[i,l,u,c],o,s);return n.runWebGLProgram(p,[a],a.dtype)}};class Go{constructor(e,t=!1,n=null,r=!1,a=!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=pe(this.outputShape.length);const o=e.filterHeight,s=e.filterWidth,i=e.outChannels/e.inChannels;let u="",c="";n&&(u=r?`float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          ${n}\n        }`:a?`float activation(float a) {\n          float b = getLeakyreluAlphaAtOutCoords();\n          ${n}\n        }`:`\n          float activation(float x) {\n            ${n}\n          }\n        `,c="result = activation(result);");const l=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`\n      ${u}\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / ${i};\n        int q = d2 - d1 * ${i};\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < ${o}; wR++) {\n          int xR = xRCorner + wR * dilations[0];\n\n          if (xR < 0 || xR >= inDims[0]) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${s}; wC++) {\n            int xC = xCCorner + wC * dilations[1];\n\n            if (xC < 0 || xC >= inDims[1]) {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        ${l}\n        ${c}\n        setOutput(result);\n      }\n    `}}class jo{constructor(e,t=!1,n=null,r=!1,o=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=pe(this.outputShape.length);const s=e.outChannels/e.inChannels,i=e.padInfo.left,u=e.strideWidth,c=e.dilationWidth,l=e.filterHeight,p=e.filterWidth,h=p;let d="\n      int xR; int xC; int xCOffset;\n      vec4 wTexel; vec4 previous; vec4 final;";for(let e=0;e<p;e++)d+=`\n          vec4 xTexelC${2*e};\n          int xTexelC${2*e}Ready;\n          vec4 xTexelC${2*e+1};\n          int xTexelC${2*e+1}Ready;\n          vec4 xC${e};`;d+=`\n    for (int r = 0; r < ${l}; r++) {\n      `;for(let e=0;e<p;e++)d+=`\n          xTexelC${2*e} = vec4(0.0);\n          xTexelC${2*e}Ready = 0;\n          xTexelC${2*e+1} = vec4(0.0);\n          xTexelC${2*e+1}Ready = 0;\n          xC${e} = vec4(0.0);`;d+="\n        xR = xRCorner + r * dilations[0];\n        if (xR >=0 && xR < inDims[0]) {\n      ";for(let e=0;e<(h+1)/2;e++){const t=2*e;if(d+=`\n          xC = xCCorner + ${t*c};\n          `,1===u){if(t<p&&(i%2==1?(d+=`\n                xCOffset = xC + 1;\n                if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${t}Ready == 0) {\n                  xTexelC${t} = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${t}.zw = vec2(0.0);\n                  }\n                  xTexelC${t}Ready = 1;\n                }\n              `,d+=1===c&&t>0?`\n                xC${t} = vec4(xTexelC${t-2}.zw, xTexelC${t}.xy);\n                `:`\n                  xCOffset = xC + 1 - 2;\n\n                  if (xCOffset >= 0 && xCOffset < inDims[1]) {\n                    previous = getX(batch, xR, xCOffset, d1);\n\n                    // Need to manually clear unused channels in case\n                    // we're reading from recycled texture.\n                    if (xCOffset + 1 >= inDims[1]) {\n                      previous.zw = vec2(0.0);\n                    }\n\n                    xC${t} = vec4(previous.zw, xTexelC${t}.xy);\n                  } else {\n                    xC${t} = vec4(0.0, 0.0, xTexelC${t}.xy);\n                  }\n                  `):d+=`\n                if (xC >= 0 && xC < inDims[1] && xTexelC${t}Ready == 0) {\n                  xTexelC${t} = getX(batch, xR, xC, d1);\n                  if (xC + 1 >= inDims[1]) {\n                    xTexelC${t}.zw = vec2(0.0);\n                  }\n                  xTexelC${t}Ready = 1;\n                }\n\n                xC${t} = xTexelC${t};\n                `,t+1<p)){const e=i%2==0?a.ZSL.nearestLargerEven(c):c;c%2==0&&i%2==1||c%2!=0&&i%2!=1?(d+=`\n                  xCOffset = xC + imod(pads[1], 2) + ${e};\n\n                  if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${t+1}Ready == 0) {\n                    xTexelC${t+1} = getX(batch, xR, xCOffset, d1);\n\n                    // Need to manually clear unused channels in case\n                    // we're reading from recycled texture.\n                    if (xCOffset + 1 >= inDims[1]) {\n                      xTexelC${t+1}.zw = vec2(0.0);\n                    }\n                    xTexelC${t+1}Ready = 1;\n                  }\n                  `,d+=c>1?`\n                    xCOffset -= 2;\n                    if (xCOffset >= 0 && xCOffset < inDims[1]) {\n                     previous = getX(batch, xR, xCOffset, d1);\n                     xC${t+1} = vec4(previous.zw, xTexelC${t+1}.xy);\n                    } else {\n                     xC${t+1} = vec4(0.0, 0.0, xTexelC${t+1}.xy);\n                    }\n                    `:`\n                    xC${t+1} = vec4(xTexelC${t}.zw, xTexelC${t+1}.xy);

2\n                    `):d+=1===e?`\n                    xC${t+1} = xTexelC${t};\n                    `:`\n                    xCOffset = xC + ${e};\n\n                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${t+1}Ready == 0) {\n                      xTexelC${t+1} = getX(batch, xR, xCOffset, d1);\n                      if (xCOffset + 1 >= inDims[1]) {\n                        xTexelC${t+1}.zw = vec2(0.0);\n                      }\n                      xTexelC${t+1}Ready = 1;\n                    }\n\n                    xC${t+1} = xTexelC${t+1};\n                    `}}else t<p&&(i%2==1?(d+=`\n                xCOffset = xC + 1 - strides[1];\n                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${t}Ready == 0) {\n                  xTexelC${t} = getX(batch, xR, xCOffset, d1);\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${t}.zw = vec2(0.0);\n                  }\n                  xTexelC${t}Ready = 1;\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${t+1}Ready == 0) {\n                  xTexelC${t+1} = getX(batch, xR, xC + 1, d1);\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xC + 2 >= inDims[1]) {\n                    xTexelC${t+1}.zw = vec2(0.0);\n                  }\n                  xTexelC${t+1}Ready = 1;\n                }\n\n                xC${t} = vec4(xTexelC${t}.zw, xTexelC${t+1}.zw);\n              `,t+1<p&&(d+=`\n                  final = vec4(0.0);\n                  xCOffset = xC + 1 + strides[1];\n                  if(xCOffset >= 0 && xCOffset < inDims[1]) {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xC${t+1} = vec4(xTexelC${t+1}.xy, final.xy);\n                `)):(d+=`\n                if(xC >= 0 && xC < inDims[1] && xTexelC${t}Ready == 0) {\n                  xTexelC${t} = getX(batch, xR, xC, d1);\n                  if (xC + 1 >= inDims[1]) {\n                    xTexelC${t}.zw = vec2(0.0);\n                  }\n                  xTexelC${t}Ready = 1;\n                }\n\n                xCOffset = xC + strides[1];\n                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${t+1}Ready == 0) {\n                  xTexelC${t+1} = getX(batch, xR, xCOffset, d1);\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${t+1}.zw = vec2(0.);\n                  }\n                  xTexelC${t+1}Ready = 1;\n                }\n\n                xC${t} = vec4(\n                  xTexelC${t}.xy, xTexelC${t+1}.xy);\n              `,t+1<p&&(d+=`\n                  xC${t+1} = vec4(xTexelC${t}.zw, xTexelC${t+1}.zw);\n                `)));t<p&&(d+=`\n            wTexel = getW(r, ${t}, d1, q);\n            dotProd += xC${t} * vec4(wTexel.xz, wTexel.xz);\n          `,t+1<p&&(d+=`\n              wTexel = getW(r, ${t+1}, d1, q);\n              dotProd += xC${t+1} * vec4(wTexel.xz, wTexel.xz);\n            `))}d+="\n    }\n  ",d+="\n      }\n    ";let f="",m="";n&&(f=r?`vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          ${n}\n        }`:o?`vec4 activation(vec4 a) {\n          vec4 b = getLeakyreluAlphaAtOutCoords();\n          ${n}\n        }`:`vec4 activation(vec4 x) {\n          ${n}\n        }`,m="result = activation(result);");const g=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),o&&this.variableNames.push("leakyreluAlpha"),this.userCode=`\n      ${f}\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / ${s};\n        int q = d2 - d1 * ${s};\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.\n        vec4 dotProd = vec4(0.000000000000001);\n\n        ${d}\n\n        vec4 result = dotProd - vec4(0.000000000000001);\n        ${g}\n        ${m}\n        setOutput(result);\n      }\n    `}}const Ko={kernelName:a.tGH,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,filter:s}=t,{strides:i,pad:u,dilations:c,dimRoundingMode:l}=r;let p=c;null==p&&(p=[1,1]),a.ZSL.assert(a.C0T.eitherStridesOrDilationsAreOne(i,p),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);const h=a.C0T.computeConv2DInfo(o.shape,s.shape,i,p,u,l,!0);let d;d=(0,a._K2)().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels===1?new jo(h):new Go(h);const f=[[h.padInfo.top,h.padInfo.left],[h.strideHeight,h.strideWidth],[h.dilationHeight,h.dilationWidth],[h.inHeight,h.inWidth
vendor: 4,840 bytes, line 2
2]];return n.runWebGLProgram(d,[o,s],"float32",f)}};class Ho{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;const t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * ${o} + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < ${e.batchSize}; b++) {\n          for (int yR = 0; yR < ${e.outHeight}; yR++) {\n            int xR = wR + yR * ${t} - ${r};\n\n            if (xR < 0 || xR >= ${e.inHeight}) {\n              continue;\n            }\n\n            for (int yC = 0; yC < ${e.outWidth}; yC++) {\n              int xC = wC + yC * ${n} - ${a};\n\n              if (xC < 0 || xC >= ${e.inWidth}) {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}class Yo{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;const t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,o=t-1-e.padInfo.top,s=n-1-e.padInfo.left,i=e.outChannels/e.inChannels;this.userCode=`\n      const ivec2 pads = ivec2(${o}, ${s});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < ${t}; wR++) {\n          float dyR = float(dyRCorner + wR) / ${r}.0;\n\n          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = ${t} - 1 - wR;\n\n          for (int wC = 0; wC < ${n}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${a}.0;\n\n            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = ${n} - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < ${i}; dm++) {\n              int d2 = d1 * ${i} + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}const Zo={kernelName:a.X$8,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,dy:s}=t,{strides:i,dilations:u,pad:c,dimRoundingMode:l,filterShape:p}=r,h=a.C0T.computeConv2DInfo(o.shape,p,i,u,c,l,!0),d=new Ho(h);return n.runWebGLProgram(d,[o,s],"float32")}};const Xo={kernelName:a.nVu,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:o,filter:s}=t,{strides:i,dilations:u,pad:c,dimRoundingMode:l,inputShape:p}=r,h=a.C0T.computeConv2DInfo(p,s.shape,i,u,c,l,!0),d=new Yo(h);return n.runWebGLProgram(d,[o,s],"float32")}};class qo{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode="\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    "}}const Qo={kernelName:a.ORI,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{x:r}=t,o=[...r.shape,...r.shape],s=a.ZSL.sizeFromShape(r.shape),i=Rr({inputs:{x:r},backend:n,attrs:{shape:[s]}}),u=new qo(s),c=n.runWebGLProgram(u,[i],i.dtype),l=Rr({inputs:{x:c},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(c),l}};class Jo{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;const{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:o,filterHeight:s,filterWidth:i,dilationHeight:u,dilationWidth:c}=e,{top:l,left:p}=r;this.userCode=`\n      const ivec2 strides = ivec2(${a}, ${o});\n      const ivec2 pads = ivec2(${l}, ${p});\n      const float neg_infinity = -3.4e38;\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.w;\n        ivec2 outTopLeftCorner =\n            coords.yz * strides - pads;\n        int hBeg = outTopLeftCorner.x;\n        int wBeg = outTopLeftCorner.y;\n\n        float curVal = neg_infinity;\n        for (int h = 0; h < ${s}; h++) {\n          int hIn = hBeg + h * ${u};\n\n          if (hIn >= 0 && hIn < ${t}

2) {\n            for (int w = 0; w < ${i}; w++) {\n              int wIn = wBeg + w * ${c};\n\n              if (wIn >= 0 && wIn < ${n}) {\n                float xVal = getX(batch, hIn, wIn, d1);\n                float wVal = getW(h, w, d1);\n\n                float val = xVal + wVal;\n                if (val > curVal) {\n                  curVal = val;\n                }\n              }\n            }\n          }\n        }\n\n        float result = curVal;\n        setOutput(result);\n      }\n    `}}const es={kernelName:a.jxD,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,filter:s}=t,{strides:i,pad:u,dilations:c}=r,l=a.C0T.computeDilation2DInfo(o.shape,s.shape,i,u,"NHWC",c);let p;const h=new Jo(l);p=n.runWebGLProgram(h,[o,s],"float32");const d=Rr({inputs:{x:p},backend:n,attrs:{shape:l.outShape}});return n.disposeIntermediateTensorInfo(p),d}};const ts={kernelName:a.Qgm,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{equation:o}=r,s=t,{allDims:i,summedDims:u,idDims:c}=a.C0T.decodeEinsumEquation(o,s.length);a.C0T.checkEinsumDimSizes(i.length,c,s);const{path:l,steps:p}=a.C0T.getEinsumComputePath(u,c),h=p.length;let d=null,f=i.length;const m=[];for(let e=0;e<h;++e){for(const t of p[e]){const{permutationIndices:e,expandDims:r}=a.C0T.getEinsumPermutation(f,c[t]);let o;a.C0T.isIdentityPermutation(e)?o=s[t]:(o=zr({inputs:{x:s[t]},backend:n,attrs:{perm:e}}),m.push(o));const i=o.shape.slice();for(let e=0;e<r.length;++e)i.splice(r[e],0,1);a.ZSL.arraysEqual(o.shape,i)||(o=Rr({inputs:{x:o},backend:n,attrs:{shape:i}}),m.push(o)),null===d?d=o:(d=Ir({inputs:{a:o,b:d},backend:n}),m.push(d))}e<h-1&&(l[e]>=0&&(d=Br({inputs:{x:d},backend:n,attrs:{axis:l[e]-(i.length-f),keepDims:!1}}),m.push(d)),f--)}for(const e of m)e!==d&&n.disposeIntermediateTensorInfo(e);return d}},ns=wr({opSnippet:"return (x >= 0.0) ? x : (exp(x) - 1.0);",packedOpSnippet:"\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n"}),rs={kernelName:a.Pah,backendName:"webgl",kernelFunc:ns},as={kernelName:a.rsH,backendName:"webgl",kernelFunc:e=>{const{inputs:t,backend:n}=e,{dy:r,y:o}=t,s=(0,a._K2)().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new cr("\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));

2\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n",r.shape,o.shape):new ir("return (b >= 1.0) ? a : a * (b + 1.0);",r.shape,o.shape);return n.runWebGLProgram(s,[r,o],r.dtype)}},os=Tr({opSnippet:"return float(a == b);",packedOpSnippet:"\n  return vec4(equal(a, b));\n",dtype:"bool",cpuKernelImpl:Jt}),ss={kernelName:a.BRl,backendName:"webgl",kernelFunc:os},is=wr({opSnippet:`\n  // Error function is calculated approximately with elementary function.\n  // See "Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables", Abramowitz and Stegun.\n  float p = ${a.C0T.ERF_P};\n  float a1 = ${a.C0T.ERF_A1};\n  float a2 = ${a.C0T.ERF_A2};\n  float a3 = ${a.C0T.ERF_A3};\n  float a4 = ${a.C0T.ERF_A4};\n  float a5 = ${a.C0T.ERF_A5};\n\n  float sign = sign(x);\n  x = abs(x);\n  float t = 1.0 / (1.0 + p * x);\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\n`}),us={kernelName:a._s9,backendName:"webgl",kernelFunc:is},cs=wr({opSnippet:vr+"\n  return exp(x);\n",packedOpSnippet:"\n  vec4 result = exp(x);\n  bvec4 isNaN = isnan(x);\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",cpuKernelImpl:en,dtype:"float32"}),ls={kernelName:a.ox3,backendName:"webgl",kernelFunc:cs};function ps(e){const{inputs:t,attrs:n,backend:r}=e,{dim:o}=n,{input:s}=t,i=s.shape.length,u=s.shape.slice();let c=o;return o<0&&(a.ZSL.assert(-(i+1)<=o,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),c=i+o+1),u.splice(c,0,1),Rr({inputs:{x:s},backend:r,attrs:{shape:u}})}const hs={kernelName:a.ybN,backendName:"webgl",kernelFunc:ps},ds="return exp(x) - 1.0;",fs=wr({opSnippet:ds,packedOpSnippet:ds,cpuKernelImpl:tn}),ms={kernelName:a.ybj,backendName:"webgl",kernelFunc:fs};class gs{constructor(e,t,n){this.variableNames=["real","imag"];const r=t[1];this.outputShape=t;const a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,o=n?`${r}.0`:"1.0";let s;if("real"===e)s="return real * expR - imag * expI;";else{if("imag"!==e)throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);s="return real * expI + imag * expR;"}this.userCode=`\n      const float exponentMultiplier = ${a};\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        ${s}\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float(${r});\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < ${r}; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / ${o};\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    `}}function ys(e,t,n){const r=n.texData.get(e.dataId),o=a.ZSL.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=Rr({inputs:{x:e},backend:n,attrs:{shape:[o/s,s]}}),u=i.shape,c=new gs("real",u,t),l=new gs("imag",u,t),p=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:u},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:u}],h=n.runWebGLProgram(c,p,"float32"),d=n.runWebGLProgram(l,p,"float32"),f=hr({inputs:{real:h,imag:d},backend:n});n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d);const m=Rr({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(f),m}const xs={kernelName:a.rGP,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{input:r}=t;return ys(r,!1,n)}};class bs{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode="\n      void main() {\n        // In

2put can be obtained from uniform value.\n        setOutput(value);\n      }\n    "}}function vs(e){const{backend:t,attrs:n}=e,{shape:r,value:o}=n;let{dtype:s}=n;if(s=s||a.ZSL.inferDtype(o),"string"===s){const e=a.ZSL.getArrayFromDType(s,a.ZSL.sizeFromShape(r));return e.fill(o),t.makeTensorInfo(r,s,e)}{const e=new bs(r,o),n=[[o]];return t.runWebGLProgram(e,[],s,n)}}const ws={kernelName:a.SQl,backendName:"webgl",kernelFunc:vs};class Ts{constructor(e){this.variableNames=["Image"],this.outputShape=[];const t=e[2];this.outputShape=e,this.userCode=`\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int x = coords[2];\n\n          int coordX = ${t} - x - 1;\n          float outputValue;\n          if(coordX >= 0 && coordX < ${t}) {\n            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);\n          } else {\n            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);\n          }\n          setOutput(outputValue);\n        }\n    `}}const Ss={kernelName:a.BxF,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{const{image:n}=e,r=t,a=new Ts(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},Cs="return floor(x);",ks=wr({opSnippet:Cs,packedOpSnippet:Cs,cpuKernelImpl:nn}),Es={kernelName:a.ZgB,backendName:"webgl",kernelFunc:ks},$s=Tr({opSnippet:"\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n",packedOpSnippet:"\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n",dtype:"int32"}),Ns={kernelName:a.ElG,backendName:"webgl",kernelFunc:$s};class Is{constructor(e){this.variableNames=["A"];const t=z(),[n,r]=e;this.outputShape=e,this.userCode=`\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${r}.0, ${n}.0);\n\n        vec4 values = ${t.texture2D}(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    `}}class As{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;const t=z(),[n,r]=e;this.outputShape=e,this.userCode=`\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n\n        vec4 result = vec4(0.);\n\n        for(int row=0; row<=1; row++) {\n          for(int col=0; col<=1; col++) {\n            texC = coords[1] + row;\n            depth = coords[2] + col;\n\n            vec2 uv = (vec2(texC, texR) + halfCR) /\n                       vec2(${r}.0, ${n}.0);\n            vec4 values = ${t.texture2D}(A, uv);\n            float value;\n            if (depth == 0) {\n              value = values.r;\n            } else if (depth == 1) {\n              value = values.g;\n            } else if (depth == 2) {\n              value = values.b;\n            } else if (depth == 3) {\n              value = values.a;\n            }\n\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\n          }\n        }\n\n        ${t.output} = result;\n      }\n    `}}const Rs={kernelName:a.awo,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e;let{pixels:o}=t;const{numChannels:s}=r,i="undefined"!=typeof HTMLVideoElement&&o instanceof HTMLVideoElement,u="undefined"!=typeof HTMLImageElement&&o instanceof HTMLImageElement,[l,p]=i?[o.videoWidth,o.videoHeight]:[o.width,o.height],h=[p,l],d=[p,l,

2s];if(u||i){const e=(0,a._K2)().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");null!=_s&&e===Os||(Os=e,_s=document.createElement("canvas").getContext("2d",{willReadFrequently:Os})),_s.canvas.width=l,_s.canvas.height=p,_s.drawImage(o,0,0,l,p),o=_s.canvas}const f=n.makeTensorInfo(h,"int32");n.texData.get(f.dataId).usage=c.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(f.dataId),o);const m=(0,a._K2)().getBool("WEBGL_PACK")?new As(d):new Is(d),g=n.runWebGLProgram(m,[f],"int32");return n.disposeData(f.dataId),g}};let _s,Os=(0,a._K2)().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");const Fs={kernelName:a.aAr,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,filter:s,bias:i,preluActivationWeights:u}=t,{strides:c,pad:l,dataFormat:p,dilations:h,dimRoundingMode:d,activation:f,leakyreluAlpha:m}=r,g=a.C0T.convertConv2DDataFormat(p),y=a.C0T.computeConv2DInfo(o.shape,s.shape,c,h,l,d,!1,g);let x;const b=[],v=null!=i,w=null!=u,T="leakyrelu"===f,S=()=>{const e=[o,s],t=(e,t)=>{if("NCHW"===t&&1===e.shape.length&&1!==e.shape[0]){const t=Rr({inputs:{x:e},backend:n,attrs:{shape:[e.shape[0],1,1]}});return b.push(t),t}return e};if(v&&e.push(t(i,p)),w&&e.push(t(u,p)),T){const t=n.makeTensorInfo([],"float32",a.ZSL.createScalarValue(m,"float32"));e.push(t),b.push(t)}return e};if(1!==y.filterHeight||1!==y.filterWidth||1!==y.dilationHeight||1!==y.dilationWidth||1!==y.strideHeight||1!==y.strideWidth||"SAME"!==y.padInfo.type&&"VALID"!==y.padInfo.type)if(y.strideWidth<=2&&"channelsLast"===g&&(0,a._K2)().getBool("WEBGL_EXP_CONV")){const e=f?Sr(f,!0):null,t=new ho(y,v,e,w,T),r=[[y.padInfo.top,y.padInfo.left],[y.strideHeight,y.strideWidth],[y.dilationHeight,y.dilationWidth],[y.inHeight,y.inWidth]],a=S();x=n.runWebGLProgram(t,a,"float32",r)}else if((0,a._K2)().getBool("WEBGL_CONV_IM2COL"))x=yo({x:o,filter:s,convInfo:y,backend:n,bias:i,activation:f,preluActivationWeights:u,leakyreluAlpha:m});else{const e=f?Sr(f,!1):null,t=new lo(y,v,e,w,T),r=S();x=n.runWebGLProgram(t,r,"float32")}else x=go({x:o,filter:s,convInfo:y,backend:n,bias:i,activation:f,preluActivationWeights:u,leakyreluAlpha:m});const C=Rr({inputs:{x:x},backend:n,attrs:{shape:y.outShape}});return b.push(x),b.forEach(e=>n.disposeIntermediateTensorInfo(e)),C}};const Ds={kernelName:a.T7M,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,filter:s,bias:i,preluActivationWeights:u}=t,{strides:c,pad:l,dilations:p,dimRoundingMode:h,activation:d,leakyreluAlpha:f}=r,m=[];let g=p;null==g&&(g=[1,1]),a.ZSL.assert(a.C0T.eitherStridesOrDilationsAreOne(c,g),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${c} and dilations '${g}'`);const y=a.C0T.computeConv2DInfo(o.shape,s.shape,c,g,l,h,!0),x=(0,a._K2)().getBool("WEBGL_PACK_DEPTHWISECONV")&&y.strideWidth<=2&&y.outChannels/y.inChannels===1,b=d?Sr(d,x):null,v=[o,s],w=null!=i,T=null!=u,S="leakyrelu"===d;if(w&&v.push(i),T&&v.push(u),S){const e=n.makeTensorInfo([],"float32",a.ZSL.createScalarValue(f,"float32"));v.push(e),m.push(e)}let C;C=x?new jo(y,w,b,T,S):new Go(y,w,b,T,S);const k=[[y.padInfo.top,y.padInfo.left],[y.strideHeight,y.strideWidth],[y.dilationHeight,y.dilationWidth],[y.inHeight,y.inWidth]],E=n.runWebGLProgram(C,v,"float32",k);return m.forEach(e=>n.disposeIntermediateTensorInfo(e)),E}};class Ls{constructor(e,t,n,r){this.sliceDim=e,this.strides=t,this.paramsShape=r,this.variableNames=["x","indices"],this.outputShape=n;const a=ae(n.length);let o="\n    int index;";for(let e=0;e<this.sliceDim;e++)o+=`\n          index = round(getIndices(coords[0], ${e}));\n          out_of_bounds = out_of_bounds || index < 0;\n          out_of_bounds = out_of_bounds || index >= ${this.paramsShape[e]};\n          flattenIndex += index * ${this.strides[e]};`;this.userCode=`\n         void main() {\n          ${a} coords = getOutputCoords();\n          int flattenIndex = 0;\n          bool out_of_bounds = false;\n\n          ${o}\n\n          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));\n        }\n      `}}const Ms={kernelName:a.O4G,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{params:r,indices:o}=t,s=o.shape,i=s[s.length-1],u=a.ZSL.sizeFromShape(r.shape),[c,l,p,h]=a.C0T.prepareAndValidate(r,o),d=Rr({inputs:{x:o},backend:n,attrs:{shape:[l,i]}}),f=Rr({inputs:{x:r},backend:n,attrs:{shape:[a.ZSL.sizeFromShape(r.shape)/p,p]}});if(n.shouldExecuteOnCPU([r,o])||"string"===r.dtype){const e=n.readSync(o.dataId),t=n.bufferSync(r),a=rn(e,t,r.dtype,l,i,p,h,r.shape,u);return n.makeTensorInfo(c,r.dtype,a.values)}const m=new Ls(i,h,[l,p],r.shape),g=n.runWebGLProgram(m,[f,d],f.dtype),y=Rr({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),y}};class Ps{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;const n=ae(this.rank),r=function(e){const t=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let r=0;r<e.length;r++)2===r?n.push("index"):n.push(`${t[r]}`);return n.join()}(e);this.userCode=`\n      void main() {\n        ${n} resRC = getOutputCoords();\n        int index = int(getIndices(resRC.x, resRC.z));\n        float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;\n        setOutput(inBounds * getA(${r}));\n      }\n    `}}function Bs(e){const{inputs:t,backend:n,attrs:r}=e,{x:o,indices:s}=t,{axis:i,batchDims:u}=r,c=a.ZSL.parseAxisParam(i,o.shape)[0];if((0,a._K2)().get("DEBUG")){const e=n.readSync(s.dataId),t=o.shape[c];for(let n=0;n<e.length;++n){const r=e[n];a.ZSL.assert(r<=t-1&&r>=0,()=>`GatherV2: the index value ${r} is not in [0, ${t-1}]`)}}const l=a.C0T.segment_util.collectGatherOpShapeInfo(o,s,c,u),p=a.ZSL.sizeFromShape(s.shape),h=[],d=Rr({inputs:{x:o},backend:n,attrs:{shape:[l.batchSize,l.outerSize,l.dimSize,l.sliceSize]}}),f=Rr({inputs:{x:s},backend:n,attrs:{shape:[l.batchSize,p/l.batchSize]}});h.push(d),h.push(f);const m=[l.batchSize,l.outerSize,p/l.batchSize,l.sliceSize];if(n.shouldExecuteOnCPU([o,s])||"string"===o.dtype){const e=n.bufferSync(f),t=n.bufferSync(d),r=an(t,e,m);

2return h.forEach(e=>n.disposeIntermediateTensorInfo(e)),n.makeTensorInfo(l.outputShape,r.dtype,r.values)}const g=new Ps(d.shape,m),y=n.runWebGLProgram(g,[d,f],d.dtype);h.push(y);const x=Rr({inputs:{x:y},backend:n,attrs:{shape:l.outputShape}});return h.forEach(e=>n.disposeIntermediateTensorInfo(e)),x}const Vs={kernelName:a.mxL,backendName:"webgl",kernelFunc:Bs},zs=Tr({opSnippet:"return float(a > b);",packedOpSnippet:"\n  return vec4(greaterThan(a, b));\n",cpuKernelImpl:on,dtype:"bool"}),Us={kernelName:a.XhZ,backendName:"webgl",kernelFunc:zs},Ws=Tr({opSnippet:"return float(a >= b);",packedOpSnippet:"\n  return vec4(greaterThanEqual(a, b));\n",dtype:"bool",cpuKernelImpl:sn}),Gs={kernelName:a.lLS,backendName:"webgl",kernelFunc:Ws};const js={kernelName:a.OAQ,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{input:r}=t;return ys(r,!0,n)}},Ks=wr({opSnippet:"return float(!isnan(x) && !isinf(x));",dtype:"bool"}),Hs={kernelName:a.gIW,backendName:"webgl",kernelFunc:Ks},Ys=wr({opSnippet:"return float(isinf(x));",dtype:"bool"}),Zs={kernelName:a.E3$,backendName:"webgl",kernelFunc:Ys},Xs=wr({opSnippet:"return float(isnan(x));",dtype:"bool"}),qs={kernelName:a.iPs,backendName:"webgl",kernelFunc:Xs},Qs=Tr({opSnippet:"return float(a < b);",packedOpSnippet:"\n  return vec4(lessThan(a, b));\n",cpuKernelImpl:un,dtype:"bool"}),Js={kernelName:a.mIA,backendName:"webgl",kernelFunc:Qs},ei=Tr({opSnippet:"return float(a <= b);",packedOpSnippet:"\n  return vec4(lessThanEqual(a, b));\n",cpuKernelImpl:cn,dtype:"bool"}),ti={kernelName:a.CwD,backendName:"webgl",kernelFunc:ei};const ni={kernelName:a.mnI,backendName:"webgl",kernelFunc:function(e){const{backend:t,attrs:n}=e,{start:r,stop:a,num:o}=n,s=ln(r,a,o);return t.makeTensorInfo([s.length],"float32",s)}},ri=wr({opSnippet:vr+"\n  return x < 0.0 ? 0./0. : log(x);\n",packedOpSnippet:"\n  vec4 result = log(x);\n  bvec4 isNaN = isnan(x);\n  result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);\n  result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);\n  result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);\n  result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);\n  return result;\n",cpuKernelImpl:pn}),ai={kernelName:a.tG8,backendName:"webgl",kernelFunc:ri},oi=wr({opSnippet:vr+"\n  return log(1.0 + x);\n"}),si={kernelName:a.Cg$,backendName:"webgl",kernelFunc:oi},ii=Tr({opSnippet:"return float(a >= 1.0 && b >= 1.0);",packedOpSnippet:"\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n",dtype:"bool"}),ui={kernelName:a.RUm,backendName:"webgl",kernelFunc:ii},ci=wr({opSnippet:"return float(!(x >= 1.0));"}),li={kernelName:a.nZd,backendName:"webgl",kernelFunc:ci},pi=Tr({opSnippet:"return float(a >= 1.0 || b >= 1.0);",packedOpSnippet:"\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n",dtype:"bool"}),hi={kernelName:a.LXA,backendName:"webgl",kernelFunc:pi};class di{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];const o=t,s=e[3]-1;let i;this.outputShape=e;const u=`float(${n}) + float(${r}) * sum`;i=.5===a?`inversesqrt(${u})`:1===a?`1.0/(${u})`:`exp(log(${u}) * float(-${a}));`,this.userCode=`\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -${o}; j <= ${o}; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  ${s}) {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * ${i};\n        setOutput(val);\n      }\n    `}}class fi{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;const o=t,s=e[3]-1;let i;this.outputShape=e;const u=`float(${n}) + float(${r}) * sum`;i=.5===a?`inversesqrt(${u})`:1===a?`1.0/(${u})`:`exp(log(${u}) * float(-${a}));`,this.userCode=`\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < ${this.outputShape[3]};\n        bool hasNextRow = c < ${this.outputShape[2]};\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - ${o};\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }

2\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - ${o}; j <= ${o}; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${s}));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * ${i};\n        setOutput(result);\n      }\n    `}}const mi={kernelName:a.jM4,backendName:"webgl",kernelFunc:e=>{const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{depthRadius:s,bias:i,alpha:u,beta:c}=r,l=(0,a._K2)().getBool("WEBGL_PACK_NORMALIZATION")?new fi(o.shape,s,i,u,c):new di(o.shape,s,i,u,c);return n.runWebGLProgram(l,[o],o.dtype)}};class gi{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < ${this.depth}; ++d) {\n          int depthBegin = int(max(0.0, float(d - ${t})));\n          int depthEnd = int(min(float(${this.depth}),\n              float(d + ${t} + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = ${this.depth};\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float(${r}) * norm + float(${n});\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float(${r})\n                * float(${a})\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * ${a});\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    `}}const yi={kernelName:a.ToN,backendName:"webgl",kernelFunc:e=>{const{inputs:t,backend:n,attrs:r}=e,{x:a,y:o,dy:s}=t,{depthRadius:i,bias:u,alpha:c,beta:l}=r,p=new gi(a.shape,i,u,c,l);return n.runWebGLProgram(p,[a,o,s],a.dtype)}};function xi(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{reductionIndices:s,keepDims:i}=r,u=o.shape.length,c=a.ZSL.parseAxisParam(s,o.shape);let l=c;const p=a.C0T.getAxesPermutation(l,u),h=null!=p,d=n.shouldExecuteOnCPU([o]);let f=o;if(h){if(d){const e=n.texData.get(f.dataId).values,t=new Array(u);for(let e=0;e<t.length;e++)t[e]=o.shape[p[e]];const r=Pn(e,o.shape,o.dtype,p,t);f=n.makeTensorInfo(t,o.dtype);n.texData.get(f.dataId).values=r}else f=Pr(o,p,n);l=a.C0T.getInnerMostAxes(l.length,u)}a.C0T.assertAxesAreInnerMostDims("max",l,u);const[m,g]=a.C0T.computeOutAndReduceShapes(f.shape,l);let y,x=m;if(i&&(x=a.C0T.expandShapeToKeepDim(m,c)),d){const e=n.texData.get(f.dataId).values,t=hn(e,a.ZSL.sizeFromShape(g),x,o.dtype);y=n.makeTensorInfo(x,o.dtype);n.texData.get(y.dataId).values=t}else y=function(e,t,n,r){const o=a.ZSL.sizeFromShape(t),s=Rr({inputs:{x:e},attrs:{shape:[a.ZSL.sizeFromShape(e.shape)/o,o]},backend:r}),i=Dr(s,e.dtype,"max",r),u=Rr({inputs:{x:i},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(i),u}(f,g,x,n);return h&&n.disposeIntermediateTensorInfo(f),y}const bi={kernelName:a.VAI,backendName:"webgl",kernelFunc:xi},vi=Tr({opSnippet:sr+"\n  return max(a, b);\n",packedOpSnippet:"\n  vec4 result = vec4(max(a, b));\n  bvec4 isNaNA = isnan(a);\n  bvec4 isNaNB = isnan(b);\n  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);\n  "+ur+"\n  return result;\n",cpuKernelImpl:dn}),wi={kernelName:a.LDN,backendName:"webgl",kernelFunc:vi};const Ti={kernelName:a.t3d,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t;B(o,"maxPool");const{filterSize:s,strides:i,pad:u,dimRoundingMode:c}=r;a.ZSL.assert(a.C0T.eitherStridesOrDilationsAreOne(i,1),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '1'`);const l=a.C0T.computePool2DInfo(o.shape,s,i,1,u,c);if(1===l.filterWidth&&1===l.filterHeight&&a.ZSL.arraysEqual(l.inShape,l.outShape))return lr({inputs:{x:o},backend:n});const p=new Ta(l,"max",!1);
vendor: 5,326 bytes, line 2
2return n.runWebGLProgram(p,[o],o.dtype)}};const Si={kernelName:a.ySp,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{filterSize:s,strides:i,pad:u,dataFormat:c,dimRoundingMode:l}=r,p=a.C0T.computePool3DInfo(o.shape,s,i,[1,1,1],u,l,c),h=new Sa(p,"max",!1);return n.runWebGLProgram(h,[o],o.dtype)}};class Ci{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;const t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,o=e.effectiveFilterWidth,s=a-1-e.padInfo.top,i=o-1-e.padInfo.left,u=a*o-1;this.userCode=`\n      const ivec2 pads = ivec2(${s}, ${i});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${a};\n          wR += ${r}) {\n          float dyR = float(dyRCorner + wR) / ${t}.0;\n\n          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < ${o}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${n}.0;\n\n            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = ${u} - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * ${o} + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}class ki{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;const t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,o=e.dilationHeight,s=e.dilationWidth,i=e.effectiveFilterDepth,u=e.effectiveFilterHeight,c=e.effectiveFilterWidth,l=i-1-e.padInfo.front,p=u-1-e.padInfo.top,h=c-1-e.padInfo.left,d=i*u*c-1;this.userCode=`\n      const ivec3 pads = ivec3(${l}, ${p}, ${h});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < ${i};\n           wD += ${a}) {\n          float dyD = float(dyDCorner + wD) / ${t}.0;\n\n          if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < ${u};\n              wR += ${o}) {\n            float dyR = float(dyRCorner + wR) / ${n}.0;\n\n            if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < ${c};\n                wC += ${s}) {\n              float dyC = float(dyCCorner + wC) / ${r}.0;\n\n              if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = ${d} -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * ${u} * ${c} +\n                  wR * ${c} + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `}}const Ei={kernelName:a.cHb,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:o,input:s}=t,i=s,{filterSize:u,strides:c,pad:l,dimRoundingMode:p}=r,h=a.C0T.computePool3DInfo(i.shape,u,c,[1,1,1],l,p),d=new Sa(h,"max",!0),f=n.runWebGLProgram(d,[i],i.dtype),m=new ki(h),g=n.runWebGLProgram(m,[o,f],i.dtype);return n.disposeIntermediateTensorInfo(f),g}};const $i={kernelName:a.RXX,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:o,input:s,output:i}=t,u=s;B([s,i],"maxPoolGrad");const{filterSize:c,strides:l,pad:p,dimRoundingMode:h}=r,d=a.C0T.computePool2DInfo(u.shape,c,l,1,p,h),f=new Ta(d,"max",!0),m=n.runWebGLProgram(f,[u],u.dtype),g=new Ci(d),y=n.runWebGLProgram(g,[o,m],u.dtype);return n.disposeIntermediateTensorInfo(m),y}};const Ni={kernelName:a.TL8,backendName:"webgl",kernelFunc:({input

2s:e,attrs:t,backend:n})=>{const{x:r}=e,{filterSize:o,strides:s,pad:i,includeBatchInIndex:u}=t,c=n;a.ZSL.assert(4===r.shape.length,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);const l=[1,1];a.ZSL.assert(a.C0T.eitherStridesOrDilationsAreOne(s,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${l}'`);const p=a.C0T.computePool2DInfo(r.shape,o,s,l,i),[h,d]=function(e,t,n,r){let a=new Ta(n,"max",!1);const o=r.runWebGLProgram(a,[e],"float32");return a=new Ta(n,"max",!0,!0,t),[o,r.runWebGLProgram(a,[e],"float32")]}(r,u,p,c);return[h,d]}};const Ii={kernelName:a.g5A,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{const{x:r}=e,{keepDims:o,axis:s}=t,i=n,u=r.shape.length,c=a.ZSL.parseAxisParam(s,r.shape);let l=c;const p=a.C0T.getAxesPermutation(l,u),h=null!=p,d=i.shouldExecuteOnCPU([r]),f=[];let m=r;if(h){if(d){const e=i.texData.get(m.dataId).values,t=new Array(u);for(let e=0;e<t.length;e++)t[e]=r.shape[p[e]];const n=Pn(e,r.shape,r.dtype,p,t);m=i.makeTensorInfo(t,r.dtype);i.texData.get(m.dataId).values=n}else m=Pr(r,p,i);f.push(m),l=a.C0T.getInnerMostAxes(l.length,u)}a.C0T.assertAxesAreInnerMostDims("sum",l,u);const[g,y]=a.C0T.computeOutAndReduceShapes(m.shape,l);let x=g;o&&(x=a.C0T.expandShapeToKeepDim(g,c));const b=function(e,t,n,r){const o=a.ZSL.sizeFromShape(t),s=Rr({inputs:{x:e},attrs:{shape:[a.ZSL.sizeFromShape(e.shape)/o,o]},backend:r}),i=Dr(s,"float32","mean",r),u=Rr({inputs:{x:i},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(i),u}(m,y,x,i);for(const e of f)i.disposeIntermediateTensorInfo(e);return b}};const Ai={kernelName:a.lNG,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{axis:s,keepDims:i}=r,u=o.shape.length,c=a.ZSL.parseAxisParam(s,o.shape);let l=c;const p=a.C0T.getAxesPermutation(l,u);let h=o;null!=p&&(h=zr({inputs:{x:o},backend:n,attrs:{perm:p}}),l=a.C0T.getInnerMostAxes(l.length,o.shape.length)),a.C0T.assertAxesAreInnerMostDims("min",l,u);const[d,f]=a.C0T.computeOutAndReduceShapes(h.shape,l),m=Rr({inputs:{x:h},backend:n,attrs:{shape:[-1,a.ZSL.sizeFromShape(f)]}}),g=Dr(m,m.dtype,"min",n);let y;if(i){y=Rr({inputs:{x:g},backend:n,attrs:{shape:a.C0T.expandShapeToKeepDim(d,c)}})}else y=Rr({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),null!=p&&n.disposeIntermediateTensorInfo(h),y}},Ri=Tr({opSnippet:sr+"\n  return min(a, b);\n",packedOpSnippet:"\n  vec4 result = vec4(min(a, b));\n  bvec4 isNaNA = isnan(a);\n  bvec4 isNaNB = isnan(b);\n  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);\n  "+ur+"\n  return result;\n",cpuKernelImpl:fn}),_i={kernelName:a.LG0,backendName:"webgl",kernelFunc:Ri};class Oi{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((t,n)=>t[0]+e[n]+t[1]);const r=e.length,a=ae(r),o=t.map(e=>e[0]).join(","),s=t.map((t,n)=>t[0]+e[n]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),u="reflect"===n?0:1;this.userCode=1!==r?`\n      ${a} start = ${a}(${o});\n      ${a} end = ${a}(${s});\n\n      void main() {\n        ${a} outC = getOutputCoords();\n        for (int i = 0; i < ${r}; i++) {\n          if (outC[i] < start[i]) {\n            outC[i] = start[i] * 2 - outC[i] - ${u};\n          } else if(outC[i] >= end[i]) {\n            outC[i] = (end[i] - 1) * 2 - outC[i] + ${u};\n          }\n        }\n        ${a} coords = outC - start;\n        setOutput(getX(${i}));\n      }\n    `:`\n        int start = ${o};\n        int end = ${s};\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start) {\n            outC = start * 2 - outC - ${u};\n          } else if(outC >= end) {\n            outC = (end - 1) * 2 - outC + ${u};\n          }\n          setOutput(getX(outC - start));\n        }\n      `}}class Fi{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((t,n)=>t[0]+e[n]+t[1]);const r=e.length,a=ae(r),o=t.map(e=>e[0]).join(","),s=t.map((t,n)=>t[0]+e[n]).join(","),i=zn("rc",r),u=zn("source",r),c=`${i[r-1]} < ${this.outputShape[r-1]}`,l=1===r?"source":`vec2(${u.slice(-2).join()})`,p="reflect"===n?0:1;let h="";if(1===r){const e=`\n        ${a} source = rc;\n        if (source < start) {\n          source = start * 2 - source - ${p};\n        } else if (source >

2= end) {\n          source = (end - 1) * 2 - source + ${p};\n        }\n        source -= start;\n      `;h=`\n        ${a} rc = outputLoc;\n        ${e}\n        result[0] = getChannel(getX(${u.join()}), ${l});\n        ${i[r-1]} += 1;\n        if(${c}) {\n          ${e}\n          result[1] = getChannel(getX(${u.join()}), ${l});\n        }\n      `}else{const e=`\n        ${a} source = rc;\n        ${a} lt = ${a}(lessThan(source, start));\n        ${a} gte = ${a}(greaterThanEqual(source, end));\n        ${a} orig = 1 - (lt + gte);\n        source = orig * source +\n                lt * (start * 2 - source - ${p}) +\n                gte * ((end - 1) * 2 - source + ${p});\n        source -= start;\n      `;h=`\n        ${a} rc = outputLoc;\n        ${e}\n        result[0] = getChannel(getX(${u.join()}), ${l});\n        ${i[r-1]} += 1;\n        if(${c}) {\n          ${e}\n          result[1] = getChannel(getX(${u.join()}), ${l});\n        }\n        rc = outputLoc;\n        ${i[r-2]} += 1;\n        if(${i[r-2]} < ${this.outputShape[r-2]}) {\n          ${e}\n          result[2] = getChannel(getX(${u.join()}), ${l});\n          ${i[r-1]} += 1;\n          if(${c}) {\n            ${e}\n            result[3] = getChannel(getX(${u.join()}), ${l});\n          }\n        }\n      `}this.userCode=`\n      const ${a} start = ${a}(${o});\n      const ${a} end = ${a}(${s});\n\n      void main() {\n        ${a} outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        ${h}\n        setOutput(result);\n      }\n    `}}const Di={kernelName:a.x7F,backendName:"webgl",kernelFunc:({inputs:e,backend:t,attrs:n})=>{const{x:r}=e,{paddings:o,mode:s}=n,i=(0,a._K2)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Fi(r.shape,o,s):new Oi(r.shape,o,s);return t.runWebGLProgram(i,[r],r.dtype)}},Li=Tr({opSnippet:"if (b == 0.0) return NAN;\n  return mod(a, b);",packedOpSnippet:"\n  vec4 result = mod(a, b);\n  bvec4 isNaN = equal(b, vec4(0.0));\n  "+ur+"\n  return result;\n"}),Mi={kernelName:a.BLA,backendName:"webgl",kernelFunc:Li};class Pi{constructor(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],this.userCode=`\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < ${t-1}; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float(${t-1}));\n      }\n    `}}const Bi=Tr({opSnippet:"\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;",packedOpSnippet:"\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n",checkOutOfBounds:!0}),Vi={kernelName:a.sDr,backendName:"webgl",kernelFunc:Bi},zi="return a - b;",Ui=Tr({opSnippet:zi,packedOpSnippet:zi,supportsComplex:!0,cpuKernelImpl:Dn}),Wi={kernelName:a.PbM,backendName:"webgl",kernelFunc:Ui};function Gi(e){const{inputs:t,backend:n,attrs:r}=e,{logits:o}=t,{dim:s}=r,i=a.ZSL.parseAxisParam([s],o.shape),u=xi({inputs:{x:o},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),c=a.C0T.expandShapeToKeepDim(u.shape,i),l=Rr({inputs:{x:u},backend:n,attrs:{shape:c}}
vendor: 4,521 bytes, line 2
2),p=Ui({inputs:{a:o,b:l},backend:n}),h=cs({inputs:{x:p},backend:n}),d=Br({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),f=Rr({inputs:{x:d},backend:n,attrs:{shape:c}}),m=Bi({inputs:{a:h,b:f},backend:n});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(l),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}const ji={kernelName:a.rFG,backendName:"webgl",kernelFunc:Gi};const Ki={kernelName:a.WT3,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:o,seed:s,normalized:i}=r,u=i?a:Gi({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=u.shape[0],l=u.shape[1],p=new Pi(c,l,o),h=[[s]],d=n.runWebGLProgram(p,[u],"int32",h);return i||n.disposeIntermediateTensorInfo(u),d}},Hi=Zn+"\n  return -x;\n";const Yi={kernelName:a.l0G,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){const e=n.texData.get(r.dataId),[t,a]=gn(e.values,r.shape,r.dtype);return n.makeTensorInfo(a,r.dtype,t)}let o;return o=(0,a._K2)().getBool("WEBGL_PACK_UNARY_OPERATIONS")?new er(r.shape,"\n  vec4 result = -x;\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n"):new Yn(r.shape,Hi),n.runWebGLProgram(o,[r],r.dtype)}},Zi=a.kpo.c7;const Xi={kernelName:a.SDM,backendName:"webgl",kernelFunc:function(e){a.C0T.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");const{inputs:t,backend:n,attrs:r}=e,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:u,scoreThreshold:c}=r,l=n.readSync(o.dataId),p=n.readSync(s.dataId),{selectedIndices:h}=Zi(l,p,i,u,c);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}},qi=a.kpo.ZS;const Qi={kernelName:a.Zl4,backendName:"webgl",kernelFunc:function(e){a.C0T.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");const{inputs:t,backend:n,attrs:r}=e,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:u,scoreThreshold:c,padToMaxOutputSize:l}=r,p=n.readSync(o.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:f}=qi(p,h,i,u,c,l);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([f]))]}},Ji=a.kpo.ut;const eu={kernelName:a.e0f,backendName:"webgl",kernelFunc:function(e){a.C0T.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");const{inputs:t,backend:n,attrs:r}=e,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:u,scoreThreshold:c,softNmsSigma:l}=r,p=n.readSync(o.dataId),h=n.readSync(s.dataId),d=i,f=u,m=c,g=l,{selectedIndices:y,selectedScores:x}=Ji(p,h,d,f,m,g);return[n.makeTensorInfo([y.length],"int32",new Int32Array(y)),n.makeTensorInfo([x.length],"float32",new Float32Array(x))]}};class tu{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float(${r}), float(${n}),\n                      float(index == coords.y)));\n      }\n    `}}const nu={kernelName:a.urI,backendName:"webgl",kernelFunc:e=>{const{inputs:t,backend:n,attrs:r}=e,{indices:o}=t,{dtype:s,depth:i,onValue:u,offValue:c}=r,l=a.ZSL.sizeFromShape(o.shape),p=new tu(l,i,u,c),h=Rr({inputs:{x:o},backend:n,attrs:{shape:[l]}}),d=n.runWebGLProgram(p,[h],s);n.disposeIntermediateTensorInfo(h);const f=Rr({inputs:{x:d},backend:n,attrs:{shape:[...o.shape,i]}});return n.disposeIntermediateTensorInfo(d),f}};function ru(e){const{inputs:t,backend:n}=e,{x:r}=t;if("complex64"===r.dtype){const e=Ga({inputs:{input:r},backend:n}),t=ru({inputs:{x:e},backend:n}),a=oo({inputs:{input:r},backend:n}),o=ru({inputs:{x:a},backend:n}),s=hr({inputs:{real:t,imag:o},backend:n});return n.disposeIntermediateTensorInfo(e),n.disposeIntermediateTensorInfo(t),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),s}return vs({attrs:{shape:r.shape,dtype:r.dtype,value:"string"===r.dtype?"":0},backend:n})}const au={kernelName:a.xJ3,backendName:"webgl",kernelFunc:ru};const ou={kernelName:a.LWX,backendName:"webgl",kernelFunc:function e(t){const{inputs:n,backend:r}=t,{x:a}=n;if("string"===a.dtype)throw new Error("onesLike is not supported under string dtype");

2if("complex64"===a.dtype){const t=Ga({inputs:{input:a},backend:r}),n=e({inputs:{x:t},backend:r}),o=oo({inputs:{input:a},backend:r}),s=ru({inputs:{x:o},backend:r}),i=hr({inputs:{real:n,imag:s},backend:r});return r.disposeIntermediateTensorInfo(t),r.disposeIntermediateTensorInfo(n),r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(s),i}return vs({attrs:{shape:a.shape,dtype:a.dtype,value:1},backend:r})}};const su={kernelName:a.mM$,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{axis:o}=r;if(1===t.length)return ps({inputs:{input:t[0]},backend:n,attrs:{dim:o}});const s=t[0].shape,i=t[0].dtype;t.forEach(e=>{a.ZSL.assertShapesMatch(s,e.shape,"All tensors passed to stack must have matching shapes"),a.ZSL.assert(i===e.dtype,()=>"All tensors passed to stack must have matching dtypes")});const u=[],c=uo({inputs:t.map(e=>{const t=ps({inputs:{input:e},backend:n,attrs:{dim:o}});return u.push(t),t}),backend:n,attrs:{axis:o}});return u.forEach(e=>n.disposeIntermediateTensorInfo(e)),c}};class iu{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((t,n)=>t[0]+e[n]+t[1]);const r=e.length,a=ae(r),o=t.map(e=>e[0]).join(","),s=t.map((t,n)=>t[0]+e[n]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);this.userCode=1!==r?`\n      ${a} start = ${a}(${o});\n      ${a} end = ${a}(${s});\n\n      void main() {\n        ${a} outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(value);\n        } else {\n          ${a} coords = outC - start;\n          setOutput(getX(${i}));\n        }\n      }\n    `:`\n        int start = ${o};\n        int end = ${s};\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(value);\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      `}}class uu{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((t,n)=>t[0]+e[n]+t[1]);const r=e.length,a=ae(r),o=t.map(e=>e[0]).join(","),s=t.map((t,n)=>t[0]+e[n]).join(","),i=zn("rc",r),u=zn("source",r),c=`${i[r-1]} < ${this.outputShape[r-1]}`,l=1===r?"source":`vec2(${u.slice(-2).join()})`,p=[`${a} rc = outputLoc;`,`${i[r-1]} += 1;\n       if(${c}) {\n      `,1===r?"":`}\n       rc = outputLoc;\n       ${i[r-2]} += 1;\n       if(${i[r-2]} < ${this.outputShape[r-2]}) {`,1===r?"":`  ${i[r-1]} += 1;\n         if(${c}) {`],h=1===r?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))";let d="";for(let e=0,t=1===r?2:4;e<t;e++)d+=`\n        ${p[e]}\n        if (${h}) {\n          result[${e}] = float(value);\n        } else {\n          ${a} source = rc - start;\n          result[${e}] = getChannel(getX(${u.join()}), ${l});\n        }\n      `;d+=1===r?"} ":"}}",this.userCode=`\n      const ${a} start = ${a}(${o});\n      const ${a} end = ${a}(${s});\n\n      void main() {\n        ${a} outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        ${d}\n        setOutput(result);\n      }\n    `}}const cu=e=>{const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{paddings:s,constantValue:i}=r;if(0===a.ZSL.sizeFromShape(o.shape)){return vs({backend:n,attrs:{shape:s.map((e,t)=>e[0]+o.shape[t]+e[1]),value:i,dtype:o.dtype}})}const u=(0,a._K2)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new uu(o.shape,s,i):new iu(o.shape,s,i),c=[[i]];return n.runWebGLProgram(u,[o],o.dtype,c)},lu={kernelName:a.ODT,backendName:"webgl",kernelFunc:cu},pu=Tr({opSnippet:"\n  if(a < 0.0 && floor(b) < b){\n    return NAN;\n  }\n  if (b == 0.0) {\n    return 1.0;\n  }\n  return (round(mod(b, 2.0)) != 1) ?\n      pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",packedOpSnippet:"\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  bvec4 isNaN1 = lessThan(a, vec4(0.0));\n  bvec4 isNaN2 = lessThan(floor(b), b);\n  bvec4 isNaN = bvec4(isNaN1.x && isNaN2.x, isNaN1.y && isNaN2.y, isNaN1.z && isNaN2.z, isNaN1.w && isNaN2.

2w);\n  "+ur+"\n  return result;\n"}),hu={kernelName:a.pyJ,backendName:"webgl",kernelFunc:pu};const du={kernelName:a.kdj,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{axis:s,keepDims:i}=r,u=o.shape.length,c=[],l=a.ZSL.parseAxisParam(s,o.shape);let p=l;const h=a.C0T.getAxesPermutation(p,u);let d,f=o;if(null!=h&&(f=zr({inputs:{x:o},backend:n,attrs:{perm:h}}),p=a.C0T.getInnerMostAxes(p.length,u),c.push(f)),a.C0T.assertAxesAreInnerMostDims("prod",p,u),n.shouldExecuteOnCPU([f])){const e=n.texData.get(f.dataId).values,{outVals:t,outShape:r,outDtype:a}=xn(f.shape,f.dtype,e,p);d=n.makeTensorInfo(r,a,t)}else{const[e,t]=a.C0T.computeOutAndReduceShapes(f.shape,p),r=a.ZSL.sizeFromShape(t),s=Rr({inputs:{x:f},backend:n,attrs:{shape:[-1,r]}}),i=Dr(s,(0,a.chL)(o.dtype),"prod",n);d=Rr({inputs:{x:i},backend:n,attrs:{shape:e}}),c.push(s),c.push(i)}if(i){c.push(d);const e=a.C0T.expandShapeToKeepDim(d.shape,l);d=Rr({inputs:{x:d},backend:n,attrs:{shape:e}})}return c.forEach(e=>n.disposeIntermediateTensorInfo(e)),d}};const fu={kernelName:a.oJ2,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{paramsNestedSplits:a,paramsDenseValues:o,indices:s}=t,{outputRaggedRank:i}=r,u=a.map(e=>n.readSync(e.dataId)),c=a.map(e=>e.shape),l=n.readSync(o.dataId),p=n.readSync(s.dataId),[h,d,f]=bn(u,c,l,o.shape,o.dtype,p,s.shape,i),m=h.map(e=>n.makeTensorInfo([e.length],"int32",e)),g=n.makeTensorInfo(f,o.dtype,d);return m.concat([g])}};const mu={kernelName:a.mH5,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{shape:a,values:o,defaultValue:s,rowPartitionTensors:i}=t,{rowPartitionTypes:u}=r,c=n.readSync(a.dataId),l=n.readSync(o.dataId),p=n.readSync(s.dataId),h=i.map(e=>n.readSync(e.dataId)),d=i.map(e=>e.shape),[f,m]=vn(c,a.shape,l,o.shape,o.dtype,p,s.shape,h,d,u);return n.makeTensorInfo(f,o.dtype,m)}},gu=e=>{const{backend:t,attrs:n}=e,{start:r,stop:a,step:o,dtype:s}=n,i=wn(r,a,o,s);return t.makeTensorInfo([i.length],s,i)},yu={kernelName:a.Q6t,backendName:"webgl",kernelFunc:gu},xu=wr({opSnippet:"return 1.0 / x;"}),bu={kernelName:a.huO,backendName:"webgl",kernelFunc:xu},vu=wr({opSnippet:Zn+"\n  return (x < 0.0) ? 0.0 : x;\n",packedOpSnippet:"\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n"}),wu={kernelName:a.fUj,backendName:"webgl",kernelFunc:vu},Tu=wr({opSnippet:Zn+"\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n",packedOpSnippet:"\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n"}),Su={kernelName:a.P_L,backendName:"webgl",kernelFunc:Tu};class Cu{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];const[o,s,i,u]=e;this.outputShape=[o,t,n,u];const c=[r&&t>1?s-1:s,r&&n>1?i-1:i],l=[r&&t>1?t-1:t,r&&n>1?n-1:n];let p;p=a?"(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":"vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          ${c[0]/l[0]},\n          ${c[1]/l[1]});\n      const vec2 inputShapeRC = vec2(${s}.0, ${i}.0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = ${p};\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    `}}
vendor: 3,261 bytes, line 2
2class ku{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];const[o,s,i,u]=e;this.outputShape=[o,t,n,u];const c=[r&&t>1?s-1:s,r&&n>1?i-1:i],l=[r&&t>1?t-1:t,r&&n>1?n-1:n];let p;p=a?"(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":"vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          ${c[0]/l[0]},\n          ${c[1]/l[1]},\n          ${c[1]/l[1]});\n      const vec3 inputShapeRC = vec3(${s}.0, ${i}.0,\n                                     ${i}.0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = ${p};\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < ${u-1};\n        bool hasNextRow = coords.z < ${n-1};\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);

2\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    `}}const Eu={kernelName:a.hgw,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:u}=r,[c,l]=u,p=(0,a._K2)().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new ku(o.shape,c,l,s,i):new Cu(o.shape,c,l,s,i);return n.runWebGLProgram(p,[o],"float32")}};class $u{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;const[,r,a]=t,[,o,s]=e,i=[n&&o>1?r-1:r,n&&s>1?a-1:a],u=[n&&o>1?o-1:o,n&&s>1?s-1:s],c=i[0]/u[0],l=i[1]/u[1],p=1/c,h=1/l,d=2*Math.ceil(p)+2,f=2*Math.ceil(h)+2;this.userCode=`\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(${c});\n        const float widthScale = float(${l});\n\n        const float invHeightScale = float(${p});\n        const float invWidthScale = float(${h});\n\n        const int winHeight = int(${d});\n        const int winWidth = int(${f});\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= ${o}) {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= ${s}) {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), ${r-1}.0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), ${a-1}.0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    `}}const Nu={kernelName:a.FCQ,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{images:a,dy:o}=t,{alignCorners:s}=r,i=new $u(o.shape,a.shape,s);return n.runWebGLProgram(i,[o],o.dtype)}};class Iu{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];const[o,s,i,u]=e;this.outputShape=[o,t,n,u];const c=[r&&t>1?s-1:s,r&&n>1?i-1:i],l=[r&&t>1?t-1:t,r&&n>1?n-1:n],p=r?"0.5":"0.0";let h;h=a?"max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":"vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          ${c[0]/l[0]},\n          ${c[1]/l[1]});\n      const vec2 inputShapeRC = vec2(${s}.0, ${i}.0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = ${h};\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${p})));\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    `}}class Au{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];const[o,s,i,u]=e;this.outputShape=[o,t,n,u];const c=[r&&t>1?s-1:s,r&&n>1?i-1:i],l=[r&&t>1?t-1:t,r&&n>1?n-1:n],p=r?"0.5":"0.0";let h;h=a?"max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":"vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          ${c[0]/l[0]},\n          ${c[1]/l[1]},\n          ${c[1]/l[1]});\n      const vec3 inputShapeRC = vec3(${s}.0, ${i}.0,\n                                     ${i}.0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = ${h};\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec3 sourceNearestRC = ivec3(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${p})));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < ${u-1};\n        bool hasNextRow = coords.z < ${n-1};

2\n\n        vec4 newValue = vec4(\n          getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),\n          hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);\n\n        setOutput(newValue);\n      }\n    `}}const Ru={kernelName:a.jOE,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:u}=r,[c,l]=u,p=(0,a._K2)().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Au(o.shape,c,l,s,i):new Iu(o.shape,c,l,s,i);return n.runWebGLProgram(p,[o],o.dtype)}};class _u{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;const[,r,a]=t,[,o,s]=e,i=[n&&o>1?r-1:r,n&&s>1?a-1:a],u=[n&&o>1?o-1:o,n&&s>1?s-1:s],c=i[0]/u[0],l=i[1]/u[1],p=1/c,h=1/l,d=2*Math.ceil(p)+2,f=2*Math.ceil(h)+2;this.userCode=`\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(${c});\n        const float widthScale = float(${l});\n\n        const float invHeightScale = float(${p});\n        const float invWidthScale = float(${h});\n\n        const int winHeight = int(${d});\n        const int winWidth = int(${f});\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= ${o}) {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= ${s}) {\n              continue;\n            }\n\n            float sourceFracRow =\n              float(${i[0]}) *\n                (float(dyR) / float(${u[0]}));\n\n            float sourceFracCol =\n                float(${i[1]}) *\n                  (float(dyC) / float(${u[1]}));\n\n            int sourceNearestRow = int(min(\n                float(int(${r}) - 1),\n                ${n} ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int(${a}) - 1),\n                ${n} ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    `}}const Ou={kernelName:a.XQy,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{images:a,dy:o}=t,{alignCorners:s}=r,i=new _u(o.shape,a.shape,s);return n.runWebGLProgram(i,[o],o.dtype)}};class Fu{constructor(e,t){this.variableNames=["x"];const n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,1===n)return void(this.userCode=`\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX(${e[0]} - coord - 1));\n        }\n      `);const r=e.map((n,r)=>(n=>-1!==t.indexOf(n)&&1!==e[n]?`${e[n]} - coords[${n}] - 1`:`coords[${n}]`)(r)).join(","),a=ae(n);this.userCode=`\n      void main() {\n        ${a} coords = getOutputCoords();\n        setOutput(getX(${r}));\n      }\n    `}}class Du{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;const n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;const r=zn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,o=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,s=ae(n);function i(n){const r=e.map((r,a)=>function(n,r){return-1!==t.indexOf(n)&&1!==e[n]?`${e[n]} - ${r[n]} - 1`:`${r[n]}`}(a,n));return`getChannel(getX(${r.join(",")}), vec2(${r.slice(-2).join(",")}))`}this.userCode=1===n?`\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX(${e[0]} - rc - 1),\n            ${e[0]} - rc - 1);\n          if(${a}){\n              result.g = getChannel(getX(${e[0]} - (rc  + 1) - 1),\n                ${e[0]} - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      `:`\n        void main() {\n          ${s} rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = ${function(e){return i(e)}(r.slice())};\n          if(${a}){\n            result.g = ${function(e){return e[n-1]="("+e[n-1]+" + 1)",i(e)}(r.slice())};\n          }\n          if(${o}) {\n            result.b = ${function(e){return e[n-2]="("+e[n-2]+" + 1)",i(e)}(r.slice())};\n            if(${a}) {\n              result.a = ${function(e){return e[n-1]="("+e[n-1]+" + 1)",e[n-2]="("+e[n-2]+" + 1)",i(e)}(r.slice())};\n            }\n          }\n          setOutput(result);\n        }\n    `}}const Lu={kernelName:a.D7i,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{dims:s}=r,i=o.shape.length,u=a.ZSL.parseAxisParam(s,o.shape);if(0===i)return lr({inputs:{x:o},backend:n});const c=(0,a._K2)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Du(o.shape,u):new Fu(o.shape,u);return n.runWebGLProgram(c,[o],o.dtype)}};class Mu{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];const n=e[1],r=e[2];this.outputShape=e;let a="";a="number"==typeof t?`float outputValue = ${t.toFixed(2)};`:`\n        vec3 fill = vec3(${t.join(",")});\n        float outputValue = fill[coords[3]];`,this.userCode=`\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int x = coords[2];\n          int y = coords[1];\n          float coordXFloat = (float(x) - params[0]) * params[3] -\n            (float(y) - params[1]) * params[2];\n          float coordYFloat = (float(x) - params[0]) * params[2] +\n            (float(y) - params[1]) * params[3];

2\n          int coordX = int(round(coordXFloat + params[0]));\n          int coordY = int(round(coordYFloat + params[1]));\n          ${a}\n          if(coordX >= 0 && coordX < ${r} && coordY >= 0 && coordY < ${n}) {\n            outputValue = getImage(coords[0], coordY, coordX, coords[3]);\n          }\n          setOutput(outputValue);\n        }\n    `}}const Pu={kernelName:a.BK4,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{const{image:r}=e,{radians:o,fillValue:s,center:i}=t,u=n,c=new Mu(r.shape,s),[l,p]=a.C0T.getImageCenter(i,r.shape[1],r.shape[2]),h=[[l,p,Math.sin(o),Math.cos(o)]];return u.runWebGLProgram(c,[r],r.dtype,h)}},Bu=wr({opSnippet:"\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n"}),Vu={kernelName:a.hVg,backendName:"webgl",kernelFunc:Bu},zu=wr({opSnippet:"return inversesqrt(x);",cpuKernelImpl:Tn}),Uu={kernelName:a.TOR,backendName:"webgl",kernelFunc:zu};class Wu{constructor(e,t,n,r,a,o,s=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=o;const i=ae(a.length),u=ae(o.length);let c="";1===n?c="i":2===n&&(c="i, j");const l=`getIndices(${c})`;let p="";1===r?p="i":2===r&&(p="i, coords[1]");const h=`getUpdates(${p})`,d=t>1?"strides[j]":"strides";this.userCode=`\n        ${i} strides = ${i}(${a});\n\n        void main() {\n          ${u} coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < ${e}; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < ${t}; j++) {\n              int index = round(${l});\n              flattenedIndex += index * ${d};\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += ${h};\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      `}}const Gu={kernelName:a.pJc,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{indices:o,updates:s}=t,{shape:i}=r,{sliceRank:u,numUpdates:c,sliceSize:l,strides:p,outputSize:h}=a.C0T.calculateShapes(s,o,i),d=[h/l,l];if(0===h)return n.makeTensorInfo(i,o.dtype);const f=Rr({inputs:{x:o},backend:n,attrs:{shape:[c,u]}}),m=Rr({inputs:{x:s},backend:n,attrs:{shape:[c,l]}}),g=n.makeTensorInfo([],"float32",new Float32Array([0])),y=new Wu(c,u,f.shape.length,m.shape.length,p,d),x=n.runWebGLProgram(y,[m,f,g],m.dtype),b=Rr({inputs:{x:x},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(g),b}};class ju{constructor(e,t,n,r){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,n];const o=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,s=2===(0,a._K2)().getNumber("WEBGL_VERSION")?"while (left < right) {":o,i="left"===r?"<":"<=";this.userCode=`\n       int findBound(int batch, float value) {\n         int left = 0;\n         int right = numInputs;\n         int mid;\n         ${s}\n           mid = (left + right) / 2;\n           if (getSortedSequence(batch, mid) ${i} value) {\n             left = mid + 1;\n           } else {\n             right = mid;\n           }\n         }\n         return right;\n       }\n\n       void main() {\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int valueIndex = coords[1];\n\n         float value = getValues(batch, valueIndex);\n\n         setOutput(float(findBound(batch, value)));\n       }\n     `}}const Ku={kernelName:a.uWl,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{sortedSequence:a,values:o}=t,{side:s}=r,i=new ju(a.shape[0],a.shape[1],o.shape[1],s),u=[[a.shape[1]]];return n.runWebGLProgram(i,[a,o],"int32",u)}};class Hu{constructor(e,t,n){let r,a;

2if(this.variableNames=["c","a","b"],this.outputShape=t,n>4)throw Error(`Where for rank ${n} is not yet supported`);if(1===n)a="resRC",r="resRC";else{const n=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],s=[];for(let r=0;r<t.length;r++)s.push(`${n[r]}`),r<e&&o.push(`${n[r]}`);r=o.join(),a=s.join()}const o=ae(n);this.userCode=`\n      void main() {\n        ${o} resRC = getOutputCoords();\n        float cVal = getC(${r});\n        if (cVal >= 1.0) {\n          setOutput(getA(${a}));\n        } else {\n          setOutput(getB(${a}));\n        }\n      }\n    `}}const Yu={kernelName:a.l6P,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{condition:r,t:o,e:s}=t,i=new Hu(r.shape.length,o.shape,o.shape.length);return n.runWebGLProgram(i,[r,o,s],(0,a.TuY)(o.dtype,s.dtype))}},Zu=wr({opSnippet:`\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = ${a.C0T.SELU_SCALEALPHA};\n  float scale = ${a.C0T.SELU_SCALE};\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n`}),Xu={kernelName:a.u$b,backendName:"webgl",kernelFunc:Zu},qu=wr({opSnippet:vr+"\n  return 1.0 / (1.0 + exp(-1.0 * x));\n",packedOpSnippet:"\n  vec4 result = 1.0 / (1.0 + exp(-1.0 * x));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",cpuKernelImpl:Cn}),Qu={kernelName:a.vI1,backendName:"webgl",kernelFunc:qu},Ju=wr({opSnippet:"\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n"}),ec={kernelName:a.YVe,backendName:"webgl",kernelFunc:Ju},tc=wr({opSnippet:vr+"\n  return sin(x);\n"}),nc={kernelName:a.hql,backendName:"webgl",kernelFunc:tc},rc=wr({opSnippet:"\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n"}),ac={kernelName:a.J3C,backendName:"webgl",kernelFunc:rc},oc=wr({opSnippet:"\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n"}),sc={kernelName:a.Fin,backendName:"webgl",kernelFunc:oc},ic={kernelName:a.A8B,backendName:"webgl",kernelFunc:e=>{const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{blockShape:s,paddings:i}=r;a.ZSL.assert(o.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");const u=s.reduce((e,t)=>e*t),c=[[0,0]];c.push(...i);for(let e=1+s.length;e<o.shape.length;++e)c.push([0,0]);const l=[],p=cu({inputs:{x:o},backend:n,attrs:{paddings:c,constantValue:0}}),h=a.C0T.getReshaped(p.shape,s,u,!1),d=a.C0T.getPermuted(h.length,s.length,!1),f=a.C0T.getReshapedPermuted(p.shape,s,u,!1),m=Rr({inputs:{x:p},backend:n,attrs:{shape:h}}),g=zr({inputs:{x:m},backend:n,attrs:{perm:d}}),y=Rr({inputs:{x:g},backend:n,attrs:{shape:f}});return l.push(p),l.push(m),l.push(g),l.forEach(e=>n.disposeIntermediateTensorInfo(e)),y}};const uc={kernelName:a.C8s,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{indices:r,values:a,denseShape:o,defaultValue:s}=t;if(1!==o.shape.length)throw new Error(`Dense shape must be a vector, saw:\n         ${o.shape}`);if(2!==r.shape.length)throw new Error(`Indices must be a matrix, saw:\n         ${r.shape}`);if(1!==a.shape.length)throw new Error(`Values must be a vector, saw:\n         ${a.shape}`);if(0!==s.shape.length)throw new Error(`Default value must be a scalar, saw:\n        ${s.shape}`);const i=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n.readSync(o.dataId),l=n.readSync(s.dataId)[0],[p,h,d,f,m]=$n(i,r.shape,r.dtype,u,a.dtype,c,l);return[n.makeTensorInfo(h,r.dtype,p),n.makeTensorInfo([h[0]],a.dtype,d),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(e=>Number(e)))),n.makeTensorInfo([m.length],r.dtype,new Int32Array(m))]}};const cc={kernelName:a.BoJ,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{inputIndices:r,inputShape:a,newShape:o}=t;if(2!==r.shape.length)throw new Error(`Input indices should be a matrix but received shape ${r.shape}`);if(1!==a.shape.length)throw new Error(`Input shape should be a vector but received shape ${a.shape}`);if(1!==o.shape.length)throw new Error(`Target shape should be a vector but received shape ${o.shape}`);const s=Array.from(n.readSync(a.dataId)),i=n.readSync(r.dataId),u=Array.from(n.readSync(o.dataId)),[c,l,p]=Nn(i,r.shape,r.dtype,s,u);return[n.makeTensorInfo(l,r.dtype,c),n.makeTensorInfo([p.length],o.dtype,new Int32Array(p))]}};const lc={kernelName:a.L6G,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{data:r,indices:a,segmentIds:o}=t;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");
vendor: 7,255 bytes, line 2
2if(1!==a.shape.length)throw new Error(`Indices should be a vector but received shape\n              ${a.shape}`);if(1!==o.shape.length)throw new Error(`Segment ids should be a vector but received shape\n              ${o.shape}`);const s=n.readSync(r.dataId),i=n.readSync(a.dataId),u=n.readSync(o.dataId),[c,l]=In(s,r.shape,r.dtype,i,u,!0);return n.makeTensorInfo(l,r.dtype,c)}};const pc={kernelName:a.DvZ,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n}=e,{data:r,indices:a,segmentIds:o}=t;if(r.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==a.shape.length)throw new Error(`Indices should be a vector but received shape\n             ${a.shape}`);if(1!==o.shape.length)throw new Error(`Segment ids should be a vector but received shape\n             ${o.shape}`);const s=n.readSync(r.dataId),i=n.readSync(a.dataId),u=n.readSync(o.dataId),[c,l]=In(s,r.shape,r.dtype,i,u);return n.makeTensorInfo(l,r.dtype,c)}};const hc={kernelName:a.jgd,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{sparseIndices:o,sparseValues:s,defaultValue:i}=t,{outputShape:u}=r,{sliceRank:c,numUpdates:l,sliceSize:p,strides:h,outputSize:d}=a.C0T.calculateShapes(s,o,u),f=!1;if("string"===s.dtype){const e=n.bufferSync(o),t=n.bufferSync(s),r=a.ZSL.decodeString(n.readSync(i.dataId)[0]),m=Sn(e,t,u,d,p,l,c,h,r,f);return n.makeTensorInfo(u,m.dtype,m.values)}const m=new Wu(l,c,o.shape.length,s.shape.length,h,[d,1],f),g=n.runWebGLProgram(m,[s,o,i],s.dtype),y=Rr({inputs:{x:g},backend:n,attrs:{shape:u}});return n.disposeIntermediateTensorInfo(g),y}};const dc={kernelName:a.Blb,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{numOrSizeSplits:s,axis:i}=r,u=a.ZSL.parseAxisParam(i,o.shape)[0],c=a.C0T.prepareSplitSize(o,s,u),l=o.shape.length,p=new Array(l).fill(0),h=o.shape.slice();return c.map(e=>{const t=[...h];t[u]=e;const r=Ma({inputs:{x:o},backend:n,attrs:{begin:p,size:t}});return p[u]+=e,r})}},fc="return sqrt(x);",mc=wr({opSnippet:fc,packedOpSnippet:fc,cpuKernelImpl:An}),gc={kernelName:a.dFH,backendName:"webgl",kernelFunc:mc},yc=wr({opSnippet:"return x * x;"}),xc={kernelName:a.M6A,backendName:"webgl",kernelFunc:yc},bc="return (a - b) * (a - b);",vc=Tr({opSnippet:bc,packedOpSnippet:bc}),wc={kernelName:a.Ddj,backendName:"webgl",kernelFunc:vc};const Tc={kernelName:a.pnw,backendName:"webgl",kernelFunc:function({inputs:e,attrs:t,backend:n}){const{x:r}=e,a=Zn+`\n    return x > 0.0 ? 1.0 : float(${t.alpha});\n  `,o=new Yn(r.shape,a);return n.runWebGLProgram(o,[r],r.dtype)}};class Sc{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;const r=n.length,a=ae(n.length),o=ae(n.length);let s="";if(1===r)s="coords * strides + begin";else{let e=0;s=n.map((t,r)=>(e++,1===n.length?`coords * strides[${r}] + begin[${r}]`:`coords[${e-1}] * strides[${r}] + begin[${r}]`)).join(",")}this.userCode=`\n      ${a} begin = ${a}(${e});\n      ${a} strides = ${a}(${t});\n\n      void main() {\n        ${o} coords = getOutputCoords();\n        setOutput(getX(${s}));\n      }\n    `}}const Cc={kernelName:a.UcO,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{begin:s,end:i,strides:u,beginMask:c,endMask:l,ellipsisMask:p,newAxisMask:h,shrinkAxisMask:d}=r,{finalShapeSparse:f,finalShape:m,isIdentity:g,sliceDim0:y,isSimpleSlice:x,begin:b,end:v,strides:w}=a.Kro.sliceInfo(o.shape,s,i,u,c,l,p,h,d);let T;if(g)T=Rr({inputs:{x:o},backend:n,attrs:{shape:m}});else if(y||x){a.ZSL.assert(o.shape.length>=1,()=>`Input must have rank at least 1, got: ${o.shape.length}`);const e=a.Kro.computeOutShape(b,v,w),t=Ma({inputs:{x:o},backend:n,attrs:{begin:b,size:e}});T=Rr({inputs:{x:t},backend:n,attrs:{shape:m}}),n.disposeIntermediateTensorInfo(t)}else{if(n.shouldExecuteOnCPU([o])){const e=n.readSync(o.dataId),t=(0,a.ra8)(o.shape,o.dtype,e),r=Rn(f,t,w,b);T=n.makeTensorInfo(m,o.dtype,r.values)}else{const e=new Sc(b,w,f);T=n.runWebGLProgram(e,[o],o.dtype)}}const S=Rr({inputs:{x:T},backend:n,attrs:{shape:m}});return n.disposeIntermediateTensorInfo(T),S}};const kc={kernelName:a.YAb,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{separator:a,nGramWidths:o,leftPad:s,rightPad:i,padWidth:u,preserveShortSequences:c}=r,{data:l,dataSplits:p}=t,h=n.readSync(l.dataId),d=n.readSync(p.dataId),[f,m]=_n(h,d,a,o,s,i,u,c);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}};const Ec={kernelName:a.iW0,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{skipEmpty:a}=r,{input:o,delimiter:s}=t;if("string"!==o.dtype)throw new Error("Input must be of datatype string");if(1!==o.shape.length)throw new Error(`Input must be a vector, got shape: ${o.shape}`);if(0!==s.shape.length)throw new Error(`Delimiter must be a scalar, got shape: ${s.shape}`);const i=n.readSync(o.dataId),u=n.readSync(s.dataId)[0],[c,l,p]=On(i,u,a),h=l.length;return[n.makeTensorInfo([h,2],"int32",c),n.makeTensorInfo([h],"string",l),n.makeTensorInfo([2],"int32",new Int32Array(p))]}};const $c={kernelName:a.$jE,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{numBuckets:a}=r,{input:o}=t;if("string"!==o.dtype)throw new Error("Input must be of datatype string");if(a<=0)throw new Error("Number of buckets must be at least 1");const s=n.readSync(o.dataId),i=Fn(s,a);return n.makeTensorInfo(o.shape,"int32",i)}},Nc=wr({opSnippet:"return tan(x);"}),Ic={kernelName:a.oFs,backendName:"webgl",kernelFunc:Nc},Ac=wr({opSnippet:"\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n"}),Rc={kernelName:a.iuW,backendName:"webgl",kernelFunc:Ac};class _c{constructor(e,t){this.variableNames=["A"];const n=new Array(e.length);for(let r=0;r<n.length;r++)n[r]=e[r]*t[r];this.outputShape=n,this.rank=n.length;const r=ae(this.rank),a=function(e){const t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(1===t)return`imod(resRC, ${e[0]})`;const n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let t=0;t<e.length;t++)r.push(`imod(${n[t]}, ${e[t]})`);return r.join()}(e);this.userCode=`\n      void main() {\n        ${r} resRC = getOutputCoords();\n        setOutput(getA(${a}));\n      }\n    `}}function Oc(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{reps:s}=r;if("string"===o.dtype||o.shape.length>5){const e=n.readSync(o.dataId),t="string"===o.dtype?e.map(e=>a.ZSL.decodeString(e)):e,r=(0,a.ra8)(o.shape,o.dtype,t),i=Ln(r,s);return n.makeTensorInfo(i.shape,i.dtype,i.values)}const i=new _c(o.shape,s);return n.runWebGLProgram(i,[o],o.dtype)}const Fc={kernelName:a.FAs,backendName:"webgl",kernelFunc:Oc};class Dc{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="\n       void main() {\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int elemIdx = coords[1];\n\n         // We compare elements pair-wise within a group of size 2 * inc.\n         // The comparing rule for each group alternates between ascending\n         // and desce

2nding. Within each group, we compare each pair at\n         // positions i and i+inc. To decide whether an element at position i\n         // is x0 or x1, we mod it by 2 * inc, if the result is smaller than\n         // inc, it is in the first half of the group, we denote it as x0,\n         // otherwise we denote it as x1.\n         // For example, as shown in the Bitonic top K paper referenced above,\n         // Figure5(a) shows that element[1] is in the\n         // second half of the group when group size is 2, but it is in the\n         // first half of the group when group size is 4.\n\n         bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;\n         int i = isFirstInPair ? elemIdx : elemIdx - inc;\n\n         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n         int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));\n         float x0 = i0 < n ? getX(batch, i0) : negativeInf;\n         float x1 = i1 < n ? getX(batch, i1) : negativeInf;\n\n         // Denotes which direction indices are in (ascending or descending).\n         bool reverse = imod(elemIdx, 2 * dir) >= dir;\n         bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);\n         if (reverse == isGreater) { // Elements in opposite order of direction\n           int iTemp = i0;\n           i0 = i1;\n           i1 = iTemp;\n         }\n         if (isFirstInPair) {\n            setOutput(float(i0));\n         } else {\n            setOutput(float(i1));\n         }\n       }\n     "}}class Lc{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="\n    void main() {\n         // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int elemIdx = coords[1];\n\n         // The output size is half of the previous size.\n         // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _ (k=4),\n         // we only need to output the indices at positions |, the indices at\n         // positions _ can be thrown away, see Figure5(b) After Phase 2\n         // (Merge phase) in the Bitonic Top K paper referenced above.\n         // For example, the paper shows we only need to output the orange bars.\n         // The output sequence should look like this | | | | | | | |.\n         // Because the sequence is halved, to map the output index back\n         // to the previous sequence to find the corresponding value,\n         // we need to double the index. When we double the index,\n         // we basically interpolate a position, so 2i looks like\n         // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position\n         // of each 2k positions by - elemIdx % k. E.g. for output at\n         // index 4,5,6,7, we want to get the corresponding element at\n         // original index 8,9,10,11, for output at index 8,9,10,11,\n         // we want to get the corresponding element at original index\n         // 16,17,18,19, so on and so forth.\n\n         int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));\n         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n         int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));\n\n         float x0 = getX(batch, i0);\n         float x1 = i1 < n ? getX(batch, i1) : x0;\n\n         setOutput(x0 >= x1 ? float(i0) : float(i1));\n       }\n     "}}function Mc(e,t){null!==t&&e.disposeIntermediateTensorInfo(t)}function Pc(e){let t=1;for(;t<e;)t*=2;return t}const Bc={kernelName:a.TBb,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:o}=t,{k:s,sorted:i}=r,u=(0,a._K2)().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),c=(0,a._K2)().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),l=o.shape,p=l[l.length-1];if(n.shouldExecuteOnCPU([o])||p<u||s>c){const e=n.readSync(o.dataId),[t,r]=Mn(e,l,o.dtype,s,i);return[n.makeTensorInfo(t.shape,t.dtype,t.values),n.makeTensorInfo(r.shape,r.dtype,r.values)]}if(0===s)return l[l.length-1]=0,[n.makeTensorInfo(l,o.dtype,[]),n.makeTensorInfo(l,"int32",[])];if(1===p)return[o,vs({attrs:{shape:l,dtype:"int32",value:0},backend:n})];const h=n.texData.get(o.dataId),d=null!==h&&h.isPacked,f=d?n.unpackTensor(o):o,m=a.ZSL.sizeFromShape(l)/p,g=Rr({inputs:{x:f},attrs:{shape:[m,p]},backend:n});d&&Mc(n,f);const y=Pc(s),x=Pc(p);let b=null;const v=()=>null===b?[g,g]:[g,b],w=(e,t,r)=>{const a=v(),o=new Dc(r),s=[[p],[null===b?1:0],[Number.NEGATIVE_INFINITY],[e],[t]],i=b;b=n.runWebGLProgram(o,a,"int32",s),Mc(n,i)};for(let e=1;e<y;e*=2){const t=2*e;for(let n=e;n>=1;n/=2)w(t,n,[m,x])}for(let e=x;e>y;e/=2){const t=v(),r=new Lc([m,e/2]),a=[[p],[null===b?1:0],[y]],o=b;b=n.runWebGLProgram(r,t,"int32",a),Mc(n,o);const s=y/2,i=2*s;for(let e=s;e>=1;e/=2)w(i,e,b.shape)}let T=b;b=Ma({inputs:{x:b},backend:n,attrs:{begin:0,size:[m,s]}}),Mc(n,T);
vendor: 2,656 bytes, line 2
2let S=Bs({inputs:{x:g,indices:b},backend:n,attrs:{axis:1,batchDims:1}});Mc(n,g);const C=l.slice(0,-1);C.push(s),T=b,b=Rr({inputs:{x:b},attrs:{shape:C},backend:n}),Mc(n,T);const k=S;return S=Rr({inputs:{x:S},attrs:{shape:C},backend:n}),Mc(n,k),[S,b]}};class Vc{constructor(e,t,n,r,a,o){this.variableNames=["Image","Transforms"],this.outputShape=o;const s="nearest"===n?1:2;let i;switch(r){case"constant":default:i=1;break;case"reflect":i=2;break;case"wrap":i=3;break;case"nearest":i=4}this.userCode=`\n            float mapCoord(float outCoord, float len) {\n              float inCoord = outCoord;\n              if(${i} == 2) {\n                if (inCoord < 0.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz2 = 2.0 * len;\n                    if (inCoord < sz2) {\n                      inCoord = sz2 * float(int(float(-inCoord / sz2))) +\n                      inCoord;\n                    }\n                    inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;\n                  }\n                } else if (inCoord > len - 1.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz2 = 2.0 * len;\n                    inCoord -= sz2 * float(int(float(inCoord / sz2)));\n                    if (inCoord >= len) {\n                      inCoord = sz2 - inCoord - 1.0;\n                    }\n                  }\n                }\n                return clamp(inCoord, 0.0, len - 1.0);\n              } else if (${i} == 3) {\n                if (inCoord < 0.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz = len - 1.0;\n                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);\n                  }\n                } else if (inCoord > len - 1.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz = len - 1.0;\n                    inCoord -= len * float(int(float(inCoord / sz)));\n                  }\n                }\n                return clamp(inCoord, 0.0, len - 1.0);\n              } else if (${i} == 4) {\n                return clamp(outCoord, 0.0, len - 1.0);\n              } else {\n                return outCoord;\n              }\n            }\n\n            float readWithFillValue(int batch, int coordY, int coordX,\n              int channel) {\n              float outputValue;\n              if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}

2) {\n                  outputValue = getImage(batch, coordY, coordX, channel);\n              } else {\n                outputValue = float(${a});\n              }\n              return outputValue;\n            }\n\n            void main() {\n              ivec4 coords = getOutputCoords();\n              float outputValue;\n              int batch = coords[0];\n              int x = coords[2];\n              int y = coords[1];\n              int channel = coords[3];\n              float xf = float(x);\n              float yf = float(y);\n              float a1 = getTransforms(batch, 0);\n              float a2 = getTransforms(batch, 1);\n              float a3 = getTransforms(batch, 2);\n              float b1 = getTransforms(batch, 3);\n              float b2 = getTransforms(batch, 4);\n              float b3 = getTransforms(batch, 5);\n              float c1 = getTransforms(batch, 6);\n              float c2 = getTransforms(batch, 7);\n              float projection = c1 * xf + c2 * yf + 1.0;\n              if (projection == 0.0) {\n                outputValue = float(${a});\n              } else {\n                float inX = (a1 * xf + a2 * yf + a3) / projection;\n                float inY = (b1 * xf + b2 * yf + b3) / projection;\n                float mapX = mapCoord(inX, float(${t}));\n                float mapY = mapCoord(inY, float(${e}));\n\n                if (${s} == 1) {\n                  int coordY = int(round(mapY));

2\n                  int coordX = int(round(mapX));\n                  outputValue = readWithFillValue(batch, coordY, coordX,\n                    channel);\n                } else {\n                  float yFloor = floor(mapY);\n                  float xFloor = floor(mapX);\n                  float yCeil = yFloor + 1.0;\n                  float xCeil = xFloor + 1.0;\n                  float valueYFloor = (xCeil - mapX) *\n                  readWithFillValue(batch, int(yFloor), int(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, int(yFloor), int(xCeil), channel);\n                  float valueYCeil = (xCeil - mapX) *\n                  readWithFillValue(batch, int(yCeil), int(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, int(yCeil), int(xCeil), channel);\n                  outputValue = (yCeil - mapY) * valueYFloor +\n                  (mapY - yFloor) * valueYCeil;\n                }\n              }\n              setOutput(outputValue);\n            }\n        `}}const zc={kernelName:a.dLy,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:o}=t,{interpolation:s,fillMode:i,fillValue:u,outputShape:c}=r,[l,p,h,d]=a.shape,[f,m]=null!=c?c:[p,h],g=new Vc(p,h,s,i,u,[l,f,m,d]);return n.runWebGLProgram(g,[a,o],"float32")}};const Uc={kernelName:a.EwU,backendName:"webgl",kernelFunc:function(e){const{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:o}=t;B(o,"unique");const s=r.readSync(o.dataId),{outputValues:i,outputShape:u,indices:c}=Bn(s,a,o.shape,o.dtype);return[r.makeTensorInfo(u,o.dtype,i),r.makeTensorInfo([c.length],"int32",c)]}};const Wc={kernelName:a.dXR,backendName:"webgl",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{value:a}=t;let{axis:o}=r;o<0&&(o+=a.shape.length);const s=a,i=s.shape.length,u=a.shape[o],c=new Array(i-1);let l=0;for(let e=0;e<i;e++)e!==o&&(c[l++]=s.shape[e]);const p=[],h=new Array(i).fill(0),d=s.shape.slice();d[o]=1;const f=new Array(u);for(let e=0;e<f.length;e++){h[o]=e;const t=Ma({inputs:{x:s},backend:n,attrs:{begin:h,size:d}}),r=Rr({inputs:{x:t},backend:n,attrs:{shape:c}});f[e]=r,p.push(t)}return p.forEach(e=>n.disposeIntermediateTensorInfo(e)),f}};class Gc{constructor(e,t){this.variableNames=["x","segmentIds"];const n=e.windowSize,r=e.batchSize,a=e.inSize,o=e.numSegments,s=o*Math.ceil(a/n);this.outputShape=[r,s];const i=4*Math.floor(n/4),u=n%4,c="\n        sumValue += dot(values, segFilter);\n    ";let l="";a%n>0&&(l=`\n        if (inIdx < 0 || inIdx >= ${a}) {\n          return initializationValue;\n        }\n      `);let p="";a%n>0&&(p=`\n        if (inIdx < 0 || inIdx >= ${a}) {\n          return -1.0;\n        }\n      `),this.userCode=`\n      const float initializationValue = 0.0;\n\n      float getValue(int batch, int inIdx) {\n        ${l}\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        ${p}\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          ${o})) * float(${n}));\n        int currentSeg = int(mod(float(outIdx), float(${o})));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < ${i}; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          ${c}\n        }\n\n        int inIdx = inOffset + ${i};\n        if (${1===u}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          ${c}\n        } else if (${2===u}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          ${c}\n        } else if (${3===u}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          ${c}\n        }\n        setOutput(sumValue);\n      }\n    `}}const jc=[Gr,Kr,Yr,Xr,Jr,na,ra,aa,la,pa,da,ma,ya,ba,wa,Ca,ka,Na,Ia,Aa,Oa,Ba,Va,za,Ka,Za,Qa,dr,to,co,xo,So,Co,ko,Eo,$o,Io,Ro,Oo,Bo,Vo,zo,Wo,Ko,Zo,Xo,Qo,es,ts,rs,as,ss,us,ls,hs,ms,xs,ws,Ss,Es,Ns,Rs,Fs,Ds,Ms,Vs,Us,Gs,pr,js,so,Hs,Zs,qs,gr,Js,ti,ni,ai,si,ui,li,hi,mi,yi,bi,wi,Ti,Si,Ei,$i,Ni,Ii,Ai,_i,Di,Mi,Ki,Ar,Yi,Xi,Qi,eu,Wa,nu,ou,su,lu,hu,br,du,fu,mu,yu,ja,Vi,bu,

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2f=o[0],m=o[1],g=o[2]}else if("same"===e){f=Math.ceil(t/a),m=Math.ceil(n/o),g=Math.ceil(r/s);const e=(f-1)*a+i-t,c=(m-1)*o+u-n,p=(g-1)*s+l-r,d=Math.floor(e/2),y=e-d,x=Math.floor(c/2),b=c-x,v=Math.floor(p/2);h={top:x,bottom:b,left:v,right:p-v,front:d,back:y,type:"SAME"}}else{if("valid"!==e)throw Error(`Unknown padding parameter: ${e}`);h={top:0,bottom:0,left:0,right:0,front:0,back:0,type:"VALID"},f=Math.ceil((t-i+1)/a),m=Math.ceil((n-u+1)/o),g=Math.ceil((r-l+1)/s)}return{padInfo:h,outDepth:f,outHeight:m,outWidth:g}}(a,l,f,m,w,T,S,$,N,I,i),F=o?v*g:v;let D;return"channelsFirst"===s?D=[u,F,R,_,O]:"channelsLast"===s&&(D=[u,R,_,O,F]),{batchSize:u,dataFormat:s,inDepth:l,inHeight:f,inWidth:m,inChannels:g,outDepth:R,outHeight:_,outWidth:O,outChannels:F,padInfo:A,strideDepth:w,strideHeight:T,strideWidth:S,filterDepth:y,filterHeight:x,filterWidth:b,effectiveFilterDepth:$,effectiveFilterHeight:N,effectiveFilterWidth:I,dilationDepth:C,dilationHeight:k,dilationWidth:E,inShape:e,outShape:D,filterShape:t}}function c(e,t,n,r=1){const a=h(t,r);return Math.floor((e[0]*(n-1)-n+a)/2)}function l(e){return"number"==typeof e?[e,e,e]:2===e.length?[e[0],e[1],1]:e}function p(e){return"number"==typeof e?[e,e,e]:e}function h(e,t){return t<=1?e:e+(e-1)*(t-1)}function d(e,t){if(!t)return Math.trunc(e);switch(t){case"round":return Math.round(e);case"ceil":return Math.ceil(e);case"floor":return Math.floor(e);default:throw new Error(`Unknown roundingMode ${t}`)}}function f(e){const[t,n,r]=l(e);return 1===t&&1===n&&1===r}function m(e,t){return f(e)||f(t)}function g(e){if("NHWC"===e)return"channelsLast";if("NCHW"===e)return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function y(e,t,n){if(null!=n){if("string"==typeof t)throw Error(`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`);if("number"==typeof t)r.vA(r.E6(t),()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`);else{if("object"!=typeof t)throw Error(`Error in ${e}: Unknown padding parameter: ${t}`);t.forEach(t=>{t.forEach(t=>{r.vA(r.E6(t),()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`)})})}}}},52046:function(e,t,n){"use strict";var r,a,o,s,i;n.d(t,{Tu:function(){return c},ch:function(){return l}}),function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"}(r||(r={})),function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"}(a||(a={})),function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"}(o||(o={})),function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"}(s||(s={})),function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"}(i||(i={}));const u={float32:s,int32:a,bool:o,complex64:i};function c(e,t){if("string"===e||"string"===t){if("string"===e&&"string"===t)return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return u[e][t]}function l(e){return c(e,"int32")}},54411:function(e,t,n){"use strict";n.d(t,{Y:function(){return a}});var r=n(448);function a(e,t){const n=[];for(let e=0;e<t.length;e++)t[e]&&n.push(e);const a=(0,r.r)(e,"int32"),o=(0,r.r)([n.length,e.length],"int32");for(let t=0;t<n.length;t++){const r=a.indexToLoc(n[t]),s=t*e.length;o.values.set(r,s)}return o.toTensor()}},57260:function(e,t,n){"use strict";n.d(t,{T2:function(){return v},Ye:function(){return b}});var r=n(15149),a=n(46574),o=n(41743),s=n(15441),i=n(37074),u=n(73673),c=n(31259),l=n(45119);class p{constructor(e,t){this.backendTimer=e,this.logger=t,null==t&&(this.logger=new d)}profileKernel(e,t,n){let r;const o=()=>{r=n()};let s;const i=c.now();if(this.backendTimer.timerAvailable())s=this.backendTimer.time(o);else{o();for(const e of r)e.dataSync();s=Promise.resolve({kernelMs:c.now()-i})}if((0,a._K)().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let t=0;t<r.length;t++){const n=r[t];n.data().then(t=>{h(t,n.dtype,e)})}return{kernelName:e,outputs:r,inputs:t,timeMs:s.then(e=>e.kernelMs),extraInfo:s.then(e=>null!=e.getExtraProfileInfo?e.getExtraProfileInfo():"")}}logKernelProfile(e){const{kernelName:t,outputs:n,timeMs:r,inputs:a,extraInfo:o}=e;

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n=e[t],{success:r,asyncInit:a}=this.initializeBackend(n);if(a||r)return{name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){const n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),o=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,o),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n,r=null;if(null==t){if("function"!=typeof e)throw new Error("Please provide a function to tidy()");t=e}else{if("string"!=typeof e&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!=typeof t)throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");r=e}return this.scopedRun(()=>this.startScope(r),()=>this.endScope(n),()=>(n=t(),n))}scopedRun(e,t,n){e();try{const e=n();return t(),e}catch(e){throw t(),e}}nextTensorId(){return x.nextTensorId++}nextVariableId(){return x.nextVariableId++}clone(e){const t=v.runKernel(s.lzr,{x:e}),n={x:e};return this.addTapeNode(this.state.activeScope.name,n,[t],e=>({x:()=>{const t={x:e},n={dtype:"float32"};return v.runKernel(s.KXH,t,n)}}),[],{}),t}runKernel(e,t,n){null==this.backendName&&this.backend;if(!(null!=(0,i._5)(e,this.backendName)))throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){const r=this.backend.numDataIds();let a=0;n.forEach(e=>{a+="complex64"===e.dtype?3:1});const o=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],s=r-t-a-o;if(s>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${s} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[];const r=this.isTapeOn(),a=this.state.numBytes,o=this.state.numTensors;let s,u;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0),null==this.backendName&&this.backend;const c=g(e)?e.kernelName:null!=this.state.activeScope?this.state.activeScope.name:"";if(g(e)){const{kernelName:t,inputs:a,attrs:o}=e;null==this.backendName&&this.backend;const c=(0,i._5)(t,this.backendName);l.vA(null!=c,()=>`Cannot find registered kernel '${t}' for backend '${this.backendName}'`),s=()=>{const e=this.backend.numDataIds();u=c.kernelFunc({inputs:a,attrs:o,backend:this.backend});const s=Array.isArray(u)?u:[u];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(t,e,s);const i=s.map(e=>null!=e.rank?e:this.makeTensorFromTensorInfo(e));if(r){const e=this.getTensorsForGradient(t,a,i);n=this.saveTensorsForBackwardMode(e)}return i}}else{const{forwardFunc:t}=e,a=e=>{r&&(n=e.map(e=>this.keep(this.clone(e))))};s=()=>{const e=this.backend.numDataIds();u=this.tidy(()=>t(this.backend,a));const n=Array.isArray(u)?u:[u];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(c,e,n),n}}const{inputs:p,attrs:h}=e,d=g(e)?null:e.backwardsFunc;let f;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{this.ENV.getBool("DEBUG")||this.state.profiling?(f=this.profiler.profileKernel(c,p,()=>s()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(f),t=f.outputs):t=s()}),r&&this.addTapeNode(c,p,t,d,n,h),this.state.profiling&&this.state.activeProfile.kernels.push({name:c,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-o,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(p).map(e=>null!=p[e]?p[e].shape:null),outputShapes:t.map(e=>e.shape),kernelTimeMs:f.timeMs,extraInfo:f.extraInfo}),Array.isArray(u)?t:t[0]}saveTensorsForBackwardMode(e){const t=e.map(e=>this.keep(this.clone(e)));return t}getTensorsForGradient(e,t,n){const r=(0,i.vQ)(e);if(null!=r){const e=r.inputsToSave||[],a=r.outputsToSave||[];let o;r.saveAllInputs?(l.vA(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(t).map(e=>t[e])):o=e.map(e=>t[e]);const s=n.filter((e,t)=>a[t]);return o.concat(s)}return[]}makeTensor(e,t,n,r){if(null==e)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;let a=e;"string"===n&&l.Kg(e[0])&&(a=e.map(e=>c.encodeString(e)));const o=r.write(a,t,n),s=new f.qY(t,n,o,this.nextTensorId());if(this.trackTensor(s,r),"string"===n){const e=this.state.tensorInfo.get(o),t=(0,l.SL)(a);this.state.numBytes+=t-e.bytes,e.bytes=t}return s}makeTensorFromDataId(e,t,n,r){const a={dataId:e,shape:t,dtype:n=n||"float32"};return this.makeTensorFromTensorInfo(a,r)}makeTensorFromTensorInfo(e,t){const{dataId:n,shape:r,dtype:a}=e,o=new f.qY(r,a,n,this.nextTensorId());return this.trackTensor(o,t),o}makeVariable(e,t=!0,n,r){n=n||this.nextVariableId().toString(),null!=r&&r!==e.dtype&&(e=e.cast(r));const a=new f.rT(e,t,n,this.nextTensorId());if(null!=this.state.registeredVariables[a.name])throw new Error(`Variable with name ${a.name} was already registered`);return this.state.registeredVariables[a.name]=a,this.incRef(a,this.backend),a}trackTensor(e,t){this.state.numTensors++,"string"===e.dtype&&this.state.numStringTensors++;let n=0;"complex64"!==e.dtype&&"string"!==e.dtype&&(n=e.size*l.jv(e.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:n})),e instanceof f.rT||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;const t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,"string"===e.dtype&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),"complex64"!==e.dtype&&"string"!==e.dtype){const t=e.size*l.jv(e.dtype);this.state.numBytes-=t}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(const e in this.state.registeredVariables){const t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),null!=this.state.registeredVariables[e.name]&&delete this.state.registeredVariables[e.name]}memory(){const e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,null==e.reasons&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;const t=this.state.numBytes,n=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(e=>e.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(const e of this.state.activeProfile.kernels)e.kernelTimeMs=await e.kernelTimeMs,e.extraInfo=await e.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>

20&&0===this.state.kernelDepth}addTapeNode(e,t,n,r,a,o){const s={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:a},u=(0,i.vQ)(e);null!=u&&(r=u.gradFunc),null!=r&&(s.gradient=e=>(e=e.map((e,t)=>{if(null==e){const e=n[t],r=l.Ty(e.size,e.dtype);return this.makeTensor(r,e.shape,e.dtype)}return e}),r(e.length>1?e:e[0],a,o))),this.state.activeTape.push(s)}keep(e){return e.kept=!0,e}startTape(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){const t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){const t=(0,m.NB)(e),n=new Set(t.map(e=>e.id));for(let e=0;e<this.state.activeScope.track.length;e++){const t=this.state.activeScope.track[e];t.kept||n.has(t.id)||t.dispose()}const r=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(e=>{e.kept||e.scopeId!==r.id||this.track(e)})}gradients(e,t,n,r=!1){if(l.vA(t.length>0,()=>"gradients() received an empty list of xs."),null!=n&&"float32"!==n.dtype)throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);const a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));l.vA(a instanceof f.qY,()=>"The result y returned by f() must be a tensor.");const o=function(e,t,n){const r={},a={};for(let e=0;e<t.length;e++)r[t[e].id]=!0;for(let n=0;n<e.length;n++){const o=e[n],s=o.inputs;for(const e in s){const n=s[e];let i=!1;for(let e=0;e<t.length;e++)if(r[n.id]){o.outputs.forEach(e=>r[e.id]=!0),i=!0,a[o.id]=!0;break}if(i)break}}const o={};o[n.id]=!0;const s={};for(let t=e.length-1;t>=0;t--){const n=e[t],r=n.inputs;for(let e=0;e<n.outputs.length;e++)if(o[n.outputs[e].id]){for(const e in r)o[r[e].id]=!0,s[n.id]=!0;break}}const i=[];for(let t=0;t<e.length;t++){const n=e[t];if(a[n.id]&&s[n.id]){const e={};for(const t in n.inputs){const a=n.inputs[t];r[a.id]&&(e[t]=a)}const t=Object.assign({},n);t.inputs=e,t.outputs=n.outputs,i.push(t)}}return i}(this.state.activeTape,t,a);if(!r&&0===o.length&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{const e={};e[a.id]=null==n?function(e){const t=(0,l.FZ)((0,l.Ze)(e),"float32");return v.makeTensor(t,e,"float32")}(a.shape):n,function(e,t,n,r){for(let a=t.length-1;a>=0;a--){const o=t[a],s=[];if(o.outputs.forEach(t=>{const n=e[t.id];null!=n?s.push(n):s.push(null)}),null==o.gradient)throw new Error(`Cannot compute gradient: gradient function not found for ${o.kernelName}.`);const i=o.gradient(s);for(const t in o.inputs){if(!(t in i))throw new Error(`Cannot backprop through input ${t}. Available gradients found: ${Object.keys(i)}.`);const a=n(()=>i[t]());if("float32"!==a.dtype)throw new Error(`Error in gradient for op ${o.kernelName}. The gradient of input ${t} must have 'float32' dtype, but has '${a.dtype}'`);const s=o.inputs[t];if(!l.r1(a.shape,s.shape))throw new Error(`Error in gradient for op ${o.kernelName}. 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r=JSON.parse(this.LS.getItem(this.keys.weightSpecs));if(null==r)throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);t.weightSpecs=r;const a=this.LS.getItem(this.keys.modelMetadata);if(null!=a){const e=JSON.parse(a);t.format=e.format,t.generatedBy=e.generatedBy,t.convertedBy=e.convertedBy,null!=e.signature&&(t.signature=e.signature),null!=e.userDefinedMetadata&&(t.userDefinedMetadata=e.userDefinedMetadata),null!=e.modelInitializer&&(t.modelInitializer=e.modelInitializer),null!=e.trainingConfig&&(t.trainingConfig=e.trainingConfig)}const o=this.LS.getItem(this.keys.weightData);if(null==o)throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);return t.weightData=function(e){if(k){const t=Buffer.from(e,"base64");return t.buffer.slice(t.byteOffset,t.byteOffset+t.byteLength)}const t=atob(e),n=new Uint8Array(t.length);for(let e=0;e<t.length;++e)n.set([t.charCodeAt(e)],e);return 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vendor: 24,343 bytes, line 2
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vendor: 24,396 bytes, line 2
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r=t.outputTensorSize,o=t.keepAspectRatio,s=t.borderMode,i=t.outputTensorFloatRange,u=X(e),c=function(e,t){return t?{xCenter:t.xCenter*e.width,yCenter:t.yCenter*e.height,width:t.width*e.width,height:t.height*e.height,rotation:t.rotation}:{xCenter:.5*e.width,yCenter:.5*e.height,width:e.width,height:e.height,rotation:0}}(u,n),l=function(e,t,n){if(void 0===n&&(n=!1),!n)return{top:0,left:0,right:0,bottom:0};var r=t.height,a=t.width;J(t,"targetSize"),J(e,"roi");var o,s,i=r/a,u=e.height/e.width,c=0,l=0;return i>u?(o=e.width,s=e.width*i,l=(1-u/i)/2):(o=e.height/i,s=e.height,c=(1-i/u)/2),e.width=o,e.height=s,{top:l,left:c,right:c,bottom:l}}(c,r,o),p=function(e,t,n,r){var a=e.width,o=e.height,s=r?-1:1,i=Math.cos(e.rotation),u=Math.sin(e.rotation),c=e.xCenter,l=e.yCenter,p=1/t,h=1/n,d=new Array(16);return d[0]=a*i*s*p,d[1]=-o*u*p,d[2]=0,d[3]=(-.5*a*i*s+.5*o*u+c)*p,d[4]=a*u*s*h,d[5]=o*i*h,d[6]=0,d[7]=(-.5*o*i-.5*a*u*s+l)*h,d[8]=0,d[9]=0,d[10]=a*p,d[11]=0,d[12]=0,d[13]=0,d[14]=0,d[15]=1,function(e){if(16!==e.length)throw new Error("Array length must be 16 but got "+e.length);return[[e[0],e[1],e[2],e[3]],[e[4],e[5],e[6],e[7]],[e[8],e[9],e[10],e[11]],[e[12],e[13],e[14],e[15]]]}(d)}(c,u.width,u.height,!1),h=a.DZQ(function(){var t=Q(e),n=a.KtR(function(e,t,n){return J(n,"inputResolution"),[1/n.width*e[0][0]*t.width,1/n.height*e[0][1]*t.width,e[0][3]*t.width,1/n.width*e[1][0]*t.height,1/n.height*e[1][1]*t.height,e[1][3]*t.height,0,0]}(p,u,r),[1,8]),o="zero"===s?"constant":"nearest",c=a.Slp.transform(a.UG6(a.wgE(t,"float32")),n,"bilinear",o,0,[r.height,r.width]);return null!=i?function(e,t){var n=function(e,t,n,r){var a=(r-n)/255;return{scale:a,offset:n-0*a}}(0,0,t[0],t[1]);return a.DZQ(function(){return a.WQq(a.lKK(e,n.scale),n.offset)})}(c,i):c});return{imageTensor:h,padding:l,transformationMatrix:p}}function te(e){return{xCenter:e.xMin+e.width/2,yCenter:e.yMin+e.height/2,width:e.width,height:e.height}}function ne(e){var t=e.relativeKeypoints;if(t.length<=1)throw new Error("2 or more keypoints required to calculate a rect.");var n=Number.MAX_VALUE,r=Number.MAX_VALUE,a=Number.MIN_VALUE,o=Number.MIN_VALUE;return t.forEach(function(e){n=Math.min(n,e.x),a=Math.max(a,e.x),r=Math.min(r,e.y),o=Math.max(o,e.y)}),{xCenter:(n+a)/2,yCenter:(r+o)/2,width:a-n,height:o-r}}function re(e,t,n,r,a){var o="rect"===n?function(e,t,n){var r,a=e.locationData;if("boundingbox"===t)r=te(a.boundingBox);else{r=ne(a);var o=n.width,s=n.height;r.xCenter=Math.round(r.xCenter*o),r.yCenter=Math.round(r.yCenter*s),r.width=Math.round(r.width*o),r.height=Math.round(r.height*s)}return r}(e,t,r):function(e,t){var n=e.locationData;return"boundingbox"===t?te(n.relativeBoundingBox):ne(n)}(e,t);return a&&(o.rotation=function(e,t,n){var r,a=e.locationData,o=n.rotationVectorStartKeypointIndex,s=n.rotationVectorEndKeypointIndex;r=n.rotationVectorTargetAngle?n.rotationVectorTargetAngle:Math.PI*n.rotationVectorTargetAngleDegree/180;var i=a.relativeKeypoints[o].x*t.width,u=a.relativeKeypoints[o].y*t.height,c=a.relativeKeypoints[s].x*t.width,l=a.relativeKeypoints[s].y*t.height;return q(r-Math.atan2(-(l-u),c-i))}(e,r,a)),o}function ae(e,t,n){for(var r=0;r<t.length;++r){var a=t[r],o=n[e[r]];o.x=a.x,o.y=a.y}}function oe(e,t,n,r){if("string"==typeof t){if("copy"===t)for(var a=0;a<n.length;++a)r[e[a]].z=n[a].z}else{var o=function(e,t){for(var n=0,r=0;r<t.length;++r)n+=e[t[r]].z;return n/t.length}(r,t);for(a=0;a<e.length;++a)r[e[a]].z=o}}function se(e,t){for(var n=function(e){var t=[].concat.apply([],e.map(function(e){return e.indexesMapping}));if(0===t.length)throw new Error("There should be at least one landmark in indexes mapping");var n=t[0],r=t[0],a=new Set(t);a.forEach(function(e){n=Math.min(n,e),r=Math.max(r,e)});var o=a.size;if(0!==n)throw new Error("Indexes are expected to start with 0 instead of "+n);if(r+1!==o)throw new Error("Indexes should have no gaps but "+(r-o+1)+" indexes are missing");return o}(t),r=new Array(n).fill(null).map(Object),a=0;a<e.length;++a){var o=e[a],s=t[a];if(o.length!==s.indexesMapping.length)throw new Error("There are "+o.length+" refinement landmarks while mapping has "+s.indexesMapping.length);ae(s.indexesMapping,o,r),oe(s.indexesMapping,s.zRefinement,o,r)}return r}function ie(e,t){return e.map(function(e){var n=s(s({},e),{x:e.x*t.width,y:e.y*t.height});return null!=e.z&&(n.z=e.z*t.width),n})}function ue(e,t){return"none"===e?t:function(e){return 1/(1+Math.exp(-e))}(t)}function ce(e,t,n,r){return i(this,void 0,void 0,function(){var a,o,s,i,c,l,p,h;return u(this,function(u){switch(u.label){case 0:return n=n||t.flipHorizontally||!1,r=r||t.flipVertically||!1,a=e.size,o=a/t.numLandmarks,[4,e.data()];case 1:for(s=u.sent(),i=[],c=0;c<t.numLandmarks;++c)l=c*o,(h={x:0,y:0}).x=n?t.inputImageWidth-s[l]:s[l],o>1&&(h.y=r?t.inputImageHeight-s[l+1]:s[l+1]),o>2&&(h.z=s[l+2]),o>3&&(h.score=ue(t.visibilityActivation,s[l+3])),i.push(h);for(p=0;p<i.length;++p)(h=i[p]).x=h.x/t.inputImageWidth,h.y=h.y/t.inputImageHeight,h.z=h.z/t.inputImageWidth/(t.normalizeZ||1);return[2,i]}})})}function le(e,t,n){var r=e.width,a=e.height,o=e.rotation;if(null==n.rotation&&null==n.rotationDegree||(o=function(e,t){return null!=t.rotation?e+=t.rotation:null!=t.rotationDegree&&(e+=Math.PI*t.rotationDegree/180),q(e)}

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pe,he={runtime:"tfjs",maxFaces:1,refineLandmarks:!1,landmarkModelUrl:"https://tfhub.dev/mediapipe/tfjs-model/face_landmarks_detection/face_mesh/1"},de={flipHorizontal:!1,staticImageMode:!1},fe={shiftX:0,shiftY:0,scaleX:1.5,scaleY:1.5,squareLong:!0},me={outputTensorSize:{width:192,height:192},outputTensorFloatRange:[0,1],borderMode:"replicate"},ge={numLandmarks:468,inputImageWidth:192,inputImageHeight:192,visibilityActivation:"none",flipHorizontally:!1,flipVertically:!1},ye={numLandmarks:80,inputImageWidth:192,inputImageHeight:192,visibilityActivation:"none",flipHorizontally:!1,flipVertically:!1},xe={numLandmarks:71,inputImageWidth:192,inputImageHeight:192,visibilityActivation:"none",flipHorizontally:!1,flipVertically:!1},be={numLandmarks:5,inputImageWidth:192,inputImageHeight:192,visibilityActivation:"none",flipHorizontally:!1,flipVertically:!1},ve={indexesMapping:Array.from(Array(468).keys()),zRefinement:"copy"},we={indexesMapping:[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],zRefinement:"none"},Te={indexesMapping:[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],zRefinement:"none"},Se={indexesMapping:[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417],zRefinement:"none"},Ce={indexesMapping:[468,469,470,471,472],zRefinement:[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173]},ke={indexesMapping:[473,474,475,476,477],zRefinement:[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398]},Ee=function(){function e(e,t,n,r){this.detector=e,this.landmarkModel=t,this.maxFaces=n,this.withAttention=r,this.prevFaceRectsFromLandmarks=null}return e.prototype.estimateFaces=function(e,t){return i(this,void 0,void 0,function(){var n,r,o,i,c,l,p,h,m,g,y,x,b,v=this;return u(this,function(u){switch(u.label){case 0:return n=function(e){if(null==e)return s({},de);var t=s({},e);return null==t.flipHorizontal&&(t.flipHorizontal=de.flipHorizontal),null==t.staticImageMode&&(t.staticImageMode=de.staticImageMode),t}(t),null==e?(this.reset(),[2,[]]):(r=X(e),o=a.DZQ(function(){var t=a.wgE(Q(e),"float32");return n.flipHorizontal&&(t=a.r2V(a.Slp.flipLeftRight(a.UG6(t,0)),[0])),t}),i=this.prevFaceRectsFromLandmarks,n.staticImageMode||null==i||i.length<this.maxFaces?[4,this.detector.detectFaces(o,!1)]:[3,2]);case 1:return 0===(l=u.sent()).length?(this.reset(),o.dispose(),[2,[]]):(c=l.map(function(e){return v.faceDetectionFrontDetectionToRoi(e,r)}),[3,3]);case 2:c=[],u.label=3;case 3:return w=[],[c,i||[]].forEach(function(e){return e.forEach(function(e){(w=w.filter(function(t){return function(e,t){var n=Z(e),r=Z(t);if(!function(e,t){return!(e.xMax<t.xMin||t.xMax<e.xMin||e.yMax<t.yMin||t.yMax<e.yMin)}(n,r))return 0;var a=Y(function(e,t){var n=Math.max(e.xMin,t.xMin),r=Math.min(e.xMax,t.xMax),a=Math.max(e.yMin,t.yMin),o=Math.min(e.yMax,t.yMax);return{xMin:n,xMax:r,yMin:a,yMax:o,width:Math.max(r-n,0),height:Math.max(o-a,0)}}(n,r)),o=Y(n)+Y(r)-a;return o>0?a/o:0}(e,t)<=.5})).push(e)})}),p=w,[4,Promise.all(p.map(function(e){return v.faceLandmark(e,o)}))];case 4:for(h=u.sent(),m=[],this.prevFaceRectsFromLandmarks=[],g=0;g<h.length;++g)null!=(y=h[g])&&(this.prevFaceRectsFromLandmarks.push(this.faceLandmarksToRoi(y,r)),null!=(x=ie(y,r))&&x.forEach(function(e,t){var n=d.get(t);null!=n&&(e.name=n)}),b=f(x),m.push({keypoints:x,box:b.locationData.relativeBoundingBox}));return o.dispose(),[2,m]}var w})})},e.prototype.dispose=function(){this.detector.dispose(),this.landmarkModel.dispose()},e.prototype.reset=function(){this.detector.reset(),this.prevFaceRectsFromLandmarks=null},e.prototype.faceDetectionFrontDetectionToRoi=function(e,t){return le(re(e,"boundingbox","normRect",t,{rotationVectorStartKeypointIndex:0,rotationVectorEndKeypointIndex:1,rotationVectorTargetAngleDegree:0}),t,fe)},e.prototype.faceLandmark=function(e,t){return i(this,void 0,void 0,function(){var n,r,o,i,c,l,p;return u(this,function(u){switch(u.label){case 0:return n=ee(t,me,e).imageTensor,r=["output_faceflag"].concat(this.withAttention?["output_mesh_identity","output_lips","Identity_6:0","Identity_1:0","Identity_2:0","Identity_5:0"]:["output_mesh"]),o=this.landmarkModel.execute(n,r),i=o[0],c=o.slice(1),[4,i.data()];

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2`Error in conv2dDerInput: inShape must be length 4, but got length ${c.length}.`),d.vA(4===l.rank,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),d.vA(4===n.rank,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);const h="NHWC"===i?c[3]:c[1],f="NHWC"===i?l.shape[3]:l.shape[1];d.vA(h===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${h}) must match input depth for filter ${n.shape[2]}.`),d.vA(f===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${f}) must match output depth for filter ${n.shape[3]}.`),k.s_("conv2dDerInput",s,u);const m={dy:l,filter:n},g={strides:r,pad:s,dataFormat:i,dimRoundingMode:u,inputShape:c},y=a.T2.runKernel(o.jfg,m,g);return p?(0,E.t)(y,[y.shape[1],y.shape[2],y.shape[3]]):y}});const re=(0,i.op)({conv2dTranspose_:function(e,t,n,r,a,o){const i=(0,s.YT)(e,"x","conv2dTranspose"),u=(0,s.YT)(t,"filter","conv2dTranspose");return ne(n,i,u,r,a,"NHWC",o)}});const ae=(0,i.op)({conv3d_:function(e,t,n,r,i="NDHWC",u=[1,1,1]){const c=(0,s.YT)(e,"x","conv3d"),l=(0,s.YT)(t,"filter","conv3d");let p=c,h=!1;4===c.rank&&(h=!0,p=(0,E.t)(c,[1,c.shape[0],c.shape[1],c.shape[2],c.shape[3]])),d.vA(5===p.rank,()=>`Error in conv3d: input must be rank 5, but got rank ${p.rank}.`),d.vA(5===l.rank,()=>`Error in conv3d: filter must be rank 5, but got rank ${l.rank}.`),d.vA(p.shape[4]===l.shape[3],()=>`Error in conv3d: depth of input (${p.shape[4]}) must match input depth for filter ${l.shape[3]}.`),d.vA((0,k.G0)(n,u),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${u}'`),d.vA("NDHWC"===i,()=>`Error in conv3d: got dataFormat of ${i} but only NDHWC is currently supported.`);const f={x:p,filter:l},m={strides:n,pad:r,dataFormat:i,dilations:u},g=a.T2.runKernel(o.A1h,f,m);return h?(0,E.t)(g,[g.shape[1],g.shape[2],g.shape[3],g.shape[4]]):g}});const oe=(0,i.op)({conv3DBackpropInput_:function(e,t,n,r,s){d.vA(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let i=e,u=t,c=!1;4===t.rank&&(c=!0,u=(0,E.t)(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),i=[1,e[0],e[1],e[2],e[3]]);const l=i[4],p=u.shape[4];d.vA(5===i.length,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${i.length}.`),d.vA(5===u.rank,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${u.rank}`),d.vA(5===n.rank,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),d.vA(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),d.vA(p===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${p}) must match output depth for filter ${n.shape[4]}.`);const h={dy:u,filter:n},f={pad:s,strides:r,inputShape:i},m=a.T2.runKernel(o.gC7,h,f);return c?(0,E.t)(m,[m.shape[1],m.shape[2],m.shape[3],m.shape[4]]):m}});const se=(0,i.op)({conv3dTranspose_:function(e,t,n,r,a){const o=(0,s.YT)(e,"x","conv3dTranspose"),i=(0,s.YT)(t,"filter","conv3dTranspose");return oe(n,o,i,r,a)}});const ie=(0,i.op)({cos_:function(e){const t={x:(0,s.YT)(e,"x","cos","float32")};return a.T2.runKernel(o.Mn0,t)}});const ue=(0,i.op)({cosh_:function(e){const t={x:(0,s.YT)(e,"x","cosh","float32")};return a.T2.runKernel(o.MnK,t)}});const ce=(0,i.op)({cumprod_:function(e,t=0,n=!1,r=!1){const i={x:(0,s.YT)(e,"x","cumprod")},u={axis:t,exclusive:n,reverse:r};return a.T2.runKernel(o.jj_,i,u)}});const le=(0,i.op)({cumsum_:function(e,t=0,n=!1,r=!1){const i={x:(0,s.YT)(e,"x","cumsum")},u={axis:t,exclusive:n,reverse:r};return a.T2.runKernel(o.nY8,i,u)}});const pe=(0,i.op)({denseBincount_:function(e,t,n,r=!1){const i=(0,s.YT)(e,"x","denseBincount"),u=(0,s.YT)(t,"weights","denseBincount");d.vA("int32"===i.dtype,()=>`Error in denseBincount: input dtype must be int32, but got ${i.dtype}`),d.vA(i.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${i.rank}.`),d.vA(n>=0,()=>`size must be non-negative, but got ${n}.`),d.vA(u.size===i.size||0===u.size,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${i.shape}, weights shape: ${u.shape}.`);const c={x:i,weights:u},l={size:n,binaryOutput:r};return a.T2.runKernel(o.wNW,c,l)}});const he=(0,i.op)({depthToSpace_:function(e,t,n="NHWC"){const r=(0,s.YT)(e,"x","depthToSpace","float32"),i="NHWC"===n?r.shape[1]:r.shape[2],u="NHWC"===n?r.shape[2]:r.shape[3],c="NHWC"===n?r.shape[3]:r.shape[1];d.vA(t>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`),d.vA(i*t>=0,()=>

2`Negative dimension size caused by overflow when multiplying\n    ${i} and ${t}  for depthToSpace with input shape\n    ${r.shape}`),d.vA(u*t>=0,()=>`Negative dimension size caused by overflow when multiplying\n    ${u} and ${t} for depthToSpace with input shape\n        ${r.shape}`),d.vA(c%(t*t)===0,()=>`Dimension size must be evenly divisible by ${t*t} but is ${c} for depthToSpace with input shape ${r.shape}`);const l={x:r},p={blockSize:t,dataFormat:n};return a.T2.runKernel(o.TMz,l,p)}});const de=(0,i.op)({depthwiseConv2d_:function(e,t,n,r,i="NHWC",u=[1,1],c){const l=(0,s.YT)(e,"x","depthwiseConv2d","float32"),p=(0,s.YT)(t,"filter","depthwiseConv2d","float32");let h=l,f=!1;3===l.rank&&(f=!0,h=(0,E.t)(l,[1,l.shape[0],l.shape[1],l.shape[2]])),d.vA(4===h.rank,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${h.rank}.`),d.vA(4===p.rank,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${p.rank}.`);const 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p=c,h=!1;3===c.rank&&(p=(0,E.t)(c,[1,c.shape[0],c.shape[1],c.shape[2]]),h=!0);const f={x:p,filter:l},m={strides:n,pad:r,dilations:i},g=a.T2.runKernel(o.jxD,f,m);return h?(0,E.t)(g,[g.shape[1],g.shape[2],g.shape[3]]):g}});const ge=(0,i.op)({floorDiv_:function(e,t){let n=(0,s.YT)(e,"a","floorDiv"),r=(0,s.YT)(t,"b","floorDiv");[n,r]=(0,p.h0)(n,r);const i={a:n,b:r};return a.T2.runKernel(o.ElG,i)}});const ye=(0,i.op)({div_:function(e,t){let n=(0,s.YT)(e,"a","div"),r=(0,s.YT)(t,"b","div");if([n,r]=(0,p.h0)(n,r),"int32"===n.dtype&&"int32"===r.dtype)return ge(n,r);const i={a:n,b:r};return a.T2.runKernel(o.sDr,i,{})}});var xe=n(62198);const be=(0,i.op)({equal_:function(e,t){let n=(0,s.YT)(e,"a","equal","string_or_numeric"),r=(0,s.YT)(t,"b","equal","string_or_numeric");[n,r]=(0,p.h0)(n,r),(0,xe.assertAndGetBroadcastShape)(n.shape,r.shape);const i={a:n,b:r};return a.T2.runKernel(o.BRl,i)}});const ve=(0,i.op)({where_:function(e,t,n){const 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n=(0,s.YT)(e,"a","lessEqual","string_or_numeric"),r=(0,s.YT)(t,"b","lessEqual","string_or_numeric");[n,r]=(0,p.h0)(n,r),(0,xe.assertAndGetBroadcastShape)(n.shape,r.shape);const i={a:n,b:r};return a.T2.runKernel(o.CwD,i)}});function et(e,t,n){if(n<=0)throw new Error("The number of values should be positive.");const r={start:e,stop:t,num:n};return a.T2.runKernel(o.mnI,{},r)}const tt=(0,i.op)({localResponseNormalization_:function(e,t=5,n=1,r=1,i=.5){const u=(0,s.YT)(e,"x","localResponseNormalization");d.vA(4===u.rank||3===u.rank,()=>`Error in localResponseNormalization: x must be rank 3 or 4 but got\n               rank ${u.rank}.`),d.vA(d.E6(t),()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`);let c=u,l=!1;3===u.rank&&(l=!0,c=(0,E.t)(u,[1,u.shape[0],u.shape[1],u.shape[2]]));const p={x:c},h={depthRadius:t,bias:n,alpha:r,beta:i},f=a.T2.runKernel(o.jM4,p,h);return l?(0,E.t)(f,[f.shape[1],f.shape[2],f.shape[3]]):f}});const nt=(0,i.op)({log_:function(e){const t={x:(0,s.YT)(e,"x","log","float32")};return a.T2.runKernel(o.tG8,t)}});const rt=(0,i.op)({log1p_:function(e){const t={x:(0,s.YT)(e,"x","log1p")};return a.T2.runKernel(o.Cg$,t)}});var at=n(21722);function ot(e){return a.T2.customGrad(e)}const st=(0,i.op)({neg_:function(e){const t={x:(0,s.YT)(e,"x","neg")};return a.T2.runKernel(o.l0G,t)}});const it=(0,i.op)({softplus_:function(e){const t={x:(0,s.YT)(e,"x","softplus")};return a.T2.runKernel(o.Fin,t)}});const ut=(0,i.op)({logSigmoid_:function(e){const t=(0,s.YT)(e,"x","logSigmoid");return ot(e=>({value:st(it(st(e))),gradFunc:t=>(0,_.l)(t,(0,O.r)(st(e)))}))(t)}});const ct=(0,i.op)({sub_:function(e,t){let n=(0,s.YT)(e,"a","sub"),r=(0,s.YT)(t,"b","sub");[n,r]=(0,p.h0)(n,r);const i={a:n,b:r};return a.T2.runKernel(o.PbM,i)}});const lt=(0,i.op)({logSoftmax_:function(e,t=-1){const n=(0,s.YT)(e,"logits","logSoftmax");if(-1===t&&(t=n.rank-1),t!==n.rank-1)throw Error(`Log Softmax along a non-last dimension is not 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2return e!==t&&t.dispose(),r};const nr=async function(e,t,n){const r=(0,s.YT)(e,"tensor","boolMask"),a=(0,s.YT)(t,"mask","boolMask","bool"),o=null==n?0:n,i=a.rank,u=r.shape;d.vA(i>0,()=>"mask cannot be scalar"),d.O3(u.slice(o,o+i),a.shape,"mask's shape must match the first K dimensions of tensor's shape,");let c=1;for(let e=o;e<o+i;e++)c*=u[e];const l=u.slice(0,o).concat([c],u.slice(o+i)),p=(0,E.t)(r,l),h=(0,E.t)(a,[-1]),f=await tr(h),m=Fn(f,[1]),g=Ge(p,m,o);return e!==r&&r.dispose(),t!==a&&a.dispose(),m.dispose(),p.dispose(),h.dispose(),f.dispose(),g};var rr=n(35287);const ar=(0,i.op)({transpose_:function(e,t,n){const r=(0,s.YT)(e,"x","transpose");if(null==t&&(t=r.shape.map((e,t)=>t).reverse()),d.vA(r.rank===t.length,()=>`Error in transpose: rank of input ${r.rank} must match length of perm ${t}.`),t.forEach(e=>{d.vA(e>=0&&e<r.rank,()=>"All entries in 'perm' must be between 0 and "+(r.rank-1)+` but got ${t}`)}),r.rank<=1)return r.clone();const i={x:r},u={perm:t};return"complex64"===r.dtype?(0,rr.DZ)(()=>{let e=on(r),t=He(r);return e=a.T2.runKernel(o.wx0,{x:e},u),t=a.T2.runKernel(o.wx0,{x:t},u),n&&(t=st(t)),(0,Z.f)(e,t)}):a.T2.runKernel(o.wx0,i,u)}});const or=(0,i.op)({movingAverage_:function(e,t,n,r,a=!0){const o=(0,s.YT)(e,"v","movingAverage"),i=(0,s.YT)(t,"x","movingAverage"),u=(0,s.YT)(n,"decay","movingAverage");(0,p.rt)(o,i),d.vA(d.r1(o.shape,i.shape),()=>"Shape mismatch in v and x");const c=(0,Re.d)(1),l=ct(c,u);let f=(0,_.l)(ct(i,o),l);if(a){d.vA(null!=r,()=>"When using zeroDebias: true, step is required.");const e=(0,s.YT)(r,"step","movingAverage");f=ye(f,ct(c,Ae(u,e)))}return h(o,f)}});var sr=n(26170);const ir=(0,i.op)({scatterND_:function(e,t,n){const r=(0,s.YT)(e,"indices","scatterND","int32"),i=(0,s.YT)(t,"updates","scatterND");sr.TT(i,r,n);const u={indices:r,updates:i},c={shape:n};return a.T2.runKernel(o.pJc,u,c)}});const ur=(0,i.op)({sparseToDense_:function(e,t,n,r=0){const i=(0,s.YT)(e,"sparseIndices","sparseToDense","int32"),u=(0,s.YT)(t,"sparseValues","sparseToDense","string_or_numeric"),c=(0,s.YT)(r,"defaultValue","sparseToDense",u.dtype);!function(e,t,n,r){if("int32"!==e.dtype)throw new Error(`tf.sparseToDense() expects the indices to be int32 type, but the dtype was ${e.dtype}.`);if(e.rank>2)throw new Error(`sparseIndices should be a scalar, vector, or matrix, but got shape ${e.shape}.`);const a=e.rank>0?e.shape[0]:1,o=e.rank>1?e.shape[1]:1;if(n.length!==o)throw new Error(`outputShape has incorrect number of elements:, ${n.length}, should be: ${o}.`);const s=t.size;if(0!==t.rank&&(1!==t.rank||s!==a))throw new Error(`sparseValues has incorrect shape ${t.shape}, should be [] or [${a}]`);if(t.dtype!==r.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}(i,u,n,c);const l={sparseIndices:i,sparseValues:u,defaultValue:c},p={outputShape:n};return a.T2.runKernel(o.jgd,l,p)}});const cr=(0,i.op)({gatherND_:function(e,t){const n=(0,s.YT)(t,"indices","gatherND","int32"),r={params:(0,s.YT)(e,"x","gatherND","string_or_numeric"),indices:n};return a.T2.runKernel(o.O4G,r)}});const lr=(0,i.op)({dropout_:function(e,t,n,r){const a=(0,s.YT)(e,"x","dropout");if(d.vA("float32"===a.dtype,()=>`x has to be a floating point tensor since it's going to be scaled, but got a ${a.dtype} tensor instead.`),d.vA(t>=0&&t<1,()=>`rate must be a float in the range [0, 1), but got ${t}.`),0===t)return e instanceof at.qY?a.clone():a;const o=function(e,t){if(null==t)return e.shape.slice();if(d.r1(e.shape,t))return t;if(e.shape.length===t.length){const n=[];for(let r=0;r<e.shape.length;r++)null==t[r]&&null!=e.shape[r]?n.push(e.shape[r]):n.push(t[r]);return n}return t}(a,n),i=1-t,u=ye(We(h(rn(o,0,1,"float32",r),i)),i);return(0,_.l)(a,u)}});function pr(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function hr(e,t,n){const r=1-e%2,a=new Float32Array(e);for(let o=0;o<e;++o){const s=2*Math.PI*o/(e+r-1);a[o]=t-n*Math.cos(s)}return zn(a,"float32")}const dr=async function(e,t,n=1){const r=(0,s.YT)(e,"predictions","inTopK"),a=(0,s.YT)(t,"targets","inTopK");(0,d.vA)(r.rank>1,()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${r.rank}`),(0,d.vA)(r.rank-1===a.rank,()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${r.rank} and targets rank ${a.rank}`),(0,d.O3)(r.shape.slice(0,r.shape.length-1),a.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");const o=r.shape[r.shape.length-1];(0,d.vA)(n>0&&n<=o,()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${o}), but got ${n}`);const i=await r.data(),u=await a.data(),[c,l]=[i.length/o,o],p=(0,d.ce)("bool",c);for(let e=0;e<c;e++){const t=e*l,r=i.subarray(t,t+l),a=[];for(let e=0;e<r.length;e++)a.push({value:r[e],index:e});a.sort((e,t)=>

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2oncat([x,b]),k=n?(0,E.t)(f,[T,g,x]):(0,E.t)(f,[T,x,g]),$=r?(0,E.t)(m,[S,b,y]):(0,E.t)(m,[S,y,b]);let N,I;null!=i&&(N=(0,s.YT)(i,"bias","fused matMul"),[N]=(0,p.h0)(N,f),xe.assertAndGetBroadcastShape(C,N.shape)),null!=c&&(I=(0,s.YT)(c,"prelu weights","fused matMul"));const A=(e,t)=>{const[a,o,s,c]=t,l=(0,mr.XB)((0,E.t)(e,s.shape),s,u);let p,h;if(n||r?!n&&r?(p=R(l,o,!1,!1),h=R(l,a,!0,!1)):n&&!r?(p=R(o,l,!1,!0),h=R(a,l,!1,!1)):(p=R(o,l,!0,!0),h=R(l,a,!0,!0)):(p=R(l,o,!1,!0),h=R(a,l,!0,!1)),null!=i){return[p,h,(0,mr.Do)(c,l)]}return[p,h]},_={a:k,b:$,bias:N,preluActivationWeights:I},O={transposeA:n,transposeB:r,activation:u,leakyreluAlpha:l};if(null==i){const e=ot((e,t,n)=>{const r=a.T2.runKernel(o.Dr,_,O);return n([e,t,r]),{value:(0,E.t)(r,C),gradFunc:A}});return e(k,$)}{const e=ot((e,t,n,r)=>{const s=a.T2.runKernel(o.Dr,_,O);return r([e,t,s,n]),{value:(0,E.t)(s,C),gradFunc:A}});return e(k,$,N)}}});const wr=(0,i.op)({hammingWindow_:function(e){return hr(e,.54,.46)}});const Tr=(0,i.op)({hannWindow_:function(e){return hr(e,.5,.5)}});const Sr=(0,i.op)({frame_:function(e,t,n,r=!1,a=0){let o=0;const s=[];for(;o+t<=e.size;)s.push(F(e,o,t)),o+=n;if(r)for(;o<e.size;){const r=o+t-e.size,i=A([F(e,o,t-r),H([r],a)]);s.push(i),o+=n}return 0===s.length?Un([],[0,t]):(0,E.t)(A(s),[s.length,t])}});const Cr=(0,i.op)({stft_:function(e,t,n,r,a=Tr){null==r&&(r=pr(t));const o=Sr(e,t,n),s=(0,_.l)(o,a(t));return _n(s,r)}});const kr=(0,i.op)({cropAndResize_:function(e,t,n,r,i="bilinear",u=0){const c=(0,s.YT)(e,"image","cropAndResize"),l=(0,s.YT)(t,"boxes","cropAndResize","float32"),p=(0,s.YT)(n,"boxInd","cropAndResize","int32"),h=l.shape[0];d.vA(4===c.rank,()=>`Error in cropAndResize: image must be rank 4,but got rank ${c.rank}.`),d.vA(2===l.rank&&4===l.shape[1],()=>`Error in cropAndResize: boxes must be have size [${h},4] but had shape ${l.shape}.`),d.vA(1===p.rank&&p.shape[0]===h,()=>`Error in cropAndResize: boxInd must be have size [${h}] but had shape ${l.shape}.`),d.vA(2===r.length,()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${r.length}.`),d.vA(r[0]>=1&&r[1]>=1,()=>`cropSize must be atleast [1,1], but was ${r}`),d.vA("bilinear"===i||"nearest"===i,()=>`method must be bilinear or nearest, but was ${i}`);const f={image:c,boxes:l,boxInd:p},m={method:i,extrapolationValue:u,cropSize:r};return a.T2.runKernel(o.MRQ,f,m)}});const Er=(0,i.op)({flipLeftRight_:function(e){const t=(0,s.YT)(e,"image","flipLeftRight","float32");d.vA(4===t.rank,()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`);const n={image:t};return a.T2.runKernel(o.BxF,n,{})}});const $r=(0,i.op)({grayscaleToRGB_:function(e){const t=(0,s.YT)(e,"image","grayscaleToRGB"),n=t.rank-1,r=t.shape[n];d.vA(t.rank>=2,()=>`Error in grayscaleToRGB: images must be at least rank 2, but got rank ${t.rank}.`),d.vA(1===r,()=>`Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${r}.`);const a=new Array(t.rank);return a.fill(1,0,n),a[n]=3,ze(t,a)}});const Nr=(0,i.op)({rotateWithOffset_:function(e,t,n=0,r=.5){const i=(0,s.YT)(e,"image","rotateWithOffset","float32");d.vA(4===i.rank,()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${i.rank}.`);const u={image:i},c={radians:t,fillValue:n,center:r};return a.T2.runKernel(o.BK4,u,c)}});function Ir(e,t,n,r,a,o){null==r&&(r=.5),null==a&&(a=Number.NEGATIVE_INFINITY),null==o&&(o=0);const s=e.shape[0];return n=Math.min(n,s),d.vA(0<=r&&r<=1,()=>`iouThreshold must be in [0, 1], but was '${r}'`),d.vA(2===e.rank,()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`),d.vA(4===e.shape[1],()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`),d.vA(1===t.rank,()=>"scores must be a 1D tensor"),d.vA(t.shape[0]===s,()=>`scores has incompatible shape with boxes. Expected ${s}, but was ${t.shape[0]}`),d.vA(0<=o&&o<=1,()=>`softNmsSigma must be in [0, 1], but was '${o}'`),{maxOutputSize:n,iouThreshold:r,scoreThreshold:a,softNmsSigma:o}}const Ar=(0,i.op)({nonMaxSuppression_:function(e,t,n,r=.5,i=Number.NEGATIVE_INFINITY){const u=(0,s.YT)(e,"boxes","nonMaxSuppression","float32"),c=(0,s.YT)(t,"scores","nonMaxSuppression","float32"),l=Ir(u,c,n,r,i),p={maxOutputSize:n=l.maxOutputSize,iouThreshold:r=l.iouThreshold,scoreThreshold:i=l.scoreThreshold};return a.T2.runKernel(o.SDM,{boxes:u,scores:c}

2,p)}});var Rr=n(43303);const _r=async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){const o=(0,s.YT)(e,"boxes","nonMaxSuppressionAsync"),i=(0,s.YT)(t,"scores","nonMaxSuppressionAsync"),u=Ir(o,i,n,r,a);n=u.maxOutputSize,r=u.iouThreshold,a=u.scoreThreshold;const c=await Promise.all([o.data(),i.data()]),l=c[0],p=c[1],{selectedIndices:h}=(0,Rr.c7)(l,p,n,r,a);return o!==e&&o.dispose(),i!==t&&i.dispose(),zn(h,"int32")};const Or=(0,i.op)({nonMaxSuppressionWithScore_:function(e,t,n,r=.5,i=Number.NEGATIVE_INFINITY,u=0){const c=(0,s.YT)(e,"boxes","nonMaxSuppression"),l=(0,s.YT)(t,"scores","nonMaxSuppression"),p=Ir(c,l,n,r,i,u),h={boxes:c,scores:l},d={maxOutputSize:n=p.maxOutputSize,iouThreshold:r=p.iouThreshold,scoreThreshold:i=p.scoreThreshold,softNmsSigma:u=p.softNmsSigma},f=a.T2.runKernel(o.e0f,h,d);return{selectedIndices:f[0],selectedScores:f[1]}}});const Fr=async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,o=0){const i=(0,s.YT)(e,"boxes","nonMaxSuppressionAsync"),u=(0,s.YT)(t,"scores","nonMaxSuppressionAsync"),c=Ir(i,u,n,r,a,o);n=c.maxOutputSize,r=c.iouThreshold,a=c.scoreThreshold,o=c.softNmsSigma;const l=await Promise.all([i.data(),u.data()]),p=l[0],h=l[1],{selectedIndices:d,selectedScores:f}=(0,Rr.ut)(p,h,n,r,a,o);return i!==e&&i.dispose(),u!==t&&u.dispose(),{selectedIndices:zn(d,"int32"),selectedScores:zn(f)}};const Dr=(0,i.op)({nonMaxSuppressionPadded_:function(e,t,n,r=.5,i=Number.NEGATIVE_INFINITY,u=!1){const c=(0,s.YT)(e,"boxes","nonMaxSuppression"),l=(0,s.YT)(t,"scores","nonMaxSuppression"),p=Ir(c,l,n,r,i,null),h={boxes:c,scores:l},d={maxOutputSize:p.maxOutputSize,iouThreshold:p.iouThreshold,scoreThreshold:p.scoreThreshold,padToMaxOutputSize:u},f=a.T2.runKernel(o.Zl4,h,d);return{selectedIndices:f[0],validOutputs:f[1]}}});const Lr=async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,o=!1){const i=(0,s.YT)(e,"boxes","nonMaxSuppressionAsync"),u=(0,s.YT)(t,"scores","nonMaxSuppressionAsync"),c=Ir(i,u,n,r,a,null),l=c.maxOutputSize,p=c.iouThreshold,h=c.scoreThreshold,[d,f]=await Promise.all([i.data(),u.data()]),{selectedIndices:m,validOutputs:g}=(0,Rr.ZS)(d,f,l,p,h,o);return i!==e&&i.dispose(),u!==t&&u.dispose(),{selectedIndices:zn(m,"int32"),validOutputs:(0,Re.d)(g,"int32")}};const Mr=(0,i.op)({resizeBilinear_:function(e,t,n=!1,r=!1){const i=(0,s.YT)(e,"images","resizeBilinear");d.vA(3===i.rank||4===i.rank,()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${i.rank}.`),d.vA(2===t.length,()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`),d.vA(!1===r||!1===n,()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false.");let u=i,c=!1;3===i.rank&&(c=!0,u=(0,E.t)(i,[1,i.shape[0],i.shape[1],i.shape[2]]));const[]=t,l={images:u},p={alignCorners:n,halfPixelCenters:r,size:t},h=a.T2.runKernel(o.hgw,l,p);return c?(0,E.t)(h,[h.shape[1],h.shape[2],h.shape[3]]):h}});const Pr=(0,i.op)({resizeNearestNeighbor_:function(e,t,n=!1,r=!1){const i=(0,s.YT)(e,"images","resizeNearestNeighbor");d.vA(3===i.rank||4===i.rank,()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${i.rank}.`),d.vA(2===t.length,()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`),d.vA("float32"===i.dtype||"int32"===i.dtype,()=>"`images` must have `int32` or `float32` as dtype"),d.vA(!1===r||!1===n,()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false.");let u=i,c=!1;3===i.rank&&(c=!0,u=(0,E.t)(i,[1,i.shape[0],i.shape[1],i.shape[2]]));const[]=t,l={images:u},p={alignCorners:n,halfPixelCenters:r,size:t},h=a.T2.runKernel(o.jOE,l,p);return c?(0,E.t)(h,[h.shape[1],h.shape[2],h.shape[3]]):h}});const Br=(0,i.op)({threshold_:function(e,t="binary",n=!1,r=.5){const a=(0,s.YT)(e,"image","threshold"),o=a.shape[0]*a.shape[1];let i,u,c,l,p=(0,_.l)(zn([r]),255);if(d.vA(3===a.rank,()=>`Error in threshold: image must be rank 3,but got rank ${a.rank}.`),d.vA(3===a.shape[2]||1===a.shape[2],()=>`Error in threshold: image color channel must be equal to 3 or 1but got ${a.shape[2]}.`),d.vA("int32"===a.dtype||"float32"===a.dtype,()=>`Error in dtype: image dtype must be int32 or float32,but got dtype ${a.dtype}.`),d.vA("otsu"===t||"binary"===t,()=>`Method must be binary or otsu, but was ${t}`),3===a.shape[2]){[i,u,c]=Rn(a,[1,1,1],-1);const e=(0,_.l)(i,.2989),t=(0,_.l)(u,.587),n=(0,_.l)(c,.114);l=h(h(e,t),n)}else l=e;if("otsu"===t){p=function(e,t){let n,r,a,o,s,i,u=zn([-1]),c=zn([0]),l=zn([0]);for(let p=0;p<e.size-1;p++){n=F(e,0,p+1),r=F(e,p+1),s=ye((0,Fe.c)(n),t),i=ye((0,Fe.c)(r),t);const d=(0,Fe.c)((0,_.l)(n,an(0,n.size)));a=ye(d,(0,Fe.c)(n));const f=H(r.shape,n.size),m=h(an(0,r.size),f),g=(0,_.l)(r,m);o=ye((0,Fe.c)(g),(0,Fe.c)(r));const y=ct(a,o),x=ct(a,o),b=(0,_.l)(s,i);l=(0,_.l)((0,_.l)(b,y),x);const v=je(l,c);c=ve(v,l,c),u=ve(v,zn([p]),u)}return u}(U((0,C.w)(mn(l),"int32"),(0,Bn.O)([]),256),o)}const f=n?Je(l,p):je(l,p);return(0,C.w)((0,_.l)(f,255),"int32")}});const Vr=(0,i.op)({transform_:function(e,t,n="nearest",r="constant",i=0,u){const c=(0,s.YT)(e,"image","transform","float32"),l=(0,s.YT)(t,"transforms","transform","float32");d.vA(4===c.rank,()=>`Error in transform: image must be rank 4,but got rank ${c.rank}.`),d.vA(2===l.rank&&(l.shape[0]===c.shape[0]||1===l.shape[0])&&8===l.shape[1],()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),d.vA(null==u||2===u.length,()=>`Error in transform: outputShape must be [height, width] or null, but got ${u}.`);const p={image:c,transforms:l},h={interpolation:n,fillMode:r,fillValue:i,outputShape:u};return a.T2.runKernel(o.dLy,p,h)}});const zr=(0,i.op)({bandPart_:function(e,t,n){(0,d.vA)(t%1==0,()=>`bandPart(): numLower must be an integer, got ${t}.`),(0,d.vA)(n%1==0,()=>`bandPart(): numUpper must be an integer, got ${n}.`);const r=(0,s.YT)(e,"a","bandPart");(0,d.vA)(r.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${r.rank}.`);const a=r.shape,[o,i]=r.shape.slice(-2);if(!(t<=o))throw new Error(`bandPart(): numLower (${t}) must not be greater than the number of rows (${o}).`);if(!(n<=i))throw new Error(`bandPart(): numUpper (${n}) must not be greater than the number of columns (${i}).`);t<0&&(t=o),n<0&&(n=i);const u=(0,E.t)(an(0,o,1,"int32"),[-1,1]),c=an(0,i,1,"int32"),l=ct(u,c),p=ht(Je(l,(0,Re.d)(+t,"int32")),Ke(l,(0,Re.d)(-n,"int32"))),h=Ct([o,i],r.dtype);return(0,E.t)(Dn(qn((0,E.t)(r,[-1,o,i])).map(e=>ve(p,e,h))),a)}});const Ur=(0,i.op)({gramSchmidt_:function(e){let t;if(Array.isArray(e)){t=!1,(0,d.vA)(null!=e&&e.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");const n=e[0].shape[0];for(let t=1;t<e.length;++t)(0,d.vA)(e[t].shape[0]===n,()=>

2`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[t].shape[0]} vs. ${n})`)}else t=!0,e=Rn(e,e.shape[0],0).map(e=>Fn(e,[0]));(0,d.vA)(e.length<=e[0].shape[0],()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`);const n=[],r=e;for(let t=0;t<e.length;++t)n.push(a.T2.tidy(()=>{let e=r[t];if(t>0)for(let r=0;r<t;++r){const t=(0,_.l)((0,Fe.c)((0,_.l)(n[r],e)),n[r]);e=ct(e,t)}return ye(e,Le(e,"euclidean"))}));return t?Dn(n,0):n}});function Wr(e,t=!1){return a.T2.tidy(()=>{(0,d.vA)(2===e.shape.length,()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`);const n=e.shape[0],r=e.shape[1];let o=Ue(n),s=(0,I.o)(e);const i=Un([[1]],[1,1]);let u=(0,I.o)(i);const c=n>=r?r:n;for(let e=0;e<c;++e){const t=s,c=u,l=o;[u,s,o]=a.T2.tidy(()=>{const t=F(s,[e,e],[n-e,1]),a=Le(t),c=F(s,[e,e],[1,1]),l=ve(je(c,0),Un([[-1]]),Un([[1]])),p=ct(c,(0,_.l)(l,a)),h=ye(t,p);u=1===h.shape[0]?(0,I.o)(i):A([i,F(h,[1,0],[h.shape[0]-1,h.shape[1]])],0);const d=st(ye(R(l,p),a)),f=F(s,[e,0],[n-e,r]),m=(0,_.l)(d,u),g=ar(u);if(0===e)s=ct(f,R(m,R(g,f)));else{const t=ct(f,R(m,R(g,f)));s=A([F(s,[0,0],[e,r]),t],0)}const y=ar(m),x=F(o,[0,e],[n,o.shape[1]-e]);if(0===e)o=ct(x,R(R(x,u),y));else{const t=ct(x,R(R(x,u),y));o=A([F(o,[0,0],[n,e]),t],1)}return[u,s,o]}),(0,rr.AS)([t,c,l])}return!t&&n>r&&(o=F(o,[0,0],[n,r]),s=F(s,[0,0],[r,r])),[o,s]})}const Gr=(0,i.op)({qr_:function(e,t=!1){if((0,d.vA)(e.rank>=2,()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`),2===e.rank)return Wr(e,t);{const n=e.shape.slice(0,e.shape.length-2).reduce((e,t)=>e*t),r=qn((0,E.t)(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),a=[],o=[];r.forEach(e=>{const[n,r]=Wr(e,t);a.push(n),o.push(r)});return[(0,E.t)(Dn(a,0),e.shape),(0,E.t)(Dn(o,0),e.shape)]}}});var jr;!function(e){e[e.NONE=0]="NONE",e[e.MEAN=1]="MEAN",e[e.SUM=2]="SUM",e[e.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS"}(jr||(jr={}));const Kr=(0,i.op)({computeWeightedLoss_:function(e,t,n=jr.SUM_BY_NONZERO_WEIGHTS){const r=(0,s.YT)(e,"losses","computeWeightedLoss");let a=null;null!=t&&(a=(0,s.YT)(t,"weights","computeWeightedLoss"));const o=null==a?r:(0,_.l)(r,a);if(n===jr.NONE)return o;if(n===jr.SUM)return(0,Fe.c)(o);if(n===jr.MEAN){if(null==a)return St(o);{const e=r.size/a.size,t=ye((0,Fe.c)(o),(0,Fe.c)(a));return e>1?ye(t,(0,Re.d)(e)):t}}if(n===jr.SUM_BY_NONZERO_WEIGHTS){if(null==a)return ye((0,Fe.c)(o),(0,Re.d)(r.size));{const e=(0,_.l)(a,kt(r.shape)),t=(0,C.w)((0,Fe.c)(Ot(e,(0,Re.d)(0))),"float32");return ye((0,Fe.c)(o),t)}}throw Error(`Unknown reduction: ${n}`)}});const Hr=(0,i.op)({absoluteDifference_:function(e,t,n,r=jr.SUM_BY_NONZERO_WEIGHTS){const a=(0,s.YT)(e,"labels","absoluteDifference"),o=(0,s.YT)(t,"predictions","absoluteDifference");let i=null;null!=n&&(i=(0,s.YT)(n,"weights","absoluteDifference")),(0,d.O3)(a.shape,o.shape,"Error in absoluteDifference: ");const c=u(ct(a,o));return Kr(c,i,r)}});const Yr=(0,i.op)({cosineDistance_:function(e,t,n,r,a=jr.SUM_BY_NONZERO_WEIGHTS){const o=(0,s.YT)(e,"labels","cosineDistance"),i=(0,s.YT)(t,"predictions","cosineDistance");let u=null;null!=r&&(u=(0,s.YT)(r,"weights","cosineDistance")),(0,d.O3)(o.shape,i.shape,"Error in cosineDistance: ");const c=(0,Re.d)(1),l=ct(c,(0,Fe.c)((0,_.l)(o,i),n,!0));return Kr(l,u,a)}});const Zr=(0,i.op)({hingeLoss_:function(e,t,n,r=jr.SUM_BY_NONZERO_WEIGHTS){let a=(0,s.YT)(e,"labels","hingeLoss");const o=(0,s.YT)(t,"predictions","hingeLoss");let i=null;null!=n&&(i=(0,s.YT)(n,"weights","hingeLoss")),(0,d.O3)(a.shape,o.shape,"Error in hingeLoss: ");const u=(0,Re.d)(1);a=ct((0,_.l)((0,Re.d)(2),a),u);const c=(0,un.V)(ct(u,(0,_.l)(a,o)));return Kr(c,i,r)}});const Xr=(0,i.op)({huberLoss_:function(e,t,n,r=1,a=jr.SUM_BY_NONZERO_WEIGHTS){const o=(0,s.YT)(e,"labels","huberLoss"),i=(0,s.YT)(t,"predictions","huberLoss");let c=null;null!=n&&(c=(0,s.YT)(n,"weights","huberLoss")),(0,d.O3)(o.shape,i.shape,"Error in huberLoss: ");const l=(0,Re.d)(r),p=u(ct(i,o)),f=$t(p,l),m=ct(p,f),g=h((0,_.l)((0,Re.d)(.5),Oe(f)),(0,_.l)(l,m));return Kr(g,c,a)}});const qr=(0,i.op)({logLoss_:function(e,t,n,r=1e-7,a=jr.SUM_BY_NONZERO_WEIGHTS){const o=(0,s.YT)(e,"labels","logLoss"),i=(0,s.YT)(t,"predictions","logLoss");let u=null;null!=n&&(u=(0,s.YT)(n,"weights","logLoss")),(0,d.O3)(o.shape,i.shape,"Error in logLoss: ");const c=(0,Re.d)(1),l=(0,Re.d)(r),p=st((0,_.l)(o,nt(h(i,l)))),f=(0,_.l)(ct(c,o),nt(h(ct(c,i),l))),m=ct(p,f);return Kr(m,u,a)}});const Qr=(0,i.op)({meanSquaredError_:function(e,t,n,r=jr.SUM_BY_NONZERO_WEIGHTS){const a=(0,s.YT)(e,"labels","meanSquaredError"),o=(0,s.YT)(t,"predictions","meanSquaredError");let i=null;null!=n&&(i=(0,s.YT)(n,"weights","meanSquaredError")),(0,d.O3)(a.shape,o.shape,"Error in meanSquaredError: ");const u=On(a,o);return Kr(u,i,r)}});const Jr=(0,i.op)({sigmoidCrossEntropy_:function(e,t,n,r=0,a=jr.SUM_BY_NONZERO_WEIGHTS){let o=(0,s.YT)(e,"multiClassLabels","sigmoidCrossEntropy");const i=(0,s.YT)(t,"logits","sigmoidCrossEntropy");let c=null;if(null!=n&&(c=(0,s.YT)(n,"weights","sigmoidCrossEntropy")),(0,d.O3)(o.shape,i.shape,"Error in sigmoidCrossEntropy: "),r>0){const e=(0,Re.d)(r),t=(0,Re.d)(1),n=(0,Re.d)(.5);o=h((0,_.l)(o,ct(t,e)),(0,_.l)(n,e))}const l=function(e,t){const n=(0,s.YT)(e,"labels","sigmoidCrossEntropyWithLogits"),r=(0,s.YT)(t,"logits","sigmoidCrossEntropyWithLogits");(0,d.O3)(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");

2const a=(0,un.V)(r),o=(0,_.l)(r,n),i=rt(Pe(st(u(r))));return h(ct(a,o),i)}(o,i);return Kr(l,c,a)}});const ea=(0,i.op)({softmaxCrossEntropy_:function(e,t,n,r=0,a=jr.SUM_BY_NONZERO_WEIGHTS){let o=(0,s.YT)(e,"onehotLabels","softmaxCrossEntropy");const i=(0,s.YT)(t,"logits","softmaxCrossEntropy");let u=null;if(null!=n&&(u=(0,s.YT)(n,"weights","softmaxCrossEntropy")),(0,d.O3)(o.shape,i.shape,"Error in softmaxCrossEntropy: "),r>0){const e=(0,Re.d)(r),t=(0,Re.d)(1),n=(0,Re.d)(o.shape[1]);o=h((0,_.l)(o,ct(t,e)),ye(e,n))}const c=function(e,t,n=-1){if(-1===n&&(n=t.rank-1),n!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${t.rank} and dim was ${n}`);const r=ot((e,t,r)=>{const a=pt(t,[n],!0),o=ct((0,C.w)(t,"float32"),a);r([e,o]);const s=st((0,_.l)(o,e));return{value:(0,Fe.c)(s,[n]),gradFunc:(e,t)=>{const[r,a]=t,o=(0,$e.SM)(e.shape,[n]);return[(0,_.l)((0,E.t)(e,o),ct((0,C.w)(r,"float32"),Pe(a))),(0,_.l)((0,E.t)(e,o),ct(Pe(a),(0,C.w)(r,"float32")))]}}});return r(e,t)}(o,i);return Kr(c,u,a)}});const ta=(0,i.op)({sparseFillEmptyRows_:function(e,t,n,r){const i=(0,s.YT)(e,"indices","sparseFillEmptyRows","int32"),u=(0,s.YT)(t,"values","sparseFillEmptyRows"),c=(0,s.YT)(n,"denseShape","sparseFillEmptyRows","int32"),l=(0,s.YT)(r,"defaultValue","sparseFillEmptyRows",u.dtype);if(2!==i.rank)throw new Error(`Indices should be Tensor2D but received shape\n        ${i.shape}`);if(1!==u.rank)throw new Error(`Values should be Tensor1D but received shape ${u.shape}`);if(1!==c.rank)throw new Error(`Dense shape should be Tensor1D but received shape ${c.shape}`);if(0!==l.rank)throw new Error(`Default value should be a scalar but received shape ${l.shape}`);const p={indices:i,values:u,denseShape:c,defaultValue:l},h=a.T2.runKernel(o.C8s,p);return{outputIndices:h[0],outputValues:h[1],emptyRowIndicator:h[2],reverseIndexMap:h[3]}}});const na=(0,i.op)({sparseReshape_:function(e,t,n){const r=(0,s.YT)(e,"inputIndices","sparseReshape","int32"),i=(0,s.YT)(t,"inputShape","sparseReshape","int32"),u=(0,s.YT)(n,"newShape","sparseReshape","int32");if(2!==r.rank)throw new Error(`Input indices should be Tensor2D but received shape\n        ${r.shape}`);if(1!==i.rank)throw new Error(`Input shape should be Tensor1D but received shape ${i.shape}`);if(1!==u.rank)throw new Error(`New shape should be Tensor1D but received shape ${u.shape}`);const c={inputIndices:r,inputShape:i,newShape:u},l=a.T2.runKernel(o.BoJ,c);return{outputIndices:l[0],outputShape:l[1]}}});const ra=(0,i.op)({sparseSegmentMean_:function(e,t,n){const r=(0,s.YT)(e,"data","sparseSegmentMean"),i=(0,s.YT)(t,"indices","sparseSegmentMean","int32"),u=(0,s.YT)(n,"segmentIds","sparseSegmentMean","int32");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==i.rank)throw new Error(`Indices should be Tensor1D but received shape\n          ${i.shape}`);if(1!==u.rank)throw new Error(`Segment ids should be Tensor1D but received shape\n          ${u.shape}`);const c={data:r,indices:i,segmentIds:u};return a.T2.runKernel(o.L6G,c)}});const aa=(0,i.op)({sparseSegmentSum_:function(e,t,n){const r=(0,s.YT)(e,"data","sparseSegmentSum"),i=(0,s.YT)(t,"indices","sparseSegmentSum","int32"),u=(0,s.YT)(n,"segmentIds","sparseSegmentSum","int32");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(1!==i.rank)throw new Error(`Indices should be Tensor1D but received shape\n         ${i.shape}`);if(1!==u.rank)throw new Error(`Segment ids should be Tensor1D but received shape\n         ${u.shape}`);const c={data:r,indices:i,segmentIds:u};return a.T2.runKernel(o.DvZ,c)}});const oa=(0,i.op)({stringNGrams_:function(e,t,n,r,i,u,c,l){const p=(0,s.YT)(e,"data","stringNGrams","string");if("string"!==p.dtype)throw new Error("Data must be of datatype string");if(1!==p.shape.length)throw new Error(`Data must be a vector, saw: ${p.shape}`);const h=(0,s.YT)(t,"dataSplits","stringNGrams");if("int32"!==h.dtype)throw new Error("Data splits must be of datatype int32");

2const d={separator:n,nGramWidths:r,leftPad:i,rightPad:u,padWidth:c,preserveShortSequences:l},f={data:p,dataSplits:h},m=a.T2.runKernel(o.YAb,f,d);return{nGrams:m[0],nGramsSplits:m[1]}}});const sa=(0,i.op)({stringSplit_:function(e,t,n=!0){const r=(0,s.YT)(e,"input","stringSplit","string"),i=(0,s.YT)(t,"delimiter","stringSplit","string");if(1!==r.rank)throw new Error(`Input should be Tensor1D but received shape ${r.shape}`);if(0!==i.rank)throw new Error(`Delimiter should be a scalar but received shape ${i.shape}`);const u={skipEmpty:n},c={input:r,delimiter:i},l=a.T2.runKernel(o.iW0,c,u);return{indices:l[0],values:l[1],shape:l[2]}}});const ia=(0,i.op)({stringToHashBucketFast_:function(e,t){const n=(0,s.YT)(e,"input","stringToHashBucketFast","string"),r={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");const i={input:n};return a.T2.runKernel(o.$jE,i,r)}}),ua={fft:Nn,ifft:In,rfft:_n,irfft:An},ca={hammingWindow:wr,hannWindow:Tr,frame:Sr,stft:Cr},la={flipLeftRight:Er,grayscaleToRGB:$r,resizeNearestNeighbor:Pr,resizeBilinear:Mr,rotateWithOffset:Nr,cropAndResize:kr,nonMaxSuppression:Ar,nonMaxSuppressionAsync:_r,nonMaxSuppressionWithScore:Or,nonMaxSuppressionWithScoreAsync:Fr,nonMaxSuppressionPadded:Dr,nonMaxSuppressionPaddedAsync:Lr,threshold:Br,transform:Vr},pa={bandPart:zr,gramSchmidt:Ur,qr:Gr},ha={absoluteDifference:Hr,computeWeightedLoss:Kr,cosineDistance:Yr,hingeLoss:Zr,huberLoss:Xr,logLoss:qr,meanSquaredError:Qr,sigmoidCrossEntropy:Jr,softmaxCrossEntropy:ea},da={sparseFillEmptyRows:ta,sparseReshape:na,sparseSegmentMean:ra,sparseSegmentSum:aa},fa={stringNGrams:oa,stringSplit:sa,stringToHashBucketFast:ia}}}]);

Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.