https://credito365.co/frontend-assets/tensorflow.3230f5e50ed04b6cad7d.js

1/*! For license information please see tensorflow.3230f5e50ed04b6cad7d.js.LICENSE.txt */
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r=y[t+e];(Number.isNaN(r)||r<n)&&(n=r)}g[e]=n}null!=p&&n.disposeIntermediateTensorInfo(d);const b=n.makeTensorInfo(h,d.dtype,g);if(u){const e=z({inputs:{x:b},backend:n,attrs:{shape:r.cxb.expandShapeToKeepDim(h,c)}});return n.disposeIntermediateTensorInfo(b),e}return b}},ar=g(((e,t)=>Math.min(e,t))),or=C(r.sly,ar),sr={kernelName:r.sly,backendName:"cpu",kernelFunc:or},ir={kernelName:r.C6u,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:o}=e,{x:s}=t,{paddings:i,mode:u}=o;(0,a.q)(s,"mirrorPad");const c=i.map(((e,t)=>e[0]+s.shape[t]+e[1])),l=i.map((e=>e[0])),p=i.map(((e,t)=>e[0]+s.shape[t])),d="reflect"===u?0:1,h=n.data.get(s.dataId).values,f=s.shape.length,m=r.euu.computeStrides(s.shape),g=r.euu.sizeFromShape(c),y=c.length,b=r.euu.computeStrides(c),w=r.euu.getTypedArrayFromDType(s.dtype,g);for(let e=0;e<g;e++){let t=r.euu.indexToLoc(e,y,b);for(let e=0;e<y;e++)t[e]<l[e]?t[e]=2*l[e]-t[e]-d:t[e]>=p[e]&&(t[e]=2*(p[e]-1)-t[e]+d);t=t.map(((e,t)=>e-l[t]));const n=r.euu.locToIndex(t,f,m);w[e]=h[n]}return{dataId:n.write(w,c,s.dtype),shape:c,dtype:s.dtype}}},ur=g(((e,t)=>{const n=e%t;return e<0&&t<0||e>=0&&t>=0?n:(n+t)%t})),cr=C(r.InO,ur),lr={kernelName:r.InO,backendName:"cpu",kernelFunc:cr};var pr=n(4792);function dr(e){const{inputs:t,backend:n,attrs:a}=e,{logits:o}=t,{dim:s}=a,i=o.shape.length;let u=s;if(-1===u&&(u=i-1),u!==i-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${i} and dim was ${u}`);const c=r.euu.parseAxisParam([u],o.shape),l=qn({inputs:{x:o},backend:n,attrs:{reductionIndices:c,keepDims:!1}}),p=r.cxb.expandShapeToKeepDim(l.shape,c),d=z({inputs:{x:l},backend:n,attrs:{shape:p}}),h=Gt({inputs:{a:o,b:d},backend:n}),f=Ot({inputs:{x:h},backend:n}),m=yt({inputs:{x:f},backend:n,attrs:{axis:c,keepDims:!1}}),g=z({inputs:{x:m},backend:n,attrs:{shape:p}}),y=Bt({inputs:{a:f,b:g},backend:n});return n.disposeIntermediateTensorInfo(l),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),y}const hr={kernelName:r.a0o,backendName:"cpu",kernelFunc:dr},fr={kernelName:r.UdG,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:o}=e,{logits:s}=t,{numSamples:i,seed:u,normalized:c}=o;(0,a.q)(s,"multinomial");const l=c?s:dr({inputs:{logits:s},backend:n,attrs:{dim:-1}}),p=l.shape[0],d=l.shape[1],h=n.data.get(l.dataId).values,f=[p,i],m=r.euu.makeZerosTypedArray(r.euu.sizeFromShape(f),"int32");for(let e=0;e<p;++e){const t=e*d,n=new Float32Array(d-1);n[0]=h[t];for(let e=1;e<n.length;++e)n[e]=n[e-1]+h[t+e];const r=pr.alea(u.toString()),a=e*i;for(let e=0;e<i;++e){const t=r();m[a+e]=n.length;for(let r=0;r<n.length;r++)if(t<n[r]){m[a+e]=r;break}}}return c||n.disposeIntermediateTensorInfo(l),n.makeTensorInfo(f,"int32",m)}},mr={kernelName:r.yUy,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n}=e,{x:o}=t;(0,a.q)(o,"neg");const s=n.data.get(o.dataId).values,[i,u]=function(e,t,n){const a=r.euu.createScalarValue(-1,n);return ht([],t,a,e,n)}(s,o.shape,o.dtype);return n.makeTensorInfo(u,o.dtype,i)}},gr=r.lKA.Wm,yr={kernelName:r.aaw,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:u,scoreThreshold:c}=r;(0,a.q)(o,"NonMaxSuppression");const l=n.data.get(o.dataId).values,p=n.data.get(s.dataId).values,{selectedIndices:d}=gr(l,p,i,u,c);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}},br=r.lKA.Mf,wr={kernelName:r.Q7n,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:u,scoreThreshold:c,padToMaxOutputSize:l}=r;(0,a.q)(o,"NonMaxSuppressionPadded");const p=n.data.get(o.dataId).values,d=n.data.get(s.dataId).values,{selectedIndices:h,validOutputs:f}=br(p,d,i,u,c,l);return[n.makeTensorInfo([h.length],"int32",new Int32Array(h)),n.makeTensorInfo([],"int32",new Int32Array([f]))]}},vr=r.lKA.eQ,kr={kernelName:r.q82,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:u,scoreThreshold:c,softNmsSigma:l}=r;(0,a.q)(o,"NonMaxSuppressionWithScore");const p=n.data.get(o.dataId).values,d=n.data.get(s.dataId).values,h=i,f=u,m=c,g=l,{selectedIndices:y,selectedScores:b}=vr(p,d,h,f,m,g);return[n.makeTensorInfo([y.length],"int32",new Int32Array(y)),n.makeTensorInfo([b.length],"float32",new Float32Array(b))]}},xr=g(((e,t)=>e!==t?1:0)),_r=C(r.Ki5,xr,null,"bool"),Ir={kernelName:r.Ki5,backendName:"cpu",kernelFunc:_r},Sr={kernelName:r.mon,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:o}=e,{indices:s}=t,{dtype:i,depth:u,onValue:c,offValue:l}=o;(0,a.q)(s,"oneHot");const p=r.euu.sizeFromShape(s.shape),d=new Float32Array(p*u);d.fill(l);const h=n.data.get(s.dataId).values;for(let e=0;e<p;++e)h[e]>=0&&h[e]<u&&(d[e*u+h[e]]=c);return n.makeTensorInfo([...s.shape,u],i,d)}};function Nr(e){const{inputs:t,backend:n}=e,{x:r}=t;if("string"===r.dtype)throw new Error("zerosLike is not supported for string tensors");if("complex64"===r.dtype){const e=A({inputs:{input:r},backend:n}),t=Nr({inputs:{x:e},backend:n}),a=Le({inputs:{input:r},backend:n}),o=Nr({inputs:{x:a},backend:n}),s=M({inputs:{real:t,imag:o},backend:n});return n.disposeIntermediateTensorInfo(e),n.disposeIntermediateTensorInfo(t),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),s}return Jt({backend:n,attrs:{shape:r.shape,value:0,dtype:r.dtype}})}const Mr={kernelName:r.qKC,backendName:"cpu",kernelFunc:Nr},Tr={kernelName:r.O_l,backendName:"cpu",kernelFunc:function e(t){const{inputs:n,backend:r}=t,{x:a}=n;if("string"===a.dtype)throw new Error("onesLike is not supported for string tensors");if("complex64"===a.dtype){const t=A({inputs:{input:a},backend:r}),n=e({inputs:{x:t},backend:r}),o=Le({inputs:{input:a},backend:r}),s=Nr({inputs:{x:o},backend:r}),i=M({inputs:{real:n,imag:s},backend:r});return r.disposeIntermediateTensorInfo(t),r.disposeIntermediateTensorInfo(n),r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(s),i}return Jt({backend:r,attrs:{shape:a.shape,value:1,dtype:a.dtype}})}};function Er(e){const{inputs:t,backend:n,attrs:a}=e,{axis:o}=a;if(1===t.length)return Pt({inputs:{input:t[0]},backend:n,attrs:{dim:o}});const s=t[0].shape,i=t[0].dtype;t.forEach((e=>{r.euu.assertShapesMatch(s,e.shape,"All tensors passed to stack must have matching shapes"),r.euu.assert(i===e.dtype,(()=>"All tensors passed to stack must have matching dtypes"))}));const u=[],c=ze({inputs:t.map((e=>{const t=Pt({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}const Ar={kernelName:r.cJi,backendName:"cpu",kernelFunc:Er},Fr={kernelName:r.Q8A,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:o}=e,{x:s}=t,{paddings:i,constantValue:u}=o;(0,a.q)(s,"pad");const c=i.map(((e,t)=>e[0]+s.shape[t]+e[1])),l=i.map((e=>e[0])),p=n.data.get(s.dataId).values,d=r.euu.sizeFromShape(s.shape),h=s.shape.length,f=r.euu.computeStrides(s.shape),m=r.euu.sizeFromShape(c),g=c.length,y=r.euu.computeStrides(c),b=r.euu.getTypedArrayFromDType(s.dtype,m);0!==u&&b.fill(u);for(let e=0;e<d;e++){const t=r.euu.indexToLoc(e,h,f).map(((e,t)=>e+l[t]));b[r.euu.locToIndex(t,g,y)]=p[e]}return{dataId:n.write(b,c,s.dtype),shape:c,dtype:s.dtype}}},Dr=g(((e,t)=>Math.pow(e,t))),Or=C(r.sTH,Dr),Cr={kernelName:r.sTH,backendName:"cpu",kernelFunc:Or},Pr={kernelName:r.e_0,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:o}=e,{x:s}=t,{axis:i,keepDims:u}=o;(0,a.q)(s,"prod");const c=s.shape.length,l=r.euu.parseAxisParam(i,s.shape),p=r.cxb.getAxesPermutation(l,c);let d=l,h=s;const f=[];null!=p&&(h=Z({inputs:{x:s},backend:n,attrs:{perm:p}}),f.push(h),d=r.cxb.getInnerMostAxes(d.length,c));const m=n.data.get(h.dataId).values,{outVals:g,outShape:y,outDtype:b}=function(e,t,n,a){const[o,s]=r.cxb.computeOutAndReduceShapes(e,a),i=(0,r.OAw)(t,"int32"),u=r.euu.makeZerosTypedArray(r.euu.sizeFromShape(o),i),c=r.euu.sizeFromShape(s);for(let e=0;e<u.length;++e){const t=e*c;let r=1;for(let e=0;e<c;++e)r*=n[t+e];u[e]=r}return{outVals:u,outShape:o,outDtype:i}}(h.shape,h.dtype,m,d);let w=y;return u&&(w=r.cxb.expandShapeToKeepDim(y,l)),f.forEach((e=>n.disposeIntermediateTensorInfo(e))),n.makeTensorInfo(w,b,g)}};function Rr(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 $r(e,t,n,a,o,s,i,u){if(0===e.length)throw new Error("paramsNestedSplits must be non empty");if(0===t[0].length)throw new Error("Split tensors must not be scalars");if(function(e,t,n){e.forEach(((e,a)=>{if(e<0||e>=n){const o=r.euu.indexToLoc(a,t.length,r.euu.computeStrides(t)).join(",");throw new Error(`indices[${o}] = ${e} is not in [0, ${n})`)}}))}(s,i,t[0][0]-1),0===a.length)throw new Error("params.rank must be nonzero");const c=a[0],{outSplits:l,valueSlices:p,numValues:d}=function(e,t,n,r){const a=[];let o=0;const s=t.length-1+n.length,i=new Array(s).fill(null).map((()=>[0]));!function(e,t){for(let n=0;n<e.length;++n){const r=e[n],a=n===e.length-1?t:e[n+1].length;if(0===r.length)throw new Error("Ragged splits may not be empty");if(r[0]<0)throw new Error("Ragged splits must be non-negative");if(r[r.length-1]>a)throw new Error("Ragged splits must not point past values");for(let e=1;e<r.length;++e)if(r[e-1]>r[e])throw new Error("Ragged splits must be sorted in ascending order")}}(n,r);let u=1;for(let e=0;e<t.length-1;++e){u*=t[e];const n=t[e+1];for(let t=1;t<u+1;++t)i[e].push(t*n)}for(let r=0;r<e.length;++r){let s=e[r],u=e[r]+1;for(let e=0;e<n.length;++e){const r=n[e],a=e+t.length-1;if(a>=0){const e=i[a],t=e[e.length-1]-r[s];for(let e=s;e<u;++e)i[a].push(r[e+1]+t)}s=r[s],u=r[u]}u!==s&&(a.push([s,u]),o+=u-s)}return{outSplits:i,valueSlices:a,numValues:o}}(s,i,e,c),h=function(e){const t=[];for(let n=0;n<e.length;++n){const a=e[n].length,o=r.euu.getArrayFromDType("int32",a);t.push(o),e[n].forEach(((e,t)=>o[t]=e))}return t}(l),f=function(e,t,n,a,o){const s=t.slice();s[0]=o;const i=r.euu.getArrayFromDType(n,r.euu.sizeFromShape(s)),u=e.length;return function(e,t,n,r,a,o){const s=Rr(t,2)[1],i=Rr(o,2)[1];let u=0;for(const t of n)for(let n=t[0];n<t[1];++n){for(let t=0;t<r;++t)a[u*i+t]=e[n*s+t];++u}}(e,t,a,0===u?0:u/t[0],i,s),[i,s]}(n,a,o,p,d);return[h,f[0],f[1]]}const Lr={kernelName:r.KGR,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{paramsNestedSplits:a,paramsDenseValues:o,indices:s}=t,{outputRaggedRank:i}=r,u=a.map((e=>n.data.get(e.dataId).values)),c=a.map((e=>e.shape)),l=n.data.get(o.dataId).values,p=n.data.get(s.dataId).values,[d,h,f]=$r(u,c,l,o.shape,o.dtype,p,s.shape),m=d.map((e=>n.makeTensorInfo([e.length],"int32",e))),g=n.makeTensorInfo(f,o.dtype,h);return m.concat([g])}},Wr=2147483647,zr={kernelName:r.sdx,backendName:"cpu",kernelFunc:function(e){const{inputs:t,backend:n}=e,{starts:a,limits:o,deltas:s}=t,i=n.data.get(a.dataId).values,u=n.data.get(o.dataId).values,c=n.data.get(s.dataId).values,[l,p]=function(e,t,n,a,o,s,i){if(t.length>1)throw new Error("starts must be a scalar or vector");if(o.length>1)throw new Error("limits must be a scalar or vector");if(i.length>1)throw new Error("deltas must be a scalar or vector");const u=0===t.length,c=0===o.length,l=0===i.length,p=[];u||p.push(t[0]),c||p.push(o[0]),l||p.push(i[0]);for(let e=1;e<p.length;++e)if(p[e]!==p[e-1])throw new Error("starts, limits, and deltas must have the same shape");const d=0===p.length?1:p[0],h=r.euu.getArrayFromDType("int32",d+1);h[0]=0;for(let t=0;t<d;++t){const n=u?e[0]:e[t],r=c?a[0]:a[t],o=l?s[0]:s[t];if(0===o)throw new Error("Requires delta != 0");let i;if(o>0&&r<n||o<0&&r>n)i=0;else if(i=Math.ceil(Math.abs((r-n)/o)),i>Wr)throw new Error("Requires ((limit - start) / delta) <= 2147483647");h[t+1]=h[t]+i}const f=h[d],m=r.euu.getArrayFromDType(n,f);let g=0;for(let t=0;t<d;++t){const n=h[t+1]-h[t];let r=u?e[0]:e[t];const a=l?s[0]:s[t];for(let e=0;e<n;++e)m[g++]=r,r+=a}return[h,m]}(i,a.shape,a.dtype,u,o.shape,c,s.shape);return[n.makeTensorInfo([l.length],"int32",l),n.makeTensorInfo([p.length],a.dtype,p)]}};var Br=r.cxb.RowPartitionType;class Ur{constructor(e,t,n,a,o,s,i,u,c,l){this.shape=e,this.shapeShape=t,this.values=n,this.valuesShape=a,this.valuesDType=o,this.defaultValue=s,this.defaultValueShape=i,this.rowPartitionValues=u,this.rowPartitionValuesShapes=c,this.rowPartitionTypes=r.cxb.getRowPartitionTypesHelper(l),this.raggedRank=r.cxb.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(e){return this.rowPartitionTypes[0]===Br.FIRST_DIM_SIZE?this.rowPartitionTypes[e+1]:this.rowPartitionTypes[e]}getRowPartitionTensor(e){return this.rowPartitionTypes[0]===Br.FIRST_DIM_SIZE?this.rowPartitionValues[e+1]:this.rowPartitionValues[e]}getMaxWidth(e){const t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case Br.VALUE_ROWIDS:return Ur.getMaxWidthValueRowID(t);case Br.ROW_SPLITS:return Ur.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${Br[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){const t=e.length;if(0===t||1===t)return 0;let n=0;for(let r=0;r<t-1;++r){const t=e[r+1]-e[r];t>n&&(n=t)}return n}static getMaxWidthValueRowID(e){const t=e.length;if(0===t)return 0;let n=0,r=e[0],a=0;for(let o=1;o<t;++o){const t=e[o];t!==r&&(r=t,a=Math.max(o-n,a),n=o)}return Math.max(t-n,a)}tensorShapeFromTensor(e,t,n=!0){if(0===t.length){if(-1===e[0])return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return Vr(e,n)}calculateOutputSize(e){const t=this.valuesShape,n=this.defaultValueShape;r.cxb.validateDefaultValueShape(n,t);const a=this.tensorShapeFromTensor(this.shape,this.shapeShape),o=r.cxb.combineRaggedTensorToTensorShapes(this.raggedRank,a,t);o[0]<0&&(o[0]=e);for(let e=1;e<=this.raggedRank;++e)o[e]<0&&(o[e]=this.getMaxWidth(e));return o}calculateFirstParentOutputIndex(e,t,n){const a=Math.min(e,n),o=[];let s=0;for(let e=0;e<a;++e,s+=t)o.push(s);for(let t=a;t<e;++t)o.push(-1);return r.euu.assert(o.length===e,(()=>"Final length of result must be equal to firstDimension.")),o}calculateOutputIndexRowSplit(e,t,n,r){const a=e.length,o=[];for(let s=0;s<a-1;++s){const a=e[s+1]-e[s];let i=Math.min(r,a),u=t[s];-1===u&&(i=0);for(let e=0;e<i;++e)o.push(u),u+=n;for(let e=0;e<a-i;++e)o.push(-1)}if(a>0&&o.length!==e[a-1])throw new Error("Invalid row split size.");return o}calculateOutputIndexValueRowID(e,t,n,r){const a=e.length,o=[];if(0===a)return[];let s=0,i=e[0];if(i>=t.length)throw new Error(`Got currentValueRowId=${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 Br.VALUE_ROWIDS:return 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e=o.sL.computeFlatOffset(s,p);return"string"===t.dtype?d.stringBytes=c.slice(e,e+o.euu.sizeFromShape(i)):a.typedArrayFromHeap(l).set(c.subarray(e,e+o.euu.sizeFromShape(i))),l}if("string"===t.dtype){const e=(0,q.Ki)(c,s,i,t.shape,t.dtype);return d.stringBytes=e,l}const h=a.typedArrayFromHeap(l),f=t.shape.length;if(2===f)!function(e,t,n,r,a){let o=0;const s=r[0],i=r[1],u=s+a[0];for(let r=s;r<u;r++){const s=r*t+i;n.set(e.subarray(s,s+a[1]),o),o+=a[1]}}(c,p[0],h,s,i);else if(3===f)!function(e,t,n,r,a,o){let s=0;const i=a[0],u=a[1],c=a[2],l=i+o[0],p=u+o[1];for(let a=i;a<l;a++)for(let i=u;i<p;i++){const u=a*t+i*n+c;r.set(e.subarray(u,u+o[2]),s),s+=o[2]}}(c,p[0],p[1],h,s,i);else if(4===f)!function(e,t,n,r,a,o,s){let i=0;const u=o[0],c=o[1],l=o[2],p=u+s[0],d=c+s[1],h=l+s[2],f=o[3];for(let o=u;o<p;o++)for(let u=c;u<d;u++)for(let c=l;c<h;c++){const l=o*t+u*n+c*r+f;a.set(e.subarray(l,l+s[3]),i),i+=s[3]}}(c,p[0],p[1],p[2],h,s,i);else{const e=(0,q.Ki)(c,s,i,t.shape,t.dtype);h.set(e)}return l}const K={kernelName:o.eKt,backendName:"wasm",kernelFunc:j},Q={kernelName:o.EV6,backendName:"wasm",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r,u=s.reduce(((e,t)=>e*t)),c=o.cxb.getReshaped(a.shape,s,u),l=o.cxb.getPermuted(c.length,s.length),p=o.cxb.getReshapedPermuted(a.shape,s,u),d=o.cxb.getSliceBeginCoords(i,s.length),h=o.cxb.getSliceSize(p,i,s.length),f=U({inputs:{x:a},backend:n,attrs:{shape:c}}),m=w({inputs:{x:f},backend:n,attrs:{perm:l}}),g=U({inputs:{x:m},backend:n,attrs:{shape:p}}),y=j({inputs:{x:g},backend:n,attrs:{begin:d,size:h}});return n.disposeData(f.dataId),n.disposeData(m.dataId),n.disposeData(g.dataId),y}};let Y;const J={kernelName:o.M3o,backendName:"wasm",setupFunc:function(e){Y=e.wasm.cwrap(o.M3o,null,["number","number","boolean","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:a}=e,{x:o,weights:s}=n,{size:i}=a,u=0!==s.shape.reduce(((e,t)=>e*t),1),c=1===o.shape.length?[i]:[o.shape[0],i],l=t.makeOutput(c,s.dtype);function p(e){return t.dataIdMap.get(e.dataId).id}return Y(p(o),i,u,p(s),r[s.dtype],p(l)),l}},Z=d(o.eCV),X={kernelName:o.orO,backendName:"wasm",kernelFunc:function(e){const{inputs:t,backend:n}=e,{s0:r,s1:a}=t,s=n.typedArrayFromHeap(r),i=n.typedArrayFromHeap(a),u=o.cxb.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeOutput([u.length],"int32",void 0,new Int32Array(u))}};function ee(e){const{inputs:{x:t},attrs:{dtype:n},backend:r}=e,a=r.makeOutput(t.shape,n),o=r.typedArrayFromHeap(t);return r.typedArrayFromHeap(a).set(o),a}const te={kernelName:o.Utj,backendName:"wasm",kernelFunc:ee},ne=u(o.OeR);let re;const ae={kernelName:o.Oe9,backendName:"wasm",setupFunc:function(e){re=e.wasm.cwrap(o.Oe9,null,["number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:o,clipValueMax:s}=r,i=n.dataIdMap.get(a.dataId).id,u=n.makeOutput(a.shape,a.dtype),c=n.dataIdMap.get(u.dataId).id;return re(i,o,s,c),u}};var oe=n(91428);function se(e){const{inputs:t,backend:n}=e,r=o.euu.parseAxisParam(e.attrs.axis,t[0].shape)[0],a=t.map((e=>e.shape));o.cxb.assertParamsConsistent(a,r);let s=o.cxb.computeOutShape(t.map((e=>e.shape)),r);const i=t.filter((e=>o.euu.sizeFromShape(e.shape)>0));if(1===i.length)return g({inputs:{x:i[0]},backend:n});const u=n.makeOutput(s,t[0].dtype);if(0===o.euu.sizeFromShape(s))return u;if("string"===i[0].dtype){const e=i.map((e=>{const t=o.euu.sizeFromShape(e.shape.slice(r));return U({inputs:{x:e},backend:n,attrs:{shape:[-1,t]}})})),a=e.map((e=>({vals:n.readSync(e.dataId),shape:e.shape})));s=o.cxb.computeOutShape(e.map((e=>e.shape)),1);const c=1===e[0].shape[0],l=(0,oe.m)(a,s,t[0].dtype,c),p=o.cxb.computeOutShape(i.map((e=>e.shape)),r);return u.shape=p,n.dataIdMap.get(u.dataId).stringBytes=o.cxb.fromStringArrayToUint8(l),e.forEach((e=>n.disposeData(e.dataId))),u}const c=o.euu.sizeFromShape(i[0].shape.slice(0,r));let l=0;const p=i.map((e=>{const t=o.euu.sizeFromShape(e.shape.slice(r));return l+=t,t})),d=i.map((e=>n.typedArrayFromHeap(e))),h=n.typedArrayFromHeap(u);for(let e=0;e<c;e++){let t=e*l;for(let n=0;n<d.length;n++){const r=p[n],a=e*r,o=d[n].subarray(a,a+r);h.set(o,t),t+=r}}return u}const ie={kernelName:o.usi,backendName:"wasm",kernelFunc:se};let ue;const ce={kernelName:o.a_P,backendName:"wasm",setupFunc:function(e){ue=e.wasm.cwrap(o.a_P,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s}=t,i=r.dataIdMap.get(a.dataId).id,u=r.dataIdMap.get(s.dataId).id,{strides:c,dilations:l,pad:p,dimRoundingMode:d,dataFormat:h}=n,f=o.cxb.convertConv2DDataFormat(h),m=o.cxb.computeConv2DInfo(a.shape,s.shape,c,l,p,d,!1,f),g=m.filterHeight,y=m.filterWidth,b=m.padInfo.top,w=m.padInfo.right,v=m.padInfo.bottom,k=m.padInfo.left,x=m.dilationHeight,_=m.dilationWidth,I=m.strideHeight,S=m.strideWidth,N=m.inChannels,M=m.outChannels,T="SAME"===m.padInfo.type?1:0;if("channelsLast"!==m.dataFormat)throw new Error(`wasm backend Conv2D does not support dataFormat:'${m.dataFormat}'. 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pe={kernelName:o.Mz5,backendName:"wasm",setupFunc:function(e){le=e.wasm.cwrap(o.Mz5,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{dy:a,filter:s}=n,{strides:i,pad:u,dataFormat:c,dimRoundingMode:l,inputShape:p}=r,d=o.cxb.convertConv2DDataFormat(c),h=o.cxb.computeConv2DInfo(p,s.shape,i,1,u,l,!1,d),{batchSize:f,filterHeight:m,filterWidth:g,inChannels:y,inHeight:b,inWidth:w,outChannels:v,outHeight:k,outWidth:x,strideHeight:_,strideWidth:I}=h,S=m-1-h.padInfo.top,N=g-1-h.padInfo.left,M="channelsLast"===h.dataFormat,T=o.euu.computeStrides(h.inShape),E=o.euu.computeStrides(a.shape),[A,F,D]=o.euu.computeStrides(s.shape),O=T[0],C=M?T[1]:T[2],P=M?T[2]:1,R=M?1:T[1],$=E[0],L=M?E[1]:E[2],W=M?E[2]:1,z=M?1:E[1],B=t.makeOutput(h.inShape,"float32"),U=t.dataIdMap.get(B.dataId).id,H=t.dataIdMap.get(a.dataId).id,V=t.dataIdMap.get(s.dataId).id;return le(H,V,f,m,g,b,w,y,k,x,v,_,I,S,N,A,F,D,O,C,P,R,$,L,W,z,U),B}};let de;const he={kernelName:o.WE3,backendName:"wasm",setupFunc:function(e){de=e.wasm.cwrap(o.WE3,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:u,dilations:c}=r;if("float32"!==a.dtype)throw new Error(`Tensor x must have dtype float32, got ${a.dtype}`);if("float32"!==s.dtype)throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);const l=o.cxb.computeConv3DInfo(a.shape,s.shape,i,c,u),p=n.makeOutput(l.outShape,a.dtype);return de(n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(p.dataId).id,l.batchSize,l.inDepth,l.inHeight,l.inWidth,l.inChannels,l.outDepth,l.outHeight,l.outWidth,l.outChannels,l.strideDepth,l.strideHeight,l.strideWidth,l.dilationDepth,l.dilationHeight,l.dilationWidth,l.filterDepth,l.filterHeight,l.filterWidth,l.padInfo.front,l.padInfo.top,l.padInfo.left),p}};let fe;const me={kernelName:o.QjG,backendName:"wasm",setupFunc:function(e){fe=e.wasm.cwrap(o.QjG,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:u,filterShape:c}=r;if("float32"!==a.dtype)throw new Error(`Tensor dy must have dtype float32, got ${a.dtype}`);if("float32"!==s.dtype)throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);const l=o.cxb.computeConv3DInfo(a.shape,c,i,1,u),p=n.makeOutput(l.filterShape,s.dtype);return fe(n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(p.dataId).id,l.batchSize,l.inDepth,l.inHeight,l.inWidth,l.inChannels,l.outDepth,l.outHeight,l.outWidth,l.outChannels,l.strideDepth,l.strideHeight,l.strideWidth,l.dilationDepth,l.dilationHeight,l.dilationWidth,l.filterDepth,l.filterHeight,l.filterWidth,l.padInfo.front,l.padInfo.top,l.padInfo.left),p}};let ge;const ye={kernelName:o.ygG,backendName:"wasm",setupFunc:function(e){ge=e.wasm.cwrap(o.ygG,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:u,inputShape:c}=r;if("float32"!==a.dtype)throw new Error(`Tensor dy must have dtype float32, got ${a.dtype}`);if("float32"!==s.dtype)throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);const l=o.cxb.computeConv3DInfo(c,s.shape,u,1,i),p=n.makeOutput(l.inShape,a.dtype);return ge(n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(p.dataId).id,l.batchSize,l.inDepth,l.inHeight,l.inWidth,l.inChannels,l.outDepth,l.outHeight,l.outWidth,l.outChannels,l.strideDepth,l.strideHeight,l.strideWidth,l.dilationDepth,l.dilationHeight,l.dilationWidth,l.filterDepth,l.filterHeight,l.filterWidth,l.padInfo.front,l.padInfo.top,l.padInfo.left),p}},be=u(o.EHc),we=u(o.YZ3);var ve;let ke;!function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"}(ve||(ve={}));const xe={kernelName:o.WO0,backendName:"wasm",setupFunc:function(e){ke=e.wasm.cwrap(o.WO0,null,["number","number","number","number","array","number","number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{method:a,extrapolationValue:o,cropSize:s}=r,{image:i,boxes:u,boxInd:c}=n,l=u.shape[0],[p,d]=s,h=[l,p,d,i.shape[3]];let f,m=t.dataIdMap.get(i.dataId);"float32"!==i.dtype&&(f=ee({backend:t,inputs:{x:i},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(f.dataId));const g=m.id,y=t.dataIdMap.get(u.dataId).id,b=t.dataIdMap.get(c.dataId).id,w=t.makeOutput(h,"float32"),v=t.dataIdMap.get(w.dataId).id,k=new Uint8Array(new Int32Array(i.shape).buffer);return ke(g,y,b,l,k,p,d,ve[a],o,v),null!=f&&t.disposeData(f.dataId),w}};let _e;const Ie={kernelName:o.yuV,backendName:"wasm",setupFunc:function(e){_e=e.wasm.cwrap(o.yuV,null,["number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:a}=e,{x:s}=t,{axis:i,exclusive:u,reverse:c}=a,l=s.shape.length;o.euu.assert("float32"===s.dtype||"int32"===s.dtype,(()=>`cumprod does not support ${s.dtype} tensors in the WASM backend`));const p=o.cxb.getAxesPermutation([i],l);let d=s;null!==p&&(d=w({inputs:{x:s},attrs:{perm:p},backend:n}));const h=o.cxb.getInnerMostAxes(1,l)[0];o.cxb.assertAxesAreInnerMostDims("cumprod",[h],l);const f=n.makeOutput(d.shape,d.dtype),m=d.shape[h],g=n.dataIdMap.get(d.dataId).id,y=n.dataIdMap.get(f.dataId).id;_e(g,u?1:0,c?1:0,m,y,r[s.dtype]);let b=f;return null!==p&&(b=w({inputs:{x:f},attrs:{perm:o.cxb.getUndoAxesPermutation(p)},backend:n}),n.disposeData(d.dataId),n.disposeData(f.dataId)),b}};let Se;const Ne={kernelName:o.gBx,backendName:"wasm",setupFunc:function(e){Se=e.wasm.cwrap(o.gBx,null,["number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:a}=e,{x:s}=t,{axis:i,exclusive:u,reverse:c}=a,l=s.shape.length;o.euu.assert("float32"===s.dtype||"int32"===s.dtype,(()=>`cumsum does not support ${s.dtype} tensors in the WASM backend`));const p=o.cxb.getAxesPermutation([i],l);let d=s;null!==p&&(d=w({inputs:{x:s},attrs:{perm:p},backend:n}));const h=o.cxb.getInnerMostAxes(1,l)[0];o.cxb.assertAxesAreInnerMostDims("cumsum",[h],l);const f=n.makeOutput(d.shape,d.dtype),m=d.shape[h],g=n.dataIdMap.get(d.dataId).id,y=n.dataIdMap.get(f.dataId).id;Se(g,u?1:0,c?1:0,m,y,r[s.dtype]);let b=f;return null!==p&&(b=w({inputs:{x:f},attrs:{perm:o.cxb.getUndoAxesPermutation(p)},backend:n}),n.disposeData(d.dataId),n.disposeData(f.dataId)),b}};let Me;const Te={kernelName:o.COo,backendName:"wasm",setupFunc:function(e){Me=e.wasm.cwrap("DenseBincount",null,["number","array","number","number","boolean","number","number","boolean","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:a}=e,{x:o,weights:s}=n,{size:i,binaryOutput:u}=a,c=0!==s.shape.reduce(((e,t)=>e*t),1),l=1===o.shape.length?[i]:[o.shape[0],i],p=t.makeOutput(l,s.dtype);function d(e){return t.dataIdMap.get(e.dataId).id}return Me(d(o),new Uint8Array(new Int32Array(o.shape).buffer),o.shape.length,i,c,d(s),r[s.dtype],u,d(p)),p}};let Ee;const Ae={kernelName:o.OEe,backendName:"wasm",setupFunc:function(e){Ee=e.wasm.cwrap(o.OEe,null,["number","number","number","array","number","array","array","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{x:a}=n,{blockSize:s,dataFormat:i}=r,u=a.shape[0],c=("NHWC"===i?a.shape[1]:a.shape[2])*s,l=("NHWC"===i?a.shape[2]:a.shape[3])*s,p=("NHWC"===i?a.shape[3]:a.shape[1])/(s*s),d="NHWC"===i?[u,c,l,p]:[u,p,c,l],h=t.makeOutput(d,"float32"),f=t.dataIdMap.get(a.dataId).id,m=new Uint8Array(new Int32Array(o.euu.computeStrides(a.shape)).buffer),g=new Uint8Array(new Int32Array(d).buffer),y=new Uint8Array(new Int32Array(o.euu.computeStrides(d)).buffer),b=t.dataIdMap.get(h.dataId).id;return Ee(f,s,"NHWC"===i?1:0,m,a.shape.length-1,g,y,d.length,b),h}};let Fe;const De={kernelName:o.Fql,backendName:"wasm",setupFunc:function(e){Fe=e.wasm.cwrap(o.Fql,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s}=t,i=r.dataIdMap.get(a.dataId).id,u=r.dataIdMap.get(s.dataId).id,{strides:c,dilations:l,pad:p,dimRoundingMode:d}=n,h=null==l?[1,1]:l,f=o.cxb.computeConv2DInfo(a.shape,s.shape,c,h,p,d,!0),m=f.filterHeight,g=f.filterWidth,y=f.padInfo.top,b=f.padInfo.right,w=f.padInfo.bottom,v=f.padInfo.left,k=f.dilationHeight,x=f.dilationWidth,_=f.strideHeight,I=f.strideWidth,S=f.inChannels,N=f.outChannels,M="SAME"===f.padInfo.type?1:0;if("channelsLast"!==f.dataFormat)throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${f.dataFormat}'. 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pt={kernelName:o.UV,backendName:"wasm",setupFunc:function(e){lt=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:a}=e,{x:s,indices:i}=n,{axis:u,batchDims:c}=a,l=o.euu.parseAxisParam(u,s.shape)[0],p=t.readSync(i.dataId),d=s.shape[l];for(let e=0;e<p.length;++e){const t=p[e];o.euu.assert(t<=d-1&&t>=0,(()=>`GatherV2: the index value ${t} is not in [0, ${d-1}]`))}const h=o.cxb.segment_util.collectGatherOpShapeInfo(s,i,l,c),f=U({inputs:{x:s},attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]},backend:t}),m=o.euu.sizeFromShape(i.shape),g=U({inputs:{x:i},attrs:{shape:[h.batchSize,m/h.batchSize]},backend:t}),y=[h.batchSize,h.outerSize,m/h.batchSize,h.sliceSize],b=t.makeOutput(y,s.dtype);if(0===o.euu.sizeFromShape(s.shape))return b;const w=f.shape.length-1,v=t.dataIdMap.get(f.dataId).id,k=t.dataIdMap.get(g.dataId).id,x=t.dataIdMap.get(b.dataId).id,_=new Uint8Array(new Int32Array(o.euu.computeStrides(f.shape)).buffer),I=new Uint8Array(new Int32Array(o.euu.computeStrides(y)).buffer);return lt(v,r[s.dtype],_,w,k,h.batchSize,I,x),t.disposeData(f.dataId),t.disposeData(g.dataId),b.shape=h.outputShape,b}},dt=d(o.o3B,0,"bool"),ht=d(o.QD,0,"bool"),ft=u(o.iwm,"bool"),mt=u(o.aMl,"bool"),gt=u(o.OiK,"bool");let yt;const bt={kernelName:o.Mb$,backendName:"wasm",setupFunc:function(e){yt=e.wasm.cwrap(o.Mb$,null,["number","number","number","number"])},kernelFunc:function(e){const{inputs:{x:t},attrs:{alpha:n},backend:a}=e,s=a.dataIdMap.get(t.dataId).id,i=a.makeOutput(t.shape,"float32");if(0!==o.euu.sizeFromShape(t.shape)){const e=a.dataIdMap.get(i.dataId).id;yt(s,r[t.dtype],n,e)}return i}},wt=d(o.GoJ,0,"bool"),vt=d(o.SMP,0,"bool");let kt;const xt={kernelName:o.Kst,backendName:"wasm",setupFunc:function(e){kt=e.wasm.cwrap(o.Kst,null,["number","number","number","number"])},kernelFunc:function(e){const{attrs:t,backend:n}=e,{start:r,stop:a,num:o}=t,s=Math.floor(o),i=n.makeOutput([s],"float32");return kt(n.dataIdMap.get(i.dataId).id,r,a,s),i}},_t=u(o.qwJ),It=u(o.eg6),St=d(o.SSA,0,"bool"),Nt=u(o._S1),Mt=d(o.whD,0,"bool"),Tt=d(o.cnd,0,"bool");let Et;const At={kernelName:o.wfw,backendName:"wasm",setupFunc:function(e){Et=e.wasm.cwrap(o.wfw,null,["number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:o,bias:s,alpha:i,beta:u}=r;if("float32"!==a.dtype)throw new Error("LRN error: x must have dtype float32");const c=n.makeOutput(a.shape,a.dtype);return Et(n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(c.dataId).id,a.shape[3],o,s,i,u),c}};let Ft;const Dt={kernelName:o.SAF,backendName:"wasm",setupFunc:function(e){Ft=e.wasm.cwrap(o.SAF,null,["number","number","number","number","number","number","number","number","number"])},kernelFunc:function(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;if("float32"!==a.dtype||"float32"!==o.dtype||"float32"!==s.dtype)throw new Error("LRNGrad error: x, y, and dy must have dtype float32");const p=n.makeOutput(a.shape,a.dtype);return Ft(n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(o.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(p.dataId).id,s.shape[3],i,u,c,l),p}};let Ot;const Ct={kernelName:o.aUJ,backendName:"wasm",setupFunc:function(e){Ot=e.wasm.cwrap(o.aUJ,null,["number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:a}=e,{reductionIndices:s,keepDims:i}=a,{x:u}=n;let c=t.dataIdMap.get(u.dataId).id,l=u;const{transposed:p,axes:d,originalAxes:h,inputWasTransposed:f}=k(u,s,t);f&&(l=p,c=t.dataIdMap.get(p.dataId).id);const m=l.shape.length;o.cxb.assertAxesAreInnerMostDims("max",d,m);const[g,y]=o.cxb.computeOutAndReduceShapes(l.shape,d),b=o.euu.sizeFromShape(y),w=t.makeOutput(g,u.dtype);if(0!==o.euu.sizeFromShape(l.shape)){const e=t.dataIdMap.get(w.dataId).id;Ot(c,r[u.dtype],b,e)}if(f&&t.disposeData(p.dataId),i){const e=o.cxb.expandShapeToKeepDim(w.shape,h);w.shape=e}return w}},Pt=d(o.qik);let Rt;const $t={kernelName:o.MNi,backendName:"wasm",setupFunc:function(e){Rt=e.wasm.cwrap(o.MNi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,attrs:n,backend:r}=e,a=t.x,s=r.dataIdMap.get(a.dataId).id;o.euu.assert("float32"===a.dtype,(()=>`Error in MaxPool: only float32 input is supported. Got ${a.dtype}.`));const{filterSize:i,strides:u,pad:c,dimRoundingMode:l}=n,p=o.cxb.computePool2DInfo(a.shape,i,u,1,c,l),d=p.filterHeight,h=p.filterWidth,f=p.padInfo.top,m=p.padInfo.right,g=p.padInfo.bottom,y=p.padInfo.left,b=p.dilationHeight,w=p.dilationWidth,v=p.strideHeight,k=p.strideWidth,x=p.inChannels,_=p.outChannels;if("channelsLast"!==p.dataFormat)throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);const I=r.makeOutput(p.outShape,"float32"),S=r.dataIdMap.get(I.dataId).id;return Rt(s,a.shape[0],a.shape[1],a.shape[2],d,h,f,m,g,y,b,w,v,k,x,_,S),I}};let Lt;const Wt={kernelName:o.C4i,backendName:"wasm",setupFunc:function(e){Lt=e.wasm.cwrap("MaxPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:u,dimRoundingMode:c,dataFormat:l}=r,p=o.cxb.computePool3DInfo(a.shape,s,i,1,u,c,l),d=n.makeOutput(p.outShape,a.dtype);return Lt(n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),d}};let zt;const Bt={kernelName:o.amh,backendName:"wasm",setupFunc:function(e){zt=e.wasm.cwrap("MaxPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,{filterSize:i,strides:u,pad:c,dimRoundingMode:l}=r,p=o.cxb.computePool3DInfo(s.shape,i,u,1,c,l),d=n.makeOutput(s.shape,s.dtype);return zt(n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),d}};let Ut;const Ht={kernelName:o.AdS,backendName:"wasm",setupFunc:function(e){Ut=e.wasm.cwrap("MaxPoolGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,{filterSize:i,strides:u,pad:c,dimRoundingMode:l}=r,p=o.cxb.computePool2DInfo(s.shape,i,u,1,c,l),d=n.makeOutput(s.shape,s.dtype);return Ut(n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.top,p.padInfo.left),d}};let Vt;const Gt={kernelName:o.yqo,backendName:"wasm",setupFunc:function(e){Vt=e.wasm.cwrap("MaxPoolWithArgmax",null,["number","number","number","number","boolean","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:a}=e,{x:s}=t,{filterSize:i,strides:u,pad:c,includeBatchInIndex:l}=a;o.euu.assert(4===s.shape.length,(()=>`Error in maxPool: input must be rank 4 but got rank ${s.shape.length}.`));const p=[1,1];o.euu.assert(o.cxb.eitherStridesOrDilationsAreOne(u,p),(()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${u} and dilations '${p}'`));const d=o.cxb.computePool2DInfo(s.shape,i,u,[1,1],c),h=n.makeOutput(d.outShape,s.dtype),f=n.makeOutput(d.outShape,"int32");return Vt(n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(h.dataId).id,n.dataIdMap.get(f.dataId).id,r[s.dtype],l,d.batchSize,d.inChannels,d.inHeight,d.inWidth,d.outHeight,d.outWidth,d.strideHeight,d.strideWidth,d.dilationHeight,d.dilationWidth,d.effectiveFilterHeight,d.effectiveFilterWidth,d.padInfo.top,d.padInfo.left),[h,f]}};let qt;const jt={kernelName:o.iN$,backendName:"wasm",setupFunc:function(e){qt=e.wasm.cwrap(o.iN$,null,["number, number, number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{axis:a,keepDims:s}=r,{x:i}=n,u=t.dataIdMap.get(i.dataId).id;let c=u,l=i;const{transposed:p,axes:d,originalAxes:h,inputWasTransposed:f}=k(i,a,t);let m=d;if(f){const e=t.dataIdMap.get(p.dataId).id;e!==u&&(l=p,c=e,m=o.cxb.getInnerMostAxes(m.length,l.shape.length))}o.cxb.assertAxesAreInnerMostDims("mean",m,l.shape.length);const[g,y]=o.cxb.computeOutAndReduceShapes(l.shape,m),b=o.euu.sizeFromShape(y);let w=l;"float32"!==l.dtype&&(w=ee({backend:t,inputs:{x:l},attrs:{dtype:"float32"}}),c=t.dataIdMap.get(w.dataId).id);const v=t.makeOutput(g,"float32");if(0!==o.euu.sizeFromShape(l.shape)){const e=t.dataIdMap.get(v.dataId).id;qt(c,b,e)}if(f&&t.disposeData(p.dataId),s){const e=o.cxb.expandShapeToKeepDim(v.shape,h);v.shape=e}return"float32"!==l.dtype&&t.disposeData(w.dataId),v}};let Kt;const Qt={kernelName:o.WW2,backendName:"wasm",setupFunc:function(e){Kt=e.wasm.cwrap(o.WW2,null,["number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:a}=e,{axis:s,keepDims:i}=a,{x:u}=n,c=t.dataIdMap.get(u.dataId).id;let l=c,p=u;const{transposed:d,axes:h,originalAxes:f,inputWasTransposed:m}=k(u,s,t);if(m){const e=t.dataIdMap.get(d.dataId).id;e!==c&&(p=d,l=e)}const g=p.shape.length;o.cxb.assertAxesAreInnerMostDims("min",h,g);const[y,b]=o.cxb.computeOutAndReduceShapes(p.shape,h),w=o.euu.sizeFromShape(b),v=t.makeOutput(y,p.dtype);if(0!==o.euu.sizeFromShape(p.shape)){const e=t.dataIdMap.get(v.dataId).id;Kt(l,r[u.dtype],w,e)}if(m&&t.disposeData(d.dataId),i){const e=o.cxb.expandShapeToKeepDim(v.shape,f);v.shape=e}return v}},Yt=d(o.sly);var Jt;let Zt;!function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"}(Jt||(Jt={}));const Xt={kernelName:o.C6u,backendName:"wasm",kernelFunc:function(e){const{inputs:{x:t},backend:n,attrs:{paddings:a,mode:o}}=e,s=a.map(((e,n)=>e[0]+t.shape[n]+e[1])),i=n.dataIdMap.get(t.dataId).id,u=n.makeOutput(s,t.dtype),c=n.dataIdMap.get(u.dataId).id,l=new Uint8Array(new Int32Array(t.shape).buffer),p=a.map((e=>e[0])),d=a.map((e=>e[1])),h=new Uint8Array(new Int32Array(p).buffer),f=new Uint8Array(new Int32Array(d).buffer);return Zt(i,l,t.shape.length,r[t.dtype],h,f,Jt[o],c),u},setupFunc:function(e){Zt=e.wasm.cwrap(o.C6u,null,["number","array","number","number","array","array","number","number"])}};let en;function tn(e){const{backend:t,inputs:{logits:n},attrs:{dim:r}}=e,a=t.dataIdMap.get(n.dataId).id,s=t.makeOutput(n.shape,n.dtype),i=t.dataIdMap.get(s.dataId).id,u=n.shape[r],c=o.euu.sizeFromShape(n.shape)/u;return 0===o.euu.sizeFromShape(s.shape)||en(a,i,u,c),s}const nn={kernelName:o.a0o,backendName:"wasm",setupFunc:function(e){en=e.wasm.cwrap(o.a0o,null,["number","number","number","number"])},kernelFunc:tn};let rn;const an={kernelName:o.UdG,backendName:"wasm",setupFunc:function(e){rn=e.wasm.cwrap(o.UdG,null,["number","number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:o,seed:s,normalized:i}=r;if("float32"!==a.dtype)throw new Error(`Tensor logits must have dtype float32, got ${a.dtype}`);const u=i?a:tn({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),[c,l]=u.shape,p=n.makeOutput([c,o],"int32");return rn(n.dataIdMap.get(u.dataId).id,c,l,o,s,n.dataIdMap.get(p.dataId).id),i||n.disposeData(u.dataId),p}},on=d(o.InO),sn=d(o.SSu),un=u(o.yUy);function cn(e,t){const n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),r=n[0],a=n[1],o=n[2],s=n[3];return e.wasm._free(t),{pSelectedIndices:r,selectedSize:a,pSelectedScores:o,pValidOutputs:s}}let ln;const pn={kernelName:o.aaw,backendName:"wasm",setupFunc:function(e){ln=e.wasm.cwrap(o.aaw,"number",["number","number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:o,scoreThreshold:s}=r,{boxes:i,scores:u}=n,c=t.dataIdMap.get(i.dataId).id,l=t.dataIdMap.get(u.dataId).id,p=ln(c,l,o,a,s),{pSelectedIndices:d,selectedSize:h,pSelectedScores:f,pValidOutputs:m}=cn(t,p);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([h],"int32",d)}};let dn;const hn={kernelName:o.Q7n,backendName:"wasm",setupFunc:function(e){dn=e.wasm.cwrap(o.Q7n,"number",["number","number","number","number","number","bool"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:o,scoreThreshold:s,padToMaxOutputSize:i}=r,{boxes:u,scores:c}=n,l=t.dataIdMap.get(u.dataId).id,p=t.dataIdMap.get(c.dataId).id,d=dn(l,p,o,a,s,i),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=cn(t,d);return t.wasm._free(m),[t.makeOutput([f],"int32",h),t.makeOutput([],"int32",g)]}};let fn;const mn={kernelName:o.q82,backendName:"wasm",setupFunc:function(e){fn=e.wasm.cwrap(o.q82,"number",["number","number","number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:o,scoreThreshold:s,softNmsSigma:i}=r,{boxes:u,scores:c}=n,l=t.dataIdMap.get(u.dataId).id,p=t.dataIdMap.get(c.dataId).id,d=fn(l,p,o,a,s,i),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=cn(t,d);return t.wasm._free(g),[t.makeOutput([f],"int32",h),t.makeOutput([f],"float32",m)]}},gn=d(o.Ki5,0,"bool");let yn;const bn={kernelName:o.mon,backendName:"wasm",setupFunc:function(e){yn=e.wasm.cwrap(o.mon,null,["number","number","number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{dtype:o,depth:s,onValue:i,offValue:u}=r,c=n.makeOutput([...a.shape,s],o),l=n.dataIdMap.get(c.dataId).id,p=n.dataIdMap.get(a.dataId).id;return yn(p,s,i,u,l),c}},wn={kernelName:o.O_l,backendName:"wasm",kernelFunc:function(e){const{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(r).fill(1),r}},vn={kernelName:o.cJi,backendName:"wasm",kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(1===t.length)return je({inputs:{input:t[0]},backend:n,attrs:{dim:a}});const s=t[0].shape,i=t[0].dtype;t.forEach((e=>{o.euu.assertShapesMatch(s,e.shape,"All tensors passed to stack must have matching shapes"),o.euu.assert(i===e.dtype,(()=>"All tensors passed to stack must have matching dtypes"))}));const u=[],c=se({inputs:t.map((e=>{const t=je({inputs:{input:e},backend:n,attrs:{dim:a}});return u.push(t),t})),backend:n,attrs:{axis:a}});return u.forEach((e=>n.disposeData(e.dataId))),c}};let kn;const xn={kernelName:o.Q8A,backendName:"wasm",kernelFunc:function(e){const{inputs:{x:t},backend:n,attrs:{paddings:a,constantValue:s}}=e,i=a.map(((e,n)=>e[0]+t.shape[n]+e[1]));if(0===o.euu.sizeFromShape(t.shape))return Ye({backend:n,attrs:{shape:i,value:s,dtype:t.dtype}});const u=n.dataIdMap.get(t.dataId).id,c=n.makeOutput(i,t.dtype),l=n.dataIdMap.get(c.dataId).id,p=new Uint8Array(new Int32Array(t.shape).buffer),d=a.map((e=>e[0])),h=a.map((e=>e[1])),f=new Uint8Array(new Int32Array(d).buffer),m=new Uint8Array(new Int32Array(h).buffer);return kn(u,p,t.shape.length,r[t.dtype],f,m,s,l),c},setupFunc:function(e){kn=e.wasm.cwrap(o.Q8A,null,["number","array","number","number","array","array","number","number"])}},_n=d(o.sTH);let In;const Sn={kernelName:o.cBF,backendName:"wasm",setupFunc:function(e){In=e.wasm.cwrap(o.cBF,null,["number","number","number"])},kernelFunc:function(e){const{inputs:t,backend:n}=e,{x:r,alpha:a}=t,o=n.dataIdMap.get(r.dataId).id,s=n.dataIdMap.get(a.dataId).id;let i=o;const u=r;let c=u;"float32"!==u.dtype&&(c=ee({backend:n,inputs:{x:r},attrs:{dtype:"float32"}}),i=n.dataIdMap.get(c.dataId).id);const l=n.makeOutput(r.shape,"float32"),p=n.dataIdMap.get(l.dataId).id;return In(i,s,p),"float32"!==u.dtype&&n.disposeData(c.dataId),l}};let Nn;const Mn={kernelName:o.e_0,backendName:"wasm",setupFunc:function(e){Nn=e.wasm.cwrap(o.e_0,null,["number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:a}=e,{axis:s,keepDims:i}=a,{x:u}=n,c=t.dataIdMap.get(u.dataId).id;let l=c,p=u;const{transposed:d,axes:h,originalAxes:f,inputWasTransposed:m}=k(u,s,t);let g=h;if(m){const e=t.dataIdMap.get(d.dataId).id;e!==c&&(p=d,l=e,g=o.cxb.getInnerMostAxes(g.length,p.shape.length))}o.cxb.assertAxesAreInnerMostDims("prod",g,p.shape.length);const[y,b]=o.cxb.computeOutAndReduceShapes(p.shape,g),w=o.euu.sizeFromShape(b),v=t.makeOutput(y,p.dtype);if(0!==o.euu.sizeFromShape(p.shape)){const e=t.dataIdMap.get(v.dataId).id;Nn(l,w,r[v.dtype],e)}if(m&&t.disposeData(d.dataId),i){const e=o.cxb.expandShapeToKeepDim(v.shape,f);v.shape=e}return v}};var Tn=n(33996);const En={kernelName:o.EHu,backendName:"wasm",kernelFunc:e=>{const{backend:t,attrs:n}=e,{start:r,stop:a,step:o,dtype:s}=n,i=(0,Tn.S)(r,a,o,s),u=t.makeOutput([i.length],s);return t.typedArrayFromHeap(u).set(i),u}},An=d(o.uMf),Fn=u(o.Ezp),Dn=u(o.IHk),On=u(o.QwE);let Cn;const Pn={kernelName:o.qaT,backendName:"wasm",setupFunc:function(e){Cn=e.wasm.cwrap(o.qaT,null,["number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{images:a}=n,{alignCorners:s,halfPixelCenters:i,size:u}=r,[c,l]=u,[p,d,h,f]=a.shape,m=[p,c,l,f];let g,y=t.dataIdMap.get(a.dataId);"float32"!==y.dtype&&(g=ee({backend:t,inputs:{x:a},attrs:{dtype:"float32"}}),y=t.dataIdMap.get(g.dataId));const b=y.id,w=t.makeOutput(m,"float32");if(0===o.euu.sizeFromShape(a.shape))return w;const v=t.dataIdMap.get(w.dataId).id;return Cn(b,p,d,h,f,c,l,s?1:0,i?1:0,v),null!=g&&t.disposeData(g.dataId),w}};let Rn;const $n={kernelName:o.ewH,backendName:"wasm",setupFunc:function(e){Rn=e.wasm.cwrap(o.ewH,null,["number","number","number","array","array","boolean"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{images:a,dy:o}=t,{alignCorners:s}=r,i=n.makeOutput(a.shape,"float32");let u,c=n.dataIdMap.get(a.dataId);return"float32"!==c.dtype&&(u=ee({backend:n,inputs:{x:a},attrs:{dtype:"float32"}}),c=n.dataIdMap.get(u.dataId)),Rn(n.dataIdMap.get(a.dataId).id,n.dataIdMap.get(o.dataId).id,n.dataIdMap.get(i.dataId).id,new Uint8Array(new Int32Array(a.shape).buffer),new Uint8Array(new Int32Array(o.shape).buffer),s),null!=u&&n.disposeData(u.dataId),i}};let Ln;const Wn={kernelName:o.Co2,backendName:"wasm",setupFunc:function(e){Ln=e.wasm.cwrap(o.Co2,null,["number","number","number","number","number","number","number","number","number","number"])},kernelFunc:function(e){const{backend:t,inputs:n,attrs:r}=e,{images:a}=n,{alignCorners:s,halfPixelCenters:i,size:u}=r,[c,l]=u,[p,d,h,f]=a.shape,m=[p,c,l,f],g=t.makeOutput(m,"float32");if(0===o.euu.sizeFromShape(a.shape))return g;let y,b=t.dataIdMap.get(a.dataId);"float32"!==b.dtype&&(y=ee({backend:t,inputs:{x:a},attrs:{dtype:"float32"}}),b=t.dataIdMap.get(y.dataId));const w=b.id,v=t.dataIdMap.get(g.dataId).id;return Ln(w,p,d,h,f,c,l,s?1:0,i?1:0,v),null!=y&&t.disposeData(y.dataId),g}};let zn;const Bn={kernelName:o.WCE,backendName:"wasm",setupFunc:function(e){zn=e.wasm.cwrap(o.WCE,null,["number","number","number","array","array","boolean"])},kernelFunc:function(e){const{inputs:t,backend:n,attrs:r}=e,{images:a,dy:o}=t,{alignCorners:s}=r,i=n.makeOutput(a.shape,"float32");let 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2class r{constructor(e,t){this.backend=e,this.dataMover=t,this.data=new WeakMap,this.dataIdsCount=0}get(e){return this.data.has(e)||this.dataMover.moveData(this.backend,e),this.data.get(e)}set(e,t){this.dataIdsCount++,this.data.set(e,t)}has(e){return this.data.has(e)}delete(e){return this.dataIdsCount--,this.data.delete(e)}numDataIds(){return this.dataIdsCount}}class a{refCount(e){return o("refCount")}incRef(e){return o("incRef")}timerAvailable(){return!0}time(e){return o("time")}read(e){return o("read")}readSync(e){return o("readSync")}readToGPU(e,t){return o("readToGPU")}numDataIds(){return o("numDataIds")}disposeData(e,t){return o("disposeData")}write(e,t,n){return o("write")}move(e,t,n,r,a){return o("move")}createTensorFromGPUData(e,t,n){return o("createTensorFromGPUData")}memory(){return o("memory")}floatPrecision(){return o("floatPrecision")}epsilon(){return 32===this.floatPrecision()?1e-7:1e-4}dispose(){return o("dispose")}}function o(e){throw new Error(`'${e}' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen`)}},75941:function(e,t,n){"use strict";function r(e,t,n){const r=function(e,t,n){return function(e,t,n){let r=0,a=e.length,o=0,s=!1;for(;r<a;){o=r+(a-r>>>1);const i=n(t,e[o]);i>0?r=o+1:(a=o,s=!i)}return s?r:-r-1}(e,t,n||a)}(e,t,n),o=r<0?-(r+1):r;e.splice(o,0,t)}function a(e,t){return e>t?1:e<t?-1:0}function o(e,t,n,r,a){return u(e,t,n,r,a,0)}function s(e,t,n,r,a,o){return u(e,t,n,r,a,0,!1,o,!0)}function i(e,t,n,r,a,o){return u(e,t,n,r,a,o,!0)}function u(e,t,n,a,o,s,i=!1,u=!1,d=!1){const h=[];for(let e=0;e<t.length;e++)t[e]>o&&h.push({score:t[e],boxIndex:e,suppressBeginIndex:0});h.sort(p);const f=s>0?-.5/s:0,m=[],g=[];for(;m.length<n&&h.length>0;){const t=h.pop(),{score:n,boxIndex:s,suppressBeginIndex:i}=t;if(n<o)break;let u=!1;for(let n=m.length-1;n>=i;--n){const r=c(e,s,m[n]);if(r>=a){u=!0;break}if(t.score=t.score*l(a,f,r),t.score<=o)break}t.suppressBeginIndex=m.length,u||(t.score===n?(m.push(s),g.push(t.score)):t.score>o&&r(h,t,p))}const y=m.length,b=n-y;u&&b>0&&(m.push(...new Array(b).fill(0)),g.push(...new Array(b).fill(0)));const w={selectedIndices:m};return i&&(w.selectedScores=g),d&&(w.validOutputs=y),w}function c(e,t,n){const r=e.subarray(4*t,4*t+4),a=e.subarray(4*n,4*n+4),o=Math.min(r[0],r[2]),s=Math.min(r[1],r[3]),i=Math.max(r[0],r[2]),u=Math.max(r[1],r[3]),c=Math.min(a[0],a[2]),l=Math.min(a[1],a[3]),p=Math.max(a[0],a[2]),d=Math.max(a[1],a[3]),h=(i-o)*(u-s),f=(p-c)*(d-l);if(h<=0||f<=0)return 0;const m=Math.max(o,c),g=Math.max(s,l),y=Math.min(i,p),b=Math.min(u,d),w=Math.max(y-m,0)*Math.max(b-g,0);return w/(h+f-w)}function l(e,t,n){const r=Math.exp(t*n*n);return n<=e?r:0}function p(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}n.d(t,{Wm:function(){return o},Mf:function(){return s},eQ:function(){return i}})},13328:function(e,t,n){"use strict";n.d(t,{_:function(){return a}});var r=n(9653);function a(e,t){const n=[];for(let e=0;e<t.length;e++)t[e]&&n.push(e);const a=(0,r.c)(e,"int32"),o=(0,r.c)([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()}},31748:function(e,t,n){"use strict";n.d(t,{cL:function(){return v},Y$:function(){return w}});var r=n(82756),a=n(41920),o=n(18308),s=n(38128),i=n(28616),u=n(44327),c=n(10680),l=n(15952);class p{constructor(e,t){this.backendTimer=e,this.logger=t,null==t&&(this.logger=new h)}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=>{d(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;n.forEach((e=>{Promise.all([e.data(),r,o]).then((n=>{this.logger.logKernelProfile(t,e,n[0],n[1],a,n[2])}))}))}}function d(e,t,n){if("float32"!==t)return!1;for(let t=0;t<e.length;t++){const r=e[t];if(isNaN(r)||!isFinite(r))return console.warn(`Found ${r} in the result of '${n}'`),!0}return!1}class h{logKernelProfile(e,t,n,r,a,o){const s="number"==typeof r?l.Uf(`${r}ms`,9):r.error,i=l.Uf(e,25),u=t.rank,c=t.size,p=l.Uf(t.shape.toString(),14);let d="";for(const e in a){const n=a[e];if(null!=n){const r=n.shape||t.shape,a=r.length;d+=`${e}: ${a}D ${a>0?r:""} `}}console.log(`%c${i}\t%c${s}\t%c${u}D ${p}\t%c${c}\t%c${d}\t%c${o}

2`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}}var f=n(74364),m=n(4172);function g(e){return null!=e.kernelName}class y{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map((e=>e.name))))}}}dispose(){for(const e in this.registeredVariables)this.registeredVariables[e].dispose()}}class b{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new y}async ready(){if(null!=this.pendingBackendInit)return this.pendingBackendInit.then((()=>{}));if(null!=this.backendInstance)return;const e=this.getSortedBackends();for(let t=0;t<e.length;t++){const n=e[t];if(await this.initializeBackend(n).success)return void await this.setBackend(n)}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(null!=this.pendingBackendInit)throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);if(null==this.backendInstance){const{name:e,asyncInit:t}=this.initializeBackendsAndReturnBest();if(t)throw new Error(`The highest priority backend '${e}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(e)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(e){if(!(e in this.registry)){if(!(e in this.registryFactory))return null;{const{asyncInit:t}=this.initializeBackend(e);if(t)return null}}return this.registry[e]}findBackendFactory(e){return e in this.registryFactory?this.registryFactory[e].factory:null}registerBackend(e,t,n=1){return e in this.registryFactory?(u.m(`${e} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[e]={factory:t,priority:n},!0)}async setBackend(e){if(null==this.registryFactory[e])throw new Error(`Backend name '${e}' not found in registry`);

2if(this.backendName=e,null==this.registry[e]){this.backendInstance=null;const{success:t,asyncInit:n}=this.initializeBackend(e);if(!(n?await t:t))return!1}return this.backendInstance=this.registry[e],this.setupRegisteredKernels(),this.profiler=new p(this.backendInstance),!0}setupRegisteredKernels(){(0,i.Ww)(this.backendName).forEach((e=>{null!=e.setupFunc&&e.setupFunc(this.backendInstance)}))}disposeRegisteredKernels(e){(0,i.Ww)(e).forEach((t=>{null!=t.disposeFunc&&t.disposeFunc(this.registry[e])}))}initializeBackend(e){const t=this.registryFactory[e];if(null==t)throw new Error(`Cannot initialize backend ${e}, no registration found.`);try{const n=t.factory();if(!n||n instanceof r.qe||"function"!=typeof n.then)return this.registry[e]=n,{success:!0,asyncInit:!1};{const t=++this.pendingBackendInitId,r=n.then((n=>!(t<this.pendingBackendInitId||(this.registry[e]=n,this.pendingBackendInit=null,0)))).catch((n=>(t<this.pendingBackendInitId||(this.pendingBackendInit=null,u.m(`Initialization of backend ${e} failed`),u.m(n.stack||n.message)),!1)));return this.pendingBackendInit=r,{success:r,asyncInit:!0}}}catch(t){return u.m(`Initialization of backend ${e} failed`),u.m(t.stack||t.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(0===Object.keys(this.registryFactory).length)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort(((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority))}initializeBackendsAndReturnBest(){const e=this.getSortedBackends();for(let t=0;t<e.length;t++){const 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 instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n)))}scopedRun(e,t,n){e();try{const e=n();return t(),e}catch(e){throw t(),e}}nextTensorId(){return b.nextTensorId++}nextVariableId(){return b.nextVariableId++}clone(e){const t=v.runKernel(s.oPg,{x:e}),n={x:e};return this.addTapeNode(this.state.activeScope.name,n,[t],(e=>({x:()=>{const t={x:e};return v.runKernel(s.Utj,t,{dtype:"float32"})}})),[],{}),t}runKernel(e,t,n){if(null==this.backendName&&this.backend,null==(0,i.G)(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 '${e}'`)}runKernelFunc(e){let t,n=[];const r=this.isTapeOn(),a=this.state.numBytes,o=this.state.numTensors;let s,u;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0),null==this.backendName&&this.backend;const c=g(e)?e.kernelName:null!=this.state.activeScope?this.state.activeScope.name:"";if(g(e)){const{kernelName:t,inputs:a,attrs:o}=e;null==this.backendName&&this.backend;const c=(0,i.G)(t,this.backendName);l.Uc(null!=c,(()=>`Cannot find registered kernel '${t}' for backend '${this.backendName}'`)),s=()=>{const e=this.backend.numDataIds();

2u=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:d}=e,h=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,h,n,d),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.kx)(e);if(null!=r){const e=r.inputsToSave||[],a=r.outputsToSave||[];let o;r.saveAllInputs?(l.Uc(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.ct(e[0])&&(a=e.map((e=>c.encodeString(e))));const o=r.write(a,t,n),s=new f.w3(t,n,o,this.nextTensorId());if(this.trackTensor(s,r),"string"===n){const e=this.state.tensorInfo.get(o),t=(0,l.YX)(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.w3(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.QB(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.U1(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.QB||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.U1(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.kx)(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.K6(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.Ck)(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.Uc(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.Uc(a instanceof f.w3,(()=>"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.Do)((0,l.It)(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.eu(a.shape,s.shape))throw new Error(`Error in gradient for op ${o.kernelName}. The gradient of input '${t}' has shape '${a.shape}', which does not match the shape of the input '${s.shape}'`);if(null==e[s.id])e[s.id]=a;else{const t=e[s.id];e[s.id]=r(t,a),t.dispose()}}}}(e,o,(e=>this.tidy(e)),k);const r=t.map((t=>e[t.id]));return 0===this.state.gradientDepth&&(this.state.activeTape.forEach((e=>{for(const t of e.saved)t.dispose()})),this.state.activeTape=null),{value:a,grads:r}}))}customGrad(e){return l.Uc(l.mg(e),(()=>"The f passed in customGrad(f) must be a function.")),(...t)=>{let n;l.Uc(t.every((e=>e instanceof f.w3)),(()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors"));const r={};return t.forEach(((e,t)=>{r[t]=e})),this.runKernelFunc({forwardFunc:(r,a)=>(n=e(...t,a),l.Uc(n.value instanceof f.w3,(()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor")),l.Uc(l.mg(n.gradFunc),(()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function.")),n.value),backwardsFunc:(e,r)=>{const a=n.gradFunc(e,r),o=Array.isArray(a)?a:[a];l.Uc(o.length===t.length,(()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...).")),l.Uc(o.every((e=>e instanceof f.w3)),(()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors."));const s={};return o.forEach(((e,t)=>{s[t]=()=>e})),s},inputs:r})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}readToGPU(e,t){return this.state.tensorInfo.get(e).backend.readToGPU(e,t)}async time(e){const t=(0,c.now)(),n=await this.backend.time(e);return n.wallMs=(0,c.now)()-t,n}track(e){return null!=this.state.activeScope&&(e.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(e)),e}get registeredVariables(){return this.state.registeredVariables}reset(){this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new y;for(const e in this.registry)this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null}}function w(){const e=(0,o.M)();if(null==e._tfengine){const t=new a.Ih(e);e._tfengine=new b(t)}return(0,a.sn)(e._tfengine.ENV),(0,f.CE)((()=>e._tfengine)),e._tfengine}b.nextTensorId=0,b.nextVariableId=0;const v=w();function k(e,t){const n={a:e,b:t};return v.runKernel(s.OMN,n)}},41920:function(e,t,n){"use strict";n.d(t,{Ih:function(){return o},_K:function(){return i},sn:function(){return c}});var r=n(15952);const a="tfjsflags";class o{constructor(e){this.global=e,this.flags={},this.flagRegistry={},this.urlFlags={},this.getQueryParams=s,this.populateURLFlags()}setPlatform(e,t){null!=this.platform&&(i().getBool("IS_TEST")||i().getBool("PROD")||console.warn(`Platform ${this.platformName} has already been set. 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2for(let t=33;t<63;t++)e[t]=2147483648+(t-32<<23);return e}(),n=function(){const e=new Uint32Array(64);for(let t=0;t<64;t++)e[t]=1024;return e[0]=e[32]=0,e}();return r=>{const a=new ArrayBuffer(4*r.length),o=new Uint32Array(a);for(let a=0;a<r.length;a++){const s=r[a],i=e[n[s>>10]+(1023&s)]+t[s>>10];o[a]=i}return new Float32Array(a)}}class C{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return null==C.instance&&(C.instance=new C),C.instance}static registerSaveRouter(e){C.getInstance().saveRouters.push(e)}static registerLoadRouter(e){C.getInstance().loadRouters.push(e)}static getSaveHandlers(e){return C.getHandlers(e,"save")}static getLoadHandlers(e,t){return C.getHandlers(e,"load",t)}static getHandlers(e,t,n){const r=[];return("load"===t?C.getInstance().loadRouters:C.getInstance().saveRouters).forEach((t=>{const a=t(e,n);null!==a&&r.push(a)})),r}}const P=e=>C.registerSaveRouter(e),R=e=>C.registerLoadRouter(e),$=e=>C.getSaveHandlers(e),L=(e,t)=>C.getLoadHandlers(e,t),W="tensorflowjs",z="models_store",B="model_info_store";function U(){if(!(0,p._K)().getBool("IS_BROWSER"))throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");const e="undefined"==typeof window?self:window,t=e.indexedDB||e.mozIndexedDB||e.webkitIndexedDB||e.msIndexedDB||e.shimIndexedDB;if(null==t)throw new Error("The current browser does not appear to support IndexedDB.");return t}function H(e){const t=e.result;t.createObjectStore(z,{keyPath:"modelPath"}),t.createObjectStore(B,{keyPath:"modelPath"})}class V{constructor(e){if(this.indexedDB=U(),null==e||!e)throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");this.modelPath=e}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");return this.databaseAction(this.modelPath,e)}async load(){return this.databaseAction(this.modelPath)}databaseAction(e,t){return new Promise(((e,n)=>{const r=this.indexedDB.open(W,1);r.onupgradeneeded=()=>H(r),r.onsuccess=()=>{const a=r.result;if(null==t){const t=a.transaction(z,"readonly"),r=t.objectStore(z).get(this.modelPath);r.onsuccess=()=>{if(null==r.result)return a.close(),n(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));e(r.result.modelArtifacts)},r.onerror=e=>(a.close(),n(r.error)),t.oncomplete=()=>a.close()}else{t.weightData=b.join(t.weightData);const r=F(t),o=a.transaction(B,"readwrite");let s,i,u=o.objectStore(B);try{s=u.put({modelPath:this.modelPath,modelArtifactsInfo:r})}catch(e){return n(e)}s.onsuccess=()=>{i=a.transaction(z,"readwrite");const s=i.objectStore(z);let c;try{c=s.put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:r})}catch(e){return n(e)}c.onsuccess=()=>e({modelArtifactsInfo:r}),c.onerror=e=>{u=o.objectStore(B);const t=u.delete(this.modelPath);t.onsuccess=()=>(a.close(),n(c.error)),t.onerror=e=>(a.close(),n(c.error))}},s.onerror=e=>(a.close(),n(s.error)),o.oncomplete=()=>{null==i?a.close():i.oncomplete=()=>a.close()}}},r.onerror=e=>n(r.error)}))}}V.URL_SCHEME="indexeddb://";const G=e=>{return(0,p._K)().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(V.URL_SCHEME)?(t=e.slice(V.URL_SCHEME.length),new V(t)):null;var t};C.registerSaveRouter(G),C.registerLoadRouter(G);class q{constructor(){this.indexedDB=U()}async listModels(){return new Promise(((e,t)=>{const n=this.indexedDB.open(W,1);n.onupgradeneeded=()=>H(n),n.onsuccess=()=>{const r=n.result,a=r.transaction(B,"readonly"),o=a.objectStore(B).getAll();o.onsuccess=()=>{const t={};for(const e of o.result)t[e.modelPath]=e.modelArtifactsInfo;e(t)},o.onerror=e=>(r.close(),t(o.error)),a.oncomplete=()=>r.close()},n.onerror=e=>t(n.error)}))}async removeModel(e){var t;return e=(t=e).startsWith(V.URL_SCHEME)?t.slice(V.URL_SCHEME.length):t,new Promise(((t,n)=>{const r=this.indexedDB.open(W,1);r.onupgradeneeded=()=>H(r),r.onsuccess=()=>{const a=r.result,o=a.transaction(B,"readwrite"),s=o.objectStore(B),i=s.get(e);let u;i.onsuccess=()=>{if(null==i.result)return a.close(),n(new Error(`Cannot find model with path '${e}' in IndexedDB.`));{const r=s.delete(e),o=()=>{u=a.transaction(z,"readwrite");const r=u.objectStore(z).delete(e);r.onsuccess=()=>t(i.result.modelArtifactsInfo),r.onerror=e=>n(i.error)};r.onsuccess=o,r.onerror=e=>(o(),a.close(),n(i.error))}},i.onerror=e=>(a.close(),n(i.error)),o.oncomplete=()=>{null==u?a.close():u.oncomplete=()=>a.close()}},r.onerror=e=>n(r.error)}))}}const j="/",K="tensorflowjs_models",Q="info",Y="model_topology",J="weight_specs",Z="weight_data",X="model_metadata";function ee(e){return{info:[K,e,Q].join(j),topology:[K,e,Y].join(j),weightSpecs:[K,e,J].join(j),weightData:[K,e,Z].join(j),modelMetadata:[K,e,X].join(j)}}function te(e){for(const t of Object.values(e))window.localStorage.removeItem(t)}function ne(e){const t=e.split(j);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(j)}

2class re{constructor(e){if(!(0,p._K)().getBool("IS_BROWSER")||"undefined"==typeof window||void 0===window.localStorage)throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,null==e||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=ee(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{const t=JSON.stringify(e.modelTopology),n=JSON.stringify(e.weightSpecs),r=F(e),a=b.join(e.weightData);try{this.LS.setItem(this.keys.info,JSON.stringify(r)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,function(e){if(I)return w.from(e).toString("base64");const t=new Uint8Array(e);let n="";for(let e=0,r=t.length;e<r;e++)n+=String.fromCharCode(t[e]);return btoa(n)}(a));const o={format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,signature:null!=e.signature?e.signature:void 0,userDefinedMetadata:null!=e.userDefinedMetadata?e.userDefinedMetadata:void 0,modelInitializer:null!=e.modelInitializer?e.modelInitializer:void 0,initializerSignature:null!=e.initializerSignature?e.initializerSignature:void 0,trainingConfig:null!=e.trainingConfig?e.trainingConfig:void 0};return this.LS.setItem(this.keys.modelMetadata,JSON.stringify(o)),{modelArtifactsInfo:r}}catch(e){throw te(this.keys),new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${r.modelTopologyBytes}, weightSpecsBytes=${r.weightSpecsBytes}, weightDataBytes=${r.weightDataBytes}.`)}}}async load(){const e=JSON.parse(this.LS.getItem(this.keys.info));if(null==e)throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);if("JSON"!==e.modelTopologyType)throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");const t={},n=JSON.parse(this.LS.getItem(this.keys.topology));if(null==n)throw new Error(`In local storage, the topology of model '${this.modelPath}' is missing.`);t.modelTopology=n;const r=JSON.parse(this.LS.getItem(this.keys.weightSpecs));if(null==r)throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);t.weightSpecs=r;const a=this.LS.getItem(this.keys.modelMetadata);if(null!=a){const e=JSON.parse(a);t.format=e.format,t.generatedBy=e.generatedBy,t.convertedBy=e.convertedBy,null!=e.signature&&(t.signature=e.signature),null!=e.userDefinedMetadata&&(t.userDefinedMetadata=e.userDefinedMetadata),null!=e.modelInitializer&&(t.modelInitializer=e.modelInitializer),null!=e.initializerSignature&&(t.initializerSignature=e.initializerSignature),null!=e.trainingConfig&&(t.trainingConfig=e.trainingConfig)}const o=this.LS.getItem(this.keys.weightData);if(null==o)throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);return t.weightData=function(e){if(I){const t=w.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 n.buffer}(o),t}}re.URL_SCHEME="localstorage://";const ae=e=>{return(0,p._K)().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(re.URL_SCHEME)?(t=e.slice(re.URL_SCHEME.length),new re(t)):null;var t};C.registerSaveRouter(ae),C.registerLoadRouter(ae);class oe{constructor(){(0,m.Uc)((0,p._K)().getBool("IS_BROWSER"),(()=>"Current environment is not a web browser")),(0,m.Uc)("undefined"==typeof window||void 0!==window.localStorage,(()=>"Current browser does not appear to support localStorage")),this.LS=window.localStorage}async listModels(){const e={},t=K+j,n=j+Q;for(let r=0;r<this.LS.length;++r){const a=this.LS.key(r);a.startsWith(t)&&a.endsWith(n)&&(e[ne(a)]=JSON.parse(this.LS.getItem(a)))}return e}async removeModel(e){var t;const n=ee(e=(t=e).startsWith(re.URL_SCHEME)?t.slice(re.URL_SCHEME.length):t);if(null==this.LS.getItem(n.info))throw new Error(`Cannot find model at path '${e}'`);const r=JSON.parse(this.LS.getItem(n.info));return te(n),r}}const se="://";class ie{constructor(){this.managers={}}static getInstance(){return null==ie.instance&&(ie.instance=new ie),ie.instance}static registerManager(e,t){(0,m.Uc)(null!=e,(()=>"scheme must not be undefined or null.")),e.endsWith(se)&&(e=e.slice(0,e.indexOf(se))),(0,m.Uc)(e.length>0,(()=>"scheme must not be an empty string."));const n=ie.getInstance();(0,m.Uc)(null==n.managers[e],(()=>`A model store manager is already registered for scheme '${e}'.`)),n.managers[e]=t}static getManager(e){const t=ie.getInstance().managers[e];if(null==t)throw new Error(`Cannot find model manager for scheme '${e}'`);return t}static getSchemes(){return 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2S)(this.iterations_,"int32")}}async getWeights(){throw new Error("getWeights() is not implemented for this optimizer yet.")}async setWeights(e){throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}}Object.defineProperty($e,Symbol.hasInstance,{value:e=>null!=e.minimize&&null!=e.computeGradients&&null!=e.applyGradients});var Le=n(86381),We=n(94380),ze=n(90256),Be=n(84320),Ue=n(50032);class He extends $e{static get className(){return"SGD"}constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=Array.isArray(e)?e[n].tensor:e[t];if(null==r)return;const a=l.cL.registeredVariables[t];(0,_e.G6)((()=>{const e=(0,Ie.W)((0,Ne.E)(this.c,r),a);a.assign(e)}))})),this.incrementIterations()}setLearningRate(e){this.learningRate=e,null!=this.c&&this.c.dispose(),this.c=(0,_e.Oi)((0,Fe.S)(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(0!==(e=await this.extractIterations(e)).length)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}}const Ve=[class extends $e{static get className(){return"Adadelta"}constructor(e,t,n=null){super(),this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],null==n&&(this.epsilon=l.cL.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=l.cL.registeredVariables[t];null==this.accumulatedGrads[n]&&(this.accumulatedGrads[n]={originalName:`${t}/accum_grad`,variable:(0,_e.G6)((()=>(0,Ee.E)(r).variable(!1)))}),null==this.accumulatedUpdates[n]&&(this.accumulatedUpdates[n]={originalName:`${t}/accum_var`,variable:(0,_e.G6)((()=>(0,Ee.E)(r).variable(!1)))});const a=Array.isArray(e)?e[n].tensor:e[t];if(null==a)return;const o=this.accumulatedGrads[n].variable,s=this.accumulatedUpdates[n].variable;(0,_e.G6)((()=>{const e=(0,Ie.W)((0,Ne.E)(o,this.rho),(0,Ne.E)((0,Te.Q)(a),1-this.rho)),t=(0,Ne.E)((0,Se.M)((0,Me._)((0,Ie.W)(s,this.epsilon)),(0,Me._)((0,Ie.W)(o,this.epsilon))),a),n=(0,Ie.W)((0,Ne.E)(s,this.rho),(0,Ne.E)((0,Te.Q)(t),1-this.rho));o.assign(e),s.assign(n);const i=(0,Ie.W)((0,Ne.E)(t,-this.learningRate),r);r.assign(i)}))})),this.incrementIterations()}dispose(){null!=this.accumulatedUpdates&&((0,_e.Mt)(this.accumulatedGrads.map((e=>e.variable))),(0,_e.Mt)(this.accumulatedUpdates.map((e=>e.variable))))}async getWeights(){const e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map((e=>({name:e.originalName,tensor:e.variable}))))}async setWeights(e){const t=(e=await this.extractIterations(e)).length/2;this.accumulatedGrads=e.slice(0,t).map((e=>({originalName:e.name,variable:e.tensor.variable(!1)}))),this.accumulatedUpdates=e.slice(t,2*t).map((e=>({originalName:e.name,variable:e.tensor.variable(!1)})))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}},class extends $e{static get className(){return"Adagrad"}constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=l.cL.registeredVariables[t];if(null==this.accumulatedGrads[n]){const e=!1;this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:(0,_e.G6)((()=>(0,Le.y)(r.shape,this.initialAccumulatorValue).variable(e)))}}const a=Array.isArray(e)?e[n].tensor:e[t];if(null==a)return;const o=this.accumulatedGrads[n].variable;(0,_e.G6)((()=>{const e=(0,Ie.W)(o,(0,Te.Q)(a));o.assign(e);const t=(0,Ie.W)((0,Ne.E)((0,Se.M)(a,(0,Me._)((0,Ie.W)(e,l.cL.backend.epsilon()))),-this.learningRate),r);r.assign(t)}))})),this.incrementIterations()}dispose(){null!=this.accumulatedGrads&&(0,_e.Mt)(this.accumulatedGrads.map((e=>e.variable)))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map((e=>({name:e.originalName,tensor:e.variable}

2))))}async setWeights(e){e=await this.extractIterations(e),this.accumulatedGrads=e.map((e=>({originalName:e.name,variable:e.tensor.variable(!1)})))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}},class extends $e{static get className(){return"Adam"}constructor(e,t,n,r=null){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],(0,_e.G6)((()=>{this.accBeta1=(0,Fe.S)(t).variable(),this.accBeta2=(0,Fe.S)(n).variable()})),null==r&&(this.epsilon=l.cL.backend.epsilon())}applyGradients(e){const t=Array.isArray(e)?e.map((e=>e.name)):Object.keys(e);(0,_e.G6)((()=>{const n=(0,ze.A)(1,this.accBeta1),r=(0,ze.A)(1,this.accBeta2);t.forEach(((t,a)=>{const o=l.cL.registeredVariables[t];null==this.accumulatedFirstMoment[a]&&(this.accumulatedFirstMoment[a]={originalName:`${t}/m`,variable:(0,_e.G6)((()=>(0,Ee.E)(o).variable(!1)))}),null==this.accumulatedSecondMoment[a]&&(this.accumulatedSecondMoment[a]={originalName:`${t}/v`,variable:(0,_e.G6)((()=>(0,Ee.E)(o).variable(!1)))});const s=Array.isArray(e)?e[a].tensor:e[t];if(null==s)return;const i=this.accumulatedFirstMoment[a].variable,u=this.accumulatedSecondMoment[a].variable,c=(0,Ie.W)((0,Ne.E)(i,this.beta1),(0,Ne.E)(s,1-this.beta1)),p=(0,Ie.W)((0,Ne.E)(u,this.beta2),(0,Ne.E)((0,Te.Q)(s),1-this.beta2)),d=(0,Se.M)(c,n),h=(0,Se.M)(p,r);i.assign(c),u.assign(p);const f=(0,Ie.W)((0,Ne.E)((0,Se.M)(d,(0,Ie.W)((0,Me._)(h),this.epsilon)),-this.learningRate),o);o.assign(f)})),this.accBeta1.assign((0,Ne.E)(this.accBeta1,this.beta1)),this.accBeta2.assign((0,Ne.E)(this.accBeta2,this.beta2))})),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),null!=this.accumulatedFirstMoment&&(0,_e.Mt)(this.accumulatedFirstMoment.map((e=>e.variable))),null!=this.accumulatedSecondMoment&&(0,_e.Mt)(this.accumulatedSecondMoment.map((e=>e.variable)))}async getWeights(){const e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map((e=>({name:e.originalName,tensor:e.variable}))))}async setWeights(e){e=await this.extractIterations(e),(0,_e.G6)((()=>{this.accBeta1.assign((0,We.g)(this.beta1,this.iterations_+1)),this.accBeta2.assign((0,We.g)(this.beta2,this.iterations_+1))}));const t=e.length/2;this.accumulatedFirstMoment=e.slice(0,t).map((e=>({originalName:e.name,variable:e.tensor.variable(!1)}))),this.accumulatedSecondMoment=e.slice(t,2*t).map((e=>({originalName:e.name,variable:e.tensor.variable(!1)})))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}},class extends $e{static get className(){return"Adamax"}constructor(e,t,n,r=null,a=0){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.decay=a,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],(0,_e.G6)((()=>{this.iteration=(0,Fe.S)(0).variable(),this.accBeta1=(0,Fe.S)(t).variable()})),null==r&&(this.epsilon=l.cL.backend.epsilon())}applyGradients(e){const t=Array.isArray(e)?e.map((e=>e.name)):Object.keys(e);(0,_e.G6)((()=>{const n=(0,ze.A)(1,this.accBeta1),r=(0,Se.M)(-this.learningRate,(0,Ie.W)((0,Ne.E)(this.iteration,this.decay),1));t.forEach(((t,a)=>{const o=l.cL.registeredVariables[t];null==this.accumulatedFirstMoment[a]&&(this.accumulatedFirstMoment[a]={originalName:`${t}/m`,variable:(0,Ee.E)(o).variable(!1)}),null==this.accumulatedWeightedInfNorm[a]&&(this.accumulatedWeightedInfNorm[a]={originalName:`${t}/v`,variable:(0,Ee.E)(o).variable(!1)});const s=Array.isArray(e)?e[a].tensor:e[t];if(null==s)return;const i=this.accumulatedFirstMoment[a].variable,u=this.accumulatedWeightedInfNorm[a].variable,c=(0,Ie.W)((0,Ne.E)(i,this.beta1),(0,Ne.E)(s,1-this.beta1)),p=(0,Ne.E)(u,this.beta2),d=(0,Be.a)(s),h=(0,Ue.W)(p,d);i.assign(c),u.assign(h);const f=(0,Ie.W)((0,Ne.E)((0,Se.M)(r,n),(0,Se.M)(c,(0,Ie.W)(h,this.epsilon))),o);o.assign(f)})),this.iteration.assign((0,Ie.W)(this.iteration,1)),this.accBeta1.assign((0,Ne.E)(this.accBeta1,this.beta1))})),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),null!=this.accumulatedFirstMoment&&(0,_e.Mt)(this.accumulatedFirstMoment.map((e=>e.variable))),null!=this.accumulatedWeightedInfNorm&&(0,_e.Mt)(this.accumulatedWeightedInfNorm.map((e=>e.variable)))}async getWeights(){throw new Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}},class extends He{static get className(){return"Momentum"}constructor(e,t,n=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=(0,Fe.

2S)(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=l.cL.registeredVariables[t];if(null==this.accumulations[n]){const e=!1;this.accumulations[n]={originalName:`${t}/momentum`,variable:(0,_e.G6)((()=>(0,Ee.E)(r).variable(e)))}}const a=this.accumulations[n].variable,o=Array.isArray(e)?e[n].tensor:e[t];null!=o&&(0,_e.G6)((()=>{let e;const t=(0,Ie.W)((0,Ne.E)(this.m,a),o);e=this.useNesterov?(0,Ie.W)((0,Ne.E)(this.c,(0,Ie.W)(o,(0,Ne.E)(t,this.m))),r):(0,Ie.W)((0,Ne.E)(this.c,t),r),a.assign(t),r.assign(e)}))})),this.incrementIterations()}dispose(){this.m.dispose(),null!=this.accumulations&&(0,_e.Mt)(this.accumulations.map((e=>e.variable)))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map((e=>({name:e.originalName,tensor:e.variable}))))}async setWeights(e){e=await this.extractIterations(e),this.accumulations=e.map((e=>({originalName:e.name,variable:e.tensor.variable(!1)})))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}},class extends $e{static get className(){return"RMSProp"}constructor(e,t=.9,n=0,r=null,a=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=n,this.epsilon=r,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=a,null==r&&(this.epsilon=l.cL.backend.epsilon()),null==e)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map((e=>e.name)):Object.keys(e)).forEach(((t,n)=>{const r=l.cL.registeredVariables[t],a=!1;null==this.accumulatedMeanSquares[n]&&(this.accumulatedMeanSquares[n]={originalName:`${t}/rms`,variable:(0,_e.G6)((()=>(0,Ee.E)(r).variable(a)))}),null==this.accumulatedMoments[n]&&(this.accumulatedMoments[n]={originalName:`${t}/momentum`,variable:(0,_e.G6)((()=>(0,Ee.E)(r).variable(a)))}),null==this.accumulatedMeanGrads[n]&&this.centered&&(this.accumulatedMeanGrads[n]={originalName:`${t}/mg`,variable:(0,_e.G6)((()=>(0,Ee.E)(r).variable(a)))});const o=Array.isArray(e)?e[n].tensor:e[t];if(null==o)return;const s=this.accumulatedMeanSquares[n].variable,i=this.accumulatedMoments[n].variable;(0,_e.G6)((()=>{const e=(0,Ie.W)((0,Ne.E)(s,this.decay),(0,Ne.E)((0,Te.Q)(o),1-this.decay));if(this.centered){const t=this.accumulatedMeanGrads[n].variable,a=(0,Ie.W)((0,Ne.E)(t,this.decay),(0,Ne.E)(o,1-this.decay)),u=(0,Se.M)((0,Ne.E)(o,this.learningRate),(0,Me._)((0,ze.A)(e,(0,Ie.W)((0,Te.Q)(a),this.epsilon)))),c=(0,Ie.W)((0,Ne.E)(i,this.momentum),u);s.assign(e),t.assign(a),i.assign(c);const l=(0,ze.A)(r,c);r.assign(l)}else{const e=(0,Ie.W)((0,Ne.E)(s,this.decay),(0,Ne.E)((0,Te.Q)(o),1-this.decay)),t=(0,Ie.W)((0,Ne.E)(i,this.momentum),(0,Se.M)((0,Ne.E)(o,this.learningRate),(0,Me._)((0,Ie.W)(e,this.epsilon))));s.assign(e),i.assign(t);const n=(0,ze.A)(r,t);r.assign(n)}}))})),this.incrementIterations()}dispose(){null!=this.accumulatedMeanSquares&&(0,_e.Mt)(this.accumulatedMeanSquares.map((e=>e.variable))),null!=this.accumulatedMeanGrads&&this.centered&&(0,_e.Mt)(this.accumulatedMeanGrads.map((e=>e.variable))),null!=this.accumulatedMoments&&(0,_e.Mt)(this.accumulatedMoments.map((e=>e.variable)))}async getWeights(){const e=[...this.accumulatedMeanSquares,...this.accumulatedMoments];return this.centered&&e.push(...this.accumulatedMeanGrads),[await this.saveIterations()].concat(e.map((e=>({name:e.originalName,tensor:e.variable}))))}async setWeights(e){e=await this.extractIterations(e);const t=this.centered?e.length/3:e.length/2,n=!1;this.accumulatedMeanSquares=e.slice(0,t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)}))),this.accumulatedMoments=e.slice(t,2*t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)}))),this.centered&&(this.accumulatedMeanGrads=e.slice(2*t,3*t).map((e=>({originalName:e.name,variable:e.tensor.variable(n)}))))}getConfig(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}}static fromConfig(e,t){return new e(t.learningRate,t.decay,t.momentum,t.epsilon,t.centered)}},He];function Ge(e){return new Promise((e=>setTimeout(e))).then(e)}

2class qe{constructor(e){if(!(0,p._K)().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(qe.URL_SCHEME)&&(e=e.slice(qe.URL_SCHEME.length)),null!=e&&0!==e.length||(e="model"),this.modelJsonFileName=e+".json",this.weightDataFileName=e+".weights.bin"}async save(e){if("undefined"==typeof document)throw new Error("Browser downloads are not supported in this environment since `document` is not present");const t=b.join(e.weightData),n=window.URL.createObjectURL(new Blob([t],{type:"application/octet-stream"}));if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");{const t=T(e,[{paths:["./"+this.weightDataFileName],weights:e.weightSpecs}]),r=window.URL.createObjectURL(new Blob([JSON.stringify(t)],{type:"application/json"})),a=null==this.modelJsonAnchor?document.createElement("a"):this.modelJsonAnchor;if(a.download=this.modelJsonFileName,a.href=r,await Ge((()=>a.dispatchEvent(new MouseEvent("click")))),null!=e.weightData){const e=null==this.weightDataAnchor?document.createElement("a"):this.weightDataAnchor;e.download=this.weightDataFileName,e.href=n,await Ge((()=>e.dispatchEvent(new MouseEvent("click"))))}return{modelArtifactsInfo:F(e)}}}}qe.URL_SCHEME="downloads://";class je{constructor(e){if(null==e||e.length<1)throw new Error(`When calling browserFiles, at least 1 file is required, but received ${e}`);this.jsonFile=e[0],this.weightsFiles=e.slice(1)}async load(){return new Promise(((e,t)=>{const n=new FileReader;n.onload=n=>{const r=JSON.parse(n.target.result),a=r.modelTopology;if(null==a)return void t(new Error(`modelTopology field is missing from file ${this.jsonFile.name}`));if(null==r.weightsManifest)return void t(new Error(`weightManifest field is missing from file ${this.jsonFile.name}`));if(0===this.weightsFiles.length)return void e({modelTopology:a});const o=A(r,(e=>this.loadWeights(e)));e(o)},n.onerror=e=>t(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),n.readAsText(this.jsonFile)}))}loadWeights(e){const t=[],n=[];for(const r of e)t.push(...r.weights),n.push(...r.paths);const r=this.checkManifestAndWeightFiles(e),a=n.map((e=>this.loadWeightsFile(e,r[e])));return Promise.all(a).then((e=>[t,e]))}loadWeightsFile(e,t){return new Promise(((n,r)=>{const a=new FileReader;a.onload=e=>{const t=e.target.result;n(t)},a.onerror=t=>r(`Failed to weights data from file of path '${e}'.`),a.readAsArrayBuffer(t)}))}checkManifestAndWeightFiles(e){const t=[],n=this.weightsFiles.map((e=>M(e.name))),r={};for(const a of e)a.paths.forEach((e=>{const a=M(e);if(-1!==t.indexOf(a))throw new Error(`Duplicate file basename found in weights manifest: '${a}'`);if(t.push(a),-1===n.indexOf(a))throw new Error(`Weight file with basename '${a}' is not provided.`);r[e]=this.weightsFiles[n.indexOf(a)]}));if(t.length!==this.weightsFiles.length)throw new Error(`Mismatch in the number of files in weights manifest (${t.length}) and the number of weight files provided (${this.weightsFiles.length}).`);return r}}function Ke(e){return new je(e)}function Qe(e,t,n,r){!function(e){(0,m.Uc)(null!=e&&Array.isArray(e)&&e.length>0,(()=>"promises must be a none empty array"))}(e),function(e,t){(0,m.Uc)(e>=0&&e<=1,(()=>`Progress fraction must be in range [0, 1], but got startFraction ${e}`)),(0,m.Uc)(t>=0&&t<=1,(()=>`Progress fraction must be in range [0, 1], but got endFraction ${t}`)),(0,m.Uc)(t>=e,(()=>`startFraction must be no more than endFraction, but got startFraction ${e} and endFraction ${t}`))}(n=null==n?0:n,r=null==r?1:r);let a=0;return Promise.all(e.map((o=>(o.then((o=>{const s=n+ ++a/e.length*(r-n);return t(s),o})),o))))}async function Ye(e,t){null==t&&(t={});const n=null==t.fetchFunc?(0,p._K)().platform.fetch:t.fetchFunc,r=e.map((e=>n(e,t.requestInit,{isBinary:!0}))),a=(null==t.onProgress?await Promise.all(r):await Qe(r,t.onProgress,0,.5)).map((e=>e.arrayBuffer()));return null==t.onProgress?await Promise.all(a):await Qe(a,t.onProgress,.5,1)}async function Je(e,t="",n,r){return Ze((e=>Ye(e,{requestInit:r}

2)))(e,t,n)}function Ze(e){return async(t,n="",r)=>{const a=t.map((()=>!1)),o={},s=null!=r?r.map((()=>!1)):[],i=[];if(t.forEach(((e,t)=>{let n=0;e.weights.forEach((e=>{const u="quantization"in e?e.quantization.dtype:e.dtype,c=g[u]*m.It(e.shape),l=()=>{a[t]=!0,null==o[t]&&(o[t]=[]),o[t].push({manifestEntry:e,groupOffset:n,sizeBytes:c})};null!=r?r.forEach(((t,n)=>{t===e.name&&(l(),s[n]=!0)})):l(),i.push(e.name),n+=c}))})),!s.every((e=>e))){const e=r.filter(((e,t)=>!s[t]));throw new Error(`Could not find weights in manifest with names: ${e.join(", ")}. \nManifest JSON has weights with names: ${i.join(", ")}.`)}const u=a.reduce(((e,t,n)=>(t&&e.push(n),e)),[]),c=[];u.forEach((e=>{t[e].paths.forEach((e=>{const t=n+(n.endsWith("/")?"":"/")+e;c.push(t)}))}));const l=await e(c),p={};let d=0;return u.forEach((e=>{const n=t[e].paths.length,r=new b(l.slice(d,d+n));o[e].forEach((e=>{const t=x(r.slice(e.groupOffset,e.groupOffset+e.sizeBytes),[e.manifestEntry]);for(const e in t)p[e]=t[e]})),d+=n})),p}}C.registerSaveRouter((e=>(0,p._K)().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(qe.URL_SCHEME)?function(e="model"){return new qe(e)}(e.slice(qe.URL_SCHEME.length)):null));class Xe{constructor(e,t){if(this.DEFAULT_METHOD="POST",null==t&&(t={}),this.weightPathPrefix=t.weightPathPrefix,this.onProgress=t.onProgress,this.weightUrlConverter=t.weightUrlConverter,null!=t.fetchFunc?((0,m.Uc)("function"==typeof t.fetchFunc,(()=>"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)")),this.fetch=t.fetchFunc):this.fetch=(0,p._K)().platform.fetch,(0,m.Uc)(null!=e&&e.length>0,(()=>"URL path for http must not be null, undefined or empty.")),Array.isArray(e)&&(0,m.Uc)(2===e.length,(()=>`URL paths for http must have a length of 2, (actual length is ${e.length}).`)),this.path=e,null!=t.requestInit&&null!=t.requestInit.body)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=t.requestInit||{}}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");const t=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);t.body=new FormData;const n=T(e,[{paths:["./model.weights.bin"],weights:e.weightSpecs}]);if(t.body.append("model.json",new Blob([JSON.stringify(n)],{type:"application/json"}),"model.json"),null!=e.weightData){const n=b.join(e.weightData);t.body.append("model.weights.bin",new Blob([n],{type:"application/octet-stream"}),"model.weights.bin")}const r=await this.fetch(this.path,t);if(r.ok)return{modelArtifactsInfo:F(e),responses:[r]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${r.status}.`)}async load(){const e=await this.fetch(this.path,this.requestInit);if(!e.ok)throw new Error(`Request to ${this.path} failed with status code ${e.status}. Please verify this URL points to the model JSON of the model to load.`);let t;try{t=await e.json()}catch(e){let t=`Failed to parse model JSON of response from ${this.path}.`;throw this.path.endsWith(".pb")?t+=" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.":t+=" Please make sure the server is serving valid JSON for this request.",new Error(t)}const n=t.modelTopology,r=t.weightsManifest;if(null==n&&null==r)throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);return A(t,(e=>this.loadWeights(e)))}async loadWeights(e){const t=Array.isArray(this.path)?this.path[1]:this.path,[n,r]=function(e){const t=e.lastIndexOf("/"),n=e.lastIndexOf("?");return[e.substring(0,t)+"/",n>t?e.substring(n):""]}(t),a=this.weightPathPrefix||n,o=D(e),s=[],i=[];for(const t of e)for(const e of t.paths)null!=this.weightUrlConverter?i.push(this.weightUrlConverter(e)):s.push(a+e+r);return this.weightUrlConverter&&s.push(...await Promise.all(i)),[o,await Ye(s,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress})]}}function et(e){return null!=e.match(Xe.URL_SCHEME_REGEX)}Xe.URL_SCHEME_REGEX=/^https?:\/\//;const tt=(e,t)=>{if("undefined"==typeof fetch&&(null==t||null==t.fetchFunc))return null;{let n=!0;if(n=Array.isArray(e)?e.every((e=>et(e))):et(e),n)return nt(e,t)}return null};function nt(e,t){return new Xe(e,t)}function rt(e,t){return nt(e,t)}C.registerSaveRouter(tt),C.registerLoadRouter(tt);class at{constructor(e){this.modelArtifacts=e}load(){return this.modelArtifacts}}

2class ot{constructor(e){this.saveHandler=e}save(e){return this.saveHandler(e)}}class st{constructor(e){e.load&&(this.load=()=>Promise.resolve(e.load())),e.save&&(this.save=t=>Promise.resolve(e.save(t)))}}function it(e,t,n,r){return new st(ut(...arguments))}function ut(e,t,n,r){return 1===arguments.length?null!=e.modelTopology||null!=e.weightSpecs?new at(e):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new at({modelTopology:e})):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new at({modelTopology:e,weightSpecs:t,weightData:n,trainingConfig:r}))}function ct(e){return new ot(e)}function lt(e){return new ot(e)}var pt=n(74144),dt=n(38128),ht=n(28616),ft=n(72180),mt=n(17336),gt=n(9556);let yt,bt=!1;function wt(e,t=3){if(t>4)throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");if(null==e)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let n=!1,r=!1,a=!1,o=!1,s=!1,i=!1;if(e.data instanceof Uint8Array)n=!0;else if("undefined"!=typeof ImageData&&e instanceof ImageData)r=!0;else if("undefined"!=typeof HTMLVideoElement&&e instanceof HTMLVideoElement)a=!0;else if("undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement)o=!0;else if(null!=e.getContext)s=!0;else{if(!("undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap))throw new Error(`pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was ${e.constructor.name}`);i=!0}if(null!=(0,ht.G)(dt.QjT,l.cL.backendName)){const n={pixels:e},r={numChannels:t};return l.cL.runKernel(dt.QjT,n,r)}const[u,c]=a?[e.videoWidth,e.videoHeight]:[e.width,e.height];let p,d;if(s)p=e.getContext("2d").getImageData(0,0,u,c).data;else if(r||n)p=e.data;else if(o||a||i){if(null==yt)if("undefined"==typeof document){if("undefined"==typeof OffscreenCanvas||"undefined"==typeof OffscreenCanvasRenderingContext2D)throw new Error("Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.");yt=new OffscreenCanvas(1,1).getContext("2d")}else yt=document.createElement("canvas").getContext("2d",{willReadFrequently:!0});yt.canvas.width=u,yt.canvas.height=c,yt.drawImage(e,0,0,u,c),p=yt.getImageData(0,0,u,c).data}if(4===t)d=new Int32Array(p);else{const e=u*c;d=new Int32Array(e*t);for(let n=0;n<e;n++)for(let e=0;e<t;++e)d[n*t+e]=p[4*n+e]}const h=[c,u,t];return(0,gt.A)(d,h,"int32")}async function vt(e,t=3){let n=null;if((0,p._K)().getBool("WRAP_TO_IMAGEBITMAP")&&function(e){return"undefined"!=typeof window&&"undefined"!=typeof ImageBitmap&&window.hasOwnProperty("createImageBitmap")&&!(e instanceof ImageBitmap)&&function(e){return null!=e&&0!==e.width&&0!==e.height}(e)&&!function(e){return null!=e&&e.data instanceof Uint8Array}(e)}(e)){let t;try{t=await createImageBitmap(e,{premultiplyAlpha:"none"})}catch(e){t=null}n=null!=t&&t.width===e.width&&t.height===e.height?t:e}else n=e;return wt(n,t)}function kt(e){if(2!==e.rank&&3!==e.rank)throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${e.rank}.`);const t=2===e.rank?1:e.shape[2];if(t>4||2===t)throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${t}`);if("float32"!==e.dtype&&"int32"!==e.dtype)throw new Error(`Unsupported type for toPixels: ${e.dtype}. Please use float32 or int32 tensors.`)}async function xt(e,t){let n=(0,ft.ay)(e,"img","toPixels");if(!(e instanceof ke.w3)){const e=n;n=(0,be.W)(e,"int32"),e.dispose()}kt(n);const[r,a]=n.shape.slice(0,2),o=2===n.rank?1:n.shape[2],s=await n.data(),i="float32"===n.dtype?255:1,u=new Uint8ClampedArray(a*r*4);for(let e=0;e<r*a;++e){const t=[0,0,0,255];for(let r=0;r<o;r++){const a=s[e*o+r];

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2function Yn(e,t,n){if((0,d.Qn)(e),null!=t&&6!==t.length)throw new Error("tensor6d() requires shape to have six numbers");const r=(0,i._y)(e,n);if(6!==r.length&&1!==r.length)throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");if(1===r.length&&null==t)throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");return t=t||r,(0,Vn.e)(e,t,r,n)}var Jn=n(65e3);const Zn=(0,u.op)({tensorScatterUpdate_:function(e,t,n){const r=(0,i.ay)(e,"tensor","tensorScatterupdate"),a=(0,i.ay)(t,"indices","tensorScatterupdate","int32"),u=(0,i.ay)(n,"updates","tensorScatterupdate");if(Jn.validateInput(u,a,r.shape),r.dtype!==u.dtype)throw new Error(`tensor and updates must have the same dtype, instead they are ${r.dtype} and ${u.dtype}.`);const c={tensor:r,indices:a,updates:u};return o.cL.runKernel(s.EBb,c,{})}}),Xn=(0,u.op)({topk_:function(e,t=1,n=!0){const r=(0,i.ay)(e,"x","topk");if(0===r.rank)throw new Error("topk() expects the input to be of rank 1 or higher");const a=r.shape[r.shape.length-1];if(t<0)throw new Error(`'k' passed to topk() must be >= 0 but got ${t}`);if(t>a)throw new Error(`'k' passed to topk() must be <= the last dimension (${a}) but got ${t}`);const u={x:r},c={k:t,sorted:n},[l,p]=o.cL.runKernel(s.iIN,u,c);return{values:l,indices:p}}}),er=(0,u.op)({truncatedNormal_:function(e,t=0,n=1,r,a){if((0,d.Ix)(e),null!=r&&"bool"===r)throw new Error("Unsupported data type $ { dtype }");const o=new en(t,n,r,!0,a),s=(0,q.c)(e,r);for(let e=0;e<s.values.length;e++)s.values[e]=o.nextValue();return s.toTensor()}}),tr=(0,u.op)({unique_:function(e,t=0){const n=(0,i.ay)(e,"x","unique","string_or_numeric");(0,d.Uc)(n.rank>0,(()=>"The input tensor must be at least 1D"));const r={x:n},a={axis:t},[u,c]=o.cL.runKernel(s.Kyi,r,a);return{values:u,indices:c}}}),nr=(0,u.op)({unsortedSegmentSum_:function(e,t,n){const r=(0,i.ay)(e,"x","unsortedSegmentSum"),a=(0,i.ay)(t,"segmentIds","unsortedSegmentSum","int32");(0,d.Uc)((0,d.EH)(n),(()=>"numSegments must be of dtype int"));const u={x:r,segmentIds:a},c={numSegments:n};return o.cL.runKernel(s.imz,u,c)}}),rr=(0,u.op)({unstack_:function(e,t=0){const n=(0,i.ay)(e,"x","unstack","string_or_numeric");d.Uc(t>=-n.shape.length&&t<n.shape.length,(()=>`Axis = ${t} is not in [-${n.shape.length}, ${n.shape.length})`));const r={value:n},a={axis:t};return o.cL.runKernel(s.YZK,r,a)}});function ar(e,t){return bt(e,t,"right")}function or(e,t=!0,n,r){return o.cL.makeVariable(e,t,n,r)}var sr=n(13328);const ir=async function(e){const t=(0,i.ay)(e,"condition","whereAsync","bool"),n=await t.data(),r=(0,sr._)(t.shape,n);

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2,wr=(0,u.op)({conv2DBackpropFilter_:function(e,t,n,r,a,i="NHWC",u){let c=e;3===e.rank&&(c=(0,N.O)(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;3===l.rank&&(l=(0,N.O)(t,[1,t.shape[0],t.shape[1],t.shape[2]])),d.Uc(4===c.rank,(()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${c.shape}.`)),d.Uc(4===l.rank,(()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`)),d.Uc(4===n.length,(()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${n}.`));const p="NHWC"===i?c.shape[3]:c.shape[1],h="NHWC"===i?l.shape[3]:l.shape[1];d.Uc(p===n[2],(()=>`Error in conv2dDerFilter: depth of input ${p}) must match input depth in filter (${n[2]}.`)),d.Uc(h===n[3],(()=>`Error in conv2dDerFilter: depth of dy (${h}) must match output depth for filter (${n[3]}).`)),S.YV("conv2dDerFilter",a,u);const f={x:c,dy:l},m={strides:r,pad:a,dataFormat:i,dimRoundingMode:u,filterShape:n};return o.cL.runKernel(s.OHx,f,m)}});var vr=n(46120);const kr=(0,u.op)({fusedConv2d_:function({x:e,filter:t,strides:n,pad:r,dataFormat:a="NHWC",dilations:u=[1,1],dimRoundingMode:c,bias:l,activation:h="linear",preluActivationWeights:f,leakyreluAlpha:m}){if(h=h||"linear",!1===(0,vr.M$)(o.cL.state.gradientDepth,h)){d.Uc("NHWC"===a,(()=>`Error in fused conv2d: got dataFormat of ${a} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`));let o=te(e,t,n,r,a,u,c);return null!=l&&(o=(0,p.W)(o,l)),(0,vr.il)(o,h,f,m)}const g=(0,i.ay)(e,"x","conv2d","float32"),y=(0,i.ay)(t,"filter","conv2d","float32");let b=g,w=!1;3===g.rank&&(w=!0,b=(0,N.O)(g,[1,g.shape[0],g.shape[1],g.shape[2]])),d.Uc(4===b.rank,(()=>`Error in fused conv2d: input must be rank 4, but got rank ${b.rank}.`)),d.Uc(4===y.rank,(()=>`Error in fused conv2d: filter must be rank 4, but got rank ${y.rank}.`)),S.YV("fused conv2d",r,c);const v="NHWC"===a?b.shape[3]:b.shape[1];d.Uc(y.shape[2]===v,(()=>`Error in conv2d: depth of input (${v}) must match input depth for filter ${y.shape[2]}.`)),d.Uc(S.uo(n,u),(()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${u}'`));

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2const Rr=(0,u.op)({nonMaxSuppression_:function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){const u=(0,i.ay)(e,"boxes","nonMaxSuppression","float32"),c=(0,i.ay)(t,"scores","nonMaxSuppression","float32"),l=Pr(u,c,n,r,a),p={maxOutputSize:n=l.maxOutputSize,iouThreshold:r=l.iouThreshold,scoreThreshold:a=l.scoreThreshold};return o.cL.runKernel(s.aaw,{boxes:u,scores:c},p)}});var $r=n(75941);const Lr=(0,u.op)({nonMaxSuppressionWithScore_:function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,u=0){const c=(0,i.ay)(e,"boxes","nonMaxSuppression"),l=(0,i.ay)(t,"scores","nonMaxSuppression"),p=Pr(c,l,n,r,a,u),d={boxes:c,scores:l},h={maxOutputSize:n=p.maxOutputSize,iouThreshold:r=p.iouThreshold,scoreThreshold:a=p.scoreThreshold,softNmsSigma:u=p.softNmsSigma},f=o.cL.runKernel(s.q82,d,h);return{selectedIndices:f[0],selectedScores:f[1]}}}),Wr=(0,u.op)({nonMaxSuppressionPadded_:function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,u=!1){const c=(0,i.ay)(e,"boxes","nonMaxSuppression"),l=(0,i.ay)(t,"scores","nonMaxSuppression"),p=Pr(c,l,n,r,a,null),d={boxes:c,scores:l},h={maxOutputSize:p.maxOutputSize,iouThreshold:p.iouThreshold,scoreThreshold:p.scoreThreshold,padToMaxOutputSize:u},f=o.cL.runKernel(s.Q7n,d,h);return{selectedIndices:f[0],validOutputs:f[1]}}}),zr=(0,u.op)({resizeBilinear_:function(e,t,n=!1,r=!1){const a=(0,i.ay)(e,"images","resizeBilinear");d.Uc(3===a.rank||4===a.rank,(()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${a.rank}.`)),d.Uc(2===t.length,(()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`)),d.Uc(!1===r||!1===n,(()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false."));let u=a,c=!1;3===a.rank&&(c=!0,u=(0,N.O)(a,[1,a.shape[0],a.shape[1],a.shape[2]]));const[]=t,l={images:u},p={alignCorners:n,halfPixelCenters:r,size:t},h=o.cL.runKernel(s.qaT,l,p);return c?(0,N.O)(h,[h.shape[1],h.shape[2],h.shape[3]]):h}}),Br=(0,u.op)({resizeNearestNeighbor_:function(e,t,n=!1,r=!1){const a=(0,i.ay)(e,"images","resizeNearestNeighbor");d.Uc(3===a.rank||4===a.rank,(()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${a.rank}.`)),d.Uc(2===t.length,(()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`)),d.Uc("float32"===a.dtype||"int32"===a.dtype,(()=>"`images` must have `int32` or `float32` as dtype")),d.Uc(!1===r||!1===n,(()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false."));let u=a,c=!1;3===a.rank&&(c=!0,u=(0,N.O)(a,[1,a.shape[0],a.shape[1],a.shape[2]]));const[]=t,l={images:u},p={alignCorners:n,halfPixelCenters:r,size:t},h=o.cL.runKernel(s.Co2,l,p);return c?(0,N.O)(h,[h.shape[1],h.shape[2],h.shape[3]]):h}}

2),Ur=(0,u.op)({threshold_:function(e,t="binary",n=!1,r=.5){const a=(0,i.ay)(e,"image","threshold"),o=a.shape[0]*a.shape[1];let s,u,c,l,h=(0,D.E)(Gn([r]),255);if(d.Uc(3===a.rank,(()=>`Error in threshold: image must be rank 3,but got rank ${a.rank}.`)),d.Uc(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.Uc("int32"===a.dtype||"float32"===a.dtype,(()=>`Error in dtype: image dtype must be int32 or float32,but got dtype ${a.dtype}.`)),d.Uc("otsu"===t||"binary"===t,(()=>`Method must be binary or otsu, but was ${t}`)),3===a.shape[2]){[s,u,c]=Pn(a,[1,1,1],-1);const e=(0,D.E)(s,.2989),t=(0,D.E)(u,.587),n=(0,D.E)(c,.114);l=(0,p.W)((0,p.W)(e,t),n)}else l=e;"otsu"===t&&(h=function(e,t){let n,r,a,o,s,i,u=Gn([-1]),c=Gn([0]),l=Gn([0]);for(let d=0;d<e.size-1;d++){n=C(e,0,d+1),r=C(e,d+1),s=(0,ye.M)((0,Pe.o)(n),t),i=(0,ye.M)((0,Pe.o)(r),t);const h=(0,Pe.o)((0,D.E)(n,cn(0,n.size)));a=(0,ye.M)(h,(0,Pe.o)(n));const f=(0,K.y)(r.shape,n.size),m=(0,p.W)(cn(0,r.size),f),g=(0,D.E)(r,m);o=(0,ye.M)((0,Pe.o)(g),(0,Pe.o)(r));const y=(0,lt.A)(a,o),b=(0,lt.A)(a,o),w=(0,D.E)(s,i);l=(0,D.E)((0,D.E)(w,y),b);const v=je(l,c);c=ve(v,l,c),u=ve(v,Gn([d]),u)}return u}(U((0,I.W)(wn(l),"int32"),(0,Hn.m)([]),256),o));const f=n?tt(l,h):je(l,h);return(0,I.W)((0,D.E)(f,255),"int32")}}),Hr=(0,u.op)({transform_:function(e,t,n="nearest",r="constant",a=0,u){const c=(0,i.ay)(e,"image","transform","float32"),l=(0,i.ay)(t,"transforms","transform","float32");d.Uc(4===c.rank,(()=>`Error in transform: image must be rank 4,but got rank ${c.rank}.`)),d.Uc(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.Uc(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:a,outputShape:u};return o.cL.runKernel(s.wjp,p,h)}}),Vr=(0,u.op)({bandPart_:function(e,t,n){const r=(0,i.ay)(e,"a","bandPart");(0,d.Uc)(r.rank>=2,(()=>`bandPart(): Rank must be at least 2, got ${r.rank}.`));const a=r.shape,[o,s]=r.shape.slice(-2);let u,c;"number"==typeof t?((0,d.Uc)(t%1==0,(()=>`bandPart(): numLower must be an integer, got ${t}.`)),(0,d.Uc)(t<=o,(()=>`bandPart(): numLower (${t}) must not be greater than the number of rows (${o}).`)),u=(0,i.ay)(t<0?o:t,"numLower","bandPart")):((0,d.Uc)("int32"===t.dtype,(()=>"bandPart(): numLower's dtype must be an int32.")),u=ve(et(t,0),o,Et(t,o))),"number"==typeof n?((0,d.Uc)(n%1==0,(()=>`bandPart(): numUpper must be an integer, got ${n}.`)),(0,d.Uc)(n<=s,(()=>`bandPart(): numUpper (${n}) must not be greater than the number of columns (${s}).`)),c=(0,i.ay)(n<0?s:n,"numUpper","bandPart")):((0,d.Uc)("int32"===n.dtype,(()=>"bandPart(): numUpper's dtype must be an int32.")),c=ve(et(n,0),s,Et(n,s)));const l=(0,N.O)(cn(0,o,1,"int32"),[-1,1]),p=cn(0,s,1,"int32"),h=(0,lt.A)(l,p),f=ht(tt(h,u),Ke(h,it(c))),m=St([o,s],r.dtype);return(0,N.O)(Wn(rr((0,N.O)(r,[-1,o,s])).map((e=>ve(f,e,m)))),a)}}),Gr=(0,u.op)({gramSchmidt_:function(e){let t;if(Array.isArray(e)){t=!1,(0,d.Uc)(null!=e&&e.length>0,(()=>"Gram-Schmidt process: input must not be null, undefined, or empty"));const n=e[0].shape[0];for(let t=1;t<e.length;++t)(0,d.Uc)(e[t].shape[0]===n,(()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[t].shape[0]} vs. ${n})`))}else t=!0,e=Pn(e,e.shape[0],0).map((e=>Ln(e,[0])));(0,d.Uc)(e.length<=e[0].shape[0],(()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`));const n=[],r=e;for(let t=0;t<e.length;++t)n.push(o.cL.tidy((()=>{let e=r[t];if(t>0)for(let r=0;r<t;++r){const t=(0,D.E)((0,Pe.o)((0,D.E)(n[r],e)),n[r]);e=(0,lt.A)(e,t)}return(0,ye.M)(e,$e(e,"euclidean"))})));return t?Wn(n,0):n}});function qr(e,t=!1){return o.cL.tidy((()=>{(0,d.Uc)(2===e.shape.length,(()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`));const n=e.shape[0],r=e.shape[1];let a=He(n),s=(0,E.c)(e);const i=qn([[1]],[1,1]);let u=(0,E.c)(i);const c=n>=r?r:n;for(let e=0;e<c;++e){const t=s,c=u,l=a;[u,s,a]=o.cL.tidy((()=>{const t=C(s,[e,e],[n-e,1]),o=$e(t),c=C(s,[e,e],[1,1]),l=ve(je(c,0),qn([[-1]]),qn([[1]])),p=(0,lt.A)(c,(0,D.E)(l,o)),d=(0,ye.M)(t,p);u=1===d.shape[0]?(0,E.c)(i):A([i,C(d,[1,0],[d.shape[0]-1,d.shape[1]])],0);const h=it((0,ye.M)(F(l,p),o)),f=C(s,[e,0],[n-e,r]),m=(0,D.E)(h,u),g=lr(u);if(0===e)s=(0,lt.A)(f,F(m,F(g,f)));else{const t=(0,lt.A)(f,F(m,F(g,f)));s=A([C(s,[0,0],[e,r]),t],0)}const y=lr(m),b=C(a,[0,e],[n,a.shape[1]-e]);if(0===e)a=(0,lt.A)(b,F(F(b,u),y));else{const t=(0,lt.A)(b,F(F(b,u),y));a=A([C(a,[0,0],[n,e]),t],1)}return[u,s,a]})),(0,cr.Mt)([t,c,l])}return!t&&n>r&&(a=C(a,[0,0],[n,r]),s=C(s,[0,0],[r,r])),[a,s]}))}

2const jr=(0,u.op)({qr_:function(e,t=!1){if((0,d.Uc)(e.rank>=2,(()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`)),2===e.rank)return qr(e,t);{const n=e.shape.slice(0,e.shape.length-2).reduce(((e,t)=>e*t)),r=rr((0,N.O)(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),a=[],o=[];return r.forEach((e=>{const[n,r]=qr(e,t);a.push(n),o.push(r)})),[(0,N.O)(Wn(a,0),e.shape),(0,N.O)(Wn(o,0),e.shape)]}}});var Kr;!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"}(Kr||(Kr={}));const Qr=(0,u.op)({computeWeightedLoss_:function(e,t,n=Kr.SUM_BY_NONZERO_WEIGHTS){const r=(0,i.ay)(e,"losses","computeWeightedLoss");let a=null;null!=t&&(a=(0,i.ay)(t,"weights","computeWeightedLoss"));const o=null==a?r:(0,D.E)(r,a);if(n===Kr.NONE)return o;if(n===Kr.SUM)return(0,Pe.o)(o);if(n===Kr.MEAN){if(null==a)return It(o);{const e=r.size/a.size,t=(0,ye.M)((0,Pe.o)(o),(0,Pe.o)(a));return e>1?(0,ye.M)(t,(0,De.S)(e)):t}}if(n===Kr.SUM_BY_NONZERO_WEIGHTS){if(null==a)return(0,ye.M)((0,Pe.o)(o),(0,De.S)(r.size));{const e=(0,D.E)(a,Nt(r.shape)),t=(0,I.W)((0,Pe.o)(Pt(e,(0,De.S)(0))),"float32");return(0,ye.M)((0,Pe.o)(o),t)}}throw Error(`Unknown reduction: ${n}`)}}),Yr=(0,u.op)({absoluteDifference_:function(e,t,n,r=Kr.SUM_BY_NONZERO_WEIGHTS){const o=(0,i.ay)(e,"labels","absoluteDifference"),s=(0,i.ay)(t,"predictions","absoluteDifference");let u=null;null!=n&&(u=(0,i.ay)(n,"weights","absoluteDifference")),(0,d.kl)(o.shape,s.shape,"Error in absoluteDifference: ");const c=(0,a.a)((0,lt.A)(o,s));return Qr(c,u,r)}}),Jr=(0,u.op)({cosineDistance_:function(e,t,n,r,a=Kr.SUM_BY_NONZERO_WEIGHTS){const o=(0,i.ay)(e,"labels","cosineDistance"),s=(0,i.ay)(t,"predictions","cosineDistance");let u=null;null!=r&&(u=(0,i.ay)(r,"weights","cosineDistance")),(0,d.kl)(o.shape,s.shape,"Error in cosineDistance: ");const c=(0,De.S)(1),l=(0,lt.A)(c,(0,Pe.o)((0,D.E)(o,s),n,!0));return Qr(l,u,a)}}),Zr=(0,u.op)({hingeLoss_:function(e,t,n,r=Kr.SUM_BY_NONZERO_WEIGHTS){let a=(0,i.ay)(e,"labels","hingeLoss");const o=(0,i.ay)(t,"predictions","hingeLoss");let s=null;null!=n&&(s=(0,i.ay)(n,"weights","hingeLoss")),(0,d.kl)(a.shape,o.shape,"Error in hingeLoss: ");const u=(0,De.S)(1);a=(0,lt.A)((0,D.E)((0,De.S)(2),a),u);const c=(0,dn.w)((0,lt.A)(u,(0,D.E)(a,o)));return Qr(c,s,r)}}),Xr=(0,u.op)({huberLoss_:function(e,t,n,r=1,o=Kr.SUM_BY_NONZERO_WEIGHTS){const s=(0,i.ay)(e,"labels","huberLoss"),u=(0,i.ay)(t,"predictions","huberLoss");let c=null;null!=n&&(c=(0,i.ay)(n,"weights","huberLoss")),(0,d.kl)(s.shape,u.shape,"Error in huberLoss: ");const l=(0,De.S)(r),h=(0,a.a)((0,lt.A)(u,s)),f=Et(h,l),m=(0,lt.A)(h,f),g=(0,p.W)((0,D.E)((0,De.S)(.5),(0,Ce.Q)(f)),(0,D.E)(l,m));return Qr(g,c,o)}}),ea=(0,u.op)({logLoss_:function(e,t,n,r=1e-7,a=Kr.SUM_BY_NONZERO_WEIGHTS){const o=(0,i.ay)(e,"labels","logLoss"),s=(0,i.ay)(t,"predictions","logLoss");let u=null;null!=n&&(u=(0,i.ay)(n,"weights","logLoss")),(0,d.kl)(o.shape,s.shape,"Error in logLoss: ");const c=(0,De.S)(1),l=(0,De.S)(r),h=it((0,D.E)(o,at((0,p.W)(s,l)))),f=(0,D.E)((0,lt.A)(c,o),at((0,p.W)((0,lt.A)(c,s),l))),m=(0,lt.A)(h,f);return Qr(m,u,a)}}),ta=(0,u.op)({meanSquaredError_:function(e,t,n,r=Kr.SUM_BY_NONZERO_WEIGHTS){const a=(0,i.ay)(e,"labels","meanSquaredError"),o=(0,i.ay)(t,"predictions","meanSquaredError");let s=null;null!=n&&(s=(0,i.ay)(n,"weights","meanSquaredError")),(0,d.kl)(a.shape,o.shape,"Error in meanSquaredError: ");const u=$n(a,o);return Qr(u,s,r)}}),na=(0,u.op)({sigmoidCrossEntropy_:function(e,t,n,r=0,o=Kr.SUM_BY_NONZERO_WEIGHTS){let s=(0,i.ay)(e,"multiClassLabels","sigmoidCrossEntropy");const u=(0,i.ay)(t,"logits","sigmoidCrossEntropy");let c=null;if(null!=n&&(c=(0,i.ay)(n,"weights","sigmoidCrossEntropy")),(0,d.kl)(s.shape,u.shape,"Error in sigmoidCrossEntropy: "),r>0){const e=(0,De.S)(r),t=(0,De.S)(1),n=(0,De.S)(.5);s=(0,p.W)((0,D.E)(s,(0,lt.A)(t,e)),(0,D.E)(n,e))}const l=function(e,t){const n=(0,i.ay)(e,"labels","sigmoidCrossEntropyWithLogits"),r=(0,i.ay)(t,"logits","sigmoidCrossEntropyWithLogits");(0,d.kl)(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");const o=(0,dn.w)(r),s=(0,D.E)(r,n),u=ot(We(it((0,a.a)(r))));return(0,p.W)((0,lt.A)(o,s),u)}(s,u);return Qr(l,c,o)}}),ra=(0,u.op)({softmaxCrossEntropy_:function(e,t,n,r=0,a=Kr.SUM_BY_NONZERO_WEIGHTS){let o=(0,i.ay)(e,"onehotLabels","softmaxCrossEntropy");const s=(0,i.ay)(t,"logits","softmaxCrossEntropy");let u=null;if(null!=n&&(u=(0,i.ay)(n,"weights","softmaxCrossEntropy")),(0,d.kl)(o.shape,s.shape,"Error in softmaxCrossEntropy: "),r>0){const e=(0,De.S)(r),t=(0,De.S)(1),n=(0,De.S)(o.shape[1]);

2o=(0,p.W)((0,D.E)(o,(0,lt.A)(t,e)),(0,ye.M)(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 ${n}`);const r=(0,st.Sw)(((e,t,r)=>{const a=dt(t,[n],!0),o=(0,lt.A)((0,I.W)(t,"float32"),a);r([e,o]);const s=it((0,D.E)(o,e));return{value:(0,Pe.o)(s,[n]),gradFunc:(e,t)=>{const[r,a]=t,o=(0,Te.Mp)(e.shape,[n]);return[(0,D.E)((0,N.O)(e,o),(0,lt.A)((0,I.W)(r,"float32"),We(a))),(0,D.E)((0,N.O)(e,o),(0,lt.A)(We(a),(0,I.W)(r,"float32")))]}}}));return r(e,t)}(o,s);return Qr(c,u,a)}}),aa={fft:Dn,ifft:On,rfft:Rn,irfft:Cn},oa={hammingWindow:Nr,hannWindow:Mr,frame:Tr,stft:Er},sa={flipLeftRight:Fr,grayscaleToRGB:Dr,resizeNearestNeighbor:Br,resizeBilinear:zr,rgbToGrayscale:Or,rotateWithOffset:Cr,cropAndResize:Ar,nonMaxSuppression:Rr,nonMaxSuppressionAsync:async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY){const o=(0,i.ay)(e,"boxes","nonMaxSuppressionAsync"),s=(0,i.ay)(t,"scores","nonMaxSuppressionAsync"),u=Pr(o,s,n,r,a);n=u.maxOutputSize,r=u.iouThreshold,a=u.scoreThreshold;const c=await Promise.all([o.data(),s.data()]),l=c[0],p=c[1],{selectedIndices:d}=(0,$r.Wm)(l,p,n,r,a);return o!==e&&o.dispose(),s!==t&&s.dispose(),Gn(d,"int32")},nonMaxSuppressionWithScore:Lr,nonMaxSuppressionWithScoreAsync:async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,o=0){const s=(0,i.ay)(e,"boxes","nonMaxSuppressionAsync"),u=(0,i.ay)(t,"scores","nonMaxSuppressionAsync"),c=Pr(s,u,n,r,a,o);n=c.maxOutputSize,r=c.iouThreshold,a=c.scoreThreshold,o=c.softNmsSigma;const l=await Promise.all([s.data(),u.data()]),p=l[0],d=l[1],{selectedIndices:h,selectedScores:f}=(0,$r.eQ)(p,d,n,r,a,o);return s!==e&&s.dispose(),u!==t&&u.dispose(),{selectedIndices:Gn(h,"int32"),selectedScores:Gn(f)}},nonMaxSuppressionPadded:Wr,nonMaxSuppressionPaddedAsync:async function(e,t,n,r=.5,a=Number.NEGATIVE_INFINITY,o=!1){const s=(0,i.ay)(e,"boxes","nonMaxSuppressionAsync"),u=(0,i.ay)(t,"scores","nonMaxSuppressionAsync"),c=Pr(s,u,n,r,a,null),l=c.maxOutputSize,p=c.iouThreshold,d=c.scoreThreshold,[h,f]=await Promise.all([s.data(),u.data()]),{selectedIndices:m,validOutputs:g}=(0,$r.Mf)(h,f,l,p,d,o);return s!==e&&s.dispose(),u!==t&&u.dispose(),{selectedIndices:Gn(m,"int32"),validOutputs:(0,De.S)(g,"int32")}},threshold:Ur,transform:Hr},ia={bandPart:Vr,gramSchmidt:Gr,qr:jr},ua={absoluteDifference:Yr,computeWeightedLoss:Qr,cosineDistance:Jr,hingeLoss:Zr,huberLoss:Xr,logLoss:ea,meanSquaredError:ta,sigmoidCrossEntropy:na,softmaxCrossEntropy:ra},ca={sparseFillEmptyRows:(0,u.op)({sparseFillEmptyRows_:function(e,t,n,r){const a=(0,i.ay)(e,"indices","sparseFillEmptyRows","int32"),u=(0,i.ay)(t,"values","sparseFillEmptyRows"),c=(0,i.ay)(n,"denseShape","sparseFillEmptyRows","int32"),l=(0,i.ay)(r,"defaultValue","sparseFillEmptyRows",u.dtype);if(2!==a.rank)throw new Error(`Indices should be Tensor2D but received shape\n        ${a.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:a,values:u,denseShape:c,defaultValue:l},d=o.cL.runKernel(s.Omm,p);return{outputIndices:d[0],outputValues:d[1],emptyRowIndicator:d[2],reverseIndexMap:d[3]}}}),sparseReshape:(0,u.op)({sparseReshape_:function(e,t,n){const r=(0,i.ay)(e,"inputIndices","sparseReshape","int32"),a=(0,i.ay)(t,"inputShape","sparseReshape","int32"),u=(0,i.ay)(n,"newShape","sparseReshape","int32");if(2!==r.rank)throw new Error(`Input indices should be Tensor2D but received shape\n        ${r.shape}`);if(1!==a.rank)throw new Error(`Input shape should be Tensor1D but received shape ${a.shape}`);if(1!==u.rank)throw new Error(`New shape should be Tensor1D but received shape ${u.shape}`);const c={inputIndices:r,inputShape:a,newShape:u},l=o.cL.runKernel(s.kfs,c);return{outputIndices:l[0],outputShape:l[1]}}}),sparseSegmentMean:(0,u.op)({sparseSegmentMean_:function(e,t,n){const r=(0,i.ay)(e,"data","sparseSegmentMean"),a=(0,i.ay)(t,"indices","sparseSegmentMean","int32"),u=(0,i.ay)(n,"segmentIds","sparseSegmentMean","int32");if(r.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");

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model has no loaded params");var t=e.split("/").reduce((function(t,n){if(!t.nextObj.hasOwnProperty(n))throw new Error("traversePropertyPath - object does not have property "+n+", for path "+e);return{obj:t.nextObj,objProp:n,nextObj:t.nextObj[n]}}),{nextObj:this.params}),n=t.obj,r=t.objProp;if(!(n&&r&&n[r]instanceof a.w3A))throw new Error("traversePropertyPath - parameter is not a tensor, for path "+e);return{obj:n,objProp:r}},e}();function ve(e,t,n){return a.G6I((function(){var r=a.Kd4(e,t.depthwise_filter,t.pointwise_filter,n,"same");return a.WQq(r,t.bias)}))}function ke(e,t,n){return void 0===n&&(n=!1),a.G6I((function(){var r=a.wDQ(n?a.WQq(a.QlL(e,t.conv0.filters,[2,2],"same"),t.conv0.bias):ve(e,t.conv0,[2,2])),o=ve(r,t.conv1,[1,1]),s=ve(a.wDQ(a.WQq(r,o)),t.conv2,[1,1]);return a.wDQ(a.WQq(r,a.WQq(o,s)))}))}function xe(e,t,n,r){return void 0===n&&(n=!1),void 0===r&&(r=!0),a.G6I((function(){var o=a.wDQ(n?a.WQq(a.QlL(e,t.conv0.filters,r?[2,2]:[1,1],"same"),t.conv0.bias):ve(e,t.conv0,r?[2,2]:[1,1])),s=ve(o,t.conv1,[1,1]),i=ve(a.wDQ(a.WQq(o,s)),t.conv2,[1,1]),u=ve(a.wDQ(a.WQq(o,a.WQq(s,i))),t.conv3,[1,1]);return a.wDQ(a.WQq(o,a.WQq(s,a.WQq(i,u))))}))}function _e(e,t,n,r){return void 0===n&&(n="same"),void 0===r&&(r=!1),a.G6I((function(){var o=a.WQq(a.QlL(e,t.filters,[1,1],n),t.bias);return r?a.wDQ(o):o}))}function Ie(e,t){Object.keys(e).forEach((function(n){t.some((function(e){return e.originalPath===n}))||e[n].dispose()}))}function Se(e,t){return function(n,r,o,s){var i=a.IFH(e(n*r*o*o),[o,o,n,r]),u=a.SC3(e(r));return t.push({paramPath:s+"/filters"},{paramPath:s+"/bias"}),{filters:i,bias:u}}}function Ne(e,t){return function(n,r,o){var s=a.Enf(e(n*r),[n,r]),i=a.SC3(e(r));return t.push({paramPath:o+"/weights"},{paramPath:o+"/bias"}),{weights:s,bias:i}}}var Me=function(e,t,n){this.depthwise_filter=e,this.pointwise_filter=t,this.bias=n};function Te(e,t){return function(n,r,o){var s=a.IFH(e(9*n),[3,3,n,1]),i=a.IFH(e(n*r),[1,1,n,r]),u=a.SC3(e(r));return t.push({paramPath:o+"/depthwise_filter"},{paramPath:o+"/pointwise_filter"},{paramPath:o+"/bias"}),new Me(s,i,u)}}function Ee(e){return function(t){var n=e(t+"/depthwise_filter",4),r=e(t+"/pointwise_filter",4),a=e(t+"/bias",1);return new Me(n,r,a)}}function Ae(e,t){return function(n,r,a){var o=e[n];if(!h(o,r))throw new Error("expected weightMap["+n+"] to be a Tensor"+r+"D, instead have "+o);return t.push({originalPath:n,paramPath:a||n}),o}}function Fe(e){var t=e;return{extractWeights:function(e){var n=t.slice(0,e);return t=t.slice(e),n},getRemainingWeights:function(){return t}}}function De(e,t){var n=Se(e,t),r=Te(e,t);function a(e,t,a,o){return void 0===o&&(o=!1),{conv0:o?n(e,t,3,a+"/conv0"):r(e,t,a+"/conv0"),conv1:r(t,t,a+"/conv1"),conv2:r(t,t,a+"/conv2")}}

2return{extractDenseBlock3Params:a,extractDenseBlock4Params:function(e,t,n,o){void 0===o&&(o=!1);var s=a(e,t,n,o);return{conv0:s.conv0,conv1:s.conv1,conv2:s.conv2,conv3:r(t,t,n+"/conv3")}}}}function Oe(e){return function(t){return{filters:e(t+"/filters",4),bias:e(t+"/bias",1)}}}function Ce(e,t){var n=Ae(e,t),r=Oe(n),a=Ee(n);return{extractDenseBlock3Params:function(e,t){return void 0===t&&(t=!1),{conv0:t?r(e+"/conv0"):a(e+"/conv0"),conv1:a(e+"/conv1"),conv2:a(e+"/conv2")}},extractDenseBlock4Params:function(e,t){return void 0===t&&(t=!1),{conv0:t?r(e+"/conv0"):a(e+"/conv0"),conv1:a(e+"/conv1"),conv2:a(e+"/conv2"),conv3:a(e+"/conv3")}}}}var Pe=function(e){function t(){return e.call(this,"FaceFeatureExtractor")||this}return i(t,e),t.prototype.forwardInput=function(e){var t=this.params;if(!t)throw new Error("FaceFeatureExtractor - load model before inference");return a.G6I((function(){var n=xe(A(e.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(a.SgB(255)),t.dense0,!0);return n=xe(n,t.dense1),n=xe(n,t.dense2),n=xe(n,t.dense3),a.q2x(n,[7,7],[2,2],"valid")}))},t.prototype.forward=function(e){return c(this,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return t=this.forwardInput,[4,pe(e)];case 1:return[2,t.apply(this,[n.sent()])]}}))}))},t.prototype.getDefaultModelName=function(){return"face_feature_extractor_model"},t.prototype.extractParamsFromWeigthMap=function(e){return function(e){var t=[],n=Ce(e,t).extractDenseBlock4Params,r={dense0:n("dense0",!0),dense1:n("dense1"),dense2:n("dense2"),dense3:n("dense3")};return Ie(e,t),{params:r,paramMappings:t}}(e)},t.prototype.extractParams=function(e){return function(e){var t=[],n=Fe(e),r=n.extractWeights,a=n.getRemainingWeights,o=De(r,t).extractDenseBlock4Params,s=o(3,32,"dense0",!0),i=o(32,64,"dense1"),u=o(64,128,"dense2"),c=o(128,256,"dense3");if(0!==a().length)throw new Error("weights remaing after extract: "+a().length);return{paramMappings:t,params:{dense0:s,dense1:i,dense2:u,dense3:c}}}(e)},t}(we);function Re(e,t){return a.G6I((function(){return a.WQq(a._o$(e,t.weights),t.bias)}))}function $e(e){var t={},n={};return Object.keys(e).forEach((function(r){(r.startsWith("fc")?n:t)[r]=e[r]})),{featureExtractorMap:t,classifierMap:n}}var Le=function(e){function t(t,n){var r=e.call(this,t)||this;return r._faceFeatureExtractor=n,r}return i(t,e),Object.defineProperty(t.prototype,"faceFeatureExtractor",{get:function(){return this._faceFeatureExtractor},enumerable:!0,configurable:!0}),t.prototype.runNet=function(e){var t=this,n=this.params;if(!n)throw new Error(this._name+" - load model before inference");return a.G6I((function(){var r=e instanceof le?t.faceFeatureExtractor.forwardInput(e):e;return Re(r.as2D(r.shape[0],-1),n.fc)}))},t.prototype.dispose=function(t){void 0===t&&(t=!0),this.faceFeatureExtractor.dispose(t),e.prototype.dispose.call(this,t)},t.prototype.loadClassifierParams=function(e){var t=this.extractClassifierParams(e),n=t.params,r=t.paramMappings;this._params=n,this._paramMappings=r},t.prototype.extractClassifierParams=function(e){return function(e,t,n){var r=[],a=Fe(e),o=a.extractWeights,s=a.getRemainingWeights,i=Ne(o,r)(t,n,"fc");if(0!==s().length)throw new Error("weights remaing after extract: "+s().length);return{paramMappings:r,params:{fc:i}}}(e,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())},t.prototype.extractParamsFromWeigthMap=function(e){var t=$e(e),n=t.featureExtractorMap,r=t.classifierMap;return this.faceFeatureExtractor.loadFromWeightMap(n),function(e){var t=[],n=Ae(e,t),r={fc:("fc",{weights:n("fc/weights",2),bias:n("fc/bias",1)})};return Ie(e,t),{params:r,paramMappings:t}}(r)},t.prototype.extractParams=function(e){var t=this.getClassifierChannelsIn(),n=this.getClassifierChannelsOut(),r=n*t+n,a=e.slice(0,e.length-r),o=e.slice(e.length-r);return this.faceFeatureExtractor.extractWeights(a),this.extractClassifierParams(o)},t}(we),We=["neutral","happy","sad","angry","fearful","disgusted","surprised"],ze=function(){function e(e){var t=this;if(7!==e.length)throw new Error("FaceExpressions.constructor - expected probabilities.length to be 7, have: "+e.length);We.forEach((function(n,r){t[n]=e[r]}))}return e.prototype.asSortedArray=function(){var e=this;return We.map((function(t){return{expression:t,probability:e[t]}})).sort((function(e,t){return t.probability-e.probability}))},e}(),Be=function(e){function t(t){return void 0===t&&(t=new Pe),e.call(this,"FaceExpressionNet",t)||this}return i(t,e),t.prototype.forwardInput=function(e){var t=this;return a.G6I((function(){return a.UhY(t.runNet(e))}))},t.prototype.forward=function(e){return c(this,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return t=this.forwardInput,[4,pe(e)];case 1:return[2,t.apply(this,[n.sent()])]}}))}))},t.prototype.predictExpressions=function(e){return c(this,void 0,void 0,(function(){var t,n,r,o,s=this;return l(this,(function(i){switch(i.label){case 0:return[4,pe(e)];case 1:return t=i.sent(),[4,this.forwardInput(t)];case 2:return n=i.sent(),[4,Promise.all(a.iqB(n).map((function(e){return c(s,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return[4,e.data()];case 1:return t=n.sent(),e.dispose(),[2,t]}}))}))})))];case 3:return r=i.sent(),n.dispose(),o=r.map((function(e){return new ze(e)})),[2,t.isBatchInput?o:o[0]]}}))}))},t.prototype.getDefaultModelName=function(){return"face_expression_model"},t.prototype.getClassifierChannelsIn=function(){return 256},t.prototype.getClassifierChannelsOut=function(){return 7},t}(Le);function Ue(e,t){var n={expressions:t};return Object.assign({},e,n)}function He(e,t,n,r){void 0===n&&(n=.1),(Array.isArray(t)?t:[t]).forEac

2h((function(t){var a=t instanceof ze?t:t.expressions instanceof ze?t.expressions:void 0;if(!a)throw new Error("drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof");var o=a.asSortedArray().filter((function(e){return e.probability>n})),s=z(t)?t.detection.box.bottomLeft:r||new _(0,0),i=new ee(o.map((function(e){return e.expression+" ("+y(e.probability)+")"})),s);i.draw(e)}))}function Ve(e){return z(e)&&e.landmarks instanceof C&&e.unshiftedLandmarks instanceof C&&e.alignedRect instanceof M}function Ge(e,t){var n=e.detection.box,r=t.shiftBy(n.x,n.y),a=r.align(),o=e.detection.imageDims,s={landmarks:r,unshiftedLandmarks:t,alignedRect:new M(e.detection.score,a.rescale(o.reverse()),o)};return Object.assign({},e,s)}var qe=function(e){void 0===e&&(e={});var t=e.drawLines,n=void 0===t||t,r=e.drawPoints,a=void 0===r||r,o=e.lineWidth,s=e.lineColor,i=e.pointSize,u=e.pointColor;this.drawLines=n,this.drawPoints=a,this.lineWidth=o||1,this.pointSize=i||2,this.lineColor=s||"rgba(0, 255, 255, 1)",this.pointColor=u||"rgba(255, 0, 255, 1)"},je=function(){function e(e,t){void 0===t&&(t={}),this.faceLandmarks=e,this.options=new qe(t)}

2return e.prototype.draw=function(e){var t=Z(e),n=this.options,r=n.drawLines,a=n.drawPoints,s=n.lineWidth,i=n.lineColor,u=n.pointSize,c=n.pointColor;r&&this.faceLandmarks instanceof R&&(t.strokeStyle=i,t.lineWidth=s,o(t,this.faceLandmarks.getJawOutline()),o(t,this.faceLandmarks.getLeftEyeBrow()),o(t,this.faceLandmarks.getRightEyeBrow()),o(t,this.faceLandmarks.getNose()),o(t,this.faceLandmarks.getLeftEye(),!0),o(t,this.faceLandmarks.getRightEye(),!0),o(t,this.faceLandmarks.getMouth(),!0)),a&&(t.strokeStyle=c,t.fillStyle=c,this.faceLandmarks.positions.forEach((function(e){t.beginPath(),t.arc(e.x,e.y,u,0,2*Math.PI),t.fill()})))},e}();function Ke(e,t){(Array.isArray(t)?t:[t]).forEach((function(t){var n=t instanceof C?t:Ve(t)?t.landmarks:void 0;if(!n)throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof");new je(n).draw(e)}))}function Qe(e,t,n){return a.WQq(a.QlL(e,t.filters,n,"same"),t.bias)}function Ye(e,t,n){void 0===n&&(n=!0);var r=n?a.wDQ(e):e;return r=ve(r,t.separable_conv0,[1,1]),r=ve(a.wDQ(r),t.separable_conv1,[1,1]),r=a._SL(r,[3,3],[2,2],"same"),a.WQq(r,Qe(e,t.expansion_conv,[2,2]))}var Je,Ze,Xe=function(e){function t(t){var n=e.call(this,"TinyXception")||this;return n._numMainBlocks=t,n}return i(t,e),t.prototype.forwardInput=function(e){var t=this,n=this.params;if(!n)throw new Error("TinyXception - load model before inference");return a.G6I((function(){var r=A(e.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(a.SgB(256)),o=a.wDQ(Qe(r,n.entry_flow.conv_in,[2,2]));return o=Ye(o,n.entry_flow.reduction_block_0,!1),o=Ye(o,n.entry_flow.reduction_block_1),v(t._numMainBlocks,0,1).forEach((function(e){o=function(e,t){var n=ve(a.wDQ(e),t.separable_conv0,[1,1]);return n=ve(a.wDQ(n),t.separable_conv1,[1,1]),n=ve(a.wDQ(n),t.separable_conv2,[1,1]),a.WQq(n,e)}(o,n.middle_flow["main_block_"+e])})),o=Ye(o,n.exit_flow.reduction_block),o=a.wDQ(ve(o,n.exit_flow.separable_conv,[1,1]))}))},t.prototype.forward=function(e){return c(this,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return t=this.forwardInput,[4,pe(e)];case 1:return[2,t.apply(this,[n.sent()])]}}))}))},t.prototype.getDefaultModelName=function(){return"tiny_xception_model"},t.prototype.extractParamsFromWeigthMap=function(e){return function(e,t){var n=[],r=function(e,t){var n=Ae(e,t),r=Oe(n),a=Ee(n);return{extractConvParams:r,extractSeparableConvParams:a,extractReductionBlockParams:function(e){return{separable_conv0:a(e+"/separable_conv0"),separable_conv1:a(e+"/separable_conv1"),expansion_conv:r(e+"/expansion_conv")}},extractMainBlockParams:function(e){return{separable_conv0:a(e+"/separable_conv0"),separable_conv1:a(e+"/separable_conv1"),separable_conv2:a(e+"/separable_conv2")}}}}(e,n),a=r.extractConvParams,o=r.extractSeparableConvParams,s=r.extractReductionBlockParams,i=r.extractMainBlockParams,u={conv_in:a("entry_flow/conv_in"),reduction_block_0:s("entry_flow/reduction_block_0"),reduction_block_1:s("entry_flow/reduction_block_1")},c={};v(t,0,1).forEach((function(e){c["main_block_"+e]=i("middle_flow/main_block_"+e)}));var l={reduction_block:s("exit_flow/reduction_block"),separable_conv:o("exit_flow/separable_conv")};return Ie(e,n),{params:{entry_flow:u,middle_flow:c,exit_flow:l},paramMappings:n}}(e,this._numMainBlocks)},t.prototype.extractParams=function(e){return function(e,t){var n=[],r=Fe(e),a=r.extractWeights,o=r.getRemainingWeights,s=function(e,t){var n=Se(e,t),r=Te(e,t);return{extractConvParams:n,extractSeparableConvParams:r,extractReductionBlockParams:function(e,t,a){return{separable_conv0:r(e,t,a+"/separable_conv0"),separable_conv1:r(t,t,a+"/separable_conv1"),expansion_conv:n(e,t,1,a+"/expansion_conv")}},extractMainBlockParams:function(e,t){return{separable_conv0:r(e,e,t+"/separable_conv0"),separable_conv1:r(e,e,t+"/separable_conv1"),separable_conv2:r(e,e,t+"/separable_conv2")}}}}(a,n),i=s.extractConvParams,u=s.extractSeparableConvParams,c=s.extractReductionBlockParams,l=s.extractMainBlockParams,p={conv_in:i(3,32,3,"entry_flow/conv_in"),reduction_block_0:c(32,64,"entry_flow/reduction_block_0"),reduction_block_1:c(64,128,"entry_flow/reduction_block_1")}

2,d={};v(t,0,1).forEach((function(e){d["main_block_"+e]=l(128,"middle_flow/main_block_"+e)}));var h={reduction_block:c(128,256,"exit_flow/reduction_block"),separable_conv:u(256,512,"exit_flow/separable_conv")};if(0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{paramMappings:n,params:{entry_flow:p,middle_flow:d,exit_flow:h}}}(e,this._numMainBlocks)},t}(we);(Ze=Je||(Je={})).FEMALE="female",Ze.MALE="male";var et,tt=function(e){function t(t){void 0===t&&(t=new Xe(2));var n=e.call(this,"AgeGenderNet")||this;return n._faceFeatureExtractor=t,n}return i(t,e),Object.defineProperty(t.prototype,"faceFeatureExtractor",{get:function(){return this._faceFeatureExtractor},enumerable:!0,configurable:!0}),t.prototype.runNet=function(e){var t=this,n=this.params;if(!n)throw new Error(this._name+" - load model before inference");return a.G6I((function(){var r=e instanceof le?t.faceFeatureExtractor.forwardInput(e):e,o=a.q2x(r,[7,7],[2,2],"valid").as2D(r.shape[0],-1);return{age:Re(o,n.fc.age).as1D(),gender:Re(o,n.fc.gender)}}))},t.prototype.forwardInput=function(e){var t=this;return a.G6I((function(){var n=t.runNet(e),r=n.age,o=n.gender;return{age:r,gender:a.UhY(o)}}))},t.prototype.forward=function(e){return c(this,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return t=this.forwardInput,[4,pe(e)];case 1:return[2,t.apply(this,[n.sent()])]}}))}))},t.prototype.predictAgeAndGender=function(e){return c(this,void 0,void 0,(function(){var t,n,r,o,s,i,u=this;return l(this,(function(p){switch(p.label){case 0:return[4,pe(e)];case 1:return t=p.sent(),[4,this.forwardInput(t)];case 2:return n=p.sent(),r=a.iqB(n.age),o=a.iqB(n.gender),s=r.map((function(e,t){return{ageTensor:e,genderTensor:o[t]}})),[4,Promise.all(s.map((function(e){var t=e.ageTensor,n=e.genderTensor;return c(u,void 0,void 0,(function(){var e,r,a,o,s;return l(this,(function(i){switch(i.label){case 0:return[4,t.data()];case 1:return e=i.sent()[0],[4,n.data()];case 2:return r=i.sent()[0],o=(a=r>.5)?Je.MALE:Je.FEMALE,s=a?r:1-r,t.dispose(),n.dispose(),[2,{age:e,gender:o,genderProbability:s}]}}))}))})))];case 3:return i=p.sent(),n.age.dispose(),n.gender.dispose(),[2,t.isBatchInput?i:i[0]]}}))}))},t.prototype.getDefaultModelName=function(){return"age_gender_model"},t.prototype.dispose=function(t){void 0===t&&(t=!0),this.faceFeatureExtractor.dispose(t),e.prototype.dispose.call(this,t)},t.prototype.loadClassifierParams=function(e){var t=this.extractClassifierParams(e),n=t.params,r=t.paramMappings;this._params=n,this._paramMappings=r},t.prototype.extractClassifierParams=function(e){return function(e){var t=[],n=Fe(e),r=n.extractWeights,a=n.getRemainingWeights,o=Ne(r,t),s=o(512,1,"fc/age"),i=o(512,2,"fc/gender");if(0!==a().length)throw new Error("weights remaing after extract: "+a().length);return{paramMappings:t,params:{fc:{age:s,gender:i}}}}(e)},t.prototype.extractParamsFromWeigthMap=function(e){var t=$e(e),n=t.featureExtractorMap,r=t.classifierMap;return this.faceFeatureExtractor.loadFromWeightMap(n),function(e){var t=[],n=Ae(e,t);function r(e){return{weights:n(e+"/weights",2),bias:n(e+"/bias",1)}}var a={fc:{age:r("fc/age"),gender:r("fc/gender")}};return Ie(e,t),{params:a,paramMappings:t}}(r)},t.prototype.extractParams=function(e){var t=e.slice(0,e.length-1539),n=e.slice(e.length-1539);return this.faceFeatureExtractor.extractWeights(t),this.extractClassifierParams(n)},t}(we),nt=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return i(t,e),t.prototype.postProcess=function(e,t,n){var r=n.map((function(e){var n=e.width,r=e.height,a=t/Math.max(r,n);return{width:n*a,height:r*a}})),o=r.length;return a.G6I((function(){var n=function(e,t){return a.Qfh([a.ymW([68],e),a.ymW([68],t)],1).as2D(1,136).as1D()},s=function(e,t){var n=r[e],a=n.width,o=n.height;return t(a,o)?Math.abs(a-o)/2:0};return e.mul(a.ymW([o,136],t)).sub(a.Qfh(Array.from(Array(o),(function(e,t){return n(function(e){return s(e,(function(e,t){return e<t}))}(t),function(e){return s(e,(function(e,t){return t<e}))}(t))})))).div(a.Qfh(Array.from(Array(o),(function(e,t){return n(r[t].width,r[t].height)}))))}))},t.prototype.forwardInput=function(e){var t=this;return a.G6I((function(){var n=t.runNet(e);return t.postProcess(n,e.inputSize,e.inputDimensions.map((function(e){return{height:e[0],width:e[1]}})))}))},t.prototype.forward=function(e){return c(this,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return t=this.forwardInput,[4,pe(e)];case 1:return[2,t.apply(this,[n.sent()])]}}))}))},t.prototype.detectLandmarks=function(e){return c(this,void 0,void 0,(function(){var t,n,r,o=this;return l(this,(function(s){switch(s.label){case 0:return[4,pe(e)];case 1:return t=s.sent(),n=a.G6I((function(){return 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2)),{height:t.getInputHeight(n),width:t.getInputWidth(n)})]}}))}))})))];case 2:return r=s.sent(),n.forEach((function(e){return e.dispose()})),[2,t.isBatchInput?r:r[0]]}}))}))},t.prototype.getClassifierChannelsOut=function(){return 136},t}(Le),rt=function(e){function t(t){return void 0===t&&(t=new Pe),e.call(this,"FaceLandmark68Net",t)||this}return i(t,e),t.prototype.getDefaultModelName=function(){return"face_landmark_68_model"},t.prototype.getClassifierChannelsIn=function(){return 256},t}(nt),at=function(e){function t(){return e.call(this,"TinyFaceFeatureExtractor")||this}return i(t,e),t.prototype.forwardInput=function(e){var t=this.params;if(!t)throw new Error("TinyFaceFeatureExtractor - load model before inference");return a.G6I((function(){var n=ke(A(e.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(a.SgB(255)),t.dense0,!0);return n=ke(n,t.dense1),n=ke(n,t.dense2),a.q2x(n,[14,14],[2,2],"valid")}))},t.prototype.forward=function(e){return c(this,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return t=this.forwardInput,[4,pe(e)];case 1:return[2,t.apply(this,[n.sent()])]}}))}))},t.prototype.getDefaultModelName=function(){return"face_feature_extractor_tiny_model"},t.prototype.extractParamsFromWeigthMap=function(e){return function(e){var t=[],n=Ce(e,t).extractDenseBlock3Params,r={dense0:n("dense0",!0),dense1:n("dense1"),dense2:n("dense2")};return Ie(e,t),{params:r,paramMappings:t}}(e)},t.prototype.extractParams=function(e){return function(e){var t=[],n=Fe(e),r=n.extractWeights,a=n.getRemainingWeights,o=De(r,t).extractDenseBlock3Params,s=o(3,32,"dense0",!0),i=o(32,64,"dense1"),u=o(64,128,"dense2");if(0!==a().length)throw new Error("weights remaing after extract: "+a().length);return{paramMappings:t,params:{dense0:s,dense1:i,dense2:u}}}(e)},t}(we),ot=function(e){function t(t){return void 0===t&&(t=new at),e.call(this,"FaceLandmark68TinyNet",t)||this}return i(t,e),t.prototype.getDefaultModelName=function(){return"face_landmark_68_tiny_model"},t.prototype.getClassifierChannelsIn=function(){return 128},t}(nt);function st(e,t,n,r,o){void 0===o&&(o="same");var s=t.conv,i=s.filters,u=s.bias,c=a.QlL(e,i,n,o);return c=function(e,t){return a.WQq(a.E7T(e,t.weights),t.biases)}(c=a.WQq(c,u),t.scale),r?a.wDQ(c):c}function it(e,t){return st(e,t,[1,1],!1)}function ut(e,t){return st(e,t,[2,2],!0,"valid")}function ct(e,t){function n(n,r,o,s){var i=function(n,r,o,s){var i=function(t,n,r){var o=e(t),s=o.length/(n*r*r);if(s%1!=0)throw new Error("depth has to be an integer: "+s+", weights.length: "+o.length+", numFilters: "+n+", filterSize: "+r);return a.G6I((function(){return a.oLj(a.IFH(o,[n,s,r,r]),[2,3,1,0])}))}(n,r,o),u=a.SC3(e(r));return t.push({paramPath:s+"/filters"},{paramPath:s+"/bias"}),{filters:i,bias:u}}(n,r,o,s+"/conv"),u=function(n,r){var o=a.SC3(e(n)),s=a.SC3(e(n));return t.push({paramPath:r+"/weights"},{paramPath:r+"/biases"}),{weights:o,biases:s}}(r,s+"/scale");return{conv:i,scale:u}}return{extractConvLayerParams:n,extractResidualLayerParams:function(e,t,r,a,o){return void 0===o&&(o=!1),{conv1:n((o?.5:1)*e,t,r,a+"/conv1"),conv2:n(e,t,r,a+"/conv2")}}}}function lt(e){var t=[],n=function(e,t){var n=Ae(e,t);function r(e){var t=n(e+"/conv/filters",4),r=n(e+"/conv/bias",1),a=function(e){return{weights:n(e+"/scale/weights",1),biases:n(e+"/scale/biases",1)}}(e);return{conv:{filters:t,bias:r},scale:a}}return{extractConvLayerParams:r,extractResidualLayerParams:function(e){return{conv1:r(e+"/conv1"),conv2:r(e+"/conv2")}}}}(e,t),r=n.extractConvLayerParams,a=n.extractResidualLayerParams,o=r("conv32_down"),s=a("conv32_1"),i=a("conv32_2"),u=a("conv32_3"),c=a("conv64_down"),l=a("conv64_1"),p=a("conv64_2"),d=a("conv64_3"),f=a("conv128_down"),m=a("conv128_1"),g=a("conv128_2"),y=a("conv256_down"),b=a("conv256_1"),w=a("conv256_2"),v=a("conv256_down_out"),k=e.fc;if(t.push({originalPath:"fc",paramPath:"fc"}),!h(k,2))throw new Error("expected weightMap[fc] to be a Tensor2D, instead have "+k);var x={conv32_down:o,conv32_1:s,conv32_2:i,conv32_3:u,conv64_down:c,conv64_1:l,conv64_2:p,conv64_3:d,conv128_down:f,conv128_1:m,conv128_2:g,conv256_down:y,conv256_1:b,conv256_2:w,conv256_down_out:v,fc:k};return Ie(e,t),{params:x,paramMappings:t}}function pt(e,t){var n=function(e,t){return st(e,t,[1,1],!0)}(e,t.conv1);return n=it(n,t.conv2),n=a.WQq(n,e),a.wDQ(n)}function dt(e,t){var n=ut(e,t.conv1);n=it(n,t.conv2);var r=a.q2x(e,2,2,"valid"),o=a.DjU(r.shape),s=r.shape[3]!==n.shape[3];if(r.shape[1]!==n.shape[1]||r.shape[2]!==n.shape[2]){var i=p(n.shape);i[1]=1;var u=a.DjU(i),c=p((n=a.WUr([n,u],1)).shape);c[2]=1;var l=a.DjU(c);n=a.WUr([n,l],2)}return r=s?a.WUr([r,o],3):r,n=a.WQq(r,n),a.wDQ(n)}i((function(){return null!==et&&et.apply(this,arguments)||this}),et=rt);var ht=function(e){function t(){return e.call(this,"FaceRecognitionNet")||this}return i(t,e),t.prototype.forwardInput=function(e){var t=this.params;if(!t)throw new Error("FaceRecognitionNet - 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expected minFaceSize to be a number > 0");if("number"!=typeof this._scaleFactor||this._scaleFactor<=0||this._scaleFactor>=1)throw new Error(this._name+" - expected scaleFactor to be a number between 0 and 1");if("number"!=typeof this._maxNumScales||this._maxNumScales<0)throw new Error(this._name+" - expected maxNumScales to be a number > 0");if(!Array.isArray(this._scoreThresholds)||3!==this._scoreThresholds.length||this._scoreThresholds.some((function(e){return"number"!=typeof e})))throw new Error(this._name+" - expected scoreThresholds to be an array of numbers of length 3");if(this._scaleSteps&&(!Array.isArray(this._scaleSteps)||this._scaleSteps.some((function(e){return"number"!=typeof e}))))throw new Error(this._name+" - expected scaleSteps to be an array of numbers")}return Object.defineProperty(e.prototype,"minFaceSize",{get:function(){return this._minFaceSize},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"scaleFactor",{get:function(){return this._scaleFactor},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"maxNumScales",{get:function(){return this._maxNumScales},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"scoreThresholds",{get:function(){return this._scoreThresholds},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"scaleSteps",{get:function(){return this._scaleSteps},enumerable:!0,configurable:!0}),e}();function gt(e,t,n){return a.G6I((function(){var r=a.QlL(e,t.filters,n,"same");return r=a.WQq(r,t.batch_norm_offset),a.Qjg(r,0,6)}))}function yt(e,t,n){var r=e.arraySync(),a=Math.min(r[t][0],r[t][2]),o=Math.min(r[t][1],r[t][3]),s=Math.max(r[t][0],r[t][2]),i=Math.max(r[t][1],r[t][3]),u=Math.min(r[n][0],r[n][2]),c=Math.min(r[n][1],r[n][3]),l=Math.max(r[n][0],r[n][2]),p=Math.max(r[n][1],r[n][3]),d=(s-a)*(i-o),h=(l-u)*(p-c);if(d<=0||h<=0)return 0;var f=Math.max(a,u),m=Math.max(o,c),g=Math.min(s,l),y=Math.min(i,p),b=Math.max(g-f,0)*Math.max(y-m,0);return b/(d+h-b)}function bt(e,t){return a.G6I((function(){var n=e.shape[0];return{boxPredictionEncoding:a.OoG(_e(e,t.box_encoding_predictor),[n,-1,1,4]),classPrediction:a.OoG(_e(e,t.class_predictor),[n,-1,3])}}))}var wt=function(){function e(e){var t=void 0===e?{}:e,n=t.minConfidence,r=t.maxResults;if(this._name="SsdMobilenetv1Options",this._minConfidence=n||.5,this._maxResults=r||100,"number"!=typeof this._minConfidence||this._minConfidence<=0||this._minConfidence>=1)throw new Error(this._name+" - 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t=a.iqB(a.oLj(e,[1,0])),n=[a.AT$(t[2],t[0]),a.AT$(t[3],t[1])];return{sizes:n,centers:[a.WQq(t[0],a.MbH(n[0],a.SgB(2))),a.WQq(t[1],a.MbH(n[1],a.SgB(2)))]}}(e),r=n.sizes,o=n.centers,s=a.iqB(a.oLj(t,[1,0])),i=a.MbH(a.E7T(a.oNF(a.MbH(s[2],a.SgB(5))),r[0]),a.SgB(2)),u=a.WQq(a.E7T(a.MbH(s[0],a.SgB(10)),r[0]),o[0]),c=a.MbH(a.E7T(a.oNF(a.MbH(s[3],a.SgB(5))),r[1]),a.SgB(2)),l=a.WQq(a.E7T(a.MbH(s[1],a.SgB(10)),r[1]),o[1]);return a.oLj(a.Qfh([a.AT$(u,i),a.AT$(l,c),a.WQq(u,i),a.WQq(l,c)]),[1,0])}(a.OoG(a.CUy(n.extra_dim,[r,1,1]),[-1,4]),a.OoG(e,[-1,4]));o=a.OoG(o,[r,o.shape[0]/r,4]);var s=a._CL(a.SME(t,[0,0,1],[-1,-1,-1])),i=a.SME(s,[0,0,0],[-1,-1,1]);return i=a.OoG(i,[r,i.shape[1]]),{boxes:a.iqB(o),scores:a.iqB(i)}}))}(o.boxPredictions,o.classPredictions,t.output_layer)}))},t.prototype.forward=function(e){return c(this,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return t=this.forwardInput,[4,pe(e)];case 1:return[2,t.apply(this,[n.sent()])]}}))}))},t.prototype.locateFaces=function(e,t){return void 0===t&&(t={}),c(this,void 0,void 0,(function(){var n,r,a,o,s,i,u,c,p,d,h,f,m,g,y,b,w,v,k,x;return l(this,(function(l){switch(l.label){case 0:return n=new wt(t),r=n.maxResults,a=n.minConfidence,[4,pe(e)];case 1:for(o=l.sent(),s=this.forwardInput(o),i=s.boxes,u=s.scores,c=i[0],p=u[0],d=1;d<i.length;d++)i[d].dispose(),u[d].dispose();return m=(f=Array).from,[4,p.data()];case 2:return h=m.apply(f,[l.sent()]),g=function(e,t,n,r,a){var o=e.shape[0],s=Math.min(n,o),i=t.map((function(e,t){return{score:e,boxIndex:t}})).filter((function(e){return e.score>a})).sort((function(e,t){return t.score-e.score})),u=[];return i.forEach((function(t){if(!(u.length>=s)){for(var n=t.score,r=u.length-1;r>=0;--r){var o=yt(e,t.boxIndex,u[r]);if(0!==o&&(t.score*=o<=.5?1:0,t.score<=a))break}n===t.score&&u.push(t.boxIndex)}})),u}(c,h,r,0,a),y=o.getReshapedInputDimensions(0),b=o.inputSize,w=b/y.width,v=b/y.height,k=c.arraySync(),x=g.map((function(e){var t=[Math.max(0,k[e][0]),Math.min(1,k[e][2])].map((function(e){return e*v})),n=t[0],r=t[1],a=[Math.max(0,k[e][1]),Math.min(1,k[e][3])].map((function(e){return e*w})),s=a[0],i=a[1];return new M(h[e],new O(s,n,i-s,r-n),{height:o.getInputHeight(0),width:o.getInputWidth(0)})})),c.dispose(),p.dispose(),[2,x]}}))}))},t.prototype.getDefaultModelName=function(){return"ssd_mobilenetv1_model"},t.prototype.extractParamsFromWeigthMap=function(e){return function(e){var t=[],n=function(e,t){var n=Ae(e,t);function r(e,t,r){return{filters:n(e+"/Conv2d_"+t+"_pointwise/weights",4,r+"/filters"),batch_norm_offset:n(e+"/Conv2d_"+t+"_pointwise/convolution_bn_offset",1,r+"/batch_norm_offset")}}function a(e){var t="mobilenetv1/conv_"+e,a="MobilenetV1/Conv2d_"+e+"_depthwise",o=t+"/depthwise_conv",s=t+"/pointwise_conv";return{depthwise_conv:{filters:n(a+"/depthwise_weights",4,o+"/filters"),batch_norm_scale:n(a+"/BatchNorm/gamma",1,o+"/batch_norm_scale"),batch_norm_offset:n(a+"/BatchNorm/beta",1,o+"/batch_norm_offset"),batch_norm_mean:n(a+"/BatchNorm/moving_mean",1,o+"/batch_norm_mean"),batch_norm_variance:n(a+"/BatchNorm/moving_variance",1,o+"/batch_norm_variance")},pointwise_conv:r("MobilenetV1",e,s)}}function o(e,t){return{filters:n(e+"/weights",4,t+"/filters"),bias:n(e+"/biases",1,t+"/bias")}}function s(e){return{box_encoding_predictor:o("Prediction/BoxPredictor_"+e+"/BoxEncodingPredictor","prediction_layer/box_predictor_"+e+"/box_encoding_predictor"),class_predictor:o("Prediction/BoxPredictor_"+e+"/ClassPredictor","prediction_layer/box_predictor_"+e+"/class_predictor")}}return{extractMobilenetV1Params:function(){return{conv_0:r("MobilenetV1",0,"mobilenetv1/conv_0"),conv_1:a(1),conv_2:a(2),conv_3:a(3),conv_4:a(4),conv_5:a(5),conv_6:a(6),conv_7:a(7),conv_8:a(8),conv_9:a(9),conv_10:a(10),conv_11:a(11),conv_12:a(12),conv_13:a(13)}},extractPredictionLayerParams:function(){return{conv_0:r("Prediction",0,"prediction_layer/conv_0"),conv_1:r("Prediction",1,"prediction_layer/conv_1"),conv_2:r("Prediction",2,"prediction_layer/conv_2"),conv_3:r("Prediction",3,"prediction_layer/conv_3"),conv_4:r("Prediction",4,"prediction_layer/conv_4"),conv_5:r("Prediction",5,"prediction_layer/conv_5"),conv_6:r("Prediction",6,"prediction_layer/conv_6"),conv_7:r("Prediction",7,"prediction_layer/conv_7"),box_predictor_0:s(0),box_predictor_1:s(1),box_predictor_2:s(2),box_predictor_3:s(3),box_predictor_4:s(4),box_predictor_5:s(5)}}}}(e,t),r=n.extractMobilenetV1Params,a=n.extractPredictionLayerParams,o=e["Output/extra_dim"];if(t.push({originalPath:"Output/extra_dim",paramPath:"output_layer/extra_dim"}),!f(o))throw new Error("expected weightMap['Output/extra_dim'] to be a Tensor3D, instead have "+o);var s={mobilenetv1:r(),prediction_layer:a(),output_layer:{extra_dim:o}};return Ie(e,t),{params:s,paramMappings:t}}(e)},t.prototype.extractParams=function(e){return function(e){var t=[],n=Fe(e),r=n.extractWeights,o=n.getRemainingWeights,s=function(e,t){function n(n,r,o,s,i){var u=a.IFH(e(n*r*o*o),[o,o,n,r]),c=a.SC3(e(r));return t.push({paramPath:s+"/filters"},{paramPath:s+"/"+(i?"batch_norm_offset":"bias")}),{filters:u,bias:c}}function r(e,t,r,a){var o=n(e,t,r,a,!0);return{filters:o.filters,batch_norm_offset:o.bias}}function o(n,o,s){var i=function(n,r){var o=a.IFH(e(9*n),[3,3,n,1]),s=a.SC3(e(n)),i=a.SC3(e(n)),u=a.SC3(e(n)),c=a.SC3(e(n));return t.push({paramPath:r+"/filters"},{paramPath:r+"/batch_norm_scale"},{paramPath:r+"/batch_norm_offset"},{paramPath:r+"/batch_norm_mean"},{paramPath:r+"/batch_norm_variance"}),{filters:o,batch_norm_scale:s,batch_norm_offset:i,batch_norm_mean:u,batch_norm_variance:c}}(n,s+"/depthwise_conv");return{depthwise_conv:i,pointwise_conv:r(n,o,1,s+"/pointwise_conv")}}return{extractMobilenetV1Params:function(){return{conv_0:r(3,32,3,"mobilenetv1/conv_0"),conv_1:o(32,64,"mobilenetv1/conv_1"),conv_2:o(64,128,"mobilenetv1/conv_2"),conv_3:o(128,128,"mobilenetv1/conv_3"),conv_4:o(128,256,"mobilenetv1/conv_4"),conv_5:o(256,256,"mobilenetv1/conv_5"),conv_6:o(256,512,"mobilenetv1/conv_6"),conv_7:o(512,512,"mobilenetv1/conv_7"),conv_8:o(512,512,"mobilenetv1/conv_8"),conv_9:o(512,512,"mobilenetv1/conv_9"),conv_10:o(512,512,"mobilenetv1/conv_10"),conv_11:o(512,512,"mobilenetv1/conv_11"),conv_12:o(512,1024,"mobilenetv1/conv_12"),conv_13:o(1024,1024,"mobilenetv1/conv_13")}},extractPredictionLayerParams:function(){return{conv_0:r(1024,256,1,"prediction_layer/conv_0"),conv_1:r(256,512,3,"prediction_layer/conv_1"),conv_2:r(512,128,1,"prediction_layer/conv_2"),conv_3:r(128,256,3,"prediction_layer/conv_3"),conv_4:r(256,128,1,"prediction_layer/conv_4"),conv_5:r(128,256,3,"prediction_layer/conv_5"),conv_6:r(256,64,1,"prediction_layer/conv_6"),conv_7:r(64,128,3,"prediction_layer/conv_7"),box_predictor_0:{box_encoding_predictor:n(512,12,1,"prediction_layer/box_predictor_0/box_encoding_predictor"),class_predictor:n(512,9,1,"prediction_layer/box_predictor_0/class_predictor")},box_predictor_1:{box_encoding_predictor:n(1024,24,1,"prediction_layer/box_predictor_1/box_encoding_predictor"),class_predictor:n(1024,18,1,"prediction_layer/box_predictor_1/class_predictor")},box_predictor_2:{box_encoding_predictor:n(512,24,1,"prediction_layer/box_predictor_2/box_encoding_predictor"),class_predictor:n(512,18,1,"prediction_layer/box_predictor_2/class_predictor")},box_predictor_3:{box_encoding_predictor:n(256,24,1,"prediction_layer/box_predictor_3/box_encoding_predictor"),class_predictor:n(256,18,1,"prediction_layer/box_predictor_3/class_predictor")},box_predictor_4:{box_encoding_predictor:n(256,24,1,"prediction_layer/box_predictor_4/box_encoding_predictor"),class_predictor:n(256,18,1,"prediction_layer/box_predictor_4/class_predictor")},box_predictor_5:{box_encoding_predictor:n(128,24,1,"prediction_layer/box_predictor_5/box_encoding_predictor"),class_predictor:n(128,18,1,"prediction_layer/box_predictor_5/class_predictor")}}}}}(r,t),i=s.extractMobilenetV1Params,u=s.extractPredictionLayerParams,c=i(),l=u(),p={extra_dim:a.Av9(r(20472),[1,5118,4])};if(t.push({paramPath:"output_layer/extra_dim"}),0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{params:{mobilenetv1:c,prediction_layer:l,output_layer:p},paramMappings:t}}(e)},t}(we);!function(e){i((function(){return null!==e&&e.apply(this,arguments)||this}),e)}(vt);var kt,xt=[new _(.738768,.874946),new _(2.42204,2.65704),new _(4.30971,7.04493),new _(10.246,4.59428),new _(12.6868,11.8741)],_t=[new _(1.603231,2.094468),new _(6.041143,7.080126

2),new _(2.882459,3.518061),new _(4.266906,5.178857),new _(9.041765,10.66308)],It=[117.001,114.697,97.404],St=function(e){return"number"==typeof e};function Nt(e){return a.G6I((function(){var t=a.E7T(e,a.SgB(.10000000149011612));return a.WQq(a.wDQ(a.AT$(e,t)),t)}))}function Mt(e,t){return a.G6I((function(){var n=a.eui(e,[[0,0],[1,1],[1,1],[0,0]]);return n=a.QlL(n,t.conv.filters,[1,1],"valid"),n=a.AT$(n,t.bn.sub),n=a.E7T(n,t.bn.truediv),Nt(n=a.WQq(n,t.conv.bias))}))}function Tt(e,t){return a.G6I((function(){var n=a.eui(e,[[0,0],[1,1],[1,1],[0,0]]);return n=a.Kd4(n,t.depthwise_filter,t.pointwise_filter,[1,1],"valid"),Nt(n=a.WQq(n,t.bias))}))}!function(e){e[e.XS=224]="XS",e[e.SM=320]="SM",e[e.MD=416]="MD",e[e.LG=608]="LG"}(kt||(kt={}));var Et=function(){function e(e){var t=void 0===e?{}:e,n=t.inputSize,r=t.scoreThreshold;if(this._name="TinyYolov2Options",this._inputSize=n||416,this._scoreThreshold=r||.5,"number"!=typeof this._inputSize||this._inputSize%32!=0)throw new Error(this._name+" - expected inputSize to be a number divisible by 32");if("number"!=typeof this._scoreThreshold||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(this._name+" - expected scoreThreshold to be a number between 0 and 1")}return Object.defineProperty(e.prototype,"inputSize",{get:function(){return this._inputSize},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"scoreThreshold",{get:function(){return this._scoreThreshold},enumerable:!0,configurable:!0}),e}(),At=function(e){function t(t){var n=e.call(this,"TinyYolov2")||this;return function(e){if(!e)throw new Error("invalid config: "+e);if("boolean"!=typeof e.withSeparableConvs)throw new Error("config.withSeparableConvs has to be a boolean, have: "+e.withSeparableConvs);if(!St(e.iouThreshold)||e.iouThreshold<0||e.iouThreshold>1)throw new Error("config.iouThreshold has to be a number between [0, 1], have: "+e.iouThreshold);if(!Array.isArray(e.classes)||!e.classes.length||!e.classes.every((function(e){return"string"==typeof e})))throw new Error("config.classes has to be an array class names: string[], have: "+JSON.stringify(e.classes));if(!Array.isArray(e.anchors)||!e.anchors.length||!e.anchors.map((function(e){return e||{}})).every((function(e){return St(e.x)&&St(e.y)})))throw new Error("config.anchors has to be an array of { x: number, y: number }, have: "+JSON.stringify(e.anchors));if(e.meanRgb&&(!Array.isArray(e.meanRgb)||3!==e.meanRgb.length||!e.meanRgb.every(St)))throw new Error("config.meanRgb has to be an array of shape [number, number, number], have: "+JSON.stringify(e.meanRgb))}(t),n._config=t,n}return i(t,e),Object.defineProperty(t.prototype,"config",{get:function(){return this._config},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"withClassScores",{get:function(){return this.config.withClassScores||this.config.classes.length>1},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"boxEncodingSize",{get:function(){return 5+(this.withClassScores?this.config.classes.length:0)},enumerable:!0,configurable:!0}),t.prototype.runTinyYolov2=function(e,t){var n=Mt(e,t.conv0);return n=Mt(n=a._SL(n,[2,2],[2,2],"same"),t.conv1),n=Mt(n=a._SL(n,[2,2],[2,2],"same"),t.conv2),n=Mt(n=a._SL(n,[2,2],[2,2],"same"),t.conv3),n=Mt(n=a._SL(n,[2,2],[2,2],"same"),t.conv4),n=Mt(n=a._SL(n,[2,2],[2,2],"same"),t.conv5),n=Mt(n=a._SL(n,[2,2],[1,1],"same"),t.conv6),_e(n=Mt(n,t.conv7),t.conv8,"valid",!1)},t.prototype.runMobilenet=function(e,t){var n=this.config.isFirstLayerConv2d?Nt(_e(e,t.conv0,"valid",!1)):Tt(e,t.conv0);return n=Tt(n=a._SL(n,[2,2],[2,2],"same"),t.conv1),n=Tt(n=a._SL(n,[2,2],[2,2],"same"),t.conv2),n=Tt(n=a._SL(n,[2,2],[2,2],"same"),t.conv3),n=Tt(n=a._SL(n,[2,2],[2,2],"same"),t.conv4),n=Tt(n=a._SL(n,[2,2],[2,2],"same"),t.conv5),n=a._SL(n,[2,2],[1,1],"same"),n=t.conv6?Tt(n,t.conv6):n,_e(n=t.conv7?Tt(n,t.conv7):n,t.conv8,"valid",!1)},t.prototype.forwardInput=function(e,t){var n=this,r=this.params;if(!r)throw new Error("TinyYolov2 - load model before inference");return a.G6I((function(){var o=e.toBatchTensor(t,!1).toFloat();return o=(o=n.config.meanRgb?A(o,n.config.meanRgb):o).div(a.SgB(256)),n.config.withSeparableConvs?n.runMobilenet(o,r):n.runTinyYolov2(o,r)}))},t.prototype.forward=function(e,t){return c(this,void 0,void 0,(function(){var n;return l(this,(function(r){switch(r.label){case 0:return n=this.forwardInput,[4,pe(e)];case 1:return[4,n.apply(this,[r.sent(),t])];case 2:return[2,r.sent()]}}))}))},t.prototype.detect=function(e,t){return void 0===t&&(t={}),c(this,void 0,void 0,(function(){var n,r,o,s,i,u,c,p,d,h,f,m,g=this;return l(this,(function(l){switch(l.label){case 0:return n=new Et(t),r=n.inputSize,o=n.scoreThreshold,[4,pe(e)];case 1:return s=l.sent(),[4,this.forwardInput(s,r)];case 2:return i=l.sent(),u=a.G6I((function(){return a.iqB(i)[0].expandDims()})),c={width:s.getInputWidth(0),height:s.getInputHeight(0)},[4,this.extractBoxes(u,s.getReshapedInputDimensions(0),o)];case 3:return p=l.sent(),i.dispose(),u.dispose(),d=p.map((function(e){return e.box})),h=p.map((function(e){return e.score})),f=p.map((function(e){return e.classScore})),m=p.map((function(e){return g.config.classes[e.label]})),[2,E(d.map((function(e){return e.rescale(r)})),h,this.config.iouThreshold,!0).map((function(e){return new N(h[e],f[e],m[e],d[e],c)}))]}}))}))},t.prototype.getDefaultModelName=function(){return""},t.prototype.extractParamsFromWeigthMap=function(e){return function(e,t){var n,r=[],a=function(e,t){var n=Ae(e,t);function r(e){return{filters:n(e+"/filters",4),bias:n(e+"/bias",1)}}return{extractConvParams:r,extractConvWithBatchNormParams:function(e){var t=r(e+"/conv"),a=function(e){return{sub:n(e+"/sub",1),truediv:n(e+"/truediv",1)}}(e+"/bn");return{conv:t,bn:a}},extractSeparableConvParams:Ee(n)}}(e,r),o=a.extractConvParams,s=a.extractConvWithBatchNormParams,i=a.extractSeparableConvParams;if(t.withSeparableConvs){var u=t.filterSizes&&t.filterSizes.length||9;n={conv0:t.isFirstLayerConv2d?o("conv0"):i("conv0"),conv1:i("conv1"),conv2:i("conv2"),conv3:i("conv3"),conv4:i("conv4"),conv5:i("conv5"),

2conv6:u>7?i("conv6"):void 0,conv7:u>8?i("conv7"):void 0,conv8:o("conv8")}}else n={conv0:s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:s("conv6"),conv7:s("conv7"),conv8:o("conv8")};return Ie(e,r),{params:n,paramMappings:r}}(e,this.config)},t.prototype.extractParams=function(e){var n=this.config.filterSizes||t.DEFAULT_FILTER_SIZES,r=n?n.length:void 0;if(7!==r&&8!==r&&9!==r)throw new Error("TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found "+r+" filterSizes in config");return function(e,t,n,r){var o,s=Fe(e),i=s.extractWeights,u=s.getRemainingWeights,c=[],l=function(e,t){var n=Se(e,t),r=Te(e,t);return{extractConvParams:n,extractConvWithBatchNormParams:function(r,o,s){var i=n(r,o,3,s+"/conv"),u=function(n,r){var o=a.SC3(e(n)),s=a.SC3(e(n));return t.push({paramPath:r+"/sub"},{paramPath:r+"/truediv"}),{sub:o,truediv:s}}(o,s+"/bn");return{conv:i,bn:u}},extractSeparableConvParams:r}}(i,c),p=l.extractConvParams,d=l.extractConvWithBatchNormParams,h=l.extractSeparableConvParams;if(t.withSeparableConvs){var f=r[0],m=r[1],g=r[2],y=r[3],b=r[4],w=r[5],v=r[6],k=r[7],x=r[8];o={conv0:t.isFirstLayerConv2d?p(f,m,3,"conv0"):h(f,m,"conv0"),conv1:h(m,g,"conv1"),conv2:h(g,y,"conv2"),conv3:h(y,b,"conv3"),conv4:h(b,w,"conv4"),conv5:h(w,v,"conv5"),conv6:k?h(v,k,"conv6"):void 0,conv7:x?h(k,x,"conv7"):void 0,conv8:p(x||k||v,5*n,1,"conv8")}}else f=r[0],m=r[1],g=r[2],y=r[3],b=r[4],w=r[5],v=r[6],k=r[7],x=r[8],o={conv0:d(f,m,"conv0"),conv1:d(m,g,"conv1"),conv2:d(g,y,"conv2"),conv3:d(y,b,"conv3"),conv4:d(b,w,"conv4"),conv5:d(w,v,"conv5"),conv6:d(v,k,"conv6"),conv7:d(k,x,"conv7"),conv8:p(x,5*n,1,"conv8")};if(0!==u().length)throw new Error("weights remaing after extract: "+u().length);return{params:o,paramMappings:c}}(e,this.config,this.boxEncodingSize,n)},t.prototype.extractBoxes=function(e,t,n){return c(this,void 0,void 0,(function(){var r,o,s,i,c,p,d,h,f,m,g,y,b,w,v,k,x,_,I,N,M,T,E,A,D,O,C,P,R,$=this;return l(this,(function(l){switch(l.label){case 0:return r=t.width,o=t.height,s=Math.max(r,o),i=s/r,c=s/o,p=e.shape[1],d=this.config.anchors.length,h=a.G6I((function(){var t=e.reshape([p,p,d,$.boxEncodingSize]);return[t.slice([0,0,0,0],[p,p,d,4]),t.slice([0,0,0,4],[p,p,d,1]),$.withClassScores?a.UhY(t.slice([0,0,0,5],[p,p,d,$.config.classes.length]),3):a.SgB(0)]})),f=h[0],m=h[1],g=h[2],y=[],[4,m.array()];case 1:return b=l.sent(),[4,f.array()];case 2:w=l.sent(),v=0,l.label=3;case 3:if(!(v<p))return[3,12];k=0,l.label=4;case 4:if(!(k<p))return[3,11];x=0,l.label=5;case 5:return x<d?(_=F(b[v][k][x][0]),!n||_>n?(I=(k+F(w[v][k][x][0]))/p*i,N=(v+F(w[v][k][x][1]))/p*c,M=Math.exp(w[v][k][x][2])*this.config.anchors[x].x/p*i,T=Math.exp(w[v][k][x][3])*this.config.anchors[x].y/p*c,E=I-M/2,A=N-T/2,D={row:v,col:k,anchor:x},this.withClassScores?[4,this.extractPredictedClass(g,D)]:[3,7]):[3,9]):[3,10];case 6:return R=l.sent(),[3,8];case 7:R={classScore:1,label:0},l.label=8;case 8:C=(O=R).classScore,P=O.label,y.push(u({box:new S(E,A,E+M,A+T),score:_,classScore:_*C,label:P},D)),l.label=9;case 9:return x++,[3,5];case 10:return k++,[3,4];case 11:return v++,[3,3];case 12:return f.dispose(),m.dispose(),g.dispose(),[2,y]}}))}))},t.prototype.extractPredictedClass=function(e,t){return c(this,void 0,void 0,(function(){var n,r,a,o;return l(this,(function(s){switch(s.label){case 0:return n=t.row,r=t.col,a=t.anchor,[4,e.array()];case 1:return o=s.sent(),[2,Array(this.config.classes.length).fill(0).map((function(e,t){return o[n][r][a][t]})).map((function(e,t){return{classScore:e,label:t}})).reduce((function(e,t){return e.classScore>t.classScore?e:t}))]}}))}))},t.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024],t}(we),Ft=function(e){function t(t){void 0===t&&(t=!0);var n=Object.assign({},{withSeparableConvs:t,iouThreshold:.4,classes:["face"]},t?{anchors:_t,meanRgb:It}:{anchors:xt,withClassScores:!0});return e.call(this,n)||this}return i(t,e),Object.defineProperty(t.prototype,"withSeparableConvs",{get:function(){return this.config.withSeparableConvs},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"anchors",{get:function(){return this.config.anchors},enumerable:!0,configurable:!0}),t.prototype.locateFaces=function(e,t){return c(this,void 0,void 0,(function(){return l(this,(function(n){switch(n.label){case 0:return[4,this.detect(e,t)];case 1:return[2,n.sent().map((function(e){return new M(e.score,e.relativeBox,{width:e.imageWidth,height:e.imageHeight})}))]}}))}))},t.prototype.getDefaultModelName=function(){return this.withSeparableConvs?"tiny_yolov2_separable_conv_model":"tiny_yolov2_model"},t.prototype.extractParamsFromWeigthMap=function(t){return e.prototype.extractParamsFromWeigthMap.call(this,t)},t}(At),Dt=function(e){function t(){var t=null!==e&&e.apply(this,arguments)||this;return t._name="TinyFaceDetectorOptions",t}return i(t,e),t}(Et),Ot=function(){function e(){}return e.prototype.then=function(e){return c(this,void 0,void 0,(function(){var t;return l(this,(function(n){switch(n.label){case 0:return t=e,[4,this.run()];case 1:return[2,t.apply(void 0,[n.sent()])]}}))}))},e.prototype.run=function(){return c(this,void 0,void 0,(function(){return l(this,(function(e){throw new Error("ComposableTask - run is not implemented")}))}))},e}();function Ct(e,t){var n={descriptor:t};return Object.assign({},e,n)}function Pt(e,t,n,r,o){return void 0===o&&(o=function(e){return e.alignedRect}),c(this,void 0,void 0,(function(){var s,i,u,c,p;return l(this,(function(l){switch(l.label){case 0:return s=e.map((function(e){return Ve(e)?o(e):e.detection})),(u=r)?[3,5]:t instanceof a.w3A?[4,he(t,s)]:[3,2];case 1:return c=l.sent(),[3,4];case 2:return[4,de(t,s)];case 3:c=l.sent(),l.label=4;case 4:u=c,l.label=5;case 5:return[4,n(i=u)];

2case 6:return p=l.sent(),i.forEach((function(e){return e instanceof a.w3A&&e.dispose()})),[2,p]}}))}))}function Rt(e,t,n,r,a){return c(this,void 0,void 0,(function(){var o=this;return l(this,(function(s){return[2,Pt([e],t,(function(e){return c(o,void 0,void 0,(function(){return l(this,(function(t){return[2,n(e[0])]}))}))}),r,a)]}))}))}function $t(e,t){var n=t[0],r=t[1];return{height:Math.floor(n*e),width:Math.floor(r*e)}}var Lt=function(e){function t(t,n,r,a){return e.call(this,{left:t,top:n,right:r,bottom:a},!0)||this}return i(t,e),t}(I);function Wt(e){return a.G6I((function(){return a.E7T(a.AT$(e,a.SgB(127.5)),a.SgB(.0078125))}))}function zt(e,t){return a.G6I((function(){return a.WQq(a.wDQ(e),a.E7T(t,a.KUd(a.wDQ(a.KUd(e)))))}))}function Bt(e,t,n){return void 0===n&&(n=!1),a.G6I((function(){var r=_e(e,t.conv1,"valid");return r=zt(r,t.prelu1_alpha),r=zt(r=_e(r=a._SL(r,n?[2,2]:[3,3],[2,2],"same"),t.conv2,"valid"),t.prelu2_alpha),zt(r=_e(r=n?r:a._SL(r,[3,3],[2,2],"valid"),t.conv3,"valid"),t.prelu3_alpha)}))}function Ut(e,t,n,r,o){o.stage1=[];var s=t.map((function(t){return a.G6I((function(){var n={scale:t},o=function(e,t){return a.G6I((function(){var n=$t(t,e.shape.slice(1)),r=n.height,o=n.width,s=Wt(a.c$0.resizeBilinear(e,[r,o]));return a.oLj(s,[0,2,1,3])}))}(e,t),s=Date.now(),i=function(e,t){return a.G6I((function(){var n=Bt(e,t,!0),r=_e(n,t.conv4_1,"valid"),o=a.aW5(a.kvL(r,3),3);return{prob:a.UhY(a.AT$(r,o),3),regions:_e(n,t.conv4_2,"valid")}}))}(o,r),u=i.prob,c=i.regions;return n.pnet=Date.now()-s,{scoresTensor:a.iqB(a.iqB(u,3)[1])[0],regionsTensor:a.iqB(c)[0],scale:t,statsForScale:n}}))})),i=s.map((function(e){var t=e.scoresTensor,r=e.regionsTensor,a=e.scale,s=e.statsForScale,i=function(e,t,n,r){for(var a=[],o=e.arraySync(),s=0;s<e.shape[0];s++)for(var i=0;i<e.shape[1];i++)o[s][i]>=r&&a.push(new _(i,s));return a.map((function(e){var r=new S(Math.round((2*e.y+1)/n),Math.round((2*e.x+1)/n),Math.round((2*e.y+12)/n),Math.round((2*e.x+12)/n)),a=o[e.y][e.x],s=t.arraySync();return{cell:r,score:a,region:new Lt(s[e.y][e.x][0],s[e.y][e.x][1],s[e.y][e.x][2],s[e.y][e.x][3])}}))}(t,r,a,n);if(t.dispose(),r.dispose(),!i.length)return o.stage1.push(s),[];var u=Date.now(),c=E(i.map((function(e){return e.cell})),i.map((function(e){return e.score})),.5);return s.nms=Date.now()-u,s.numBoxes=c.length,o.stage1.push(s),c.map((function(e){return i[e]}))})),u=i.reduce((function(e,t){return e.concat(t)}),[]),c=[],l=[];if(u.length>0){var p=Date.now(),d=E(u.map((function(e){return e.cell})),u.map((function(e){return e.score})),.7);o.stage1_nms=Date.now()-p,l=d.map((function(e){return u[e].score})),c=d.map((function(e){return u[e]})).map((function(e){var t=e.cell,n=e.region;return new S(t.left+n.left*t.width,t.top+n.top*t.height,t.right+n.right*t.width,t.bottom+n.bottom*t.height).toSquare().round()}))}return{boxes:c,scores:l}}function Ht(e,t,n){var r=n.width,o=n.height;return c(this,void 0,void 0,(function(){var n,s,i,u=this;return l(this,(function(p){switch(p.label){case 0:return n=Z(e),[4,Promise.all(t.map((function(t){return c(u,void 0,void 0,(function(){var r,a,o,s,i,u,c,p;return l(this,(function(l){return r=t.padAtBorders(e.height,e.width),a=r.y,o=r.ey,s=r.x,i=r.ex,u=s-1,c=a-1,p=n.getImageData(u,c,i-u,o-c),[2,Y.isNodejs()?ie(p):createImageBitmap(p)]}))}))})))];case 1:return s=p.sent(),i=[],s.forEach((function(e){var t=Z(se({width:r,height:o}));t.drawImage(e,0,0,r,o);for(var n=t.getImageData(0,0,r,o).data,a=[],s=0;s<n.length;s+=4)a.push(n[s+2]),a.push(n[s+1]),a.push(n[s]);i.push(a)})),[2,i.map((function(e){return a.G6I((function(){return Wt(a.oLj(a.IFH(e,[1,r,o,3]),[0,2,1,3]).toFloat())}))}))]}}))}))}function Vt(e,t,n,r,o){return c(this,void 0,void 0,(function(){var s,i,u,c,p,d,h,f,m,g,y,b,w,v;return l(this,(function(l){switch(l.label){case 0:return s=Date.now(),[4,Ht(e,t,{width:24,height:24})];case 1:return i=l.sent(),o.stage2_extractImagePatches=Date.now()-s,s=Date.now(),u=i.map((function(e){var t=function(e,t){return a.G6I((function(){var n=Bt(e,t),r=zt(Re(a.OoG(n,[n.shape[0],t.fc1.weights.shape[0]]),t.fc1),t.prelu4_alpha),o=Re(r,t.fc2_1),s=a.aW5(a.kvL(o,1),1),i=a.UhY(a.AT$(o,s),1),u=Re(r,t.fc2_2);return{scores:a.iqB(i,1)[1],regions:u}}))}(e,r);return e.dispose(),t})),o.stage2_rnet=Date.now()-s,c=u.length>1?a.WUr(u.map((function(e){return e.scores}))):u[0].scores,h=(d=Array).from,[4,c.data()];case 2:return p=h.apply(d,[l.sent()]),c.dispose(),f=p.map((function(e,t){return{score:e,idx:t}})).filter((function(e){return e.score>n})).map((function(e){return e.idx})),m=f.map((function(e){return t[e]})),g=f.map((function(e){return p[e]})),y=[],b=[],m.length>0&&(s=Date.now(),w=E(m,g,.7),o.stage2_nms=Date.now()-s,v=w.map((function(e){var t=u[f[e]].regions.arraySync();return new Lt(t[0][0],t[0][1],t[0][2],t[0][3])})),b=w.map((function(e){return g[e]})),y=w.map((function(e,t){return m[e].calibrate(v[t])}))),u.forEach((function(e){e.regions.dispose(),e.scores.dispose()})),[2,{boxes:y,scores:b}]}}))}))}function Gt(e,t,n,r,o){return c(this,void 0,void 0,(function(){var s,i,u,c,p,d,h,f,m,g,y,b,w,v,k;return l(this,(function(l){switch(l.label){case 0:return s=Date.now(),[4,Ht(e,t,{width:48,height:48})];case 1:return i=l.sent(),o.stage3_extractImagePatches=Date.now()-s,s=Date.now(),u=i.map((function(e){var t=function(e,t){return a.G6I((function(){var n=Bt(e,t);n=zt(n=_e(n=a._SL(n,[2,2],[2,2],"same"),t.conv4,"valid"),t.prelu4_alpha);var r=zt(Re(a.OoG(n,[n.shape[0],t.fc1.weights.shape[0]]),t.fc1),t.prelu5_alpha),o=Re(r,t.fc2_1),s=a.aW5(a.kvL(o,1),1),i=a.UhY(a.AT$(o,s),1),u=Re(r,t.fc2_2),c=Re(r,t.fc2_3);return{scores:a.iqB(i,1)[1],regions:u,points:c}}))}(e,r);return e.dispose(),t})),o.stage3_onet=Date.now()-s,c=u.length>1?a.WUr(u.map((function(e){return e.scores}))):u[0].scores,h=(d=Array).from,[4,c.data()];case 2:return p=h.apply(d,[l.sent()]),c.dispose(),f=p.map((function(e,t){return{score:e,idx:t}})).filter((function(e){return e.score>n})).map((function(e){return e.idx})),m=f.map((function(e){var t=u[e].regions.arraySync();return new Lt(t[0][0],t[0][1],t[0][2],t[0][3])})),g=f.map((function(e,n){return t[e].calibrate(m[n])})),y=f.map((function(e){return p[e]})),b=[],w=[],v=[],g.length>0&&(s=Date.now(),k=E(g,y,.7,!1),o.stage3_nms=Date.now()-s,b=k.map((function(e){return g[e]})),w=k.map((function(e){return y[e]})),v=k.map((function(e,t){return Array(5).fill(0).map((function(n,r){var a=u[e].points.arraySync();return new 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2=!1,this.idTensor=(0,N.SgB)(0),(0,N.Oi1)(this.idTensor)}get id(){return this.idTensor.id}get closed(){return this.closed_}clearAndClose(e){this.tensors.forEach((t=>{null!=e&&e.has(t.tensor.id)||t.tensor.dispose()})),this.tensors=[],this.closed_=!0,this.idTensor.dispose()}size(){return this.tensors.length}read(e){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||e>=this.size())throw new Error(`Tried to read from index ${e}, but array size is: ${this.size()}`);const t=this.tensors[e];if(t.cleared)throw new Error(`TensorArray ${this.name}: Could not read index ${e} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);return this.clearAfterRead&&(t.cleared=!0),t.read=!0,t.tensor}readMany(e){return e.map((e=>this.read(e)))}write(e,t){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||!this.dynamicSize&&e>=this.maxSize)throw new Error(`Tried to write to index ${e}, but array is not resizeable and size is: ${this.maxSize}`);const n=this.tensors[e]||{};if(t.dtype!==this.dtype)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e},\n          because the value dtype is ${t.dtype}, but TensorArray dtype is ${this.dtype}.`);if(0!==this.size()||null!=this.elementShape&&0!==this.elementShape.length||(this.elementShape=t.shape),ve(this.elementShape,t.shape,`TensorArray ${this.name}: Could not write to TensorArray index ${e}.`),n.read)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been read.`);if(n.written)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been written.`);n.tensor=t,(0,N.Oi1)(t),n.written=!0,this.tensors[e]=n}writeMany(e,t){if(e.length!==t.length)throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${e.length} is not the same as tensors size: ${t.length}.`);e.forEach(((e,n)=>this.write(e,t[n])))}gather(e,t){if(t&&t!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${t}`);if(e)e=e.slice(0,this.size());else{e=[];for(let t=0;t<this.size();t++)e.push(t)}if(0===e.length)return(0,N.mwg)([],[0].concat(this.elementShape));const n=this.readMany(e);return ve(this.elementShape,n[0].shape,"TensorArray shape mismatch: "),(0,N.Qfh)(n,0)}concat(e){if(e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(0===this.size())return(0,N.mwg)([],[0].concat(this.elementShape));const t=[];for(let e=0;e<this.size();e++)t.push(e);const n=this.readMany(t);return ve(this.elementShape,n[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${n[0].shape})`),(0,N.WUr)(n,0)}scatter(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);if(e.length!==t.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${e.length} vs. ${t.shape[0]}`);const n=Math.max(...e);if(!this.dynamicSize&&n>=this.maxSize)throw new Error(`Max index must be < array size (${n}  vs. ${this.maxSize})`);this.writeMany(e,(0,N.iqB)(t,0))}split(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);let n=0;const r=e.map((e=>(n+=e,n)));if(n!==t.shape[0])throw new Error(`Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        ${n}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);const a=0===n?0:t.size/n,o=[];(0,N.G6I)((()=>{t=(0,N.OoG)(t,[1,n,a]);for(let n=0;n<e.length;++n){const s=[0,0===n?0:r[n-1],0],i=[1,e[n],a];o[n]=(0,N.OoG)((0,N.SME)(t,s,i),this.elementShape)}return o}));const s=[];for(let t=0;t<e.length;t++)s[t]=t;this.writeMany(s,o)}}class Se{get id(){return this.idTensor.id}constructor(e,t,n,r=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,null!=e&&e.forEach((e=>{if(n!==e.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${e.dtype}`);ve(t,e.shape,"TensorList shape mismatch: "),(0,N.Oi1)(e)})),this.idTensor=(0,N.SgB)(0),this.maxNumElements=r,(0,N.Oi1)(this.idTensor)}copy(){return new Se([...this.tensors],this.elementShape,this.elementDtype)}

2clearAndClose(e){this.tensors.forEach((t=>{null!=e&&e.has(t.id)||t.dispose()})),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(e,t,n=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(-1!==n&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);ve(e,this.elementShape,"TensorList shape mismatch: ");const r=xe(this.elementShape,this.tensors,e);return(0,N.G6I)((()=>{const e=this.tensors.map((e=>(0,N.OoG)(e,r)));return(0,N.Qfh)(e,0)}))}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(0===this.size())throw new Error("Trying to pop from an empty list.");const n=xe(this.elementShape,this.tensors,e),r=this.tensors.pop();return r.kept=!1,ve(r.shape,e,"TensorList shape mismatch: "),(0,N.OoG)(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(ve(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");(0,N.Oi1)(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(-1!==this.maxNumElements&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);const t=new Se([],this.elementShape,this.elementDtype,this.maxNumElements);t.tensors.length=e;for(let n=0;n<Math.min(this.tensors.length,e);++n)t.tensors[n]=this.tensors[n];return t}getItem(e,t,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${this.elementDtype}`);if(e<0||e>this.tensors.length)throw new Error(`Trying to access element ${e} in a list with ${this.tensors.length} elements.`);if(null==this.tensors[e])throw new Error(`element at index ${e} is null.`);ve(this.tensors[e].shape,t,"TensorList shape mismatch: ");const r=xe(this.elementShape,this.tensors,t);return(0,N.OoG)(this.tensors[e],r)}setItem(e,t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(e<0||-1!==this.maxNumElements&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);ve(this.elementShape,t.shape,"TensorList shape mismatch: "),(0,N.Oi1)(t),null!=this.tensors[e]&&(this.tensors[e].kept=!1),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);ve(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());const r=xe(this.elementShape,this.tensors,n);return 0===e.length?(0,N.mwg)([],[0].concat(r)):(0,N.G6I)((()=>{const t=e.map((e=>(0,N.OoG)(this.tensors[e],r)));return(0,N.Qfh)(t,0)}))}concat(e,t){if(e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);ve(this.elementShape,t,"TensorList shape mismatch: ");const n=xe(this.elementShape,this.tensors,t);return 0===this.size()?(0,N.mwg)([],[0].concat(n)):(0,N.G6I)((()=>{const e=this.tensors.map((e=>(0,N.OoG)(e,n)));return(0,N.WUr)(e,0)}))}}function Ne(e,t,n){const[r,a]=E("fusedOps",e,t,n),o="biasadd"===r,s=!o,i="prelu"===a,u="fusedbatchnorm"===r,c=E("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=E("strides",e,t,n),p=P(e,t,n),d=E("dataFormat",e,t,n).toUpperCase(),h=E("dilations",e,t,n);let[f,m]=E("args",e,t,n);return s&&(m=f,f=void 0),{stride:l,pad:p,dataFormat:d,dilations:h,biasArg:f,preluArg:m,activationFunc:a,leakyreluAlpha:E("leakyreluAlpha",e,t,n)}}function Me(e,t,n){return{boxes:E("boxes",e,t,n),scores:E("scores",e,t,n),maxOutputSize:E("maxOutputSize",e,t,n),iouThreshold:E("iouThreshold",e,t,n),scoreThreshold:E("scoreThreshold",e,t,n),softNmsSigma:E("softNmsSigma",e,t,n)}}var Te=n(12988);class Ee{get id(){return this.handle.id}constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=(0,N.SgB)(0),this.tensorMap=new Map,(0,N.Oi1)(this.handle)}

2clearAndClose(){this.tensorMap.forEach((e=>e.dispose())),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return Te.S(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,N.G6I)((()=>{const e=(0,N.iqB)(t),r=n.length,a=e.length;N.euu.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,N.Oi1)(a),this.tensorMap.set(r,a)}return this.handle}))}async find(e,t){this.checkKeyAndValueTensor(e,t);const n=await e.data();return(0,N.G6I)((()=>{const e=[];for(let r=0;r<n.length;r++){const a=n[r],o=this.findWithDefault(a,t);e.push(o)}return(0,N.Qfh)(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 ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}}function Ae(e,t,n,r,a=N.G6I){const o=((e,t,n)=>{switch(e.category){case"arithmetic":return a((()=>((e,t,n,r=x)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[r.add(E("a",e,t,n),E("b",e,t,n))];case"AddN":return[r.addN(E("tensors",e,t,n))];case"FloorMod":case"Mod":return[r.mod(E("a",e,t,n),E("b",e,t,n))];case"Mul":return[r.mul(E("a",e,t,n),E("b",e,t,n))];case"RealDiv":case"Div":return[r.div(E("a",e,t,n),E("b",e,t,n))];case"DivNoNan":return[r.divNoNan(E("a",e,t,n),E("b",e,t,n))];case"FloorDiv":return[r.floorDiv(E("a",e,t,n),E("b",e,t,n))];case"Sub":return[r.sub(E("a",e,t,n),E("b",e,t,n))];case"Minimum":return[r.minimum(E("a",e,t,n),E("b",e,t,n))];case"Maximum":return[r.maximum(E("a",e,t,n),E("b",e,t,n))];case"Pow":return[r.pow(E("a",e,t,n),E("b",e,t,n))];case"SquaredDifference":return[r.squaredDifference(E("a",e,t,n),E("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"basic_math":return a((()=>((e,t,n,r=x)=>{switch(e.op){case"Abs":case"ComplexAbs":return[r.abs(E("x",e,t,n))];case"Acos":return[r.acos(E("x",e,t,n))];case"Acosh":return[r.acosh(E("x",e,t,n))];case"Asin":return[r.asin(E("x",e,t,n))];case"Asinh":return[r.asinh(E("x",e,t,n))];case"Atan":return[r.atan(E("x",e,t,n))];case"Atan2":return[r.atan2(E("x",e,t,n),E("y",e,t,n))];case"Atanh":return[r.atanh(E("x",e,t,n))];case"Ceil":return[r.ceil(E("x",e,t,n))];case"Complex":return[r.complex(E("real",e,t,n),E("imag",e,t,n))];case"Cos":return[r.cos(E("x",e,t,n))];case"Cosh":return[r.cosh(E("x",e,t,n))];case"Elu":return[r.elu(E("x",e,t,n))];case"Erf":return[r.erf(E("x",e,t,n))];case"Exp":return[r.exp(E("x",e,t,n))];case"Expm1":return[r.expm1(E("x",e,t,n))];case"Floor":return[r.floor(E("x",e,t,n))];case"Log":return[r.log(E("x",e,t,n))];case"Log1p":return[r.log1p(E("x",e,t,n))];case"Imag":return[r.imag(E("x",e,t,n))];case"Neg":return[r.neg(E("x",e,t,n))];case"Reciprocal":return[r.reciprocal(E("x",e,t,n))];case"Real":return[r.real(E("x",e,t,n))];case"Relu":return[r.relu(E("x",e,t,n))];case"Round":return[r.round(E("x",e,t,n))];case"Selu":return[r.selu(E("x",e,t,n))];case"Sigmoid":return[r.sigmoid(E("x",e,t,n))];case"Sin":return[r.sin(E("x",e,t,n))];case"Sign":return[r.sign(E("x",e,t,n))];case"Sinh":return[r.sinh(E("x",e,t,n))];case"Softplus":return[r.softplus(E("x",e,t,n))];case"Sqrt":return[r.sqrt(E("x",e,t,n))];case"Square":return[r.square(E("x",e,t,n))];case"Tanh":return[r.tanh(E("x",e,t,n))];case"Tan":return[r.tan(E("x",e,t,n))];case"ClipByValue":return[r.clipByValue(E("x",e,t,n),E("clipValueMin",e,t,n),E("clipValueMax",e,t,n))];case"Relu6":return[r.relu6(E("x",e,t,n))];case"Rsqrt":return[r.rsqrt(A(e.inputNames[0],t,n))];case"LeakyRelu":return[r.leakyRelu(E("x",e,t,n),E("alpha",e,t,n))];case"Prelu":return[r.prelu(E("x",e,t,n),E("alpha",e,t,n))];case"IsNan":return[r.isNaN(A(e.inputNames[0],t,n))];case"IsInf":return[r.isInf(A(e.inputNames[0],t,n))];case"IsFinite":return[r.isFinite(A(e.inputNames[0],t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"control":return(async(e,t,n)=>{switch(e.op){case"If":case"StatelessIf":{const r=E("thenBranch",e,t,n),a=E("elseBranch",e,t,n),o=E("cond",e,t,n),s=E("args",e,t,n);return(await o.data())[0]?n.functionMap[r].executeFunctionAsync(s,n.tensorArrayMap,n.tensorListMap):n.functionMap[a].executeFunctionAsync(s,n.tensorArrayMap,n.tensorListMap)}case"While":case"StatelessWhile":{const r=E("body",e,t,n),a=E("cond",e,t,n),o=E("args",e,t,n),s=await n.functionMap[a].executeFunctionAsync(o,n.tensorArrayMap,n.tensorListMap),i=o.map((e=>e.id));let u=await s[0].data();

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[R(E("pred",e,t,n))];case"Switch":{const r=E("pred",e,t,n);let a=E("data",e,t,n);return a.kept||(a=R(a)),(await r.data())[0]?[void 0,a]:[a,void 0]}case"Merge":{const r=e.inputNames.find((e=>void 0!==A(e,t,n)));return r?[R(A(r,t,n))]:void 0}case"Enter":{const r=E("frameName",e,t,n),a=E("tensor",e,t,n);return n.enterFrame(r),[R(a)]}case"Exit":{const r=E("tensor",e,t,n);return n.exitFrame(),[R(r)]}case"NextIteration":{const r=E("tensor",e,t,n);return n.nextIteration(),[R(r)]}case"TensorArrayV3":{const r=E("size",e,t,n),a=E("dtype",e,t,n),o=E("elementShape",e,t,n),s=E("dynamicSize",e,t,n),i=E("clearAfterRead",e,t,n),u=E("identicalElementShapes",e,t,n),c=E("name",e,t,n),l=new Ie(c,a,r,o,u,s,i);return n.addTensorArray(l),[l.idTensor,(0,N.SgB)(1)]}case"TensorArrayWriteV3":{const r=E("tensorArrayId",e,t,n),a=E("index",e,t,n),o=E("tensor",e,t,n),s=n.getTensorArray(r.id);return s.write(a,o),[s.idTensor]}case"TensorArrayReadV3":{const r=E("tensorArrayId",e,t,n),a=E("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{const r=E("tensorArrayId",e,t,n),a=E("indices",e,t,n),o=E("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,o)]}case"TensorArrayScatterV3":{const r=E("tensorArrayId",e,t,n),a=E("indices",e,t,n),o=E("tensor",e,t,n),s=n.getTensorArray(r.id);return s.scatter(a,o),[s.idTensor]}case"TensorArrayConcatV3":{const r=E("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),o=E("dtype",e,t,n);return[a.concat(o)]}case"TensorArraySplitV3":{const r=E("tensorArrayId",e,t,n),a=E("tensor",e,t,n),o=E("lengths",e,t,n),s=n.getTensorArray(r.id);return s.split(o,a),[s.idTensor]}case"TensorArraySizeV3":{const r=E("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return[(0,N.SgB)(a.size(),"int32")]}case"TensorArrayCloseV3":{const r=E("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{const r=E("tensorListId",e,t,n),a=E("index",e,t,n),o=E("tensor",e,t,n),s=n.getTensorList(r.id);return s.setItem(a,o),[s.idTensor]}case"TensorListGetItem":{const r=E("tensorListId",e,t,n),a=E("index",e,t,n),o=E("elementShape",e,t,n),s=E("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,o,s)]}case"TensorListScatterV2":case"TensorListScatter":{const r=E("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 Se([],n,e.dtype,r),s=(0,N.iqB)(e,0);return t.forEach(((e,t)=>{o.setItem(e,s[t])})),o}(E("tensor",e,t,n),r,E("elementShape",e,t,n),E("numElements",e,t,n));return n.addTensorList(a),[a.idTensor]}case"TensorListReserve":case"EmptyTensorList":{const r=E("elementShape",e,t,n),a=E("elementDType",e,t,n);let o;o="TensorListReserve"===e.op?"numElements":"maxNumElements";const s=E(o,e,t,n),i=function(e,t,n,r){return new Se([],e,t,r)}(r,a,0,"TensorListReserve"===e.op?-1:s);return n.addTensorList(i),[i.idTensor]}case"TensorListGather":{const r=E("tensorListId",e,t,n),a=E("indices",e,t,n),o=E("elementShape",e,t,n),s=E("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,s,o)]}case"TensorListStack":{const 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a((()=>((e,t,n,r=x)=>{switch(e.op){case"Equal":return[r.equal(E("a",e,t,n),E("b",e,t,n))];case"NotEqual":return[r.notEqual(E("a",e,t,n),E("b",e,t,n))];case"Greater":return[r.greater(E("a",e,t,n),E("b",e,t,n))];case"GreaterEqual":return[r.greaterEqual(E("a",e,t,n),E("b",e,t,n))];case"Less":return[r.less(E("a",e,t,n),E("b",e,t,n))];case"LessEqual":return[r.lessEqual(E("a",e,t,n),E("b",e,t,n))];case"LogicalAnd":return[r.logicalAnd(E("a",e,t,n),E("b",e,t,n))];case"LogicalNot":return[r.logicalNot(E("a",e,t,n))];case"LogicalOr":return[r.logicalOr(E("a",e,t,n),E("b",e,t,n))];

2case"Select":case"SelectV2":return[r.where(E("condition",e,t,n),E("a",e,t,n),E("b",e,t,n))];case"BitwiseAnd":return[r.bitwiseAnd(E("a",e,t,n),E("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"matrices":return a((()=>((e,t,n,r=x)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[r.matMul(E("a",e,t,n),E("b",e,t,n),E("transposeA",e,t,n),E("transposeB",e,t,n))];case"Einsum":return[r.einsum(E("equation",e,t,n),...E("tensors",e,t,n))];case"Transpose":return[r.transpose(E("x",e,t,n),E("perm",e,t,n))];case"_FusedMatMul":const[a,o]=E("fusedOps",e,t,n),s="biasadd"===a,i="prelu"===o,u=E("numArgs",e,t,n),c=E("leakyreluAlpha",e,t,n);if(s){if(i&&2!==u)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&1!==u)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}const[l,p]=E("args",e,t,n);return[r.fused.matMul({a:E("a",e,t,n),b:E("b",e,t,n),transposeA:E("transposeA",e,t,n),transposeB:E("transposeB",e,t,n),bias:l,activation:o,preluActivationWeights:p,leakyreluAlpha:c})];case"MatrixBandPart":return[r.linalg.bandPart(E("a",e,t,n),E("numLower",e,t,n),E("numUpper",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"normalization":return a((()=>((e,t,n,r=x)=>{switch(e.op){case"EuclideanNorm":return[r.euclideanNorm(E("x",e,t,n),E("axis",e,t,n),E("keepDims",e,t,n))];case"FusedBatchNorm":case"FusedBatchNormV2":case"FusedBatchNormV3":return[r.batchNorm(E("x",e,t,n),E("mean",e,t,n),E("variance",e,t,n),E("offset",e,t,n),E("scale",e,t,n),E("epsilon",e,t,n))];case"LRN":return[r.localResponseNormalization(E("x",e,t,n),E("radius",e,t,n),E("bias",e,t,n),E("alpha",e,t,n),E("beta",e,t,n))];case"Softmax":return[r.softmax(E("x",e,t,n))];case"LogSoftmax":return[r.logSoftmax(E("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"ragged":return a((()=>((e,t,n,r=x)=>{switch(e.op){case"RaggedGather":{const{outputNestedSplits:a,outputDenseValues:o}=r.raggedGather(E("paramsNestedSplits",e,t,n),E("paramsDenseValues",e,t,n),E("indices",e,t,n),E("outputRaggedRank",e,t,n));return a.concat(o)}case"RaggedRange":{const{rtNestedSplits:a,rtDenseValues:o}=r.raggedRange(E("starts",e,t,n),E("limits",e,t,n),E("splits",e,t,n));return[a,o]}case"RaggedTensorToTensor":return[r.raggedTensorToTensor(E("shape",e,t,n),E("values",e,t,n),E("defaultValue",e,t,n),E("rowPartitionTensors",e,t,n),E("rowPartitionTypes",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"reduction":return a((()=>((e,t,n,r=x)=>{switch(e.op){case"Max":{const a=E("axis",e,t,n),o=E("keepDims",e,t,n);return[r.max(E("x",e,t,n),a,o)]}case"Mean":{const a=E("axis",e,t,n),o=E("keepDims",e,t,n);return[r.mean(E("x",e,t,n),a,o)]}case"Min":{const a=E("axis",e,t,n),o=E("keepDims",e,t,n);return[r.min(E("x",e,t,n),a,o)]}case"Sum":{const a=E("axis",e,t,n),o=E("keepDims",e,t,n);return[r.sum(E("x",e,t,n),a,o)]}case"All":{const a=E("axis",e,t,n),o=E("keepDims",e,t,n);return[r.all(E("x",e,t,n),a,o)]}case"Any":{const a=E("axis",e,t,n),o=E("keepDims",e,t,n);return[r.any(E("x",e,t,n),a,o)]}case"ArgMax":{const a=E("axis",e,t,n);return[r.argMax(E("x",e,t,n),a)]}case"ArgMin":{const a=E("axis",e,t,n);return[r.argMin(E("x",e,t,n),a)]}case"Prod":{const a=E("axis",e,t,n),o=E("keepDims",e,t,n);return[r.prod(E("x",e,t,n),a,o)]}case"Cumprod":{const a=E("axis",e,t,n),o=E("exclusive",e,t,n),s=E("reverse",e,t,n);return[r.cumprod(E("x",e,t,n),a,o,s)]}case"Cumsum":{const a=E("axis",e,t,n),o=E("exclusive",e,t,n),s=E("reverse",e,t,n);return[r.cumsum(E("x",e,t,n),a,o,s)]}case"Bincount":const a=E("x",e,t,n),o=E("weights",e,t,n),s=E("size",e,t,n);return[r.bincount(a,o,s)];case"DenseBincount":{const a=E("x",e,t,n),o=E("weights",e,t,n),s=E("size",e,t,n),i=E("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=x)=>{switch(e.op){case"ConcatV2":case"Concat":{const a=E("n",e,t,n),o=E("axis",e,t,n);let s=E("tensors",e,t,n);return s=s.slice(0,a),[r.concat(s,o)]}case"Gather":{const a=E("x",e,t,n),o=E("indices",e,t,n);return[r.gather(a,r.cast(o,"int32"),0)]}case"GatherV2":{const a=E("axis",e,t,n),o=E("batchDims",e,t,n),s=E("x",e,t,n),i=E("indices",e,t,n);return[r.gather(s,r.cast(i,"int32"),a,o)]}case"Reverse":{const a=E("dims",e,t,n),o=[];for(let e=0;e<a.length;e++)a[e]&&o.push(e);const s=E("x",e,t,n);return[r.reverse(s,o)]}case"ReverseV2":{const a=E("axis",e,t,n),o=E("x",e,t,n);return[r.reverse(o,a)]}case"Slice":{const a=E("begin",e,t,n),o=E("size",e,t,n);return[r.slice(E("x",e,t,n),a,o)]}

2case"StridedSlice":{const a=E("begin",e,t,n),o=E("end",e,t,n),s=E("strides",e,t,n),i=E("beginMask",e,t,n),u=E("endMask",e,t,n),c=E("ellipsisMask",e,t,n),l=E("newAxisMask",e,t,n),p=E("shrinkAxisMask",e,t,n),d=E("x",e,t,n);return[r.stridedSlice(d,a,o,s,i,u,c,l,p)]}case"Pack":return(0,N.G6I)((()=>{const a=E("axis",e,t,n),o=E("tensors",e,t,n),s=o[0].shape,i=r.squeeze(o[0]).shape,u=o.map((e=>{const t=N.euu.arraysEqual(e.shape,s);if(!t&&!N.euu.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=E("axis",e,t,n),o=E("tensor",e,t,n);return r.unstack(o,a)}case"Tile":{const a=E("reps",e,t,n);return[r.tile(E("x",e,t,n),a)]}case"Split":case"SplitV":{const a=E("axis",e,t,n),o=E("numOrSizeSplits",e,t,n),s=E("x",e,t,n);return r.split(s,o,a)}case"ScatterNd":{const a=E("indices",e,t,n),o=E("values",e,t,n),s=E("shape",e,t,n);return[r.scatterND(a,o,s)]}case"GatherNd":{const a=E("x",e,t,n),o=E("indices",e,t,n);return[r.gatherND(a,o)]}case"SparseToDense":{const a=E("sparseIndices",e,t,n),o=E("outputShape",e,t,n),s=E("sparseValues",e,t,n),i=E("defaultValue",e,t,n);return[r.sparseToDense(a,s,o,s.dtype===i.dtype?i:r.cast(i,s.dtype))]}case"TensorScatterUpdate":{const a=E("indices",e,t,n),o=E("values",e,t,n),s=E("tensor",e,t,n);return[r.tensorScatterUpdate(s,a,o)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}})(e,t,n)));case"sparse":return a((()=>((e,t,n,r=x)=>{switch(e.op){case"SparseFillEmptyRows":{const{outputIndices:a,outputValues:o,emptyRowIndicator:s,reverseIndexMap:i}=r.sparse.sparseFillEmptyRows(E("indices",e,t,n),E("values",e,t,n),E("denseShape",e,t,n),E("defaultValue",e,t,n));return[a,o,s,i]}case"SparseReshape":{const{outputIndices:a,outputShape:o}=r.sparse.sparseReshape(E("inputIndices",e,t,n),E("inputShape",e,t,n),E("newShape",e,t,n));return[a,o]}case"SparseSegmentMean":return[r.sparse.sparseSegmentMean(E("data",e,t,n),E("indices",e,t,n),E("segmentIds",e,t,n))];case"SparseSegmentSum":return[r.sparse.sparseSegmentSum(E("data",e,t,n),E("indices",e,t,n),E("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=x)=>{switch(e.op){case"FFT":return[r.fft(E("x",e,t,n))];case"IFFT":return[r.ifft(E("x",e,t,n))];case"RFFT":return[r.rfft(E("x",e,t,n))];case"IRFFT":return[r.irfft(E("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=x)=>{switch(e.op){case"StaticRegexReplace":return[r.string.staticRegexReplace(E("input",e,t,n),E("pattern",e,t,n),E("rewrite",e,t,n),E("replaceGlobal",e,t,n))];case"StringNGrams":{const{nGrams:a,nGramsSplits:o}=r.string.stringNGrams(E("data",e,t,n),E("dataSplits",e,t,n),E("separator",e,t,n),E("nGramWidths",e,t,n),E("leftPad",e,t,n),E("rightPad",e,t,n),E("padWidth",e,t,n),E("preserveShortSequences",e,t,n));return[a,o]}case"StringSplit":{const{indices:a,values:o,shape:s}=r.string.stringSplit(E("input",e,t,n),E("delimiter",e,t,n),E("skipEmpty",e,t,n));return[a,o,s]}case"StringToHashBucketFast":return[r.string.stringToHashBucketFast(E("input",e,t,n),E("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=x)=>{switch(e.op){case"Cast":return[r.cast(E("x",e,t,n),E("dtype",e,t,n))];case"ExpandDims":{const a=E("axis",e,t,n);return[r.expandDims(E("x",e,t,n),a)]}case"Squeeze":{const a=E("axis",e,t,n);return[r.squeeze(E("x",e,t,n),a)]}case"Reshape":return[r.reshape(E("x",e,t,n),E("shape",e,t,n))];case"EnsureShape":return[r.ensureShape(E("x",e,t,n),E("shape",e,t,n))];case"MirrorPad":return[r.mirrorPad(E("x",e,t,n),E("padding",e,t,n),E("mode",e,t,n))];case"PadV2":case"Pad":return[r.pad(E("x",e,t,n),E("padding",e,t,n),E("constantValue",e,t,n))];case"SpaceToBatchND":{const a=E("blockShape",e,t,n),o=E("paddings",e,t,n);return[r.spaceToBatchND(E("x",e,t,n),a,o)]}case"BatchToSpaceND":{const a=E("blockShape",e,t,n),o=E("crops",e,t,n);return[r.batchToSpaceND(E("x",e,t,n),a,o)]}case"DepthToSpace":{const a=E("blockSize",e,t,n),o=E("dataFormat",e,t,n).toUpperCase();return[r.depthToSpace(E("x",e,t,n),a,o)]}case"BroadcastTo":return[r.broadcastTo(E("x",e,t,n),E("shape",e,t,n))];case"BroadcastArgs":return[r.broadcastArgs(E("s0",e,t,n),E("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=r.getHashTableHandleByName(e.name);if(null!=a)return[a];{const a=E("keyDType",e,t,n),o=E("valueDType",e,t,n),s=new Ee(a,o);return r.addHashTable(e.name,s),[s.handle]}}case"InitializeTable":case"InitializeTableV2":case"LookupTableImport":case"LookupTableImportV2":{const a=E("tableHandle",e,t,n,r),o=E("keys",e,t,n),s=E("values",e,t,n),i=r.getHashTableById(a.id);return[await i.import(o,s)]}case"LookupTableFind":case"LookupTableFindV2":{const a=E("tableHandle",e,t,n,r),o=E("keys",e,t,n),s=E("defaultValue",e,t,n),i=r.getHashTableById(a.id);return[await i.find(o,s)]}case"LookupTableSize":case"LookupTableSizeV2":{const a=E("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);

2case"custom":const o=T(e.op);if(o&&o.customExecutor)return o.customExecutor(new be(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 N.euu.isPromise(o)?o.then((e=>[].concat(e))):[].concat(o)}class Fe{constructor(e={},t={},n={},r={},a){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=r,this.parseNodeNameCache=a,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 De(e,t,n,r){const a=new Set,o=[];let s=null,i=null;const u=new Set,c=new Set(Object.keys(e).map((e=>C(e)[0])));r=r||[];const l=new Set(r.map((e=>C(e.name)[0]))),p=[...t];for(;p.length>0;){const e=p.pop();($e(e)||Le(e)||We(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]&&(c.has(e.name)||l.has(e.name)||(0!==e.inputs.length?e.inputs.forEach((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}}class Oe extends Error{constructor(e){super(`NodesExecutionOrderError: ${e}`)}}const Ce=new Set(["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"]),Pe=new Set(["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"]),Re=new Set(["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"]);function $e(e){return Ce.has(e.op)}function Le(e){return Pe.has(e.op)}function We(e){return Re.has(e.op)}class ze{get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){const t=Object.keys(e).map((t=>e[t].map((e=>e.id))));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map((e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0})))}get outputs(){return this._outputs.map((e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0})))}get inputNodes(){return this._inputs.map((e=>e.signatureKey||e.name))}get outputNodes(){return this._outputs.map((e=>{const t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t}))}get functions(){return Object.keys(this._functions).reduce(((e,t)=>(e[t]=this._functions[t].signature,e)),{})}constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,null!=e.functions&&Object.keys(e.functions).forEach((t=>{this._functionExecutorMap[t]=new ze(e.functions[t],this)}))}getCompilationKey(e,t){const n=e.map((e=>e.name)).sort(),r=t.map((e=>e.name)).sort();return n.join(this.SEPARATOR)+"--"+r.join(this.SEPARATOR)}compile(e,t){const n=De(e,t,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:a,syncInputs:o}=n;if(null!=a)throw new Error(`This execution contains the node '${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}]`)}const s=function(e,t){const{usedNodes:n,inputs:r}=t,a=Object.keys(r).map((e=>C(e)[0])).map((t=>e.nodes[t])),o=e.initNodes||[],s=e=>n.has("string"==typeof e?e:e.name);function i(e){return[...new Map(e.map((e=>[e.name,e]))).values()]}const u=i([...a,...e.weights,...o]).filter(s),c=i([...u,...Object.values(e.nodes)]).filter(s),l=new Map(c.map((e=>[e.name,e]))),p={};for(const e of c){p[e.name]=p[e.name]||0;for(const t of e.children)s(t)||(p[t.name]=Number.POSITIVE_INFINITY),p[t.name]=(p[t.name]||0)+1}const d=Object.entries(p).filter((([,e])=>0===e)).map((([e])=>e)),h=[...d];for(;d.length>0;){const e=d.pop(),t=l.get(e);for(const e of t.children.filter(s))0==--p[e.name]&&(h.push(e.name),d.push(e.name))}const f=function(e,t){const n=new Map(e.map((e=>[e.name,e]))),r=t.map((e=>e.name)),a=new Set(r);for(;r.length>0;){const e=r.pop(),t=n.get(e);for(const e of t.children)n.has(e.name)&&!a.has(e.name)&&(a.add(e.name),r.push(e.name))}return e.filter((e=>a.has(e.name)))}(h.map((e=>l.get(e))),u);return function(e,t){const n=new Map(e.map(((e,t)=>[e.name,t]))),r=new Set(t.map((e=>e.name))),a=e=>r.has("string"==typeof e?e:e.name),o=new Set(e.map((e=>e.name))),s=e=>o.has("string"==typeof e?e:e.name);for(const t of e){for(const e of t.children.filter(s)){if(!n.has(e.name))throw new Oe(`Child ${e.name} of node ${t.name} is unreachable.`);if(n.get(t.name)>n.get(e.name))throw new Oe(`Node ${t.name} is scheduled to run after its child ${e.name}.`)}if(!a(t))for(const e of t.inputs){if(!n.has(e.name))throw new Oe(`Input ${e.name} of node ${t.name} is unreachable.`);if(n.get(e.name)>n.get(t.name))throw new Oe(`Node ${t.name} is scheduled to run before its input ${e.name}.`)}}}(f,u),f}(this.graph,n),i=function(e){const t=new Map(e.map(((e,t)=>[e.name,t]))),n=Number.MAX_SAFE_INTEGER,r=e.map(((e,t)=>$e(e)?n:t)),a=e=>{const n=r[t.get(e.name)];return null==n?-1:n},o=e.map(((e,t)=>e.children.map(a).reduce(((e,t)=>Math.max(e,t)),r[t]))),s=new Map;for(let t=0;t<e.length;++t){const r=o[t];if(r===n)continue;const a=e[t],i=e[r];s.has(i.name)||s.set(i.name,[]),s.get(i.name).push(a)}return s}(s);return{orderedNodes:s,nodeLiveUntilMap:i}}cloneAndKeepTensor(e){if(null==e)return null;const t=e.clone();return(0,N.Oi1)(t),t}cloneTensorList(e){return e?e.map((e=>this.cloneAndKeepTensor(e))):null}cloneTensorMap(e){return Object.fromEntries(Object.entries(e).map((([e,t])=>[e,this.cloneTensorList(t)])))}execute(e,t){this.disposeIntermediateTensors(),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[C(e)[0]])),a=t.map((e=>C(e)[0])),o=new Set(a);let s=a.map((e=>this.graph.nodes[e]));0===s.length&&(s=this._outputs);const i=this.getCompilationKey(r,s);let u=this.compiledMap.get(i);null==u&&(u=this.compile(e,s),this.compiledMap.set(i,u));try{this.keepIntermediateTensors=(0,N._K2)().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){this.keepIntermediateTensors=!1,console.warn(e.message)}const c={},l={};return(0,N.G6I)((()=>{const n=new Fe(this.weightMap,c,l,this.functionExecutorMap,this.parseNodeNameCache),r=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(e).forEach((t=>{const[a,o]=C(t,n),s=[];s[o]=e[t],r[a]=s,this.keepIntermediateTensors&&(this.clonedTensorsMap[a]=this.cloneTensorList(s))}));const a=this.getFrozenTensorIds(r),{orderedNodes:s,nodeLiveUntilMap:i}=u;for(const e of s){if(r[e.name])continue;const t=Ae(e,r,n,this._resourceManager);if(N.euu.isPromise(t))throw new Error(`The execution of the op '${e.op}' returned a promise. Please use model.executeAsync() instead.`);r[e.name]=t,this.keepIntermediateTensors&&(this.clonedTensorsMap[e.name]=this.cloneTensorList(t)),this.checkTensorForDisposalWithNodeLiveUntilInfo(e,r,n,a,o,i.get(e.name))}return null==this.parent&&n.dispose(a),t.map((e=>A(e,r,n)))}

2))}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){if(!$e(t)&&!o.has(e)){for(const r of n[e])null!=r&&(s[r.id]=(s[r.id]||0)+t.children.length);for(const e of t.inputs){if($e(e))continue;const t=F(e.name,n,r);if(null!=t)for(const e of t){if(!e||e.kept||a.has(e.id))continue;const t=s[e.id];1===t?(e.dispose(),delete s[e.id]):null!=t&&s[e.id]--}}}}checkTensorForDisposalWithNodeLiveUntilInfo(e,t,n,r,a,o){function s(e){return $e(e)||a.has(e.name)}if(!$e(e)&&null!=o)for(const e of o){if(s(e))continue;const a=F(e.name,t,n);for(const e of a)!e||e.kept||r.has(e.id)||e.dispose()}}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){this.clonedTensorsMap&&(Object.values(this.clonedTensorsMap).forEach((e=>{for(const t of e)t&&!t.isDisposed&&t.dispose()})),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(e,t,n=!1,r={},a={}){this.disposeIntermediateTensors(),n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepIntermediateTensors=(0,N._K2)().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){this.keepIntermediateTensors=!1,console.warn(e.message)}const o=new Fe(this.weightMap,r,a,this.functionExecutorMap,this.parseNodeNameCache);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));const s=await this.executeWithControlFlow(e,o,t,n),i=t.map((e=>A(e,s,o))),u=i.map((e=>e.id)),c=Object.keys(e).map((t=>e[t].id)),l=new Set([...u,...c,...this.weightIds]);return Object.values(s).forEach((e=>{e.forEach((e=>{!e||e.isDisposed||l.has(e.id)||e.dispose()}))})),null==this.parent&&o.dispose(l),i}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[C(e)[0]])),s=n.map((e=>C(e)[0])),i=new Set(s);let u=s.map((e=>this.graph.nodes[e]));0===u.length&&(u=this._outputs);const{usedNodes:c,missingInputs:l,dynamicNode:p,syncInputs:d}=De(e,u,this.weightMap,this._initNodes),h=[...o,...this.graph.weights,...this._initNodes||[]].map((e=>({node:e,contexts:t.currentContext}))),f=Object.assign({},this.weightMap);Object.keys(e).forEach((t=>{const[n,r]=C(t),a=[];a[r]=e[t],f[n]=a}));const m={},g=this.getFrozenTensorIds(f),y={};for(;h.length>0;){const e=this.processStack(o,h,t,f,y,g,i,m,c);await Promise.all(e)}null!=p||r||console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");const b=u.filter((e=>!$e(e)&&!A(e.name,f,t))).map((e=>e.name));if(b.length>0){let e="";throw null!=p&&(e=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${d}]`),new Error(`Cannot compute the outputs [${b}] from the provided inputs [${a}]. Consider providing the following inputs: [${l}]. ${e}`)}return f}processStack(e,t,n,r,a,o,s,i,u){const c=[];for(;t.length>0;){const e=t.pop();n.currentContext=e.contexts;let l="";if("Enter"===e.node.op&&E("isConstant",e.node,r,n)&&([l]=D(e.node.name,n)),null==r[e.node.name]){const p=Ae(e.node,r,n,this._resourceManager);l||([l]=D(e.node.name,n));const d=n.currentContext;N.euu.isPromise(p)?c.push(p.then((c=>(r[l]=c,this.keepIntermediateTensors&&(this.clonedTensorsMap[l]=this.cloneTensorList(c)),n.currentContext=d,this.checkTensorForDisposal(l,e.node,r,n,o,s,i),this.processChildNodes(e.node,t,n,r,a,u),c)))):(r[l]=p,this.keepIntermediateTensors&&(this.clonedTensorsMap[l]=this.cloneTensorList(p)),this.checkTensorForDisposal(l,e.node,r,n,o,s,i),this.processChildNodes(e.node,t,n,r,a,u))}else this.processChildNodes(e.node,t,n,r,a,u)}return c}processChildNodes(e,t,n,r,a,o){e.children.forEach((e=>{const[s]=D(e.name,n);!a[s]&&o.has(e.name)&&("Merge"===e.op?e.inputNames.some((e=>!!A(e,r,n)))&&(a[s]=!0,t.push({contexts:n.currentContext,node:e})):e.inputNames.every((e=>!!A(e,r,n)))&&(a[s]=!0,t.push({contexts:n.currentContext,node:e})))}))}dispose(){Object.keys(this.weightMap).forEach((e=>this.weightMap[e].forEach((e=>e.dispose()))))}checkInputShapeAndType(e){Object.keys(e).forEach((t=>{const n=e[t],[r]=C(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){const e=a.attrParams.shape.value,t=e.length===n.shape.length&&n.shape.every(((t,n)=>-1===e[n]||e[n]===t));N.euu.assert(t,(()=>`The shape of dict['${a.name}'] provided in model.execute(dict) must be [${e}], but was [${n.shape}]`))}a.attrParams.dtype&&a.attrParams.dtype.value&&N.euu.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 ${n.dtype}`))}))}mapInputs(e){var t,n;const r={};for(const a in e){const o=null===(n=null===(t=this._signature)||void 0===t?void 0:t.inputs)||void 0===n?void 0:n[a];null!=o?r[o.name]=e[a]:r[a]=e[a]}return r}checkInputs(e){const t=Object.keys(e).filter((e=>{const[t]=C(e);return null==this.graph.nodes[t]}));if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map((e=>{var t,n;const r=null===(n=null===(t=this._signature)||void 0===t?void 0:t.outputs)||void 0===n?void 0:n[e];return null!=r?r.name:e}),{})}checkOutputs(e){e.forEach((e=>{const[t]=C(e);if(!this.graph.nodes[t])throw new Error(`The output '${e}' is not found in the graph`)}))}}class Be{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(const e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(const e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}}const Ue="?tfjs-format=file",He="model.json";class Ve{get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}constructor(e,t={},n=N.io){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=n,null==t&&(this.loadOptions={}),this.resourceManager=new Be}findIOHandler(){const e=this.modelUrl;if(null!=e.load)this.handler=e;else if(null!=this.loadOptions.requestInit)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{const t=this.io.getLoadHandlers(e,this.loadOptions);if(0===t.length)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),null==this.handler.load)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");const e=this.handler.load();return N.euu.isPromise(e)?e.then((e=>this.loadSync(e))):this.loadSync(e)}loadSync(e){this.artifacts=e;const t=this.artifacts.modelTopology;let n=this.artifacts.signature;if(null!=this.artifacts.userDefinedMetadata){const e=this.artifacts.userDefinedMetadata;null!=e.signature&&(n=e.signature),null!=e.structuredOutputKeys&&(this.structuredOutputKeys=e.structuredOutputKeys)}this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;const r=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new ze(re.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,null!=e.modelInitializer&&null!=e.modelInitializer.node){const t=re.Instance.transformGraph(e.modelInitializer);this.initializer=new ze(t),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if("string"==typeof e){const t=this.io.getSaveHandlers(e);if(0===t.length)throw new Error(`Cannot find any save handlers for URL '${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)}addStructuredOutputNames(e){if(this.structuredOutputKeys){const t=e instanceof N.w3A?[e]:e,n={};return t.forEach(((e,t)=>n[this.structuredOutputKeys[t]]=e)),n}return e}predict(e,t){const n=this.execute(e,this.outputNodes);return this.addStructuredOutputNames(n)}async predictAsync(e,t){const n=await this.executeAsync(e,this.outputNodes);return this.addStructuredOutputNames(n)}normalizeInputs(e){var t;if(!(e instanceof N.w3A||Array.isArray(e))){const n=null===(t=this.signature)||void 0===t?void 0:t.inputs;if(null!=n)for(const t in n){const r=n[t];null!=r.resourceId&&(e[t]=this.resourceIdToCapturedInput[r.resourceId])}return e}e=Array.isArray(e)?e:[e];const n=Object.keys(this.resourceIdToCapturedInput).length;if(e.length+n!==this.inputNodes.length)throw new Error(`Input tensor count mismatch, the graph model has ${this.inputNodes.length-n} non-resource placeholders, while there are ${e.length} input tensors provided.`);let r=0;return this.inputNodes.reduce(((t,n)=>{var a,o,s;const i=null===(s=null===(o=null===(a=this.signature)||void 0===a?void 0:a.inputs)||void 0===o?void 0:o[n])||void 0===s?void 0:s.resourceId;return t[n]=null!=i?this.resourceIdToCapturedInput[i]:e[r++],t}),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}executeInitializerGraph(){return null==this.initializer?[]:null==this.initializerSignature?this.initializer.execute({},[]):this.initializer.execute({},Object.keys(this.initializerSignature.outputs))}async executeInitializerGraphAsync(){return null==this.initializer?[]:null==this.initializerSignature?this.initializer.executeAsync({},[]):this.initializer.executeAsync({},Object.keys(this.initializerSignature.outputs))}setResourceIdToCapturedInput(e){if(this.resourceIdToCapturedInput={},this.initializerSignature){const t=this.initializerSignature.outputs,n=Object.keys(t);for(let r=0;r<n.length;r++){const a=t[n[r]];this.resourceIdToCapturedInput[a.resourceId]=e[r]}}}execute(e,t){null==this.resourceIdToCapturedInput&&this.setResourceIdToCapturedInput(this.executeInitializerGraph()),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){null==this.resourceIdToCapturedInput&&this.setResourceIdToCapturedInput(await this.executeInitializerGraphAsync()),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.resourceIdToCapturedInput&&(0,N.Mtx)(this.resourceIdToCapturedInput)),this.resourceManager.dispose()}}async function Ge(e,t={},n=N.io){if(null==e)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");null==t&&(t={}),t.fromTFHub&&"string"==typeof e&&(e=function(e){return e.endsWith("/")||(e+="/"),`${e}${He}${Ue}`}(e));const r=new Ve(e,t,n);return await r.load(),r}var qe=function(){return qe=Object.assign||function(e){for(var t,n=1,r=arguments.length;n<r;n++)for(var a in t=arguments[n])Object.prototype.hasOwnProperty.call(t,a)&&(e[a]=t[a]);return e},qe.apply(this,arguments)};

2function je(e,t,n,r){return new(n||(n=Promise))((function(t,a){function o(e){try{i(r.next(e))}catch(e){a(e)}}function s(e){try{i(r.throw(e))}catch(e){a(e)}}function i(e){var r;e.done?t(e.value):(r=e.value,r instanceof n?r:new n((function(e){e(r)}))).then(o,s)}i((r=r.apply(e,[])).next())}))}function Ke(e,t){var n,r,a,o,s={label:0,sent:function(){if(1&a[0])throw a[1];return a[1]},trys:[],ops:[]};return o={next:i(0),throw:i(1),return:i(2)},"function"==typeof Symbol&&(o[Symbol.iterator]=function(){return this}),o;function i(o){return function(i){return function(o){if(n)throw new TypeError("Generator is already executing.");for(;s;)try{if(n=1,r&&(a=2&o[0]?r.return:o[0]?r.throw||((a=r.return)&&a.call(r),0):r.next)&&!(a=a.call(r,o[1])).done)return a;switch(r=0,a&&(o=[2&o[0],a.value]),o[0]){case 0:case 1:a=o;break;case 4:return s.label++,{value:o[1],done:!1};case 5:s.label++,r=o[1],o=[0];continue;case 7:o=s.ops.pop(),s.trys.pop();continue;default:if(!((a=(a=s.trys).length>0&&a[a.length-1])||6!==o[0]&&2!==o[0])){s=0;continue}if(3===o[0]&&(!a||o[1]>a[0]&&o[1]<a[3])){s.label=o[1];break}if(6===o[0]&&s.label<a[1]){s.label=a[1],a=o;break}if(a&&s.label<a[2]){s.label=a[2],s.ops.push(o);break}a[2]&&s.ops.pop(),s.trys.pop();continue}o=t.call(e,s)}catch(e){o=[6,e],r=0}finally{n=a=0}if(5&o[0])throw o[1];return{value:o[0]?o[1]:void 0,done:!0}}([o,i])}}}var Qe=["rightEye","leftEye","noseTip","mouthCenter","rightEarTragion","leftEarTragion"],Ye={modelType:"short",runtime:"mediapipe",maxFaces:1},Je=function(){function e(e){var t=this;this.width=0,this.height=0,this.selfieMode=!1,this.faceDetectorSolution=new S.c({locateFile:function(t,n){if(e.solutionPath){var r=e.solutionPath.replace(/\/+$/,"");return"".concat(r,"/").concat(t)}return"".concat(n,"/").concat(t)}}),this.faceDetectorSolution.setOptions({selfieMode:this.selfieMode,model:e.modelType}),this.faceDetectorSolution.onResults((function(e){if(t.height=e.image.height,t.width=e.image.width,t.faces=[],null!==e.detections)for(var n=0,r=e.detections;n<r.length;n++){var a=r[n];t.faces.push(t.normalizedToAbsolute(a.landmarks,{xMin:s=(o=a.boundingBox).xCenter-o.width/2,xMax:s+o.width,yMin:i=o.yCenter-o.height/2,yMax:i+o.height,width:o.width,height:o.height}))}var o,s,i}))}return e.prototype.normalizedToAbsolute=function(e,t){var n=this;return{keypoints:e.map((function(e,t){return{x:e.x*n.width,y:e.y*n.height,name:Qe[t]}})),box:{xMin:t.xMin*this.width,yMin:t.yMin*this.height,xMax:t.xMax*this.width,yMax:t.yMax*this.height,width:t.width*this.width,height:t.height*this.height}}},e.prototype.estimateFaces=function(e,t){return je(this,0,void 0,(function(){var n,r;return Ke(this,(function(a){switch(a.label){case 0:return t&&t.flipHorizontal&&t.flipHorizontal!==this.selfieMode&&(this.selfieMode=t.flipHorizontal,this.faceDetectorSolution.setOptions({selfieMode:this.selfieMode})),e instanceof N.w3A?(r=ImageData.bind,[4,N.aW8.toPixels(e)]):[3,2];case 1:return n=new(r.apply(ImageData,[void 0,a.sent(),e.shape[1],e.shape[0]])),[3,3];case 2:n=e,a.label=3;case 3:return e=n,[4,this.faceDetectorSolution.send({image:e})];case 4:return a.sent(),[2,this.faces]}}))}))},e.prototype.dispose=function(){this.faceDetectorSolution.close()},e.prototype.reset=function(){this.faceDetectorSolution.reset(),this.width=0,this.height=0,this.faces=null,this.selfieMode=!1},e.prototype.initialize=function(){return this.faceDetectorSolution.initialize()},e}();function Ze(e){return je(this,0,void 0,(function(){var t,n;return Ke(this,(function(r){switch(r.label){case 0:return t=function(e){if(null==e)return qe({},Ye);var t=qe({},e);return t.runtime="mediapipe",null==t.modelType&&(t.modelType=Ye.modelType),null==t.maxFaces&&(t.maxFaces=Ye.maxFaces),t}(e),[4,(n=new Je(t)).initialize()];case 1:return r.sent(),[2,n]}}))}))}function Xe(e){return e instanceof N.w3A?{height:e.shape[0],width:e.shape[1]}:{height:e.height,width:e.width}}function et(e){return e instanceof N.w3A?e:N.aW8.fromPixels(e)}function tt(e,t){N.euu.assert(0!==e.width,(function(){return"".concat(t," width cannot be 0.")})),N.euu.assert(0!==e.height,(function(){return"".concat(t," height cannot be 0.")}))}function nt(e){null==e.reduceBoxesInLowestLayer&&(e.reduceBoxesInLowestLayer=!1),null==e.interpolatedScaleAspectRatio&&(e.interpolatedScaleAspectRatio=1),null==e.fixedAnchorSize&&(e.fixedAnchorSize=!1);for(var t=[],n=0;n<e.numLayers;){for(var r=[],a=[],o=[],s=[],i=n;i<e.strides.length&&e.strides[i]===e.strides[n];){var u=rt(e.minScale,e.maxScale,i,e.strides.length);if(0===i&&e.reduceBoxesInLowestLayer)o.push(1),o.push(2),o.push(.5),s.push(.1),s.push(u),s.push(u);else{for(var c=0;c<e.aspectRatios.length;++c)o.push(e.aspectRatios[c]),s.push(u);if(e.interpolatedScaleAspectRatio>0){var l=i===e.strides.length-1?1:rt(e.minScale,e.maxScale,i+1,e.strides.length);s.push(Math.sqrt(u*l)),o.push(e.interpolatedScaleAspectRatio)}}i++}for(var p=0;p<o.length;++p){var d=Math.sqrt(o[p]);r.push(s[p]/d),a.push(s[p]*d)}var h=0,f=0;if(e.featureMapHeight.length>0)h=e.featureMapHeight[n],f=e.featureMapWidth[n];else{var m=e.strides[n];h=Math.ceil(e.inputSizeHeight/m),f=Math.ceil(e.inputSizeWidth/m)}for(var g=0;g<h;++g)for(var y=0;y<f;++y)for(var b=0;b<r.length;++b){var w={xCenter:(y+e.anchorOffsetX)/f,yCenter:(g+e.anchorOffsetY)/h,width:0,height:0};e.fixedAnchorSize?(w.width=1,w.height=1):(w.width=a[b],w.height=r[b]),t.push(w)}n=i}return t}function rt(e,t,n,r){return 1===r?.5*(e+t):e+(t-e)*n/(r-1)}function at(e,t){var n=t[0],r=t[1];return[n*e[0]+r*e[1]+e[3],n*e[4]+r*e[5]+e[7]]}function ot(e,t,n,r){return je(this,0,void 0,(function(){var r,a,o,s,i;return Ke(this,(function(u){switch(u.label){case 0:return e.sort((function(e,t){return Math.max.apply(Math,t.score)-Math.max.apply(Math,e.score)})),r=(0,N.Enf)(e.map((function(e){return[e.locationData.relativeBoundingBox.yMin,e.locationData.relativeBoundingBox.xMin,e.locationData.relativeBoundingBox.yMax,e.locationData.relativeBoundingBox.xMax]}))),a=(0,N.SC3)(e.map((function(e){return e.score[0]}

2))),[4,N.c$0.nonMaxSuppressionAsync(r,a,t,n)];case 1:return[4,(o=u.sent()).array()];case 2:return s=u.sent(),i=e.filter((function(e,t){return s.indexOf(t)>-1})),(0,N.Mtx)([r,a,o]),[2,i]}}))}))}function st(e,t,n){return je(this,0,void 0,(function(){var r,a,o,s,i;return Ke(this,(function(u){switch(u.label){case 0:return r=e[0],a=e[1],o=function(e,t,n){return(0,N.G6I)((function(){var r,a,o,s;n.reverseOutputOrder?(a=(0,N.sLr)((0,N.SME)(e,[0,n.boxCoordOffset+0],[-1,1])),r=(0,N.sLr)((0,N.SME)(e,[0,n.boxCoordOffset+1],[-1,1])),s=(0,N.sLr)((0,N.SME)(e,[0,n.boxCoordOffset+2],[-1,1])),o=(0,N.sLr)((0,N.SME)(e,[0,n.boxCoordOffset+3],[-1,1]))):(r=(0,N.sLr)((0,N.SME)(e,[0,n.boxCoordOffset+0],[-1,1])),a=(0,N.sLr)((0,N.SME)(e,[0,n.boxCoordOffset+1],[-1,1])),o=(0,N.sLr)((0,N.SME)(e,[0,n.boxCoordOffset+2],[-1,1])),s=(0,N.sLr)((0,N.SME)(e,[0,n.boxCoordOffset+3],[-1,1]))),a=(0,N.WQq)((0,N.E7T)((0,N.MbH)(a,n.xScale),t.w),t.x),r=(0,N.WQq)((0,N.E7T)((0,N.MbH)(r,n.yScale),t.h),t.y),n.applyExponentialOnBoxSize?(o=(0,N.E7T)((0,N.oNF)((0,N.MbH)(o,n.hScale)),t.h),s=(0,N.E7T)((0,N.oNF)((0,N.MbH)(s,n.wScale)),t.w)):(o=(0,N.E7T)((0,N.MbH)(o,n.hScale),t.h),s=(0,N.E7T)((0,N.MbH)(s,n.wScale),t.h));var i=(0,N.AT$)(r,(0,N.MbH)(o,2)),u=(0,N.AT$)(a,(0,N.MbH)(s,2)),c=(0,N.WQq)(r,(0,N.MbH)(o,2)),l=(0,N.WQq)(a,(0,N.MbH)(s,2)),p=(0,N.WUr)([(0,N.OoG)(i,[n.numBoxes,1]),(0,N.OoG)(u,[

2n.numBoxes,1]),(0,N.OoG)(c,[n.numBoxes,1]),(0,N.OoG)(l,[n.numBoxes,1])],1);if(n.numKeypoints)for(var d=0;d<n.numKeypoints;++d){var h=n.keypointCoordOffset+d*n.numValuesPerKeypoint,f=void 0,m=void 0;n.reverseOutputOrder?(f=(0,N.sLr)((0,N.SME)(e,[0,h],[-1,1])),m=(0,N.sLr)((0,N.SME)(e,[0,h+1],[-1,1]))):(m=(0,N.sLr)((0,N.SME)(e,[0,h],[-1,1])),f=(0,N.sLr)((0,N.SME)(e,[0,h+1],[-1,1])));var g=(0,N.WQq)((0,N.E7T)((0,N.MbH)(f,n.xScale),t.w),t.x),y=(0,N.WQq)((0,N.E7T)((0,N.MbH)(m,n.yScale),t.h),t.y);p=(0,N.WUr)([p,(0,N.OoG)(g,[n.numBoxes,1]),(0,N.OoG)(y,[n.numBoxes,1])],1)}return p}))}(a,t,n),s=(0,N.G6I)((function(){var e=r;return n.sigmoidScore?(null!=n.scoreClippingThresh&&(e=(0,N.Qjg)(r,-n.scoreClippingThresh,n.scoreClippingThresh)),e=(0,N._CL)(e)):e})),[4,it(o,s,n)];case 1:return i=u.sent(),(0,N.Mtx)([o,s]),[2,i]}}))}))}function it(e,t,n){return je(this,0,void 0,(function(){var r,a,o,s,i,u,c,l,p,d,h,f;return Ke(this,(function(m){switch(m.label){case 0:return r=[],[4,e.data()];case 1:return a=m.sent(),[4,t.data()];case 2:for(o=m.sent(),s=0;s<n.numBoxes;++s)if(!(null!=n.minScoreThresh&&o[s]<n.minScoreThresh||(i=s*n.numCoords,u=ut(a[i+0],a[i+1],a[i+2],a[i+3],o[s],n.flipVertically,s),(c=u.locationData.relativeBoundingBox).width<0||c.height<0))){if(n.numKeypoints>0)for((l=u.locationData).relativeKeypoints=[],p=n.numKeypoints*n.numValuesPerKeypoint,d=0;d<p;d+=n.numValuesPerKeypoint)h=i+n.keypointCoordOffset+d,f={x:a[h+0],y:n.flipVertically?1-a[h+1]:a[h+1]},l.relativeKeypoints.push(f);r.push(u)}return[2,r]}}))}))}function ut(e,t,n,r,a,o,s){return{score:[a],ind:s,locationData:{relativeBoundingBox:{xMin:t,yMin:o?1-n:e,xMax:r,yMax:o?1-e:n,width:r-t,height:n-e}}}}var ct,lt={reduceBoxesInLowestLayer:!1,interpolatedScaleAspectRatio:1,featureMapHeight:[],featureMapWidth:[],numLayers:4,minScale:.1484375,maxScale:.75,inputSizeHeight:128,inputSizeWidth:128,anchorOffsetX:.5,anchorOffsetY:.5,strides:[8,16,16,16],aspectRatios:[1],fixedAnchorSize:!0},pt={reduceBoxesInLowestLayer:!1,interpolatedScaleAspectRatio:0,featureMapHeight:[],featureMapWidth:[],numLayers:1,minScale:.1484375,maxScale:.75,inputSizeHeight:192,inputSizeWidth:192,anchorOffsetX:.5,anchorOffsetY:.5,strides:[4],aspectRatios:[1],fixedAnchorSize:!0},dt={runtime:"tfjs",modelType:"short",maxFaces:1,detectorModelUrl:"https://tfhub.dev/mediapipe/tfjs-model/face_detection/short/1"},ht={applyExponentialOnBoxSize:!1,flipVertically:!1,ignoreClasses:[],numClasses:1,numBoxes:896,numCoords:16,boxCoordOffset:0,keypointCoordOffset:4,numKeypoints:6,numValuesPerKeypoint:2,sigmoidScore:!0,scoreClippingThresh:100,reverseOutputOrder:!0,xScale:128,yScale:128,hScale:128,wScale:128,minScoreThresh:.5},ft={applyExponentialOnBoxSize:!1,flipVertically:!1,ignoreClasses:[],numClasses:1,numBoxes:2304,numCoords:16,boxCoordOffset:0,keypointCoordOffset:4,numKeypoints:6,numValuesPerKeypoint:2,sigmoidScore:!0,scoreClippingThresh:100,reverseOutputOrder:!0,xScale:192,yScale:192,hScale:192,wScale:192,minScoreThresh:.6},mt={outputTensorSize:{width:128,height:128},keepAspectRatio:!0,outputTensorFloatRange:[-1,1],borderMode:"zero"},gt={outputTensorSize:{width:192,height:192},keepAspectRatio:!0,outputTensorFloatRange:[-1,1],borderMode:"zero"},yt=function(){function e(e,t,n){this.detectorModel=t,this.maxFaces=n,"full"===e?(this.imageToTensorConfig=gt,this.tensorsToDetectionConfig=ft,this.anchors=nt(pt)):(this.imageToTensorConfig=mt,this.tensorsToDetectionConfig=ht,this.anchors=nt(lt));var r=(0,N.SC3)(this.anchors.map((function(e){return e.width}))),a=(0,N.SC3)(this.anchors.map((function(e){return e.height}))),o=(0,N.SC3)(this.anchors.map((function(e){return e.xCenter}))),s=(0,N.SC3)(this.anchors.map((function(e){return e.yCenter})));this.anchorTensor={x:o,y:s,w:r,h:a}}return e.prototype.dispose=function(){this.detectorModel.dispose(),(0,N.Mtx)([this.anchorTensor.x,this.anchorTensor.y,this.anchorTensor.

2w,this.anchorTensor.h])},e.prototype.reset=function(){},e.prototype.detectFaces=function(e,t){return void 0===t&&(t=!1),je(this,0,void 0,(function(){var n,r,a,o,s,i,u,c,l,p,d;return Ke(this,(function(h){switch(h.label){case 0:return null==e?(this.reset(),[2,[]]):(n=(0,N.G6I)((function(){var n=(0,N.WM5)(et(e),"float32");return t&&(n=(0,N.sLr)(N.c$0.flipLeftRight((0,N.aW5)(n,0)),[0])),n})),r=function(e,t,n){var r=t.outputTensorSize,a=t.keepAspectRatio,o=t.borderMode,s=t.outputTensorFloatRange,i=Xe(e),u=function(e,t){return{xCenter:.5*e.width,yCenter:.5*e.height,width:e.width,height:e.height,rotation:0}}(i),c=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;tt(t,"targetSize"),tt(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}}(u,r,a),l=function(e,t,n,r){var a=e.width,o=e.height,s=Math.cos(e.rotation),i=Math.sin(e.rotation),u=e.xCenter,c=e.yCenter,l=1/t,p=1/n,d=new Array(16);return d[0]=a*s*1*l,d[1]=-o*i*l,d[2]=0,d[3]=(-.5*a*s*1+.5*o*i+u)*l,d[4]=a*i*1*p,d[5]=o*s*p,d[6]=0,d[7]=(-.5*o*s-.5*a*i*1+c)*p,d[8]=0,d[9]=0,d[10]=a*l,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 ".concat(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)}(u,i.width,i.height),p=(0,N.G6I)((function(){var t=et(e),n=(0,N.Enf)(function(e,t,n){return tt(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]}(l,i,r),[1,8]),a="zero"===o?"constant":"nearest",u=N.c$0.transform((0,N.aW5)((0,N.WM5)(t,"float32")),n,"bilinear",a,0,[r.height,r.width]);return null!=s?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(0,N.G6I)((function(){return(0,N.WQq)((0,N.E7T)(e,n.scale),n.offset)}))}(u,s):u}));return{imageTensor:p,padding:c,transformationMatrix:l}}(n,this.imageToTensorConfig),a=r.imageTensor,o=r.transformationMatrix,s=this.detectorModel.execute(a,"Identity:0"),i=function(e){return(0,N.G6I)((function(){var t=function(e){return(0,N.G6I)((function(){return[(0,N.SME)(e,[0,0,0],[1,-1,1]),(0,N.SME)(e,[0,0,1],[1,-1,-1])]}))}(e),n=t[0],r=t[1];return{boxes:(0,N.sLr)(r),logits:(0,N.sLr)(n)}}))}(s),u=i.boxes,[4,st([c=i.logits,u],this.anchorTensor,this.tensorsToDetectionConfig)]);case 1:return 0===(l=h.sent()).length?((0,N.Mtx)([n,a,s,c,u]),[2,l]):[4,ot(l,this.maxFaces,.3)];case 2:return p=h.sent(),d=function(e,t){void 0===e&&(e=[]);var n,r=(n=t,[].concat.apply([],n));return e.forEach((function(e){var t=e.locationData;t.relativeKeypoints.forEach((function(e){var t=at(r,[e.x,e.y]),n=t[0],a=t[1];e.x=n,e.y=a}));var n=t.relativeBoundingBox,a=Number.MAX_VALUE,o=Number.MAX_VALUE,s=Number.MIN_VALUE,i=Number.MIN_VALUE;[[n.xMin,n.yMin],[n.xMin+n.width,n.yMin],[n.xMin+n.width,n.yMin+n.height],[n.xMin,n.yMin+n.height]].forEach((function(e){var t=at(r,e),n=t[0],u=t[1];a=Math.min(a,n),s=Math.max(s,n),o=Math.min(o,u),i=Math.max(i,u)})),t.relativeBoundingBox={xMin:a,xMax:s,yMin:o,yMax:i,width:s-a,height:i-o}})),e}(p,o),(0,N.Mtx)([n,a,s,c,u]),[2,d]}}))}))},e.prototype.estimateFaces=function(e,t){return je(this,0,void 0,(function(){var n,r;return Ke(this,(function(a){return n=Xe(e),r=!!t&&t.flipHorizontal,[2,this.detectFaces(e,r).then((function(e){return e.map((function(e){for(var t=e.locationData.relativeKeypoints.map((function(e,t){return qe(qe({},e),{x:e.x*n.width,y:e.y*n.height,name:Qe[t]})})),r=e.locationData.relativeBoundingBox,a=0,o=["width","xMax","xMin"];a<o.length;a++)r[o[a]]*=n.width;for(var s=0,i=["height","yMax","yMin"];s<i.length;s++)r[i[s]]*=n.height;return{keypoints:t,box:r}}))}))]}))}))},e}();function bt(e){return je(this,0,void 0,(function(){var t,n,r;return Ke(this,(function(a){switch(a.label){case 0:return t=function(e){if(null==e)return qe({},dt);var t=qe({},e);return null==t.modelType&&(t.modelType=dt.modelType),null==t.maxFaces&&(t.maxFaces=dt.maxFaces),null==t.detectorModelUrl&&("full"===t.modelType?t.detectorModelUrl="https://tfhub.dev/mediapipe/tfjs-model/face_detection/full/1":t.detectorModelUrl="https://tfhub.dev/mediapipe/tfjs-model/face_detection/short/1"),t}(e),n="string"==typeof t.detectorModelUrl&&t.detectorModelUrl.indexOf("https://tfhub.dev")>-1,[4,Ge(t.detectorModelUrl,{fromTFHub:n})];case 1:return r=a.sent(),[2,new yt(t.modelType,r,t.maxFaces)]}}))}))}function wt(e,t){return je(this,0,void 0,(function(){var n,r;

2return Ke(this,(function(a){if(e===ct.MediaPipeFaceDetector){if(r=void 0,null!=(n=t)){if("tfjs"===n.runtime)return[2,bt(n)];if("mediapipe"===n.runtime)return[2,Ze(n)];r=n.runtime}throw new Error("Expect modelConfig.runtime to be either 'tfjs' "+"or 'mediapipe', but got ".concat(r))}throw new Error("".concat(e," is not a supported model name."))}))}))}(ct||(ct={})).MediaPipeFaceDetector="MediaPipeFaceDetector"}}]);