https://portal.simplehire.ai/assets/ort.webgpu.bundle.min-Blm_AXyt.js

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jr(this,c)),this.externalTensors.add(c),p}async getCachedTensor(r,n,i,f,s,p,c){let m=this.getMLContext(r);for(let[y,v]of this.freeTensors.entries())if(v.canReuseTensor(m,n,i)){pe("verbose",()=>`[WebNN] Reusing tensor {dataType: ${n}, ${c?`fallbackDataType: ${c},`:""} shape: ${i}`);let b=this.freeTensors.splice(y,1)[0];return b.sessionId=r,b}pe("verbose",()=>`[WebNN] MLContext.createTensor {dataType: ${n}, ${c?`fallbackDataType: ${c},`:""} shape: ${i}}`);let w=await m.createTensor({dataType:c??n,shape:i,dimensions:i,usage:f,writable:s,readable:p});return new zr({sessionId:r,context:m,tensor:w,dataType:n,shape:i,fallbackDataType:c})}releaseTensor(r){this.externalTensors.has(r)&&this.externalTensors.delete(r),this.freeTensors.push(r)}},Pi=(...r)=>new Xo(...r)}),$i={};Rt($i,{WebNNBackend:()=>Ni});var St,Zo,Ni,vl=G(()=>{wt(),nt(),yl(),bl(),Li(),St=new Map([[1,"float32"],[10,"float16"],[6,"int32"],[12,"uint32"],[7,"int64"],[13,"uint64"],[22,"int4"],[21,"uint4"],[3,"int8"],[2,"uint8"],[9,"uint8"]]),Zo=(r,n)=>{if(r===n)return!0;if(r===void 0||n===void 0)return!1;let i=Object.keys(r).sort(),f=Object.keys(n).sort();return i.length===f.length&&i.every((s,p)=>s===f[p]&&r[s]===n[s])},Ni=class{constructor(r){this.tensorManager=Pi(this),this.mlContextBySessionId=new Map,this.sessionIdsByMLContext=new Map,this.mlContextCache=[],this.sessionGraphInputs=new Map,this.sessionGraphOutputs=new Map,this.temporaryGraphInputs=[],this.temporaryGraphOutputs=[],this.temporarySessionTensorIds=new Map,this.mlOpSupportLimitsBySessionId=new Map,Ri(r.logLevel,!!r.debug)}get currentSessionId(){if(this.activeSessionId===void 0)throw new Error("No active session");return this.activeSessionId}onRunStart(r){pe("verbose",()=>`[WebNN] onRunStart {sessionId: ${r}}`),this.activeSessionId=r}onRunEnd(r){pe("verbose",()=>`[WebNN] onRunEnd {sessionId: ${r}}`);let n=this.temporarySessionTensorIds.get(r);if(n){for(let i of n)pe("verbose",()=>`[WebNN] releasing temporary tensor {tensorId: ${i}}`),this.tensorManager.releaseTensorId(i);this.temporarySessionTensorIds.delete(r),this.activeSessionId=void 0}}async createMLContext(r){if(r instanceof GPUDevice){let i=this.mlContextCache.findIndex(f=>f.gpuDevice===r);if(i!==-1)return this.mlContextCache[i].mlContext;{let f=await navigator.ml.createContext(r);return this.mlContextCache.push({gpuDevice:r,mlContext:f}),f}}else if(r===void 0){let i=this.mlContextCache.findIndex(f=>f.options===void 0&&f.gpuDevice===void 0);if(i!==-1)return this.mlContextCache[i].mlContext;{let f=await navigator.ml.createContext();return this.mlContextCache.push({mlContext:f}),f}}let n=this.mlContextCache.findIndex(i=>Zo(i.options,r));if(n!==-1)return this.mlContextCache[n].mlContext;{let i=await navigator.ml.createContext(r);return this.mlContextCache.push({options:r,mlContext:i}),i}}registerMLContext(r,n){this.mlContextBySessionId.set(r,n);let i=this.sessionIdsByMLContext.get(n);i||(i=new Set,this.sessionIdsByMLContext.set(n,i)),i.add(r),this.mlOpSupportLimitsBySessionId.has(r)||this.mlOpSupportLimitsBySessionId.set(r,n.opSupportLimits()),this.temporaryGraphInputs.length>0&&(this.sessionGraphInputs.set(r,this.temporaryGraphInputs),this.temporaryGraphInputs=[]),this.temporaryGraphOutputs.length>0&&(this.sessionGraphOutputs.set(r,this.temporaryGraphOutputs),this.temporaryGraphOutputs=[])}onReleaseSession(r){this.sessionGraphInputs.delete(r),this.sessionGraphOutputs.delete(r);let n=this.mlContextBySessionId.get(r);if(!n)return;this.tensorManager.releaseTensorsForSession(r),this.mlContextBySessionId.delete(r),this.mlOpSupportLimitsBySessionId.delete(r);let i=this.sessionIdsByMLContext.get(n);if(i.delete(r),i.size===0){this.sessionIdsByMLContext.delete(n);let f=this.mlContextCache.findIndex(s=>s.mlContext===n);f!==-1&&this.mlContextCache.splice(f,1)}}getMLContext(r){return this.mlContextBySessionId.get(r)}getMLOpSupportLimits(r){return this.mlOpSupportLimitsBySessionId.get(r)}reserveTensorId(){return this.tensorManager.reserveTensorId()}releaseTensorId(r){pe("verbose",()=>`[WebNN] releaseTensorId {tensorId: ${r}}`),this.tensorManager.releaseTensorId(r)}async ensureTensor(r,n,i,f,s){let p=St.get(i);if(!p)throw new Error(`Unsupported ONNX data type: ${i}`);return this.tensorManager.ensureTensor(r??this.currentSessionId,n,p,f,s)}async createTemporaryTensor(r,n,i){pe("verbose",()=>`[WebNN] createTemporaryTensor {onnxDataType: ${n}, shape: ${i}}`);let f=St.get(n);if(!f)throw new Error(`Unsupported ONNX data type: ${n}`);let s=this.tensorManager.reserveTensorId();await this.tensorManager.ensureTensor(r,s,f,i,!1);let p=this.temporarySessionTensorIds.get(r);return p?p.push(s):this.temporarySessionTensorIds.set(r,[s]),s}uploadTensor(r,n){if(!Y().shouldTransferToMLTensor)throw new Error("Trying to upload to a MLTensor while shouldTransferToMLTensor is false");pe("verbose",()=>`[WebNN] uploadTensor {tensorId: ${r}, data: ${n.byteLength}}`),this.tensorManager.upload(r,n)}async downloadTensor(r,n){return this.tensorManager.download(r,n)}createMLTensorDownloader(r,n){return async()=>{let i=await this.tensorManager.download(r);return Bi(i,n)}}registerMLTensor(r,n,i,f){let s=St.get(i);if(!s)throw new Error(`Unsupported ONNX data type: ${i}`);let p=this.tensorManager.registerTensor(r,n,s,f);return pe("verbose",()=>`[WebNN] registerMLTensor {tensor: ${n}, dataType: ${s}, dimensions: ${f}} -> {tensorId: ${p}}`),p}registerMLConstant(r,n,i,f,s,p,c=!1){if(!p)throw new Error("External mounted files are not available.");let m=r;r.startsWith("./")&&(m=r.substring(2));let w=p.get(m);

8L++){if(typeof M[L]!="string")throw new TypeError(`tensor data at index ${L} is not a string`);m.setValue(C+L*w,be(M[L],i),"*")}}else{let L=m.webnnIsGraphInput,X=m.webnnIsGraphOutput;if(y!=="string"&&L&&X){let W=m.UTF8ToString(s);if(L(f,W)||X(f,W)){let ne=Qe(y);I=pt(ne,v),E="ml-tensor";let de=m.webnnCreateTemporaryTensor,d=m.webnnUploadTensor;if(!de||!d)throw new Error('Tensor location "ml-tensor" is not supported without using WebNN.');let V=await de(f,ne,v);d(V,new Uint8Array(M.buffer,M.byteOffset,M.byteLength)),C=V}else I=M.byteLength,C=m._malloc(I),i.push(C),m.HEAPU8.set(new Uint8Array(M.buffer,M.byteOffset,I),C)}else I=M.byteLength,C=m._malloc(I),i.push(C),m.HEAPU8.set(new Uint8Array(M.buffer,M.byteOffset,I),C)}}let P=m.stackSave(),z=m.stackAlloc(4*v.length);try{v.forEach((L,X)=>m.setValue(z+X*w,L,w===4?"i32":"i64"));let M=m._OrtCreateTensor(Qe(y),C,I,z,v.length,Jr(E));M===0&&q(`Can't create tensor for input/output. session=${f}, index=${p}.`),n.push(M)}finally{m.stackRestore(P)}},wn=async(r,n,i,f,s,p)=>{var ae,O,x,ze;let c=Y(),m=c.PTR_SIZE,w=Fe.get(r);if(!w)throw new Error(`cannot run inference. invalid session id: ${r}`);let y=w[0],v=w[1],b=w[2],E=w[3],C=w[4],I=w[5],P=n.length,z=f.length,M=0,L=[],X=[],W=[],ne=[],de=[],d=c.stackSave(),V=c.stackAlloc(P*m),k=c.stackAlloc(P*m),j=c.stackAlloc(z*m),ie=c.stackAlloc(z*m);try{[M,L]=Ii(p),et("wasm prepareInputOutputTensor");for(let $=0;$<P;$++)await Hr(i[$],X,ne,r,v[n[$]],n[$],C);for(let $=0;$<z;$++)await Hr(s[$],W,ne,r,b[f[$]],P+f[$],C);tt("wasm prepareInputOutputTensor");for(let $=0;$<P;$++)c.setValue(V+$*m,X[$],"*"),c.setValue(k+$*m,v[n[$]],"*");for(let $=0;$<z;$++)c.setValue(j+$*m,W[$],"*"),c.setValue(ie+$*m,b[f[$]],"*");if(E&&!I){let{handle:$,outputPreferredLocations:he,outputPreferredLocationsEncoded:ke}=E;if(v.length!==P)throw new Error(`input count from feeds (${P}

8{if(!It){if(ct)throw new Error("multiple calls to 'initWasm()' detected.");if(Ut)throw new Error("previous call to 'initWasm()' failed.");if(ct=!0,Ve())return new Promise((r,n)=>{ge==null||ge.terminate(),Oi().then(([i,f])=>{try{ge=f,ge.onerror=p=>n(p),ge.onmessage=Qo,Yr=[r,n];let s={type:"init-wasm",in:ee};!s.in.wasm.wasmPaths&&(i||Kr)&&(s.in.wasm.wasmPaths={wasm:new URL("/assets/ort-wasm-simd-threaded.asyncify-CvvOzbbq.wasm",import.meta.url).href}),ge.postMessage(s),Ht=i}catch(s){n(s)}},n)});try{await sn(ee.wasm),await pn(ee),It=!0}catch(r){throw Ut=!0,r}finally{ct=!1}}},Di=async r=>{if(Ve())return Ke(),new Promise((n,i)=>{Ze("init-ep",[n,i]);let f={type:"init-ep",in:{epName:r,env:ee}};ge.postMessage(f)});await dn(ee,r)},Gi=async r=>Ve()?(Ke(),new Promise((n,i)=>{Ze("copy-from",[n,i]);let f={type:"copy-from",in:{buffer:r}};ge.postMessage(f,[r.buffer])})):Qt(r),Wi=async(r,n)=>{if(Ve()){if(n!=null&&n.preferredOutputLocation)throw new Error('session option "preferredOutputLocation" is not supported for proxy.');return Ke(),new Promise((i,f)=>{Ze("create",[i,f]);let s={type:"create",in:{model:r,options:{...n}}},p=[];r instanceof Uint8Array&&p.push(r.buffer),ge.postMessage(s,p)})}else return hn(r,n)},Fi=async r=>{if(Ve())return Ke(),new Promise((n,i)=>{Ze("release",[n,i]);let f={type:"release",in:r};ge.postMessage(f)});mn(r)},Vi=async(r,n,i,f,s,p)=>{if(Ve()){if(i.some(c=>c[3]!=="cpu"))throw new Error("input tensor on GPU is not supported for proxy.");if(s.some(c=>c))throw new Error("pre-allocated output tensor is not supported for proxy.");return Ke(),new Promise((c,m)=>{Ze("run",[c,m]);let w=i,y={type:"run",in:{sessionId:r,inputIndices:n,inputs:w,outputIndices:f,options:p}};ge.postMessage(y,yn(w))})}else return wn(r,n,i,f,s,p)},zi=async r=>{if(Ve())return Ke(),new Promise((n,i)=>{Ze("end-profiling",[n,i]);let f={type:"end-profiling",in:r};ge.postMessage(f)});gn(r)}}),Xr,ei,qi,Tl=G(()=>{rt(),ji(),wt(),an(),Mi(),Xr=(r,n)=>{switch(r.location){case"cpu":return[r.type,r.dims,r.data,"cpu"];case"gpu-buffer":return[r.type,r.dims,{gpuBuffer:r.gpuBuffer},"gpu-buffer"];case"ml-tensor":return[r.type,r.dims,{mlTensor:r.mlTensor},"ml-tensor"];default:throw new Error(`invalid data location: ${r.location} for ${n()}`)}},ei=r=>{switch(r[3]){case"cpu":return new Me(r[0],r[2],r[1]);case"gpu-buffer":{let n=r[0];if(!fn(n))throw new Error(`not supported data type: ${n} for deserializing GPU tensor`);let{gpuBuffer:i,download:f,dispose:s}=r[2];return Me.fromGpuBuffer(i,{dataType:n,dims:r[1],download:f,dispose:s})}case"ml-tensor":{let n=r[0];if(!ln(n))throw new Error(`not supported data type: ${n} for deserializing MLTensor tensor`);let{mlTensor:i,download:f,dispose:s}=r[2];return Me.fromMLTensor(i,{dataType:n,dims:r[1],download:f,dispose:s})}default:throw new Error(`invalid data location: ${r[3]}`)}},qi=class{async fetchModelAndCopyToWasmMemory(r){return Gi(await cn(r))}async loadModel(r,n){ht();let i;typeof r=="string"?i=await this.fetchModelAndCopyToWasmMemory(r):i=r,[this.sessionId,this.inputNames,this.outputNames,this.inputMetadata,this.outputMetadata]=await Wi(i,n),mt()}async dispose(){return Fi(this.sessionId)}async run(r,n,i){ht();let f=[],s=[];Object.entries(r).forEach(b=>{let E=b[0],C=b[1],I=this.inputNames.indexOf(E);if(I===-1)throw new Error(`invalid input '${E}'`);f.push(C),s.push(I)});let p=[],c=[];Object.entries(n).forEach(b=>{let E=b[0],C=b[1],I=this.outputNames.indexOf(E);if(I===-1)throw new Error(`invalid output '${E}'`);p.push(C),c.push(I)});let m=f.map((b,E)=>Xr(b,()=>`input "${this.inputNames[s[E]]}"`)),w=p.map((b,E)=>b?Xr(b,()=>`output "${this.outputNames[c[E]]}"`):null),y=await Vi(this.sessionId,s,m,c,w,i),v={};for(let b=0;b<y.length;b++)v[this.outputNames[c[b]]]=p[b]??ei(y[b]);return mt(),v}startProfiling(){}endProfiling(){zi(this.sessionId)}}}),Hi={};Rt(Hi,{OnnxruntimeWebAssemblyBackend:()=>tn,initializeFlags:()=>en,wasmBackend:()=>Yi});var en,tn,Yi,El=G(()=>{rt(),ji(),Tl(),en=()=>{(typeof ee.wasm.initTimeout!="number"||ee.wasm.initTimeout<0)&&(ee.wasm.initTimeout=0);let r=ee.wasm.simd;if(typeof r!="boolean"&&r!==void 0&&r!=="fixed"&&r!=="relaxed"&&(console.warn(`Property "env.wasm.simd" is set to unknown value "${r}". Reset it to \`false\` and ignore SIMD feature checking.`),ee.wasm.simd=!1),typeof ee.wasm.proxy!="boolean"&&(ee.wasm.proxy=!1),typeof ee.wasm.trace!="boolean"&&(ee.wasm.trace=!1),typeof ee.wasm.numThreads!="number"||!Number.isInteger(ee.wasm.numThreads)||ee.wasm.numThreads<=0)if(typeof self<"u"&&!self.crossOriginIsolated)ee.wasm.numThreads=1;else{let n=typeof navigator>"u"?Qf("node:os").cpus().length:navigator.hardwareConcurrency;ee.wasm.numThreads=Math.min(4,Math.ceil((n||1)/2))}},tn=class{async init(r){en(),await _i(),await Di(r)}async createInferenceSessionHandler(r,n){let i=new qi;return await i.loadModel(r,n),i}},Yi=new tn});rt();rt();rt();var xl="1.27.0",Al=vi;{let r=(El(),Zt(Hi)).wasmBackend;dt("webgpu",r,5),dt("webnn",r,5),dt("cpu",r,10),dt("wasm",r,10)}Object.defineProperty(ee.versions,"web",{value:xl,enumerable:!0});export{bi as InferenceSession,Zr as TRACE,et as TRACE_EVENT_BEGIN,tt as TRACE_EVENT_END,ht as TRACE_FUNC_BEGIN,mt as TRACE_FUNC_END,Me as Tensor,Al as default,ee as env,dt as registerBackend};