9 lines
25 KiB
JavaScript
9 lines
25 KiB
JavaScript
/*!
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* ONNX Runtime Web v1.22.0
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* Copyright (c) Microsoft Corporation. All rights reserved.
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* Licensed under the MIT License.
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*/
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import{createRequire}from"module";const require=createRequire(import.meta.url);
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P=0;P<bt;P++)R.push(Number(s.getValue(Ie+P*i,le)));s._OrtFree(Ie)!==0&&w("Can't free memory for tensor dims.");let N=R.reduce((P,T)=>P*T,1);v=ae(ee);let X=u?.outputPreferredLocations[o[m]];if(v==="string"){if(X==="gpu-buffer"||X==="ml-tensor")throw new Error("String tensor is not supported on GPU.");let P=[];for(let T=0;T<N;T++){let G=s.getValue(_+T*i,"*"),te=s.getValue(_+(T+1)*i,"*"),Le=T===N-1?void 0:te-G;P.push(s.UTF8ToString(G,Le))}W.push([v,R,P,"cpu"])}else if(X==="gpu-buffer"&&N>0){let P=s.jsepGetBuffer;if(!P)throw new Error('preferredLocation "gpu-buffer" is not supported without using WebGPU.');let T=P(_),G=J(ee,N);if(G===void 0||!ie(v))throw new Error(`Unsupported data type: ${v}`);H=!0,W.push([v,R,{gpuBuffer:T,download:s.jsepCreateDownloader(T,G,v),dispose:()=>{s._OrtReleaseTensor(F)!==0&&w("Can't release tensor.")}},"gpu-buffer"])}else if(X==="ml-tensor"&&N>0){let P=s.webnnEnsureTensor,T=s.webnnIsGraphInputOutputTypeSupported;if(!P||!T)throw new Error('preferredLocation "ml-tensor" is not supported without using WebNN.');if(J(ee,N)===void 0||!ue(v))throw new Error(`Unsupported data type: ${v}`);if(!T(e,v,!1))throw new Error(`preferredLocation "ml-tensor" for ${v} output is not supported by current WebNN Context.`);let te=await P(e,_,ee,R,!1);H=!0,W.push([v,R,{mlTensor:te,download:s.webnnCreateMLTensorDownloader(_,v),dispose:()=>{s.webnnReleaseTensorId(_),s._OrtReleaseTensor(F)}},"ml-tensor"])}else if(X==="ml-tensor-cpu-output"&&N>0){let P=s.webnnCreateMLTensorDownloader(_,v)(),T=W.length;H=!0,ve.push((async()=>{let G=[T,await P];return s.webnnReleaseTensorId(_),s._OrtReleaseTensor(F),G})()),W.push([v,R,[],"cpu"])}else{let P=Ne(v),T=new P(N);new Uint8Array(T.buffer,T.byteOffset,T.byteLength).set(s.HEAPU8.subarray(_,_+T.byteLength)),W.push([v,R,T,"cpu"])}}finally{s.stackRestore(Pe),v==="string"&&_&&s._free(_),H||s._OrtReleaseTensor(F)}}u&&!p&&(s._OrtClearBoundOutputs(u.handle)!==0&&w("Can't clear bound outputs."),Y.set(e,[l,f,d,u,p,!1]));for(let[m,F]of await Promise.all(ve))W[m][2]=F;return W}finally{s.webnnOnRunEnd?.(l),s.stackRestore(I),D.forEach(M=>s._OrtReleaseTensor(M)),h.forEach(M=>s._OrtReleaseTensor(M)),E.forEach(M=>s._free(M)),b!==0&&s._OrtReleaseRunOptions(b),g.forEach(M=>s._free(M))}},Ze=e=>{let t=y(),n=Y.get(e);if(!n)throw new Error("invalid session id");let o=n[0],r=t._OrtEndProfiling(o);r===0&&w("Can't get an profile file name."),t._OrtFree(r)}});import{env as Ee}from"onnxruntime-common";var Se,Ke,Qe,et,tt,rt,nt,ot,st,at,Oe=C(()=>{"use strict";Xe();V();me();Se=!1,Ke=!1,Qe=!1,et=async()=>{if(!Ke){if(Se)throw new Error("multiple calls to 'initWasm()' detected.");if(Qe)throw new Error("previous call to 'initWasm()' failed.");Se=!0;try{await De(Ee.wasm),await He(Ee),Ke=!0}catch(e){throw Qe=!0,e}finally{Se=!1}}},tt=async e=>{await Ve(Ee,e)},rt=async e=>he(e),nt=async(e,t)=>qe(e,t),ot=async e=>{Je(e)},st=async(e,t,n,o,r,a)=>Ye(e,t,n,o,r,a),at=async e=>{Ze(e)}});import{Tensor as Te,TRACE_FUNC_BEGIN as it,TRACE_FUNC_END as ut}from"onnxruntime-common";var ct,Ft,ce,ft=C(()=>{"use strict";Oe();we();re();ye();ct=(e,t)=>{switch(e.location){case"cpu":return[e.type,e.dims,e.data,"cpu"];case"gpu-buffer":return[e.type,e.dims,{gpuBuffer:e.gpuBuffer},"gpu-buffer"];case"ml-tensor":return[e.type,e.dims,{mlTensor:e.mlTensor},"ml-tensor"];default:throw new Error(`invalid data location: ${e.location} for ${t()}`)}},Ft=e=>{switch(e[3]){case"cpu":return new Te(e[0],e[2],e[1]);case"gpu-buffer":{let t=e[0];if(!ie(t))throw new Error(`not supported data type: ${t} for deserializing GPU tensor`);let{gpuBuffer:n,download:o,dispose:r}=e[2];return Te.fromGpuBuffer(n,{dataType:t,dims:e[1],download:o,dispose:r})}case"ml-tensor":{let t=e[0];if(!ue(t))throw new Error(`not supported data type: ${t} for deserializing MLTensor tensor`);let{mlTensor:n,download:o,dispose:r}=e[2];return Te.fromMLTensor(n,{dataType:t,dims:e[1],download:o,dispose:r})}default:throw new Error(`invalid data location: ${e[3]}`)}},ce=class{async fetchModelAndCopyToWasmMemory(t){return rt(await Q(t))}async loadModel(t,n){it();let o;typeof t=="string"?$?o=await Q(t):o=await this.fetchModelAndCopyToWasmMemory(t):o=t,[this.sessionId,this.inputNames,this.outputNames,this.inputMetadata,this.outputMetadata]=await nt(o,n),ut()}async dispose(){return ot(this.sessionId)}async run(t,n,o){it();let r=[],a=[];Object.entries(t).forEach(u=>{let p=u[0],S=u[1],O=this.inputNames.indexOf(p);if(O===-1)throw new Error(`invalid input '${p}'`);r.push(S),a.push(O)});let s=[],i=[];Object.entries(n).forEach(u=>{let p=u[0],S=u[1],O=this.outputNames.indexOf(p);if(O===-1)throw new Error(`invalid output '${p}'`);s.push(S),i.push(O)});let c=r.map((u,p)=>ct(u,()=>`input "${this.inputNames[a[p]]}"`)),l=s.map((u,p)=>u?ct(u,()=>`output "${this.outputNames[i[p]]}"`):null),f=await st(this.sessionId,a,c,i,l,o),d={};for(let u=0;u<f.length;u++)d[this.outputNames[i[u]]]=s[u]??Ft(f[u]);return ut(),d}startProfiling(){}endProfiling(){at(this.sessionId)}}});var pt={};ht(pt,{OnnxruntimeWebAssemblyBackend:()=>fe,initializeFlags:()=>lt,wasmBackend:()=>Rt});import{env as A}from"onnxruntime-common";var lt,fe,Rt,dt=C(()=>{"use strict";Oe();ft();lt=()=>{(typeof A.wasm.initTimeout!="number"||A.wasm.initTimeout<0)&&(A.wasm.initTimeout=0);let e=A.wasm.simd;if(typeof e!="boolean"&&e!==void 0&&e!=="fixed"&&e!=="relaxed"&&(console.warn(`Property "env.wasm.simd" is set to unknown value "${e}". Reset it to \`false\` and ignore SIMD feature checking.`),A.wasm.simd=!1),typeof A.wasm.proxy!="boolean"&&(A.wasm.proxy=!1),typeof A.wasm.trace!="boolean"&&(A.wasm.trace=!1),typeof A.wasm.numThreads!="number"||!Number.isInteger(A.wasm.numThreads)||A.wasm.numThreads<=0)if(typeof self<"u"&&!self.crossOriginIsolated)A.wasm.numThreads=1;else{let t=typeof navigator>"u"?de("node:os").cpus().length:navigator.hardwareConcurrency;A.wasm.numThreads=Math.min(4,Math.ceil((t||1)/2))}},fe=class{async init(t){lt(),await et(),await tt(t)}async createInferenceSessionHandler(t,n){let o=new ce;return await o.loadModel(t,n),o}},Rt=new fe});export*from"onnxruntime-common";import*as Nt from"onnxruntime-common";import{registerBackend as mt,env as Gt}from"onnxruntime-common";var _e="1.22.0";var Fr=Nt;{let e=(dt(),Et(pt)).wasmBackend;mt("cpu",e,10),mt("wasm",e,10)}Object.defineProperty(Gt.versions,"web",{value:_e,enumerable:!0});export{Fr as default};
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