https://claudecommunity.com.au/_next/static/chunks/4451.7cdc7ec2d3f015fe.js

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Releasing tensor."),this.releaseTensor()}this.activeUpload?this.activeUpload.set(t):this.activeUpload=new Uint8Array(t)}async download(e){if(this.activeUpload){let t=this.wrapper?.isDataConverted?e7(this.activeUpload,this.wrapper?.type):this.activeUpload;return e?void(e instanceof ArrayBuffer?new Uint8Array(e).set(t):new Uint8Array(e.buffer,e.byteOffset,e.byteLength).set(t)):t.buffer}if(!this.wrapper)throw Error("Tensor has not been created.");return e?this.wrapper.read(e):this.wrapper.read()}},to=class{constructor(e){this.backend=e,this.tensorTrackersById=new Map,this.freeTensors=[],this.externalTensors=new Set}getMLContext(e){let t=this.backend.getMLContext(e);if(!t)throw Error("MLContext not found for session.");return t}getMLOpSupportLimits(e){return this.backend.getMLOpSupportLimits(e)}reserveTensorId(){let e=te();return this.tensorTrackersById.set(e,new ta(this)),e}releaseTensorId(e){let t=this.tensorTrackersById.get(e);t&&(this.tensorTrackersById.delete(e),t.tensorWrapper&&this.releaseTensor(t.tensorWrapper))}async ensureTensor(e,t,r,n,o){e6("verbose",()=>`[WebNN] TensorManager.ensureTensor {tensorId: ${t}, dataType: ${r}, shape: ${n}, copyOld: ${o}}`);let i=this.tensorTrackersById.get(t);if(!i)throw Error("Tensor not found.");return i.ensureTensor(e,r,n,o)}upload(e,t){let r=this.tensorTrackersById.get(e);if(!r)throw Error("Tensor not found.");r.upload(t)}async download(e,t){e6("verbose",()=>`[WebNN] TensorManager.download {tensorId: ${e}, dstBuffer: ${t?.byteLength}}`);let r=this.tensorTrackersById.get(e);if(!r)throw Error("Tensor not found.");return r.download(t)}releaseTensorsForSession(e){for(let t of this.freeTensors)t.sessionId===e&&t.destroy();this.freeTensors=this.freeTensors.filter(t=>t.sessionId!==e)}registerTensor(e,t,r,n){let o=this.getMLContext(e),i=te(),s=new tn({sessionId:e,context:o,tensor:t,dataType:r,shape:n});return this.tensorTrackersById.set(i,new ta(this,s)),this.externalTensors.add(s),i}async getCachedTensor(e,t,r,n,o,i,s){let u=this.getMLContext(e);for(let[n,o]of this.freeTensors.entries())if(o.canReuseTensor(u,t,r)){e6("verbose",()=>`[WebNN] Reusing tensor {dataType: ${t}, ${s?`fallbackDataType: ${s},`:""} shape: ${r}`);let o=this.freeTensors.splice(n,1)[0];return o.sessionId=e,o}e6("verbose",()=>`[WebNN] MLContext.createTensor {dataType: ${t}, ${s?`fallbackDataType: ${s},`:""} shape: ${r}}`);let f=await u.createTensor({dataType:s??t,shape:r,dimensions:r,usage:n,writable:o,readable:i});return new tn({sessionId:e,context:u,tensor:f,dataType:t,shape:r,fallbackDataType:s})}releaseTensor(e){this.externalTensors.has(e)&&this.externalTensors.delete(e),this.freeTensors.push(e)}},ti=(...e)=>new to(...e)}

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t=this.temporarySessionTensorIds.get(e);if(t){for(let e of t)e6("verbose",()=>`[WebNN] releasing temporary tensor {tensorId: ${e}}`),this.tensorManager.releaseTensorId(e);this.temporarySessionTensorIds.delete(e),this.activeSessionId=void 0}}async createMLContext(e){if(e instanceof GPUDevice){let t=this.mlContextCache.findIndex(t=>t.gpuDevice===e);if(-1!==t)return this.mlContextCache[t].mlContext;{let t=await navigator.ml.createContext(e);return this.mlContextCache.push({gpuDevice:e,mlContext:t}),t}}if(void 0===e){let e=this.mlContextCache.findIndex(e=>void 0===e.options&&void 0===e.gpuDevice);if(-1!==e)return this.mlContextCache[e].mlContext;{let e=await navigator.ml.createContext();return this.mlContextCache.push({mlContext:e}),e}}let t=this.mlContextCache.findIndex(t=>((e,t)=>{if(e===t)return!0;if(void 0===e||void 0===t)return!1;let r=Object.keys(e).sort(),n=Object.keys(t).sort();return r.length===n.length&&r.every((r,o)=>r===n[o]&&e[r]===t[r])})(t.options,e));if(-1!==t)return this.mlContextCache[t].mlContext;{let t=await navigator.ml.createContext(e);return this.mlContextCache.push({options:e,mlContext:t}),t}}registerMLContext(e,t){this.mlContextBySessionId.set(e,t);let r=this.sessionIdsByMLContext.get(t);r||(r=new Set,this.sessionIdsByMLContext.set(t,r)),r.add(e),this.mlOpSupportLimitsBySessionId.has(e)||this.mlOpSupportLimitsBySessionId.set(e,t.opSupportLimits()),this.temporaryGraphInputs.length>0&&(this.sessionGraphInputs.set(e,this.temporaryGraphInputs),this.temporaryGraphInputs=[]),this.temporaryGraphOutputs.length>0&&(this.sessionGraphOutputs.set(e,this.temporaryGraphOutputs),this.temporaryGraphOutputs=[])}onReleaseSession(e){this.sessionGraphInputs.delete(e),this.sessionGraphOutputs.delete(e);let t=this.mlContextBySessionId.get(e);if(!t)return;this.tensorManager.releaseTensorsForSession(e),this.mlContextBySessionId.delete(e),this.mlOpSupportLimitsBySessionId.delete(e);let r=this.sessionIdsByMLContext.get(t);if(r.delete(e),0===r.size){this.sessionIdsByMLContext.delete(t);let e=this.mlContextCache.findIndex(e=>e.mlContext===t);-1!==e&&this.mlContextCache.splice(e,1)}}getMLContext(e){return this.mlContextBySessionId.get(e)}getMLOpSupportLimits(e){return this.mlOpSupportLimitsBySessionId.get(e)}reserveTensorId(){return this.tensorManager.reserveTensorId()}releaseTensorId(e){e6("verbose",()=>`[WebNN] releaseTensorId {tensorId: ${e}}`),this.tensorManager.releaseTensorId(e)}async ensureTensor(e,t,r,n,o){let i=tb.get(r);if(!i)throw Error(`Unsupported ONNX data type: ${r}`);return this.tensorManager.ensureTensor(e??this.currentSessionId,t,i,n,o)}async createTemporaryTensor(e,t,r){e6("verbose",()=>`[WebNN] createTemporaryTensor {onnxDataType: ${t}, shape: ${r}}`);let n=tb.get(t);if(!n)throw Error(`Unsupported ONNX data type: ${t}`);let o=this.tensorManager.reserveTensorId();await this.tensorManager.ensureTensor(e,o,n,r,!1);let i=this.temporarySessionTensorIds.get(e);return i?i.push(o):this.temporarySessionTensorIds.set(e,[o]),o}uploadTensor(e,t){if(!eN().shouldTransferToMLTensor)throw Error("Trying to upload to a MLTensor while shouldTransferToMLTensor is false");e6("verbose",()=>`[WebNN] uploadTensor {tensorId: ${e}, data: ${t.byteLength}}`),this.tensorManager.upload(e,t)}async downloadTensor(e,t){return this.tensorManager.download(e,t)}createMLTensorDownloader(e,t){return async()=>{let r=await this.tensorManager.download(e);return e0(r,t)}}registerMLTensor(e,t,r,n){let o=tb.get(r);if(!o)throw Error(`Unsupported ONNX data type: ${r}`);let i=this.tensorManager.registerTensor(e,t,o,n);return e6("verbose",()=>`[WebNN] registerMLTensor {tensor: ${t}, dataType: ${o}, dimensions: ${n}} -> {tensorId: ${i}}`),i}registerMLConstant(e,t,r,n,o,i,s=!1){if(!i)throw Error("External mounted files are not available.");let u=e;e.startsWith("./")&&(u=e.substring(2));let f=i.get(u);if(!f)throw Error(`File with name ${u} not found in preloaded files.`);if(t+r>f.byteLength)throw Error("Out of bounds: data offset and length exceed the external file data size.");let l=f.slice(t,t+r).buffer,c;switch(o.dataType){case"float32":c=new Float32Array(l);break;case"float16":c="u">typeof Float16Array?new Float16Array(l):new Uint16Array(l);break;case"int32":c=new Int32Array(l);break;case"uint32":c=new Uint32Array(l);break;case"int64":s?(c=new Int32Array(e5(new Uint8Array(l),"int64").buffer),o.dataType="int32"):c=new BigInt64Array(l);break;case"uint64":c=new BigUint64Array(l);break;case"int8":c=new Int8Array(l);break;case"int4":case"uint4":case"uint8":c=new Uint8Array(l);break;default:throw Error(`Unsupported data type: ${o.dataType} in creating WebNN Constant from external data.`)}return e6("verbose",()=>`[WebNN] registerMLConstant {dataType: ${o.dataType}, shape: ${o.shape}}} ${s?"(Note: it was int64 data type and registered to int32 as 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4if(r){if("object"!=typeof r.limits||"object"!=typeof r.features||"function"!=typeof r.requestDevice)throw Error("Invalid GPU adapter set in `env.webgpu.adapter`. It must be a GPUAdapter object.")}else{let t=e.webgpu.powerPreference;if(void 0!==t&&"low-power"!==t&&"high-performance"!==t)throw Error(`Invalid powerPreference setting: "${t}"`);let n=e.webgpu.forceFallbackAdapter;if(void 0!==n&&"boolean"!=typeof n)throw Error(`Invalid forceFallbackAdapter setting: "${n}"`);if(!(r=await navigator.gpu.requestAdapter({powerPreference:t,forceFallbackAdapter:n})))throw Error('Failed to get GPU adapter. You may need to enable flag "--enable-unsafe-webgpu" if you are using Chrome.')}}if("webnn"===t&&(typeof navigator>"u"||!navigator.ml))throw Error("WebNN is not supported in current environment");if("webgpu"===t&&eN().webgpuInit(t=>{e.webgpu.device=t}),"webnn"===t){let t=new(tK(),j(tw)).WebNNBackend(e);eN().webnnInit([t,()=>t.reserveTensorId(),e=>t.releaseTensorId(e),async(e,r,n,o,i)=>t.ensureTensor(e,r,n,o,i),(e,r)=>{t.uploadTensor(e,r)},async(e,r)=>t.downloadTensor(e,r),(e,r)=>t.registerMLContext(e,r),!!e.trace])}},tx=new Map,tA=(e,t)=>{let r=eN(),n=r.stackSave(),o=0;try{let n=r.PTR_SIZE,i=r.stackAlloc(2*n);0!==r._OrtGetInputOutputMetadata(e,t,i,i+n)&&eD("Can't get session input/output metadata.");let s=Number(r.getValue(i,"*"));o=Number(r.getValue(i+n,"*"));let u=r.HEAP32[o/4];if(0===u)return[s,0];let f=r.HEAPU32[o/4+1],l=[];for(let e=0;e<f;e++){let t=Number(r.getValue(o+8+e*n,"*"));l.push(0!==t?r.UTF8ToString(t):Number(r.getValue(o+8+(e+f)*n,"*")))}return[s,u,l]}finally{r.stackRestore(n),0!==o&&r._OrtFree(o)}},tC=e=>{let t=eN(),r=t._malloc(e.byteLength);if(0===r)throw Error(`Can't create a session. failed to allocate a buffer of size ${e.byteLength}.`);return t.HEAPU8.set(e,r),[r,e.byteLength]},tO=async(e,t)=>{let r,n,o=eN();Array.isArray(e)?[r,n]=e:e.buffer===o.HEAPU8.buffer?[r,n]=[e.byteOffset,e.byteLength]:[r,n]=tC(e);let i=0,s=0,u=0,f=[],l=[],c=[];try{if([s,f]=await ez(t),t?.externalData&&o.mountExternalData){let e=[];for(let r of t.externalData){let t="string"==typeof r?r:r.path;e.push(eK("string"==typeof r?r:r.data).then(e=>{o.mountExternalData(t,e)}))}await Promise.all(e)}for(let e of t?.executionProviders??[])if(("string"==typeof e?e:e.name)==="webnn"){if(o.shouldTransferToMLTensor=!1,"string"!=typeof e){let t=e?.context,r=e?.gpuDevice,n=e?.deviceType,i=e?.powerPreference;t?o.currentContext=t:r?o.currentContext=await o.webnnCreateMLContext(r):o.currentContext=await o.webnnCreateMLContext({deviceType:n,powerPreference:i})}else o.currentContext=await o.webnnCreateMLContext();break}i=await o._OrtCreateSession(r,n,s),o.webgpuOnCreateSession?.(i),0===i&&eD("Can't create a session."),o.jsepOnCreateSession?.(),o.currentContext&&(o.webnnRegisterMLContext(i,o.currentContext),o.currentContext=void 0,o.shouldTransferToMLTensor=!0);let[e,p]=(e=>{let t=eN(),r=t.stackSave();try{let r=t.PTR_SIZE,n=t.stackAlloc(2*r);0!==t._OrtGetInputOutputCount(e,n,n+r)&&eD("Can't get session input/output count.");let o=4===r?"i32":"i64";return[Number(t.getValue(n,o)),Number(t.getValue(n+r,o))]}finally{t.stackRestore(r)}})(i),d=!!t?.enableGraphCapture,h=[],m=[],g=[],y=[],w=[];for(let t=0;t<e;t++){let[e,r,n]=tA(i,t);0===e&&eD("Can't get an input name."),l.push(e);let s=o.UTF8ToString(e);h.push(s),g.push(0===r?{name:s,isTensor:!1}:{name:s,isTensor:!0,type:eH(r),shape:n})}for(let r=0;r<p;r++){let[n,s,u]=tA(i,r+e);0===n&&eD("Can't get an output name."),c.push(n);let f=o.UTF8ToString(n);m.push(f),y.push(0===s?{name:f,isTensor:!1}:{name:f,isTensor:!0,type:eH(s),shape:u});{if(d&&t?.preferredOutputLocation===void 0){w.push("gpu-buffer");continue}let e="string"==typeof t?.preferredOutputLocation?t.preferredOutputLocation:t?.preferredOutputLocation?.[f]??"cpu",r=o.webnnIsGraphOutput;if("cpu"===e&&r&&r(i,f)){w.push("ml-tensor-cpu-output");continue}if("cpu"!==e&&"cpu-pinned"!==e&&"gpu-buffer"!==e&&"ml-tensor"!==e)throw Error(`Not supported preferred output location: ${e}.`);if(d&&"gpu-buffer"!==e)throw Error(`Not supported preferred output location: ${e}. Only 'gpu-buffer' location is supported when enableGraphCapture is true.`);w.push(e)}}let b=null;return w.some(e=>"gpu-buffer"===e||"ml-tensor"===e||"ml-tensor-cpu-output"===e)&&(u=o._OrtCreateBinding(i),0===u&&eD("Can't create IO binding."),b={handle:u,outputPreferredLocations:w,outputPreferredLocationsEncoded:w.map(e=>"ml-tensor-cpu-output"===e?"ml-tensor":e).map(e=>eJ(e))}),tx.set(i,[i,l,c,b,d,!1]),[i,h,m,g,y]}

4catch(e){throw l.forEach(e=>o._OrtFree(e)),c.forEach(e=>o._OrtFree(e)),0!==u&&0!==o._OrtReleaseBinding(u)&&eD("Can't release IO binding."),0!==i&&0!==o._OrtReleaseSession(i)&&eD("Can't release session."),e}finally{o._free(r),0!==s&&0!==o._OrtReleaseSessionOptions(s)&&eD("Can't release session options."),f.forEach(e=>o._free(e)),o.unmountExternalData?.()}},tI=e=>{let t=eN(),r=tx.get(e);if(!r)throw Error(`cannot release session. invalid session id: ${e}`);let[n,o,i,s,u]=r;s&&(u&&0!==t._OrtClearBoundOutputs(s.handle)&&eD("Can't clear bound outputs."),0!==t._OrtReleaseBinding(s.handle)&&eD("Can't release IO binding.")),t.jsepOnReleaseSession?.(e),t.webnnOnReleaseSession?.(e),t.webgpuOnReleaseSession?.(e),o.forEach(e=>t._OrtFree(e)),i.forEach(e=>t._OrtFree(e)),0!==t._OrtReleaseSession(n)&&eD("Can't release session."),tx.delete(e)},tS=async(e,t,r,n,o,i,s=!1)=>{if(!e)return void t.push(0);let u=eN(),f=u.PTR_SIZE,l=e[0],c=e[1],p=e[3],d=p,h,m;if("string"===l&&("gpu-buffer"===p||"ml-tensor"===p))throw Error("String tensor is not supported on GPU.");if(s&&"gpu-buffer"!==p)throw Error(`External buffer must be provided for input/output index ${i} when enableGraphCapture is true.`);if("gpu-buffer"===p){let t=e[2].gpuBuffer;m=eq(ej(l),c);{let e=u.webgpuRegisterBuffer;if(!e)throw Error('Tensor location "gpu-buffer" is not supported without using WebGPU.');h=e(t,n)}}else if("ml-tensor"===p){let t=e[2].mlTensor;m=eq(ej(l),c);let r=u.webnnRegisterMLTensor;if(!r)throw Error('Tensor location "ml-tensor" is not supported without using WebNN.');h=r(n,t,ej(l),c)}else{let t=e[2];if(Array.isArray(t)){m=f*t.length,h=u._malloc(m),r.push(h);for(let e=0;e<t.length;e++){if("string"!=typeof t[e])throw TypeError(`tensor data at index ${e} is not a string`);u.setValue(h+e*f,ek(t[e],r),"*")}}else{let e=u.webnnIsGraphInput,i=u.webnnIsGraphOutput;if("string"!==l&&e&&i){let s=u.UTF8ToString(o);if(e(n,s)||i(n,s)){let e=ej(l);m=eq(e,c),d="ml-tensor";let r=u.webnnCreateTemporaryTensor,o=u.webnnUploadTensor;if(!r||!o)throw Error('Tensor location "ml-tensor" is not supported without using WebNN.');let i=await r(n,e,c);o(i,new Uint8Array(t.buffer,t.byteOffset,t.byteLength)),h=i}else m=t.byteLength,h=u._malloc(m),r.push(h),u.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,m),h)}else m=t.byteLength,h=u._malloc(m),r.push(h),u.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,m),h)}}let g=u.stackSave(),y=u.stackAlloc(4*c.length);try{c.forEach((e,t)=>u.setValue(y+t*f,e,4===f?"i32":"i64"));let e=u._OrtCreateTensor(ej(l),h,m,y,c.length,eJ(d));0===e&&eD(`Can't create tensor for input/output. session=${n}, index=${i}.`),t.push(e)}finally{u.stackRestore(g)}},tU=async(e,t,r,n,o,i)=>{let s=eN(),u=s.PTR_SIZE,f=tx.get(e);if(!f)throw Error(`cannot run inference. invalid session id: ${e}`);let l=f[0],c=f[1],p=f[2],d=f[3],h=f[4],m=f[5],g=t.length,y=n.length,w=0,b=[],v=[],T=[],E=[],x=[],A=s.stackSave(),C=s.stackAlloc(g*u),O=s.stackAlloc(g*u),I=s.stackAlloc(y*u),S=s.stackAlloc(y*u);try{let f;[w,b]=eG(i),P("wasm prepareInputOutputTensor");for(let n=0;n<g;n++)await tS(r[n],v,E,e,c[t[n]],t[n],h);for(let t=0;t<y;t++)await tS(o[t],T,E,e,p[n[t]],g+n[t],h);$("wasm prepareInputOutputTensor");for(let e=0;e<g;e++)s.setValue(C+e*u,v[e],"*"),s.setValue(O+e*u,c[t[e]],"*");for(let e=0;e<y;e++)s.setValue(I+e*u,T[e],"*"),s.setValue(S+e*u,p[n[e]],"*");if(d&&!m){let{handle:r,outputPreferredLocations:i,outputPreferredLocationsEncoded:u}=d;if(c.length!==g)throw Error(`input count from feeds (${g}

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