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To allow LiteRT.js to load the JSPI wasm file, use a directory path instead of a full file path.`),await z("jspi"));let s=Fe;o&&(t!=null&&t.threads?s=Ge:t!=null&&t.jspi?s=Oe:s=Le);let a=e;if(r.endsWith(".wasm"))throw new Error("Please load the `.js` file corresponding to the `.wasm` file, or load the directory containing it.");return r.endsWith(".js")||(a=_e(e,s)),ae(We,a)}function He(e,t){if(X())throw new Error("LiteRT is already loading / loaded.");return G(Ne(e,t).then(async r=>(K(r),r.setDefaultEnvironment(await N.create()),r)).catch(r=>{throw G(void 0),r})),fe()}function Ye(){if(X()&&!$())throw new Error("LiteRT is loading and can not be unloaded or canceled until it is finished loading.");$()&&(T().delete(),K(void 0)),G(void 0)}var H=Promise.resolve();async function qe(e,t,r={}){const n=T(),o=n.liteRtWasm,s=r.environment??n.getDefaultEnvironment();if(!s.webGpuDevice)throw new Error("WebGPU device is required for streamed loading in this implementation.");const a=H;let i;H=new Promise(u=>{i=u}),await a;try{o.registerStreamWeightsCallback(async(u,l,p,f)=>{const h=[];if(u.length!==l.length)throw new Error(`Stream weights callback received arrays of different lengths: tflIds=${u.length}, wgpuBufferIds=${l.length}, `);for(let w=0;w<u.length;w++)h.push({id:u[w],wgpuBufferId:l[w],offset:p[w],length:f[w]});h.sort((w,D)=>w.offset-D.offset),console.log(`[StreamWeights] Starting loading session for ${h.length} tensors:`,JSON.stringify(h));const d=t.getReader();let R=0,m=new Uint8Array(0),v=0;try{for(;v<h.length;){const w=h[v],D=w.offset-R,C=D+w.length;if(C<=m.length){if(D<0)throw new Error(`Stream logic error: weight starts before current buffer (req.offset=${w.offset}, streamOffset=${R}).`);let b=m.subarray(D,C);if(b.byteLength%4!==0){const W=b.byteLength+3&-4,k=new Uint8Array(W);k.set(b),b=k}const B=o.WebGPU.getJsObject(w.wgpuBufferId);if(!B)throw new Error(`Failed to find GPUBuffer for ID: ${w.wgpuBufferId}`);console.log(`[StreamWeights] Writing ${b.byteLength} bytes to GPUBuffer ${w.wgpuBufferId} (tflId=${w.id}, first 5 bytes=${Array.from(b.slice(0,5))})`),s.webGpuDevice.queue.writeBuffer(B,0,b),v++}
1else{const{done:b,value:B}=await d.read();if(b)throw new Error("Stream ended before all weights were loaded.");const W=new Uint8Array(m.length+B.length);W.set(m),W.set(B,m.length),m=W}if(v<h.length){const b=h[v].offset-R,B=Math.min(b,m.length);(B>1024*1024||B===m.length)&&(m=m.slice(B),R+=B)}}}finally{d.releaseLock()}});try{const u=o._malloc(e.byteLength);o.HEAPU8.set(e,u);const l=o.loadModel(s.liteRtEnvironment,u,e.byteLength),p=new te(l,()=>{o._free(u)}),f=re(r,s,o.getThreadCount()),h=await o.compileModel(s.liteRtEnvironment,l,f),d=new ee(p,h,f,()=>{n._unregisterObjectForDeletion(d)});return n._registerObjectForDeletion(d),d}finally{o.registerStreamWeightsCallback(void 0)}}finally{i()}}async function Y(e,t={}){const r=t.environment??e.environment,n=T().liteRtWasm,o=e.liteRtTensorBuffer;if(o.bufferType().value!==g.HOST_MEMORY)throw new Error("Source tensor is not in host memory. Cannot copy to host memory.");const a=o.lock(n.LiteRtTensorBufferLockMode.READ);let i;try{i=n.LiteRtTensorBuffer.createManaged(r.liteRtEnvironment,n.LiteRtTensorBufferType.HOST_MEMORY,o.tensorType(),o.size());const u=i.lock(n.LiteRtTensorBufferLockMode.WRITE);try{const l=new Uint8Array(n.HEAPU8.buffer,a,o.size());n.HEAPU8.set(l,u)}finally{i.unlock()}}finally{o.unlock()}if(!i)throw new Error("Failed to create destination tensor buffer.");return new S(i,r)}async function q(e,t={}){const r=t.environment??e.environment,n=r.webGpuDevice;if(!n)throw new Error("No WebGPU device is available. Did you forget to pass a destination environment that has a WebGPU device?");const o=T().liteRtWasm,a=e.liteRtTensorBuffer.size()+3&-4,i=n.createBuffer({size:a,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,mappedAtCreation:!0}),u=await i.getMappedRange(),l=new Uint8Array(u),p=e.liteRtTensorBuffer.lock(o.LiteRtTensorBufferLockMode.READ);try{const d=new Uint8Array(o.HEAPU8.buffer,p,e.liteRtTensorBuffer.size());l.set(d)}finally{e.liteRtTensorBuffer.unlock()}i.unmap();const f=n.createBuffer({size:a,usage:GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST|GPUBufferUsage.STORAGE}),h=n.createCommandEncoder();return h.copyBufferToBuffer(i,0,f,0,a),n.queue.submit([h.finish()]),i.destroy(),new S(f,e.type.layout.dimensions,e.type.dtype,r,()=>{f.destroy()})}async function J(e,t={}){const r=t.environment??e.environment,n=e.environment.webGpuDevice;if(!n)throw new Error("No WebGPU device is available. Does the source tensor have a WebGPU device?");const o=T().liteRtWasm,s=e.liteRtTensorBuffer,a=s.bufferType();if(a!==o.LiteRtTensorBufferType.WEB_GPU_BUFFER_PACKED)throw new Error(`Cannot convert a tensor with a non-WebGPU buffer type ${a} to a CPU tensor.`);const i=o.WebGPU.getJsObject(s.getWebGpuBuffer()),u=s.offset(),l=s.tensorType(),p=l.layout(),f=p.numElements(),h=P(l.elementType().value).typedArrayConstructor;p.delete(),l.delete();let d=i,R=()=>{};if(!(i.usage&GPUBufferUsage.MAP_READ)){d=n.createBuffer({size:i.size,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ}),R=()=>{d.destroy()};const D=n.createCommandEncoder();D.copyBufferToBuffer(i,0,d,0,i.size),n.queue.submit([D.finish()])}await d.mapAsync(GPUMapMode.READ);const m=d.getMappedRange(),v=new h(m,u,f),w=new S(v,e.type.layout.dimensions,r);return d.unmap(),R(),w}function F(e){return async(t,r)=>{const n=await e(t,r);return t.delete(),n}}function Ie(){S.copyFunctions.set(g.HOST_MEMORY,new Map([[g.HOST_MEMORY,{copyTo:Y,moveTo:F(Y)}],[g.WEB_GPU_BUFFER_PACKED,{copyTo:q,moveTo:F(q)}]])),S.copyFunctions.set(g.WEB_GPU_BUFFER_PACKED,new Map([[g.HOST_MEMORY,{copyTo:J,moveTo:F(J)}]]))}Ie();export{ee as CompiledModel,N as Environment,We as LiteRt,le as LiteRtNotLoadedError,S as Tensor,g as TensorBufferType,$e as getDefaultEnvironment,T as getGlobalLiteRt,fe as getGlobalLiteRtPromise,je as getWebGpuDevice,ke as isWebGPUSupported,xe as loadAndCompile,He as loadLiteRt,qe as loadModelAndWeights,ze as setWebGpuDevice,Me as supportsFeature,Ye as unloadLiteRt};
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.