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(indices[${ot}])`);let gt=d<2?"":` + fn i2o_${n}(indices: ${v.indices}) -> u32 { + return ${Ie.join("+")}; + }`,ut=ot=>(te.indicesToOffset=!0,d<2?ot:`i2o_${n}(${ot})`),vt=(...ot)=>d===0?"0u":`${v.indices}(${ot.map(oe).join(",")})`,Dt=(ot,Vt)=>d<2?`${ot}`:`${zt(ot,Vt,d)}`,Rt=(ot,Vt,nr)=>d<2?`${ot}=${nr};`:`${zt(ot,Vt,d)}=${nr};`,gr={},Mr=(ot,Vt)=>{te.broadcastedIndicesToOffset=!0;let nr=`${Vt.name}broadcastedIndicesTo${n}Offset`;if(nr in gr)return`${nr}(${ot})`;let Wr=[];for(let pn=d-1;pn>=0;pn--){let kn=Vt.indicesGet("outputIndices",pn+Vt.rank-d);Wr.push(`${Dt(be,pn)} * (${kn} % ${Dt(we,pn)})`)}return gr[nr]=`fn ${nr}(outputIndices: ${Vt.type.indices}) -> u32 { + return ${Wr.length>0?Wr.join("+"):"0u"}; + }`,`${nr}(${ot})`},ir=(ot,Vt)=>(()=>{if(v.storage===v.value)return`${n}[${ot}]=${Vt};`;if(v.storage==="vec2"&&v.value==="i32")return`${n}[${ot}]=vec2(u32(${Vt}), select(0u, 0xFFFFFFFFu, ${Vt} < 0));`;if(v.storage==="vec2"&&v.value==="u32")return`${n}[${ot}]=vec2(u32(${Vt}), 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}`})(),Hr=(...ot)=>{if(ot.length!==d)throw new Error(`indices length must be ${d}`);let Vt=ot.map(oe).join(",");return d===0?Fr("0u"):d===1?Fr(Vt[0]):(te.get=!0,te.getByIndices=!0,te.indicesToOffset=!0,`get_${n}(${Vt})`)},Nt=ot=>d<2?Fr(ot):(te.getByIndices=!0,te.indicesToOffset=!0,`get_${n}ByIndices(${ot})`),er=d<2?"":` + fn set_${n}ByIndices(indices: ${v.indices}, value: ${H}) { + ${ir(`i2o_${n}(indices)`,"value")} + }`,yr=d<2?"":(()=>{let ot=x.map(nr=>`d${nr}: u32`).join(", "),Vt=x.map(nr=>`d${nr}`).join(", ");return` + fn set_${n}(${ot}, value: ${H}) { + set_${n}ByIndices(${vt(Vt)}, value); + }`})();return{impl:()=>{let ot=[],Vt=!1;return te.offsetToIndices&&(ot.push(De),Vt=!0),te.indicesToOffset&&(ot.push(gt),Vt=!0),te.broadcastedIndicesToOffset&&(Object.values(gr).forEach(nr=>ot.push(nr)),Vt=!0),te.set&&(ot.push(yr),Vt=!0),te.setByIndices&&(ot.push(er),Vt=!0),te.get&&(ot.push(hr),Vt=!0),te.getByIndices&&(ot.push(Zr),Vt=!0),!f&&Vt&&ot.unshift(`const ${we} = 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[${i}, ${s}, ${u}] exceeds the maximum workgroup invocations ${this.limits.maxComputeInvocationsPerWorkgroup}.`);let c=this.normalizedDispatchGroup[1]===1&&this.normalizedDispatchGroup[2]===1,f=c?`@builtin(global_invocation_id) global_id : vec3, + @builtin(workgroup_id) workgroup_id : vec3, + @builtin(local_invocation_id) local_id : vec3`:`@builtin(global_invocation_id) global_id : vec3, + @builtin(local_invocation_id) local_id : vec3, + @builtin(local_invocation_index) local_idx : u32, + @builtin(workgroup_id) workgroup_id : vec3, + @builtin(num_workgroups) num_workgroups : vec3`,d=c?"let global_idx = global_id.x; let local_idx = local_id.x;":`let global_idx = (workgroup_id.z * num_workgroups[0] * num_workgroups[1] + + workgroup_id.y * num_workgroups[0] + workgroup_id.x) * ${i*s*u}u + local_idx;`;return`@compute @workgroup_size(${i}, ${s}, ${u}) + fn main(${f}) { + ${d} + `}appendVariableUniforms(n){n.rank!==0&&(n.shape.startsWith("uniforms.")&&this.uniforms.push({name:n.shape.replace("uniforms.",""),type:"u32",length:n.rank}),n.strides.startsWith("uniforms.")&&this.uniforms.push({name:n.strides.replace("uniforms.",""),type:"u32",length:n.rank}))}declareVariable(n,i){if(n.usage==="internal")throw new Error("cannot use internal variable with declareVariable(). use registerInternalVariables() instead.");this.variables.push(n),this.appendVariableUniforms(n);let s=n.usage==="input"?"read":"read_write",u=n.type.storage;return`@group(0) @binding(${i}) var ${n.name}: array<${u}>;`}declareVariables(...n){return n.map(i=>this.declareVariable(i,this.variableIndex++)).join(` +`)}registerInternalVariable(n){if(n.usage!=="internal")throw new Error("cannot use input or output variable with registerInternalVariable(). use declareVariables() instead.");this.internalVariables.push(n),this.appendVariableUniforms(n)}registerInternalVariables(...n){return 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c=0;c1&&d===1&&u.unshift(f)}return u}}),du,_a,Ho,pu,hi,fu,wa,yo=h(()=>{Zt(),Jt(),_r(),ar(),du=n=>{if(!n||n.length!==1)throw new Error("Transpose requires 1 input.")},_a=(n,i)=>i&&i.length!==n?[...new Array(n).keys()].reverse():i,Ho=(n,i)=>ct.sortBasedOnPerm(n,_a(n.length,i)),pu=(n,i,s,u)=>{let c=[];c.push(`fn perm(i: ${u.type.indices}) -> ${s.type.indices} { + var a: ${s.type.indices};`);for(let f=0;f{let s=n.dataType,u=n.dims.length,c=_a(u,i),f=Ho(n.dims,c),d=Gt("output",s,f.length),x=_t("a",s,u),k;if(c.length===2&&c[0]===1&&c[1]===0){let $=d.type.value,H=[16,16,1];k=q=>` + ${q.registerUniform("output_size","u32").declareVariables(x,d)} + var tile : array, ${H[0]}>; + ${q.mainStart(H)} + var x = workgroup_id.x * ${H[0]}u + local_id.x; + var y = workgroup_id.y * ${H[0]}u + local_id.y; + let width = uniforms.output_shape[0]; + let height = uniforms.output_shape[1]; + if (x < width && y < height) { + tile[local_id.y][local_id.x] = ${x.getByOffset("y * width + x")}; + } + workgroupBarrier(); + x = workgroup_id.y * ${H[0]}u + local_id.x; + y = workgroup_id.x * ${H[0]}u + local_id.y; + if (x < height && y < width) { + ${d.setByOffset("y * height + x","tile[local_id.x][local_id.y]")} + } + }`}else k=$=>` + ${$.registerUniform("output_size","u32").declareVariables(x,d)} + + ${pu(c,u,x,d)} + + ${$.mainStart()} + ${$.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + + let indices = ${d.offsetToIndices("global_idx")}; + let aIndices = perm(indices); + + ${d.setByOffset("global_idx",x.getByIndices("aIndices"))} + }`;return{name:"Transpose",shaderCache:{hint:`${i}`,inputDependencies:["rank"]},getRunData:$=>{let H=ct.size(f);return{outputs:[{dims:f,dataType:$[0].dataType}],dispatchGroup:{x:Math.ceil(H/64)},programUniforms:[{type:12,data:H},...At($[0].dims,f)]}},getShaderSource:k}},fu=(n,i)=>{du(n.inputs),n.compute(hi(n.inputs[0],i.perm))},wa=n=>qt({perm:n.perm})}),hu,mu,gu,_u,ya,wu,yu,va,vu,bu,Xn,xu,Mu,ba,Tu,ku,xa,Su,Eu,Ma,Cu,rf=h(()=>{Zt(),Jt(),ar(),$a(),yo(),hu={max:"select(bestValue, candidate, candidate > bestValue)",min:"select(bestValue, candidate, candidate < bestValue)",mean:"bestValue + candidate",sum:"bestValue + candidate",prod:"bestValue * candidate",sumSquare:"bestValue + candidate * candidate",logSumExp:"bestValue + exp(candidate)",l1:"bestValue + abs(candidate)",l2:"bestValue + candidate * candidate",logSum:"bestValue + candidate"},mu={max:"select(bestValue, candidate, candidate > bestValue)",min:"select(bestValue, candidate, candidate < bestValue)",mean:"bestValue + candidate",sum:"bestValue + candidate",prod:"bestValue * candidate",sumSquare:"bestValue + candidate",logSumExp:"bestValue + candidate",l1:"bestValue + candidate",l2:"bestValue + candidate",logSum:"bestValue + candidate"},gu={max:"_A[offset]",min:"_A[offset]",mean:"0",sum:"0",prod:"1",sumSquare:"0",logSumExp:"0",l1:"0",l2:"0",logSum:"0"},_u={max:"bestValue",min:"bestValue",sum:"bestValue",prod:"bestValue",sumSquare:"bestValue",logSumExp:"log(bestValue)",l1:"bestValue",l2:"sqrt(bestValue)",logSum:"log(bestValue)"},ya=(n,i)=>{let s=[];for(let u=i-n;u{let s=[],u=n.length;for(let f=0;fn[f]);return[s,c]},yu=(n,i)=>{let s=n.length+i.length,u=[],c=0;for(let f=0;f{for(let s=0;s{let s=[];if(!va(n,i)){for(let u=0;us.push(u))}return s},bu=(n,i,s,u,c,f,d)=>{let x=s[0].dims,k=ct.size(f),$=ct.size(d),H=_t("_A",s[0].dataType,x),q=Gt("output",c,f),v=32,oe=` + var aBestValues : array; + `;return{name:n,shaderCache:i,getShaderSource:te=>` + ${te.registerUniform("reduceSize","u32").declareVariables(H,q)} + ${oe} + fn DIV_CEIL(a : u32, b : u32) -> u32 { + return ((a - 1u) / b + 1u); + } + ${te.mainStart(v)} + + let outputIndex = global_idx / ${v}; + let offset = outputIndex * uniforms.reduceSize; + + var bestValue = f32(${gu[u]}); + let Length = uniforms.reduceSize; + for (var k = local_idx; k < Length; k = k + ${v}) { + let candidate = f32(${H.getByOffset("offset + k")}); + bestValue = ${hu[u]}; + } + aBestValues[local_idx] = bestValue; + workgroupBarrier(); + + var reduceSize = min(Length, ${v}u); + for (var currentSize = reduceSize / 2u; reduceSize > 1u; + currentSize = reduceSize / 2u) { + let interval = DIV_CEIL(reduceSize, 2u); + if (local_idx < currentSize) { + let candidate = aBestValues[local_idx + interval]; + bestValue = ${mu[u]}; + aBestValues[local_idx] = bestValue; + } + reduceSize = interval; + workgroupBarrier(); + } + + if (local_idx == 0u) { + ${q.setByOffset("outputIndex",`${u==="mean"?`${q.type.storage}(bestValue / f32(uniforms.reduceSize))`:`${q.type.storage}(${_u[u]})`}`)}; + } + }`,getRunData:()=>({outputs:[{dims:f,dataType:c}],dispatchGroup:{x:k},programUniforms:[{type:12,data:$}]})}},Xn=(n,i,s,u)=>{let c=n.inputs.length===1?s:Is(n.inputs,s),f=c.axes;f.length===0&&!c.noopWithEmptyAxes&&(f=n.inputs[0].dims.map((oe,te)=>te));let d=ct.normalizeAxes(f,n.inputs[0].dims.length),x=d,k=n.inputs[0],$=vu(x,n.inputs[0].dims.length);$.length>0&&(k=n.compute(hi(n.inputs[0],$),{inputs:[0],outputs:[-1]})[0],x=ya(x.length,k.dims.length));let[H,q]=wu(k.dims,x),v=H;c.keepDims&&(v=yu(H,d)),n.compute(bu(i,{hint:c.cacheKey,inputDependencies:["type"]},[k],u,n.inputs[0].dataType,v,q),{inputs:[k]})},xu=(n,i)=>{Xn(n,"ReduceMeanShared",i,"mean")},Mu=(n,i)=>{Xn(n,"ReduceL1Shared",i,"l1")},ba=(n,i)=>{Xn(n,"ReduceL2Shared",i,"l2")},Tu=(n,i)=>{Xn(n,"ReduceLogSumExpShared",i,"logSumExp")},ku=(n,i)=>{Xn(n,"ReduceMaxShared",i,"max")},xa=(n,i)=>{Xn(n,"ReduceMinShared",i,"min")},Su=(n,i)=>{Xn(n,"ReduceProdShared",i,"prod")},Eu=(n,i)=>{Xn(n,"ReduceSumShared",i,"sum")},Ma=(n,i)=>{Xn(n,"ReduceSumSquareShared",i,"sumSquare")},Cu=(n,i)=>{Xn(n,"ReduceLogSumShared",i,"logSum")}}),Qn,Pu,As,Is,ii,$u,Ta,Au,Iu,ka,Fu,Ou,Sa,zu,Du,Yn,Lu,Ru,Ea,Bu,Nu,Ca,ju,Uu,Pa,Vu,$a=h(()=>{Zt(),Jt(),_r(),ar(),rf(),Qn=n=>{if(!n||n.length===0||n.length>2)throw new Error("Reduce op requires 1 or 2 inputs.");if(n.length===2&&n[1].dims.length!==1)throw new Error("Invalid axes input dims.")},Pu=n=>["","",`var value = ${n.getByIndices("input_indices")};`,""],As=(n,i,s,u,c,f,d=!1,x=!1)=>{let k=[],$=s[0].dims,H=$.length,q=ct.normalizeAxes(c,H),v=!x&&q.length===0;$.forEach((de,we)=>{v||q.indexOf(we)>=0?d&&k.push(1):k.push(de)});let oe=k.length,te=ct.size(k);return{name:n,shaderCache:i,getShaderSource:de=>{let we=[],be=_t("_A",s[0].dataType,H),he=Gt("output",f,oe),De=u(be,he,q),Ae=De[2];for(let Ie=0,gt=0;Ie=0?(d&>++,Ae=`for(var j${Ie}: u32 = 0; j${Ie} < ${$[Ie]}; j${Ie}++) { + ${De[2].includes("last_index")?`let last_index = j${Ie};`:""} + ${be.indicesSet("input_indices",Ie,`j${Ie}`)} + ${Ae} + }`):(we.push(`${be.indicesSet("input_indices",Ie,he.indicesGet("output_indices",gt))};`),gt++);return` + + ${de.registerUniform("output_size","u32").declareVariables(be,he)} + + ${de.mainStart()} + ${de.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + var input_indices: ${be.type.indices}; + let output_indices = ${he.offsetToIndices("global_idx")}; + + ${we.join(` +`)} + ${De[0]} // init ops for reduce max/min + ${De[1]} + ${Ae} + ${De[3]} + ${De.length===4?he.setByOffset("global_idx","value"):De.slice(4).join(` +`)} + }`},getRunData:()=>({outputs:[{dims:k,dataType:f}],dispatchGroup:{x:Math.ceil(te/64)},programUniforms:[{type:12,data:te},...At($,k)]})}},Is=(n,i)=>{let s=[];return n[1].dims[0]>0&&n[1].getBigInt64Array().forEach(u=>s.push(Number(u))),qt({axes:s,keepDims:i.keepDims,noopWithEmptyAxes:i.noopWithEmptyAxes})},ii=(n,i,s,u)=>{let c=n.inputs,f=c.length===1?s:Is(c,s);n.compute(As(i,{hint:f.cacheKey,inputDependencies:["rank"]},[c[0]],f.noopWithEmptyAxes&&f.axes.length===0?Pu:u,f.axes,c[0].dataType,f.keepDims,f.noopWithEmptyAxes),{inputs:[0]})},$u=(n,i)=>{Qn(n.inputs),ii(n,"ReduceLogSum",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += 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f32(0);","",`sum += f32(${s.getByIndices("input_indices")});`,`let value = ${u.type.value}(sum / ${f});`]})},Ou=(n,i)=>{Qn(n.inputs),ii(n,"ReduceMin",i,(s,u,c)=>{let f=[];for(let d=0;d=0||c.length===0)&&f.push(`input_indices[${d}] = 0;`);return[`${f.join(` +`)}`,`var value = ${s.getByIndices("input_indices")};`,`value = min(value, ${s.getByIndices("input_indices")});`,""]})},Sa=(n,i)=>{Qn(n.inputs),ii(n,"ReduceProd",i,(s,u)=>[`var value = ${u.type.storage}(1);`,"",`value *= ${s.getByIndices("input_indices")};`,""])},zu=(n,i)=>{Qn(n.inputs),ii(n,"ReduceSum",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += ${s.getByIndices("input_indices")};`,""])},Du=(n,i)=>{Qn(n.inputs),ii(n,"ReduceSumSquare",i,(s,u)=>[`var t = ${u.type.value}(0); var value = ${u.type.value}(0);`,"",`t = ${s.getByIndices("input_indices")}; value += t * t;`,""])},Yn=(n,i,s)=>{if(i.length===0)return s;let u=1,c=1;for(let f=0;f1024},Lu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Fu(n,i):xu(n,i)},Ru=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Ta(n,i):Mu(n,i)},Ea=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Au(n,i):ba(n,i)},Bu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Iu(n,i):Tu(n,i)},Nu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?ka(n,i):ku(n,i)},Ca=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Ou(n,i):xa(n,i)},ju=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Sa(n,i):Su(n,i)},Uu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?zu(n,i):Eu(n,i)},Pa=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Du(n,i):Ma(n,i)},Vu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?$u(n,i):Cu(n,i)}}),Fs,Wu,Gu,Os,nf=h(()=>{Zt(),_r(),$a(),Fs=n=>{if(!n||n.length===0||n.length>2)throw new Error("ArgMinMaxOp op requires 1 or 2 inputs.");if(n[0].dataType!==1)throw new Error("Invalid input type.")},Wu=(n,i)=>{Fs(n.inputs);let s=(u,c,f)=>{let d=[];for(let x=0;x=0||f.length===0)&&d.push(`input_indices[${x}] = 0;`);return[`${d.join(` +`)}`,`var value = ${u.getByIndices("input_indices")}; +var best_index : i32 = 0;`,`if (${u.getByIndices("input_indices")} ${i.selectLastIndex>0?"<=":"<"} value) { + value = ${u.getByIndices("input_indices")}; + best_index = i32(last_index); + }`,"",c.setByOffset("global_idx","best_index")]};n.compute(As("ArgMin",{hint:i.cacheKey,inputDependencies:["rank"]},[n.inputs[0]],s,[i.axis],7,i.keepDims),{inputs:[0]})},Gu=(n,i)=>{Fs(n.inputs);let s=(u,c,f)=>{let d=[];for(let x=0;x=0||f.length===0)&&d.push(`input_indices[${x}] = 0;`);return[`${d.join(` +`)}`,`var value = ${u.getByIndices("input_indices")}; +var best_index : i32 = 0;`,`if (${u.getByIndices("input_indices")} ${i.selectLastIndex>0?">=":">"} value) { + value = ${u.getByIndices("input_indices")}; + best_index = i32(last_index); + }`,"",c.setByOffset("global_idx","best_index")]};n.compute(As("argMax",{hint:i.cacheKey,inputDependencies:["rank"]},[n.inputs[0]],s,[i.axis],7,i.keepDims),{inputs:[0]})},Os=n=>qt(n)}),Hu,Aa,qu,Ku,vo,Xu,Qu,zs=h(()=>{Zt(),pe(),ar(),Hu=(n,i)=>{let s=n[0],u=n[1],c=n[2],f=n[3],d=n[4],x=n[5];if(d&&x)throw new Error("Attention cannot have both past and relative_position_bias");if(s.dims.length!==3)throw new Error('Input "input" must have 3 dimensions');let k=s.dims[0],$=s.dims[1],H=s.dims[2];if(c.dims.length!==1)throw new Error('Input "bias" is expected to have 1 dimensions');if(u.dims.length!==2)throw new Error('Input "weights" is expected to have 2 dimensions');if(u.dims[0]!==H)throw new Error("Input 1 dimension 0 should have same length as dimension 2 of input 0");if(c.dims[0]!==u.dims[1])throw new Error('Input "bias" dimension 0 should have same length as dimension 1 of input "weights"');let q=c.dims[0]/3,v=q,oe=v;if(i.qkvHiddenSizes.length>0){if(i.qkvHiddenSizes.length!==3)throw new Error("qkv_hidden_sizes attribute should have 3 elements");for(let De of i.qkvHiddenSizes)if(De%i.numHeads!==0)throw new Error("qkv_hidden_sizes should be divisible by num_heads");q=i.qkvHiddenSizes[0],v=i.qkvHiddenSizes[1],oe=i.qkvHiddenSizes[2]}let te=$;if(q!==v)throw new Error("qkv_hidden_sizes first element should be same as the second");if(c.dims[0]!==q+v+oe)throw new Error('Input "bias" dimension 0 should have same length as sum of Q/K/V hidden sizes');let de=0;if(d){if(v!==oe)throw new Error('Input "past" expect k_hidden_size == v_hidden_size');if(d.dims.length!==5)throw new Error('Input "past" must have 5 dimensions');if(d.dims[0]!==2)throw new Error('Input "past" first dimension must be 2');if(d.dims[1]!==k)throw new Error('Input "past" second dimension must be batch_size');if(d.dims[2]!==i.numHeads)throw new Error('Input "past" third dimension must be num_heads');if(d.dims[4]!==v/i.numHeads)throw new Error('Input "past" fifth dimension must be k_hidden_size / num_heads');i.pastPresentShareBuffer||(de=d.dims[3])}let we=te+de,be=-1,he=0;if(f)throw new Error("Mask not supported");if(d)throw new Error("past is not supported");return{batchSize:k,sequenceLength:$,pastSequenceLength:de,kvSequenceLength:te,totalSequenceLength:we,maxSequenceLength:be,inputHiddenSize:H,hiddenSize:q,vHiddenSize:oe,headSize:Math.floor(q/i.numHeads),vHeadSize:Math.floor(oe/i.numHeads),numHeads:i.numHeads,isUnidirectional:!1,pastPresentShareBuffer:!1,maskFilterValue:i.maskFilterValue,maskType:he,scale:i.scale,broadcastResPosBias:!1,passPastInKv:!1,qkvFormat:1}},Aa=(n,i,s,u)=>{let c=vr(u),f=64,d=u/c;d{let oe=Gt("x",i.dataType,i.dims,c),te=[{name:"d_inv",type:Er(i.dataType)},{name:"d_comp",type:"u32"},{name:"elements_per_thread",type:"u32"}];return` + var thread_max: array; + var thread_sum: array; + ${v.registerUniforms(te).declareVariables(oe)} + ${v.mainStart([f,1,1])} + let local_offset = local_idx * uniforms.elements_per_thread; + let offset = workgroup_id.x * uniforms.d_comp + local_offset; + + var thread_max_vector = ${H}(-3.402823e+38f); + for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) { + thread_max_vector = max(${H}(x[offset + i]), thread_max_vector); + } + thread_max[local_idx] = ${(()=>{switch(c){case 1:return"thread_max_vector";case 2:return"max(thread_max_vector.x, thread_max_vector.y)";case 4:return"max(max(thread_max_vector.x, thread_max_vector.y), max(thread_max_vector.z, thread_max_vector.w))";default:throw new Error(`Unsupported components: ${c}`)}})()}; + workgroupBarrier(); + + var max_value = f32(-3.402823e+38f); + for (var i = 0u; i < ${f}; i++) { + max_value = max(thread_max[i], max_value); + } + + var sum_vector = ${H}(0); + for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) { + sum_vector += exp(${H}(x[offset + i]) - max_value); + } + thread_sum[local_idx] = ${(()=>{switch(c){case 1:return"sum_vector";case 2:return"sum_vector.x + sum_vector.y";case 4:return"sum_vector.x + sum_vector.y + sum_vector.z + sum_vector.w";default:throw new Error(`Unsupported components: ${c}`)}})()}; + workgroupBarrier(); + + var sum: f32 = 0; + for (var i = 0u; i < ${f}; i++) { + sum += thread_sum[i]; + } + + if (sum == 0) { + for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) { + x[offset + i] = ${oe.type.value}(uniforms.d_inv); + } + } else { + for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) { + var f32input = ${H}(x[offset + i]); + x[offset + i] = ${oe.type.value}(exp(f32input - max_value) / sum); + } + } + }`};return{name:"AttentionProbsSoftmax",shaderCache:{hint:`${f};${$};${c}`},getShaderSource:q,getRunData:()=>({outputs:[],dispatchGroup:{x:s},programUniforms:k})}},qu=(n,i,s,u,c,f,d,x)=>{let k=x+f.kvSequenceLength,$=[f.batchSize,f.numHeads,f.sequenceLength,k],H=f.kvNumHeads===void 0&&n.outputCount>1,q=H?[f.batchSize,f.numHeads,k,f.headSize]:void 0,v=d.scale===0?1/Math.sqrt(f.headSize):d.scale,oe=vr(f.headSize),te=f.headSize/oe,de=12,we={x:Math.ceil(k/de),y:Math.ceil(f.sequenceLength/de),z:f.batchSize*f.numHeads},be=[{type:12,data:f.sequenceLength},{type:12,data:te},{type:12,data:k},{type:12,data:f.numHeads},{type:1,data:v},{type:12,data:x},{type:12,data:f.kvSequenceLength}],he=["type","type"];u&&he.push("type"),c&&he.push("type");let De=[{dims:$,dataType:i.dataType,gpuDataType:0}];H&&De.push({dims:q,dataType:i.dataType,gpuDataType:0});let Ae=Ie=>{let gt=_t("q",i.dataType,i.dims,oe),ut=_t("key",s.dataType,s.dims,oe),vt=[gt,ut];if(u){let ir=_t("past_key",u.dataType,u.dims,oe);vt.push(ir)}c&&vt.push(_t("relative_position_bias",c.dataType,c.dims));let Dt=Gt("output",i.dataType,$),Rt=[Dt];H&&Rt.push(Gt("present_key",i.dataType,q,oe));let gr=Er(1,oe),Mr=[{name:"M",type:"u32"},{name:"K",type:"u32"},{name:"N",type:"u32"},{name:"num_heads",type:"u32"},{name:"alpha",type:"f32"},{name:"past_sequence_length",type:"u32"},{name:"kv_sequence_length",type:"u32"}];return` + const TILE_SIZE = ${de}u; + + var tileQ: array<${gt.type.storage}, ${de*de}>; + var tileK: array<${gt.type.storage}, ${de*de}>; + ${Ie.registerUniforms(Mr).declareVariables(...vt,...Rt)} + ${Ie.mainStart([de,de,1])} + // x holds the N and y holds the M + let headIdx = workgroup_id.z; + let m = workgroup_id.y * TILE_SIZE; + let n = workgroup_id.x * TILE_SIZE; + let qOffset = uniforms.M * uniforms.K * headIdx + m * uniforms.K; + ${u&&H?` + let kOffset = uniforms.kv_sequence_length * uniforms.K * headIdx; + let pastKeyOffset = uniforms.past_sequence_length * uniforms.K * headIdx;`:` + let kOffset = uniforms.N * uniforms.K * headIdx + n * uniforms.K;`} + ${H?"let presentKeyOffset = headIdx * uniforms.N * uniforms.K;":""} + var value = ${gr}(0); + for (var w: u32 = 0u; w < uniforms.K; w += TILE_SIZE) { + if (global_id.y < uniforms.M && w + local_id.x < uniforms.K) { + tileQ[TILE_SIZE * local_id.y + local_id.x] = q[qOffset + local_id.y * uniforms.K + w + local_id.x]; + } + if (n + local_id.y < uniforms.N && w + local_id.x < uniforms.K) { + var idx = TILE_SIZE * local_id.y + local_id.x; + ${u&&H?` + if (n + local_id.y < uniforms.past_sequence_length) { + tileK[idx] = past_key[pastKeyOffset + (n + local_id.y) * uniforms.K + w + local_id.x]; + } else { + tileK[idx] = + key[kOffset + (n + local_id.y - uniforms.past_sequence_length) * uniforms.K + w + local_id.x]; + }`:"tileK[idx] = key[kOffset + local_id.y * uniforms.K + w + local_id.x];"} + ${H?"present_key[presentKeyOffset + (n + local_id.y) * uniforms.K + w + local_id.x] = tileK[idx];":""} + } + workgroupBarrier(); + + for (var k: u32 = 0u; k < TILE_SIZE && w+k < uniforms.K; k++) { + value += ${gr}(tileQ[TILE_SIZE * local_id.y + k] * tileK[TILE_SIZE * local_id.x + k]); + } + + workgroupBarrier(); + } + + let headOffset = headIdx * uniforms.M * uniforms.N; + if (global_id.y < uniforms.M && global_id.x < uniforms.N) { + let outputIdx = headOffset + global_id.y * uniforms.N + global_id.x; + var sum: f32 = ${(()=>{switch(oe){case 1:return"value";case 2:return"value.x + value.y";case 4:return"value.x + value.y + value.z + value.w";default:throw new Error(`Unsupported components: ${oe}`)}})()}; + output[outputIdx] = ${Dt.type.value} (sum * uniforms.alpha) + ${c?"relative_position_bias[outputIdx]":"0.0"}; + } + }`};return{name:"AttentionProbs",shaderCache:{hint:`${oe};${c!==void 0};${u!==void 0};${n.outputCount}`,inputDependencies:he},getRunData:()=>({outputs:De,dispatchGroup:we,programUniforms:be}),getShaderSource:Ae}},Ku=(n,i,s,u,c,f)=>{let d=f+c.kvSequenceLength,x=c.nReps?c.nReps:1,k=c.vHiddenSize*x,$=c.kvNumHeads==null&&n.outputCount>1,H=$?[c.batchSize,c.numHeads,d,c.headSize]:void 0,q=[c.batchSize,c.sequenceLength,k],v=12,oe={x:Math.ceil(c.vHeadSize/v),y:Math.ceil(c.sequenceLength/v),z:c.batchSize*c.numHeads},te=[{type:12,data:c.sequenceLength},{type:12,data:d},{type:12,data:c.vHeadSize},{type:12,data:c.numHeads},{type:12,data:k},{type:12,data:f},{type:12,data:c.kvSequenceLength}],de=u?["type","type","type"]:["type","type"],we=[{dims:q,dataType:i.dataType,gpuDataType:0}];$&&we.push({dims:H,dataType:i.dataType,gpuDataType:0});let be=he=>{let De=_t("probs",i.dataType,i.dims),Ae=_t("v",s.dataType,s.dims),Ie=[De,Ae];u&&Ie.push(_t("past_value",u.dataType,u.dims));let gt=[Gt("output",i.dataType,q)];$&>.push(Gt("present_value",i.dataType,H));let ut=[{name:"M",type:"u32"},{name:"K",type:"u32"},{name:"N",type:"u32"},{name:"num_heads",type:"u32"},{name:"v_hidden_size",type:"u32"},{name:"past_sequence_length",type:"u32"},{name:"kv_sequence_length",type:"u32"}];return` + const TILE_SIZE = ${v}u; + var tileQ: array<${De.type.value}, ${v*v}>; + var tileK: array<${De.type.value}, ${v*v}>; + ${he.registerUniforms(ut).declareVariables(...Ie,...gt)} + ${he.mainStart([v,v,1])} + let headIdx = workgroup_id.z; + let m = global_id.y; + let n = global_id.x; + + let offsetA = headIdx * (uniforms.M * uniforms.K) + m * uniforms.K; + ${u&&$?` + let pastValueOffset = headIdx * uniforms.N * uniforms.past_sequence_length + n; + let vOffset = headIdx * uniforms.N * uniforms.kv_sequence_length + n; + `:` + let offsetB = headIdx * uniforms.N * uniforms.K + n; + `} + ${$?"let presentValueOffset = headIdx * uniforms.N * uniforms.K + n;":""} + var value = ${De.type.storage}(0); + for (var w: u32 = 0u; w < uniforms.K; w += TILE_SIZE) { + if (m < uniforms.M && w + local_id.x < uniforms.K) { + tileQ[TILE_SIZE * local_id.y + local_id.x] = probs[offsetA + w + local_id.x]; + } + if (n < uniforms.N && w + local_id.y < uniforms.K) { + var idx = TILE_SIZE * local_id.y + local_id.x; + ${u&&$?` + if (w + local_id.y < uniforms.past_sequence_length) { + tileK[idx] = past_value[pastValueOffset + (w + local_id.y) * uniforms.N]; + } else { + tileK[idx] = v[vOffset + (w + local_id.y - uniforms.past_sequence_length) * uniforms.N]; + } + `:` + tileK[idx] = v[offsetB + (w + local_id.y) * uniforms.N]; + `} + ${$?"present_value[presentValueOffset + (w + local_id.y) * uniforms.N] = tileK[idx];":""} + } + workgroupBarrier(); + for (var k: u32 = 0u; k < TILE_SIZE && w+k < uniforms.K; k++) { + value += tileQ[TILE_SIZE * local_id.y + k] * tileK[TILE_SIZE * k + local_id.x]; + } + workgroupBarrier(); + } + + // we need to transpose output from BNSH_v to BSND_v + let batchIdx = workgroup_id.z / uniforms.num_heads; + let currentBatchHeadNumber = workgroup_id.z % uniforms.num_heads; + if (m < uniforms.M && n < uniforms.N) { + let outputIdx = batchIdx * uniforms.M * uniforms.v_hidden_size + m * uniforms.v_hidden_size + + currentBatchHeadNumber * uniforms.N + n; + output[outputIdx] = value; + } + }`};return{name:"AttentionScore",shaderCache:{hint:`${u!==void 0};${n.outputCount}`,inputDependencies:de},getRunData:()=>({outputs:we,dispatchGroup:oe,programUniforms:te}),getShaderSource:be}},vo=(n,i,s,u,c,f,d,x,k,$,H)=>{let q=n.outputCount,v=$.kvNumHeads!==void 0||q>1?$.pastSequenceLength:0,oe=v+$.kvSequenceLength,te=$.kvNumHeads===void 0&&q>1&&d?[i,s,d]:[i,s];k&&te.push(k);let de=n.compute(qu(n,i,s,q>1?d:void 0,k,$,H,v),{inputs:te,outputs:$.kvNumHeads===void 0&&q>1?[-1,1]:[-1]})[0];n.compute(Aa(n,de,$.batchSize*$.numHeads*$.sequenceLength,oe),{inputs:[de],outputs:[]});let we=$.kvNumHeads===void 0&&q>1&&x?[de,u,x]:[de,u];n.compute(Ku(n,de,u,q>1&&x?x:void 0,$,v),{inputs:we,outputs:$.kvNumHeads===void 0&&q>1?[0,2]:[0]})},Xu=(n,i)=>{let s=[i.batchSize,i.numHeads,i.sequenceLength,i.headSize],u=i.sequenceLength,c=i.inputHiddenSize,f=i.headSize,d=12,x={x:Math.ceil(i.headSize/d),y:Math.ceil(i.sequenceLength/d),z:i.batchSize*i.numHeads},k=[n.inputs[0],n.inputs[1],n.inputs[2]],$=[{type:12,data:u},{type:12,data:c},{type:12,data:f},{type:12,data:i.numHeads},{type:12,data:i.headSize},{type:12,data:i.hiddenSize},{type:12,data:i.hiddenSize+i.hiddenSize+i.vHiddenSize}],H=q=>{let v=Gt("output_q",k[0].dataType,s),oe=Gt("output_k",k[0].dataType,s),te=Gt("output_v",k[0].dataType,s),de=_t("input",k[0].dataType,k[0].dims),we=_t("weight",k[1].dataType,k[1].dims),be=_t("bias",k[2].dataType,k[2].dims),he=de.type.storage,De=[{name:"M",type:"u32"},{name:"K",type:"u32"},{name:"N",type:"u32"},{name:"num_heads",type:"u32"},{name:"head_size",type:"u32"},{name:"hidden_size",type:"u32"},{name:"ldb",type:"u32"}];return` + const TILE_SIZE = ${d}u; + var tileInput: array<${he}, ${d*d}>; + var tileWeightQ: array<${he}, ${d*d}>; + var tileWeightK: array<${he}, ${d*d}>; + var tileWeightV: array<${he}, ${d*d}>; + ${q.registerUniforms(De).declareVariables(de,we,be,v,oe,te)} + ${q.mainStart([d,d,1])} + let batchIndex = workgroup_id.z / uniforms.num_heads; + let headNumber = workgroup_id.z % uniforms.num_heads; + let m = global_id.y; + let n = global_id.x; + + let inputOffset = batchIndex * (uniforms.M * uniforms.K) + m * uniforms.K; + let biasOffsetQ = headNumber * uniforms.head_size; + let biasOffsetK = uniforms.hidden_size + biasOffsetQ; + let biasOffsetV = uniforms.hidden_size + biasOffsetK; + + var valueQ = ${he}(0); + var valueK = ${he}(0); + var valueV = ${he}(0); + for (var w: u32 = 0u; w < uniforms.K; w += TILE_SIZE) { + if (m < uniforms.M && w + local_id.x < uniforms.K) { + tileInput[TILE_SIZE * local_id.y + local_id.x] = input[inputOffset + w + local_id.x]; + } + if (n < uniforms.N && w + local_id.y < uniforms.K) { + let offset = n + (w + local_id.y) * uniforms.ldb; + tileWeightQ[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetQ + offset]; + tileWeightK[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetK + offset]; + tileWeightV[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetV + offset]; + } + workgroupBarrier(); + for (var k: u32 = 0u; k({outputs:[{dims:s,dataType:n.inputs[0].dataType,gpuDataType:0},{dims:s,dataType:n.inputs[0].dataType,gpuDataType:0},{dims:s,dataType:n.inputs[0].dataType,gpuDataType:0}],dispatchGroup:x,programUniforms:$}),getShaderSource:H},{inputs:k,outputs:[-1,-1,-1]})},Qu=(n,i)=>{let s=Hu(n.inputs,i),[u,c,f]=Xu(n,s);return vo(n,u,c,f,n.inputs[4],void 0,void 0,void 0,n.inputs[5],s,i)}}),Yu,Zu,Ju,ec,tc=h(()=>{Z(),Zt(),Jt(),_r(),ar(),Yu=(n,i)=>{if(!n||n.length!==5)throw new Error("BatchNormalization requires 5 inputs");let s=(u,c,f)=>{let d=c.length;if(d!==u.length)throw new Error(`${f}: num dimensions != ${d}`);c.forEach((x,k)=>{if(x!==u[k])throw new Error(`${f}: dim[${k}] do not match`)})};if(n[0].dims.length>1){let u=i.format==="NHWC"?i.spatial?n[0].dims.slice(-1):n[0].dims.slice(-1).concat(n[0].dims.slice(1,n[0].dims.length-1)):n[0].dims.slice(1,i.spatial?2:void 0);s(n[1].dims,u,"Invalid input scale"),s(n[2].dims,u,"Invalid input B"),s(n[3].dims,u,"Invalid input mean"),s(n[4].dims,u,"Invalid input var")}else s(n[1].dims,[1],"Invalid input scale"),s(n[2].dims,[1],"Invalid input B"),s(n[3].dims,[1],"Invalid input mean"),s(n[4].dims,[1],"Invalid input var")},Zu=(n,i)=>{let{epsilon:s,spatial:u,format:c}=i,f=n[0].dims,d=u?vr(f[f.length-1]):1,x=c==="NHWC"&&f.length>1?d:1,k=ct.size(f)/d,$=u,H=$?f.length:f,q=_t("x",n[0].dataType,n[0].dims,d),v=_t("scale",n[1].dataType,n[1].dims,x),oe=_t("bias",n[2].dataType,n[2].dims,x),te=_t("inputMean",n[3].dataType,n[3].dims,x),de=_t("inputVar",n[4].dataType,n[4].dims,x),we=Gt("y",n[0].dataType,H,d),be=()=>{let De="";if(u)De=`let cOffset = ${f.length===1?"0u":c==="NHWC"?`outputIndices[${f.length-1}] / ${d}`:"outputIndices[1]"};`;else if(c==="NCHW")De=` + ${we.indicesSet("outputIndices","0","0")} + let cOffset = ${we.indicesToOffset("outputIndices")};`;else{De=`var cIndices = ${v.type.indices}(0); + cIndices[0] = outputIndices[${f.length-1}];`;for(let Ae=1;Ae` + const epsilon = ${s}; + ${De.registerUniform("outputSize","u32").declareVariables(q,v,oe,te,de,we)} + ${De.mainStart()} + ${De.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + var outputIndices = ${we.offsetToIndices(`global_idx * ${d}`)}; + ${be()} + let scale = ${v.getByOffset("cOffset")}; + let bias = ${oe.getByOffset("cOffset")}; + let inputMean = ${te.getByOffset("cOffset")}; + let inputVar = ${de.getByOffset("cOffset")}; + let x = ${q.getByOffset("global_idx")}; + let value = (x - inputMean) * inverseSqrt(inputVar + epsilon) * scale + bias; + ${we.setByOffset("global_idx","value")} + }`;return{name:"BatchNormalization",shaderCache:{hint:`${i.epsilon}_${i.format}_${u}_${d}`,inputDependencies:$?["rank","type","type","type","type"]:void 0},getShaderSource:he,getRunData:()=>({outputs:[{dims:n[0].dims,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(k/64)},programUniforms:$?[{type:12,data:k},...At(f)]:[{type:12,data:k}]})}},Ju=n=>qt(n),ec=(n,i)=>{let{inputs:s,outputCount:u}=n,c=Ju({...i,outputCount:u});if(N.webgpu.validateInputContent&&Yu(s,c),i.trainingMode)throw new Error("BatchNormalization trainingMode is not supported yet.");n.compute(Zu(s,c))}}),rc,nc,Ia,of=h(()=>{Jt(),ar(),rc=n=>{if(n[0].dims.length!==3)throw new Error("input should have 3 dimensions");if(![320,640,1280].includes(n[0].dims[2]))throw new Error("number of channels should be 320, 640 or 1280");if(n[1].dims.length!==1)throw new Error("bias is expected to have 1 dimensions");if(n[0].dims[2]!==n[1].dims[0])throw new Error("last dimension of input and bias are not the same")},nc=n=>{let i=n[0].dims,s=n[0].dims[2],u=ct.size(i)/4,c=n[0].dataType,f=_t("input",c,i,4),d=_t("bias",c,[s],4),x=_t("residual",c,i,4),k=Gt("output",c,i,4);return{name:"BiasAdd",getRunData:()=>({outputs:[{dims:i,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(u/64)}}),getShaderSource:$=>` + const channels = ${s}u / 4; + ${$.declareVariables(f,d,x,k)} + + ${$.mainStart()} + ${$.guardAgainstOutOfBoundsWorkgroupSizes(u)} + let value = ${f.getByOffset("global_idx")} + + ${d.getByOffset("global_idx % channels")} + ${x.getByOffset("global_idx")}; + ${k.setByOffset("global_idx","value")} + }`}},Ia=n=>{rc(n.inputs),n.compute(nc(n.inputs))}}),ic,br,oc,sc,Fa,ac,lc,Oa,uc,cc,Ds,dc,pc,fc,za,hc,bo,mc,Ls,gc,Da,_c,wc,yc,La,vc,bc,Ra,xc,Mc,Ba,Tc,kc,Na,Sc,ja,Ua,Va,Wa,Ec,Cc,Ga,Pc,$c,Ac,Ha=h(()=>{Zt(),Jt(),_r(),ar(),ic=(n,i,s,u,c,f)=>{let d=Math.ceil(i/4),x="";typeof c=="string"?x=`${c}(a)`:x=c("a");let k=_t("inputData",s,[d],4),$=Gt("outputData",u,[d],4);return` + ${n.registerUniform("vec_size","u32").declareVariables(k,$)} + + ${f??""} + + ${n.mainStart()} + ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")} + + let a = ${k.getByOffset("global_idx")}; + ${$.setByOffset("global_idx",x)} + }`},br=(n,i,s,u,c,f=n.dataType)=>({name:i,shaderCache:{hint:c,inputDependencies:["type"]},getShaderSource:d=>ic(d,ct.size(n.dims),n.dataType,f,s,u),getRunData:d=>({outputs:[{dims:n.dims,dataType:f}],dispatchGroup:{x:Math.ceil(ct.size(d[0].dims)/64/4)},programUniforms:[{type:12,data:Math.ceil(ct.size(n.dims)/4)}]})}),oc=n=>{n.compute(br(n.inputs[0],"Abs","abs"))},sc=n=>{n.compute(br(n.inputs[0],"Acos","acos"))},Fa=n=>{n.compute(br(n.inputs[0],"Acosh","acosh"))},ac=n=>{n.compute(br(n.inputs[0],"Asin","asin"))},lc=n=>{n.compute(br(n.inputs[0],"Asinh","asinh"))},Oa=n=>{n.compute(br(n.inputs[0],"Atan","atan"))},uc=n=>{n.compute(br(n.inputs[0],"Atanh","atanh"))},cc=n=>qt(n),Ds=(n,i)=>{let s;switch(i.to){case 10:s="vec4";break;case 1:s="vec4";break;case 12:s="vec4";break;case 6:s="vec4";break;case 9:s="vec4";break;default:throw new RangeError(`not supported type (specified in attribute 'to' from 'Cast' operator): ${i.to}`)}n.compute(br(n.inputs[0],"Cast",s,void 0,i.cacheKey,i.to))},dc=n=>{let i=n.length>=2&&n[1].data!==0?n[1].getFloat32Array()[0]:cn,s=n.length>=3&&n[2].data!==0?n[2].getFloat32Array()[0]:On;return qt({min:i,max:s})},pc=(n,i)=>{let s=n.inputs.length===1?i:dc(n.inputs),u=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Clip",c=>`clamp(${c}, clip_min_, clip_max_)`,` + const clip_min_: vec4<${u}> = vec4(${u}(${s.min})); + const clip_max_: vec4<${u}> = vec4(${u}(${s.max})); +`,s.cacheKey),{inputs:[0]})},fc=n=>{n.compute(br(n.inputs[0],"Ceil","ceil"))},za=n=>{n.compute(br(n.inputs[0],"Cos","cos"))},hc=n=>{n.compute(br(n.inputs[0],"Cosh","cosh"))},bo=n=>qt(n),mc=(n,i)=>{let s=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Elu",u=>`elu_vf32(${u})`,` + const elu_alpha_ = ${s}(${i.alpha}); + + fn elu_f32(a: ${s}) -> ${s} { + return select((exp(a) - 1.0) * elu_alpha_, a, a >= 0.0); + } + + fn elu_vf32(v: vec4<${s}>) -> vec4<${s}> { + return vec4(elu_f32(v.x), elu_f32(v.y), elu_f32(v.z), elu_f32(v.w)); + }`,i.cacheKey))},Ls=(n="f32")=>` +const r0: ${n} = 0.3275911; +const r1: ${n} = 0.254829592; +const r2: ${n} = -0.284496736; +const r3: ${n} = 1.421413741; +const r4: ${n} = -1.453152027; +const r5: ${n} = 1.061405429; + +fn erf_vf32(v: vec4<${n}>) -> vec4<${n}> { + let absv = abs(v); + let x = 1.0 / (1.0 + r0 * absv); + return sign(v) * (1.0 - ((((r5 * x + r4) * x + r3) * x + r2) * x + r1) * x * exp(-absv * absv)); +}`,gc=n=>{let i=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Erf",s=>`erf_vf32(${s})`,Ls(i)))},Da=n=>{n.compute(br(n.inputs[0],"Exp","exp"))},_c=n=>{n.compute(br(n.inputs[0],"Floor","floor"))},wc=n=>{let i=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Gelu",s=>`0.5 * ${s} * (1.0 + erf_vf32(${s} * 0.7071067811865475))`,Ls(i)))},yc=(n,i)=>{let s=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"LeakyRelu",u=>`select(leaky_relu_alpha_ * ${u}, ${u}, ${u} >= vec4<${s}>(0.0))`,`const leaky_relu_alpha_ = ${s}(${i.alpha});`,i.cacheKey))},La=n=>{n.compute(br(n.inputs[0],"Not",i=>`!${i}`))},vc=n=>{n.compute(br(n.inputs[0],"Neg",i=>`-${i}`))},bc=n=>{n.compute(br(n.inputs[0],"Reciprocal",i=>`1.0/${i}`))},Ra=n=>{let i=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Relu",s=>`select(vec4<${i}>(0.0), ${s}, ${s} > vec4<${i}>(0.0))`))},xc=n=>{n.compute(br(n.inputs[0],"Sigmoid",i=>`(1.0 / (1.0 + exp(-${i})))`))},Mc=n=>qt(n),Ba=(n,i)=>{let s=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"HardSigmoid",u=>`max(vec4<${s}>(0.0), min(vec4<${s}>(1.0), ${i.alpha} * ${u} + vec4<${s}>(${i.beta})))`,void 0,i.cacheKey))},Tc=n=>{n.compute(br(n.inputs[0],"Sin","sin"))},kc=n=>{n.compute(br(n.inputs[0],"Sinh","sinh"))},Na=n=>{n.compute(br(n.inputs[0],"Sqrt","sqrt"))},Sc=n=>{n.compute(br(n.inputs[0],"Tan","tan"))},ja=n=>`sign(${n}) * (1 - exp(-2 * abs(${n}))) / (1 + exp(-2 * abs(${n})))`,Ua=n=>{n.compute(br(n.inputs[0],"Tanh",ja))},Va=(n="f32")=>` +const fast_gelu_a: ${n} = 0.5; +const fast_gelu_b: ${n} = 0.7978845608028654; +const fast_gelu_c: ${n} = 0.035677408136300125; + +fn tanh_v(v: vec4<${n}>) -> vec4<${n}> { + return ${ja("v")}; +} +`,Wa=n=>`(fast_gelu_a + fast_gelu_a * tanh_v(${n} * (fast_gelu_c * ${n} * ${n} + fast_gelu_b))) * ${n}`,Ec=n=>{let i=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"FastGelu",Wa,Va(i),void 0,n.inputs[0].dataType))},Cc=(n,i)=>{let s=Er(n.inputs[0].dataType);return n.compute(br(n.inputs[0],"ThresholdedRelu",u=>`select(vec4<${s}>(0.0), ${u}, ${u} > thresholded_relu_alpha_)`,`const thresholded_relu_alpha_ = vec4<${s}>(${i.alpha});`,i.cacheKey)),0},Ga=n=>{n.compute(br(n.inputs[0],"Log","log"))},Pc=(n,i)=>` +const alpha = vec4<${n}>(${i}); +const one = ${n}(1.0); +const zero = ${n}(0.0); + +fn quick_gelu_impl(x: vec4<${n}>) -> vec4<${n}> { + let v = x *alpha; + var x1 : vec4<${n}>; + for (var i = 0; i < 4; i = i + 1) { + if (v[i] >= zero) { + x1[i] = one / (one + exp(-v[i])); + } else { + x1[i] = one - one / (one + exp(v[i])); + } + } + return x * x1; +} +`,$c=n=>`quick_gelu_impl(${n})`,Ac=(n,i)=>{let s=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"QuickGelu",$c,Pc(s,i.alpha),i.cacheKey,n.inputs[0].dataType))}}),qa,Ic,Fc,Oc=h(()=>{Jt(),ar(),Ha(),qa=n=>{if(n[0].dims.length!==3)throw new Error("input should have 3 dimensions");if(![2560,5120,10240].includes(n[0].dims[2]))throw new Error("hidden state should be 2560, 5120 or 10240");if(n[1].dims.length!==1)throw new Error("bias is expected to have 1 dimensions");if(n[0].dims[2]!==n[1].dims[0])throw new Error("last dimension of input and bias are not the same")},Ic=n=>{let i=n[0].dims.slice();i[2]=i[2]/2;let s=_t("input",n[0].dataType,n[0].dims,4),u=_t("bias",n[0].dataType,[n[0].dims[2]],4),c=Gt("output",n[0].dataType,i,4),f=ct.size(i)/4,d=Sr(n[0].dataType);return{name:"BiasSplitGelu",getRunData:()=>({outputs:[{dims:i,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(f/64)}}),getShaderSource:x=>` + const M_SQRT2 = sqrt(2.0); + const halfChannels = ${n[0].dims[2]/4/2}u; + + ${x.declareVariables(s,u,c)} + + ${Ls(d)} + + ${x.mainStart()} + ${x.guardAgainstOutOfBoundsWorkgroupSizes(f)} + let biasIdx = global_idx % halfChannels; + let batchIndex = global_idx / halfChannels; + let inputOffset = biasIdx + batchIndex * halfChannels * 2; + let valueLeft = input[inputOffset] + bias[biasIdx]; + let valueRight = input[inputOffset + halfChannels] + bias[biasIdx + halfChannels]; + let geluRight = valueRight * 0.5 * (erf_vf32(valueRight / M_SQRT2) + 1); + + ${c.setByOffset("global_idx","valueLeft * geluRight")} + }`}},Fc=n=>{qa(n.inputs),n.compute(Ic(n.inputs))}}),zc,Dc,Zn,Lc,Rc,Ka,Bc,Nc,jc,Uc,Vc,Wc,Xa,sf=h(()=>{Zt(),Jt(),ar(),zc=(n,i,s,u,c,f,d,x,k,$,H,q)=>{let v,oe;typeof x=="string"?v=oe=(he,De)=>`${x}((${he}),(${De}))`:typeof x=="function"?v=oe=x:(v=x.scalar,oe=x.vector);let te=Gt("outputData",H,u.length,4),de=_t("aData",k,i.length,4),we=_t("bData",$,s.length,4),be;if(c)if(f){let he=ct.size(i)===1,De=ct.size(s)===1,Ae=i.length>0&&i[i.length-1]%4===0,Ie=s.length>0&&s[s.length-1]%4===0;he||De?be=te.setByOffset("global_idx",oe(he?`${de.type.value}(${de.getByOffset("0")}.x)`:de.getByOffset("global_idx"),De?`${we.type.value}(${we.getByOffset("0")}.x)`:we.getByOffset("global_idx"))):be=` + let outputIndices = ${te.offsetToIndices("global_idx * 4u")}; + let offsetA = ${de.broadcastedIndicesToOffset("outputIndices",te)}; + let offsetB = ${we.broadcastedIndicesToOffset("outputIndices",te)}; + ${te.setByOffset("global_idx",oe(d||Ae?de.getByOffset("offsetA / 4u"):`${de.type.value}(${de.getByOffset("offsetA / 4u")}[offsetA % 4u])`,d||Ie?we.getByOffset("offsetB / 4u"):`${we.type.value}(${we.getByOffset("offsetB / 4u")}[offsetB % 4u])`))} + `}else be=te.setByOffset("global_idx",oe(de.getByOffset("global_idx"),we.getByOffset("global_idx")));else{if(!f)throw new Error("no necessary to use scalar implementation for element-wise binary op implementation.");let he=(De,Ae,Ie="")=>{let gt=`aData[indexA${Ae}][componentA${Ae}]`,ut=`bData[indexB${Ae}][componentB${Ae}]`;return` + let outputIndices${Ae} = ${te.offsetToIndices(`global_idx * 4u + ${Ae}u`)}; + let offsetA${Ae} = ${de.broadcastedIndicesToOffset(`outputIndices${Ae}`,te)}; + let offsetB${Ae} = ${we.broadcastedIndicesToOffset(`outputIndices${Ae}`,te)}; + let indexA${Ae} = offsetA${Ae} / 4u; + let indexB${Ae} = offsetB${Ae} / 4u; + let componentA${Ae} = offsetA${Ae} % 4u; + let componentB${Ae} = offsetB${Ae} % 4u; + ${De}[${Ae}] = ${Ie}(${v(gt,ut)}); + `};H===9?be=` + var data = vec4(0); + ${he("data",0,"u32")} + ${he("data",1,"u32")} + ${he("data",2,"u32")} + ${he("data",3,"u32")} + outputData[global_idx] = dot(vec4(0x1, 0x100, 0x10000, 0x1000000), vec4(data));`:be=` + ${he("outputData[global_idx]",0)} + ${he("outputData[global_idx]",1)} + ${he("outputData[global_idx]",2)} + ${he("outputData[global_idx]",3)} + `}return` + ${n.registerUniform("vec_size","u32").declareVariables(de,we,te)} + + ${q??""} + + ${n.mainStart()} + ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")} + ${be} + }`},Dc=(n,i,s,u,c,f,d=s.dataType)=>{let x=!ct.areEqual(s.dims,u.dims),k=s.dims,$=ct.size(s.dims),H=!1,q=!1,v=[x];if(x){let oe=gn.calcShape(s.dims,u.dims,!1);if(!oe)throw new Error("Can't perform binary op on the given tensors");k=oe,$=ct.size(k);let te=ct.size(s.dims)===1,de=ct.size(u.dims)===1,we=s.dims.length>0&&s.dims[s.dims.length-1]%4===0,be=u.dims.length>0&&u.dims[u.dims.length-1]%4===0;v.push(te),v.push(de),v.push(we),v.push(be);let he=1;for(let De=1;Deoe.toString()).join("_"),inputDependencies:["rank","rank"]},getShaderSource:oe=>zc(oe,s.dims,u.dims,k,H,x,q,c,s.dataType,u.dataType,d,f),getRunData:()=>({outputs:[{dims:k,dataType:d}],dispatchGroup:{x:Math.ceil($/64/4)},programUniforms:[{type:12,data:Math.ceil(ct.size(k)/4)},...At(s.dims,u.dims,k)]})}},Zn=(n,i,s,u,c,f)=>{n.compute(Dc(i,c??"",n.inputs[0],n.inputs[1],s,u,f))},Lc=n=>{Zn(n,"Add",(i,s)=>`${i}+${s}`)},Rc=n=>{Zn(n,"Div",(i,s)=>`${i}/${s}`)},Ka=n=>{Zn(n,"Equal",{scalar:(i,s)=>`u32(${i}==${s})`,vector:(i,s)=>`vec4(${i}==${s})`},void 0,void 0,9)},Bc=n=>{Zn(n,"Mul",(i,s)=>`${i}*${s}`)},Nc=n=>{let i=_t("input",n.inputs[0].dataType,n.inputs[0].dims).type.value;Zn(n,"Pow",{scalar:(s,u)=>`pow_custom(${s},${u})`,vector:(s,u)=>`pow_vector_custom(${s},${u})`},` + fn pow_custom(a : ${i}, b : ${i}) -> ${i} { + if (b == ${i}(0.0)) { + return ${i}(1.0); + } else if (a < ${i}(0.0) && f32(b) != floor(f32(b))) { + return ${i}(pow(f32(a), f32(b))); // NaN + } + return select(sign(a), ${i}(1.0), round(f32(abs(b) % ${i}(2.0))) != 1.0) * ${i}(${i==="i32"?"round":""}(pow(f32(abs(a)), f32(b)))); + } + fn pow_vector_custom(a : vec4<${i}>, b : vec4<${i}>) -> vec4<${i}> { + // TODO: implement vectorized pow + return vec4<${i}>(pow_custom(a.x, b.x), pow_custom(a.y, b.y), pow_custom(a.z, b.z), pow_custom(a.w, b.w)); + } + `)},jc=n=>{Zn(n,"Sub",(i,s)=>`${i}-${s}`)},Uc=n=>{Zn(n,"Greater",{scalar:(i,s)=>`u32(${i}>${s})`,vector:(i,s)=>`vec4(${i}>${s})`},void 0,void 0,9)},Vc=n=>{Zn(n,"Less",{scalar:(i,s)=>`u32(${i}<${s})`,vector:(i,s)=>`vec4(${i}<${s})`},void 0,void 0,9)},Wc=n=>{Zn(n,"GreaterOrEqual",{scalar:(i,s)=>`u32(${i}>=${s})`,vector:(i,s)=>`vec4(${i}>=${s})`},void 0,void 0,9)},Xa=n=>{Zn(n,"LessOrEqual",{scalar:(i,s)=>`u32(${i}<=${s})`,vector:(i,s)=>`vec4(${i}<=${s})`},void 0,void 0,9)}}),Gc,Qa,Hc,qc,Ui,Kc,af=h(()=>{Zt(),Jt(),_r(),ar(),Gc=(n,i)=>{if(!n||n.length<1)throw new Error("too few inputs");let s=0,u=n[s],c=u.dataType,f=u.dims.length;n.forEach((d,x)=>{if(x!==s){if(d.dataType!==c)throw new Error("input tensors should be one type");if(d.dims.length!==f)throw new Error("input tensors should have the same shape");d.dims.forEach((k,$)=>{if($!==i&&k!==u.dims[$])throw new Error("non concat dimensions must match")})}})},Qa=(n,i)=>` + fn calculateInputIndex(index: u32) -> u32 { + let sizeInConcatAxis = array(${i}); + for (var i: u32 = 0u; i < ${n}; i += 1u ) { + if (index < sizeInConcatAxis[i]) { + return i; + } + } + return ${n}u; + }`,Hc=(n,i)=>{let s=n.length,u=[];for(let c=0;c{let c=ct.size(s),f=new Array(n.length),d=new Array(n.length),x=0,k=[],$=[],H=[{type:12,data:c}];for(let de=0;de`uniforms.sizeInConcatAxis${de}`).join(","),te=de=>` + + ${(()=>{de.registerUniform("outputSize","u32");for(let we=0;we(${oe}); + ${v} -= sizeInConcatAxis[inputIndex - 1u]; + } + + ${Hc(d,q)} + }`;return{name:"Concat",shaderCache:{hint:`${i}`,inputDependencies:k},getRunData:()=>({outputs:[{dims:s,dataType:u}],dispatchGroup:{x:Math.ceil(c/64)},programUniforms:H}),getShaderSource:te}},Ui=(n,i)=>{let s=n.inputs,u=s[0].dims,c=ct.normalizeAxis(i.axis,u.length);Gc(s,c);let f=u.slice();f[c]=s.reduce((x,k)=>x+(k.dims.length>c?k.dims[c]:0),0);let d=s.filter(x=>ct.size(x.dims)>0);n.compute(qc(d,c,f,s[0].dataType),{inputs:d})},Kc=n=>qt({axis:n.axis})}),Vi,Wi,Ei,Ya,Gi=h(()=>{Zt(),Jt(),Vi=(n,i,s="f32")=>{switch(n.activation){case"Relu":return`value = max(value, ${i}(0.0));`;case"Sigmoid":return`value = (${i}(1.0) / (${i}(1.0) + exp(-value)));`;case"Clip":return`value = clamp(value, ${i}(${s}(uniforms.clip_min)), ${i}(${s}(uniforms.clip_max)));`;case"HardSigmoid":return`value = max(${i}(0.0), min(${i}(1.0), ${s}(uniforms.alpha) * value + ${s}(uniforms.beta)));`;case"LeakyRelu":return`value = select(${s}(uniforms.alpha) * value, value, value >= ${i}(0.0));`;case"Tanh":return`let e2x = exp(-2.0 * abs(value)); + value = sign(value) * (1.0 - e2x) / (1.0 + e2x); + `;case"":return"";default:throw new Error(`Unsupported activation ${n.activation}`)}},Wi=(n,i)=>{n.activation==="Clip"?i.push({type:1,data:n.clipMax},{type:1,data:n.clipMin}):n.activation==="HardSigmoid"?i.push({type:1,data:n.alpha},{type:1,data:n.beta}):n.activation==="LeakyRelu"&&i.push({type:1,data:n.alpha})},Ei=(n,i)=>{n.activation==="Clip"?i.push({name:"clip_max",type:"f32"},{name:"clip_min",type:"f32"}):n.activation==="HardSigmoid"?i.push({name:"alpha",type:"f32"},{name:"beta",type:"f32"}):n.activation==="LeakyRelu"&&i.push({name:"alpha",type:"f32"})},Ya=n=>{let i=(n==null?void 0:n.activation)||"";if(i==="HardSigmoid"){let[s,u]=(n==null?void 0:n.activation_params)||[.2,.5];return{activation:i,alpha:s,beta:u}}else if(i==="Clip"){let[s,u]=(n==null?void 0:n.activation_params)||[cn,On];return{activation:i,clipMax:u,clipMin:s}}else if(i==="LeakyRelu"){let[s]=(n==null?void 0:n.activation_params)||[.01];return{activation:i,alpha:s}}return{activation:i}}}),vn,Za,xo=h(()=>{vn=(n,i)=>{switch(n){case 1:return i;case 2:return`vec2<${i}>`;case 3:return`vec3<${i}>`;case 4:return`vec4<${i}>`;default:throw new Error(`${n}-component is not supported.`)}},Za=n=>` + ${n?"value = value + getBiasByOutputCoords(coords);":""} + `}),Ja,Xc=h(()=>{Ja=n=>` +fn getIndexFromCoords4D(coords : vec4, shape : vec4) -> i32 { + return dot(coords, vec4( + shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1)); +} +fn getOutputIndexFromCoords(coords : vec4) -> i32 { + return dot(coords, vec4( + i32(${n}.x), i32(${n}.y), i32(${n}.z), 1)); +} +`}),Qc,qo,Rs,el,Yc,Bs,Ns,tl,js=h(()=>{Zt(),Jt(),ar(),Gi(),xo(),Qc=(n,i)=>n?` + mm_Asub[inputRow][inputCol] = mm_readA(batch, + kStart + inputRow, + globalRowStart / innerElementSize + inputCol${i?", batchIndices":""}); + `:` + mm_Asub[inputRow][inputCol] = mm_readA(batch, + globalRow + innerRow, + kStart / innerElementSize + inputCol${i?", batchIndices":""}); + `,qo=(n,i)=>n?` + let ACached0 = mm_Asub[k * innerElementSize][localRow]; + let ACached1 = mm_Asub[k * innerElementSize + 1][localRow]; + let ACached2 = mm_Asub[k * innerElementSize + 2][localRow]; + ${i===3?"":"let ACached3 = mm_Asub[k * innerElementSize + 3][localRow];"} + for (var i = 0; i < rowPerThread; i = i + 1) { + acc[i] = BCached0 * ACached0[i] + acc[i]; + acc[i] = BCached1 * ACached1[i] + acc[i]; + acc[i] = BCached2 * ACached2[i] + acc[i]; + ${i===3?"":"acc[i] = BCached3 * ACached3[i] + acc[i];"} + }`:` + for (var i = 0; i < rowPerThread; i = i + 1) { + let ACached = mm_Asub[tileRow + i][k]; + acc[i] = BCached0 * ACached.x + acc[i]; + acc[i] = BCached1 * ACached.y + acc[i]; + acc[i] = BCached2 * ACached.z + acc[i]; + ${i===3?"":"acc[i] = BCached3 * ACached.w + acc[i];"} + }`,Rs=(n,i,s="f32",u,c=!1,f=32,d=!1,x=32)=>{let k=i[1]*n[1],$=i[0]*n[0],H=c?k:f,q=c?f:k,v=H/i[0],oe=f/i[1];if(!((c&&v===4&&n[1]===4||!c&&(v===3||v===4))&&H%i[0]===0&&f%i[1]===0&&n[0]===4))throw new Error(`If transposeA ${c} is true, innerElementSize ${v} and workPerThread[1] ${n[1]} must be 4. + Otherwise, innerElementSize ${v} must be 3 or 4. + tileAWidth ${H} must be divisible by workgroupSize[0]${i[0]}. tileInner ${f} must be divisible by workgroupSize[1] ${i[1]}. colPerThread ${n[0]} must be 4.`);return` +var mm_Asub: array, ${H/v}>, ${q}>; +var mm_Bsub: array, ${$/n[0]}>, ${f}>; + +const rowPerThread = ${n[1]}; +const colPerThread = ${n[0]}; +const innerElementSize = ${v}; +const tileInner = ${f}; + +@compute @workgroup_size(${i[0]}, ${i[1]}, ${i[2]}) +fn main(@builtin(local_invocation_id) localId : vec3, + @builtin(global_invocation_id) globalId : vec3, + @builtin(workgroup_id) workgroupId : vec3) { + let localRow = i32(localId.y); + let tileRow = localRow * rowPerThread; + let tileCol = i32(localId.x); + + let globalRow =i32(globalId.y) * rowPerThread; + let globalCol = i32(globalId.x); + let batch = ${d?"0":"i32(globalId.z)"}; + ${u?`let batchIndices = ${u.offsetToIndices("u32(batch)")};`:""} + let globalRowStart = i32(workgroupId.y) * ${k}; + + let num_tiles = ${d?`${Math.ceil(x/f)}`:"(uniforms.dim_inner - 1) / tileInner + 1"}; + var kStart = ${d?`i32(globalId.z) * ${x}`:"0"}; + + var acc: array, rowPerThread>; + + // Loop over shared dimension. + let tileRowB = localRow * ${oe}; + for (var t = 0; t < num_tiles; t = t + 1) { + // Load one tile of A into local memory. + for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) { + let inputRow = tileRow + innerRow; + let inputCol = tileCol; + ${Qc(c,u)} + } + + // Load one tile of B into local memory. + for (var innerRow = 0; innerRow < ${oe}; innerRow = innerRow + 1) { + let inputRow = tileRowB + innerRow; + let inputCol = tileCol; + mm_Bsub[inputRow][inputCol] = mm_readB(batch, kStart + inputRow, globalCol${u?", batchIndices":""}); + } + kStart = kStart + tileInner; + workgroupBarrier(); + + // Compute acc values for a single thread. + for (var k = 0; k < tileInner / innerElementSize; k = k + 1) { + let BCached0 = mm_Bsub[k * innerElementSize][tileCol]; + let BCached1 = mm_Bsub[k * innerElementSize + 1][tileCol]; + let BCached2 = mm_Bsub[k * innerElementSize + 2][tileCol]; + ${v===3?"":"let BCached3 = mm_Bsub[k * innerElementSize + 3][tileCol];"} + + ${qo(c,v)} + } + + workgroupBarrier(); + } + + for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) { + mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]); + } +}`},el=(n,i)=>n?` + mm_Asub[inputRow][inputCol] = mm_readA(batch, + kStart + inputRow, + globalRowStart + inputCol${i?", batchIndices":""}); + `:` + mm_Asub[inputRow][inputCol] = mm_readA(batch, + globalRowStart + inputRow, + kStart + inputCol${i?", batchIndices":""}); + `,Yc=n=>n?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];",Bs=(n,i,s="f32",u,c=!1,f=32,d=!1,x=32,k=!1)=>{let $=n[1]*i[1],H=n[0]*i[0],q=c?$:f,v=c?f:$;if(!(v%i[1]===0&&q%i[0]===0&&f%i[1]===0))throw new Error(`tileAHight ${v} must be divisible by workgroupSize[1]${i[1]}, tileAWidth ${q} must be divisible by workgroupSize[0]${i[0]}, tileInner ${f} must be divisible by workgroupSize[1]${i[1]}`);let oe=v/i[1],te=q/i[0],de=f/i[1],we=k?` + let localRow = i32(localId.y); + let localCol = i32(localId.x); + let globalRowStart = i32(workgroupId.y) * ${$}; + let globalColStart = i32(workgroupId.x) * ${H}; + + // Loop over shared dimension. + for (var t = 0; t < num_tiles; t = t + 1) { + // Load one tile of A into local memory. + for (var inputRow = localRow; inputRow < ${v}; inputRow = inputRow + ${i[1]}) { + for (var inputCol = localCol; inputCol < ${q}; inputCol = inputCol + ${i[0]}) { + ${el(c,u)} + } + } + // Load one tile of B into local memory. + for (var inputRow = localRow; inputRow < ${f}; inputRow = inputRow + ${i[1]}) { + for (var inputCol = localCol; inputCol < ${H}; inputCol = inputCol + ${i[0]}) { + mm_Bsub[inputRow][inputCol] = mm_readB(batch, + kStart + inputRow, + globalColStart + inputCol${u?", batchIndices":""}); + } + } + kStart = kStart + tileInner; + workgroupBarrier(); + + // Compute acc values for a single thread. + var BCached : array<${s}, colPerThread>; + for (var k = 0; k < tileInner; k = k + 1) { + for (var inner = 0; inner < colPerThread; inner = inner + 1) { + BCached[inner] = mm_Bsub[k][localCol + inner * ${i[0]}]; + } + for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) { + let ACached = ${c?`mm_Asub[k][localRow + innerRow * ${i[1]}];`:`mm_Asub[localRow + innerRow * ${i[1]}][k];`} + for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) { + acc[innerRow][innerCol] = acc[innerRow][innerCol] + + ACached * BCached[innerCol]; + } + } + } + workgroupBarrier(); + } + for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) { + let gRow = globalRowStart + localRow + innerRow * ${i[1]}; + for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) { + let gCol = globalColStart + localCol + innerCol * ${i[0]}; + mm_write(batch, gRow, gCol, acc[innerRow][innerCol]); + } + } + `:` +let tileRow = i32(localId.y) * rowPerThread; +let tileCol = i32(localId.x) * colPerThread; + +let globalRow = i32(globalId.y) * rowPerThread; +let globalCol = i32(globalId.x) * colPerThread; +let globalRowStart = i32(workgroupId.y) * ${$}; + +let tileRowA = i32(localId.y) * ${oe}; +let tileColA = i32(localId.x) * ${te}; +let tileRowB = i32(localId.y) * ${de}; +// Loop over shared dimension. +for (var t = 0; t < num_tiles; t = t + 1) { + // Load one tile of A into local memory. + for (var innerRow = 0; innerRow < ${oe}; innerRow = innerRow + 1) { + for (var innerCol = 0; innerCol < ${te}; innerCol = innerCol + 1) { + let inputRow = tileRowA + innerRow; + let inputCol = tileColA + innerCol; + ${el(c,u)} + } + } + + // Load one tile of B into local memory. + for (var innerRow = 0; innerRow < ${de}; innerRow = innerRow + 1) { + for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) { + let inputRow = tileRowB + innerRow; + let inputCol = tileCol + innerCol; + mm_Bsub[inputRow][inputCol] = mm_readB(batch, + kStart + inputRow, + globalCol + innerCol${u?", batchIndices":""}); + } + } + kStart = kStart + tileInner; + workgroupBarrier(); + + // Compute acc values for a single thread. + var BCached : array<${s}, colPerThread>; + for (var k = 0; k < tileInner; k = k + 1) { + for (var inner = 0; inner < colPerThread; inner = inner + 1) { + BCached[inner] = mm_Bsub[k][tileCol + inner]; + } + + for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) { + ${Yc(c)} + for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) { + acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol]; + } + } + } + + workgroupBarrier(); +} + +for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) { + for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) { + mm_write(batch, globalRow + innerRow, globalCol + innerCol, + acc[innerRow][innerCol]); + } +} +`;return` + var mm_Asub : array, ${v}>; + var mm_Bsub : array, ${f}>; + const rowPerThread = ${n[1]}; + const colPerThread = ${n[0]}; + const tileInner = ${f}; + +@compute @workgroup_size(${i[0]}, ${i[1]}, ${i[2]}) +fn main(@builtin(local_invocation_id) localId : vec3, + @builtin(global_invocation_id) globalId : vec3, + @builtin(workgroup_id) workgroupId : vec3) { + let batch = ${d?"0":"i32(globalId.z)"}; + ${u?`let batchIndices = ${u.offsetToIndices("u32(batch)")};`:""} + let num_tiles = ${d?`${Math.ceil(x/f)}`:"(uniforms.dim_inner - 1) / tileInner + 1"}; + var kStart = ${d?`i32(globalId.z) * ${x}`:"0"}; + + var acc : array, rowPerThread>; + ${we} + } +`},Ns=(n,i,s,u,c,f=!1)=>{let[d,x,k]=c,[$,H,q,v]=u,oe=wo(d,k),te=wo(x,k),de=Sr(u[0].type.tensor),we=()=>{let he=H.rank,De=$.rank,Ae=`var aIndices: ${H.type.indices};`;for(let Ie=he-2-1,gt=De-1;Ie>=0;Ie--,gt--)Ae+=` +aIndices[${Ie}] = ${De>1?`batchIndices[${gt}]`:"batchIndices"};`;return oe.forEach(Ie=>{Ae+=` +aIndices[${Ie}] = 0;`}),Ae+=` +aIndices[${he-2}] = u32(row); + aIndices[${he-1}] = u32(colIn);`,Ae},be=()=>{let he=q.rank,De=$.rank,Ae=`var bIndices: ${q.type.indices};`;for(let Ie=he-2-1,gt=De-1;Ie>=0;Ie--,gt--)Ae+=` +bIndices[${Ie}] = ${De>1?`batchIndices[${gt}]`:"batchIndices"};`;return te.forEach(Ie=>{Ae+=` +bIndices[${Ie}] = 0;`}),Ae+=` +bIndices[${he-2}] = u32(row); + bIndices[${he-1}] = u32(colIn);`,Ae};return` + fn mm_readA(batch: i32, row: i32, colIn: i32, batchIndices: ${$.type.indices}) -> ${vn(n,de)} { + var value = ${vn(n,de)}(0.0); + let col = colIn * ${n}; + if(row < uniforms.dim_a_outer && col < uniforms.dim_inner) + { + ${we()} + value = ${H.getByIndices("aIndices")}; + } + return value; + } + + fn mm_readB(batch: i32, row: i32, colIn: i32, batchIndices: ${$.type.indices}) -> ${vn(n,de)} { + var value = ${vn(n,de)}(0.0); + let col = colIn * ${n}; + if(row < uniforms.dim_inner && col < uniforms.dim_b_outer) + { + ${be()} + value = ${q.getByIndices("bIndices")}; + } + return value; + } + + fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${vn(n,de)}) { + let col = colIn * ${n}; + if (row < uniforms.dim_a_outer && col < uniforms.dim_b_outer) { + var value = valueIn; + let coords = vec3(batch, row, colIn); + ${i?`value = value + ${f?"bias[colIn]":`${vn(n,de)}(bias[row])`};`:""} + ${s} + ${v.setByIndices("vec3(coords)","value")} + } + } + `},tl=(n,i,s,u,c=!1)=>{let f=n[0].dims,d=n[1].dims,x=f.slice(0,-2),k=d.slice(0,-2),$=u?u.slice(0,-2):s.slice(0,-2),H=ct.size($),q=f[f.length-2],v=f[f.length-1],oe=d[d.length-1],te=v%4===0&&oe%4===0,de=q<=8?[4,1,1]:[4,4,1],we=[8,8,1],be=[Math.ceil(oe/we[0]/de[0]),Math.ceil(q/we[1]/de[1]),Math.ceil(H/we[2]/de[2])],he=te?4:1,De=[...x,q,v/he],Ae=De.length,Ie=[...k,v,oe/he],gt=Ie.length,ut=[H,q,oe/he],vt=[{type:6,data:q},{type:6,data:oe},{type:6,data:v}];Wi(i,vt),vt.push(...At($,De,Ie));let Dt=["rank","rank"],Rt=n.length>2;Rt&&(vt.push(...At(n[2].dims)),Dt.push("rank")),vt.push(...At(ut));let gr=Mr=>{let ir=$.length,Fr=ma("batchDims",n[0].dataType,ir,1),Zr=Sr(n[0].dataType),hr=_t("a",n[0].dataType,Ae,he),Hr=_t("b",n[1].dataType,gt,he),Nt=Gt("result",n[0].dataType,ut.length,he),er=[hr,Hr];if(Rt){let Wr=c?he:1;er.push(_t("bias",n[2].dataType,n[2].dims.length,Wr))}let yr=[{name:"dim_a_outer",type:"i32"},{name:"dim_b_outer",type:"i32"},{name:"dim_inner",type:"i32"}];Ei(i,yr);let ot=Sr(Nt.type.tensor),Vt=Vi(i,Nt.type.value,ot),nr=Ns(he,Rt,Vt,[Fr,hr,Hr,Nt],[x,k,$],c);return` + ${Mr.registerUniforms(yr).registerInternalVariables(Fr).declareVariables(...er,Nt)} + ${nr} + ${te?Rs(de,we,Zr,Fr):Bs(de,we,Zr,Fr)} + `};return{name:"MatMul",shaderCache:{hint:`${de};${i.activation};${te};${c}`,inputDependencies:Dt},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:be[0],y:be[1],z:be[2]},programUniforms:vt}),getShaderSource:gr}}}),Zc,lf,uf=h(()=>{Zt(),jn(),ar(),Gi(),xo(),Xc(),js(),Zc=(n,i,s,u,c=!1,f,d=4,x=4,k=4,$="f32")=>{let H=Dt=>{switch(Dt){case 1:return"resData = x[xIndex];";case 3:return`resData = vec3<${$}>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);`;case 4:return"resData = x[xIndex / 4];";default:throw new Error(`innerElementSize ${Dt} is not supported.`)}},q=Dt=>{switch(Dt){case 1:return"return w[row * i32(uniforms.w_shape[3]) + colIn];";case 4:return"return w[row * i32(uniforms.w_shape[3]) / 4 + colIn];";default:throw new Error(`innerElementSize ${Dt} is not supported.`)}},v=n?` + let coord = vec4(batch, xRow, xCol, xCh); + `:` + let coord = vec4(batch, xCh, xRow, xCol); + `,oe=n?` + let coords = vec4( + batch, + row / outWidth, + row % outWidth, + col); + `:` + let coords = vec4( + batch, + row, + col / outWidth, + col % outWidth); + `,te=n?"i32(uniforms.x_shape[1])":"i32(uniforms.x_shape[2])",de=n?"i32(uniforms.x_shape[2])":"i32(uniforms.x_shape[3])",we=n?"row":"col",be=n?"col":"row",he=` + let inChannels = i32(uniforms.w_shape[2]); + let outWidth = ${n?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"}; + let outRow = ${we} / outWidth; + let outCol = ${we} % outWidth; + + let WRow = ${be} / (i32(uniforms.w_shape[1]) * inChannels); + let WCol = ${be} / inChannels % i32(uniforms.w_shape[1]); + let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0]; + let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1]; + let xCh = ${be} % inChannels; + var resData = ${vn(d,$)}(0.0); + // The bounds checking is always needed since we use it to pad zero for + // the 'same' padding type. + if (xRow >= 0 && xRow < ${te} && xCol >= 0 && xCol < ${de}) { + ${v} + let xIndex = getIndexFromCoords4D(coord, vec4(uniforms.x_shape)); + ${H(d)} + } + return resData;`,De=n?i&&u?` + let col = colIn * ${d}; + ${he}`:` + let col = colIn * ${d}; + if (row < uniforms.dim_a_outer && col < uniforms.dim_inner) { + ${he} + } + return ${vn(d,$)}(0.0);`:u&&s?` + let col = colIn * ${d}; + ${he}`:` + let col = colIn * ${d}; + if (row < uniforms.dim_inner && col < uniforms.dim_b_outer) { + ${he} + } + return ${vn(d,$)}(0.0);`,Ae=`${q(x)}`,Ie=vn(k,$),gt=vn(n?d:x,$),ut=vn(n?x:d,$),vt=Vi(f,Ie,$);return` + fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${gt} { + ${n?De:Ae} + } + + fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${ut} { + ${n?Ae:De} + } + + fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${Ie}) { + let col = colIn * ${k}; + if (row < uniforms.dim_a_outer && col < uniforms.dim_b_outer) + { + var value = valueIn; + let outWidth = ${n?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"}; + ${oe} + ${Za(c)} + ${vt} + setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value); + } + }`},lf=(n,i,s,u,c,f,d,x)=>{let k=i.format==="NHWC",$=k?n[0].dims[3]:n[0].dims[1],H=s[0],q=k?s[2]:s[3],v=k?s[1]:s[2],oe=k?s[3]:s[1],te=k&&($%4===0||$%3===0)&&oe%4===0,de=k?oe:q*v,we=k?q*v:oe,be=[8,8,1],he=u<=8?[4,1,1]:[4,4,1],De=[Math.ceil(de/be[0]/he[0]),Math.ceil(we/be[1]/he[1]),Math.ceil(H/be[2]/he[2])];Vr("verbose",()=>`[conv2d_mm_webgpu] dispatch = ${De}`);let Ae=te?k&&$%4!==0?3:4:1,Ie=be[1]*he[1],gt=be[0]*he[0],ut=Math.max(be[0]*Ae,be[1]),vt=u%Ie===0,Dt=c%gt===0,Rt=f%ut===0,gr=te?[Ae,4,4]:[1,1,1],Mr=[{type:6,data:u},{type:6,data:c},{type:6,data:f},{type:6,data:[i.pads[0],i.pads[1]]},{type:6,data:i.strides},{type:6,data:i.dilations}];Wi(i,Mr),Mr.push(...At(n[0].dims,n[1].dims));let ir=["rank","rank"];d&&(Mr.push(...At(n[2].dims)),ir.push("rank")),Mr.push(...At(s));let Fr=Zr=>{let hr=[{name:"dim_a_outer",type:"i32"},{name:"dim_b_outer",type:"i32"},{name:"dim_inner",type:"i32"},{name:"pad",type:"i32",length:2},{name:"stride",type:"i32",length:2},{name:"dilation",type:"i32",length:2}];Ei(i,hr);let Hr=te?4:1,Nt=Sr(n[0].dataType),er=` + fn setOutputAtIndex(flatIndex : i32, value : ${te?`vec4<${Nt}>`:Nt}) { + result[flatIndex] = ${te?`vec4<${Nt}>`:Nt}(value); + } + fn setOutputAtCoords(d0 : i32, d1 : i32, d2 : i32, d3 : i32, value : ${te?`vec4<${Nt}>`:Nt}) { + let flatIndex = getOutputIndexFromCoords(vec4(d0, d1, d2, d3)); + setOutputAtIndex(flatIndex ${te?"/ 4":""}, value); + }`,yr=_t("x",n[0].dataType,n[0].dims.length,Ae===3?1:Ae),ot=_t("w",n[1].dataType,n[1].dims.length,Hr),Vt=[yr,ot],nr=Gt("result",n[0].dataType,s.length,Hr);if(d){let Wr=_t("bias",n[2].dataType,n[2].dims.length,Hr);Vt.push(Wr),er+=` + fn getBiasByOutputCoords(coords : vec4) -> ${te?`vec4<${Nt}>`:Nt} { + return bias[coords.${k?"w":"y"}${te?"/ 4":""}]; + }`}return` + ${Ja("uniforms.result_strides")} + //struct Uniforms { xShape : vec4, wShape : vec4, outShape : vec4, + // outShapeStrides: vec3, filterDims : vec2, pad : vec2, stride : vec2, + // dilation : vec2, dimAOuter : i32, dimBOuter : i32, dimInner : i32 }; + ${Zr.registerUniforms(hr).declareVariables(...Vt,nr)} + ${er} + ${Zc(k,vt,Dt,Rt,d,i,gr[0],gr[1],gr[2],Nt)} + ${te?Rs(he,be,Nt,void 0,!k,ut):Bs(he,be,Nt,void 0,!k,ut,!1,void 0,x)}`};return{name:"Conv2DMatMul",shaderCache:{hint:`${i.cacheKey};${Ae};${te};${vt};${Dt};${Rt};${Ie};${gt};${ut}`,inputDependencies:ir},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:De[0],y:De[1],z:De[2]},programUniforms:Mr}),getShaderSource:Fr}}}),Jc,rl,Ci,ed,nl,td,rd,nd,il=h(()=>{Zt(),jn(),Jt(),ar(),Gi(),xo(),Jc=n=>{let i=1;for(let s=0;stypeof n=="number"?[n,n,n]:n,Ci=(n,i)=>i<=1?n:n+(n-1)*(i-1),ed=(n,i,s,u=1)=>{let c=Ci(i,u);return Math.floor((n[0]*(s-1)-s+c)/2)},nl=(n,i,s,u,c)=>{c==null&&(c=ed(n,i[0],u[0]));let f=[0,0,0,s];for(let d=0;d<3;d++)n[d]+2*c>=i[d]&&(f[d]=Math.trunc((n[d]-i[d]+2*c)/u[d]+1));return f},td=(n,i,s,u,c,f,d,x,k,$)=>{let H,q,v,oe;if(n==="VALID"&&(n=0),typeof n=="number"){H={top:n,bottom:n,left:n,right:n,front:n,back:n};let te=nl([i,s,u,1],[x,k,$],1,[c,f,d],n);q=te[0],v=te[1],oe=te[2]}else if(Array.isArray(n)){if(!n.every((de,we,be)=>de===be[0]))throw Error(`Unsupported padding parameter: ${n}`);H={top:n[0],bottom:n[1],left:n[2],right:n[3],front:n[4],back:n[5]};let te=nl([i,s,u,1],[x,k,$],1,[c,f,d],n[0]);q=te[0],v=te[1],oe=te[2]}else if(n==="SAME_UPPER"){q=Math.ceil(i/c),v=Math.ceil(s/f),oe=Math.ceil(u/d);let te=(q-1)*c+x-i,de=(v-1)*f+k-s,we=(oe-1)*d+$-u,be=Math.floor(te/2),he=te-be,De=Math.floor(de/2),Ae=de-De,Ie=Math.floor(we/2),gt=we-Ie;H={top:De,bottom:Ae,left:Ie,right:gt,front:be,back:he}}else throw Error(`Unknown padding parameter: ${n}`);return{padInfo:H,outDepth:q,outHeight:v,outWidth:oe}},rd=(n,i,s,u,c,f=!1,d="channelsLast")=>{let x,k,$,H,q;if(d==="channelsLast")[x,k,$,H,q]=n;else if(d==="channelsFirst")[x,q,k,$,H]=n;else throw new Error(`Unknown dataFormat ${d}`);let[v,,oe,te,de]=i,[we,be,he]=rl(s),[De,Ae,Ie]=rl(u),gt=Ci(oe,De),ut=Ci(te,Ae),vt=Ci(de,Ie),{padInfo:Dt,outDepth:Rt,outHeight:gr,outWidth:Mr}=td(c,k,$,H,we,be,he,gt,ut,vt),ir=f?v*q:v,Fr=[0,0,0,0,0];return d==="channelsFirst"?Fr=[x,ir,Rt,gr,Mr]:d==="channelsLast"&&(Fr=[x,Rt,gr,Mr,ir]),{batchSize:x,dataFormat:d,inDepth:k,inHeight:$,inWidth:H,inChannels:q,outDepth:Rt,outHeight:gr,outWidth:Mr,outChannels:ir,padInfo:Dt,strideDepth:we,strideHeight:be,strideWidth:he,filterDepth:oe,filterHeight:te,filterWidth:de,effectiveFilterDepth:gt,effectiveFilterHeight:ut,effectiveFilterWidth:vt,dilationDepth:De,dilationHeight:Ae,dilationWidth:Ie,inShape:n,outShape:Fr,filterShape:i}},nd=(n,i,s,u,c,f)=>{let d=f==="channelsLast";d?n[0].dims[3]:n[0].dims[1];let x=[64,1,1],k={x:s.map((we,be)=>be)},$=[Math.ceil(Jc(k.x.map(we=>s[we]))/x[0]),1,1];Vr("verbose",()=>`[conv3d_naive_webgpu] dispatch = ${$}`);let H=1,q=ct.size(s),v=[{type:12,data:q},{type:12,data:u},{type:12,data:c},{type:12,data:i.strides},{type:12,data:i.dilations}];Wi(i,v),v.push(...At(n[0].dims,n[1].dims));let oe=["rank","rank"],te=n.length===3;te&&(v.push(...At(n[2].dims)),oe.push("rank")),v.push(...At(s));let de=we=>{let be=[{name:"output_size",type:"u32"},{name:"filter_dims",type:"u32",length:u.length},{name:"pads",type:"u32",length:c.length},{name:"strides",type:"u32",length:i.strides.length},{name:"dilations",type:"u32",length:i.dilations.length}];Ei(i,be);let he=1,De=Sr(n[0].dataType),Ae=_t("x",n[0].dataType,n[0].dims.length,H),Ie=_t("W",n[1].dataType,n[1].dims.length,he),gt=[Ae,Ie],ut=Gt("result",n[0].dataType,s.length,he),vt="";if(te){let gr=_t("bias",n[2].dataType,n[2].dims.length,he);gt.push(gr),vt+=` + fn getBiasByOutputCoords(coords : array) -> ${De} { + return bias[${d?zt("coords",4,5):zt("coords",1,5)}]; + }`}let Dt=vn(H,De),Rt=Vi(i,Dt,De);return` + ${vt} + fn getX(d0 : u32, d1 : u32, d2 : u32, d3 : u32, d4 : u32) -> f32 { + let aIndices = array(d0, d1, d2, d3, d4); + return ${Ae.getByIndices("aIndices")}; + } + fn getW(d0 : u32, d1 : u32, d2 : u32, d3 : u32, d4 : u32) -> f32 { + let aIndices = array(d0, d1, d2, d3, d4); + return ${Ie.getByIndices("aIndices")}; + } + ${we.registerUniforms(be).declareVariables(...gt,ut)} + ${we.mainStart()} + ${we.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + let coords = ${ut.offsetToIndices("global_idx")}; + let batch = ${zt("coords",0,Ae.rank)}; + let d2 = ${d?zt("coords",Ae.rank-1,Ae.rank):zt("coords",1,Ae.rank)}; + let xFRCCorner = vec3(${d?zt("coords",1,Ae.rank):zt("coords",2,Ae.rank)}, + ${d?zt("coords",2,Ae.rank):zt("coords",3,Ae.rank)}, + ${d?zt("coords",3,Ae.rank):zt("coords",4,Ae.rank)}) * uniforms.strides - uniforms.pads; + let xFCorner = xFRCCorner.x; + let xRCorner = xFRCCorner.y; + let xCCorner = xFRCCorner.z; + let xShapeY = ${d?zt("uniforms.x_shape",1,Ae.rank):zt("uniforms.x_shape",2,Ae.rank)}; + let xShapeZ = ${d?zt("uniforms.x_shape",2,Ae.rank):zt("uniforms.x_shape",3,Ae.rank)}; + let xShapeW = ${d?zt("uniforms.x_shape",3,Ae.rank):zt("uniforms.x_shape",4,Ae.rank)}; + let xShapeU = ${d?zt("uniforms.x_shape",4,Ae.rank):zt("uniforms.x_shape",1,Ae.rank)}; + let inputDepthNearestVec4 = (xShapeU / 4) * 4; + let inputDepthVec4Remainder = xShapeU % 4; + + var value = 0.0; + for (var wF = 0u; wF < uniforms.filter_dims[0]; wF++) { + let xF = xFCorner + wF * uniforms.dilations[0]; + if (xF < 0 || xF >= xShapeY) { + continue; + } + + for (var wR = 0u; wR < uniforms.filter_dims[1]; wR++) { + let xR = xRCorner + wR * uniforms.dilations[1]; + if (xR < 0 || xR >= xShapeZ) { + continue; + } + + for (var wC = 0u; wC < uniforms.filter_dims[2]; wC++) { + let xC = xCCorner + wC * uniforms.dilations[2]; + if (xC < 0 || xC >= xShapeW) { + continue; + } + + for (var d1 = 0u; d1 < inputDepthNearestVec4; d1 += 4) { + ${d?`let xValues = vec4( + getX(batch, xF, xR, xC, d1), + getX(batch, xF, xR, xC, d1 + 1), + getX(batch, xF, xR, xC, d1 + 2), + getX(batch, xF, xR, xC, d1 + 3)); + `:`let xValues = vec4( + getX(batch, d1, xF, xR, xC), + getX(batch, d1 + 1, xF, xR, xC), + getX(batch, d1 + 2, xF, xR, xC), + getX(batch, d1 + 3, xF, xR, xC)); + `} + let wValues = vec4( + getW(d2, d1, wF, wR, wC), + getW(d2, d1 + 1, wF, wR, wC), + getW(d2, d1 + 2, wF, wR, wC), + getW(d2, d1 + 3, wF, wR, wC)); + value += dot(xValues, wValues); + } + if (inputDepthVec4Remainder == 1) { + ${d?`value += getX(batch, xF, xR, xC, inputDepthNearestVec4) + * getW(d2, inputDepthNearestVec4, wF, wR, wC);`:`value += getX(batch, inputDepthNearestVec4, xF, xR, xC) + * getW(d2, inputDepthNearestVec4, wF, wR, wC);`} + } else if (inputDepthVec4Remainder == 2) { + ${d?`let xValues = vec2( + getX(batch, xF, xR, xC, inputDepthNearestVec4), + getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1)); + `:`let xValues = vec2( + getX(batch, inputDepthNearestVec4, xF, xR, xC), + getX(batch, inputDepthNearestVec4 + 1, xF, xR, xC)); + `} + let wValues = vec2( + getW(d2, inputDepthNearestVec4, wF, wR, wC), + getW(d2, inputDepthNearestVec4 + 1, wF, wR, wC)); + value += dot(xValues, wValues); + } else if (inputDepthVec4Remainder == 3) { + ${d?`let xValues = vec3( + getX(batch, xF, xR, xC, inputDepthNearestVec4), + getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1), + getX(batch, xF, xR, xC, inputDepthNearestVec4 + 2)); + `:`let xValues = vec3( + getX(batch, inputDepthNearestVec4, xF, xR, xC), + getX(batch, inputDepthNearestVec4 + 1, xF, xR, xC), + getX(batch, inputDepthNearestVec4 + 2, xF, xR, xC)); + `} + let wValues = vec3( + getW(d2, inputDepthNearestVec4, wF, wR, wC), + getW(d2, inputDepthNearestVec4 + 1, wF, wR, wC), + getW(d2, inputDepthNearestVec4 + 2, wF, wR, wC)); + value += dot(xValues, wValues); + } + } + } + } + ${te?"value = value + getBiasByOutputCoords(coords)":""}; + ${Rt} + result[global_idx] = f32(value); + }`};return{name:"Conv3DNaive",shaderCache:{hint:`${i.cacheKey};${d};${H};${te}`,inputDependencies:oe},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:$[0],y:$[1],z:$[2]},programUniforms:v}),getShaderSource:de}}}),id,od,cf=h(()=>{Zt(),Jt(),ar(),cd(),Gi(),id=(n,i,s)=>{let u=n.length>2,c=u?"value += b[output_channel];":"",f=n[0].dims,d=n[1].dims,x=d[0]/i.group,k=i.format==="NHWC",$=Us(f,d,i.dilations,i.pads,i.strides,k),H=ct.size($),q=[{type:12,data:H},{type:12,data:i.dilations},{type:12,data:[i.strides[0],i.strides[1]]},{type:12,data:[i.pads[0],i.pads[1]]},{type:12,data:x}];Wi(i,q),q.push(...At(f,d));let v=["rank","rank"];u&&(q.push(...At(n[2].dims)),v.push("rank")),q.push(...At($));let oe=te=>{let de=Gt("output",n[0].dataType,$.length),we=Sr(de.type.tensor),be=Vi(i,de.type.value,we),he=_t("x",n[0].dataType,f.length),De=_t("w",n[1].dataType,d.length),Ae=[he,De];u&&Ae.push(_t("b",n[2].dataType,n[2].dims.length));let Ie=[{name:"output_size",type:"u32"},{name:"dilations",type:"u32",length:i.dilations.length},{name:"strides",type:"u32",length:2},{name:"pads",type:"u32",length:2},{name:"output_channels_per_group",type:"u32"}];return Ei(i,Ie),` + ${te.registerUniforms(Ie).declareVariables(...Ae,de)} + + ${te.mainStart()} + ${te.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + + let outputIndices = ${de.offsetToIndices("global_idx")}; + let batch: u32 = outputIndices[0]; + let output_channel: u32 = outputIndices[${k?3:1}]; + let xRCCorner: vec2 = vec2(outputIndices[${k?1:2}], outputIndices[${k?2:3}]) * uniforms.strides - uniforms.pads; + let group_id: u32 = output_channel / uniforms.output_channels_per_group; + + var value: ${de.type.value} = ${de.type.value}(0); + for (var wInChannel: u32 = 0u; wInChannel < uniforms.w_shape[1]; wInChannel++) { + let input_channel = group_id * uniforms.w_shape[1] + wInChannel; + for (var wHeight: u32 = 0u; wHeight < uniforms.w_shape[2]; wHeight++) { + let xHeight = xRCCorner.x + wHeight * uniforms.dilations[0]; + + if (xHeight < 0u || xHeight >= uniforms.x_shape[${k?1:2}]) { + continue; + } + + for (var wWidth: u32 = 0u; wWidth < uniforms.w_shape[3]; wWidth++) { + let xWidth = xRCCorner.y + wWidth * uniforms.dilations[1]; + if (xWidth < 0u || xWidth >= uniforms.x_shape[${k?2:3}]) { + continue; + } + + let xVal = ${k?he.get("batch","xHeight","xWidth","input_channel"):he.get("batch","input_channel","xHeight","xWidth")}; + let wVal = ${De.get("output_channel","wInChannel","wHeight","wWidth")}; + value += xVal*wVal; + } + } + } + ${c} + ${be} + ${de.setByOffset("global_idx","value")} + }`};return{name:"GroupedConv",shaderCache:{hint:i.cacheKey,inputDependencies:v},getRunData:()=>({outputs:[{dims:s?s($):$,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(H/64)},programUniforms:q}),getShaderSource:oe}},od=(n,i,s)=>{let u=n.length>2,c=vr(s[3]),f=vr(s[2]),d=ct.size(s)/c/f,x=[n[0].dims[0],n[0].dims[1],n[0].dims[2],n[0].dims[3]/c],k=[n[1].dims[0],n[1].dims[1],n[1].dims[2],n[1].dims[3]/c],$=[s[0],s[1],s[2],s[3]/c],H=[{type:12,data:d},{type:6,data:[i.strides[0],i.strides[1]]},{type:6,data:[i.pads[0],i.pads[1]]}];Wi(i,H),H.push(...At(x,k,$));let q=(f-1)*i.strides[1]+k[1],v=oe=>{let te=Gt("output",n[0].dataType,$.length,c),de=Sr(te.type.tensor),we=Vi(i,te.type.value,de),be=_t("x",n[0].dataType,x.length,c),he=_t("w",n[1].dataType,k.length,c),De=[be,he];u&&De.push(_t("b",n[2].dataType,n[2].dims,c));let Ae=u?"value += b[output_channel];":"",Ie=[{name:"output_size",type:"u32"},{name:"strides",type:"i32",length:2},{name:"pads",type:"i32",length:2}];return Ei(i,Ie),` + ${oe.registerUniforms(Ie).declareVariables(...De,te)} + ${oe.mainStart()} + ${oe.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + let width0 = uniforms.output_shape[3]; + let output_channel = global_idx % width0; + var index1 = global_idx / width0; + let width1 = uniforms.output_shape[2] / ${f}u; + let col = (index1 % width1) * ${f}u; + index1 = index1 / width1; + let row = index1 % uniforms.output_shape[1]; + let batch = index1 / uniforms.output_shape[1]; + + let x_corner = vec2(i32(row), i32(col)) * uniforms.strides - uniforms.pads; + + var x_vals: array<${be.type.value}, ${q}>; + var values: array<${te.type.value}, ${f}>; + let input_channel = output_channel; + // Use constant instead of uniform can give better performance for w's height/width. + for (var w_height: u32 = 0u; w_height < ${k[0]}; w_height++) { + let x_height = x_corner.x + i32(w_height); + if (x_height >= 0 && u32(x_height) < uniforms.x_shape[1]) { + for (var i = 0; i < ${q}; i++) { + let x_width = x_corner.y + i; + if (x_width >= 0 && u32(x_width) < uniforms.x_shape[2]) { + x_vals[i] = ${be.get("batch","u32(x_height)","u32(x_width)","input_channel")}; + } else { + x_vals[i] = ${be.type.value}(0); + } + } + for (var w_width: u32 = 0u; w_width < ${k[1]}; w_width++) { + let w_val = ${he.get("w_height","w_width","0","output_channel")}; + for (var i = 0u; i < ${f}u; i++) { + values[i] = fma(x_vals[i * u32(uniforms.strides[1]) + w_width], w_val, values[i]); + } + } + } + } + + for (var i = 0u; i < ${f}u; i++) { + var value = values[i]; + ${Ae} + ${we} + ${te.set("batch","row","col + i","output_channel","value")}; + } + }`};return{name:"GroupedConv-Vectorize",shaderCache:{hint:`${i.cacheKey};${c};${f};${q};${k[0]};${k[1]}`,inputDependencies:u?["rank","rank","type"]:["rank","rank"]},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:H}),getShaderSource:v}}}),ol,sd,ad,sl=h(()=>{Zt(),Jt(),js(),ar(),Gi(),ol=(n,i,s,u,c=!1)=>{let f=n[0].dims,d=n[1].dims,x=f[f.length-2],k=d[d.length-1],$=f[f.length-1],H=vr(k),q=vr($),v=vr(x),oe=ct.size(s)/H/v,te=n.length>2,de=u?u.slice(0,-2):s.slice(0,-2),we=[ct.size(de),x,k],be=[{type:12,data:oe},{type:12,data:x},{type:12,data:k},{type:12,data:$}];Wi(i,be),be.push(...At(de,f,d)),te&&be.push(...At(n[2].dims)),be.push(...At(we));let he=De=>{let Ae=ma("batch_dims",n[0].dataType,de.length),Ie=_t("a",n[0].dataType,f.length,q),gt=_t("b",n[1].dataType,d.length,H),ut=Gt("output",n[0].dataType,we.length,H),vt=Sr(ut.type.tensor),Dt=Vi(i,ut.type.value,vt),Rt=[Ie,gt],gr="";if(te){let er=c?H:1;Rt.push(_t("bias",n[2].dataType,n[2].dims.length,er)),gr=`${c?`value += bias[col / ${er}];`:`value += ${ut.type.value}(bias[row + i]);`}`}let Mr=f.slice(0,-2),ir=d.slice(0,-2),Fr=wo(Mr,de),Zr=wo(ir,de),hr=[{name:"output_size",type:"u32"},{name:"M",type:"u32"},{name:"N",type:"u32"},{name:"K",type:"u32"}];Ei(i,hr);let Hr=(er,yr)=>{let ot=er.rank,Vt=er.name;if(ot===2)return`var ${Vt}_indices = ${er.type.indices}(0u, 0u);`;let nr=Ae.rank,Wr=`var ${Vt}_indices: ${er.type.indices};`;for(let pn=ot-2-1,kn=nr-1;pn>=0;pn--,kn--)Wr+=` +${Vt}_indices[${pn}] = ${nr>1?`batch_indices[${kn}]`:"batch_indices"};`;return yr.forEach(pn=>{Wr+=` +${Vt}_indices[${pn}] = 0;`}),Wr+=`${Vt}_indices[${ot-2}] = 0u; + ${Vt}_indices[${ot-1}] = 0u;`,Wr},Nt=()=>{let er=`var a_data: ${Ie.type.value};`;for(let yr=0;yr; + for (var k: u32 = 0u; k < uniforms.K; k = k + ${q}) { + ${Nt()} + } + for (var i = 0u; i < ${v}u; i++) { + var value = values[i]; + ${gr} + ${Dt} + let cur_indices = ${ut.type.indices}(batch, row + i, col); + let offset = ${ut.indicesToOffset("cur_indices")}; + ${ut.setByOffset(`offset / ${H}`,"value")}; + } + } + `};return{name:"MatMulNaive",shaderCache:{hint:`${i.activation};${H};${q};${v};${c}`,inputDependencies:te?["rank","rank","rank"]:["rank","rank"]},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(oe/64)},programUniforms:be}),getShaderSource:he}},sd=n=>{if(!n||n.length!==2)throw new Error("MatMul requires 2 inputs.");if(n[0].dims[n[0].dims.length-1]!==n[1].dims[n[1].dims.length-2])throw new Error("shared dimension does not match.")},ad=n=>{sd(n.inputs);let i=gn.calcShape(n.inputs[0].dims,n.inputs[1].dims,!0);if(!i)throw new Error("Can't use matmul on the given tensors");let s=i[i.length-1],u=n.inputs[0].dims[n.inputs[0].dims.length-1];s<8&&u<8?n.compute(ol(n.inputs,{activation:""},i)):n.compute(tl(n.inputs,{activation:""},i))}}),Us,Vs,al,Ws,ll,ul,ld,ud,Ko,cd=h(()=>{Jt(),uf(),il(),js(),cf(),Gi(),sl(),yo(),Us=(n,i,s,u,c,f)=>{let d=n[0],x=n.slice(f?1:2,f?3:4),k=x.length,$=i[0],H=i.slice(2).map((v,oe)=>v+(v-1)*(s[oe]-1)),q=x.map((v,oe)=>v+u[oe]+u[oe+k]).map((v,oe)=>Math.floor((v-H[oe]+c[oe])/c[oe]));return q.splice(0,0,d),q.splice(f?3:1,0,$),q},Vs=[2,3,1,0],al=(n,i)=>{if(!n||n.length!==2&&n.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(n[0].dims.length>5)throw new Error("greater than 5D is not supported");if(n[0].dims.length!==n[1].dims.length)throw new Error("filter does not have same dimension as input");let s=n[0].dims[i.format==="NHWC"?n[0].dims.length-1:1],u=n[1].dims[1]*i.group;if(s!==u)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(n.length===3&&(n[2].dims.length!==1||n[1].dims[0]!==n[2].dims[0]))throw new Error("invalid bias");let c=n[0].dims.length-2;if(i.dilations.length!==c)throw new Error(`dilations should be ${c}D`);if(i.strides.length!==c)throw new Error(`strides should be ${c}D`);if(i.pads.length!==c*2)throw new Error(`pads should be ${c*2}D`);if(i.kernelShape.length!==0&&i.kernelShape.length!==n[1].dims.length-2)throw new Error("invalid kernel shape")},Ws=(n,i)=>{let s=n.kernelShape.slice();for(let f=2;f{let i=Ya(n),s=n.format,u=["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][n.auto_pad],c=n.dilations,f=n.group,d=n.kernel_shape,x=n.pads,k=n.strides,$=n.w_is_const();return{autoPad:u,format:s,dilations:c,group:f,kernelShape:d,pads:x,strides:k,wIsConst:$,...i,cacheKey:`${n.format};${i.activation};`}},ul=(n,i,s)=>{let u=Ws(s,i),c=s.format==="NHWC";if(s.group!==1){if(!n.adapterInfo.isArchitecture("ampere")&&c&&i[1].dims[0]===s.group&&i[1].dims[1]===1&&s.dilations[0]===1&&s.dilations[1]===1){let gt=Us(i[0].dims,i[1].dims,s.dilations,u.pads,s.strides,c),ut=n.kernelCustomData.wT??n.compute(hi(i[1],Vs),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!n.kernelCustomData.wT&&(n.kernelCustomData.wT=ut);let vt=[i[0],ut];i.length===3&&vt.push(i[2]),n.compute(od(vt,u,gt),{inputs:vt})}else n.compute(id(i,u));return}let f=i.length===3,d=i[0].dims[c?1:2],x=i[0].dims[c?2:3],k=i[0].dims[c?3:1],$=i[1].dims[2],H=i[1].dims[3],q=Us(i[0].dims,i[1].dims,s.dilations,u.pads,s.strides,c),v=q[c?1:2],oe=q[c?2:3],te=q[c?3:1],de=c&&$===d&&H===x&&s.pads[0]===0&&s.pads[1]===0;if(de||$===1&&H===1&&s.dilations[0]===1&&s.dilations[1]===1&&s.strides[0]===1&&s.strides[1]===1&&s.pads[0]===0&&s.pads[1]===0){let gt=q[0],ut,vt,Dt,Rt=[];if(c){let ir=n.kernelCustomData.wT??n.compute(hi(i[1],Vs),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];if(s.wIsConst&&!n.kernelCustomData.wT&&(n.kernelCustomData.wT=ir),de){let Fr=d*x*k;ut=i[0].reshape([1,gt,Fr]),vt=ir.reshape([1,Fr,te]),Dt=[1,gt,te]}else ut=i[0].reshape([gt,d*x,k]),vt=ir.reshape([1,k,te]),Dt=[gt,v*oe,te];Rt.push(ut),Rt.push(vt)}else ut=i[0].reshape([gt,k,d*x]),vt=i[1].reshape([1,te,k]),Dt=[gt,te,v*oe],Rt.push(vt),Rt.push(ut);f&&Rt.push(i[2]);let gr=Dt[2],Mr=Rt[0].dims[Rt[0].dims.length-1];gr<8&&Mr<8?n.compute(ol(Rt,u,q,Dt,c),{inputs:Rt}):n.compute(tl(Rt,u,q,Dt,c),{inputs:Rt});return}let we=!0,be=n.kernelCustomData.wT??n.compute(hi(i[1],Vs),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!n.kernelCustomData.wT&&(n.kernelCustomData.wT=be);let he=[i[0],be];f&&he.push(i[2]);let De=c?v*oe:te,Ae=c?te:v*oe,Ie=$*H*k;n.compute(lf(he,u,q,De,Ae,Ie,f,we),{inputs:he})},ld=(n,i)=>{let s=i.format==="NHWC",u=[n.inputs[0].reshape(s?[n.inputs[0].dims[0],1,n.inputs[0].dims[1],n.inputs[0].dims[2]]:[n.inputs[0].dims[0],n.inputs[0].dims[1],1,n.inputs[0].dims[2]]),n.inputs[1].reshape([n.inputs[1].dims[0],n.inputs[1].dims[1],1,n.inputs[1].dims[2]])];n.inputs.length===3&&u.push(n.inputs[2]);let c=[0,i.pads[0],0,i.pads[1]],f=[1].concat(i.strides),d=[1].concat(i.dilations),x=[1].concat(i.kernelShape),k=Ws({...i,pads:c,strides:f,dilations:d,kernelShape:x},u);n.compute(id(u,k,$=>s?[$[0],$[2],$[3]]:[]))},ud=(n,i,s)=>{let u=s.format==="NHWC"?"channelsLast":"channelsFirst",c=Ws(s,i),f=s.autoPad==="NOTSET"?s.pads:s.autoPad,d=rd(i[0].dims,i[1].dims,s.strides,s.dilations,f,!1,u);n.compute(nd(i,c,d.outShape,[d.filterDepth,d.filterHeight,d.filterWidth],[d.padInfo.front,d.padInfo.top,d.padInfo.left],u))},Ko=(n,i)=>{al(n.inputs,i),n.inputs[0].dims.length===3?ld(n,i):n.inputs[0].dims.length===5?ud(n,n.inputs,i):ul(n,n.inputs,i)}}),dd,pd,df=h(()=>{Zt(),jn(),ar(),Gi(),xo(),Xc(),js(),dd=(n,i=!1,s,u,c=4)=>{let f=we=>{switch(we){case 1:return"return w[getIndexFromCoords4D(coord, vec4(uniforms.w_shape))];";case 4:return` + let coord1 = vec4(coordX, coordY, col + 1, rowInner); + let coord2 = vec4(coordX, coordY, col + 2, rowInner); + let coord3 = vec4(coordX, coordY, col + 3, rowInner); + let v0 = w[getIndexFromCoords4D(coord, vec4(uniforms.w_shape))]; + let v1 = w[getIndexFromCoords4D(coord1, vec4(uniforms.w_shape))]; + let v2 = w[getIndexFromCoords4D(coord2, vec4(uniforms.w_shape))]; + let v3 = w[getIndexFromCoords4D(coord3, vec4(uniforms.w_shape))]; + return ${u}(v0, v1, v2, v3); + `;default:throw new Error(`innerElementSize ${we} is not supported.`)}},d=n?` + let coord = vec4(batch, iXR, iXC, xCh); + `:` + let coord = vec4(batch, xCh, iXR, iXC); + `,x=n?` + let coords = vec4( + batch, + row / outWidth, + row % outWidth, + col); + `:` + let coords = vec4( + batch, + row, + col / outWidth, + col % outWidth); + `,k=n?"i32(uniforms.x_shape[1])":"i32(uniforms.x_shape[2])",$=n?"i32(uniforms.x_shape[2])":"i32(uniforms.x_shape[3])",H=n?"row":"col",q=n?"col":"row",v=` + let inChannels = ${n?"i32(uniforms.x_shape[3])":"i32(uniforms.x_shape[1])"}; + let outWidth = ${n?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"}; + let outRow = ${H} / outWidth; + let outCol = ${H} % outWidth; + + let WRow = ${q} / (uniforms.filter_dims[1] * inChannels); + let WCol = ${q} / inChannels % uniforms.filter_dims[1]; + let xR = f32(outRow - uniforms.pads[0] + uniforms.dilations[0] * WRow) / f32(uniforms.strides[0]); + let xC = f32(outCol - uniforms.pads[1] + uniforms.dilations[1] * WCol) / f32(uniforms.strides[1]); + if (xR < 0.0 || xR >= f32(${k}) || fract(xR) > 0.0) { + return ${u}(0.0); + } + if (xC < 0.0 || xC >= f32(${$}) || fract(xC) > 0.0) { + return ${u}(0.0); + } + let iXR = i32(xR); + let iXC = i32(xC); + let xCh = ${q} % inChannels; + ${d} + return x[getIndexFromCoords4D(coord, vec4(uniforms.x_shape))/${c}];`,oe=n?` + let col = colIn * ${c}; + if (row < uniforms.dim_a_outer && col < uniforms.dim_inner) { + ${v} + } + return ${u}(0.0);`:` + let col = colIn * ${c}; + if (row < uniforms.dim_inner && col < uniforms.dim_b_outer) { + ${v} + } + return ${u}(0.0);`,te=` + let col = colIn * ${c}; + let inChannels = ${n?"i32(uniforms.x_shape[3])":"i32(uniforms.x_shape[1])"}; + let coordX = uniforms.filter_dims[0] - 1 - row / (uniforms.filter_dims[1] * inChannels); + let coordY = uniforms.filter_dims[1] - 1 - (row / inChannels) % uniforms.filter_dims[1]; + if (${n?"row < uniforms.dim_inner && col < uniforms.dim_b_outer":"row < uniforms.dim_inner && col < uniforms.dim_a_outer"} && coordX >= 0 && coordY >= 0) { + let rowInner = row % inChannels; + let coord = vec4(coordX, coordY, col, rowInner); + ${f(c)} + } + return ${u}(0.0); + `,de=Vi(s,u);return` + fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${u} { + ${n?oe:te} + } + + fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${u} { + ${n?te:oe} + } + + fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${u}) { + let col = colIn * ${c}; + if (row < uniforms.dim_a_outer && col < uniforms.dim_b_outer) { + var value = valueInput; + let outWidth = ${n?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"}; + ${x} + ${Za(i)} + ${de} + result[getIndexFromCoords4D(coords, vec4(uniforms.result_shape))/${c}] = value; + } + }`},pd=(n,i,s,u,c,f,d,x)=>{let k=i.format==="NHWC",$=k?n[0].dims[3]:n[0].dims[1],H=s[0],q=k?s[2]:s[3],v=k?s[1]:s[2],oe=k?s[3]:s[1],te=k&&$%4===0&&$%3&&oe%4===0,de=k?oe:q*v,we=k?q*v:oe,be=[8,8,1],he=u<=8?[4,1,1]:[4,4,1],De=[Math.ceil(de/be[0]/he[0]),Math.ceil(we/be[1]/he[1]),Math.ceil(H/be[2]/he[2])];Vr("verbose",()=>`[conv_backprop_mm_webgpu] dispatch = ${De}`);let Ae=te?4:1,Ie=Math.max(be[0]*Ae,be[1]),gt=te?4:1,ut=[i.kernelShape[k?1:2],i.kernelShape[k?2:3]],vt=[ut[0]+(i.dilations[0]<=1?0:(ut[0]-1)*(i.dilations[0]-1)),ut[1]+(i.dilations[1]<=1?0:(ut[1]-1)*(i.dilations[1]-1))],Dt=[vt[0]-1-Math.floor((i.pads[0]+i.pads[2])/2),vt[1]-1-Math.floor((i.pads[1]+i.pads[3])/2)],Rt=[{type:6,data:u},{type:6,data:c},{type:6,data:f},{type:6,data:i.strides},{type:6,data:i.dilations},{type:6,data:ut},{type:6,data:Dt}];Wi(i,Rt),Rt.push(...At(n[0].dims,n[1].dims));let gr=["rank","rank"];d&&(Rt.push(...At(n[2].dims)),gr.push("rank")),Rt.push(...At(s));let Mr=ir=>{let Fr=_t("x",n[0].dataType,n[0].dims.length,gt),Zr=_t("w",n[1].dataType,n[1].dims.length,1),hr=Gt("result",n[0].dataType,s.length,gt),Hr=[Fr,Zr],Nt="";if(d){let ot=_t("bias",n[2].dataType,n[2].dims.length,gt);Hr.push(ot),Nt+=` + fn getBiasByOutputCoords(coords : vec4) -> ${ot.type.value} { + return bias[coords.${k?"w":"y"}${te?"/ 4":""}]; + }`}let er=[{name:"dim_a_outer",type:"i32"},{name:"dim_b_outer",type:"i32"},{name:"dim_inner",type:"i32"},{name:"strides",type:"i32",length:2},{name:"dilations",type:"i32",length:2},{name:"filter_dims",type:"i32",length:ut.length},{name:"pads",type:"i32",length:Dt.length}];Ei(i,er);let yr=Sr(n[0].dataType,1);if(yr!=="f16"&&yr!=="f32")throw new Error(`elemType ${yr} is not supported.`);return` + ${Ja("uniforms.result_strides")} + ${ir.registerUniforms(er).declareVariables(...Hr,hr)}; + ${Nt} + ${dd(k,d,i,Fr.type.value,Ae)} + ${te?Rs(he,be,yr,void 0,!k,Ie):Bs(he,be,yr,void 0,!k,Ie,!1,void 0,x)}`};return{name:"Conv2DTransposeMatMul",shaderCache:{hint:`${i.cacheKey};${he};${be};${te}`,inputDependencies:gr},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:De[0],y:De[1],z:De[2]},programUniforms:Rt}),getShaderSource:Mr}}}),cl,Xo,mm=h(()=>{Zt(),jn(),Jt(),ar(),cl=(n,i,s,u,c,f=!1,d,x,k=!1)=>{let $=k?1:2,H=k?2:3,q=k?3:1,v=f?2:1,oe=` + fn setOutputAtIndex(flatIndex : u32, value : ${f?`vec4<${d}>`:d}) { + result[flatIndex] = ${f?`vec4<${d}>`:d}(value); + }`;u&&(oe+=` + fn getBiasByOutputCoords(coords : vec4) -> ${f?`vec4<${d}>`:d} { + return bias[coords.${k?"w":"y"}${f?"/ 4":""}]; + }`);let te=f?4:1,de=_t("W",i[1].dataType,i[1].dims.length,te),we=_t("Dy",i[0].dataType,i[0].dims.length,te),be=[we,de];u&&be.push(_t("bias",i[2].dataType,[s[q]].length,te));let he=Gt("result",i[0].dataType,s.length,te),De=`{ + let batch: u32 = ${c?"global_id.z":"workgroup_id.z"} / uniforms.result_shape[1]; + let r = ${c?"global_id.z":"workgroup_id.z"} % uniforms.result_shape[1]; + let c = ${c?"global_id.y":"workgroup_id.y"} * ${v}; + let d1: u32 = ${c?"global_id.x":"workgroup_id.x"} * 4; + + let dyCorner = vec2(i32(r), i32(c)) - vec2(uniforms.pads); + + // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1). + // ? = to be determined. : = across all values in that axis. + var dotProd: array, ${v}>; + for (var i = 0; i < ${v}; i++) { + dotProd[i] = vec4<${d}>(0.0); + } + for (var wR: u32 = 0; wR < uniforms.filter_dims[0]; wR = wR + 1) { + var dyR = (${d}(dyCorner.x) + ${d}(wR)) / ${d}(uniforms.strides.x); + let wRPerm = uniforms.filter_dims[0] - 1 - wR; + if (dyR < 0.0 || dyR >= ${d}(uniforms.Dy_shape[1]) || + fract(dyR) > 0.0 || wRPerm < 0) { + continue; + } + let idyR: u32 = u32(dyR); + + for (var wC: u32 = 0; wC < uniforms.filter_dims[1]; wC = wC + 1) { + let dyC = (${d}(dyCorner.y) + ${d}(wC)) / ${d}(uniforms.strides.y); + let dyC2 = (${d}(dyCorner.y) + 1.0 + ${d}(wC)) / ${d}(uniforms.strides.y); + let wCPerm = uniforms.filter_dims[1] - 1 - wC; + if (wCPerm < 0) { + continue; + } + var bDyCVal = true; + var bDyCVal2 = true; + if (dyC < 0.0 || dyC >= ${d}(uniforms.Dy_shape[2]) || + fract(dyC) > 0.0) { + bDyCVal = false; + } + if (dyC2 < 0.0 || dyC2 >= ${d}(uniforms.Dy_shape[2]) || + fract(dyC2) > 0.0) { + bDyCVal2 = false; + } + + let idyC: u32 = u32(dyC); + let idyC2: u32 = u32(dyC2); + if (bDyCVal && bDyCVal2) { + let d2Length = uniforms.Dy_shape[3]; + for (var d2 :u32 = 0; d2 < d2Length; d2 = d2 + 4) { + let wValue0 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1","d2")}; + let wValue1 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 1","d2")}; + let wValue2 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 2","d2")}; + let wValue3 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 3","d2")}; + + var xValue = ${we.get("batch","idyR","idyC","d2")}; + let tmpval = vec4<${d}>(dot(xValue, wValue0), + dot(xValue, wValue1), + dot(xValue, wValue2), + dot(xValue, wValue3)); + dotProd[0] = dotProd[0] + tmpval; + + xValue = ${we.get("batch","idyR","idyC2","d2")}; + + dotProd[1] = dotProd[1] + vec4<${d}>(dot(xValue, wValue0), + dot(xValue, wValue1), + dot(xValue, wValue2), + dot(xValue, wValue3)); + } + } else if (bDyCVal) { + let d2Length = uniforms.Dy_shape[${q}]; + for (var d2: u32 = 0; d2 < d2Length; d2 = d2 + 4) { + let wValue0 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1","d2")}; + let wValue1 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 1","d2")}; + let wValue2 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 2","d2")}; + let wValue3 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 3","d2")}; + + var xValue = ${we.get("batch","idyR","idyC","d2")}; + let tmpval = vec4<${d}>(dot(xValue, wValue0), + dot(xValue, wValue1), + dot(xValue, wValue2), + dot(xValue, wValue3)); + dotProd[0] = dotProd[0] + tmpval; + } + } else if (bDyCVal2) { + let d2Length = uniforms.Dy_shape[3]; + for (var d2: u32 = 0; d2 < d2Length; d2 = d2 + 4) { + let wValue0 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1","d2")}; + let wValue1 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 1","d2")}; + let wValue2 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 2","d2")}; + let wValue3 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 3","d2")}; + + var xValue = ${we.get("batch","idyR","idyC2","d2")}; + let tmpval = vec4<${d}>(dot(xValue, wValue0), + dot(xValue, wValue1), + dot(xValue, wValue2), + dot(xValue, wValue3)); + dotProd[1] = dotProd[1] + tmpval; + } + } + } + } + + for (var i: u32 = 0; i < ${v}; i = i + 1) { + let value = dotProd[i] + ${u?"bias[c+i]":`vec4<${d}>(0.0)`}; + ${he.set("batch","r","c + i","d1","value")}; + } + }`,Ae=` + let outputIndices = ${he.offsetToIndices("global_idx")}; + let batch = ${he.indicesGet("outputIndices",0)}; + let d1 = ${he.indicesGet("outputIndices",q)}; + let r = ${he.indicesGet("outputIndices",$)}; + let c = ${he.indicesGet("outputIndices",H)}; + let dyCorner = vec2(i32(r), i32(c)) - uniforms.pads; + let dyRCorner = dyCorner.x; + let dyCCorner = dyCorner.y; + let groupId = d1 / uniforms.output_channels_per_group; + let wOutChannel = d1 - groupId * uniforms.output_channels_per_group; + // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1). + // ? = to be determined. : = across all values in that axis. + var dotProd = ${d}(0.0); + for (var wR: u32 = 0; wR < uniforms.effective_filter_dims.x; wR = wR + 1) { + if (wR % uniforms.dilations.x != 0) { + continue; + } + let dyR = (${d}(dyRCorner) + ${d}(wR)) / ${d}(uniforms.strides[0]); + let wRPerm = uniforms.filter_dims.x - 1 - wR / uniforms.dilations.x; + if (dyR < 0.0 || dyR >= ${d}(uniforms.Dy_shape[${$}]) || fract(dyR) > 0.0 || + wRPerm < 0) { + continue; + } + let idyR: u32 = u32(dyR); + + for (var wC: u32 = 0; wC < uniforms.effective_filter_dims.y; wC = wC + 1) { + if (wC % uniforms.dilations.y != 0) { + continue; + } + let dyC = (${d}(dyCCorner) + ${d}(wC)) / ${d}(uniforms.strides.y); + let wCPerm = uniforms.filter_dims.y - 1 - wC / uniforms.dilations.y; + if (dyC < 0.0 || dyC >= ${d}(uniforms.Dy_shape[${H}]) || + fract(dyC) > 0.0 || wCPerm < 0) { + continue; + } + let idyC: u32 = u32(dyC); + var inputChannel = groupId * uniforms.input_channels_per_group; + for (var d2: u32 = 0; d2 < uniforms.input_channels_per_group; d2 = d2 + 1) { + let xValue = ${k?we.get("batch","idyR","idyC","inputChannel"):we.get("batch","inputChannel","idyR","idyC")}; + let wValue = ${de.get("inputChannel","wOutChannel","u32(wRPerm)","u32(wCPerm)")}; + dotProd = dotProd + xValue * wValue; + inputChannel = inputChannel + 1; + } + } + } + let value = dotProd + ${u?"bias[d1]":`${d}(0.0)`}; + ${he.setByOffset("global_idx","value")}; + `;return` + ${n.registerUniforms(x).declareVariables(...be,he)} + ${oe} + + ${n.mainStart()} + ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}; + ${f?De:Ae}}`},Xo=(n,i,s)=>{let u=n.length>2,c=i.outputShape,f=ct.size(c),d=[Math.ceil(f/64),1,1];Vr("verbose",()=>`[conv2d_backprop_webgpu] dispatch = ${d}`);let x=i.format==="NHWC",k=["rank","rank"],$=[i.strides[0],i.strides[1]],H=[i.kernelShape[x?1:2],i.kernelShape[x?2:3]],q=[i.dilations[0],i.dilations[1]],v=[H[0]+(i.dilations[0]<=1?0:(i.kernelShape[x?1:2]-1)*(i.dilations[0]-1)),H[1]+(i.dilations[1]<=1?0:(i.kernelShape[x?2:3]-1)*(i.dilations[1]-1))],oe=[v[0]-1-Math.floor((i.pads[0]+i.pads[2])/2),v[1]-1-Math.floor(i.pads[1]+i.pads[3])/2],te=!1,de=i.group,we=n[1].dims,be=we[0]/de,he=we[1],De=[{type:12,data:f},{type:12,data:$},{type:12,data:H},{type:12,data:q},{type:12,data:v},{type:6,data:oe},{type:12,data:be},{type:12,data:he},...At(n[0].dims,n[1].dims)];u&&(De.push(...At(n[2].dims)),k.push("rank")),De.push(...At(c));let Ae=d[1]===1&&d[2]===1,Ie=gt=>{let ut=[{name:"output_size",type:"u32"},{name:"strides",type:"u32",length:$.length},{name:"filter_dims",type:"u32",length:H.length},{name:"dilations",type:"u32",length:H.length},{name:"effective_filter_dims",type:"u32",length:v.length},{name:"pads",type:"i32",length:oe.length},{name:"input_channels_per_group",type:"u32"},{name:"output_channels_per_group",type:"u32"}],vt=Sr(n[0].dataType);return`${cl(gt,n,c,u,Ae,te,vt,ut,x)}`};return{name:"ConvTranspose2D",shaderCache:{hint:`${i.cacheKey};`,inputDependencies:k},getRunData:()=>({dispatchGroup:{x:d[0],y:d[1],z:d[2]},outputs:[{dims:s?s(c):c,dataType:n[0].dataType}],programUniforms:De}),getShaderSource:Ie}}}),fd,hd,dl,pl,md,fl,gd,_d,hl,pf,gm=h(()=>{df(),mm(),Gi(),yo(),fd=(n,i,s,u,c,f)=>(n-1)*i+s+(u-1)*c+1-f,hd=(n,i,s,u,c)=>{let f=Math.floor(n/2);i==="SAME_UPPER"?(s[u]=f,s[c]=n-f):i==="SAME_LOWER"&&(s[u]=n-f,s[c]=f)},dl=(n,i,s,u,c,f,d,x,k,$)=>{let H=n.length-2,q=$.length===0;if(k.length===0)for(let te=0;te{let s=n.kernelShape.slice();if(n.kernelShape.length===0||n.kernelShape.reduce((q,v)=>q*v,1)===0){s.length=0;for(let q=2;qq+v,0)===0){let q=i[0].dims.length-2;k=new Array(q).fill(1)}let $=n.strides.slice();if($.reduce((q,v)=>q+v,0)===0){let q=i[0].dims.length-2;$=new Array(q).fill(1)}dl(x,s,k,n.autoPad,n.group,c,$,u,d,f);let H=Object.assign({},n);return Object.assign(H,{kernelShape:s,pads:c,outputPadding:d,outputShape:f,dilations:k,strides:$}),H},md=n=>{let i=Ya(n),s=n.format,u=["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][typeof n.autoPad>"u"?0:n.autoPad],c=n.dilations,f=n.group,d=n.kernelShape,x=n.pads,k=n.strides,$=n.wIsConst(),H=n.outputPadding,q=n.outputShape;return{autoPad:u,format:s,dilations:c,group:f,kernelShape:d,outputPadding:H,outputShape:q,pads:x,strides:k,wIsConst:$,...i,cacheKey:`${n.format};${i.activation};`}},fl=(n,i)=>{if(!n||n.length!==2&&n.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(n[0].dims.length!==4&&n[0].dims.length!==3)throw new Error("currently only support 2-dimensional conv");if(n[0].dims.length!==n[1].dims.length)throw new Error("filter does not have same dimension as input");let s=n[0].dims[i.format==="NHWC"?n[0].dims.length-1:1],u=n[1].dims[0];if(s!==u)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");let c=n[1].dims[1]*i.group;if(n.length===3&&(n[2].dims.length!==1||n[2].dims[0]!==c))throw new Error("invalid bias");let f=n[0].dims.length-2;if(i.dilations.reduce((d,x)=>d+x,0)>0&&i.dilations.length!==f)throw new Error(`dilations should be ${f}D`);if(i.strides.reduce((d,x)=>d+x,0)>0&&i.strides.length!==f)throw new Error(`strides should be ${f}D`);if(i.pads.reduce((d,x)=>d+x,0)>0&&i.pads.length!==f*2)throw new Error(`pads should be ${f*2}D`);if(i.outputPadding.length!==f&&i.outputPadding.length!==0)throw new Error(`output_padding should be ${f}D`);if(i.kernelShape.reduce((d,x)=>d+x,0)>0&&i.kernelShape.length!==0&&i.kernelShape.length!==n[1].dims.length-2)throw new Error("invalid kernel shape");if(i.outputShape.length!==0&&i.outputShape.length!==n[0].dims.length-2)throw new Error("invalid output shape")},gd=[2,3,1,0],_d=(n,i,s)=>{let u=pl(s,i),c=s.format==="NHWC",f=u.outputShape,d=f[c?3:1],x=i[0].dims[c?3:1];if(u.group!==1||d===1&&x===1){n.compute(Xo(i,u));return}let k=f[c?1:2],$=f[c?2:3],H=i[1].dims[2],q=i[1].dims[3],v=c?k*$:d,oe=c?d:k*$,te=H*q*x,de=!0,we=n.kernelCustomData.wT??n.compute(hi(i[1],gd),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!n.kernelCustomData.wT&&(n.kernelCustomData.wT=we);let be=[i[0],we],he=i.length===3;he&&(!c&&i[2].dims.length===1?be.push(i[2].reshape([i[2].dims[0],1,1])):be.push(i[2])),n.compute(pd(be,u,f,v,oe,te,he,de),{inputs:be})},hl=(n,i)=>{let s=i.format==="NHWC",u=[n.inputs[0].reshape(s?[n.inputs[0].dims[0],1,n.inputs[0].dims[1],n.inputs[0].dims[2]]:[n.inputs[0].dims[0],n.inputs[0].dims[1],1,n.inputs[0].dims[2]]),n.inputs[1].reshape([n.inputs[1].dims[0],n.inputs[1].dims[1],1,n.inputs[1].dims[2]])];n.inputs.length===3&&u.push(n.inputs[2]);let c=i.kernelShape;(c.length===0||c[0]===0)&&(c=[n.inputs[1].dims[2]]);let f=i.dilations;(f.length===0||f[0]===0)&&(f=[1]);let d=i.strides;(d.length===0||d[0]===0)&&(d=[1]);let x=i.pads;x.length===0&&(x=[0,0]),x=[0,x[0],0,x[1]],d=[1].concat(d),f=[1].concat(f),c=[1].concat(c);let k=pl({...i,pads:x,strides:d,dilations:f,kernelShape:c},u);n.compute(Xo(u,k,$=>s?[$[0],$[2],$[3]]:[$[0],$[1],$[3]]))},pf=(n,i)=>{fl(n.inputs,i),n.inputs[0].dims.length===3?hl(n,i):_d(n,n.inputs,i)}}),ml,gl,wd,ff=h(()=>{Zt(),Jt(),_r(),ar(),ml=(n,i,s,u)=>{let c=ct.size(i),f=i.length,d=_t("input",n,f),x=Gt("output",n,f),k=s.dataType===6?s.getInt32Array()[0]:Number(s.getBigInt64Array()[0]),$=ct.normalizeAxis(k,f),H=q=>{let v=` i32(${d.indicesGet("inputIndices","uniforms.axis")}) `,oe=zt("uniforms.input_shape","uniforms.axis",f),te=u.reverse?v+(u.exclusive?" + 1":""):"0",de=u.reverse?oe:v+(u.exclusive?"":" + 1");return` + ${q.registerUniform("outputSize","u32").registerUniform("axis","u32").declareVariables(d,x)} + ${q.mainStart()} + ${q.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + var inputIndices = ${x.offsetToIndices("global_idx")}; + var sum = ${x.type.value}(0); + let first : i32 = ${te}; + let last : i32 = ${de}; + for (var i : i32 = first; i < last; i++) { + ${d.indicesSet("inputIndices","uniforms.axis","u32(i)")}; + sum = sum + ${d.getByIndices("inputIndices")}; + } + ${x.setByOffset("global_idx","sum")}; + }`};return{name:"CumSum",shaderCache:{hint:u.cacheKey,inputDependencies:["rank"]},getRunData:()=>({outputs:[{dims:i,dataType:n}],dispatchGroup:{x:Math.ceil(c/64)},programUniforms:[{type:12,data:c},{type:12,data:$},...At(i,i)]}),getShaderSource:H}},gl=(n,i)=>{let s=n.inputs[0].dims,u=n.inputs[0].dataType,c=n.inputs[1];n.compute(ml(u,s,c,i),{inputs:[0]})},wd=n=>{let i=n.exclusive===1,s=n.reverse===1;return qt({exclusive:i,reverse:s})}}),_l,yd,vd,wl,bd,hf=h(()=>{Zt(),Jt(),_r(),ar(),_l=n=>{if(!n||n.length!==1)throw new Error("DepthToSpace requires 1 input.");if(n[0].dims.length!==4)throw new Error("DepthToSpace requires 4D input.")},yd=(n,i,s,u)=>{let c=[];c.push(`fn perm(i: ${u.type.indices}) -> ${s.type.indices} { + var a: ${s.type.indices};`);for(let f=0;f{let 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he=k?[s,u*$,c*$,f/$**2]:[s,f/$**2,u*$,c*$],De=ct.size(he),Ae=q.dims,Ie=ct.sortBasedOnPerm(Ae,x);return{outputs:[{dims:he,dataType:be[0].dataType}],dispatchGroup:{x:Math.ceil(De/64)},programUniforms:[{type:12,data:De},...At(Ae,Ie)]}},getShaderSource:we}},wl=(n,i)=>{_l(n.inputs),n.compute(vd(n.inputs[0],i))},bd=n=>qt({blocksize:n.blocksize,mode:n.mode,format:n.format})}),Qo,Yo,yl,Rr,mf,gf,_f,Gs,xd,Md,Td,wf=h(()=>{Zt(),Jt(),_r(),ar(),Qo="[a-zA-Z]|\\.\\.\\.",Yo="("+Qo+")+",yl="^"+Yo+"$",Rr="("+Yo+",)*"+Yo,mf="^"+Rr+"$",gf=class{constructor(n=-1){this.symbolToIndices=new Map,this.inputIndex=n}addSymbol(n,i){let s=this.symbolToIndices.get(n);s===void 0?s=[i]:s.push(i),this.symbolToIndices.set(n,s)}},_f=class{constructor(n,i){var c;this.equation=i,this.hasEllipsis=!1,this.symbolToInfo=new Map,this.lhs=new Array,this.outputDims=[];let[s,u]=i.includes("->")?i.split("->",2):[i,""];if(!s.match(RegExp(mf)))throw new Error("Invalid LHS term");if(s.split(",").forEach((f,d)=>{let x=n[d].dims.slice();if(!f.match(RegExp(yl)))throw new Error("Invalid LHS term");let k=this.processTerm(f,!0,x,d);this.lhs.push(k)}),u==="")u+=[...this.symbolToInfo.entries()].filter(([f,d])=>d.count===1||f==="...").map(([f])=>f).join("");else if(!u.match(RegExp(Yo)))throw new Error("Invalid RHS");(c=u.match(RegExp(Qo,"g")))==null||c.forEach(f=>{if(f==="...")this.outputDims=this.outputDims.concat(this.ellipsisDims);else{let d=this.symbolToInfo.get(f);if(d===void 0)throw new Error("Invalid RHS symbol");this.outputDims.push(d.dimValue)}}),this.rhs=this.processTerm(u,!1,this.outputDims)}addSymbol(n,i,s){let u=this.symbolToInfo.get(n);if(u!==void 0){if(u.dimValue!==i&&u.count!==1)throw new Error("Dimension mismatch");u.count++,u.inputIndices.push(s)}else u={count:1,dimValue:i,inputIndices:[s]};this.symbolToInfo.set(n,u)}processTerm(n,i,s,u=-1){let c=s.length,f=!1,d=[],x=0;if(!n.match(RegExp(yl))&&!i&&n!=="")throw new Error("Invalid LHS term");let k=n.match(RegExp(Qo,"g")),$=new gf(u);return k==null||k.forEach((H,q)=>{if(H==="..."){if(f)throw new Error("Only one ellipsis is allowed per input term");f=!0;let v=c-k.length+1;if(v<0)throw new Error("Ellipsis out of bounds");if(d=s.slice(x,x+v),this.hasEllipsis){if(this.ellipsisDims.length!==d.length||this.ellipsisDims.toString()!==d.toString())throw new Error("Ellipsis dimensions mismatch")}else if(i)this.hasEllipsis=!0,this.ellipsisDims=d;else throw new Error("Ellipsis must be specified in the LHS");for(let oe=0;oen+"_max",xd=(n,i,s,u)=>{let c=n.map($=>$.length).map(($,H)=>_t(`input${H}`,i,$)),f=ct.size(u),d=Gt("output",i,u.length),x=[...s.symbolToInfo.keys()].filter($=>!s.rhs.symbolToIndices.has($)),k=$=>{let H=[],q="var prod = 1.0;",v="var sum = 0.0;",oe="sum += prod;",te=[],de=[],we=[],be=[],he=s.symbolToInfo.size===s.rhs.symbolToIndices.size;s.symbolToInfo.forEach((Ae,Ie)=>{var gt;if(s.rhs.symbolToIndices.has(Ie)){let ut=(gt=s.rhs.symbolToIndices.get(Ie))==null?void 0:gt[0];ut!==void 0&&s.lhs.forEach((vt,Dt)=>{if(Ae.inputIndices.includes(Dt)){let Rt=vt.symbolToIndices.get(Ie);if(Rt===void 0)throw new Error("Invalid symbol error");Rt.forEach(gr=>{H.push(`${c[Dt].indicesSet(`input${Dt}Indices`,gr,d.indicesGet("outputIndices",ut))}`)})}})}else s.lhs.forEach((ut,vt)=>{if(Ae.inputIndices.includes(vt)){let Dt=ut.symbolToIndices.get(Ie);if(Dt===void 0)throw new Error("Invalid symbol error");Dt.forEach(Rt=>{te.push(`${c[vt].indicesSet(`input${vt}Indices`,Rt,`${Ie}`)}`)}),be.push(`prod *= ${c[vt].getByIndices(`input${vt}Indices`)};`)}}),de.push(`for(var ${Ie}: u32 = 0; ${Ie} < uniforms.${Gs(Ie)}; ${Ie}++) {`),we.push("}")});let De=he?[...H,`let sum = ${c.map((Ae,Ie)=>Ae.getByIndices(`input${Ie}Indices`)).join(" * ")};`]:[...H,v,...de,...te,q,...be,oe,...we];return` + ${$.registerUniforms(x.map(Ae=>({name:`${Gs(Ae)}`,type:"u32"}))).registerUniform("outputSize","u32").declareVariables(...c,d)} + + ${$.mainStart()} + ${$.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + var outputIndices = ${d.offsetToIndices("global_idx")}; + ${c.map((Ae,Ie)=>`var input${Ie}Indices: ${c[Ie].type.indices};`).join(` +`)} + ${De.join(` +`)}; + ${d.setByOffset("global_idx","sum")}; + }`};return{name:"Einsum",shaderCache:{hint:s.equation,inputDependencies:n.map(()=>"rank")},getRunData:()=>{let $=x.filter(q=>s.symbolToInfo.has(q)).map(q=>{var v;return{type:12,data:((v=s.symbolToInfo.get(q))==null?void 0:v.dimValue)||0}});$.push({type:12,data:f});let H=n.map((q,v)=>[...At(q)]).reduce((q,v)=>q.concat(v),$);return H.push(...At(u)),{outputs:[{dims:u,dataType:i}],dispatchGroup:{x:Math.ceil(f/64)},programUniforms:H}},getShaderSource:k}},Md=(n,i)=>{let s=new _f(n.inputs,i.equation),u=s.outputDims,c=n.inputs.map((f,d)=>f.dims);n.compute(xd(c,n.inputs[0].dataType,s,u))},Td=n=>{let i=n.equation.replace(/\s+/g,"");return qt({equation:i})}}),vl,Hs,kd,Sd,bl,_m=h(()=>{Zt(),Jt(),ar(),vl=n=>{if(!n||n.length!==2)throw new Error("Expand requires 2 input.");let i=n[0].dims,s=Array.from(n[1].getBigInt64Array(),Number),u=s.length{let s=n.length-i.length,u=[];for(let c=0;cn.length>i.length?Hs(n,i):Hs(i,n),Sd=n=>{let i=n[0].dims,s=Array.from(n[1].getBigInt64Array(),Number),u=kd(i,s),c=n[0].dataType,f=c===9?4:1,d=Math.ceil(ct.size(u)/f),x=$=>{let H=_t("input",c,i.length,f),q=Gt("output",c,u.length,f),v;if(c===9){let oe=(te,de,we="")=>` + let outputIndices${de} = ${q.offsetToIndices(`outputOffset + ${de}u`)}; + let offset${de} = ${H.broadcastedIndicesToOffset(`outputIndices${de}`,q)}; + let index${de} = offset${de} / 4u; + let component${de} = offset${de} % 4u; + ${te}[${de}] = ${we}(${H.getByOffset(`index${de}`)}[component${de}]); + `;v=` + let outputOffset = global_idx * ${f}; + var data = vec4(0); + ${oe("data",0,"u32")} + ${oe("data",1,"u32")} + ${oe("data",2,"u32")} + ${oe("data",3,"u32")} + ${q.setByOffset("global_idx","data")} + }`}else v=` + let outputIndices = ${q.offsetToIndices("global_idx")}; + let inputOffset = ${H.broadcastedIndicesToOffset("outputIndices",q)}; + ${q.setByOffset("global_idx",H.getByOffset("inputOffset"))} + }`;return` + ${$.registerUniform("vec_size","u32").declareVariables(H,q)} + ${$.mainStart()} + ${$.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")} + ${v}`},k=[{type:12,data:d},...At(i,u)];return{name:"Expand",shaderCache:{hint:`${u.length}`,inputDependencies:["rank"]},getShaderSource:x,getRunData:()=>({outputs:[{dims:u,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:k})}},bl=n=>{vl(n.inputs),n.compute(Sd(n.inputs),{inputs:[0]})}}),yf,Ed,vf=h(()=>{Zt(),Jt(),ar(),Ha(),yf=n=>{let i=n[0].dataType,s=ct.size(n[0].dims),u=ct.size(n[1].dims),c=u%4===0,f=d=>{let x=_t("x",i,[1],4),k=_t("bias",i,[1],4),$=Gt("y",i,[1],4),H=[{name:"output_vec_size",type:"u32"},{name:"bias_size",type:"u32"}],q=oe=>` + let bias${oe}_offset: u32 = (global_idx * 4 + ${oe}) % uniforms.bias_size; + let bias${oe} = ${k.getByOffset(`bias${oe}_offset / 4`)}[bias${oe}_offset % 4];`,v=c?` + let bias = ${k.getByOffset("global_idx % (uniforms.bias_size / 4)")};`:`${q(0)}${q(1)}${q(2)}${q(3)} + let bias = ${x.type.value}(bias0, bias1, bias2, bias3);`;return`${d.registerUniforms(H).declareVariables(x,k,$)} + + ${Va(Er(i))} + + ${d.mainStart(Un)} + ${d.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_vec_size")} + + let x = ${x.getByOffset("global_idx")}; + ${v} + let x_in = x + bias; + ${$.setByOffset("global_idx",Wa("x_in"))} + }`};return{name:"FastGeluWithBias",shaderCache:{hint:`${c}`,inputDependencies:["type","type"]},getShaderSource:f,getRunData:d=>({outputs:[{dims:d[0].dims,dataType:d[0].dataType}],programUniforms:[{type:12,data:Math.ceil(s/4)},{type:12,data:u}],dispatchGroup:{x:Math.ceil(s/Un/4)}})}},Ed=n=>{n.inputs.length<2||ct.size(n.inputs[1].dims)===0?Ec(n):n.compute(yf(n.inputs))}}),Cd,Pd,$d,Ad,bf=h(()=>{Zt(),Jt(),_r(),ar(),Cd=n=>{if(!n||n.length!==2)throw new Error("Gather requires 2 inputs.")},Pd=(n,i)=>{let s=n[0].dims,u=n[1].dims,c=s.length,f=ct.normalizeAxis(i.axis,c),d=s.slice(0);d.splice(f,1,...u);let x=s[f],k=n[0].dataType===9?4:1,$=Math.ceil(ct.size(d)/k),H=[{type:12,data:$},{type:6,data:x},{type:12,data:f},...At(n[0].dims,n[1].dims,d)],q=v=>{let oe=_t("data",n[0].dataType,n[0].dims.length,k),te=_t("inputIndices",n[1].dataType,n[1].dims.length),de=Gt("output",n[0].dataType,d.length,k),we=he=>{let De=u.length,Ae=`var indicesIndices${he} = ${te.type.indices}(0);`;for(let Ie=0;Ie1?`indicesIndices${he}[${Ie}]`:`indicesIndices${he}`} = ${d.length>1?`outputIndices${he}[uniforms.axis + ${Ie}]`:`outputIndices${he}`};`;Ae+=` + var idx${he} = ${te.getByIndices(`indicesIndices${he}`)}; + if (idx${he} < 0) { + idx${he} = idx${he} + uniforms.axisDimLimit; + } + var dataIndices${he} : ${oe.type.indices}; + `;for(let Ie=0,gt=0;Ie1?`dataIndices${he}[${Ie}]`:`dataIndices${he}`} = u32(idx${he});`,gt+=De):(Ae+=`${c>1?`dataIndices${he}[${Ie}]`:`dataIndices${he}`} = ${d.length>1?`outputIndices${he}[${gt}]`:`outputIndices${he}`};`,gt++);return Ae},be;if(n[0].dataType===9){let he=(De,Ae,Ie="")=>` + let outputIndices${Ae} = ${de.offsetToIndices(`outputOffset + ${Ae}u`)}; + ${we(Ae)}; + let offset${Ae} = ${oe.indicesToOffset(`dataIndices${Ae}`)}; + let index${Ae} = offset${Ae} / 4u; + let component${Ae} = offset${Ae} % 4u; + ${De}[${Ae}] = ${Ie}(${oe.getByOffset(`index${Ae}`)}[component${Ae}]); + `;be=` + let outputOffset = global_idx * ${k}; + var value = vec4(0); + ${he("value",0,"u32")} + ${he("value",1,"u32")} + ${he("value",2,"u32")} + ${he("value",3,"u32")} + ${de.setByOffset("global_idx","value")} + `}else be=` + let outputIndices = ${de.offsetToIndices("global_idx")}; + ${we("")}; + let value = ${oe.getByIndices("dataIndices")}; + ${de.setByOffset("global_idx","value")}; + `;return` + ${v.registerUniform("outputSize","u32").registerUniform("axisDimLimit","i32").registerUniform("axis","u32").declareVariables(oe,te,de)} + ${v.mainStart()} + ${v.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + ${be} + }`};return{name:"Gather",shaderCache:{hint:i.cacheKey,inputDependencies:["rank","rank"]},getRunData:()=>({outputs:[{dims:d,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil($/64)},programUniforms:H}),getShaderSource:q}},$d=n=>qt({axis:n.axis}),Ad=(n,i)=>{let s=n.inputs;Cd(s),n.compute(Pd(n.inputs,i))}}),Id,Fd,Od,zd,xf=h(()=>{Zt(),Jt(),_r(),ar(),Id=n=>{if(!n||n.length!==2)throw new Error("GatherElements requires 2 inputs.");if(n[0].dims.length<1)throw new Error("GatherElements requires that the data input be rank >= 1.");if(n[0].dims.length!==n[1].dims.length)throw new Error(`GatherElements requires that the data input and + indices input tensors be of same rank.`)},Fd=(n,i)=>{let s=n[0].dims,u=n[0].dataType,c=s.length,f=n[1].dims,d=n[1].dataType,x=ct.normalizeAxis(i.axis,c),k=s[x],$=f.slice(0),H=ct.size($),q=_t("input",u,c),v=_t("indicesInput",d,f.length),oe=Gt("output",u,$.length),te=[{type:12,data:H},{type:6,data:k},{type:12,data:x}];return te.push(...At(s,f,$)),{name:"GatherElements",shaderCache:{inputDependencies:["rank","rank"]},getRunData:()=>({outputs:[{dims:$,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(H/64)},programUniforms:te}),getShaderSource:de=>` + ${de.registerUniform("outputSize","u32").registerUniform("axisDimLimit","i32").registerUniform("axis","u32").declareVariables(q,v,oe)} + ${de.mainStart()} + ${de.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + + let outputIndices = ${oe.offsetToIndices("global_idx")}; + + var idx = ${v.getByOffset("global_idx")}; + if (idx < 0) { + idx = idx + uniforms.axisDimLimit; + } + var inputIndices = ${q.type.indices}(outputIndices); + ${q.indicesSet("inputIndices","uniforms.axis","u32(idx)")}; + let value = ${q.getByIndices("inputIndices")}; + + ${oe.setByOffset("global_idx","value")}; + }`}},Od=n=>qt({axis:n.axis}),zd=(n,i)=>{let s=n.inputs;Id(s),n.compute(Fd(n.inputs,i))}}),Dd,Ld,Rd,Mf,Bd=h(()=>{Zt(),Jt(),ar(),Dd=n=>{if(!n)throw new Error("Input is missing");if(n.length<2||n.length>3)throw new Error("Invaid input number.");if(n.length===3&&n[2].dims.length>2)throw new Error("Invalid input shape of C");if(n[0].dataType!==n[1].dataType||n.length===3&&n[0].dataType!==n[2].dataType)throw new Error("Input types are mismatched")},Ld=(n,i)=>{let s=n[0].dims.slice(),u=n[1].dims.slice(),[c,f,d]=Tr.getShapeOfGemmResult(s,i.transA,u,i.transB,n.length===3?n[2].dims:void 0),x=[c,f];if(!x)throw new Error("Can't use gemm on the given tensors");let k=ct.size(x),$=[{type:12,data:k},{type:12,data:c},{type:12,data:f},{type:12,data:d},{type:1,data:i.alpha},{type:1,data:i.beta}],H=["type","type"];n.length===3&&($.push(...At(n[2].dims)),H.push("rank")),$.push(...At(x));let q=v=>{let oe="";i.transA&&i.transB?oe="value += a[k * uniforms.M + m] * b[n * uniforms.K + k];":i.transA&&!i.transB?oe="value += a[k * uniforms.M + m] * b[k * uniforms.N + n];":!i.transA&&i.transB?oe="value += a[m * uniforms.K + k] * b[n * uniforms.K + k];":!i.transA&&!i.transB&&(oe="value += a[m * uniforms.K + k] * b[k * uniforms.N + n];");let te=i.alpha===1?"":"value *= uniforms.alpha;",de=_t("a",n[0].dataType,n[0].dims),we=_t("b",n[1].dataType,n[1].dims),be=de.type.value,he=null,De=[de,we];n.length===3&&(he=_t("c",n[2].dataType,n[2].dims.length),De.push(he));let Ae=Gt("output",n[0].dataType,x.length);De.push(Ae);let Ie=[{name:"output_size",type:"u32"},{name:"M",type:"u32"},{name:"N",type:"u32"},{name:"K",type:"u32"},{name:"alpha",type:"f32"},{name:"beta",type:"f32"}];return` + ${v.registerUniforms(Ie).declareVariables(...De)} + + ${v.mainStart()} + ${v.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + + let m = global_idx / uniforms.N; + let n = global_idx % uniforms.N; + + var value = ${be}(0); + for (var k: u32 = 0u; k < uniforms.K; k++) { + ${oe} + } + + ${te} + ${he!=null?`let cOffset = ${he.broadcastedIndicesToOffset("vec2(m, n)",Ae)}; value += ${be}(uniforms.beta) * ${he.getByOffset("cOffset")};`:""} + output[global_idx] = value; + }`};return{name:"Gemm",shaderCache:{hint:`${i.cacheKey}`,inputDependencies:H},getRunData:()=>({outputs:[{dims:x,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(k/64)},programUniforms:$}),getShaderSource:q}},Rd=n=>{let i=n.transA,s=n.transB,u=n.alpha,c=n.beta;return{transA:i,transB:s,alpha:u,beta:c,cacheKey:`${n.transA};${n.transB};${n.alpha===1}`}},Mf=(n,i)=>{Dd(n.inputs),n.compute(Ld(n.inputs,i))}}),Pn,Nd,jd,xl,Ud,Zo,Vd,Wd=h(()=>{Zt(),Jt(),_r(),pe(),zs(),ar(),yo(),Pn=(n,i)=>n.length>i&&n[i].dims.length>0&&ct.size(n[i].dims)>0?n[i]:void 0,Nd=(n,i)=>{let s=n[0],u=Pn(n,1),c=Pn(n,2),f=Pn(n,3),d=Pn(n,4),x=Pn(n,5),k=Pn(n,6),$=Pn(n,7);if(s.dims.length!==3&&s.dims.length!==5)throw new Error("Input query is expected to have 3 or 5 dimensions");let H=!1,q=s.dims[0],v=s.dims[1],oe=s.dims.length===3?H?s.dims[2]/3:s.dims[2]:i.numHeads*s.dims[4],te=v,de=0,we=0,be=Math.floor(oe/i.numHeads);if(k&&$){if(k.dims.length!==4)throw new Error('Input "past_key" is expected to have 4 dimensions');if(k.dims[0]!==q||k.dims[1]!==i.numHeads||k.dims[3]!==be)throw new Error('Input "past_key" shape (batch_size, num_heads, past_sequence_length, head_size)');if($.dims[0]!==q||$.dims[1]!==i.numHeads||$.dims[3]!==be)throw new Error('Input "past_value" shape (batch_size, num_heads, past_sequence_length, head_size)');if(k.dims[2]!==$.dims[2])throw new Error('Input "past_key" and "past_value" shall have same dim 2 (past_sequence_length)');if($.dims.length!==4)throw new Error('Input "past_value" is expected to have 4 dimensions');de=k.dims[2],we=k.dims[2]}else if(k||$)throw new Error('Input "past_key" and "past_value" shall be both present or both absent');let he;if(u){if(s.dims.length!==3)throw new Error('Input "query" is expected to have 3 dimensions when key is given');if(u.dims.length<3||u.dims.length>5)throw new Error('Input "key" is expected to have 3, 4, or 5 dimensions');if(s.dims[0]!==u.dims[0])throw new Error('Input "query" and "key" shall have same dim 0 (batch size)');if(u.dims.length===3){if(u.dims[2]!==s.dims[2])throw new Error('Input "query" and "key" shall have same dim 2 (hidden_size)');he=2,te=u.dims[1]}else if(u.dims.length===5){if(u.dims[2]!==i.numHeads||u.dims[3]!==2||u.dims[4]!==be)throw new Error('Expect "key" shape (batch_size, kv_sequence_length, num_heads, 2, head_size) for packed kv');if(c)throw new Error('Expect "value" be none when "key" has packed kv format.');he=5,te=u.dims[1]}else{if(u.dims[1]!==i.numHeads||u.dims[3]!==be)throw new Error('Expect "key" shape (batch_size, num_heads, kv_sequence_length, head_size) for past_key');he=0,te=u.dims[2]}}else{if(s.dims.length!==3&&s.dims.length!==5)throw new Error('Input "query" is expected to have 3 or 5 dimensions when key is empty');if(s.dims.length===5&&(s.dims[2]!==i.numHeads||s.dims[3]!==3))throw new Error('Expect "query" shape (batch_size, kv_sequence_length, num_heads, 3, head_size) for packed kv');he=3}if(f){if(f.dims.length!==1)throw new Error('Input "bias" is expected to have 1 dimension');if(c&&s.dims.length===5&&s.dims[3]===2)throw new Error("bias is not allowed for packed kv.")}let De=0;if(d){De=8;let vt=d.dims;throw vt.length===1?vt[0]===q?De=1:vt[0]===3*q+2&&(De=3):vt.length===2&&vt[0]===q&&vt[1]===te&&(De=5),De===8?new Error('Input "key_padding_mask" shape shall be (batch_size) or (batch_size, kv_sequence_length)'):new Error("Mask not supported")}let Ae=!1,Ie=oe;if(c){if(c.dims.length!==3&&c.dims.length!==4)throw new Error('Input "value" is expected to have 3 or 4 dimensions');if(s.dims[0]!==c.dims[0])throw new Error('Input "query" and "value" shall have same dim 0 (batch_size)');if(c.dims.length===3){if(te!==c.dims[1])throw new Error('Input "key" and "value" shall have the same dim 1 (kv_sequence_length)');Ie=c.dims[2]}else{if(te!==c.dims[2])throw new Error('Input "past_key" and "past_value" shall have the same dim 2 (kv_sequence_length)');Ie=c.dims[1]*c.dims[3],Ae=!0}}let gt=de+te,ut=!1;if(d)throw new Error("Key padding mask is not supported");if(x){if(x.dims.length!==4)throw new Error('Input "relative_position_bias" is expected to have 4 dimensions');if(x.dims[0]!==q&&x.dims[0]!==1||x.dims[1]!==i.numHeads||x.dims[2]!==v||x.dims[3]!==gt)throw new Error('Input "relative_position_bias" shape (batch_size, 1, sequence_length, kv_sequence_length)')}return{batchSize:q,sequenceLength:v,pastSequenceLength:de,kvSequenceLength:te,totalSequenceLength:gt,maxSequenceLength:we,inputHiddenSize:0,hiddenSize:oe,vHiddenSize:Ie,headSize:be,vHeadSize:Math.floor(Ie/i.numHeads),numHeads:i.numHeads,isUnidirectional:!1,pastPresentShareBuffer:!1,maskFilterValue:i.maskFilterValue,maskType:De,scale:i.scale,broadcastResPosBias:ut,passPastInKv:Ae,qkvFormat:he}},jd=n=>qt({...n}),xl=qt({perm:[0,2,1,3]}),Ud=(n,i,s,u,c,f,d)=>{let x=[u,c,f],k=ct.size(x),$=[{type:12,data:k},{type:12,data:d},{type:12,data:f}],H=q=>{let v=Gt("qkv_with_bias",i.dataType,x),oe=_t("qkv",i.dataType,x),te=_t("bias",s.dataType,x),de=[{name:"output_size",type:"u32"},{name:"bias_offset",type:"u32"},{name:"hidden_size",type:"u32"}];return` + ${q.registerUniforms(de).declareVariables(oe,te,v)} + ${q.mainStart()} + ${q.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + let bias_offset_idx = (global_idx % uniforms.hidden_size) + uniforms.bias_offset; + + qkv_with_bias[global_idx] = qkv[global_idx] + bias[bias_offset_idx]; + }`};return n.compute({name:"MultiHeadAttentionAddBias",shaderCache:{inputDependencies:["type","type"]},getRunData:()=>({outputs:[{dims:x,dataType:i.dataType,gpuDataType:0}],dispatchGroup:{x:Math.ceil(k/64)},programUniforms:$}),getShaderSource:H},{inputs:[i,s],outputs:[-1]})[0]},Zo=(n,i,s,u,c,f,d,x)=>{let k=f;if(d){if(u===1)throw new Error("AddBiasReshape is not implemented. Please export your model with packed QKV or KV");return k=Ud(n,f,d,i,u,s*c,x),k=k.reshape([i,u,s,c]),n.compute(hi(k,xl.perm),{inputs:[k],outputs:[-1]})[0]}else return f.dims.length===3&&(k=f.reshape([i,u,s,c])),n.compute(hi(k,xl.perm),{inputs:[k],outputs:[-1]})[0]},Vd=(n,i)=>{let s=Nd(n.inputs,i),u=n.inputs[0],c=Pn(n.inputs,1),f=Pn(n.inputs,2),d=Pn(n.inputs,3),x=Pn(n.inputs,4),k=Pn(n.inputs,5),$=Pn(n.inputs,6),H=Pn(n.inputs,7);if(u.dims.length===5)throw new Error("Packed QKV is not implemented");if((c==null?void 0:c.dims.length)===5)throw new Error("Packed KV is not implemented");let q=c&&f&&c.dims.length===4&&f.dims.length===4,v=Zo(n,s.batchSize,s.numHeads,s.sequenceLength,s.headSize,u,d,0);if(q)return vo(n,v,c,f,x,void 0,$,H,k,s,i);if(!c||!f)throw new Error("key and value must be provided");let oe=Zo(n,s.batchSize,s.numHeads,s.kvSequenceLength,s.headSize,c,d,s.hiddenSize),te=Zo(n,s.batchSize,s.numHeads,s.kvSequenceLength,s.vHeadSize,f,d,2*s.hiddenSize);vo(n,v,oe,te,x,void 0,$,H,k,s,i)}}),Ml,Gd,Hd,Tl,qd,Kd=h(()=>{Zt(),Jt(),ar(),Ml=n=>Array.from(n.getBigInt64Array(),Number),Gd=n=>{if(!n||n.length!==2)throw new Error("Tile requires 2 inputs.");if(n[0].dataType!==1&&n[0].dataType!==10&&n[0].dataType!==6&&n[0].dataType!==12)throw new Error("Tile only support float, float16, int32, and uint32 data types");if(n[1].dataType!==7)throw new Error("Tile `repeats` input should be of int64 data type");if(n[1].dims.length!==1)throw new Error("Tile `repeats` input should be 1-D");if(Ml(n[1]).length!==n[0].dims.length)throw new Error("Tile `repeats` input should have same number of elements as rank of input data tensor")},Hd=(n,i)=>{let s=[];for(let u=0;u{let s=n[0].dims,u=i??Ml(n[1]),c=Hd(s,u),f=ct.size(c),d=n[0].dataType,x=_t("input",d,s.length),k=Gt("output",d,c.length),$=H=>` + const inputShape = ${x.indices(...s)}; + ${H.registerUniform("output_size","u32").declareVariables(x,k)} + ${H.mainStart()} + ${H.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + let output_indices = ${k.offsetToIndices("global_idx")}; + var input_indices: ${x.type.indices}; + for (var i = 0; i < ${s.length}; i++) { + let input_dim_i = ${x.indicesGet("uniforms.input_shape","i")}; + let input_dim_value = ${k.indicesGet("output_indices","i")} % input_dim_i; + + ${x.indicesSet("input_indices","i","input_dim_value")} + } + ${k.setByOffset("global_idx",x.getByIndices("input_indices"))} + }`;return{name:"Tile",shaderCache:{hint:`${u}`,inputDependencies:["rank"]},getRunData:()=>({outputs:[{dims:c,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(f/64)},programUniforms:[{type:12,data:f},...At(n[0].dims,c)]}),getShaderSource:$}},qd=n=>{Gd(n.inputs),n.compute(Tl(n.inputs),{inputs:[0]})}}),Xd,kl,Qd,Yd,Sl,Zd,Tf=h(()=>{Zt(),Jt(),_r(),zs(),ar(),Wd(),Kd(),yo(),Xd=(n,i)=>{let s=n[0],u=n[1],c=n[2],f=n[3],d=n[4];if(s.dims.length!==3&&s.dims.length!==5)throw new Error("Input query is expected to have 3 or 5 dimensions");let x=!1,k=s.dims[0],$=s.dims[1],H=s.dims.length===3?x?s.dims[2]/3:s.dims[2]:i.numHeads*s.dims[4],q=$,v=0,oe=0,te=Math.floor(H/i.numHeads),de=f&&f.dims.length!==0,we=d&&d.dims.length!==0,be=!0;if(de&&we){if(f.dims.length!==4)throw new Error('Input "past_key" is expected to have 4 dimensions');if(d.dims.length!==4)throw new Error('Input "past_value" is expected to have 4 dimensions');v=f.dims[1],oe=f.dims[1]}else if(de||we)throw new Error('Input "past_key" and "past_value" shall be both present or both absent');let he;if(u){if(s.dims.length!==3)throw new Error('Input "query" is expected to have 3 dimensions when key is given');if(u.dims.length<3||u.dims.length>5)throw new Error('Input "key" is expected to have 3, 4, or 5 dimensions');if(s.dims[0]!==u.dims[0])throw new Error('Input "query" and "key" shall have same dim 0 (batch size)');if(u.dims.length===3){if(s.dims[2]%u.dims[2]!==0)throw new Error('Dimension 2 of "query" should be a multiple of "key"');he=2,q=u.dims[1]}else if(u.dims.length===5){if(u.dims[2]!==i.numHeads||u.dims[3]!==2||u.dims[4]!==te)throw new Error('Expect "key" shape (batch_size, kv_sequence_length, num_heads, 2, head_size) for packed kv');if(c)throw new Error('Expect "value" be none when "key" has packed kv format.');he=5,q=u.dims[1]}else{if(u.dims[1]!==i.numHeads||u.dims[3]!==te)throw new Error('Expect "key" shape (batch_size, num_heads, kv_sequence_length, head_size) for past_key');he=0,q=u.dims[2]}}else{if(s.dims.length!==3&&s.dims.length!==5)throw new Error('Input "query" is expected to have 3 or 5 dimensions when key is empty');if(s.dims.length===5&&(s.dims[2]!==i.numHeads||s.dims[3]!==3))throw new Error('Expect "query" shape (batch_size, kv_sequence_length, num_heads, 3, head_size) for packed kv');he=3}let De=0,Ae=!1,Ie=H;if(c){if(c.dims.length!==3&&c.dims.length!==4)throw new Error('Input "value" is expected to have 3 or 4 dimensions');if(s.dims[0]!==c.dims[0])throw new Error('Input "query" and "value" shall have same dim 0 (batch_size)');if(c.dims.length===3){if(q!==c.dims[1])throw new Error('Input "key" and "value" shall have the same dim 1 (kv_sequence_length)');Ie=c.dims[2]}else{if(q!==c.dims[2])throw new Error('Input "past_key" and "past_value" shall have the same dim 2 (kv_sequence_length)');Ie=c.dims[1]*c.dims[3],Ae=!0}}let gt=v+q;return{batchSize:k,sequenceLength:$,pastSequenceLength:v,kvSequenceLength:q,totalSequenceLength:gt,maxSequenceLength:oe,inputHiddenSize:0,hiddenSize:H,vHiddenSize:Ie,headSize:te,vHeadSize:Math.floor(Ie/i.kvNumHeads),numHeads:i.numHeads,kvNumHeads:i.kvNumHeads,nReps:i.numHeads/i.kvNumHeads,pastPresentShareBuffer:!1,maskType:De,scale:i.scale,broadcastResPosBias:!1,passPastInKv:Ae,qkvFormat:he,isPastkvBSNH:be}},kl=(n,i,s,u)=>{let c=[u.batchSize,u.totalSequenceLength,u.kvNumHeads,u.headSize],f=4,d=ct.size(c)/f,x=u.totalSequenceLength,k=Gt("present_kv",s,c.length,f),$=_t("new_kv",n.dataType,n.dims.length,f),H=i?_t("past_kv",i.dataType,i.dims.length,f):void 0,q=Math.ceil(u.headSize/f),v={x,y:n.dims[0],z:1},oe=i?["rank","rank"]:["rank"],te=[{type:12,data:d},{type:12,data:u.pastSequenceLength},{type:12,data:u.kvSequenceLength},{type:12,data:u.totalSequenceLength}],de=[$];H?(te.push(...At(n.dims),...At(i.dims),...At(c)),de.push(H)):te.push(...At(n.dims),...At(c));let we=[{name:"output_size",type:"u32"},{name:"past_seqlen",type:"u32"},{name:"new_seqlen",type:"u32"},{name:"present_seqlen",type:"u32"}],be=` let past_batch_stride = uniforms.past_seqlen * num_heads * H; + var past_head_stride = uniforms.past_seqlen * H; + if (is_bsnh) { + past_head_stride = H; + } + let in_offset = b * past_batch_stride + s * row_stride + n * past_head_stride + h; + present_kv[out_offset] = past_kv[in_offset];`,he=` let new_batch_stride = uniforms.new_seqlen * num_heads * H; + let new_row_stride = num_heads * H; + let new_head_stride = H; + let in_offset = b * new_batch_stride + (s - past_seqlen) * new_row_stride + n * new_head_stride + h; + present_kv[out_offset] = new_kv[in_offset];`,De=i?`if (s < past_seqlen) { + ${be} + } else if (s < past_seqlen + uniforms.new_seqlen) { + ${he} + }`:`if (s < past_seqlen + uniforms.new_seqlen) { + ${he} + }`,Ae=Ie=>` + + ${Ie.registerUniforms(we).declareVariables(...de,k)} + ${Ie.mainStart([q,u.kvNumHeads,1])} + ${Ie.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + var indices = ${k.offsetToIndices("global_idx")}; + let h = local_id.x; + let n = local_id.y; + let s = workgroup_id.x; + let b = workgroup_id.y; + let num_heads = ${u.kvNumHeads}u; + let H = ${q}u; + + let present_seqlen = uniforms.present_seqlen; + let present_batch_stride = present_seqlen * num_heads * H; + var row_stride = H; + let is_bsnh = ${u.isPastkvBSNH}; + + if (is_bsnh) { + row_stride = num_heads * H; + } + var present_head_stride = present_seqlen * H; + if (is_bsnh) { + present_head_stride = H; + } + + let past_seqlen = uniforms.past_seqlen; + + let out_offset = b * present_batch_stride + s * row_stride + n * present_head_stride + h; + ${De} + }`;return{name:"ConcatPastNew",shaderCache:{hint:`${u.kvNumHeads}${q}${!!i}`,inputDependencies:oe},getRunData:()=>({outputs:[{dims:c,dataType:s}],dispatchGroup:v,programUniforms:te}),getShaderSource:Ae}},Qd=n=>qt({...n}),Yd=qt({perm:[0,2,1,3]}),Sl=(n,i,s,u,c)=>{let f=i,d=u.kvNumHeads,x=u.nReps;return i.dims.length===3&&u.kvSequenceLength!==0&&(f=i.reshape([u.batchSize,u.kvSequenceLength,d,u.headSize])),s?f=n.compute(kl(f,s,f.dataType,u),{inputs:[f,s],outputs:[u.isPastkvBSNH?c:-1]})[0]:f=n.compute(kl(f,void 0,f.dataType,u),{inputs:[f],outputs:[u.isPastkvBSNH?c:-1]})[0],x!==1&&(f=n.compute(Tl([f],[1,1,1,x]),{inputs:[f],outputs:[-1]})[0],f=f.reshape([u.batchSize,u.totalSequenceLength,d*x,u.headSize])),n.compute(hi(f,Yd.perm),{inputs:[f],outputs:[-1]})[0]},Zd=(n,i)=>{var k;let s=Xd(n.inputs,i);if(n.inputs[0].dims.length===5)throw new Error("Packed QKV is not implemented");if(((k=n.inputs[1])==null?void 0:k.dims.length)===5)throw new Error("Packed KV is not implemented");let u=Zo(n,s.batchSize,s.numHeads,s.sequenceLength,s.headSize,n.inputs[0],void 0,0),c=n.inputs[3]&&n.inputs[3].dims.length!==0?n.inputs[3]:void 0,f=n.inputs[4]&&n.inputs[4].dims.length!==0?n.inputs[4]:void 0,d=Sl(n,n.inputs[1],c,s,1),x=Sl(n,n.inputs[2],f,s,2);vo(n,u,d,x,void 0,void 0,void 0,void 0,void 0,s,i)}}),Jd,ep,tp,rp,wm=h(()=>{Zt(),Jt(),ar(),Jd=(n,i)=>{let s=n[0].dims,u=s,c=2,f=ct.sizeToDimension(s,c),d=ct.sizeFromDimension(s,c),x=vr(d),k=d/x,$=[s[0],s[1],k],H=["rank","type","type"],q=[{type:12,data:d},{type:12,data:k}];q.push(...At($,$));let v=oe=>{let te=_t("x",n[0].dataType,$.length,x),de=_t("scale",n[1].dataType,n[1].dims),we=_t("bias",n[2].dataType,n[2].dims),be=Gt("output",n[0].dataType,$.length,x),he=[te,de,we,be],De=te.type.value,Ae=x===1?"f32":`vec${x}`,Ie=64,gt=[{name:"normSize",type:"u32"},{name:"normPackedSize",type:"u32"}];return` + var meanShared : f32; + var squaredNormShared : f32; + var workgroupShared : array<${Ae}, ${Ie}>; + const workgroupSize = ${Ie}u; + ${oe.registerUniforms(gt).declareVariables(...he)} + ${oe.mainStart(Ie)} + let norm = global_idx / workgroupSize; + let batch = norm / uniforms.x_shape[1]; + let channel = norm % uniforms.x_shape[1]; + let localIndex = local_id.x; + + // initialize workgroup memory + var initial = ${Ae}(0); + for (var h = localIndex; h < uniforms.normPackedSize; h += workgroupSize) { + initial = initial + ${Ae}(${te.get("batch","channel","h")}); + } + workgroupShared[localIndex] = initial; + workgroupBarrier(); + + // Calculate the mean of current channel data. + for (var currSize = workgroupSize >> 1; currSize > 0; currSize = currSize >> 1) { + if (localIndex < currSize) { + workgroupShared[localIndex] = workgroupShared[localIndex] + workgroupShared[localIndex + currSize]; + } + workgroupBarrier(); + } + if (localIndex == 0) { + meanShared = ${Vn("workgroupShared[0]",x)} / f32(uniforms.normSize); + } + workgroupBarrier(); + + // reinitialize workgroup memory. + initial = ${Ae}(0); + for (var h = localIndex; h < uniforms.normPackedSize; h += workgroupSize) { + let deviation = ${Ae}(${te.get("batch","channel","h")}) - ${Ae}(meanShared); + initial = initial + deviation * deviation; + } + workgroupShared[localIndex] = initial; + workgroupBarrier(); + + // Calculate the sum of square of deviation of current channel data. + for (var currSize = workgroupSize >> 1; currSize > 0; currSize = currSize >> 1) { + if (localIndex < currSize) { + workgroupShared[localIndex] = workgroupShared[localIndex] + workgroupShared[localIndex + currSize]; + } + workgroupBarrier(); + } + if (localIndex == 0) { + squaredNormShared = ${Vn("workgroupShared[0]",x)}; + } + workgroupBarrier(); + + let invStdDev = inverseSqrt(squaredNormShared / f32(uniforms.normSize) + f32(${i.epsilon})); + let channelScale = invStdDev * f32(${de.getByOffset("channel")}); + let channelShift = f32(${we.getByOffset("channel")}) - meanShared * channelScale; + for (var h = localIndex; h < uniforms.normPackedSize; h += workgroupSize) { + let value = ${te.get("batch","channel","h")} * ${De}(${Ae}(channelScale)) + ${De}(${Ae}(channelShift)); + ${be.set("batch","channel","h","value")}; + } + }`};return{name:"InstanceNormalization",shaderCache:{hint:`${i.epsilon};${x}`,inputDependencies:H},getRunData:()=>({outputs:[{dims:u,dataType:n[0].dataType}],dispatchGroup:{x:f},programUniforms:q}),getShaderSource:v}},ep=(n,i,s,u,c,f,d,x)=>{let k=vr(d),$=64,H=k===1?"vec2f":`mat2x${k}f`,q=k===1?"f32":`vec${k}f`,v=(gt,ut)=>`${H}(${gt}, ${ut})`,oe=c*d/k,te=Math.ceil(f/$),de=["type"],we=[{type:12,data:te},{type:12,data:f},{type:12,data:Math.floor(d/k)},{type:12,data:Math.floor(f*d/k)}],be=gt=>{let ut=_t("input",i.dataType,i.dims,k);return` + ${gt.declareVariables(ut)} + @group(0) @binding(1) var output : array<${H}>; + struct Uniforms {wg_size:u32, H:u32, C:u32, image_size:u32}; + @group(0) @binding(2) var uniforms: Uniforms; + + ${gt.mainStart($)} + let currentImageNumber = global_idx / ${$} / uniforms.C; + let currentChannelNumber = (global_idx / ${$}) % uniforms.C; + let wgOffset = local_id.x * uniforms.wg_size; + if (wgOffset >= uniforms.H) { + return; + } + let wgMax = min(wgOffset + uniforms.wg_size, uniforms.H); + + let offset = currentImageNumber * uniforms.image_size + currentChannelNumber; + var sum = ${Lr("f32",k)}; + var squaredSum = ${Lr("f32",k)}; + for (var i: u32 = wgOffset; i < wgMax; i++) { + let value = ${q}(input[offset + i * uniforms.C]); + sum += value; + squaredSum += value * value; + } + output[global_idx] = ${v("sum","squaredSum")}; + }`},he=n.compute({name:"InstanceNormComputeMean",shaderCache:{hint:`${k}`,inputDependencies:de},getRunData:()=>({outputs:[{dims:[c,d,$,2],dataType:1}],dispatchGroup:{x:c*d/k},programUniforms:we}),getShaderSource:be},{inputs:[i],outputs:[-1]})[0],De=[{type:12,data:oe},{type:12,data:f},{type:12,data:Math.floor(d/k)},{type:12,data:Math.floor($*d/k)}],Ae=["type","type","type"],Ie=gt=>{let ut=_t("scale",s.dataType,s.dims,k),vt=_t("bias",u.dataType,u.dims,k);return` + @group(0) @binding(0) var input : array<${H}>; + @group(0) @binding(1) var scale : array<${ut.type.storage}>; + @group(0) @binding(2) var bias : array<${vt.type.storage}>; + @group(0) @binding(3) var output : array<${H}>; + struct Uniforms {units_of_work : u32, H: u32, C : u32, image_size : u32}; + @group(0) @binding(4) var uniforms: Uniforms; + + ${gt.mainStart()} + ${gt.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.units_of_work")} + let currentImageNumber = global_idx / uniforms.C; + let currentChannelNumber = global_idx % uniforms.C; + + let offset = currentImageNumber * uniforms.image_size; + var sum = ${Lr("f32",k)}; + var squaredSum = ${Lr("f32",k)}; + for (var i: u32 = 0; i < min(${$}, uniforms.H); i++) { + let value = input[offset + i + currentChannelNumber * ${$}]; + sum += value[0]; + squaredSum += value[1]; + } + sum = sum / f32(uniforms.H); + squaredSum = squaredSum / f32(uniforms.H); + let invStdDev = inverseSqrt(squaredSum - sum * sum + f32(${x})); + let channelScale = invStdDev * ${q}(scale[currentChannelNumber]); + let channelShift = ${q}(bias[currentChannelNumber]) - sum * channelScale; + + output[global_idx] = ${v("channelScale","channelShift")}; + }`};return n.compute({name:"InstanceNormComputeChannelScaleShift",shaderCache:{hint:`${k};${x}`,inputDependencies:Ae},getRunData:()=>({outputs:[{dims:[c,d,2],dataType:1}],dispatchGroup:{x:Math.ceil(oe/64)},programUniforms:De}),getShaderSource:Ie},{inputs:[he,s,u],outputs:[-1]})[0]},tp=(n,i,s)=>{let u=i[0].dims,c=u,f=u[0],d=u[u.length-1],x=ct.sizeFromDimension(u,1)/d,k=vr(d),$=ct.size(c)/k,H=[{type:12,data:x},{type:12,data:Math.floor(d/k)}],q=["type","type"],v=ep(n,i[0],i[1],i[2],f,x,d,s.epsilon),oe=te=>{let de=Sr(i[0].dataType),we=k===1?"vec2f":`mat2x${k}f`,be=k===1?de:`vec${k}<${de}>`,he=_t("input",i[0].dataType,i[0].dims,k),De=Gt("output",i[0].dataType,c,k);return` + @group(0) @binding(0) var input : array<${he.type.storage}>; + @group(0) @binding(1) var scaleInput : array<${we}>; + @group(0) @binding(2) var output : array<${De.type.storage}>; + struct Uniforms {H: u32, C : u32}; + @group(0) @binding(3) var uniforms: Uniforms; + + ${te.mainStart()} + let currentImageNumber = global_idx / (uniforms.C * uniforms.H); + let currentChannelNumber = global_idx % uniforms.C; + + let scaleOffset = currentImageNumber * uniforms.C + currentChannelNumber; + let scale = scaleInput[scaleOffset]; + output[global_idx] = fma(input[global_idx], ${be}(scale[0]), ${be}(scale[1])); + }`};n.compute({name:"InstanceNormalizationNHWC",shaderCache:{hint:`${k}`,inputDependencies:q},getRunData:()=>({outputs:[{dims:c,dataType:i[0].dataType}],dispatchGroup:{x:Math.ceil($/64)},programUniforms:H}),getShaderSource:oe},{inputs:[i[0],v]})},rp=(n,i)=>{i.format==="NHWC"?tp(n,n.inputs,i):n.compute(Jd(n.inputs,i))}}),ur,np,hn,bn=h(()=>{Zt(),Jt(),ar(),ur=n=>{if(!n||n.length<2)throw new Error("layerNorm requires at least 2 inputs.")},np=(n,i,s)=>{let u=i.simplified,c=n[0].dims,f=n[1],d=!u&&n[2],x=c,k=ct.normalizeAxis(i.axis,c.length),$=ct.sizeToDimension(c,k),H=ct.sizeFromDimension(c,k),q=ct.size(f.dims),v=d?ct.size(d.dims):0;if(q!==H||d&&v!==H)throw new Error(`Size of X.shape()[axis:] == ${H}. + Size of scale and bias (if provided) must match this. + Got scale size of ${q} and bias size of ${v}`);let oe=[];for(let Ie=0;Ie1,he=s>2,De=Ie=>{let gt=Sr(n[0].dataType),ut=[_t("x",n[0].dataType,n[0].dims,te),_t("scale",f.dataType,f.dims,te)];d&&ut.push(_t("bias",d.dataType,d.dims,te)),ut.push(Gt("output",n[0].dataType,x,te)),be&&ut.push(Gt("mean_data_output",1,oe)),he&&ut.push(Gt("inv_std_output",1,oe));let vt=[{name:"norm_count",type:"u32"},{name:"norm_size",type:"f32"},{name:"norm_size_vectorized",type:"u32"},{name:"epsilon",type:"f32"}];return` + ${Ie.registerUniforms(vt).declareVariables(...ut)} + ${Ie.mainStart()} + ${Ie.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.norm_count")} + let offset = global_idx * uniforms.norm_size_vectorized; + var mean_vector = ${Lr("f32",te)}; + var mean_square_vector = ${Lr("f32",te)}; + + for (var h: u32 = 0u; h < uniforms.norm_size_vectorized; h++) { + let value = ${Xr(gt,te,"x[h + offset]")}; + mean_vector += value; + mean_square_vector += value * value; + } + let mean = ${Vn("mean_vector",te)} / uniforms.norm_size; + let inv_std_dev = inverseSqrt(${Vn("mean_square_vector",te)} / uniforms.norm_size ${u?"":"- mean * mean"} + uniforms.epsilon); + + for (var j: u32 = 0; j < uniforms.norm_size_vectorized; j++) { + let f32input = ${Xr(gt,te,"x[j + offset]")}; + let f32scale = ${Xr(gt,te,"scale[j]")}; + output[j + offset] = ${ut[0].type.value}((f32input ${u?"":"- mean"}) * inv_std_dev * f32scale + ${d?`+ ${Xr(gt,te,"bias[j]")}`:""} + ); + } + + ${be?"mean_data_output[global_idx] = mean":""}; + ${he?"inv_std_output[global_idx] = inv_std_dev":""}; + }`},Ae=[{dims:x,dataType:n[0].dataType}];return be&&Ae.push({dims:oe,dataType:1}),he&&Ae.push({dims:oe,dataType:1}),{name:"LayerNormalization",shaderCache:{hint:`${te};${s};${u}`,inputDependencies:de},getRunData:()=>({outputs:Ae,dispatchGroup:{x:Math.ceil($/64)},programUniforms:we}),getShaderSource:De}},hn=(n,i)=>{ur(n.inputs),n.compute(np(n.inputs,i,n.outputCount))}}),xn,to,kf,ip,Sf=h(()=>{Zt(),Jt(),_r(),ar(),xn=(n,i)=>{if(n.length<3||n.length>4)throw new Error("MatMulNBits requires 3 or 4 inputs");let s=n[0],u=s.dims.length;if(s.dims[u-1]!==i.k)throw new Error("The last dim of input shape does not match the k value");let c=Math.floor((i.k+i.blockSize-1)/i.blockSize),f=i.blockSize/8*i.bits,d=n[1];if(!ct.areEqual(d.dims,[i.n,c,f]))throw new Error("The second inputs must be 3D tensor with shape N X nBlocksPerCol X blobSize");let x=n[2].dims;if(ct.size(x)!==i.n*c)throw new Error("scales input size error.");if(n.length===4){let k=n[3].dims,$=i.bits>4?i.n*c:i.n*Math.floor((c+1)/2);if(ct.size(k)!==$)throw new Error("zeroPoints input size error.")}},to=(n,i,s,u)=>{let c=n[0].dims,f=c.length,d=Math.floor((i.k+i.blockSize-1)/i.blockSize),x=c[f-2],k=i.k,$=i.n,H=c.slice(0,f-2),q=ct.size(H),v=i.blockSize/8*i.bits/4,oe=n[0].dataType,te=vr(x),de=vr(i.k),we=vr(v),be=ki(oe),he=x*d*be,De=Math.floor(u/he),Ae=d<=s[0]&&De>0,Ie=!Ae||De>=4?vr($):De>=2&&vr($)>=2?2:1,gt=H.concat([x,$]),ut=ct.size(gt)/Ie/te,vt=Ae?[]:[{type:12,data:ut},{type:12,data:i.blockSize}],Dt=[q,x,k/de],Rt=ct.convertShape(n[1].dims).slice();Rt.splice(-1,1,v/we),vt.push(...At(Dt)),vt.push(...At(Rt)),vt.push(...At(n[2].dims)),n.length===4&&vt.push(...At(ct.convertShape(n[3].dims)));let gr=[q,x,$/Ie];vt.push(...At(gr));let Mr=ir=>{let Fr=Dt.length,Zr=_t("a",n[0].dataType,Fr,de),hr=_t("b",12,Rt.length,we),Hr=_t("scales",n[2].dataType,n[2].dims.length),Nt=[Zr,hr,Hr],er=n.length===4?_t("zero_points",12,n[3].dims.length):void 0;er&&Nt.push(er);let yr=gr.length,ot=Gt("output",n[0].dataType,yr,Ie),Vt=[{name:"output_size",type:"u32"},{name:"block_size",type:"u32"}],nr=Sr(n[0].dataType),Wr=(()=>{switch(de){case 1:return`array<${nr}, 8>`;case 2:return`mat4x2<${nr}>`;case 4:return`mat2x4<${nr}>`;default:throw new Error(`${de}-component is not supported.`)}})(),pn=` + for (var word: u32 = 0; word < ${v}; word += ${we}) { + ${hr.indicesSet("b_indices","2","word")}; + let b_data = ${hr.getByIndices("b_indices")}; + for (var i: u32 = 0; i < ${we}; i++) { + let b_value: u32 = ${we===1?"b_data":"b_data[word + i]"}; + let b_mask: u32 = 0x0F0F0F0Fu; + let b_value_lower: vec4 = unpack4xU8(b_value & b_mask); + let b_value_upper: vec4 = unpack4xU8((b_value >> 4) & b_mask); + let b_quantized_values = ${Wr}(${Array.from({length:4},(rs,si)=>`${nr}(b_value_lower[${si}]), ${nr}(b_value_upper[${si}])`).join(", ")}); + let b_dequantized_values = ${de===1?`${Wr}(${Array.from({length:8},(rs,si)=>`(b_quantized_values[${si}] - zero_point) * scale`).join(", ")});`:`(b_quantized_values - ${Wr}(${Array(8).fill("zero_point").join(",")})) * scale;`}; + // Number of B elements per 32-bit word is 32/bits = 32/4 = 8 + for (var m: u32 = 0; m < ${Ae?x:te}u; m++) { + ${Zr.indicesSet("a_indices",Fr-2,Ae?"m":`row * ${te} + m`)}; + ${Zr.indicesSet("a_indices",Fr-1,"word_offset")}; + var input_offset = ${Zr.indicesToOffset("a_indices")}; + var a_data: ${Wr}; + for (var j: u32 = 0; j < ${8/de}; j++) { + a_data[j] = ${Zr.getByOffset("input_offset")}; + input_offset++; + } + ${Ae?"workgroup_shared[workgroup_shared_offset + m]":"output_values[m]"}${Ie>1?"[c]":""} += ${Array.from({length:8/de},(rs,si)=>`${de===1?`a_data[${si}] * b_dequantized_values[${si}]`:`dot(a_data[${si}], b_dequantized_values[${si}])`}`).join(" + ")}; + } + word_offset += ${8/de}; + } + }`,kn=er?` + zero_point_offset += 4; + if (zero_point_offset == 32) { + zero_point_offset = 0; + zero_point_index++; + zero_point_word = ${er.getByOffset("zero_point_index")}; + }`:"";return Ae?` + var workgroup_shared: array<${ot.type.value}, ${x*d}>; + ${ir.declareVariables(...Nt,ot)} + ${ir.mainStart([d,1,1])} + var a_indices: ${Zr.type.indices}; + var block = local_id.x; + var col = workgroup_id.y; + var batch = workgroup_id.z; + ${Zr.indicesSet("a_indices","0","batch")}; + // Two zero points are packed into one byte when uniforms.bits is 4. + for (var c: u32 = 0; c < ${Ie}; c++) { + let col_times_components_plus_c = col * ${Ie} + c; + ${er?` + var zero_point_bytes_per_col: u32 = (${d} + 1) / 2; + var zero_point_byte_count: u32 = col_times_components_plus_c * zero_point_bytes_per_col + (block >> 0x1u); + var zero_point_word_index: u32 = zero_point_byte_count >> 0x2u; + var zero_point_byte_offset: u32 = zero_point_byte_count & 0x3u; + var zero_point_nibble_offset: u32 = block & 0x1u; + var zero_point_bits_offset: u32 = (zero_point_byte_offset << 3) + (zero_point_nibble_offset << 2); + var zero_point_word: u32 = ${er.getByOffset("zero_point_word_index")} >> zero_point_bits_offset;`:""} + var b_indices: ${hr.type.indices}; + ${hr.indicesSet("b_indices","0","col_times_components_plus_c")}; + // The scale and zero points are computed per block. + var scales_index = col_times_components_plus_c * ${d} + block; + let scale = ${Hr.getByOffset("scales_index")}; + // The default zero point is 8 for unsigned 4-bit quantization. + let zero_point = ${nr}(${er?"(zero_point_word) & 0xFu":8}); + ${hr.indicesSet("b_indices","1","block")}; + var word_offset: u32 = block * ${i.blockSize/de}; + var workgroup_shared_offset: u32 = block * ${x}; + ${pn} + } + workgroupBarrier(); + var output_indices: ${ot.type.indices}; + var elements_per_thread: u32 = ${Math.ceil(x/d)}; + ${ot.indicesSet("output_indices","0","batch")}; + ${ot.indicesSet("output_indices",yr-1,"col")}; + ${ot.indicesSet("output_indices",yr-2,"local_id.x * elements_per_thread")}; + var output_offset = ${ot.indicesToOffset("output_indices")}; + for (var m: u32 = 0u; m < elements_per_thread; m++) { + var row = m + local_id.x * elements_per_thread; + if (row < ${x}) { + var output_value: ${ot.type.value} = ${ot.type.value}(0); + var workgroup_shared_offset: u32 = row; + for (var b: u32 = 0u; b < ${d}u; b++) { + output_value += workgroup_shared[workgroup_shared_offset]; + workgroup_shared_offset += ${x}; + } + ${ot.setByOffset("output_offset","output_value")}; + output_offset += ${$/Ie}; + } + } + }`:` + ${ir.registerUniforms(Vt).declareVariables(...Nt,ot)} + ${ir.mainStart()} + ${ir.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + var output_values: array<${ot.type.value}, ${te}>; + var output_indices = ${ot.offsetToIndices("global_idx")}; + var col = ${ot.indicesGet("output_indices",yr-1)}; + var row = ${ot.indicesGet("output_indices",yr-2)}; + var a_indices: ${Zr.type.indices} = output_indices; + // Two zero points are packed into one byte because uniforms.bits <= 4. + // zero_point_offset is either 0 or 4. It is bit offset within one byte. + // TODO support zero_point_offset for bits > 4 + ${er?` + var zero_point_abs_offset = col * ${Ie} * ((${d} + 1) / 2); + var zero_point_index: u32 = zero_point_abs_offset / 4; + var zero_point_word: u32 = ${er.getByOffset("zero_point_index")}; + var zero_point_offset: u32 = (zero_point_abs_offset % 4) * 8;`:""} + var scale_index = col * ${d*Ie}; + var b_indices: ${hr.type.indices}; + for (var c: u32 = 0; c < ${Ie}; c++) { + ${hr.indicesSet("b_indices","0",`col * ${Ie} + c`)}; + var block_offset: u32 = 0; + for (var block: u32 = 0; block < ${d}; block++) { + // The scale and zero points are computed per block. + let scale = ${Hr.getByOffset("scale_index")}; + // The default zero point is 8 for unsigned 4-bit quantization. + let zero_point = ${nr}(${er?"extractBits(zero_point_word, zero_point_offset, 4)":8}); + ${hr.indicesSet("b_indices","1","block")}; + var word_offset: u32 = block_offset; + ${pn} + scale_index++; + ${kn} + block_offset += uniforms.block_size / ${de}; + } + // Drop the trailing 4 bits if the zero_poit_offset is not a byte boundary to align with the next byte. + ${er?`if (zero_point_offset % 8 > 0) { + ${kn} + }`:""} + } + for (var k: u32 = 0u; k < ${te}u; k++) { + ${ot.indicesSet("output_indices",yr-2,`${te} * row + k`)}; + ${ot.setByIndices("output_indices","output_values[k]")} + } + }`};return{name:Ae?"BlockwiseMatMulNBits":"MatMulNBits",shaderCache:{hint:`${i.cacheKey};${x};${oe};${n.length}`,inputDependencies:Array(n.length).fill("rank")},getRunData:()=>({outputs:[{dims:gt,dataType:oe}],name:Ae?"BlockwiseMatMulNBits":"MatMulNBits",dispatchGroup:Ae?{x:1,y:Math.ceil($/Ie),z:q}:{x:Math.ceil(ut/64)},programUniforms:vt}),getShaderSource:Mr}},kf=(n,i)=>{xn(n.inputs,i);let s=n.getMaxComputeWorkgroupSizes(),u=n.getMaxComputeWorkgroupStoragesize();n.compute(to(n.inputs,i,s,u))},ip=n=>qt(n)}),V,G,ne,Ee,Ze,it,wt,Ct,Wt,cr=h(()=>{Zt(),Jt(),ar(),V=n=>{if(!n||n.length<1)throw new Error("Too few inputs");if(n[0].dataType!==1&&n[0].dataType!==10)throw new Error("Input type must be float or float16.");if(n.length>=2){let i=n[0].dims.length*2===n[1].dims[0];if(n.length===4&&(i=n[3].dims[0]*2===n[1].dims[0]),!i)throw new Error("The pads should be a 1D tensor of shape [2 * input_rank] or [2 * num_axes].")}},G=(n,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=` + k = i32(${n.indicesGet("indices",c)}) - ${zt("uniforms.pads",c,s)}; + if (k < 0) { + break; + } + if (k >= i32(${zt("uniforms.x_shape",c,i)})) { + break; + } + offset += k * i32(${zt("uniforms.x_strides",c,i)}); + `;return` + value = ${n.type.value}(uniforms.constant_value); + for (var i = 0; i < 1; i++) { + var offset = 0; + var k = 0; + ${u} + value = x[offset]; + } + `},ne=(n,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=` + k = i32(${n.indicesGet("indices",c)}) - ${zt("uniforms.pads",c,s)}; + if (k < 0) { + k = -k; + } + { + let _2n_1 = 2 * (i32(${zt("uniforms.x_shape",c,i)}) - 1); + k = k % _2n_1; + if(k >= i32(${zt("uniforms.x_shape",c,i)})) { + k = _2n_1 - k; + } + } + offset += k * i32(${zt("uniforms.x_strides",c,i)}); + `;return` + var offset = 0; + var k = 0; + ${u} + value = x[offset]; + `},Ee=(n,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=` + k = i32(${n.indicesGet("indices",c)}) - ${zt("uniforms.pads",c,s)}; + if (k < 0) { + k = 0; + } + if (k >= i32(${zt("uniforms.x_shape",c,i)})) { + k = i32(${zt("uniforms.x_shape",c,i)}) - 1; + } + offset += k * i32(${zt("uniforms.x_strides",c,i)}); + `;return` + var offset = 0; + var k = 0; + ${u} + value = x[offset]; + `},Ze=(n,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=` + k = i32(${n.indicesGet("indices",c)}) - ${zt("uniforms.pads",c,s)}; + if (k < 0) { + k += i32(${zt("uniforms.x_shape",c,i)}]); + } + if (k >= i32(${zt("uniforms.x_shape",c,i)})) { + k -= i32(${zt("uniforms.x_shape",c,i)}); + } + offset += k * i32(${zt("uniforms.x_strides",c,i)}); + `;return` + var offset = 0; + var k = 0; + ${u} + value = x[offset]; + `},it=(n,i,s)=>{switch(s.mode){case 0:return G(n,i,s.pads.length);case 1:return ne(n,i,s.pads.length);case 2:return Ee(n,i,s.pads.length);case 3:return Ze(n,i,s.pads.length);default:throw new Error("Invalid mode")}},wt=(n,i)=>{let s=ct.padShape(n[0].dims.slice(),i.pads),u=n[0].dims,c=ct.size(s),f=[{type:12,data:c},{type:6,data:i.pads}];i.mode===0&&f.push({type:n[0].dataType,data:i.value}),f.push(...At(n[0].dims,s));let d=["rank"],x=k=>{let $=Gt("output",n[0].dataType,s.length),H=_t("x",n[0].dataType,u.length),q=H.type.value,v=it($,u.length,i),oe=[{name:"output_size",type:"u32"},{name:"pads",type:"i32",length:i.pads.length}];return i.mode===0&&oe.push({name:"constant_value",type:q}),` + ${k.registerUniforms(oe).declareVariables(H,$)} + ${k.mainStart()} + ${k.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + + let indices = ${$.offsetToIndices("global_idx")}; + + var value = ${q}(0); + ${v} + output[global_idx] = value; + }`};return{name:"Pad",shaderCache:{hint:`${i.mode}`,inputDependencies:d},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(ct.size(s)/64)},programUniforms:f}),getShaderSource:x}},Ct=(n,i)=>{if(n.length>1){let s=n[1].getBigInt64Array(),u=n.length>=3&&n[2].data?n[2].getFloat32Array()[0]:0,c=n[0].dims.length,f=new Int32Array(2*c).fill(0);if(n.length>=4){let x=n[3].getBigInt64Array();for(let k=0;kf[Number(k)]=Number(x));let d=[];return f.forEach(x=>d.push(x)),{mode:i.mode,value:u,pads:d}}else return i},Wt=(n,i)=>{V(n.inputs);let s=Ct(n.inputs,i);n.compute(wt(n.inputs,s),{inputs:[0]})}}),lr,Ir,dr,wr,pr,mr,xr,Nr,$n,zn,Pi,Mn,dn,Tn,qs,Ks,El,ym,mi,Jo=h(()=>{Z(),Zt(),Jt(),ar(),lr=n=>{if(N.webgpu.validateInputContent&&(!n||n.length!==1))throw new Error("Pool ops requires 1 input.")},Ir=(n,i,s)=>{let u=i.format==="NHWC",c=n.dims.slice();u&&c.splice(1,0,c.pop());let f=Object.hasOwnProperty.call(i,"dilations"),d=i.kernelShape.slice(),x=i.strides.slice(),k=f?i.dilations.slice():[],$=i.pads.slice();Kn.adjustPoolAttributes(s,c,d,x,k,$);let H=Kn.computePoolOutputShape(s,c,x,k,d,$,i.autoPad),q=Object.assign({},i);f?Object.assign(q,{kernelShape:d,strides:x,pads:$,dilations:k,cacheKey:i.cacheKey}):Object.assign(q,{kernelShape:d,strides:x,pads:$,cacheKey:i.cacheKey});let v=H.slice();return v.push(v.splice(1,1)[0]),[q,u?v:H]},dr=(n,i)=>{let s=i.format==="NHWC",u=ct.size(n),c=ct.size(i.kernelShape),f=[{type:12,data:u},{type:12,data:c}],d=[{name:"outputSize",type:"u32"},{name:"kernelSize",type:"u32"}];if(i.kernelShape.length<=2){let x=i.kernelShape[i.kernelShape.length-1],k=i.strides[i.strides.length-1],$=i.pads[i.pads.length/2-1],H=i.pads[i.pads.length-1],q=!!($+H);f.push({type:12,data:x},{type:12,data:k},{type:12,data:$},{type:12,data:H}),d.push({name:"kw",type:"u32"},{name:"sw",type:"u32"},{name:"pwStart",type:"u32"},{name:"pwEnd",type:"u32"});let v=!1;if(i.kernelShape.length===2){let oe=i.kernelShape[i.kernelShape.length-2],te=i.strides[i.strides.length-2],de=i.pads[i.pads.length/2-2],we=i.pads[i.pads.length-2];v=!!(de+we),f.push({type:12,data:oe},{type:12,data:te},{type:12,data:de},{type:12,data:we}),d.push({name:"kh",type:"u32"},{name:"sh",type:"u32"},{name:"phStart",type:"u32"},{name:"phEnd",type:"u32"})}return[f,d,!0,q,v]}else{if(s)throw new Error("Pooling with kernelShape.length > 2 is not supported for NHWC format.");let x=ct.computeStrides(i.kernelShape);f.push({type:12,data:x},{type:12,data:i.pads},{type:12,data:i.strides}),d.push({name:"kernelStrides",type:"u32",length:x.length},{name:"pads",type:"u32",length:i.pads.length},{name:"strides",type:"u32",length:i.strides.length});let k=i.pads.reduce(($,H)=>$+H);return[f,d,!!k,!1,!1]}},wr=(n,i,s,u,c,f,d,x,k,$,H,q)=>{let v=c.format==="NHWC",oe=i.type.value,te=Gt("output",i.type.tensor,u);if(c.kernelShape.length<=2){let de="",we="",be="",he=s-(v?2:1);if(H?de=` + for (var i: u32 = 0u; i < uniforms.kw; i++) { + xIndices[${he}] = indices[${he}] * uniforms.sw - uniforms.pwStart + i; + if (xIndices[${he}] < 0 || xIndices[${he}] + >= uniforms.x_shape[${he}]) { + pad++; + continue; + } + let x_val = x[${i.indicesToOffset("xIndices")}]; + ${f} + }`:de=` + for (var i: u32 = 0u; i < uniforms.kw; i++) { + xIndices[${he}] = indices[${he}] * uniforms.sw - uniforms.pwStart + i; + let x_val = x[${i.indicesToOffset("xIndices")}]; + ${f} + }`,c.kernelShape.length===2){let De=s-(v?3:2);q?we=` + for (var j: u32 = 0u; j < uniforms.kh; j++) { + xIndices[${De}] = indices[${De}] * uniforms.sh - uniforms.phStart + j; + if (xIndices[${De}] < 0 || xIndices[${De}] >= uniforms.x_shape[${De}]) { + pad += i32(uniforms.kw); + continue; + } + `:we=` + for (var j: u32 = 0u; j < uniforms.kh; j++) { + xIndices[${De}] = indices[${De}] * uniforms.sh - uniforms.phStart + j; + `,be=` + } + `}return` + ${n.registerUniforms(k).declareVariables(i,te)} + + ${n.mainStart()} + ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + + let indices = ${te.offsetToIndices("global_idx")}; + var xIndices = ${te.offsetToIndices("global_idx")}; + + var value = ${oe}(${x}); + var pad = 0; + ${we} + ${de} + ${be} + ${d} + + output[global_idx] = value; + }`}else{if(v)throw new Error("Pooling with kernelShape.length > 2 is not supported for NHWC format.");let de=c.kernelShape.length,we=c.pads.length,be="";return $?be=` + if (xIndices[j] >= uniforms.x_shape[j]) { + pad++; + isPad = true; + break; + } + } + if (!isPad) { + let x_val = x[${i.indicesToOffset("xIndices")}]; + ${f} + }`:be=` + } + let x_val = x[${i.indicesToOffset("xIndices")}]; + ${f} + `,` + ${n.registerUniforms(k).declareVariables(i,te)} + + ${n.mainStart()} + ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + let indices = ${te.offsetToIndices("global_idx")}; + var xIndices = ${te.offsetToIndices("global_idx")}; + + var offsets: array; + + var value = ${oe}(${x}); + var pad = 0; + var isPad = false; + + for (var i: u32 = 0u; i < uniforms.kernelSize; i++) { + var offset = i; + for (var j = 0u; j < ${de-1}u; j++) { + offsets[j] = offset / ${zt("uniforms.kernelStrides","j",de)}; + offset -= offsets[j] * ${zt("uniforms.kernelStrides","j",de)}; + } + offsets[${de-1}] = offset; + + isPad = false; + for (var j = ${s-de}u; j < ${s}u; j++) { + xIndices[j] = indices[j] * ${zt("uniforms.strides",`j - ${s-de}u`,de)} + + offsets[j - ${s-de}u] - ${zt("uniforms.pads","j - 2u",we)}; + ${be} + } + ${d} + + output[global_idx] = value; + }`}},pr=n=>`${n.format};${n.ceilMode};${n.autoPad};${n.kernelShape.length}`,mr=n=>`${pr(n)};${n.countIncludePad}`,xr=n=>`${pr(n)};${n.storageOrder};${n.dilations}`,Nr=n=>({format:n.format,autoPad:["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][n.auto_pad],ceilMode:n.ceil_mode,kernelShape:n.kernel_shape,strides:n.strides,pads:n.pads}),$n=(n,i,s,u)=>{let[c,f]=Ir(i,u,s),d=_t("x",i.dataType,i.dims.length),x=d.type.value,k="value += x_val;",$="";c.countIncludePad?$+=`value /= ${x}(uniforms.kernelSize);`:$+=`value /= ${x}(i32(uniforms.kernelSize) - pad);`;let[H,q,v,oe,te]=dr(f,c);H.push(...At(i.dims,f));let de=["rank"];return{name:n,shaderCache:{hint:`${u.cacheKey};${v};${oe};${te}`,inputDependencies:de},getRunData:()=>({outputs:[{dims:f,dataType:i.dataType}],dispatchGroup:{x:Math.ceil(ct.size(f)/64)},programUniforms:H}),getShaderSource:we=>wr(we,d,i.dims.length,f.length,c,k,$,0,q,v,oe,te)}},zn=n=>{let i=n.count_include_pad!==0,s=Nr(n);if(s.ceilMode!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");let u={countIncludePad:i,...s,cacheKey:""};return{...u,cacheKey:mr(u)}},Pi=(n,i)=>{lr(n.inputs),n.compute($n("AveragePool",n.inputs[0],!1,i))},Mn={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[]},dn=n=>{let i=n.format;return{format:i,...Mn,cacheKey:i}},Tn=(n,i)=>{lr(n.inputs),n.compute($n("GlobalAveragePool",n.inputs[0],!0,i))},qs=(n,i,s,u)=>{let[c,f]=Ir(i,u,s),d=` + value = max(x_val, value); + `,x="",k=_t("x",i.dataType,i.dims.length),$=["rank"],[H,q,v,oe,te]=dr(f,c);return H.push(...At(i.dims,f)),{name:n,shaderCache:{hint:`${u.cacheKey};${v};${oe};${te}`,inputDependencies:$},getRunData:()=>({outputs:[{dims:f,dataType:i.dataType}],dispatchGroup:{x:Math.ceil(ct.size(f)/64)},programUniforms:H}),getShaderSource:de=>wr(de,k,i.dims.length,f.length,c,d,x,i.dataType===10?-65504:-1e5,q,v,oe,te)}},Ks=(n,i)=>{lr(n.inputs),n.compute(qs("MaxPool",n.inputs[0],!1,i))},El=n=>{let i=n.storage_order,s=n.dilations,u=Nr(n);if(i!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(u.ceilMode!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");let c={storageOrder:i,dilations:s,...u,cacheKey:""};return{...c,cacheKey:xr(c)}},ym=n=>{let i=n.format;return{format:i,...Mn,cacheKey:i}},mi=(n,i)=>{lr(n.inputs),n.compute(qs("GlobalMaxPool",n.inputs[0],!0,i))}}),Ef,Cf,Pf,$f=h(()=>{Z(),Zt(),ar(),Ef=(n,i,s)=>{let u=n===i,c=ni&&s>0;if(u||c||f)throw new Error("Range these inputs' contents are invalid.")},Cf=(n,i,s,u)=>{let c=Math.abs(Math.ceil((i-n)/s)),f=[c],d=c,x=[{type:12,data:d},{type:u,data:n},{type:u,data:s},...At(f)],k=$=>{let H=Gt("output",u,f.length),q=H.type.value,v=[{name:"outputSize",type:"u32"},{name:"start",type:q},{name:"delta",type:q}];return` + ${$.registerUniforms(v).declareVariables(H)} + ${$.mainStart()} + ${$.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + output[global_idx] = uniforms.start + ${q}(global_idx) * uniforms.delta; + }`};return{name:"Range",shaderCache:{hint:`${u}`},getShaderSource:k,getRunData:()=>({outputs:[{dims:f,dataType:u}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:x})}},Pf=n=>{let i=0,s=0,u=0;n.inputs[0].dataType===6?(i=n.inputs[0].getInt32Array()[0],s=n.inputs[1].getInt32Array()[0],u=n.inputs[2].getInt32Array()[0]):n.inputs[0].dataType===1&&(i=n.inputs[0].getFloat32Array()[0],s=n.inputs[1].getFloat32Array()[0],u=n.inputs[2].getFloat32Array()[0]),N.webgpu.validateInputContent&&Ef(i,s,u),n.compute(Cf(i,s,u,n.inputs[0].dataType),{inputs:[]})}}),b0,x0,M0,T0,k0,S0,E0,C0,P0,$0,A0,vm,I0,F0,O0,z0,D0,L0,R0,nx=h(()=>{Zt(),Jt(),_r(),ar(),b0=(n,i)=>{if(n.every(s=>s>0||(()=>{throw new Error("Resize requires scales input values to be positive")})),n.length>0){if(i.mode==="linear"){if(!(n.length===2||n.length===3||n.length===4&&n[0]===1&&n[1]===1||n.length===4&&n[0]===1&&n[3]===1||n.length===5&&n[0]===1&&n[1]===1))throw new Error(`For linear mode, Resize requires scales to be 2D, 3D, 4D with either two outermost or one innermost and + one outermost scale values equal to 1, or 5D with two outermost scale values equal to 1`)}else if(i.mode==="cubic"&&!(n.length===2||n.length===4&&n[0]===1&&n[1]===1||n.length===4&&n[0]===1&&n[3]===1))throw new Error("Resize requires scales input size to be 2 or 4 for cubic mode")}},x0=(n,i,s)=>{i.every(c=>c>=0&&c{throw new Error("Resize requires axes input values to be positive and less than rank")}));let u=new Array(s).fill(1);return i.forEach((c,f)=>u[c]=n[f]),u},M0=(n,i,s,u,c,f)=>{let[d,x,k]=s>10?[1,2,3]:[-1,n.length>1?1:-1,-1],$=n[0].dims.length;if(d>0&&n.length>d&&n[d].dims.length>0)n[d].getFloat32Array().forEach(H=>f.push(H));else if(i.coordinateTransformMode==="tf_crop_and_resize")throw new Error("Resize requires RoI input to be specified when coordinateTransformMode is tfCropAndResize");if(x>0&&n.length>x&&n[x].dims.length>0){if(n[x].getFloat32Array().forEach(H=>u.push(H)),u.length!==0&&u.length!==$&&s>=18&&u.length!==i.axes.length)throw new Error("Resize requires scales input size to be same as input rank or axes size for opset 18 and up");b0(u,i),i.axes.length>0&&x0(u,i.axes,$).forEach((H,q)=>u[q]=H)}if(k>0&&n.length>k&&(n[k].getBigInt64Array().forEach(H=>c.push(Number(H))),c.length!==$||s>=18&&c.length===i.axes.length))throw new Error("Resize requires sizes input size to be same as input rank or axes size for opset 18 and up");if(i.axes.length>0){if(u.length!==i.axes.length)throw new Error('Resize requires "scales" input size to be of axes rank when axes attributes is specified');if(c.length!==i.axes.length)throw new Error('Resize requires "sizes" input size to be of rank axes rank when axes attributes is specified')}if(typeof u<"u"&&typeof c<"u"&&u.length>0&&c.length>$)throw new Error("Resize requires only of scales or sizes to be specified")},T0=(n,i)=>`fn getOriginalCoordinateFromResizedCoordinate(xResized: u32, xScale: f32, lengthResized: u32, + lengthOriginal: u32, roiStart: f32, roiEnd: f32) -> ${i} { `+(()=>{switch(n){case"asymmetric":return`return ${i}(xResized) / ${i}(xScale);`;case"pytorch_half_pixel":return`if (lengthResized > 1) { + return (${i}(xResized) + 0.5) / ${i}(xScale) - 0.5; + } else { + return 0.0; + }`;case"tf_half_pixel_for_nn":return`return (${i}(xResized) + 0.5) / ${i}(xScale);`;case"align_corners":return`if (lengthResized == 1) { + return 0.0; + } else { + // The whole part and the fractional part are calculated separately due to inaccuracy of floating + // point division. As an example, f32(21) / f32(7) may evaluate to 2.99... instead of 3, causing an + // offset-by-one error later in floor(). + let whole = ${i}(xResized * (lengthOriginal - 1) / (lengthResized - 1)); + let fract = + ${i}(xResized * (lengthOriginal - 1) % (lengthResized - 1)) / ${i}(lengthResized - 1); + return whole + fract; + }`;case"tf_crop_and_resize":return`if (lengthResized > 1) { + return ${i}(roiStart) * ${i}(lengthOriginal - 1) + + (${i}(xResized) * ${i}(roiEnd - roiStart) * ${i}(lengthOriginal - 1)) / + ${i}(lengthResized - 1); + } else { + return 0.5 * ${i}(roiStart + roiEnd) * ${i}(lengthOriginal - 1); + }`;case"half_pixel_symmetric":return`const outputWidth = ${i}xScale * ${i}(lengthResized); + const adjustment = ${i}(lengthResized) / outputWidth; + const center = ${i}(lengthOriginal) / 2; + const offset = center * (1 - adjustment); + return offset + ((${i}(xResized) + 0.5) / ${i}(xScale)) - 0.5;`;case"half_pixel":return`return ((${i}(xResized) + 0.5) / ${i}(xScale)) - 0.5;`;default:throw new Error(`Coordinate transform mode ${n} is not supported`)}})()+"}",k0=(n,i,s)=>`fn getNearestPixelFromOriginal(xOriginal: ${s}, isDownSample: bool) -> ${s} {`+(()=>{switch(n){case"round_prefer_ceil":return"if (fract(xOriginal) == 0.5) { return ceil(xOriginal); } else { return round(xOriginal); }";case"floor":return"return floor(xOriginal);";case"ceil":return"return ceil(xOriginal);";case"round_prefer_floor":return"if (fract(xOriginal) == 0.5) { return floor(xOriginal); } else { return round(xOriginal); }";case"simple":default:if(i<11)return"if (isDownSample) { return ceil(xOriginal); } else { return xOriginal; }";throw new Error(`Nearest mode ${n} is not supported`)}})()+"}",S0=(n,i,s)=>{let u=new Array(s).fill(0).concat(new Array(s).fill(1)),c=n.length===0?u:n.slice();return i.length>0?(i.forEach((f,d)=>{u[f]=c[d],u[d+s]=c[i.length+d]}),u):c},E0=(n,i,s,u)=>{let c=[];if(s.length>0)if(u.length>0){if(n.forEach(f=>c.push(f)),Math.max(...u)>n.length)throw new Error("axes is out of bound");u.forEach((f,d)=>c[f]=s[d])}else s.forEach(f=>c.push(f));else{if(i.length===0)throw new Error("Resize requires either scales or sizes.");c=n.map((f,d)=>Math.round(f*i[d]))}return c},C0=(n,i,s)=>{let u=(()=>{switch(s.keepAspectRatioPolicy){case"not_larger":return s.axes.length>0?Math.min(...s.axes.map(f=>i[f]),Number.MAX_VALUE):Math.min(...i,Number.MAX_VALUE);case"not_smaller":return s.axes.length>0?Math.max(...s.axes.map(f=>i[f]),Number.MIN_VALUE):Math.max(...i,Number.MIN_VALUE);default:throw new Error(`Keep aspect ratio policy ${s.keepAspectRatioPolicy} is not supported`)}})();i.fill(1,0,i.length);let c=n.slice();return s.axes.length>0?(s.axes.forEach(f=>i[f]=u),s.axes.forEach(f=>c[f]=Math.round(n[f]*i[f]))):(i.fill(u,0,i.length),c.forEach((f,d)=>c[d]=Math.round(f*i[d]))),c},P0=(n,i,s,u,c)=>` + fn calculateOriginalIndicesFromOutputIndices(output_indices: ${n.type.indices}) -> array<${n.type.value}, ${s.length}> { + var original_indices: array<${n.type.value}, ${s.length}>; + for (var i:u32 = 0; i < ${s.length}; i++) { + var output_index = ${n.indicesGet("output_indices","i")}; + var scale = ${zt("uniforms.scales","i",u)}; + var roi_low = ${zt("uniforms.roi","i",c)}; + var roi_hi = ${zt("uniforms.roi",`i + ${i.length}`,c)}; + if (scale == 1.0) { + original_indices[i] = ${n.type.value}(output_index); + } else { + var input_shape_i = ${zt("uniforms.input_shape","i",i.length)}; + var output_shape_i = ${zt("uniforms.output_shape","i",s.length)}; + original_indices[i] = getOriginalCoordinateFromResizedCoordinate(output_index, scale, output_shape_i, + input_shape_i, roi_low, roi_hi); + } + } + return original_indices; + }`,$0=(n,i,s,u,c,f,d)=>` + fn calculateInputIndicesFromOutputIndices(output_indices: ${i.type.indices}) -> ${n.type.indices} { + var input_indices: ${n.type.indices}; + for (var i:u32 = 0; i < ${u.length}; i++) { + var output_index = ${i.indicesGet("output_indices","i")}; + var input_index: u32; + var scale = ${zt("uniforms.scales","i",c)}; + if (scale == 1.0) { + input_index = output_index; + } else { + var roi_low = ${zt("uniforms.roi","i",f)}; + var roi_hi = ${zt("uniforms.roi",`i + ${s.length}`,f)}; + var input_shape_i = ${zt("uniforms.input_shape","i",s.length)}; + var output_shape_i = ${zt("uniforms.output_shape","i",u.length)}; + var original_idx = getOriginalCoordinateFromResizedCoordinate(output_index, scale, output_shape_i, + input_shape_i, roi_low, roi_hi); + if (!${d} || (original_idx >= 0 && original_idx < ${i.type.value}(input_shape_i))) { + if (original_idx < 0) { + input_index = 0; + } else if (original_idx > ${i.type.value}(input_shape_i - 1)) { + input_index = input_shape_i - 1; + } else { + input_index = u32(getNearestPixelFromOriginal(original_idx, scale < 1)); + } + } else { + input_index = u32(original_idx); + } + } + ${n.indicesSet("input_indices","i"," input_index")} + } + return input_indices; + }`,A0=(n,i)=>` + fn checkInputIndices(input_indices: ${n.type.indices}) -> bool { + for (var i:u32 = 0; i < ${i.length}; i++) { + var input_index = ${n.indicesGet("input_indices","i")}; + if (input_index < 0 || input_index >= ${zt("uniforms.input_shape","i",i.length)}) { + return false; + } + } + return true; + }`,vm=(n,i,s,u)=>n.rank>u?` + ${n.indicesSet("input_indices",i,"channel")}; + ${n.indicesSet("input_indices",s,"batch")}; +`:"",I0=(n,i,s,u,c)=>{let[f,d,x,k]=s.length===2?[-1,0,1,-1]:[0,2,3,1],$=n.type.value;return` + fn getInputValue(batch: u32, channel: u32, row: u32, col: u32) -> ${$} { + var input_indices: ${n.type.indices}; + ${n.indicesSet("input_indices",d,`max(0, min(row, ${s[d]} - 1))`)}; + ${n.indicesSet("input_indices",x,`max(0, min(col, ${s[x]} - 1))`)}; + ${vm(n,k,f,2)} + return ${n.getByIndices("input_indices")}; + } + + fn bilinearInterpolation(output_indices: ${i.type.indices}) -> ${$} { + var originalIndices = calculateOriginalIndicesFromOutputIndices(output_indices); + var row:${$} = originalIndices[${d}]; + var col:${$} = originalIndices[${x}]; + ${u?`if (row < 0 || row > (${s[d]} - 1) || col < 0 || col > (${s[x]} - 1)) { + return ${c}; + }`:""}; + row = max(0, min(row, ${s[d]} - 1)); + col = max(0, min(col, ${s[x]} - 1)); + var row1: u32 = u32(row); + var col1: u32 = u32(col); + var row2: u32 = u32(row + 1); + var col2: u32 = u32(col + 1); + var channel: u32 = ${s.length>2?`u32(originalIndices[${k}])`:"0"}; + var batch: u32 = ${s.length>2?`u32(originalIndices[${f}])`:"0"}; + var x11: ${$} = getInputValue(batch, channel, row1, col1); + var x12: ${$} = getInputValue(batch, channel, row1, col2); + var x21: ${$} = getInputValue(batch, channel, row2, col1); + var x22: ${$} = getInputValue(batch, channel, row2, col2); + var dx1: ${$} = abs(row - ${$}(row1)); + var dx2: ${$} = abs(${$}(row2) - row); + var dy1: ${$} = abs(col - ${$}(col1)); + var dy2: ${$} = abs(${$}(col2) - col); + if (row1 == row2) { + dx1 = 0.5; + dx2 = 0.5; + } + if (col1 == col2) { + dy1 = 0.5; + dy2 = 0.5; + } + return (x11 * dx2 * dy2 + x12 * dx2 * dy1 + x21 * dx1 * dy2 + x22 * dx1 * dy1); + }`},F0=(n,i,s,u,c,f,d,x,k,$)=>{let H=s.length===2,[q,v]=H?[0,1]:[2,3],oe=n.type.value,te=de=>{let we=de===q?"row":"col";return` + fn ${we}CubicInterpolation(input_indices: ${n.type.indices}, output_indices: ${i.type.indices}) -> ${oe} { + var output_index = ${i.indicesGet("output_indices",de)}; + var originalIdx: ${oe} = getOriginalCoordinateFromResizedCoordinate(output_index, ${c[de]}, + ${u[de]}, ${s[de]}, ${f[de]}, ${f[de]} + ${s.length}); + var fractOriginalIdx: ${oe} = originalIdx - floor(originalIdx); + var coefs = getCubicInterpolationCoefs(fractOriginalIdx); + + if (${x} && (originalIdx < 0 || originalIdx > (${s[de]} - 1))) { + return ${k}; + } + var data: array<${oe}, 4> = array<${oe}, 4>(0.0, 0.0, 0.0, 0.0); + for (var i: i32 = -1; i < 3; i++) { + var ${we}: ${oe} = originalIdx + ${oe}(i); + if (${we} < 0 || ${we} >= ${s[de]}) { + ${$?`coefs[i + 1] = 0.0; + continue;`:x?`return ${k};`:`${we} = max(0, min(${we}, ${s[de]} - 1));`}; + } + var input_indices_copy: ${n.type.indices} = input_indices; + ${n.indicesSet("input_indices_copy",de,`u32(${we})`)}; + data[i + 1] = ${de===q?n.getByIndices("input_indices_copy"):"rowCubicInterpolation(input_indices_copy, output_indices)"}; + } + return cubicInterpolation1D(data, coefs); + }`};return` + ${te(q)}; + ${te(v)}; + fn getCubicInterpolationCoefs(s: ${oe}) -> array<${oe}, 4> { + var absS = abs(s); + var coeffs: array<${oe}, 4> = array<${oe}, 4>(0.0, 0.0, 0.0, 0.0); + var oneMinusAbsS: ${oe} = 1.0 - absS; + var twoMinusAbsS: ${oe} = 2.0 - absS; + var onePlusAbsS: ${oe} = 1.0 + absS; + coeffs[0] = ((${d} * onePlusAbsS - 5 * ${d}) * onePlusAbsS + 8 * ${d}) * onePlusAbsS - 4 * ${d}; + coeffs[1] = ((${d} + 2) * absS - (${d} + 3)) * absS * absS + 1; + coeffs[2] = ((${d} + 2) * oneMinusAbsS - (${d} + 3)) * oneMinusAbsS * oneMinusAbsS + 1; + coeffs[3] = ((${d} * twoMinusAbsS - 5 * ${d}) * twoMinusAbsS + 8 * ${d}) * twoMinusAbsS - 4 * ${d}; + return coeffs; + } + + fn cubicInterpolation1D(x: array<${oe}, 4>, coefs: array<${oe}, 4>) -> ${oe} { + var coefsSum: ${oe} = coefs[0] + coefs[1] + coefs[2] + coefs[3]; + return (x[0] * coefs[0] + x[1] * coefs[1]+ x[2] * coefs[2]+ x[3] * coefs[3]) / coefsSum; + } + + fn bicubicInterpolation(output_indices: ${i.type.indices}) -> ${oe} { + var input_indices: ${n.type.indices} = output_indices; + return colCubicInterpolation(input_indices, output_indices); + } + `},O0=(n,i,s,u,c)=>{let[f,d,x,k,$]=s.length===3?[-1,0,1,2,-1]:[0,2,3,4,1],H=n.type.value;return` + fn getInputValue(batch: u32, channel: u32, depth:u32, height: u32, width: u32) -> ${H} { + var input_indices: ${n.type.indices}; + ${n.indicesSet("input_indices",d,`max(0, min(depth, ${s[d]} - 1))`)}; + ${n.indicesSet("input_indices",x,`max(0, min(height, ${s[x]} - 1))`)}; + ${n.indicesSet("input_indices",k,`max(0, min(width, ${s[k]} - 1))`)}; + ${vm(n,$,f,3)} + return ${n.getByIndices("input_indices")}; + } + + fn trilinearInterpolation(output_indices: ${i.type.indices}) -> ${H} { + var originalIndices = calculateOriginalIndicesFromOutputIndices(output_indices); + var depth:${H} = originalIndices[${d}]; + var height:${H} = originalIndices[${x}]; + var width:${H} = originalIndices[${k}]; + ${u?`if (depth < 0 || depth > (${s[d]} - 1) || height < 0 || height > (${s[x]} - 1) || width < 0 || (width > ${s[k]} - 1)) { + return ${c}; + }`:""}; + + depth = max(0, min(depth, ${s[d]} - 1)); + height = max(0, min(height, ${s[x]} - 1)); + width = max(0, min(width, ${s[k]} - 1)); + var depth1: u32 = u32(depth); + var height1: u32 = u32(height); + var width1: u32 = u32(width); + var depth2: u32 = u32(depth + 1); + var height2: u32 = u32(height + 1); + var width2: u32 = u32(width + 1); + var channel: u32 = ${s.length>3?`u32(originalIndices[${$}])`:"0"}; + var batch: u32 = ${s.length>3?`u32(originalIndices[${f}])`:"0"}; + + var x111: ${H} = getInputValue(batch, channel, depth1, height1, width1); + var x112: ${H} = getInputValue(batch, channel, depth1, height1, width2); + var x121: ${H} = getInputValue(batch, channel, depth1, height2, width1); + var x122: ${H} = getInputValue(batch, channel, depth1, height2, width2); + var x211: ${H} = getInputValue(batch, channel, depth2, height1, width1); + var x212: ${H} = getInputValue(batch, channel, depth2, height1, width2); + var x221: ${H} = getInputValue(batch, channel, depth2, height2, width1); + var x222: ${H} = getInputValue(batch, channel, depth2, height2, width2); + var dx1: ${H} = abs(depth - ${H}(depth1)); + var dx2: ${H} = abs(${H}(depth2) - depth); + var dy1: ${H} = abs(height - ${H}(height1)); + var dy2: ${H} = abs(${H}(height2) - height); + var dz1: ${H} = abs(width - ${H}(width1)); + var dz2: ${H} = abs(${H}(width2) - width); + if (depth1 == depth2) { + dx1 = 0.5; + dx2 = 0.5; + } + if (height1 == height2) { + dy1 = 0.5; + dy2 = 0.5; + } + if (width1 == width2) { + dz1 = 0.5; + dz2 = 0.5; + } + return (x111 * dx2 * dy2 * dz2 + x112 * dx2 * dy2 * dz1 + x121 * dx2 * dy1 *dz2 + x122 * dx2 * dy1 * dz1 + + x211 * dx1 * dy2 * dz2 + x212 * dx1 * dy2 * dz1 + x221 * dx1 * dy1 *dz2 + x222 * dx1 * dy1 * dz1); + }`},z0=(n,i,s,u,c,f)=>{let d=n.dims,x=S0(f,i.axes,d.length),k=E0(d,u,c,i.axes),$=u.slice();u.length===0&&($=d.map((he,De)=>he===0?1:k[De]/he),i.keepAspectRatioPolicy!=="stretch"&&(k=C0(d,$,i)));let H=Gt("output",n.dataType,k.length),q=_t("input",n.dataType,d.length),v=ct.size(k),oe=d.length===k.length&&d.every((he,De)=>he===k[De]),te=i.coordinateTransformMode==="tf_crop_and_resize",de=i.extrapolationValue,we=q.type.value,be=he=>` + ${oe?"":` + ${T0(i.coordinateTransformMode,we)}; + ${(()=>{switch(i.mode){case"nearest":return` + ${A0(q,d)}; + ${k0(i.nearestMode,s,we)}; + ${$0(q,H,d,k,$.length,x.length,te)}; + `;case"linear":return` + ${P0(H,d,k,$.length,x.length)}; + ${(()=>{if(d.length===2||d.length===4)return`${I0(q,H,d,te,de)}`;if(d.length===3||d.length===5)return`${O0(q,H,d,te,de)}`;throw Error("Linear mode only supports input dims 2, 3, 4 and 5 are supported in linear mode.")})()}; + `;case"cubic":return` + ${(()=>{if(d.length===2||d.length===4)return`${F0(q,H,d,k,$,x,i.cubicCoeffA,te,i.extrapolationValue,i.excludeOutside)}`;throw Error("Cubic mode only supports input dims 2 and 4 are supported in linear mode.")})()}; + `;default:throw Error("Invalid resize mode")}})()}; + `} + ${he.registerUniform("output_size","u32").registerUniform("scales","f32",$.length).registerUniform("roi","f32",x.length).declareVariables(q,H)} + ${he.mainStart()} + ${he.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")} + ${oe?"output[global_idx] = input[global_idx];":` + let output_indices = ${H.offsetToIndices("global_idx")}; + var input_indices: ${q.type.indices}; + ${(()=>{switch(i.mode){case"nearest":return`input_indices = calculateInputIndicesFromOutputIndices(output_indices); + if (checkInputIndices(input_indices)) { + output[global_idx] = ${q.getByIndices("input_indices")}; + } else { + output[global_idx] = ${i.extrapolationValue}; + }`;case"linear":return`output[global_idx] = ${d.length===2||d.length===4?"bilinearInterpolation":"trilinearInterpolation"}(output_indices);`;case"cubic":return"output[global_idx] = bicubicInterpolation(output_indices);";default:throw Error(`Unsupported resize mode: ${i.mode}`)}})()}; +`} + }`;return{name:"Resize",shaderCache:{hint:`${i.cacheKey}|${s}|${$.length>0?$:""}|${c.length>0?c:""}|${x.length>0?x:""}|${oe}|${d}`,inputDependencies:["rank"]},getShaderSource:be,getRunData:()=>({outputs:[{dims:k,dataType:n.dataType}],dispatchGroup:{x:Math.ceil(v/64)},programUniforms:[{type:12,data:v},{type:1,data:$},{type:1,data:x},...At(d,k)]})}},D0=n=>{let i=n.customDataBuffer;return new Uint32Array(i,i.byteOffset,1)[0]},L0=(n,i)=>{let s=[],u=[],c=[],f=D0(n);if(i.antialias!==0)throw Error("Only default value (0) for Antialias attribute is supported");M0(n.inputs,i,f,s,u,c),n.compute(z0(n.inputs[0],i,f,s,u,c),{inputs:[0]})},R0=n=>{let i=n.antialias,s=n.axes,u=n.coordinateTransformMode,c=n.cubicCoeffA,f=n.excludeOutside!==0,d=n.extrapolationValue,x=n.keepAspectRatioPolicy,k=n.mode,$=n.nearestMode===""?"simple":n.nearestMode;return qt({antialias:i,axes:s,coordinateTransformMode:u,cubicCoeffA:c,excludeOutside:f,extrapolationValue:d,keepAspectRatioPolicy:x,mode:k,nearestMode:$})}}),B0,N0,j0,ix=h(()=>{Zt(),Jt(),_r(),ar(),B0=(n,i)=>{let[s,u,c,f]=n,{numHeads:d,rotaryEmbeddingDim:x}=i;if(s.dims.length!==3&&s.dims.length!==4)throw new Error(`Input 'x' is expected to have 3 or 4 dimensions, got ${s.dims.length}`);if(!ct.areEqual(u.dims,[])&&!ct.areEqual(u.dims,[1])&&u.dims.length!==2)throw new Error(`Input 'position_ids' is expected to have 0, 1, or 2 dimensions, got ${u.dims.length}`);if(c.dims.length!==2)throw new Error(`Input 'cos_cache' is expected to have 2 dimensions, got ${c.dims.length}`);if(f.dims.length!==2)throw new Error(`Input 'sin_cache' is expected to have 2 dimensions, got ${f.dims.length}`);if(!ct.areEqual(c.dims,f.dims))throw new Error("Inputs 'cos_cache' and 'sin_cache' are expected to have the same shape");if(x>0&&d===0)throw new Error("num_heads must be provided if rotary_embedding_dim is specified");let k=s.dims[0],$=s.dims[s.dims.length-2],H=c.dims[0],q=ct.sizeFromDimension(s.dims,1)/$,v=x===0?c.dims[1]*2:q/d;if(x>v)throw new Error("rotary_embedding_dim must be less than or equal to head_size");if(u.dims.length===2){if(k!==u.dims[0])throw new Error(`Input 'position_ids' dimension 0 should be of size batch_size, got ${u.dims[0]}`);if($!==u.dims[1])throw new Error(`Input 'position_ids' dimension 1 should be of size sequence_length, got ${u.dims[1]}`)}if(v/2!==c.dims[1]&&x/2!==c.dims[1])throw new Error(`Input 'cos_cache' dimension 1 should be same as head_size / 2 or rotary_embedding_dim / 2, got ${c.dims[1]}`);if($>H)throw new Error("Updating cos_cache and sin_cache in RotaryEmbedding is not currently supported")},N0=(n,i)=>{let{interleaved:s,numHeads:u,rotaryEmbeddingDim:c,scale:f}=i,d=n[0].dims[0],x=ct.sizeFromDimension(n[0].dims,1),k=n[0].dims[n[0].dims.length-2],$=x/k,H=n[2].dims[1],q=c===0?H*2:$/u,v=new Array(d,k,$/q,q-H),oe=ct.computeStrides(v),te=[{type:1,data:f},{type:12,data:v},{type:12,data:oe},...n[0].dims.length===3?new Array({type:12,data:[x,$,q,1]}):[],...n[0].dims.length===4?new Array({type:12,data:[x,q,k*q,1]}):[],...At(n[0].dims,n[1].dims,n[2].dims,n[3].dims,n[0].dims)],de=we=>{let be=_t("input",n[0].dataType,n[0].dims.length),he=_t("position_ids",n[1].dataType,n[1].dims.length),De=_t("cos_cache",n[2].dataType,n[2].dims.length),Ae=_t("sin_cache",n[3].dataType,n[3].dims.length),Ie=Gt("output",n[0].dataType,n[0].dims.length);return we.registerUniforms([{name:"scale",type:"f32"},{name:"global_shape",type:"u32",length:v.length},{name:"global_strides",type:"u32",length:oe.length},{name:"input_output_strides",type:"u32",length:oe.length}]),` + ${we.declareVariables(be,he,De,Ae,Ie)} + + ${we.mainStart(Un)} + let half_rotary_emb_dim = uniforms.${De.name}_shape[1]; + let bsnh = global_idx / uniforms.global_strides % uniforms.global_shape; + let size = uniforms.global_shape[0] * uniforms.global_strides[0]; + ${we.guardAgainstOutOfBoundsWorkgroupSizes("size")} + + if (bsnh[3] < half_rotary_emb_dim) { + let position_ids_idx = + ${he.broadcastedIndicesToOffset("bsnh.xy",Gt("",he.type.tensor,2))}; + let position_id = + u32(${he.getByOffset("position_ids_idx")}) + select(0, bsnh[1], position_ids_idx == 0); + let i = dot(bsnh, uniforms.input_output_strides) + select(0, bsnh[3], ${s}); + let j = i + select(half_rotary_emb_dim, 1, ${s}); + let re = ${be.getByOffset("i")} * ${De.get("position_id","bsnh[3]")} - + ${be.getByOffset("j")} * ${Ae.get("position_id","bsnh[3]")}; + ${Ie.setByOffset("i","re")} + let im = ${be.getByOffset("i")} * ${Ae.get("position_id","bsnh[3]")} + + ${be.getByOffset("j")} * ${De.get("position_id","bsnh[3]")}; + ${Ie.setByOffset("j","im")} + } else { + let k = dot(bsnh, uniforms.input_output_strides) + half_rotary_emb_dim; + ${Ie.setByOffset("k",be.getByOffset("k"))} + } + }`};return{name:"RotaryEmbedding",shaderCache:{hint:qt({interleaved:s}).cacheKey,inputDependencies:["rank","rank","rank","rank"]},getShaderSource:de,getRunData:()=>({outputs:[{dims:n[0].dims,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(ct.size(v)/Un)},programUniforms:te})}},j0=(n,i)=>{B0(n.inputs,i),n.compute(N0(n.inputs,i))}}),U0,V0,W0,ox=h(()=>{Zt(),Jt(),ar(),U0=n=>{if(!n||n.length<3)throw new Error("layerNorm requires at least 3 inputs.");let i=n[0],s=n[1],u=n[2];if(i.dataType!==s.dataType||i.dataType!==u.dataType)throw new Error("All inputs must have the same data type");if(i.dims.length!==3&&i.dims.length!==2)throw new Error("Input must be 2D or 3D");if(s.dims.length!==3&&s.dims.length!==2)throw new Error("Skip must be 2D or 3D");let c=i.dims[i.dims.length-1],f=i.dims[i.dims.length-2];if(s.dims[s.dims.length-1]!==c)throw new Error("Skip must have the same hidden size as input");if(s.dims[s.dims.length-2]!==f)throw new Error("Skip must have the same sequence length as input");if(u.dims.length!==1)throw new Error("Gamma must be 1D");if(u.dims[u.dims.length-1]!==c)throw new Error("Gamma must have the same hidden size as input");if(n.length>3){let d=n[3];if(d.dims.length!==1)throw new Error("Beta must be 1D");if(d.dims[d.dims.length-1]!==c)throw new Error("Beta must have the same hidden size as input")}if(n.length>4){let d=n[4];if(d.dims.length!==1)throw new Error("Bias must be 1D");if(d.dims[d.dims.length-1]!==c)throw new Error("Bias must have the same hidden size as input")}},V0=(n,i,s,u)=>{let c=i.simplified,f=n[0].dims,d=ct.size(f),x=f,k=d,$=f.slice(-1)[0],H=u?f.slice(0,-1).concat(1):[],q=!c&&n.length>3,v=n.length>4,oe=u&&s>1,te=u&&s>2,de=s>3,we=64,be=vr($),he=[{type:12,data:k},{type:12,data:be},{type:12,data:$},{type:1,data:i.epsilon}],De=Ie=>{let gt=[{name:"output_size",type:"u32"},{name:"components",type:"u32"},{name:"hidden_size",type:"u32"},{name:"epsilon",type:"f32"}],ut=[_t("x",n[0].dataType,n[0].dims,be),_t("skip",n[1].dataType,n[1].dims,be),_t("gamma",n[2].dataType,n[2].dims,be)];q&&ut.push(_t("beta",n[3].dataType,n[3].dims,be)),v&&ut.push(_t("bias",n[4].dataType,n[4].dims,be)),ut.push(Gt("output",n[0].dataType,x,be)),oe&&ut.push(Gt("mean_output",1,H)),te&&ut.push(Gt("inv_std_output",1,H)),de&&ut.push(Gt("input_skip_bias_sum",n[0].dataType,x,be));let vt=Sr(n[0].dataType),Dt=Sr(1,be);return` + + ${Ie.registerUniforms(gt).declareVariables(...ut)} + var sum_shared : array<${Dt}, ${we}>; + var sum_squared_shared : array<${Dt}, ${we}>; + + ${Ie.mainStart([we,1,1])} + let ix = local_id.x; + let iy = global_id.x / ${we}; + + let hidden_size_vectorized: u32 = uniforms.hidden_size / uniforms.components; + var stride = hidden_size_vectorized / ${we}; + let offset = ix * stride + iy * hidden_size_vectorized; + let offset1d = stride * ix; + if (ix == ${we-1}) { + stride = hidden_size_vectorized - stride * ix; + } + for (var i: u32 = 0; i < stride; i++) { + let skip_value = skip[offset + i]; + let bias_value = ${v?"bias[offset1d + i]":vt+"(0.0)"}; + let input_value = x[offset + i]; + let value = input_value + skip_value + bias_value; + ${de?"input_skip_bias_sum[offset + i] = value;":""} + output[offset + i] = value; + let f32_value = ${Xr(vt,be,"value")}; + sum_shared[ix] += f32_value; + sum_squared_shared[ix] += f32_value * f32_value; + } + workgroupBarrier(); + + var reduce_size : u32 = ${we}; + for (var curr_size = reduce_size >> 1; curr_size > 0; curr_size = reduce_size >> 1) { + reduce_size = curr_size + (reduce_size & 1); + if (ix < curr_size) { + sum_shared[ix] += sum_shared[ix + reduce_size]; + sum_squared_shared[ix] += sum_squared_shared[ix + reduce_size]; + } + workgroupBarrier(); + } + + let sum = sum_shared[0]; + let square_sum = sum_squared_shared[0]; + let mean = ${Vn("sum",be)} / f32(uniforms.hidden_size); + let inv_std_dev = inverseSqrt(${Vn("square_sum",be)} / f32(uniforms.hidden_size) ${c?"":"- mean * mean"} + uniforms.epsilon); + ${oe?"mean_output[global_idx] = mean;":""} + ${te?"inv_std_output[global_idx] = inv_std_dev;":""} + + for (var i: u32 = 0; i < stride; i++) { + output[offset + i] = (output[offset + i] ${c?"":`- ${vt}(mean)`}) * + ${vt}(inv_std_dev) * gamma[offset1d + i] + ${q?"+ beta[offset1d + i]":""}; + } + }`},Ae=[{dims:x,dataType:n[0].dataType}];return s>1&&Ae.push({dims:H,dataType:1}),s>2&&Ae.push({dims:H,dataType:1}),s>3&&Ae.push({dims:f,dataType:n[0].dataType}),{name:"SkipLayerNormalization",shaderCache:{hint:`${be};${oe};${te};${de}`,inputDependencies:n.map((Ie,gt)=>"type")},getShaderSource:De,getRunData:()=>({outputs:Ae,dispatchGroup:{x:Math.ceil(k/$)},programUniforms:he})}},W0=(n,i)=>{U0(n.inputs);let s=[0];n.outputCount>1&&s.push(-3),n.outputCount>2&&s.push(-3),n.outputCount>3&&s.push(3),n.compute(V0(n.inputs,i,n.outputCount,!1),{outputs:s})}}),G0,op,H0,bm,q0,K0,X0,Q0,sx=h(()=>{Zt(),Jt(),_r(),ar(),G0=(n,i)=>{if(!n||n.length<1)throw new Error("too few inputs");if(i.axes.length!==0){if(i.axes.length!==i.starts.length||i.axes.length!==i.ends.length)throw new Error("axes, starts and ends must have the same length")}else if(i.starts.length!==i.ends.length)throw new Error("starts and ends must have the same length");n.slice(1).forEach((s,u)=>{if(n[u+1].dataType!==6&&n[u+1].dataType!==7)throw new Error(`Input ${u} must be an array of int32 or int64`)})},op=(n,i)=>{let s=[];if(n.length>i)if(n[i].dataType===7)n[i].getBigInt64Array().forEach(u=>s.push(Number(u)));else if(n[i].dataType===6)n[i].getInt32Array().forEach(u=>s.push(Number(u)));else throw new Error(`Input ${i} must be an array of int32 or int64`);return s},H0=(n,i)=>{if(n.length>1){let s=op(n,1),u=op(n,2),c=op(n,3);return c.length===0&&(c=[...Array(n[0].dims.length).keys()]),qt({starts:s,ends:u,axes:c})}else return i},bm=(n,i,s,u,c)=>{let f=n;return n<0&&(f+=s[u[i]]),c[i]<0?Math.max(0,Math.min(f,s[u[i]]-1)):Math.max(0,Math.min(f,s[u[i]]))},q0=(n,i,s)=>`fn calculateInputIndices(output_indices: ${i.type.indices}) -> ${n.type.indices} { + var input_indices: ${n.type.indices}; + var carry = 0u; + for (var i = ${s.length}; i >= 0; i--) { + let input_shape_i = ${zt("uniforms.input_shape","i",s.length)}; + let steps_i = ${zt("uniforms.steps","i",s.length)}; + let signs_i = ${zt("uniforms.signs","i",s.length)}; + let starts_i = ${zt("uniforms.starts","i",s.length)}; + var output_index = ${i.indicesGet("output_indices","i")}; + var input_index = output_index * steps_i + starts_i + carry; + carry = input_index / input_shape_i; + input_index = input_index % input_shape_i; + if (signs_i < 0) { + input_index = input_shape_i - input_index - 1u + starts_i; + } + ${n.indicesSet("input_indices","i","input_index")}; + } + return input_indices; + }`,K0=(n,i)=>{let s=n[0].dims,u=ct.size(s),c=i.axes.length>0?ct.normalizeAxes(i.axes,s.length):[...Array(s.length).keys()],f=op(n,4);f.forEach(be=>be!==0||(()=>{throw new Error("step cannot be 0")})),f.length===0&&(f=Array(c.length).fill(1));let d=i.starts.map((be,he)=>bm(be,he,s,c,f)),x=i.ends.map((be,he)=>bm(be,he,s,c,f));if(c.length!==d.length||c.length!==x.length)throw new Error("start, ends and axes should have the same number of elements");if(c.length!==s.length)for(let be=0;beMath.sign(be));f.forEach((be,he,De)=>{if(be<0){let Ae=(x[he]-d[he])/be,Ie=d[he],gt=Ie+Ae*f[he];d[he]=gt,x[he]=Ie,De[he]=-be}});let $=s.slice(0);c.forEach((be,he)=>{$[be]=Math.ceil((x[be]-d[be])/f[be])});let H={dims:$,dataType:n[0].dataType},q=Gt("output",n[0].dataType,$.length),v=_t("input",n[0].dataType,n[0].dims.length),oe=ct.size($),te=[{name:"outputSize",type:"u32"},{name:"starts",type:"u32",length:d.length},{name:"signs",type:"i32",length:k.length},{name:"steps",type:"u32",length:f.length}],de=[{type:12,data:oe},{type:12,data:d},{type:6,data:k},{type:12,data:f},...At(n[0].dims,$)],we=be=>` + ${be.registerUniforms(te).declareVariables(v,q)} + ${q0(v,q,s)} + ${be.mainStart()} + ${be.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")} + let output_indices = ${q.offsetToIndices("global_idx")}; + let input_indices = calculateInputIndices(output_indices); + ${q.setByOffset("global_idx",v.getByIndices("input_indices"))} + }`;return{name:"Slice",shaderCache:{hint:`${k.length}_${d.length}_${f.length}`,inputDependencies:["rank"]},getShaderSource:we,getRunData:()=>({outputs:[H],dispatchGroup:{x:Math.ceil(u/64)},programUniforms:de})}},X0=(n,i)=>{G0(n.inputs,i);let s=H0(n.inputs,i);n.compute(K0(n.inputs,s),{inputs:[0]})},Q0=n=>{let i=n.starts,s=n.ends,u=n.axes;return qt({starts:i,ends:s,axes:u})}}),Y0,Z0,J0,ew,ax=h(()=>{Zt(),Jt(),_r(),ar(),Y0=n=>{if(!n||n.length!==1)throw new Error("Softmax op requires 1 input.")},Z0=(n,i)=>{let s=n.dims,u=ct.size(s),c=64,f=i.axis;if(f<0&&(f=s.length+f),fbe===4?`max(max(${we}.x, ${we}.y), max(${we}.z, ${we}.w))`:be===2?`max(${we}.x, ${we}.y)`:be===3?`max(max(${we}.x, ${we}.y), ${we}.z)`:we,q=_t("x",n.dataType,n.dims,k),v=Gt("result",n.dataType,n.dims,k),oe=q.type.value,te=Sr(n.dataType)==="f32"?`var threadMax = ${oe}(-3.402823e+38f);`:`var threadMax = ${oe}(-65504.0h);`,de=we=>` + var rowMaxShared : ${oe}; + var rowSumShared : ${oe}; + var threadShared : array<${oe}, ${c}>; + + fn getValue(row: i32, col: i32, row_stride: i32) -> ${oe} { + let index = row * row_stride + col; + return x[index]; + } + + fn setValue(row: i32, col: i32, row_stride: i32, value: ${oe}) { + let index = row * row_stride + col; + result[index] = value; + } + ${we.registerUniform("packedCols","i32").declareVariables(q,v)} + ${we.mainStart()} + let gindex = i32(global_idx); + let lindex = i32(local_idx); + const wg = ${c}; + let row = gindex / wg; + let cols = uniforms.packedCols; + let row_stride : i32 = uniforms.packedCols; + + // find the rows max + ${te} + for (var col = lindex; col < cols; col += wg) { + let value = getValue(row, col, row_stride); + threadMax = max(threadMax, value); + } + if (lindex < cols) { + threadShared[lindex] = threadMax; + } + workgroupBarrier(); + + var reduceSize = min(cols, wg); + for (var currSize = reduceSize >> 1; currSize > 0; currSize = reduceSize >> 1) { + reduceSize = currSize + (reduceSize & 1); + if (lindex < currSize) { + threadShared[lindex] = max(threadShared[lindex], threadShared[lindex + reduceSize]); + } + workgroupBarrier(); + } + if (lindex == 0) { + rowMaxShared = ${oe}(${H("threadShared[0]",k)}); + } + workgroupBarrier(); + + // find the rows sum + var threadSum = ${oe}(0.0); + for (var col = lindex; col < cols; col += wg) { + let subExp = exp(getValue(row, col, row_stride) - rowMaxShared); + threadSum += subExp; + } + threadShared[lindex] = threadSum; + workgroupBarrier(); + + for (var currSize = wg >> 1; currSize > 0; currSize = currSize >> 1) { + if (lindex < currSize) { + threadShared[lindex] = threadShared[lindex] + threadShared[lindex + currSize]; + } + workgroupBarrier(); + } + if (lindex == 0) { + rowSumShared = ${oe}(${Vn("threadShared[0]",k)}); + } + workgroupBarrier(); + + // calculate final value for each element in the row + for (var col = lindex; col < cols; col += wg) { + let value = exp(getValue(row, col, row_stride) - rowMaxShared) / rowSumShared; + setValue(row, col, row_stride, value); + } + }`;return{name:"Softmax",shaderCache:{hint:`${k}`,inputDependencies:["type"]},getRunData:()=>({outputs:[{dims:s,dataType:n.dataType}],dispatchGroup:{x},programUniforms:[{type:6,data:$}]}),getShaderSource:de}},J0=(n,i)=>{Y0(n.inputs),n.compute(Z0(n.inputs[0],i))},ew=n=>qt({axis:n.axis})}),tw,rw,nw,iw,ow,sw,aw,lx=h(()=>{Zt(),Jt(),_r(),ar(),tw=n=>{if(!n||n.length<1)throw new Error("too few inputs")},rw=(n,i)=>{let s=[],u=i.numOutputs;return n[1].dims[0]>0&&(n[1].getBigInt64Array().forEach(c=>s.push(Number(c))),u=s.length),qt({numOutputs:u,axis:i.axis,splitSizes:s})},nw=n=>` +fn calculateOutputIndex(index: u32) -> u32 { + for (var i: u32 = 0u; i < ${n}u; i += 1u ) { + if (index < ${zt("uniforms.size_in_split_axis","i",n)}) { + return i; + } + } + return ${n}u; +}`,iw=n=>{let i=n.length,s=[];for(let u=0;u{let s=n[0].dims,u=ct.size(s),c=n[0].dataType,f=ct.normalizeAxis(i.axis,s.length),d=new Array(i.numOutputs),x=_t("input",c,s.length),k=new Array(i.numOutputs),$=[],H=[],q=0,v=[{type:12,data:u}];for(let te=0;te` + ${te.registerUniform("input_size","u32").registerUniform("size_in_split_axis","u32",k.length).declareVariables(x,...d)} + ${nw(k.length)} + ${iw(d)} + + ${te.mainStart()} + ${te.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.input_size")} + + var indices = ${x.offsetToIndices("global_idx")}; + var index = ${x.indicesGet("indices",f)}; + let output_number = calculateOutputIndex(index); + if (output_number != 0) { + index -= ${zt("uniforms.size_in_split_axis","output_number - 1u",k.length)}; + ${x.indicesSet("indices",f,"index")}; + } + writeBufferData(output_number, indices, global_idx); + }`;return{name:"Split",shaderCache:{hint:i.cacheKey,inputDependencies:["rank"]},getShaderSource:oe,getRunData:()=>({outputs:$,dispatchGroup:{x:Math.ceil(u/64)},programUniforms:v})}},sw=(n,i)=>{tw(n.inputs);let s=n.inputs.length===1?i:rw(n.inputs,i);n.compute(ow(n.inputs,s),{inputs:[0]})},aw=n=>{let i=n.axis,s=n.splitSizes,u=n.numOutputs<0?s.length:n.numOutputs;if(u!==s.length)throw new Error("numOutputs and splitSizes lengh must be equal");return qt({axis:i,numOutputs:u,splitSizes:s})}}),lw,uw,cw,ux=h(()=>{Zt(),Jt(),ar(),lw=(n,i,s,u,c)=>{let f=Gt("output_data",c,s.length,4),d=_t("a_data",i[1].dataType,i[1].dims.length,4),x=_t("b_data",i[2].dataType,i[2].dims.length,4),k=_t("c_data",i[0].dataType,i[0].dims.length,4),$,H=(q,v,oe)=>`select(${v}, ${q}, ${oe})`;if(!u)$=f.setByOffset("global_idx",H(d.getByOffset("global_idx"),x.getByOffset("global_idx"),k.getByOffset("global_idx")));else{let q=(v,oe,te="")=>{let de=`a_data[index_a${oe}][component_a${oe}]`,we=`b_data[index_b${oe}][component_b${oe}]`,be=`bool(c_data[index_c${oe}] & (0xffu << (component_c${oe} * 8)))`;return` + let output_indices${oe} = ${f.offsetToIndices(`global_idx * 4u + ${oe}u`)}; + let offset_a${oe} = ${d.broadcastedIndicesToOffset(`output_indices${oe}`,f)}; + let offset_b${oe} = ${x.broadcastedIndicesToOffset(`output_indices${oe}`,f)}; + let offset_c${oe} = ${k.broadcastedIndicesToOffset(`output_indices${oe}`,f)}; + let index_a${oe} = offset_a${oe} / 4u; + let index_b${oe} = offset_b${oe} / 4u; + let index_c${oe} = offset_c${oe} / 4u; + let component_a${oe} = offset_a${oe} % 4u; + let component_b${oe} = offset_b${oe} % 4u; + let component_c${oe} = offset_c${oe} % 4u; + ${v}[${oe}] = ${te}(${H(de,we,be)}); + `};c===9?$=` + var data = vec4(0); + ${q("data",0,"u32")} + ${q("data",1,"u32")} + ${q("data",2,"u32")} + ${q("data",3,"u32")} + output_data[global_idx] = dot(vec4(0x1, 0x100, 0x10000, 0x1000000), vec4(data));`:$=` + ${q("output_data[global_idx]",0)} + ${q("output_data[global_idx]",1)} + ${q("output_data[global_idx]",2)} + ${q("output_data[global_idx]",3)} + `}return` + ${n.registerUniform("vec_size","u32").declareVariables(k,d,x,f)} + ${n.mainStart()} + ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")} + ${$} + }`},uw=n=>{let i=n[1].dims,s=n[2].dims,u=n[0].dims,c=n[1].dataType,f=!(ct.areEqual(i,s)&&ct.areEqual(s,u)),d=i,x=ct.size(i);if(f){let $=gn.calcShape(gn.calcShape(i,s,!1),u,!1);if(!$)throw new Error("Can't perform where op on the given tensors");d=$,x=ct.size(d)}let k=Math.ceil(x/4);return{name:"Where",shaderCache:{inputDependencies:["rank","rank","rank"]},getShaderSource:$=>lw($,n,d,f,c),getRunData:()=>({outputs:[{dims:d,dataType:c}],dispatchGroup:{x:Math.ceil(x/64/4)},programUniforms:[{type:12,data:k},...At(u,i,s,d)]})}},cw=n=>{n.compute(uw(n.inputs))}}),dw,cx=h(()=>{nf(),zs(),tc(),of(),Oc(),sf(),af(),cd(),gm(),ff(),hf(),wf(),_m(),vf(),bf(),xf(),Bd(),Tf(),wm(),bn(),sl(),Sf(),Wd(),cr(),Jo(),$f(),$a(),nx(),ix(),ox(),sx(),ax(),lx(),Kd(),yo(),Ha(),ux(),dw=new 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Map,this.attributesBound=!1}getArtifact(n){return this.repo.get(n)}setArtifact(n,i){this.repo.set(n,i)}run(n,i,s,u,c){et(n.programInfo.name);let f=this.backend.device,d=this.backend.getComputePassEncoder();this.backend.writeTimestamp(this.backend.pendingDispatchNumber*2);let x=[];for(let $ of i)x.push({binding:x.length,resource:{buffer:$.buffer}});for(let $ of s)x.push({binding:x.length,resource:{buffer:$.buffer}});c&&x.push({binding:x.length,resource:c});let k=f.createBindGroup({layout:n.computePipeline.getBindGroupLayout(0),entries:x,label:n.programInfo.name});if(this.backend.sessionStatus==="capturing"){let $={kernelId:this.backend.currentKernelId,computePipeline:n.computePipeline,bindGroup:k,dispatchGroup:u};this.backend.capturedCommandList.get(this.backend.currentSessionId).push($)}d.setPipeline(n.computePipeline),d.setBindGroup(0,k),d.dispatchWorkgroups(...u),this.backend.writeTimestamp(this.backend.pendingDispatchNumber*2+1),this.backend.pendingDispatchNumber++,(this.backend.pendingDispatchNumber>=this.backend.maxDispatchNumber||this.backend.queryType==="at-passes")&&this.backend.endComputePass(),this.backend.pendingDispatchNumber>=this.backend.maxDispatchNumber&&this.backend.flush(),A(n.programInfo.name)}dispose(){}build(n,i){et(n.name);let s=this.backend.device,u=[];s.features.has("shader-f16")&&u.push("enable f16;");let c=cu(i,this.backend.device.limits),f=n.getShaderSource(c),d=`${u.join(` +`)} +${c.additionalImplementations} +${f}`,x=s.createShaderModule({code:d,label:n.name});Vr("verbose",()=>`[WebGPU] ${n.name} shader code: ${d}`);let k=s.createComputePipeline({compute:{module:x,entryPoint:"main"},layout:"auto",label:n.name});return A(n.name),{programInfo:n,computePipeline:k,uniformVariablesInfo:c.variablesInfo}}normalizeDispatchGroupSize(n){let i=typeof n=="number"?n:n.x,s=typeof n=="number"?1:n.y||1,u=typeof n=="number"?1:n.z||1,c=this.backend.device.limits.maxComputeWorkgroupsPerDimension;if(i<=c&&s<=c&&u<=c)return[i,s,u];let f=i*s*u,d=Math.ceil(Math.sqrt(f));if(d>c){if(d=Math.ceil(Math.cbrt(f)),d>c)throw new Error("Total dispatch size exceeds WebGPU maximum.");return[d,d,d]}else return[d,d,1]}}}),fw,hw,mw,gw,px=h(()=>{Z(),Zt(),jn(),W(),Ar(),cx(),dx(),fw=(n,i)=>{if(i.length!==n.length)throw new Error(`inputDependencies length ${i.length} is not equal to inputTensors length ${n.length}.`);let s=[];for(let u=0;u{var c,f;let u=n.name;return(c=n.shaderCache)!=null&&c.hint&&(u+="["+n.shaderCache.hint+"]"),u+=":"+s+`:${fw(i,((f=n.shaderCache)==null?void 0:f.inputDependencies)??new Array(i.length).fill("dims"))}`,u},mw=class{constructor(n){n&&(this.architecture=n.architecture,this.vendor=n.vendor)}isArchitecture(n){return this.architecture===n}isVendor(n){return this.vendor===n}},gw=class{constructor(){this.currentSessionId=null,this.currentKernelId=null,this.commandEncoder=null,this.computePassEncoder=null,this.maxDispatchNumber=16,this.pendingDispatchNumber=0,this.pendingKernels=[],this.pendingQueries=new Map,this.sessionStatus="default",this.capturedCommandList=new Map,this.capturedPendingKernels=new Map,this.sessionExternalDataMapping=new Map}get currentKernelCustomData(){if(this.currentKernelId===null)throw new Error("currentKernelCustomData(): currentKernelId is null. (should not happen)");let n=this.kernelCustomData.get(this.currentKernelId);return n||(n={},this.kernelCustomData.set(this.currentKernelId,n)),n}async initialize(n,i){this.env=n;let s=[],u={requiredLimits:{maxComputeWorkgroupStorageSize:i.limits.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:i.limits.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:i.limits.maxStorageBufferBindingSize,maxBufferSize:i.limits.maxBufferSize,maxComputeInvocationsPerWorkgroup:i.limits.maxComputeInvocationsPerWorkgroup,maxComputeWorkgroupSizeX:i.limits.maxComputeWorkgroupSizeX,maxComputeWorkgroupSizeY:i.limits.maxComputeWorkgroupSizeY,maxComputeWorkgroupSizeZ:i.limits.maxComputeWorkgroupSizeZ},requiredFeatures:s};i.features.has("chromium-experimental-timestamp-query-inside-passes")?s.push("chromium-experimental-timestamp-query-inside-passes"):i.features.has("timestamp-query")&&s.push("timestamp-query"),i.features.has("shader-f16")&&s.push("shader-f16"),this.device=await i.requestDevice(u),this.adapterInfo=new mw(i.info||await i.requestAdapterInfo()),this.gpuDataManager=tr(this),this.programManager=new pw(this),this.kernels=new Map,this.kernelPersistentData=new Map,this.kernelCustomData=new Map,_o(n.logLevel,!!n.debug),this.device.onuncapturederror=c=>{c.error instanceof GPUValidationError&&console.error(`An uncaught WebGPU validation error was raised: ${c.error.message}`)},Object.defineProperty(this.env.webgpu,"device",{value:this.device,writable:!1,enumerable:!0,configurable:!1}),Object.defineProperty(this.env.webgpu,"adapter",{value:i,writable:!1,enumerable:!0,configurable:!1}),this.setQueryType()}dispose(){typeof this.querySet<"u"&&this.querySet.destroy(),this.gpuDataManager.dispose()}getCommandEncoder(){return this.commandEncoder||(this.commandEncoder=this.device.createCommandEncoder()),this.commandEncoder}getComputePassEncoder(){if(!this.computePassEncoder){let n=this.getCommandEncoder(),i={};this.queryType==="at-passes"&&(i.timestampWrites={querySet:this.querySet,beginningOfPassWriteIndex:this.pendingDispatchNumber*2,endOfPassWriteIndex:this.pendingDispatchNumber*2+1}),this.computePassEncoder=n.beginComputePass(i)}return this.computePassEncoder}endComputePass(){this.computePassEncoder&&(this.computePassEncoder.end(),this.computePassEncoder=null)}flush(){if(!this.commandEncoder)return;et(),this.endComputePass();let n;this.queryType!=="none"&&(this.commandEncoder.resolveQuerySet(this.querySet,0,this.pendingDispatchNumber*2,this.queryResolveBuffer,0),n=this.device.createBuffer({size:this.pendingDispatchNumber*2*8,usage:GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST}),this.pendingQueries.set(n,this.pendingKernels),this.pendingKernels=[],this.commandEncoder.copyBufferToBuffer(this.queryResolveBuffer,0,n,0,this.pendingDispatchNumber*2*8)),this.device.queue.submit([this.commandEncoder.finish()]),this.gpuDataManager.refreshPendingBuffers(),this.commandEncoder=null,this.pendingDispatchNumber=0,this.queryType!=="none"&&n.mapAsync(GPUMapMode.READ).then(()=>{var u;let i=new BigUint64Array(n.getMappedRange()),s=this.pendingQueries.get(n);for(let c=0;c"u"&&(this.queryTimeBase=oe);let de=Number(oe-this.queryTimeBase),we=Number(te-this.queryTimeBase);if(!Number.isSafeInteger(de)||!Number.isSafeInteger(we))throw new RangeError("incorrect timestamp range");if((u=this.env.webgpu.profiling)!=null&&u.ondata)this.env.webgpu.profiling.ondata({version:1,inputsMetadata:q.map(be=>({dims:be.dims,dataType:fi(be.dataType)})),outputsMetadata:v.map(be=>({dims:be.dims,dataType:fi(be.dataType)})),kernelId:d,kernelType:k,kernelName:$,programName:H,startTime:de,endTime:we});else{let be="";q.forEach((De,Ae)=>{be+=`input[${Ae}]: [${De.dims}] | ${fi(De.dataType)}, `});let he="";v.forEach((De,Ae)=>{he+=`output[${Ae}]: [${De.dims}] | ${fi(De.dataType)}, `}),console.log(`[profiling] kernel "${d}|${k}|${$}|${H}" ${be}${he}execution time: ${we-de} ns`)}je("GPU",`${H}::${oe}::${te}`)}n.unmap(),this.pendingQueries.delete(n)}),A()}run(n,i,s,u,c,f){et(n.name);let d=[];for(let he=0;heDe):s;if(H.length!==x.length)throw new Error(`Output size ${H.length} must be equal to ${x.length}.`);let q=[],v=[];for(let he=0;he=f)throw new Error(`Invalid output index: ${H[he]}`);if(H[he]===-3)continue;let De=H[he]===-1,Ae=H[he]===-2,Ie=De||Ae?c(x[he].dataType,x[he].dims):u(H[he],x[he].dataType,x[he].dims);if(q.push(Ie),Ie.data===0)continue;let gt=this.gpuDataManager.get(Ie.data);if(!gt)throw new Error(`no GPU data for output: ${Ie.data}`);if(De&&this.temporaryData.push(gt),Ae){let ut=this.kernelPersistentData.get(this.currentKernelId);ut||(ut=[],this.kernelPersistentData.set(this.currentKernelId,ut)),ut.push(gt)}v.push(gt)}if(d.length!==i.length||v.length!==q.length){if(v.length===0)return A(n.name),q;throw new Error(`Program ${n.name} has zero-sized tensor(s) in inputs or outputs. This is not supported now.`)}let oe;if($){let he=0,De=[];$.forEach(ut=>{let vt=typeof ut.data=="number"?[ut.data]:ut.data;if(vt.length===0)return;let Dt=ut.type===10?2:4,Rt,gr;ut.type===10?(gr=vt.length>4?16:vt.length>2?8:vt.length*Dt,Rt=vt.length>4?16:Dt*vt.length):(gr=vt.length<=2?vt.length*Dt:16,Rt=16),he=Math.ceil(he/gr)*gr,De.push(he);let Mr=ut.type===10?8:4;he+=vt.length>4?Math.ceil(vt.length/Mr)*Rt:vt.length*Dt});let Ae=16;he=Math.ceil(he/Ae)*Ae;let Ie=new ArrayBuffer(he);$.forEach((ut,vt)=>{let Dt=De[vt],Rt=typeof ut.data=="number"?[ut.data]:ut.data;if(ut.type===6)new Int32Array(Ie,Dt,Rt.length).set(Rt);else if(ut.type===12)new Uint32Array(Ie,Dt,Rt.length).set(Rt);else if(ut.type===10)new Uint16Array(Ie,Dt,Rt.length).set(Rt);else if(ut.type===1)new Float32Array(Ie,Dt,Rt.length).set(Rt);else throw new Error(`Unsupported uniform type: ${fi(ut.type)}`)});let gt=this.gpuDataManager.create(he,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.device.queue.writeBuffer(gt.buffer,0,Ie,0,he),this.gpuDataManager.release(gt.id),oe={offset:0,size:he,buffer:gt.buffer}}let te=this.programManager.normalizeDispatchGroupSize(k),de=te[1]===1&&te[2]===1,we=hw(n,i,de),be=this.programManager.getArtifact(we);if(be||(be=this.programManager.build(n,te),this.programManager.setArtifact(we,be),Vr("info",()=>`[artifact] key: ${we}, programName: ${n.name}`)),$&&be.uniformVariablesInfo){if($.length!==be.uniformVariablesInfo.length)throw new Error(`Uniform variables count mismatch: expect ${be.uniformVariablesInfo.length}, got ${$.length} in program "${be.programInfo.name}".`);for(let he=0;he<$.length;he++){let De=$[he],Ae=De.type,Ie=typeof De.data=="number"?1:De.data.length,[gt,ut]=be.uniformVariablesInfo[he];if(Ae!==gt||Ie!==ut)throw new Error(`Uniform variable ${he} mismatch: expect type ${gt} with size ${ut}, got type ${Ae} with size ${Ie} in program "${be.programInfo.name}".`)}}if(Vr("info",()=>`[ProgramManager] run "${n.name}" (key=${we}) with ${te[0]}x${te[1]}x${te[2]}`),this.queryType!=="none"||this.sessionStatus==="capturing"){let he={kernelId:this.currentKernelId,programName:be.programInfo.name,inputTensorViews:i,outputTensorViews:q};this.pendingKernels.push(he),this.sessionStatus==="capturing"&&this.capturedPendingKernels.get(this.currentSessionId).push(he)}return this.programManager.run(be,d,v,te,oe),A(n.name),q}upload(n,i){this.gpuDataManager.upload(n,i)}memcpy(n,i){this.gpuDataManager.memcpy(n,i)}async download(n,i){await this.gpuDataManager.download(n,i)}alloc(n){return this.gpuDataManager.create(n).id}free(n){return this.gpuDataManager.release(n)}createKernel(n,i,s,u){let c=dw.get(n);if(!c)throw new Error(`kernel not implemented: ${n}`);let f={kernelType:n,kernelName:u,kernelEntry:c[0],attributes:[c[1],s]};this.kernels.set(i,f)}releaseKernel(n){let i=this.kernelPersistentData.get(n);if(i){for(let s of i)this.gpuDataManager.release(s.id);this.kernelPersistentData.delete(n)}this.kernelCustomData.delete(n),this.kernels.delete(n)}computeKernel(n,i,s){let u=this.kernels.get(n);if(!u)throw new Error(`kernel not created: ${n}`);let c=u.kernelType,f=u.kernelName,d=u.kernelEntry,x=u.attributes;if(this.currentKernelId!==null)throw new Error(`kernel "[${c}] ${f}" is not allowed to be called recursively`);this.currentKernelId=n,x[0]&&(x[1]=x[0](x[1]),x[0]=void 0),Vr("info",()=>`[WebGPU] Start to run kernel "[${c}] ${f}"...`);let k=this.env.debug;this.temporaryData=[];try{return k&&this.device.pushErrorScope("validation"),d(i,x[1]),0}catch($){return s.push(Promise.resolve(`[WebGPU] Kernel "[${c}] ${f}" failed. ${$}`)),1}finally{k&&s.push(this.device.popErrorScope().then($=>$?`GPU validation error for kernel "[${c}] ${f}": ${$.message}`:null));for(let $ of this.temporaryData)this.gpuDataManager.release($.id);this.temporaryData=[],this.currentKernelId=null}}registerBuffer(n,i,s,u){let c=this.sessionExternalDataMapping.get(n);c||(c=new Map,this.sessionExternalDataMapping.set(n,c));let f=c.get(i),d=this.gpuDataManager.registerExternalBuffer(s,u,f==null?void 0:f[1]);return c.set(i,[d,s]),d}unregisterBuffers(n){let i=this.sessionExternalDataMapping.get(n);i&&(i.forEach(s=>this.gpuDataManager.unregisterExternalBuffer(s[1])),this.sessionExternalDataMapping.delete(n))}getBuffer(n){let i=this.gpuDataManager.get(n);if(!i)throw new Error(`no GPU data for buffer: ${n}`);return i.buffer}createDownloader(n,i,s){return async()=>{let u=await kt(this,n,i);return Ue(u.buffer,s)}}writeTimestamp(n){this.queryType==="inside-passes"&&this.computePassEncoder.writeTimestamp(this.querySet,n)}setQueryType(){var n;this.queryType="none",(((n=this.env.webgpu.profiling)==null?void 0:n.mode)==="default"||(typeof this.env.trace>"u"?this.env.wasm.trace:this.env.trace))&&(this.device.features.has("chromium-experimental-timestamp-query-inside-passes")?this.queryType="inside-passes":this.device.features.has("timestamp-query")&&(this.queryType="at-passes"),this.queryType!=="none"&&typeof this.querySet>"u"&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:this.maxDispatchNumber*2}),this.queryResolveBuffer=this.device.createBuffer({size:this.maxDispatchNumber*2*8,usage:GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE})))}captureBegin(){Vr("info","captureBegin"),this.capturedCommandList.get(this.currentSessionId)||this.capturedCommandList.set(this.currentSessionId,[]),this.capturedPendingKernels.get(this.currentSessionId)||this.capturedPendingKernels.set(this.currentSessionId,[]),this.flush(),this.sessionStatus="capturing"}captureEnd(){Vr("info","captureEnd"),this.flush(),this.sessionStatus="default"}replay(){Vr("info","replay"),this.sessionStatus="replaying";let n=this.capturedCommandList.get(this.currentSessionId),i=this.capturedPendingKernels.get(this.currentSessionId),s=n.length;this.pendingKernels=[];for(let u=0;u=this.maxDispatchNumber||this.queryType==="at-passes")&&this.endComputePass(),this.pendingDispatchNumber>=this.maxDispatchNumber&&this.flush()}this.flush(),this.sessionStatus="default"}onReleaseSession(n){this.unregisterBuffers(n),this.capturedCommandList.has(n)&&this.capturedCommandList.delete(n),this.capturedPendingKernels.has(n)&&this.capturedPendingKernels.delete(n),this.gpuDataManager.onReleaseSession(n)}onRunStart(n){this.currentSessionId=n,this.setQueryType()}}}),_w={};g(_w,{init:()=>yw});var Af,ww,yw,fx=h(()=>{Zt(),px(),jn(),Jt(),Af=class ex{constructor(i,s,u,c){this.module=i,this.dataType=s,this.data=u,this.dims=c}getFloat32Array(){if(this.dataType!==1)throw new Error("Invalid data type");let i=ct.size(this.dims);return i===0?new Float32Array:new Float32Array(this.module.HEAP8.buffer,this.data,i)}getBigInt64Array(){if(this.dataType!==7)throw new Error("Invalid data type");let i=ct.size(this.dims);return i===0?new BigInt64Array:new BigInt64Array(this.module.HEAP8.buffer,this.data,i)}getInt32Array(){if(this.dataType!==6)throw new Error("Invalid data type");let i=ct.size(this.dims);return i===0?new Int32Array:new Int32Array(this.module.HEAP8.buffer,this.data,i)}reshape(i){if(ct.size(i)!==ct.size(this.dims))throw new Error("Invalid new shape");return new ex(this.module,this.dataType,this.data,i)}},ww=class{constructor(n,i,s){this.module=n,this.backend=i,this.customDataOffset=0,this.customDataSize=0,this.adapterInfo=i.adapterInfo;let u=n.HEAPU32,c=s>>>2;this.opKernelContext=u[c++];let f=u[c++];this.outputCount=u[c++],this.customDataOffset=u[c++],this.customDataSize=u[c++];let d=[];for(let x=0;xtypeof x=="number"?this.inputs[x]:x))??this.inputs,u=(i==null?void 0:i.outputs)??[],c=(x,k,$)=>new Af(this.module,k,this.output(x,$),$),f=(x,k)=>{let $=ki(x);if(!$)throw new Error(`Unsupported data type: ${x}`);let H=$*ct.size(k),q=H>0?this.backend.gpuDataManager.create(H).id:0;return new Af(this.module,x,q,k)};return this.backend.run(n,s,u,c,f,this.outputCount)}output(n,i){let s=this.module.stackSave();try{let u=this.module.stackAlloc((1+i.length)*4),c=u>>2;this.module.HEAPU32[c++]=i.length;for(let f=0;f{let c=i.jsepInit;if(!c)throw new Error("Failed to initialize JSEP. The WebAssembly module is not built with JSEP support.");if(n==="webgpu"){let f=new gw;await f.initialize(s,u),c("webgpu",[f,d=>f.alloc(d),d=>f.free(d),(d,x,k,$=!1)=>{if($)Vr("verbose",()=>`[WebGPU] jsepCopyGpuToGpu: src=${d}, dst=${x}, size=${k}`),f.memcpy(d,x);else{Vr("verbose",()=>`[WebGPU] jsepCopyCpuToGpu: dataOffset=${d}, gpuDataId=${x}, size=${k}`);let H=i.HEAPU8.subarray(d>>>0,(d>>>0)+k);f.upload(x,H)}},async(d,x,k)=>{Vr("verbose",()=>`[WebGPU] jsepCopyGpuToCpu: gpuDataId=${d}, dataOffset=${x}, size=${k}`),await f.download(d,()=>i.HEAPU8.subarray(x>>>0,(x>>>0)+k))},(d,x,k)=>f.createKernel(d,x,k,i.UTF8ToString(i._JsepGetNodeName(x))),d=>f.releaseKernel(d),(d,x,k,$)=>{Vr("verbose",()=>`[WebGPU] jsepRun: sessionHandle=${k}, kernel=${d}, contextDataOffset=${x}`);let H=new ww(i,f,x);return f.computeKernel(d,H,$)},()=>f.captureBegin(),()=>f.captureEnd(),()=>f.replay()])}else c("webnn")}}),vw,xm,Mm,es,bw,If,Tm,km,Sm,Em,Cm,Pm,xw=h(()=>{Cs(),Ps(),Zt(),wn(),Ni(),jo(),vw=(n,i)=>{Gr()._OrtInit(n,i)!==0&&Dr("Can't initialize onnxruntime.")},xm=async n=>{vw(n.wasm.numThreads,Ji(n.logLevel))},Mm=async(n,i)=>{{let s=(fx(),y(_w)).init;if(i==="webgpu"){if(typeof navigator>"u"||!navigator.gpu)throw new Error("WebGPU is not supported in current environment");let u=n.webgpu.adapter;if(u){if(typeof u.limits!="object"||typeof u.features!="object"||typeof u.requestDevice!="function")throw new Error("Invalid GPU adapter set in `env.webgpu.adapter`. It must be a GPUAdapter object.")}else{let c=n.webgpu.powerPreference;if(c!==void 0&&c!=="low-power"&&c!=="high-performance")throw new Error(`Invalid powerPreference setting: "${c}"`);let f=n.webgpu.forceFallbackAdapter;if(f!==void 0&&typeof f!="boolean")throw new Error(`Invalid forceFallbackAdapter setting: "${f}"`);if(u=await navigator.gpu.requestAdapter({powerPreference:c,forceFallbackAdapter:f}),!u)throw new Error('Failed to get GPU adapter. You may need to enable flag "--enable-unsafe-webgpu" if you are using Chrome.')}await s("webgpu",Gr(),n,u)}if(i==="webnn"){if(typeof navigator>"u"||!navigator.ml)throw new Error("WebNN is not supported in current environment");await s("webnn",Gr(),n)}}},es=new Map,bw=n=>{let i=Gr(),s=i.stackSave();try{let u=i.stackAlloc(8);return i._OrtGetInputOutputCount(n,u,u+4)!==0&&Dr("Can't get session input/output count."),[i.HEAP32[u/4],i.HEAP32[u/4+1]]}finally{i.stackRestore(s)}},If=n=>{let i=Gr(),s=i._malloc(n.byteLength);if(s===0)throw new Error(`Can't create a session. failed to allocate a buffer of size ${n.byteLength}.`);return i.HEAPU8.set(n,s),[s,n.byteLength]},Tm=async(n,i)=>{var q,v;let s,u,c=Gr();Array.isArray(n)?[s,u]=n:n.buffer===c.HEAPU8.buffer?[s,u]=[n.byteOffset,n.byteLength]:[s,u]=If(n);let f=0,d=0,x=0,k=[],$=[],H=[];try{if([d,k]=ji(i),(i==null?void 0:i.externalData)&&c.mountExternalData){let Ae=[];for(let Ie of i.externalData){let gt=typeof 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All Rights Reserved. + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * ============================================================================= + *//** + * @license + * Copyright 2020 Google LLC. All Rights Reserved. + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * ============================================================================= + *//** + * @license + * Copyright 2019 Google LLC. All Rights Reserved. + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * ============================================================================= + */},"./src/backends/onnx.js":(e,t,r)=>{var o;r.r(t),r.d(t,{Tensor:()=>_.Tensor,createInferenceSession:()=>S,deviceToExecutionProviders:()=>T,isONNXProxy:()=>b,isONNXTensor:()=>C});var a=r("./src/env.js"),l=r("?2ce3"),p=r("./node_modules/onnxruntime-web/dist/ort.webgpu.bundle.min.mjs"),_=r("./node_modules/onnxruntime-common/dist/esm/index.js");const h=Object.freeze({auto:null,gpu:null,cpu:"cpu",wasm:"wasm",webgpu:"webgpu",cuda:"cuda",dml:"dml",webnn:{name:"webnn",deviceType:"cpu"},"webnn-npu":{name:"webnn",deviceType:"npu"},"webnn-gpu":{name:"webnn",deviceType:"gpu"},"webnn-cpu":{name:"webnn",deviceType:"cpu"}}),g=[];let M,y;if(a.apis.IS_NODE_ENV){switch(y=l??(o||(o=r.t(l,2))),process.platform){case"win32":g.push("dml");break;case"linux":process.arch==="x64"&&g.push("cuda");break}g.push("cpu"),M=["cpu"]}else y=p,a.apis.IS_WEBNN_AVAILABLE&&g.push("webnn-npu","webnn-gpu","webnn-cpu","webnn"),a.apis.IS_WEBGPU_AVAILABLE&&g.push("webgpu"),g.push("wasm"),M=["wasm"];const E=y.InferenceSession;function T(I=null){if(!I)return M;switch(I){case"auto":return g;case"gpu":return g.filter(U=>["webgpu","cuda","dml","webnn-gpu"].includes(U))}if(g.includes(I))return[h[I]??I];throw new Error(`Unsupported device: "${I}". 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ae(ne,Ee)}async function Se(V,G,ne=!1){const Ee=V.sessions[ne?"decoder_model_merged":"model"],{past_key_values:Ze,...it}=G;Ee.inputNames.includes("use_cache_branch")&&(it.use_cache_branch=Y(!!Ze)),Ee.inputNames.includes("position_ids")&&it.attention_mask&&!it.position_ids&&(it.position_ids=me(it,Ze)),V.addPastKeyValues(it,Ze);const wt=(0,_.pick)(it,Ee.inputNames);return await ae(Ee,wt)}async function Xe(V,{input_ids:G=null,attention_mask:ne=null,pixel_values:Ee=null,position_ids:Ze=null,inputs_embeds:it=null,past_key_values:wt=null,generation_config:Ct=null,logits_processor:Wt=null,...cr}){if(!it){if(it=await V.encode_text({input_ids:G}),Ee&&G.dims[1]!==1){const Ir=await V.encode_image({pixel_values:Ee});({inputs_embeds:it,attention_mask:ne}=V._merge_input_ids_with_image_features({image_features:Ir,inputs_embeds:it,input_ids:G,attention_mask:ne}))}else if(wt&&Ee&&G.dims[1]===1){const 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p.Callable{constructor(ne,Ee){super();He(this,"main_input_name","input_ids");He(this,"forward_params",["input_ids","attention_mask"]);this.config=ne,this.sessions=Ee;const Ze=z.get(this.constructor),it=I.get(Ze);switch(this.can_generate=!1,this._forward=null,this._prepare_inputs_for_generation=null,it){case b.DecoderOnly:this.can_generate=!0,this._forward=Se,this._prepare_inputs_for_generation=X;break;case b.Seq2Seq:case b.Vision2Seq:case b.Musicgen:this.can_generate=!0,this._forward=_e,this._prepare_inputs_for_generation=ie;break;case b.EncoderDecoder:this._forward=_e;break;case b.ImageTextToText:this.can_generate=!0,this._forward=Xe,this._prepare_inputs_for_generation=Me;break;default:this._forward=L;break}this.can_generate&&this.forward_params.push("past_key_values"),this.custom_config=this.config["transformers.js_config"]??{}}async dispose(){var Ee;const ne=[];for(const Ze of Object.values(this.sessions))(Ee=Ze==null?void 0:Ze.handler)!=null&&Ee.dispose&&ne.push(Ze.handler.dispose());return await Promise.all(ne)}static async from_pretrained(ne,{progress_callback:Ee=null,config:Ze=null,cache_dir:it=null,local_files_only:wt=!1,revision:Ct="main",model_file_name:Wt=null,subfolder:cr="onnx",device:lr=null,dtype:Ir=null,use_external_data_format:dr=null,session_options:wr={}}={}){let pr={progress_callback:Ee,config:Ze,cache_dir:it,local_files_only:wt,revision:Ct,model_file_name:Wt,subfolder:cr,device:lr,dtype:Ir,use_external_data_format:dr,session_options:wr};const mr=z.get(this),xr=I.get(mr);Ze=pr.config=await o.AutoConfig.from_pretrained(ne,pr);let Nr;if(xr===b.DecoderOnly)Nr=await Promise.all([j(ne,{model:pr.model_file_name??"model"},pr),(0,h.getModelJSON)(ne,"generation_config.json",!1,pr)]);else if(xr===b.Seq2Seq||xr===b.Vision2Seq)Nr=await Promise.all([j(ne,{model:"encoder_model",decoder_model_merged:"decoder_model_merged"},pr),(0,h.getModelJSON)(ne,"generation_config.json",!1,pr)]);else if(xr===b.MaskGeneration)Nr=await Promise.all([j(ne,{model:"vision_encoder",prompt_encoder_mask_decoder:"prompt_encoder_mask_decoder"},pr)]);else if(xr===b.EncoderDecoder)Nr=await Promise.all([j(ne,{model:"encoder_model",decoder_model_merged:"decoder_model_merged"},pr)]);else if(xr===b.ImageTextToText){const $n={embed_tokens:"embed_tokens",vision_encoder:"vision_encoder",decoder_model_merged:"decoder_model_merged"};Ze.is_encoder_decoder&&($n.model="encoder_model"),Nr=await Promise.all([j(ne,$n,pr),(0,h.getModelJSON)(ne,"generation_config.json",!1,pr)])}else xr===b.Musicgen?Nr=await Promise.all([j(ne,{model:"text_encoder",decoder_model_merged:"decoder_model_merged",encodec_decode:"encodec_decode"},pr),(0,h.getModelJSON)(ne,"generation_config.json",!1,pr)]):(xr!==b.EncoderOnly&&console.warn(`Model type for '${mr??(Ze==null?void 0:Ze.model_type)}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`),Nr=await Promise.all([j(ne,{model:pr.model_file_name??"model"},pr)]));return new this(Ze,...Nr)}async _call(ne){return await this.forward(ne)}async forward(ne){return await this._forward(this,ne)}_get_logits_warper(ne){const Ee=new g.LogitsProcessorList;return ne.temperature!==null&&ne.temperature!==1&&Ee.push(new g.TemperatureLogitsWarper(ne.temperature)),ne.top_k!==null&&ne.top_k!==0&&Ee.push(new g.TopKLogitsWarper(ne.top_k)),ne.top_p!==null&&ne.top_p<1&&Ee.push(new g.TopPLogitsWarper(ne.top_p)),Ee}_get_logits_processor(ne,Ee,Ze=null){const it=new g.LogitsProcessorList;if(ne.repetition_penalty!==null&&ne.repetition_penalty!==1&&it.push(new g.RepetitionPenaltyLogitsProcessor(ne.repetition_penalty)),ne.no_repeat_ngram_size!==null&&ne.no_repeat_ngram_size>0&&it.push(new g.NoRepeatNGramLogitsProcessor(ne.no_repeat_ngram_size)),ne.bad_words_ids!==null&&it.push(new g.NoBadWordsLogitsProcessor(ne.bad_words_ids,ne.eos_token_id)),ne.min_length!==null&&ne.eos_token_id!==null&&ne.min_length>0&&it.push(new g.MinLengthLogitsProcessor(ne.min_length,ne.eos_token_id)),ne.min_new_tokens!==null&&ne.eos_token_id!==null&&ne.min_new_tokens>0&&it.push(new g.MinNewTokensLengthLogitsProcessor(Ee,ne.min_new_tokens,ne.eos_token_id)),ne.forced_bos_token_id!==null&&it.push(new g.ForcedBOSTokenLogitsProcessor(ne.forced_bos_token_id)),ne.forced_eos_token_id!==null&&it.push(new g.ForcedEOSTokenLogitsProcessor(ne.max_length,ne.forced_eos_token_id)),ne.begin_suppress_tokens!==null){const wt=Ee>1||ne.forced_bos_token_id===null?Ee:Ee+1;it.push(new g.SuppressTokensAtBeginLogitsProcessor(ne.begin_suppress_tokens,wt))}return ne.guidance_scale!==null&&ne.guidance_scale>1&&it.push(new g.ClassifierFreeGuidanceLogitsProcessor(ne.guidance_scale)),Ze!==null&&it.extend(Ze),it}_prepare_generation_config(ne,Ee,Ze=M.GenerationConfig){const it={...this.config};for(const Ct of["decoder","generator","text_config"])Ct in it&&Object.assign(it,it[Ct]);const wt=new Ze(it);return"generation_config"in this&&Object.assign(wt,this.generation_config),ne&&Object.assign(wt,ne),Ee&&Object.assign(wt,(0,_.pick)(Ee,Object.getOwnPropertyNames(wt))),wt}_get_stopping_criteria(ne,Ee=null){const Ze=new T.StoppingCriteriaList;return ne.max_length!==null&&Ze.push(new T.MaxLengthCriteria(ne.max_length,this.config.max_position_embeddings??null)),ne.eos_token_id!==null&&Ze.push(new T.EosTokenCriteria(ne.eos_token_id)),Ee&&Ze.extend(Ee),Ze}_validate_model_class(){if(!this.can_generate){const ne=[Hs,bl,vl,Gs],Ee=z.get(this.constructor),Ze=new Set,it=this.config.model_type;for(const Ct of ne){const Wt=Ct.get(it);Wt&&Ze.add(Wt[0])}let wt=`The current model class (${Ee}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;throw Ze.size>0&&(wt+=` Please use the following class instead: ${[...Ze].join(", ")}`),Error(wt)}}prepare_inputs_for_generation(...ne){return this._prepare_inputs_for_generation(this,...ne)}_update_model_kwargs_for_generation({generated_input_ids:ne,outputs:Ee,model_inputs:Ze,is_encoder_decoder:it}){return Ze.past_key_values=this.getPastKeyValues(Ee,Ze.past_key_values),Ze.input_ids=new y.Tensor("int64",ne.flat(),[ne.length,1]),it||(Ze.attention_mask=(0,y.cat)([Ze.attention_mask,(0,y.ones)([Ze.attention_mask.dims[0],1])],1)),Ze.position_ids=null,Ze}_prepare_model_inputs({inputs:ne,bos_token_id:Ee,model_kwargs:Ze}){const it=(0,_.pick)(Ze,this.forward_params),wt=this.main_input_name;if(wt in it){if(ne)throw new Error("`inputs`: {inputs}` were passed alongside {input_name} which is not allowed. Make sure to either pass {inputs} or {input_name}=...")}else it[wt]=ne;return{inputs_tensor:it[wt],model_inputs:it,model_input_name:wt}}async _prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:ne,model_inputs:Ee,model_input_name:Ze,generation_config:it}){if(this.sessions.model.inputNames.includes("inputs_embeds")&&!Ee.inputs_embeds&&"_prepare_inputs_embeds"in this){const{input_ids:Ct,pixel_values:Wt,attention_mask:cr,...lr}=Ee,Ir=await this._prepare_inputs_embeds(Ee);Ee={...lr,...(0,_.pick)(Ir,["inputs_embeds","attention_mask"])}}let{last_hidden_state:wt}=await L(this,Ee);if(it.guidance_scale!==null&&it.guidance_scale>1)wt=(0,y.cat)([wt,(0,y.full_like)(wt,0)],0),"attention_mask"in Ee&&(Ee.attention_mask=(0,y.cat)([Ee.attention_mask,(0,y.zeros_like)(Ee.attention_mask)],0));else if(Ee.decoder_input_ids){const Ct=xe(Ee.decoder_input_ids).dims[0];if(Ct!==wt.dims[0]){if(wt.dims[0]!==1)throw new Error(`The encoder outputs have a different batch size (${wt.dims[0]}) than the decoder inputs (${Ct}).`);wt=(0,y.cat)(Array.from({length:Ct},()=>wt),0)}}return Ee.encoder_outputs=wt,Ee}_prepare_decoder_input_ids_for_generation({batch_size:ne,model_input_name:Ee,model_kwargs:Ze,decoder_start_token_id:it,bos_token_id:wt,generation_config:Ct}){let{decoder_input_ids:Wt,...cr}=Ze;if(Wt)Array.isArray(Wt[0])||(Wt=Array.from({length:ne},()=>Wt));else if(it??(it=wt),this.config.model_type==="musicgen")Wt=Array.from({length:ne*this.config.decoder.num_codebooks},()=>[it]);else if(Array.isArray(it)){if(it.length!==ne)throw new Error(`\`decoder_start_token_id\` expcted to have length ${ne} but got ${it.length}`);Wt=it}else Wt=Array.from({length:ne},()=>[it]);return Wt=xe(Wt),Ze.decoder_attention_mask=(0,y.ones_like)(Wt),{input_ids:Wt,model_inputs:cr}}async generate({inputs:ne=null,generation_config:Ee=null,logits_processor:Ze=null,stopping_criteria:it=null,streamer:wt=null,...Ct}){this._validate_model_class(),Ee=this._prepare_generation_config(Ee,Ct);let{inputs_tensor:Wt,model_inputs:cr,model_input_name:lr}=this._prepare_model_inputs({inputs:ne,model_kwargs:Ct});const Ir=this.config.is_encoder_decoder;Ir&&("encoder_outputs"in cr||(cr=await this._prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:Wt,model_inputs:cr,model_input_name:lr,generation_config:Ee})));let dr;Ir?{input_ids:dr,model_inputs:cr}=this._prepare_decoder_input_ids_for_generation({batch_size:cr[lr].dims.at(0),model_input_name:lr,model_kwargs:cr,decoder_start_token_id:Ee.decoder_start_token_id,bos_token_id:Ee.bos_token_id,generation_config:Ee}):dr=cr[lr];let wr=dr.dims.at(-1);Ee.max_new_tokens!==null&&(Ee.max_length=wr+Ee.max_new_tokens);const pr=this._get_logits_processor(Ee,wr,Ze),mr=this._get_stopping_criteria(Ee,it),xr=cr[lr].dims.at(0),Nr=O.LogitsSampler.getSampler(Ee),$n=new Array(xr).fill(0),zn=dr.tolist();wt&&wt.put(zn);let Pi=null,Mn={};for(;;){cr=this.prepare_inputs_for_generation(zn,cr,Ee);const Tn=await this.forward(cr);if(Ee.output_attentions&&Ee.return_dict_in_generate){const mi=this.getAttentions(Tn);for(const Jo in mi)Jo in Mn||(Mn[Jo]=[]),Mn[Jo].push(mi[Jo])}const qs=Tn.logits.slice(null,-1,null),Ks=pr(zn,qs),El=[];for(let mi=0;mimi)){Ee.return_dict_in_generate&&(Pi=this.getPastKeyValues(Tn,cr.past_key_values,!1));break}cr=this._update_model_kwargs_for_generation({generated_input_ids:El,outputs:Tn,model_inputs:cr,is_encoder_decoder:Ir})}wt&&wt.end();const dn=new y.Tensor("int64",zn.flat(),[zn.length,zn[0].length]);return Ee.return_dict_in_generate?{sequences:dn,past_key_values:Pi,...Mn}:dn}getPastKeyValues(ne,Ee,Ze=!0){const it=Object.create(null);for(const wt in ne)if(wt.startsWith("present")){const Ct=wt.replace("present","past_key_values");if(Ee&&wt.includes("encoder"))it[Ct]=Ee[Ct];else{if(Ze&&Ee){const Wt=Ee[Ct];Wt.location==="gpu-buffer"&&Wt.dispose()}it[Ct]=ne[wt]}}return it}getAttentions(ne){const Ee={};for(const Ze of["cross_attentions","encoder_attentions","decoder_attentions"])for(const it in ne)it.startsWith(Ze)&&(Ze in Ee||(Ee[Ze]=[]),Ee[Ze].push(ne[it]));return Ee}addPastKeyValues(ne,Ee){if(Ee)Object.assign(ne,Ee);else{const Ze=this.custom_config.kv_cache_dtype??"float32",it=Ze==="float16"?new Uint16Array:[],wt=(0,o.getKeyValueShapes)(this.config);for(const Ct in wt)ne[Ct]=new y.Tensor(Ze,it,wt[Ct])}}async encode_image({pixel_values:ne}){const Ee=(await ae(this.sessions.vision_encoder,{pixel_values:ne})).image_features;return this.config.num_image_tokens||(console.warn(`The number of image tokens was not set in the model configuration. Setting it to the number of features detected by the vision encoder (${Ee.dims[1]}).`),this.config.num_image_tokens=Ee.dims[1]),Ee}async encode_text({input_ids:ne}){return(await ae(this.sessions.embed_tokens,{input_ids:ne})).inputs_embeds}}class ge{}class Ke extends ge{constructor({last_hidden_state:G,hidden_states:ne=null,attentions:Ee=null}){super(),this.last_hidden_state=G,this.hidden_states=ne,this.attentions=Ee}}class Le extends Q{}class Be extends Le{}class We extends Le{async _call(G){return new bn(await super._call(G))}}class st extends Le{async _call(G){return new ur(await super._call(G))}}class pt extends Le{async _call(G){return new hn(await super._call(G))}}class Ge extends Le{async _call(G){return new xn(await super._call(G))}}class Te extends Q{}class je extends Te{}class Ye extends Q{}class et extends Ye{}class A extends Ye{async _call(G){return new bn(await super._call(G))}}class $e extends Ye{async _call(G){return new ur(await super._call(G))}}class Pe extends Ye{async _call(G){return new hn(await super._call(G))}}class se extends Ye{async _call(G){return new xn(await super._call(G))}}class re extends Q{}class ye extends re{}class R extends re{async _call(G){return new bn(await super._call(G))}}class ee extends re{async _call(G){return new ur(await super._call(G))}}class D extends re{async _call(G){return new hn(await super._call(G))}}class ue extends re{async _call(G){return new xn(await super._call(G))}}class le extends Q{}class ke extends le{}class Ne extends le{async _call(G){return new bn(await super._call(G))}}class dt extends le{async _call(G){return new ur(await super._call(G))}}class Je extends le{async _call(G){return new hn(await super._call(G))}}class Ve extends le{async _call(G){return new xn(await super._call(G))}}class Z extends Q{}class ve extends Z{}class Re extends Z{async _call(G){return new bn(await super._call(G))}}class qe extends Z{async _call(G){return new ur(await super._call(G))}}class Qe extends Z{async _call(G){return new hn(await super._call(G))}}class tt extends Z{async _call(G){return new xn(await super._call(G))}}class ft extends Q{}class ht extends ft{}class Tt extends ft{async _call(G){return new bn(await super._call(G))}}class bt extends ft{async _call(G){return new ur(await super._call(G))}}class Et extends ft{async _call(G){return new hn(await super._call(G))}}class Lt extends ft{async _call(G){return new xn(await super._call(G))}}class at extends Q{}class Ot extends at{}class Ut extends at{async _call(G){return new bn(await super._call(G))}}class Xt extends at{async _call(G){return new ur(await super._call(G))}}class Yt extends at{async _call(G){return new hn(await super._call(G))}}class rr extends at{async _call(G){return new xn(await super._call(G))}}class Ht extends Q{}class Pr extends Ht{}class Yr extends Ht{async _call(G){return new ur(await super._call(G))}}class $r extends Ht{async _call(G){return new hn(await super._call(G))}}class mt extends Ht{async _call(G){return new xn(await super._call(G))}}class $t extends Ht{async _call(G){return new bn(await super._call(G))}}class Bt extends Q{}class un extends Bt{}class Bi extends Bt{async _call(G){return new bn(await super._call(G))}}class Mi extends Bt{async _call(G){return new ur(await super._call(G))}}class Gr extends Bt{async _call(G){return new hn(await super._call(G))}}class wn extends Q{}class Kr extends wn{}class pi extends wn{async _call(G){return new bn(await super._call(G))}}class Dr extends wn{async _call(G){return new ur(await super._call(G))}}class Ni extends wn{async _call(G){return new xn(await super._call(G))}}class Ti extends Q{}class Cs extends Ti{}class Lo extends Ti{async _call(G){return new bn(await super._call(G))}}class Ro extends Ti{async _call(G){return new ur(await super._call(G))}}class Bo extends Ti{async _call(G){return new hn(await super._call(G))}}class No extends Ti{async _call(G){return new xn(await super._call(G))}}class ji extends Q{}class Ps extends ji{}class fo extends ji{async _call(G){return new bn(await super._call(G))}}class fi extends ji{async _call(G){return new ur(await super._call(G))}}class ki extends ji{async _call(G){return new xn(await super._call(G))}}class Si extends Q{}class Ji extends Si{}class ho extends Si{async _call(G){return new ur(await super._call(G))}}class mo extends Si{async _call(G){return new xn(await super._call(G))}}class Zt extends Si{async _call(G){return new bn(await super._call(G))}}class eo extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(this,"forward_params",["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"]);this.generation_config=Ze}}class jo extends eo{}class Uo extends eo{}class go extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Vo extends go{}class Wo extends go{}class _o extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Go extends _o{}class Vr extends _o{}class jn extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Ue extends jn{}class W extends jn{}class pe extends jn{async _call(G){return new ur(await super._call(G))}}class Ce extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Fe extends Ce{}class Oe extends Ce{}class rt extends Ce{async _call(G){return new ur(await super._call(G))}}class Mt extends Ce{}class St extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class kt extends St{}class It extends St{}class tr extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Ar extends tr{}class or extends tr{}class qt extends Q{}class _r extends qt{}class Cn extends qt{async _call(G){return new bn(await super._call(G))}}class gn extends qt{async _call(G){return new ur(await super._call(G))}}class ct extends qt{async _call(G){return new hn(await super._call(G))}}class Kn extends qt{async _call(G){return new xn(await super._call(G))}}class Tr extends Q{}class cn extends Tr{}class On extends Tr{async _call(G){return new bn(await super._call(G))}}class Jt extends Tr{async _call(G){return new ur(await super._call(G))}}class Un extends Tr{async _call(G){return new hn(await super._call(G))}}class yn extends Tr{async _call(G){return new xn(await super._call(G))}}class Sr extends Q{}class Er extends Sr{}class At extends Sr{async _call(G){return new bn(await super._call(G))}}class vr extends Sr{async _call(G){return new ur(await super._call(G))}}class Lr extends Sr{async _call(G){return new hn(await super._call(G))}}class Xr extends Sr{async _call(G){return new xn(await super._call(G))}}class Vn extends Q{}class zt extends Vn{}class $s extends Vn{}class _t extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(this,"requires_attention_mask",!1);He(this,"main_input_name","input_features");He(this,"forward_params",["input_features","attention_mask","decoder_input_ids","decoder_attention_mask","past_key_values"]);this.generation_config=Ze}}class Gt extends _t{}class ma extends _t{_prepare_generation_config(G,ne){return super._prepare_generation_config(G,ne,C.WhisperGenerationConfig)}_retrieve_init_tokens(G){const ne=[G.decoder_start_token_id];let Ee=G.language;const Ze=G.task;if(G.is_multilingual){Ee||(console.warn("No language specified - defaulting to English (en)."),Ee="en");const wt=`<|${(0,w.whisper_language_to_code)(Ee)}|>`;ne.push(G.lang_to_id[wt]),ne.push(G.task_to_id[Ze??"transcribe"])}else if(Ee||Ze)throw new Error("Cannot specify `task` or `language` for an English-only model. If the model is intended to be multilingual, pass `is_multilingual=true` to generate, or update the generation config.");return!G.return_timestamps&&G.no_timestamps_token_id&&ne.at(-1)!==G.no_timestamps_token_id?ne.push(G.no_timestamps_token_id):G.return_timestamps&&ne.at(-1)===G.no_timestamps_token_id&&(console.warn("<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `true`."),ne.pop()),ne.filter(it=>it!=null)}async generate({inputs:G=null,generation_config:ne=null,logits_processor:Ee=null,stopping_criteria:Ze=null,...it}){ne=this._prepare_generation_config(ne,it);const wt=it.decoder_input_ids??this._retrieve_init_tokens(ne);if(ne.return_timestamps&&(Ee??(Ee=new g.LogitsProcessorList),Ee.push(new g.WhisperTimeStampLogitsProcessor(ne,wt))),ne.begin_suppress_tokens&&(Ee??(Ee=new g.LogitsProcessorList),Ee.push(new g.SuppressTokensAtBeginLogitsProcessor(ne.begin_suppress_tokens,wt.length))),ne.return_token_timestamps){if(!ne.alignment_heads)throw new Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");ne.task==="translate"&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),ne.output_attentions=!0,ne.return_dict_in_generate=!0}const Ct=await super.generate({inputs:G,generation_config:ne,logits_processor:Ee,decoder_input_ids:wt,...it});return ne.return_token_timestamps&&(Ct.token_timestamps=this._extract_token_timestamps(Ct,ne.alignment_heads,ne.num_frames)),Ct}_extract_token_timestamps(G,ne,Ee=null,Ze=.02){if(!G.cross_attentions)throw new Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");Ee==null&&console.warn("`num_frames` has not been set, meaning the entire audio will be analyzed. This may lead to inaccurate token-level timestamps for short audios (< 30 seconds).");let it=this.config.median_filter_width;it===void 0&&(console.warn("Model config has no `median_filter_width`, using default value of 7."),it=7);const wt=G.cross_attentions,Ct=Array.from({length:this.config.decoder_layers},(mr,xr)=>(0,y.cat)(wt.map(Nr=>Nr[xr]),2)),Wt=(0,y.stack)(ne.map(([mr,xr])=>{if(mr>=Ct.length)throw new Error(`Layer index ${mr} is out of bounds for cross attentions (length ${Ct.length}).`);return Ee?Ct[mr].slice(null,xr,null,[0,Ee]):Ct[mr].slice(null,xr)})).transpose(1,0,2,3),[cr,lr]=(0,y.std_mean)(Wt,-2,0,!0),Ir=Wt.clone();for(let mr=0;mrNr[Tn+1]-Nr[Tn]),Pi=(0,_.mergeArrays)([1],zn).map(dn=>!!dn),Mn=[];for(let dn=0;dndr.findIndex(wr=>wr==it)),Wt=Ct.every(dr=>dr===-1),cr=Ct.every(dr=>dr!==-1);if(!Wt&&!cr)throw new Error("Every input should contain either 0 or 1 image token.");if(Wt)return{inputs_embeds:G,attention_mask:Ze};const lr=[],Ir=[];for(let dr=0;drit*wt,1);G.input_labels=new y.Tensor("int64",new BigInt64Array(Ze).fill(1n),Ee)}const ne={image_embeddings:G.image_embeddings,image_positional_embeddings:G.image_positional_embeddings};return G.input_points&&(ne.input_points=G.input_points),G.input_labels&&(ne.input_labels=G.input_labels),G.input_boxes&&(ne.input_boxes=G.input_boxes),await ae(this.sessions.prompt_encoder_mask_decoder,ne)}async _call(G){return new Wc(await super._call(G))}}class Wc extends ge{constructor({iou_scores:G,pred_masks:ne}){super(),this.iou_scores=G,this.pred_masks=ne}}class Xa extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class sf extends Xa{}class Gc extends Xa{}class Qa extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Hc extends Qa{}class qc extends Qa{}class Ui extends Q{}class Kc extends Ui{}class af extends Ui{async _call(G){return new to(await super._call(G))}}class Vi extends Ui{async _call(G){return new ur(await super._call(G))}}class Wi extends Ui{async _call(G){return new hn(await super._call(G))}}class Ei extends Q{}class Ya extends Ei{}class Gi extends Ei{async _call(G){return new hn(await super._call(G))}}class vn extends Q{}class Za extends vn{}class xo extends Q{}class Ja extends xo{}class Xc extends xo{async _call(G){return new to(await super._call(G))}}class Qc extends xo{async _call(G){return new ur(await super._call(G))}}class qo extends Q{}class Rs extends qo{}class el extends qo{async _call(G){return new to(await super._call(G))}}class Yc extends qo{async _call(G){return new ur(await super._call(G))}}class Bs extends qo{async _call(G){return new hn(await super._call(G))}}class Ns extends Q{}class tl extends Ns{}class js extends Ns{async _call(G){return new to(await super._call(G))}}class Zc extends Ns{async _call(G){return new ur(await super._call(G))}}class lf extends Q{}class uf extends Ui{}class Jc extends Ui{async _call(G){return new to(await super._call(G))}}class rl extends Ui{async _call(G){return new ur(await super._call(G))}}class Ci extends Q{}class ed extends Ci{}class nl extends Ci{async _call(G){return new to(await super._call(G))}}class td extends Ci{async _call(G){return new ur(await super._call(G))}}class rd extends Ci{async _call(G){return new np(await super._call(G))}}class nd extends Ci{async _call(G){return new hn(await super._call(G))}}class il extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class id extends il{}class od extends il{}class cf extends il{async generate_speech(G,ne,{threshold:Ee=.5,minlenratio:Ze=0,maxlenratio:it=20,vocoder:wt=null}={}){const Ct={input_ids:G},{encoder_outputs:Wt,encoder_attention_mask:cr}=await L(this,Ct),lr=Wt.dims[1]/this.config.reduction_factor,Ir=Math.floor(lr*it),dr=Math.floor(lr*Ze),wr=this.config.num_mel_bins;let pr=[],mr=null,xr=null,Nr=0;for(;;){++Nr;const Pi=Y(!!xr);let Mn;xr?Mn=xr.output_sequence_out:Mn=new y.Tensor("float32",new Float32Array(wr),[1,1,wr]);let dn={use_cache_branch:Pi,output_sequence:Mn,encoder_attention_mask:cr,speaker_embeddings:ne,encoder_hidden_states:Wt};this.addPastKeyValues(dn,mr),xr=await ae(this.sessions.decoder_model_merged,dn),mr=this.getPastKeyValues(xr,mr);const{prob:Tn,spectrum:qs}=xr;if(pr.push(qs),Nr>=dr&&(Array.from(Tn.data).filter(Ks=>Ks>=Ee).length>0||Nr>=Ir))break}const $n=(0,y.cat)(pr),{waveform:zn}=await ae(wt.sessions.model,{spectrogram:$n});return{spectrogram:$n,waveform:zn}}}class ol extends Q{constructor(){super(...arguments);He(this,"main_input_name","spectrogram")}}class sd extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class ad extends sd{}class sl extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Us extends sl{}class Vs extends sl{}class al extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Ws extends al{}class ll extends al{}class ul extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class ld extends ul{}class ud extends ul{}class Ko extends Q{}class cd extends Ko{}class dd extends Ko{static async from_pretrained(G,ne={}){return ne.model_file_name??(ne.model_file_name="text_model"),super.from_pretrained(G,ne)}}class pd extends Ko{static async from_pretrained(G,ne={}){return ne.model_file_name??(ne.model_file_name="audio_model"),super.from_pretrained(G,ne)}}class df extends Q{}class cl extends df{async _call(G){return new Sf(await super._call(G))}}class Xo extends Q{}class mm extends Xo{}class fd extends Xo{}class hd extends Xo{}class dl extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class pl extends dl{}class md extends dl{}class fl extends Q{}class gd extends fl{}class _d extends fl{async _call(G){return new ur(await super._call(G))}}class hl extends Q{}class pf extends hl{}class gm extends hl{}class ml extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(this,"forward_params",["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"]);this.generation_config=Ze}_apply_and_filter_by_delay_pattern_mask(ne){const[Ee,Ze]=ne.dims,it=this.config.decoder.num_codebooks,wt=Ze-it;let Ct=0;for(let lr=0;lr0&&wr<=wt&&(ne.data[Ct++]=ne.data[lr])}const Wt=Math.floor(Ee/it),cr=Ct/(Wt*it);return new y.Tensor(ne.type,ne.data.slice(0,Ct),[Wt,it,cr])}prepare_inputs_for_generation(ne,Ee,Ze){let it=structuredClone(ne);for(let Ct=0;Ct=Wt&&(it[Ct][Wt]=BigInt(this.config.decoder.pad_token_id));return Ze.guidance_scale!==null&&Ze.guidance_scale>1&&(it=it.concat(it)),super.prepare_inputs_for_generation(it,Ee,Ze)}async generate(ne){const Ee=await super.generate(ne),Ze=this._apply_and_filter_by_delay_pattern_mask(Ee).unsqueeze_(0),{audio_values:it}=await ae(this.sessions.encodec_decode,{audio_codes:Ze});return it}}class gl extends Q{}class wd extends gl{}class ff extends gl{async _call(G){return new ur(await super._call(G))}}class _l extends Q{}class yd extends _l{}class vd extends _l{async _call(G){return new ur(await super._call(G))}}class wl extends Q{}class bd extends wl{}class hf extends wl{async _call(G){return new ur(await super._call(G))}}class Qo extends Q{}class Yo extends Qo{}class yl extends Qo{async _call(G){return new ur(await super._call(G))}}class Rr{static async from_pretrained(G,{progress_callback:ne=null,config:Ee=null,cache_dir:Ze=null,local_files_only:it=!1,revision:wt="main",model_file_name:Ct=null,subfolder:Wt="onnx",device:cr=null,dtype:lr=null,use_external_data_format:Ir=null,session_options:dr={}}={}){let wr={progress_callback:ne,config:Ee,cache_dir:Ze,local_files_only:it,revision:wt,model_file_name:Ct,subfolder:Wt,device:cr,dtype:lr,use_external_data_format:Ir,session_options:dr};if(wr.config=await o.AutoConfig.from_pretrained(G,wr),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let pr of this.MODEL_CLASS_MAPPINGS){const mr=pr.get(wr.config.model_type);if(mr)return await mr[1].from_pretrained(G,wr)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${wr.config.model_type}", attempting to construct from base class.`),await Q.from_pretrained(G,wr);throw Error(`Unsupported model type: ${wr.config.model_type}`)}}He(Rr,"MODEL_CLASS_MAPPINGS",null),He(Rr,"BASE_IF_FAIL",!1);const mf=new Map([["bert",["BertModel",Be]],["nomic_bert",["NomicBertModel",je]],["roformer",["RoFormerModel",et]],["electra",["ElectraModel",ke]],["esm",["EsmModel",un]],["convbert",["ConvBertModel",ye]],["camembert",["CamembertModel",ve]],["deberta",["DebertaModel",ht]],["deberta-v2",["DebertaV2Model",Ot]],["mpnet",["MPNetModel",Cs]],["albert",["AlbertModel",Ji]],["distilbert",["DistilBertModel",Pr]],["roberta",["RobertaModel",_r]],["xlm",["XLMModel",cn]],["xlm-roberta",["XLMRobertaModel",Er]],["clap",["ClapModel",cd]],["clip",["CLIPModel",pu]],["clipseg",["CLIPSegModel",wu]],["chinese_clip",["ChineseCLIPModel",_u]],["siglip",["SiglipModel",yo]],["mobilebert",["MobileBertModel",Kr]],["squeezebert",["SqueezeBertModel",Ps]],["wav2vec2",["Wav2Vec2Model",Kc]],["wav2vec2-bert",["Wav2Vec2BertModel",tl]],["unispeech",["UniSpeechModel",Ja]],["unispeech-sat",["UniSpeechSatModel",Rs]],["hubert",["HubertModel",uf]],["wavlm",["WavLMModel",ed]],["audio-spectrogram-transformer",["ASTModel",zt]],["vits",["VitsModel",cl]],["pyannote",["PyAnnoteModel",Ya]],["wespeaker-resnet",["WeSpeakerResNetModel",Za]],["detr",["DetrModel",dc]],["rt_detr",["RTDetrModel",mc]],["table-transformer",["TableTransformerModel",_c]],["vit",["ViTModel",Xu]],["fastvit",["FastViTModel",Yu]],["mobilevit",["MobileViTModel",rc]],["mobilevitv2",["MobileViTV2Model",of]],["owlvit",["OwlViTModel",oc]],["owlv2",["Owlv2Model",ac]],["beit",["BeitModel",uc]],["deit",["DeiTModel",vc]],["convnext",["ConvNextModel",Ic]],["convnextv2",["ConvNextV2Model",zc]],["dinov2",["Dinov2Model",Lc]],["resnet",["ResNetModel",xc]],["swin",["SwinModel",Tc]],["swin2sr",["Swin2SRModel",Sc]],["donut-swin",["DonutSwinModel",Ha]],["yolos",["YolosModel",Bc]],["dpt",["DPTModel",Va]],["glpn",["GLPNModel",Pc]],["hifigan",["SpeechT5HifiGan",ol]],["efficientnet",["EfficientNetModel",gd]],["mobilenet_v1",["MobileNetV1Model",wd]],["mobilenet_v2",["MobileNetV2Model",yd]],["mobilenet_v3",["MobileNetV3Model",bd]],["mobilenet_v4",["MobileNetV4Model",Yo]]]),gf=new Map([["t5",["T5Model",jo]],["longt5",["LongT5Model",Vo]],["mt5",["MT5Model",Go]],["bart",["BartModel",Ue]],["mbart",["MBartModel",Fe]],["marian",["MarianModel",sf]],["whisper",["WhisperModel",Gt]],["m2m_100",["M2M100Model",Hc]],["blenderbot",["BlenderbotModel",kt]],["blenderbot-small",["BlenderbotSmallModel",Ar]]]),_f=new Map([["bloom",["BloomModel",Wu]],["gpt2",["GPT2Model",vu]],["gptj",["GPTJModel",Su]],["gpt_bigcode",["GPTBigCodeModel",Cu]],["gpt_neo",["GPTNeoModel",xu]],["gpt_neox",["GPTNeoXModel",Tu]],["codegen",["CodeGenModel",Pu]],["llama",["LlamaModel",ii]],["cohere",["CohereModel",Au]],["gemma",["GemmaModel",Fu]],["gemma2",["Gemma2Model",zu]],["openelm",["OpenELMModel",Lu]],["qwen2",["Qwen2Model",Bu]],["phi",["PhiModel",ju]],["phi3",["Phi3Model",Vu]],["mpt",["MptModel",nf]],["opt",["OPTModel",qu]],["mistral",["MistralModel",Us]],["starcoder2",["Starcoder2Model",Ws]],["falcon",["FalconModel",ld]],["stablelm",["StableLmModel",pl]]]),Gs=new Map([["speecht5",["SpeechT5ForSpeechToText",od]],["whisper",["WhisperForConditionalGeneration",ma]]]),xd=new Map([["speecht5",["SpeechT5ForTextToSpeech",cf]]]),Md=new Map([["vits",["VitsModel",cl]],["musicgen",["MusicgenForConditionalGeneration",ml]]]),Td=new Map([["bert",["BertForSequenceClassification",st]],["roformer",["RoFormerForSequenceClassification",$e]],["electra",["ElectraForSequenceClassification",dt]],["esm",["EsmForSequenceClassification",Mi]],["convbert",["ConvBertForSequenceClassification",ee]],["camembert",["CamembertForSequenceClassification",qe]],["deberta",["DebertaForSequenceClassification",bt]],["deberta-v2",["DebertaV2ForSequenceClassification",Xt]],["mpnet",["MPNetForSequenceClassification",Ro]],["albert",["AlbertForSequenceClassification",ho]],["distilbert",["DistilBertForSequenceClassification",Yr]],["roberta",["RobertaForSequenceClassification",gn]],["xlm",["XLMForSequenceClassification",Jt]],["xlm-roberta",["XLMRobertaForSequenceClassification",vr]],["bart",["BartForSequenceClassification",pe]],["mbart",["MBartForSequenceClassification",rt]],["mobilebert",["MobileBertForSequenceClassification",Dr]],["squeezebert",["SqueezeBertForSequenceClassification",fi]]]),wf=new Map([["bert",["BertForTokenClassification",pt]],["roformer",["RoFormerForTokenClassification",Pe]],["electra",["ElectraForTokenClassification",Je]],["esm",["EsmForTokenClassification",Gr]],["convbert",["ConvBertForTokenClassification",D]],["camembert",["CamembertForTokenClassification",Qe]],["deberta",["DebertaForTokenClassification",Et]],["deberta-v2",["DebertaV2ForTokenClassification",Yt]],["mpnet",["MPNetForTokenClassification",Bo]],["distilbert",["DistilBertForTokenClassification",$r]],["roberta",["RobertaForTokenClassification",ct]],["xlm",["XLMForTokenClassification",Un]],["xlm-roberta",["XLMRobertaForTokenClassification",Lr]]]),vl=new Map([["t5",["T5ForConditionalGeneration",Uo]],["longt5",["LongT5ForConditionalGeneration",Wo]],["mt5",["MT5ForConditionalGeneration",Vr]],["bart",["BartForConditionalGeneration",W]],["mbart",["MBartForConditionalGeneration",Oe]],["marian",["MarianMTModel",Gc]],["m2m_100",["M2M100ForConditionalGeneration",qc]],["blenderbot",["BlenderbotForConditionalGeneration",It]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",or]]]),Hs=new Map([["bloom",["BloomForCausalLM",Gu]],["gpt2",["GPT2LMHeadModel",bu]],["gptj",["GPTJForCausalLM",Eu]],["gpt_bigcode",["GPTBigCodeForCausalLM",rf]],["gpt_neo",["GPTNeoForCausalLM",Mu]],["gpt_neox",["GPTNeoXForCausalLM",ku]],["codegen",["CodeGenForCausalLM",As]],["llama",["LlamaForCausalLM",$u]],["cohere",["CohereForCausalLM",Iu]],["gemma",["GemmaForCausalLM",Ou]],["gemma2",["Gemma2ForCausalLM",Du]],["openelm",["OpenELMForCausalLM",Ru]],["qwen2",["Qwen2ForCausalLM",Nu]],["phi",["PhiForCausalLM",Uu]],["phi3",["Phi3ForCausalLM",$a]],["mpt",["MptForCausalLM",Hu]],["opt",["OPTForCausalLM",Ku]],["mbart",["MBartForCausalLM",Mt]],["mistral",["MistralForCausalLM",Vs]],["starcoder2",["Starcoder2ForCausalLM",ll]],["falcon",["FalconForCausalLM",ud]],["trocr",["TrOCRForCausalLM",ad]],["stablelm",["StableLmForCausalLM",md]]]),kd=new Map([["bert",["BertForMaskedLM",We]],["roformer",["RoFormerForMaskedLM",A]],["electra",["ElectraForMaskedLM",Ne]],["esm",["EsmForMaskedLM",Bi]],["convbert",["ConvBertForMaskedLM",R]],["camembert",["CamembertForMaskedLM",Re]],["deberta",["DebertaForMaskedLM",Tt]],["deberta-v2",["DebertaV2ForMaskedLM",Ut]],["mpnet",["MPNetForMaskedLM",Lo]],["albert",["AlbertForMaskedLM",Zt]],["distilbert",["DistilBertForMaskedLM",$t]],["roberta",["RobertaForMaskedLM",Cn]],["xlm",["XLMWithLMHeadModel",On]],["xlm-roberta",["XLMRobertaForMaskedLM",At]],["mobilebert",["MobileBertForMaskedLM",pi]],["squeezebert",["SqueezeBertForMaskedLM",fo]]]),Sd=new Map([["bert",["BertForQuestionAnswering",Ge]],["roformer",["RoFormerForQuestionAnswering",se]],["electra",["ElectraForQuestionAnswering",Ve]],["convbert",["ConvBertForQuestionAnswering",ue]],["camembert",["CamembertForQuestionAnswering",tt]],["deberta",["DebertaForQuestionAnswering",Lt]],["deberta-v2",["DebertaV2ForQuestionAnswering",rr]],["mpnet",["MPNetForQuestionAnswering",No]],["albert",["AlbertForQuestionAnswering",mo]],["distilbert",["DistilBertForQuestionAnswering",mt]],["roberta",["RobertaForQuestionAnswering",Kn]],["xlm",["XLMForQuestionAnswering",yn]],["xlm-roberta",["XLMRobertaForQuestionAnswering",Xr]],["mobilebert",["MobileBertForQuestionAnswering",Ni]],["squeezebert",["SqueezeBertForQuestionAnswering",ki]]]),bl=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",ga]]]),_m=new Map([["llava",["LlavaForConditionalGeneration",wo]],["moondream1",["Moondream1ForConditionalGeneration",ar]],["florence2",["Florence2ForConditionalGeneration",_a]]]),yf=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",ga]]]),Ed=new Map([["vit",["ViTForImageClassification",Qu]],["fastvit",["FastViTForImageClassification",Zu]],["mobilevit",["MobileViTForImageClassification",nc]],["mobilevitv2",["MobileViTV2ForImageClassification",ic]],["beit",["BeitForImageClassification",cc]],["deit",["DeiTForImageClassification",bc]],["convnext",["ConvNextForImageClassification",Fc]],["convnextv2",["ConvNextV2ForImageClassification",Dc]],["dinov2",["Dinov2ForImageClassification",Rc]],["resnet",["ResNetForImageClassification",Mc]],["swin",["SwinForImageClassification",kc]],["segformer",["SegformerForImageClassification",fd]],["efficientnet",["EfficientNetForImageClassification",_d]],["mobilenet_v1",["MobileNetV1ForImageClassification",ff]],["mobilenet_v2",["MobileNetV2ForImageClassification",vd]],["mobilenet_v3",["MobileNetV3ForImageClassification",hf]],["mobilenet_v4",["MobileNetV4ForImageClassification",yl]]]),vf=new Map([["detr",["DetrForObjectDetection",pc]],["rt_detr",["RTDetrForObjectDetection",Ls]],["table-transformer",["TableTransformerForObjectDetection",wc]],["yolos",["YolosForObjectDetection",Nc]]]),Cd=new Map([["owlvit",["OwlViTForObjectDetection",sc]],["owlv2",["Owlv2ForObjectDetection",lc]]]),Pd=new Map([["detr",["DetrForSegmentation",fc]],["clipseg",["CLIPSegForImageSegmentation",yu]]]),$d=new Map([["segformer",["SegformerForSemanticSegmentation",hd]]]),Ad=new Map([["sam",["SamModel",Vc]]]),bf=new Map([["wav2vec2",["Wav2Vec2ForCTC",af]],["wav2vec2-bert",["Wav2Vec2BertForCTC",js]],["unispeech",["UniSpeechForCTC",Xc]],["unispeech-sat",["UniSpeechSatForCTC",el]],["wavlm",["WavLMForCTC",nl]],["hubert",["HubertForCTC",Jc]]]),Id=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Vi]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",Zc]],["unispeech",["UniSpeechForSequenceClassification",Qc]],["unispeech-sat",["UniSpeechSatForSequenceClassification",Yc]],["wavlm",["WavLMForSequenceClassification",td]],["hubert",["HubertForSequenceClassification",rl]],["audio-spectrogram-transformer",["ASTForAudioClassification",$s]]]),Fd=new Map([["wavlm",["WavLMForXVector",rd]]]),Od=new Map([["unispeech-sat",["UniSpeechSatForAudioFrameClassification",Bs]],["wavlm",["WavLMForAudioFrameClassification",nd]],["wav2vec2",["Wav2Vec2ForAudioFrameClassification",Wi]],["pyannote",["PyAnnoteForAudioFrameClassification",Gi]]]),zd=new Map([["vitmatte",["VitMatteForImageMatting",ec]]]),xf=new Map([["swin2sr",["Swin2SRForImageSuperResolution",ja]]]),Dd=new Map([["dpt",["DPTForDepthEstimation",Wa]],["depth_anything",["DepthAnythingForDepthEstimation",Cc]],["glpn",["GLPNForDepthEstimation",$c]]]),Ld=new Map([["clip",["CLIPVisionModelWithProjection",fu]],["siglip",["SiglipVisionModel",mu]]]),Rd=[[mf,b.EncoderOnly],[gf,b.EncoderDecoder],[_f,b.DecoderOnly],[Td,b.EncoderOnly],[wf,b.EncoderOnly],[vl,b.Seq2Seq],[Gs,b.Seq2Seq],[Hs,b.DecoderOnly],[kd,b.EncoderOnly],[Sd,b.EncoderOnly],[bl,b.Vision2Seq],[_m,b.ImageTextToText],[Ed,b.EncoderOnly],[Pd,b.EncoderOnly],[$d,b.EncoderOnly],[zd,b.EncoderOnly],[xf,b.EncoderOnly],[Dd,b.EncoderOnly],[vf,b.EncoderOnly],[Cd,b.EncoderOnly],[Ad,b.MaskGeneration],[bf,b.EncoderOnly],[Id,b.EncoderOnly],[xd,b.Seq2Seq],[Md,b.EncoderOnly],[Fd,b.EncoderOnly],[Od,b.EncoderOnly],[Ld,b.EncoderOnly]];for(const[V,G]of Rd)for(const[ne,Ee]of V.values())I.set(ne,G),z.set(Ee,ne),U.set(ne,Ee);const Mf=[["MusicgenForConditionalGeneration",ml,b.Musicgen],["CLIPTextModelWithProjection",hi,b.EncoderOnly],["SiglipTextModel",hu,b.EncoderOnly],["ClapTextModelWithProjection",dd,b.EncoderOnly],["ClapAudioModelWithProjection",pd,b.EncoderOnly]];for(const[V,G,ne]of Mf)I.set(V,ne),z.set(G,V),U.set(V,G);class Bd extends Rr{}He(Bd,"MODEL_CLASS_MAPPINGS",Rd.map(G=>G[0])),He(Bd,"BASE_IF_FAIL",!0);class Pn extends Rr{}He(Pn,"MODEL_CLASS_MAPPINGS",[Td]);class Nd extends Rr{}He(Nd,"MODEL_CLASS_MAPPINGS",[wf]);class jd extends Rr{}He(jd,"MODEL_CLASS_MAPPINGS",[vl]);class xl extends Rr{}He(xl,"MODEL_CLASS_MAPPINGS",[Gs]);class Ud extends Rr{}He(Ud,"MODEL_CLASS_MAPPINGS",[xd]);class Zo extends Rr{}He(Zo,"MODEL_CLASS_MAPPINGS",[Md]);class Vd extends Rr{}He(Vd,"MODEL_CLASS_MAPPINGS",[Hs]);class Wd extends Rr{}He(Wd,"MODEL_CLASS_MAPPINGS",[kd]);class Ml extends Rr{}He(Ml,"MODEL_CLASS_MAPPINGS",[Sd]);class Gd extends Rr{}He(Gd,"MODEL_CLASS_MAPPINGS",[bl]);class Hd extends Rr{}He(Hd,"MODEL_CLASS_MAPPINGS",[Ed]);class Tl extends Rr{}He(Tl,"MODEL_CLASS_MAPPINGS",[Pd]);class qd extends Rr{}He(qd,"MODEL_CLASS_MAPPINGS",[$d]);class Kd extends Rr{}He(Kd,"MODEL_CLASS_MAPPINGS",[vf]);class Xd extends Rr{}He(Xd,"MODEL_CLASS_MAPPINGS",[Cd]);class kl extends Rr{}He(kl,"MODEL_CLASS_MAPPINGS",[Ad]);class Qd extends Rr{}He(Qd,"MODEL_CLASS_MAPPINGS",[bf]);class Yd extends Rr{}He(Yd,"MODEL_CLASS_MAPPINGS",[Id]);class Sl extends Rr{}He(Sl,"MODEL_CLASS_MAPPINGS",[Fd]);class Zd extends Rr{}He(Zd,"MODEL_CLASS_MAPPINGS",[Od]);class Tf extends Rr{}He(Tf,"MODEL_CLASS_MAPPINGS",[yf]);class Jd extends Rr{}He(Jd,"MODEL_CLASS_MAPPINGS",[zd]);class ep extends Rr{}He(ep,"MODEL_CLASS_MAPPINGS",[xf]);class tp extends Rr{}He(tp,"MODEL_CLASS_MAPPINGS",[Dd]);class rp extends Rr{}He(rp,"MODEL_CLASS_MAPPINGS",[Ld]);class wm extends ge{constructor({logits:G,past_key_values:ne,encoder_outputs:Ee,decoder_attentions:Ze=null,cross_attentions:it=null}){super(),this.logits=G,this.past_key_values=ne,this.encoder_outputs=Ee,this.decoder_attentions=Ze,this.cross_attentions=it}}class ur extends ge{constructor({logits:G}){super(),this.logits=G}}class np extends ge{constructor({logits:G,embeddings:ne}){super(),this.logits=G,this.embeddings=ne}}class hn extends ge{constructor({logits:G}){super(),this.logits=G}}class bn extends ge{constructor({logits:G}){super(),this.logits=G}}class xn extends ge{constructor({start_logits:G,end_logits:ne}){super(),this.start_logits=G,this.end_logits=ne}}class to extends ge{constructor({logits:G}){super(),this.logits=G}}class kf extends ge{constructor({logits:G,past_key_values:ne}){super(),this.logits=G,this.past_key_values=ne}}class ip extends ge{constructor({alphas:G}){super(),this.alphas=G}}class Sf extends ge{constructor({waveform:G,spectrogram:ne}){super(),this.waveform=G,this.spectrogram=ne}}},"./src/models/whisper/common_whisper.js":(e,t,r)=>{r.r(t),r.d(t,{WHISPER_LANGUAGE_MAPPING:()=>a,WHISPER_TO_LANGUAGE_CODE_MAPPING:()=>l,whisper_language_to_code:()=>p});const o=[["en","english"],["zh","chinese"],["de","german"],["es","spanish"],["ru","russian"],["ko","korean"],["fr","french"],["ja","japanese"],["pt","portuguese"],["tr","turkish"],["pl","polish"],["ca","catalan"],["nl","dutch"],["ar","arabic"],["sv","swedish"],["it","italian"],["id","indonesian"],["hi","hindi"],["fi","finnish"],["vi","vietnamese"],["he","hebrew"],["uk","ukrainian"],["el","greek"],["ms","malay"],["cs","czech"],["ro","romanian"],["da","danish"],["hu","hungarian"],["ta","tamil"],["no","norwegian"],["th","thai"],["ur","urdu"],["hr","croatian"],["bg","bulgarian"],["lt","lithuanian"],["la","latin"],["mi","maori"],["ml","malayalam"],["cy","welsh"],["sk","slovak"],["te","telugu"],["fa","persian"],["lv","latvian"],["bn","bengali"],["sr","serbian"],["az","azerbaijani"],["sl","slovenian"],["kn","kannada"],["et","estonian"],["mk","macedonian"],["br","breton"],["eu","basque"],["is","icelandic"],["hy","armenian"],["ne","nepali"],["mn","mongolian"],["bs","bosnian"],["kk","kazakh"],["sq","albanian"],["sw","swahili"],["gl","galician"],["mr","marathi"],["pa","punjabi"],["si","sinhala"],["km","khmer"],["sn","shona"],["yo","yoruba"],["so","somali"],["af","afrikaans"],["oc","occitan"],["ka","georgian"],["be","belarusian"],["tg","tajik"],["sd","sindhi"],["gu","gujarati"],["am","amharic"],["yi","yiddish"],["lo","lao"],["uz","uzbek"],["fo","faroese"],["ht","haitian creole"],["ps","pashto"],["tk","turkmen"],["nn","nynorsk"],["mt","maltese"],["sa","sanskrit"],["lb","luxembourgish"],["my","myanmar"],["bo","tibetan"],["tl","tagalog"],["mg","malagasy"],["as","assamese"],["tt","tatar"],["haw","hawaiian"],["ln","lingala"],["ha","hausa"],["ba","bashkir"],["jw","javanese"],["su","sundanese"]],a=new Map(o),l=new Map([...o.map(([_,h])=>[h,_]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);function p(_){_=_.toLowerCase();let h=l.get(_);if(h===void 0)if(a.has(_))h=_;else{const M=_.length===2?a.keys():a.values();throw new Error(`Language "${_}" is not supported. Must be one of: ${JSON.stringify(M)}`)}return h}},"./src/models/whisper/generation_whisper.js":(e,t,r)=>{r.r(t),r.d(t,{WhisperGenerationConfig:()=>a});var o=r("./src/generation/configuration_utils.js");class a extends o.GenerationConfig{constructor(){super(...arguments);He(this,"return_timestamps",null);He(this,"return_token_timestamps",null);He(this,"num_frames",null);He(this,"alignment_heads",null);He(this,"task",null);He(this,"language",null);He(this,"no_timestamps_token_id",null);He(this,"prompt_ids",null);He(this,"is_multilingual",null);He(this,"lang_to_id",null);He(this,"task_to_id",null);He(this,"max_initial_timestamp_index",1)}}},"./src/ops/registry.js":(e,t,r)=>{r.r(t),r.d(t,{TensorOpRegistry:()=>p});var o=r("./src/backends/onnx.js"),a=r("./src/utils/tensor.js");const l=async(_,h,g)=>{const M=await(0,o.createInferenceSession)(new Uint8Array(_),h);return async y=>{const E=Object.fromEntries(Object.entries(y).map(([O,S])=>[O,S.ort_tensor])),T=await M.run(E);return Array.isArray(g)?g.map(O=>new a.Tensor(T[O])):new a.Tensor(T[g])}};class p{static get bilinear_interpolate_4d(){return this._bilinear_interpolate_4d||(this._bilinear_interpolate_4d=l([8,9,18,0,58,128,1,10,40,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,17,10,4,109,111,100,101,34,6,108,105,110,101,97,114,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,20],this.session_options,"y")),this._bilinear_interpolate_4d}static get bicubic_interpolate_4d(){return this._bicubic_interpolate_4d||(this._bicubic_interpolate_4d=l([8,9,18,0,58,127,10,39,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,16,10,4,109,111,100,101,34,5,99,117,98,105,99,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,20],this.session_options,"y")),this._bicubic_interpolate_4d}static get matmul(){return this._matmul||(this._matmul=l([8,9,18,0,58,55,10,17,10,1,97,10,1,98,18,1,99,34,6,77,97,116,77,117,108,18,1,114,90,9,10,1,97,18,4,10,2,8,1,90,9,10,1,98,18,4,10,2,8,1,98,9,10,1,99,18,4,10,2,8,1,66,2,16,20],this.session_options,"c")),this._matmul}static get stft(){return this._stft||(this._stft=l([8,7,18,0,58,148,1,10,38,10,1,115,10,1,106,10,1,119,10,1,108,18,1,111,34,4,83,84,70,84,42,15,10,8,111,110,101,115,105,100,101,100,24,1,160,1,2,18,1,115,90,26,10,1,115,18,21,10,19,8,1,18,15,10,3,18,1,98,10,3,18,1,115,10,3,18,1,99,90,11,10,1,106,18,6,10,4,8,7,18,0,90,16,10,1,119,18,11,10,9,8,1,18,5,10,3,18,1,119,90,11,10,1,108,18,6,10,4,8,7,18,0,98,31,10,1,111,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,102,10,3,18,1,100,10,3,18,1,99,66,2,16,17],this.session_options,"o")),this._stft}static get rfft(){return this._rfft||(this._rfft=l([8,9,18,0,58,97,10,33,10,1,120,10,0,10,1,97,18,1,121,34,3,68,70,84,42,15,10,8,111,110,101,115,105,100,101,100,24,1,160,1,2,18,1,100,90,21,10,1,120,18,16,10,14,8,1,18,10,10,3,18,1,115,10,3,18,1,99,90,11,10,1,97,18,6,10,4,8,7,18,0,98,21,10,1,121,18,16,10,14,8,1,18,10,10,3,18,1,115,10,3,18,1,99,66,2,16,20],this.session_options,"y")),this._rfft}static get top_k(){return this._top_k||(this._top_k=l([8,10,18,0,58,73,10,18,10,1,120,10,1,107,18,1,118,18,1,105,34,4,84,111,112,75,18,1,116,90,9,10,1,120,18,4,10,2,8,1,90,15,10,1,107,18,10,10,8,8,7,18,4,10,2,8,1,98,9,10,1,118,18,4,10,2,8,1,98,9,10,1,105,18,4,10,2,8,7,66,2,16,21],this.session_options,["v","i"])),this._top_k}}He(p,"session_options",{})},"./src/pipelines.js":(e,t,r)=>{r.r(t),r.d(t,{AudioClassificationPipeline:()=>Y,AutomaticSpeechRecognitionPipeline:()=>L,DepthEstimationPipeline:()=>Le,DocumentQuestionAnsweringPipeline:()=>Q,FeatureExtractionPipeline:()=>ce,FillMaskPipeline:()=>I,ImageClassificationPipeline:()=>Xe,ImageFeatureExtractionPipeline:()=>xe,ImageSegmentationPipeline:()=>me,ImageToImagePipeline:()=>Ke,ImageToTextPipeline:()=>Se,ObjectDetectionPipeline:()=>ie,Pipeline:()=>S,QuestionAnsweringPipeline:()=>b,SummarizationPipeline:()=>z,Text2TextGenerationPipeline:()=>U,TextClassificationPipeline:()=>C,TextGenerationPipeline:()=>N,TextToAudioPipeline:()=>ge,TokenClassificationPipeline:()=>w,TranslationPipeline:()=>B,ZeroShotAudioClassificationPipeline:()=>_e,ZeroShotClassificationPipeline:()=>ae,ZeroShotImageClassificationPipeline:()=>X,ZeroShotObjectDetectionPipeline:()=>Me,pipeline:()=>st});var o=r("./src/tokenizers.js"),a=r("./src/models.js"),l=r("./src/processors.js"),p=r("./src/utils/generic.js"),_=r("./src/utils/core.js"),h=r("./src/utils/maths.js"),g=r("./src/utils/audio.js"),M=r("./src/utils/tensor.js"),y=r("./src/utils/image.js");async function E(Ge){return Array.isArray(Ge)||(Ge=[Ge]),await Promise.all(Ge.map(Te=>y.RawImage.read(Te)))}async function T(Ge,Te){return Array.isArray(Ge)||(Ge=[Ge]),await Promise.all(Ge.map(je=>typeof je=="string"||je instanceof URL?(0,g.read_audio)(je,Te):je instanceof Float64Array?new Float32Array(je):je))}function O(Ge,Te){Te&&(Ge=Ge.map($e=>$e|0));const[je,Ye,et,A]=Ge;return{xmin:je,ymin:Ye,xmax:et,ymax:A}}class S extends p.Callable{constructor({task:Te,model:je,tokenizer:Ye=null,processor:et=null}){super(),this.task=Te,this.model=je,this.tokenizer=Ye,this.processor=et}async dispose(){await this.model.dispose()}}class C extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=1}={}){const Ye=this.tokenizer(Te,{padding:!0,truncation:!0}),et=await this.model(Ye),A=this.model.config.problem_type==="multi_label_classification"?se=>se.sigmoid():se=>new M.Tensor("float32",(0,h.softmax)(se.data),se.dims),$e=this.model.config.id2label,Pe=[];for(const se of et.logits){const re=A(se),ye=await(0,M.topk)(re,je),R=ye[0].tolist(),D=ye[1].tolist().map((ue,le)=>({label:$e?$e[ue]:`LABEL_${ue}`,score:R[le]}));je===1?Pe.push(...D):Pe.push(D)}return Array.isArray(Te)||je===1?Pe:Pe[0]}}class w extends S{constructor(Te){super(Te)}async _call(Te,{ignore_labels:je=["O"]}={}){const Ye=Array.isArray(Te),et=this.tokenizer(Ye?Te:[Te],{padding:!0,truncation:!0}),$e=(await this.model(et)).logits,Pe=this.model.config.id2label,se=[];for(let re=0;re<$e.dims[0];++re){const ye=et.input_ids[re],R=$e[re],ee=[];for(let D=0;DJe==this.tokenizer.sep_token_id);se[R].map((Je,Ve)=>Je==1&&(Ve===0||Ve>D&&re.findIndex(Z=>Z==ee[Ve])===-1));const ue=A[R].tolist(),le=$e[R].tolist();for(let Je=1;JeVe==ee[Je])!==-1)&&(ue[Je]=-1/0,le[Je]=-1/0);const ke=(0,h.softmax)(ue).map((Je,Ve)=>[Je,Ve]),Ne=(0,h.softmax)(le).map((Je,Ve)=>[Je,Ve]);ke[0][0]=0,Ne[0][0]=0;const dt=(0,_.product)(ke,Ne).filter(Je=>Je[0][1]<=Je[1][1]).map(Je=>[Je[0][1],Je[1][1],Je[0][0]*Je[1][0]]).sort((Je,Ve)=>Ve[2]-Je[2]);for(let Je=0;Jeue==this.tokenizer.mask_token_id);if(re===-1)throw Error(`Mask token (${this.tokenizer.mask_token}) not found in text.`);const ye=et[Pe][re],R=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(ye.data),ye.dims),je),ee=R[0].tolist(),D=R[1].tolist();A.push(D.map((ue,le)=>{const ke=se.slice();return ke[re]=ue,{score:ee[le],token:Number(ue),token_str:this.tokenizer.model.vocab[ue],sequence:this.tokenizer.decode(ke,{skip_special_tokens:!0})}}))}return Array.isArray(Te)?A:A[0]}}class U extends S{constructor(je){super(je);He(this,"_key","generated_text")}async _call(je,Ye={}){Array.isArray(je)||(je=[je]),this.model.config.prefix&&(je=je.map(re=>this.model.config.prefix+re));const et=this.model.config.task_specific_params;et&&et[this.task]&&et[this.task].prefix&&(je=je.map(re=>et[this.task].prefix+re));const A=this.tokenizer,$e={padding:!0,truncation:!0};let Pe;this instanceof B&&"_build_translation_inputs"in A?Pe=A._build_translation_inputs(je,$e,Ye):Pe=A(je,$e);const se=await this.model.generate({...Pe,...Ye});return A.batch_decode(se,{skip_special_tokens:!0}).map(re=>({[this._key]:re}))}}class z extends U{constructor(je){super(je);He(this,"_key","summary_text")}}class B extends U{constructor(je){super(je);He(this,"_key","translation_text")}}function j(Ge){return Array.isArray(Ge)&&Ge.every(Te=>"role"in Te&&"content"in Te)}class N extends S{constructor(Te){super(Te)}async _call(Te,je={}){let Ye=!1,et=!1,A;if(typeof Te=="string")A=Te=[Te];else if(Array.isArray(Te)&&Te.every(D=>typeof D=="string"))Ye=!0,A=Te;else{if(j(Te))Te=[Te];else if(Array.isArray(Te)&&Te.every(j))Ye=!0;else throw new Error("Input must be a string, an array of strings, a Chat, or an array of Chats");et=!0,A=Te.map(D=>this.tokenizer.apply_chat_template(D,{tokenize:!1,add_generation_prompt:!0}))}const $e=je.add_special_tokens??!1,Pe=et?!1:je.return_full_text??!0;this.tokenizer.padding_side="left";const se=this.tokenizer(A,{add_special_tokens:$e,padding:!0,truncation:!0}),re=await this.model.generate({...se,...je}),ye=this.tokenizer.batch_decode(re,{skip_special_tokens:!0});let R;!Pe&&se.input_ids.dims.at(-1)>0&&(R=this.tokenizer.batch_decode(se.input_ids,{skip_special_tokens:!0}).map(D=>D.length));const ee=Array.from({length:Te.length},D=>[]);for(let D=0;D[je.toLowerCase(),Ye])),this.entailment_id=this.label2id.entailment,this.entailment_id===void 0&&(console.warn("Could not find 'entailment' in label2id mapping. Using 2 as entailment_id."),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,this.contradiction_id===void 0&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(Te,je,{hypothesis_template:Ye="This example is {}.",multi_label:et=!1}={}){const A=Array.isArray(Te);A||(Te=[Te]),Array.isArray(je)||(je=[je]);const $e=je.map(re=>Ye.replace("{}",re)),Pe=et||je.length===1,se=[];for(const re of Te){const ye=[];for(const D of $e){const ue=this.tokenizer(re,{text_pair:D,padding:!0,truncation:!0}),le=await this.model(ue);Pe?ye.push([le.logits.data[this.contradiction_id],le.logits.data[this.entailment_id]]):ye.push(le.logits.data[this.entailment_id])}const ee=(Pe?ye.map(D=>(0,h.softmax)(D)[1]):(0,h.softmax)(ye)).map((D,ue)=>[D,ue]).sort((D,ue)=>ue[0]-D[0]);se.push({sequence:re,labels:ee.map(D=>je[D[1]]),scores:ee.map(D=>D[0])})}return A?se:se[0]}}class ce extends S{constructor(Te){super(Te)}async _call(Te,{pooling:je="none",normalize:Ye=!1,quantize:et=!1,precision:A="binary"}={}){const $e=this.tokenizer(Te,{padding:!0,truncation:!0}),Pe=await this.model($e);let se=Pe.last_hidden_state??Pe.logits??Pe.token_embeddings;if(je!=="none")if(je==="mean")se=(0,M.mean_pooling)(se,$e.attention_mask);else if(je==="cls")se=se.slice(null,0);else throw Error(`Pooling method '${je}' not supported.`);return Ye&&(se=se.normalize(2,-1)),et&&(se=(0,M.quantize_embeddings)(se,A)),se}}class xe extends S{constructor(Te){super(Te)}async _call(Te,{pool:je=null}={}){const Ye=await E(Te),{pixel_values:et}=await this.processor(Ye),A=await this.model({pixel_values:et});let $e;if(je){if(!("pooler_output"in A))throw Error("No pooled output was returned. Make sure the model has a 'pooler' layer when using the 'pool' option.");$e=A.pooler_output}else $e=A.last_hidden_state??A.logits??A.image_embeds;return $e}}class Y extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=5}={}){const Ye=this.processor.feature_extractor.config.sampling_rate,et=await T(Te,Ye),A=this.model.config.id2label,$e=[];for(const Pe of et){const se=await this.processor(Pe),ye=(await this.model(se)).logits[0],R=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(ye.data),ye.dims),je),ee=R[0].tolist(),ue=R[1].tolist().map((le,ke)=>({label:A?A[le]:`LABEL_${le}`,score:ee[ke]}));$e.push(ue)}return Array.isArray(Te)?$e:$e[0]}}class _e extends S{constructor(Te){super(Te)}async _call(Te,je,{hypothesis_template:Ye="This is a sound of {}."}={}){const et=!Array.isArray(Te);et&&(Te=[Te]);const A=je.map(ye=>Ye.replace("{}",ye)),$e=this.tokenizer(A,{padding:!0,truncation:!0}),Pe=this.processor.feature_extractor.config.sampling_rate,se=await T(Te,Pe),re=[];for(const ye of se){const R=await this.processor(ye),ee=await this.model({...$e,...R}),D=(0,h.softmax)(ee.logits_per_audio.data);re.push([...D].map((ue,le)=>({score:ue,label:je[le]})))}return et?re[0]:re}}class L extends S{constructor(Te){super(Te)}async _call(Te,je={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(Te,je);case"wav2vec2":case"wav2vec2-bert":case"unispeech":case"unispeech-sat":case"hubert":return this._call_wav2vec2(Te,je);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(Te,je){je.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),je.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');const Ye=!Array.isArray(Te);Ye&&(Te=[Te]);const et=this.processor.feature_extractor.config.sampling_rate,A=await T(Te,et),$e=[];for(const Pe of A){const se=await this.processor(Pe),ye=(await this.model(se)).logits[0],R=[];for(const D of ye)R.push((0,h.max)(D.data)[1]);const ee=this.tokenizer.decode(R);$e.push({text:ee})}return Ye?$e[0]:$e}async _call_whisper(Te,je){const Ye=je.return_timestamps??!1,et=je.chunk_length_s??0,A=je.force_full_sequences??!1;let $e=je.stride_length_s??null;const Pe={...je};Ye==="word"&&(Pe.return_token_timestamps=!0,Pe.return_timestamps=!1);const se=!Array.isArray(Te);se&&(Te=[Te]);const re=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,ye=this.processor.feature_extractor.config.hop_length,R=this.processor.feature_extractor.config.sampling_rate,ee=await T(Te,R),D=[];for(const ue of ee){let le=[];if(et>0){if($e===null)$e=et/6;else if(et<=$e)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const dt=R*et,Je=R*$e,Ve=dt-2*Je;let Z=0;for(;;){const ve=Z+dt,Re=ue.subarray(Z,ve),qe=await this.processor(Re),Qe=Z===0,tt=ve>=ue.length;if(le.push({stride:[Re.length,Qe?0:Je,tt?0:Je],input_features:qe.input_features,is_last:tt}),tt)break;Z+=Ve}}else le=[{stride:[ue.length,0,0],input_features:(await this.processor(ue)).input_features,is_last:!0}];for(const dt of le){Pe.num_frames=Math.floor(dt.stride[0]/ye);const Je=await this.model.generate({inputs:dt.input_features,...Pe});Ye==="word"?(dt.tokens=Je.sequences.tolist()[0],dt.token_timestamps=Je.token_timestamps.tolist()[0].map(Ve=>(0,h.round)(Ve,2))):dt.tokens=Je[0].tolist(),dt.stride=dt.stride.map(Ve=>Ve/R)}const[ke,Ne]=this.tokenizer._decode_asr(le,{time_precision:re,return_timestamps:Ye,force_full_sequences:A});D.push({text:ke,...Ne})}return se?D[0]:D}}class Se extends S{constructor(Te){super(Te)}async _call(Te,je={}){const Ye=Array.isArray(Te),et=await E(Te),{pixel_values:A}=await this.processor(et),$e=[];for(const Pe of A){Pe.dims=[1,...Pe.dims];const se=await this.model.generate({inputs:Pe,...je}),re=this.tokenizer.batch_decode(se,{skip_special_tokens:!0}).map(ye=>({generated_text:ye.trim()}));$e.push(re)}return Ye?$e:$e[0]}}class Xe extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=5}={}){const Ye=await E(Te),{pixel_values:et}=await this.processor(Ye),A=await this.model({pixel_values:et}),$e=this.model.config.id2label,Pe=[];for(const se of A.logits){const re=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(se.data),se.dims),je),ye=re[0].tolist(),ee=re[1].tolist().map((D,ue)=>({label:$e?$e[D]:`LABEL_${D}`,score:ye[ue]}));Pe.push(ee)}return Array.isArray(Te)?Pe:Pe[0]}}class me extends S{constructor(Te){super(Te),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(Te,{threshold:je=.5,mask_threshold:Ye=.5,overlap_mask_area_threshold:et=.8,label_ids_to_fuse:A=null,target_sizes:$e=null,subtask:Pe=null}={}){if(Array.isArray(Te)&&Te.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");const re=await E(Te),ye=re.map(Ne=>[Ne.height,Ne.width]),{pixel_values:R,pixel_mask:ee}=await this.processor(re),D=await this.model({pixel_values:R,pixel_mask:ee});let ue=null;if(Pe!==null)ue=this.subtasks_mapping[Pe];else for(let[Ne,dt]of Object.entries(this.subtasks_mapping))if(dt in this.processor.feature_extractor){ue=this.processor.feature_extractor[dt].bind(this.processor.feature_extractor),Pe=Ne;break}const le=this.model.config.id2label,ke=[];if(Pe==="panoptic"||Pe==="instance"){const Ne=ue(D,je,Ye,et,A,$e??ye)[0],dt=Ne.segmentation;for(const Je of Ne.segments_info){const Ve=new Uint8ClampedArray(dt.data.length);for(let ve=0;veYe.replace("{}",ee)),Pe=this.tokenizer($e,{padding:this.model.config.model_type==="siglip"?"max_length":!0,truncation:!0}),{pixel_values:se}=await this.processor(A),re=await this.model({...Pe,pixel_values:se}),ye=this.model.config.model_type==="siglip"?ee=>ee.sigmoid().data:ee=>(0,h.softmax)(ee.data),R=[];for(const ee of re.logits_per_image){const ue=[...ye(ee)].map((le,ke)=>({score:le,label:je[ke]}));ue.sort((le,ke)=>ke.score-le.score),R.push(ue)}return et?R:R[0]}}class ie extends S{constructor(Te){super(Te)}async _call(Te,{threshold:je=.9,percentage:Ye=!1}={}){const et=Array.isArray(Te);if(et&&Te.length!==1)throw Error("Object detection pipeline currently only supports a batch size of 1.");const A=await E(Te),$e=Ye?null:A.map(D=>[D.height,D.width]),{pixel_values:Pe,pixel_mask:se}=await this.processor(A),re=await this.model({pixel_values:Pe,pixel_mask:se}),ye=this.processor.feature_extractor.post_process_object_detection(re,je,$e),R=this.model.config.id2label,ee=ye.map(D=>D.boxes.map((ue,le)=>({score:D.scores[le],label:R[D.classes[le]],box:O(ue,!Ye)})));return et?ee:ee[0]}}class Me extends S{constructor(Te){super(Te)}async _call(Te,je,{threshold:Ye=.1,top_k:et=null,percentage:A=!1}={}){const $e=Array.isArray(Te),Pe=await E(Te),se=this.tokenizer(je,{padding:!0,truncation:!0}),re=await this.processor(Pe),ye=[];for(let R=0;R({score:ke.scores[Je],label:je[ke.classes[Je]],box:O(dt,!A)})).sort((dt,Je)=>Je.score-dt.score);et!==null&&(Ne=Ne.slice(0,et)),ye.push(Ne)}return $e?ye:ye[0]}}class Q extends S{constructor(Te){super(Te)}async _call(Te,je,Ye={}){throw new Error("This pipeline is not yet supported in Transformers.js v3.")}}class ge extends S{constructor(je){super(je);He(this,"DEFAULT_VOCODER_ID","Xenova/speecht5_hifigan");this.vocoder=je.vocoder??null}async _call(je,{speaker_embeddings:Ye=null}={}){return this.processor?this._call_text_to_spectrogram(je,{speaker_embeddings:Ye}):this._call_text_to_waveform(je)}async _call_text_to_waveform(je){const Ye=this.tokenizer(je,{padding:!0,truncation:!0}),{waveform:et}=await this.model(Ye),A=this.model.config.sampling_rate;return{audio:et.data,sampling_rate:A}}async _call_text_to_spectrogram(je,{speaker_embeddings:Ye}){if(this.vocoder||(console.log("No vocoder specified, using default HifiGan vocoder."),this.vocoder=await a.AutoModel.from_pretrained(this.DEFAULT_VOCODER_ID,{dtype:"fp32"})),(typeof Ye=="string"||Ye instanceof URL)&&(Ye=new Float32Array(await(await fetch(Ye)).arrayBuffer())),Ye instanceof Float32Array)Ye=new M.Tensor("float32",Ye,[1,Ye.length]);else if(!(Ye instanceof M.Tensor))throw new Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");const{input_ids:et}=this.tokenizer(je,{padding:!0,truncation:!0}),{waveform:A}=await this.model.generate_speech(et,Ye,{vocoder:this.vocoder}),$e=this.processor.feature_extractor.config.sampling_rate;return{audio:A.data,sampling_rate:$e}}}class Ke extends S{constructor(Te){super(Te)}async _call(Te){const je=await E(Te),Ye=await this.processor(je),et=await this.model(Ye),A=[];for(const $e of et.reconstruction){const Pe=$e.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");A.push(y.RawImage.fromTensor(Pe))}return A.length>1?A:A[0]}}class Le extends S{constructor(Te){super(Te)}async _call(Te){const je=await E(Te),Ye=await this.processor(je),{predicted_depth:et}=await this.model(Ye),A=[];for(let $e=0;$e1?A:A[0]}}const Be=Object.freeze({"text-classification":{tokenizer:o.AutoTokenizer,pipeline:C,model:a.AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:o.AutoTokenizer,pipeline:w,model:a.AutoModelForTokenClassification,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:o.AutoTokenizer,pipeline:b,model:a.AutoModelForQuestionAnswering,default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:o.AutoTokenizer,pipeline:I,model:a.AutoModelForMaskedLM,default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:o.AutoTokenizer,pipeline:z,model:a.AutoModelForSeq2SeqLM,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:o.AutoTokenizer,pipeline:B,model:a.AutoModelForSeq2SeqLM,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:o.AutoTokenizer,pipeline:U,model:a.AutoModelForSeq2SeqLM,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:o.AutoTokenizer,pipeline:N,model:a.AutoModelForCausalLM,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:o.AutoTokenizer,pipeline:ae,model:a.AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:Y,model:a.AutoModelForAudioClassification,processor:l.AutoProcessor,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:o.AutoTokenizer,pipeline:_e,model:a.AutoModel,processor:l.AutoProcessor,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:o.AutoTokenizer,pipeline:L,model:[a.AutoModelForSpeechSeq2Seq,a.AutoModelForCTC],processor:l.AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:o.AutoTokenizer,pipeline:ge,model:[a.AutoModelForTextToWaveform,a.AutoModelForTextToSpectrogram],processor:[l.AutoProcessor,null],default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:o.AutoTokenizer,pipeline:Se,model:a.AutoModelForVision2Seq,processor:l.AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:Xe,model:a.AutoModelForImageClassification,processor:l.AutoProcessor,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:me,model:[a.AutoModelForImageSegmentation,a.AutoModelForSemanticSegmentation],processor:l.AutoProcessor,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:o.AutoTokenizer,pipeline:X,model:a.AutoModel,processor:l.AutoProcessor,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:ie,model:a.AutoModelForObjectDetection,processor:l.AutoProcessor,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"zero-shot-object-detection":{tokenizer:o.AutoTokenizer,pipeline:Me,model:a.AutoModelForZeroShotObjectDetection,processor:l.AutoProcessor,default:{model:"Xenova/owlvit-base-patch32"},type:"multimodal"},"document-question-answering":{tokenizer:o.AutoTokenizer,pipeline:Q,model:a.AutoModelForDocumentQuestionAnswering,processor:l.AutoProcessor,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"image-to-image":{pipeline:Ke,model:a.AutoModelForImageToImage,processor:l.AutoProcessor,default:{model:"Xenova/swin2SR-classical-sr-x2-64"},type:"image"},"depth-estimation":{pipeline:Le,model:a.AutoModelForDepthEstimation,processor:l.AutoProcessor,default:{model:"Xenova/dpt-large"},type:"image"},"feature-extraction":{tokenizer:o.AutoTokenizer,pipeline:ce,model:a.AutoModel,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"},"image-feature-extraction":{processor:l.AutoProcessor,pipeline:xe,model:[a.AutoModelForImageFeatureExtraction,a.AutoModel],default:{model:"Xenova/vit-base-patch16-224-in21k"},type:"image"}}),We=Object.freeze({"sentiment-analysis":"text-classification",ner:"token-classification",asr:"automatic-speech-recognition","text-to-speech":"text-to-audio",embeddings:"feature-extraction"});async function st(Ge,Te=null,{progress_callback:je=null,config:Ye=null,cache_dir:et=null,local_files_only:A=!1,revision:$e="main",device:Pe=null,dtype:se=null,model_file_name:re=null,session_options:ye={}}={}){Ge=We[Ge]??Ge;const R=Be[Ge.split("_",1)[0]];if(!R)throw Error(`Unsupported pipeline: ${Ge}. Must be one of [${Object.keys(Be)}]`);Te||(Te=R.default.model,console.log(`No model specified. Using default model: "${Te}".`));const ee={progress_callback:je,config:Ye,cache_dir:et,local_files_only:A,revision:$e,device:Pe,dtype:se,model_file_name:re,session_options:ye},D=new Map([["tokenizer",R.tokenizer],["model",R.model],["processor",R.processor]]),ue=await pt(D,Te,ee);ue.task=Ge,(0,_.dispatchCallback)(je,{status:"ready",task:Ge,model:Te});const le=R.pipeline;return new le(ue)}async function pt(Ge,Te,je){const Ye=Object.create(null),et=[];for(let[A,$e]of Ge.entries()){if(!$e)continue;let Pe;Array.isArray($e)?Pe=new Promise(async(se,re)=>{var R,ee;let ye;for(let D of $e){if(D===null){se(null);return}try{se(await D.from_pretrained(Te,je));return}catch(ue){if((R=ue.message)!=null&&R.includes("Unsupported model type"))ye=ue;else if((ee=ue.message)!=null&&ee.includes("Could not locate file"))ye=ue;else{re(ue);return}}}re(ye)}):Pe=$e.from_pretrained(Te,je),Ye[A]=Pe,et.push(Pe)}await Promise.all(et);for(let[A,$e]of Object.entries(Ye))Ye[A]=await $e;return Ye}},"./src/processors.js":(e,t,r)=>{r.r(t),r.d(t,{ASTFeatureExtractor:()=>$e,AutoProcessor:()=>Je,BeitFeatureExtractor:()=>Le,BitImageProcessor:()=>I,CLIPFeatureExtractor:()=>z,CLIPImageProcessor:()=>B,ChineseCLIPFeatureExtractor:()=>j,ClapFeatureExtractor:()=>Pe,ConvNextFeatureExtractor:()=>ae,ConvNextImageProcessor:()=>ce,DPTFeatureExtractor:()=>w,DPTImageProcessor:()=>b,DeiTFeatureExtractor:()=>Ke,DetrFeatureExtractor:()=>st,DonutFeatureExtractor:()=>Be,EfficientNetImageProcessor:()=>_e,FeatureExtractor:()=>O,Florence2Processor:()=>dt,GLPNFeatureExtractor:()=>U,ImageFeatureExtractor:()=>S,MobileNetV1FeatureExtractor:()=>L,MobileNetV2FeatureExtractor:()=>Se,MobileNetV3FeatureExtractor:()=>Xe,MobileNetV4FeatureExtractor:()=>me,MobileViTFeatureExtractor:()=>X,MobileViTImageProcessor:()=>ie,NougatImageProcessor:()=>We,OwlViTFeatureExtractor:()=>Me,OwlViTProcessor:()=>Ne,Owlv2ImageProcessor:()=>Q,Processor:()=>R,PyAnnoteFeatureExtractor:()=>se,PyAnnoteProcessor:()=>le,RTDetrImageProcessor:()=>ge,SamImageProcessor:()=>Ge,SamProcessor:()=>ee,SeamlessM4TFeatureExtractor:()=>A,SegformerFeatureExtractor:()=>C,SiglipImageProcessor:()=>N,SpeechT5FeatureExtractor:()=>ye,SpeechT5Processor:()=>ke,Swin2SRImageProcessor:()=>Te,ViTFeatureExtractor:()=>xe,ViTImageProcessor:()=>Y,VitMatteImageProcessor:()=>je,Wav2Vec2FeatureExtractor:()=>et,Wav2Vec2ProcessorWithLM:()=>ue,WeSpeakerFeatureExtractor:()=>re,WhisperFeatureExtractor:()=>Ye,WhisperProcessor:()=>D,YolosFeatureExtractor:()=>pt});var o=r("./src/utils/generic.js"),a=r("./src/utils/core.js"),l=r("./src/utils/hub.js"),p=r("./src/utils/maths.js"),_=r("./src/utils/tensor.js");r("./src/utils/image.js");var h=r("./src/utils/audio.js");function g([Ve,Z,ve,Re]){return[Ve-ve/2,Z-Re/2,Ve+ve/2,Z+Re/2]}function M(Ve,Z=.5,ve=null,Re=!1){const qe=Ve.logits,Qe=Ve.pred_boxes,[tt,ft,ht]=qe.dims;if(ve!==null&&ve.length!==tt)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let Tt=[];for(let bt=0;btZ&&Yt.push(Ht)}else{let Ht=(0,p.max)(Xt.data)[1];if(Ht===ht-1||(rr=(0,p.softmax)(Xt.data),rr[Ht]Yr*Et[($r+1)%2])),Lt.boxes.push(Pr),Lt.classes.push(Ht),Lt.scores.push(rr[Ht])}}Tt.push(Lt)}return Tt}function y(Ve,Z){var ve;if(!(Ve instanceof Float32Array||Ve instanceof Float64Array))throw new Error(`${Z} expects input to be a Float32Array or a Float64Array, but got ${((ve=Ve==null?void 0:Ve.constructor)==null?void 0:ve.name)??typeof Ve} instead. If using the feature extractor directly, remember to use \`read_audio(url, sampling_rate)\` to obtain the raw audio data of the file/url.`)}function E(Ve,Z,ve=0,Re=null){const qe=Ve/Z;let Qe=(0,p.bankers_round)(qe)*Z;return Re!==null&&Qe>Re&&(Qe=Math.floor(qe)*Z),QeQe?Tt=Math.floor(Qe*ht/qe):Qe>qe&&(ht=Math.floor(qe*Tt/Qe)),await Z.resize(Tt,ht,{resample:Re}))}async crop_margin(Z,ve=200){const Re=Z.clone().grayscale(),qe=(0,p.min)(Re.data)[0],tt=(0,p.max)(Re.data)[0]-qe;if(tt===0)return Z;const ft=ve/255;let ht=Re.width,Tt=Re.height,bt=0,Et=0;const Lt=Re.data;for(let at=0;atthis.preprocess(Qe)));return{pixel_values:(0,_.stack)(Re.map(Qe=>Qe.pixel_values),0),original_sizes:Re.map(Qe=>Qe.original_size),reshaped_input_sizes:Re.map(Qe=>Qe.reshaped_input_size)}}}class C extends S{post_process_semantic_segmentation(Z,ve=null){const Re=Z.logits,qe=Re.dims[0];if(ve!==null&&ve.length!==qe)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const Qe=[];for(let tt=0;ttLt[Ht]&&(Lt[Ht]=rr[Ht],at[Ht]=Yt)}const Ot=new Array(ht.dims[0]),Ut=Et.data;for(let Yt=0;YtYt!==void 0);Qe.push({segmentation:Et,labels:Xt})}return Qe}}class w extends S{}class b extends w{}class I extends S{}class U extends S{}class z extends S{}class B extends z{}class j extends S{}class N extends S{}class ae extends S{constructor(Z){super(Z),this.crop_pct=this.config.crop_pct??224/256}async resize(Z){var Re;const ve=(Re=this.size)==null?void 0:Re.shortest_edge;if(ve===void 0)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(ve<384){const qe=Math.floor(ve/this.crop_pct),[Qe,tt]=this.get_resize_output_image_size(Z,{shortest_edge:qe});Z=await Z.resize(Qe,tt,{resample:this.resample}),Z=await Z.center_crop(ve,ve)}else Z=await Z.resize(ve,ve,{resample:this.resample});return Z}}class ce extends ae{}class xe extends S{}class Y extends S{}class _e extends S{constructor(Z){super(Z),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(ve=>ve*ve))}}class L extends S{}class Se extends S{}class Xe extends S{}class me extends S{}class X extends S{}class ie extends X{}class Me extends S{post_process_object_detection(...Z){return M(...Z)}}class Q extends Me{}class ge extends S{post_process_object_detection(...Z){return M(...Z)}}class Ke extends S{}class Le extends S{}class Be extends S{pad_image(Z,ve,Re,qe={}){const[Qe,tt,ft]=ve;let ht=this.image_mean;Array.isArray(this.image_mean)||(ht=new Array(ft).fill(ht));let Tt=this.image_std;Array.isArray(Tt)||(Tt=new Array(ft).fill(ht));const bt=ht.map((Et,Lt)=>-Et/Tt[Lt]);return super.pad_image(Z,ve,Re,{center:!0,constant_values:bt,...qe})}}class We extends Be{}class st extends S{async _call(Z){const ve=await super._call(Z),Re=[ve.pixel_values.dims[0],64,64],qe=new _.Tensor("int64",new BigInt64Array(Re.reduce((Qe,tt)=>Qe*tt)).fill(1n),Re);return{...ve,pixel_mask:qe}}post_process_object_detection(...Z){return M(...Z)}remove_low_and_no_objects(Z,ve,Re,qe){let Qe=[],tt=[],ft=[];for(let ht=0;htRe&&(Qe.push(bt),tt.push(at),ft.push(Et))}return[Qe,tt,ft]}check_segment_validity(Z,ve,Re,qe=.5,Qe=.8){let tt=[],ft=0,ht=0;const Tt=ve[Re].data;for(let Et=0;Et=qe&&++ht;let bt=ft>0&&ht>0;return bt&&(bt=ft/ht>Qe),[bt,tt]}compute_segments(Z,ve,Re,qe,Qe,tt=null,ft=null){let[ht,Tt]=ft??Z[0].dims,bt=new _.Tensor("int32",new Int32Array(ht*Tt),[ht,Tt]),Et=[];if(ft!==null)for(let Xt=0;Xtat[Ht]&&(Lt[Ht]=Xt,at[Ht]=rr[Ht])}let Ot=0;const Ut=bt.data;for(let Xt=0;Xtqe!==ve.dims[Qe]))throw Error(`The first ${Re.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new _.Tensor("int64",Z.flat(1/0).map(BigInt),Re)}async _call(Z,{input_points:ve=null,input_labels:Re=null,input_boxes:qe=null}={}){const Qe=await super._call(Z);if(ve&&(Qe.input_points=this.reshape_input_points(ve,Qe.original_sizes,Qe.reshaped_input_sizes)),Re){if(!Qe.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");Qe.input_labels=this.add_input_labels(Re,Qe.input_points)}return qe&&(Qe.input_boxes=this.reshape_input_points(qe,Qe.original_sizes,Qe.reshaped_input_sizes,!0)),Qe}async post_process_masks(Z,ve,Re,{mask_threshold:qe=0,binarize:Qe=!0,pad_size:tt=null}={}){const ft=[];tt=tt??this.pad_size;const ht=[tt.height,tt.width];for(let Tt=0;Ttqe&&(Ot[Ut]=1);Lt=new _.Tensor("bool",Ot,Lt.dims)}ft.push(Lt)}return ft}generate_crop_boxes(Z,ve,{crop_n_layers:Re=0,overlap_ratio:qe=512/1500,points_per_crop:Qe=32,crop_n_points_downscale_factor:tt=1}={}){}}class Te extends S{pad_image(Z,ve,Re,qe={}){const[Qe,tt,ft]=ve;return super.pad_image(Z,ve,{width:tt+(Re-tt%Re)%Re,height:Qe+(Re-Qe%Re)%Re},{mode:"symmetric",center:!1,constant_values:-1,...qe})}}class je extends S{async _call(Z,ve){Array.isArray(Z)||(Z=[Z]),Array.isArray(ve)||(ve=[ve]);const Re=await Promise.all(Z.map(tt=>this.preprocess(tt))),qe=await Promise.all(ve.map(tt=>this.preprocess(tt,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:(0,_.stack)(Re.map((tt,ft)=>(0,_.cat)([tt.pixel_values,qe[ft].pixel_values],0)),0),original_sizes:Re.map(tt=>tt.original_size),reshaped_input_sizes:Re.map(tt=>tt.reshaped_input_size)}}}class Ye extends O{constructor(Z){var ve;super(Z),(ve=this.config).mel_filters??(ve.mel_filters=(0,h.mel_filter_bank)(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney")),this.window=(0,h.window_function)(this.config.n_fft,"hann")}async _extract_fbank_features(Z){const ve=await(0,h.spectrogram)(Z,this.window,this.config.n_fft,this.config.hop_length,{power:2,mel_filters:this.config.mel_filters,log_mel:"log10",max_num_frames:this.config.nb_max_frames}),Re=ve.data,qe=(0,p.max)(Re)[0];for(let Qe=0;Qethis.config.n_samples?(console.warn("Attempting to extract features for audio longer than 30 seconds. If using a pipeline to extract transcript from a long audio clip, remember to specify `chunk_length_s` and/or `stride_length_s`."),ve=Z.slice(0,this.config.n_samples)):(ve=new Float32Array(this.config.n_samples),ve.set(Z)),{input_features:(await this._extract_fbank_features(ve)).unsqueeze_(0)}}}class et extends O{_zero_mean_unit_var_norm(Z){const Re=Z.reduce((Qe,tt)=>Qe+tt,0)/Z.length,qe=Z.reduce((Qe,tt)=>Qe+(tt-Re)**2,0)/Z.length;return Z.map(Qe=>(Qe-Re)/Math.sqrt(qe+1e-7))}async _call(Z){y(Z,"Wav2Vec2FeatureExtractor"),Z instanceof Float64Array&&(Z=new Float32Array(Z));let ve=Z;this.config.do_normalize&&(ve=this._zero_mean_unit_var_norm(ve));const Re=[1,ve.length];return{input_values:new _.Tensor("float32",ve,Re),attention_mask:new _.Tensor("int64",new BigInt64Array(ve.length).fill(1n),Re)}}}class A extends O{constructor(Z){super(Z);const ve=this.config.sampling_rate,Re=(0,h.mel_filter_bank)(256,this.config.num_mel_bins,20,Math.floor(ve/2),ve,null,"kaldi",!0);for(let qe=0;qeRe*32768),(0,h.spectrogram)(Z,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:ve,transpose:!0})}async _call(Z,{padding:ve=!0,pad_to_multiple_of:Re=2,do_normalize_per_mel_bins:qe=!0,return_attention_mask:Qe=!0}={}){y(Z,"SeamlessM4TFeatureExtractor");let tt=await this._extract_fbank_features(Z,this.config.max_length);if(qe){const[Ot,Ut]=tt.dims,Xt=tt.data;for(let Yt=0;Yt0){const rr=new Float32Array(Ut*(Ot+Yt));rr.set(Xt),rr.fill(this.config.padding_value,Xt.length);const Ht=Ot+Yt;tt=new _.Tensor(tt.type,rr,[Ht,Ut]),Qe&&(ft=new _.Tensor("int64",new BigInt64Array(Ht),[1,Ht]),ft.data.fill(1n,0,Ot))}}const[ht,Tt]=tt.dims,bt=this.config.stride;if(ht%bt!==0)throw new Error(`The number of frames (${ht}) must be a multiple of the stride (${bt}).`);const Lt=tt.view(1,Math.floor(ht/bt),Tt*bt),at={input_features:Lt};if(Qe){const Ot=Lt.dims[1],Ut=new BigInt64Array(Ot);if(ft){const Xt=ft.data;for(let Yt=1,rr=0;Yt0)if(Re==="rand_trunc"){const ft=Math.floor(Math.random()*(tt+1));Z=Z.subarray(ft,ft+ve),Qe=await this._extract_fbank_features(Z,this.mel_filters_slaney,this.config.nb_max_samples)}else throw new Error(`Truncation strategy "${Re}" not implemented`);else{if(tt<0){let ft=new Float64Array(ve);if(ft.set(Z),qe==="repeat")for(let ht=Z.length;ht({id:ht,start:Tt*Re,end:bt*Re,confidence:Et/(bt-Tt)})))}return qe}}class re extends O{constructor(Z){super(Z);const ve=this.config.sampling_rate,Re=(0,h.mel_filter_bank)(256,this.config.num_mel_bins,20,Math.floor(ve/2),ve,null,"kaldi",!0);for(let qe=0;qeve*32768),(0,h.spectrogram)(Z,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,transpose:!0,min_num_frames:this.min_num_frames})}async _call(Z){y(Z,"WeSpeakerFeatureExtractor");const ve=(await this._extract_fbank_features(Z)).unsqueeze_(0);if(this.config.fbank_centering_span===null){const Re=ve.mean(1).data,qe=ve.data,[Qe,tt,ft]=ve.dims;for(let ht=0;ht/gm,bboxes:/([^<]+)?/gm},this.size_per_bin=1e3}construct_prompts(Z){typeof Z=="string"&&(Z=[Z]);const ve=[];for(const Re of Z)if(this.task_prompts_without_inputs.has(Re))ve.push(this.task_prompts_without_inputs.get(Re));else{for(const[qe,Qe]of this.task_prompts_with_input)if(Re.includes(qe)){ve.push(Qe.replaceAll("{input}",Re).replaceAll(qe,""));break}ve.length!==Z.length&&ve.push(Re)}return ve}post_process_generation(Z,ve,Re){const qe=this.tasks_answer_post_processing_type.get(ve)??"pure_text";Z=Z.replaceAll("","").replaceAll("","");let Qe;switch(qe){case"pure_text":Qe=Z;break;case"description_with_bboxes":case"bboxes":case"phrase_grounding":case"ocr":const tt=qe==="ocr"?"quad_boxes":"bboxes",ft=Z.matchAll(this.regexes[tt]),ht=[],Tt=[];for(const[bt,Et,...Lt]of ft)ht.push(Et?Et.trim():ht.at(-1)??""),Tt.push(Lt.map((at,Ot)=>(Number(at)+.5)/this.size_per_bin*Re[Ot%2]));Qe={labels:ht,[tt]:Tt};break;default:throw new Error(`Task "${ve}" (of type "${qe}") not yet implemented.`)}return{[ve]:Qe}}}class Je{static async from_pretrained(Z,{progress_callback:ve=null,config:Re=null,cache_dir:qe=null,local_files_only:Qe=!1,revision:tt="main"}={}){let ft=Re??await(0,l.getModelJSON)(Z,"preprocessor_config.json",!0,{progress_callback:ve,config:Re,cache_dir:qe,local_files_only:Qe,revision:tt}),ht=ft.feature_extractor_type??ft.image_processor_type,Tt=this.FEATURE_EXTRACTOR_CLASS_MAPPING[ht];if(!Tt)if(ft.size!==void 0)console.warn(`Feature extractor type "${ht}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),Tt=S;else throw new Error(`Unknown Feature Extractor type: ${ht}`);let bt=this.PROCESSOR_CLASS_MAPPING[ft.processor_class]??R,Et=new Tt(ft);return new bt(Et)}}He(Je,"FEATURE_EXTRACTOR_CLASS_MAPPING",{ImageFeatureExtractor:S,WhisperFeatureExtractor:Ye,ViTFeatureExtractor:xe,MobileViTFeatureExtractor:X,MobileViTImageProcessor:ie,MobileNetV1FeatureExtractor:L,MobileNetV2FeatureExtractor:Se,MobileNetV3FeatureExtractor:Xe,MobileNetV4FeatureExtractor:me,OwlViTFeatureExtractor:Me,Owlv2ImageProcessor:Q,CLIPFeatureExtractor:z,CLIPImageProcessor:B,Florence2Processor:dt,ChineseCLIPFeatureExtractor:j,SiglipImageProcessor:N,ConvNextFeatureExtractor:ae,ConvNextImageProcessor:ce,SegformerFeatureExtractor:C,BitImageProcessor:I,DPTImageProcessor:b,DPTFeatureExtractor:w,GLPNFeatureExtractor:U,BeitFeatureExtractor:Le,DeiTFeatureExtractor:Ke,DetrFeatureExtractor:st,RTDetrImageProcessor:ge,YolosFeatureExtractor:pt,DonutFeatureExtractor:Be,NougatImageProcessor:We,EfficientNetImageProcessor:_e,ViTImageProcessor:Y,VitMatteImageProcessor:je,SamImageProcessor:Ge,Swin2SRImageProcessor:Te,Wav2Vec2FeatureExtractor:et,SeamlessM4TFeatureExtractor:A,SpeechT5FeatureExtractor:ye,ASTFeatureExtractor:$e,ClapFeatureExtractor:Pe,PyAnnoteFeatureExtractor:se,WeSpeakerFeatureExtractor:re}),He(Je,"PROCESSOR_CLASS_MAPPING",{WhisperProcessor:D,Wav2Vec2ProcessorWithLM:ue,PyAnnoteProcessor:le,SamProcessor:ee,SpeechT5Processor:ke,OwlViTProcessor:Ne,Florence2Processor:dt})},"./src/tokenizers.js":(e,t,r)=>{r.r(t),r.d(t,{AlbertTokenizer:()=>Ut,AutoTokenizer:()=>jn,BartTokenizer:()=>Gr,BertTokenizer:()=>Ot,BlenderbotSmallTokenizer:()=>Vo,BlenderbotTokenizer:()=>go,BloomTokenizer:()=>Dr,CLIPTokenizer:()=>Zt,CamembertTokenizer:()=>$t,CodeGenTokenizer:()=>mo,CodeLlamaTokenizer:()=>Cs,CohereTokenizer:()=>Vr,ConvBertTokenizer:()=>Yr,DebertaTokenizer:()=>rr,DebertaV2Tokenizer:()=>Ht,DistilBertTokenizer:()=>mt,ElectraTokenizer:()=>un,EsmTokenizer:()=>ji,FalconTokenizer:()=>Bo,GPT2Tokenizer:()=>Mi,GPTNeoXTokenizer:()=>No,GemmaTokenizer:()=>fo,Grok1Tokenizer:()=>fi,HerbertTokenizer:()=>Pr,LlamaTokenizer:()=>Ti,M2M100Tokenizer:()=>Ji,MBart50Tokenizer:()=>Kr,MBartTokenizer:()=>wn,MPNetTokenizer:()=>Ro,MarianTokenizer:()=>jo,MobileBertTokenizer:()=>Xt,NllbTokenizer:()=>Si,NougatTokenizer:()=>_o,PreTrainedTokenizer:()=>at,Qwen2Tokenizer:()=>Ps,RoFormerTokenizer:()=>$r,RobertaTokenizer:()=>pi,SiglipTokenizer:()=>eo,SpeechT5Tokenizer:()=>Wo,SqueezeBertTokenizer:()=>Yt,T5Tokenizer:()=>Bi,TokenizerModel:()=>xe,VitsTokenizer:()=>Go,Wav2Vec2CTCTokenizer:()=>Uo,WhisperTokenizer:()=>ho,XLMRobertaTokenizer:()=>Lo,XLMTokenizer:()=>Bt,is_chinese_char:()=>U});var o=r("./src/utils/generic.js"),a=r("./src/utils/core.js"),l=r("./src/utils/hub.js"),p=r("./src/utils/maths.js"),_=r("./src/utils/tensor.js"),h=r("./src/utils/data-structures.js"),g=r("./node_modules/@huggingface/jinja/dist/index.js"),M=r("./src/models/whisper/common_whisper.js"),y=r("./src/utils/constants.js");async function E(Ue,W){const pe=await Promise.all([(0,l.getModelJSON)(Ue,"tokenizer.json",!0,W),(0,l.getModelJSON)(Ue,"tokenizer_config.json",!0,W)]);return W.legacy!==null&&(pe[1].legacy=W.legacy),pe}function T(Ue,W){const pe=[];let Ce=0;for(const Fe of Ue.matchAll(W)){const Oe=Fe[0];Ce0&&pe.push(Oe),Ce=Fe.index+Oe.length}return Ce=19968&&Ue<=40959||Ue>=13312&&Ue<=19903||Ue>=131072&&Ue<=173791||Ue>=173824&&Ue<=177983||Ue>=177984&&Ue<=178207||Ue>=178208&&Ue<=183983||Ue>=63744&&Ue<=64255||Ue>=194560&&Ue<=195103}function z(Ue,W,pe){const Ce=[];let Fe=0;for(;Fethis.tokens_to_ids.get(pe)??this.unk_token_id)}convert_ids_to_tokens(W){return W.map(pe=>this.vocab[pe]??this.unk_token)}}class Y extends xe{constructor(W){super(W),this.tokens_to_ids=S(W.vocab),this.unk_token_id=this.tokens_to_ids.get(W.unk_token),this.unk_token=W.unk_token,this.max_input_chars_per_word=W.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[pe,Ce]of this.tokens_to_ids)this.vocab[Ce]=pe}encode(W){const pe=[];for(const Ce of W){const Fe=[...Ce];if(Fe.length>this.max_input_chars_per_word){pe.push(this.unk_token);continue}let Oe=!1,rt=0;const Mt=[];for(;rt0&&(It=this.config.continuing_subword_prefix+It),this.tokens_to_ids.has(It)){kt=It;break}--St}if(kt===null){Oe=!0;break}Mt.push(kt),rt=St}Oe?pe.push(this.unk_token):pe.push(...Mt)}return pe}}class _e extends xe{constructor(W,pe){super(W);const Ce=W.vocab.length;this.vocab=new Array(Ce),this.scores=new Array(Ce);for(let Fe=0;Fe[Fe,Oe])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=pe.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=(0,p.min)(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new h.CharTrie,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(W){const pe=W.sentence,Ce=pe.length;let Fe=0;for(;Fe{const Ue=[...Array.from({length:94},(Fe,Oe)=>Oe+33),...Array.from({length:12},(Fe,Oe)=>Oe+161),...Array.from({length:82},(Fe,Oe)=>Oe+174)],W=Ue.slice();let pe=0;for(let Fe=0;Fe<256;++Fe)Ue.includes(Fe)||(Ue.push(Fe),W.push(256+pe),pe+=1);const Ce=W.map(Fe=>String.fromCharCode(Fe));return Object.fromEntries(Ue.map((Fe,Oe)=>[Fe,Ce[Oe]]))})(),Se=(0,a.reverseDictionary)(L);class Xe extends xe{constructor(W){super(W),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=S(W.vocab),this.unk_token_id=this.tokens_to_ids.get(W.unk_token),this.unk_token=W.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[pe,Ce]of this.tokens_to_ids)this.vocab[Ce]=pe;this.bpe_ranks=new Map(W.merges.map((pe,Ce)=>[pe,Ce])),this.merges=W.merges.map(pe=>pe.split(this.BPE_SPLIT_TOKEN)),this.end_of_word_suffix=W.end_of_word_suffix,this.continuing_subword_suffix=W.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.ignore_merges=this.config.ignore_merges??!1,this.cache=new Map}bpe(W){if(W.length===0)return[];const pe=this.cache.get(W);if(pe!==void 0)return pe;const Ce=Array.from(W);this.end_of_word_suffix&&(Ce[Ce.length-1]+=this.end_of_word_suffix);let Fe=[];if(Ce.length>1){const Oe=new h.PriorityQueue((St,kt)=>St.score`<0x${rt.toString(16).toUpperCase().padStart(2,"0")}>`)):pe.push(this.unk_token)}return pe}}class me extends xe{constructor(W,pe){super(W),this.tokens_to_ids=S(pe.target_lang?W.vocab[pe.target_lang]:W.vocab),this.bos_token=pe.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=pe.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=pe.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=pe.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=new Array(this.tokens_to_ids.size);for(const[Ce,Fe]of this.tokens_to_ids)this.vocab[Fe]=Ce}encode(W){return W}}class X extends o.Callable{constructor(W){super(),this.config=W}static fromConfig(W){if(W===null)return null;switch(W.type){case"BertNormalizer":return new pt(W);case"Precompiled":return new Qe(W);case"Sequence":return new st(W);case"Replace":return new ie(W);case"NFC":return new Me(W);case"NFKC":return new Q(W);case"NFKD":return new ge(W);case"Strip":return new Ke(W);case"StripAccents":return new Le(W);case"Lowercase":return new Be(W);case"Prepend":return new We(W);default:throw new Error(`Unknown Normalizer type: ${W.type}`)}}normalize(W){throw Error("normalize should be implemented in subclass.")}_call(W){return this.normalize(W)}}class ie extends X{normalize(W){const pe=O(this.config.pattern);return pe===null?W:W.replaceAll(pe,this.config.content)}}class Me extends X{normalize(W){return W=W.normalize("NFC"),W}}class Q extends X{normalize(W){return W=W.normalize("NFKC"),W}}class ge extends X{normalize(W){return W=W.normalize("NFKD"),W}}class Ke extends X{normalize(W){return this.config.strip_left&&this.config.strip_right?W=W.trim():(this.config.strip_left&&(W=W.trimStart()),this.config.strip_right&&(W=W.trimEnd())),W}}class Le extends X{normalize(W){return W=b(W),W}}class Be extends X{normalize(W){return W=W.toLowerCase(),W}}class We extends X{normalize(W){return W=this.config.prepend+W,W}}class st extends X{constructor(W){super(W),this.normalizers=W.normalizers.map(pe=>X.fromConfig(pe))}normalize(W){return this.normalizers.reduce((pe,Ce)=>Ce.normalize(pe),W)}}class pt extends X{_tokenize_chinese_chars(W){const pe=[];for(let Ce=0;Cethis.pre_tokenize_text(Ce,pe)):this.pre_tokenize_text(W,pe)).flat()}_call(W,pe){return this.pre_tokenize(W,pe)}}class Te extends Ge{constructor(W){super(),this.pattern=new RegExp(`[^\\s${j}]+|[${j}]`,"gu")}pre_tokenize_text(W,pe){return W.trim().match(this.pattern)||[]}}class je extends Ge{constructor(W){super(),this.config=W,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=new RegExp("'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)|\\s+","gu"),this.byte_encoder=L,this.text_encoder=new TextEncoder}pre_tokenize_text(W,pe){return this.add_prefix_space&&!W.startsWith(" ")&&(W=" "+W),(this.use_regex?W.match(this.pattern)||[]:[W]).map(Fe=>Array.from(this.text_encoder.encode(Fe),Oe=>this.byte_encoder[Oe]).join(""))}}class Ye extends Ge{constructor(W){super(),this.config=W,this.pattern=O(this.config.pattern,this.config.invert)}pre_tokenize_text(W,pe){return this.pattern===null?[]:this.config.invert?W.match(this.pattern)||[]:T(W,this.pattern)}}class et extends Ge{constructor(W){super(),this.config=W,this.pattern=new RegExp(`[^${j}]+|[${j}]+`,"gu")}pre_tokenize_text(W,pe){return W.match(this.pattern)||[]}}class A extends Ge{constructor(W){super(),this.config=W;const pe=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(pe,"gu")}pre_tokenize_text(W,pe){return W.match(this.pattern)||[]}}class $e extends o.Callable{constructor(W){super(),this.config=W}static fromConfig(W){if(W===null)return null;switch(W.type){case"TemplateProcessing":return new re(W);case"ByteLevel":return new ye(W);case"RobertaProcessing":return new se(W);case"BertProcessing":return new Pe(W);case"Sequence":return new R(W);default:throw new Error(`Unknown PostProcessor type: ${W.type}`)}}post_process(W,...pe){throw Error("post_process should be implemented in subclass.")}_call(W,...pe){return this.post_process(W,...pe)}}class Pe extends $e{constructor(W){super(W),this.cls=W.cls[0],this.sep=W.sep[0]}post_process(W,pe=null,{add_special_tokens:Ce=!0}={}){Ce&&(W=(0,a.mergeArrays)([this.cls],W,[this.sep]));let Fe=new Array(W.length).fill(0);if(pe!==null){const Oe=Ce&&this instanceof se?[this.sep]:[],rt=Ce?[this.sep]:[];W=(0,a.mergeArrays)(W,Oe,pe,rt),Fe=(0,a.mergeArrays)(Fe,new Array(pe.length+Oe.length+rt.length).fill(1))}return{tokens:W,token_type_ids:Fe}}}class se extends Pe{}class re extends $e{constructor(W){super(W),this.single=W.single,this.pair=W.pair}post_process(W,pe=null,{add_special_tokens:Ce=!0}={}){const Fe=pe===null?this.single:this.pair;let Oe=[],rt=[];for(const Mt of Fe)"SpecialToken"in Mt?Ce&&(Oe.push(Mt.SpecialToken.id),rt.push(Mt.SpecialToken.type_id)):"Sequence"in Mt&&(Mt.Sequence.id==="A"?(Oe=(0,a.mergeArrays)(Oe,W),rt=(0,a.mergeArrays)(rt,new Array(W.length).fill(Mt.Sequence.type_id))):Mt.Sequence.id==="B"&&(Oe=(0,a.mergeArrays)(Oe,pe),rt=(0,a.mergeArrays)(rt,new Array(pe.length).fill(Mt.Sequence.type_id))));return{tokens:Oe,token_type_ids:rt}}}class ye extends $e{post_process(W,pe=null){return pe&&(W=(0,a.mergeArrays)(W,pe)),{tokens:W}}}class R extends $e{constructor(W){super(W),this.processors=W.processors.map(pe=>$e.fromConfig(pe))}post_process(W,pe=null,Ce={}){let Fe;for(const Oe of this.processors)if(Oe instanceof ye)W=Oe.post_process(W).tokens,pe&&(pe=Oe.post_process(pe).tokens);else{const rt=Oe.post_process(W,pe,Ce);W=rt.tokens,Fe=rt.token_type_ids}return{tokens:W,token_type_ids:Fe}}}class ee extends o.Callable{constructor(W){super(),this.config=W,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=W.trim_offsets}static fromConfig(W){if(W===null)return null;switch(W.type){case"WordPiece":return new Ne(W);case"Metaspace":return new qe(W);case"ByteLevel":return new dt(W);case"Replace":return new D(W);case"ByteFallback":return new ue(W);case"Fuse":return new le(W);case"Strip":return new ke(W);case"Sequence":return new Ve(W);case"CTC":return new Je(W);case"BPEDecoder":return new Z(W);default:throw new Error(`Unknown Decoder type: ${W.type}`)}}_call(W){return this.decode(W)}decode(W){return this.decode_chain(W).join("")}decode_chain(W){throw Error("`decode_chain` should be implemented in subclass.")}}class D extends ee{decode_chain(W){const pe=O(this.config.pattern);return pe===null?W:W.map(Ce=>Ce.replaceAll(pe,this.config.content))}}class ue extends ee{constructor(W){super(W),this.text_decoder=new TextDecoder}decode_chain(W){const pe=[];let Ce=[];for(const Fe of W){let Oe=null;if(Fe.length===6&&Fe.startsWith("<0x")&&Fe.endsWith(">")){const rt=parseInt(Fe.slice(3,5),16);isNaN(rt)||(Oe=rt)}if(Oe!==null)Ce.push(Oe);else{if(Ce.length>0){const rt=this.text_decoder.decode(Uint8Array.from(Ce));pe.push(rt),Ce=[]}pe.push(Fe)}}if(Ce.length>0){const Fe=this.text_decoder.decode(Uint8Array.from(Ce));pe.push(Fe),Ce=[]}return pe}}class le extends ee{decode_chain(W){return[W.join("")]}}class ke extends ee{constructor(W){super(W),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(W){return W.map(pe=>{let Ce=0;for(let Oe=0;Oe(Ce!==0&&(pe.startsWith(this.config.prefix)?pe=pe.replace(this.config.prefix,""):pe=" "+pe),this.cleanup&&(pe=w(pe)),pe))}}class dt extends ee{constructor(W){super(W),this.byte_decoder=Se,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(W){const pe=W.join(""),Ce=new Uint8Array([...pe].map(Oe=>this.byte_decoder[Oe]));return this.text_decoder.decode(Ce)}decode_chain(W){const pe=[];let Ce=[];for(const Fe of W)this.added_tokens.find(Oe=>Oe.content===Fe)!==void 0?(Ce.length>0&&(pe.push(this.convert_tokens_to_string(Ce)),Ce=[]),pe.push(Fe)):Ce.push(Fe);return Ce.length>0&&pe.push(this.convert_tokens_to_string(Ce)),pe}}class Je extends ee{constructor(W){super(W),this.pad_token=this.config.pad_token,this.word_delimiter_token=this.config.word_delimiter_token,this.cleanup=this.config.cleanup}convert_tokens_to_string(W){if(W.length===0)return"";const pe=[W[0]];for(let Oe=1;OeOe!==this.pad_token).join("");return this.cleanup&&(Fe=w(Fe).replaceAll(this.word_delimiter_token," ").trim()),Fe}decode_chain(W){return[this.convert_tokens_to_string(W)]}}class Ve extends ee{constructor(W){super(W),this.decoders=W.decoders.map(pe=>ee.fromConfig(pe))}decode_chain(W){return this.decoders.reduce((pe,Ce)=>Ce.decode_chain(pe),W)}}class Z extends ee{constructor(W){super(W),this.suffix=this.config.suffix}decode_chain(W){return W.map((pe,Ce)=>pe.replaceAll(this.suffix,Ce===W.length-1?"":" "))}}class ve extends ee{decode_chain(W){let pe="";for(let Ce=1;CeCe.normalize("NFKC")).join("～"):W=W.normalize("NFKC"),W}}class tt extends Ge{constructor(W){super(),this.tokenizers=W.pretokenizers.map(pe=>Ge.fromConfig(pe))}pre_tokenize_text(W,pe){return this.tokenizers.reduce((Ce,Fe)=>Fe.pre_tokenize(Ce,pe),[W])}}class ft extends Ge{constructor(W){super()}pre_tokenize_text(W,pe){return W.match(/\w+|[^\w\s]+/g)||[]}}class ht extends Ge{constructor(W){super()}pre_tokenize_text(W,pe){return B(W)}}class Tt extends Ge{constructor(W){super(),this.config=W,this.pattern=O(this.config.pattern),this.content=this.config.content}pre_tokenize_text(W,pe){return this.pattern===null?[W]:[W.replaceAll(this.pattern,this.config.content)]}}const bt=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function Et(Ue,W,pe,Ce){for(const Fe of Object.keys(Ue)){const Oe=W-Ue[Fe].length,rt=pe(Fe),Mt=new Array(Oe).fill(rt);Ue[Fe]=Ce==="right"?(0,a.mergeArrays)(Ue[Fe],Mt):(0,a.mergeArrays)(Mt,Ue[Fe])}}function Lt(Ue,W){for(const pe of Object.keys(Ue))Ue[pe].length=W}class at extends o.Callable{constructor(pe,Ce){super();He(this,"return_token_type_ids",!1);He(this,"padding_side","right");this._tokenizer_config=Ce,this.normalizer=X.fromConfig(pe.normalizer),this.pre_tokenizer=Ge.fromConfig(pe.pre_tokenizer),this.model=xe.fromConfig(pe.model,Ce),this.post_processor=$e.fromConfig(pe.post_processor),this.decoder=ee.fromConfig(pe.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(const Fe of pe.added_tokens){const Oe=new ce(Fe);this.added_tokens.push(Oe),this.model.tokens_to_ids.set(Oe.content,Oe.id),this.model.vocab[Oe.id]=Oe.content,Oe.special&&(this.special_tokens.push(Oe.content),this.all_special_ids.push(Oe.id))}if(this.additional_special_tokens=Ce.additional_special_tokens??[],this.special_tokens.push(...this.additional_special_tokens),this.special_tokens=[...new Set(this.special_tokens)],this.decoder&&(this.decoder.added_tokens=this.added_tokens,this.decoder.end_of_word_suffix=this.model.end_of_word_suffix),this.added_tokens_regex=this.added_tokens.length>0?new RegExp(this.added_tokens.toSorted((Fe,Oe)=>Oe.content.length-Fe.content.length).map(Fe=>`${Fe.lstrip?"\\s*":""}(${(0,a.escapeRegExp)(Fe.content)})${Fe.rstrip?"\\s*":""}`).join("|")):null,this.mask_token=this.getToken("mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken("pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken("sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.unk_token=this.getToken("unk_token"),this.unk_token_id=this.model.tokens_to_ids.get(this.unk_token),this.model_max_length=Ce.model_max_length,this.remove_space=Ce.remove_space,this.clean_up_tokenization_spaces=Ce.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=Ce.do_lowercase_and_remove_accent??!1,Ce.padding_side&&(this.padding_side=Ce.padding_side),this.legacy=!1,this.chat_template=Ce.chat_template??null,Array.isArray(this.chat_template)){const Fe=Object.create(null);for(const{name:Oe,template:rt}of this.chat_template){if(typeof Oe!="string"||typeof rt!="string")throw new Error('Chat template must be a list of objects with "name" and "template" properties');Fe[Oe]=rt}this.chat_template=Fe}this._compiled_template_cache=new Map}getToken(...pe){for(const Ce of pe){const Fe=this._tokenizer_config[Ce];if(Fe)if(typeof Fe=="object"){if(Fe.__type==="AddedToken")return Fe.content;throw Error(`Unknown token: ${Fe}`)}else return Fe}return null}static async from_pretrained(pe,{progress_callback:Ce=null,config:Fe=null,cache_dir:Oe=null,local_files_only:rt=!1,revision:Mt="main",legacy:St=null}={}){const kt=await E(pe,{progress_callback:Ce,config:Fe,cache_dir:Oe,local_files_only:rt,revision:Mt,legacy:St});return new this(...kt)}_call(pe,{text_pair:Ce=null,add_special_tokens:Fe=!0,padding:Oe=!1,truncation:rt=null,max_length:Mt=null,return_tensor:St=!0,return_token_type_ids:kt=null}={}){const It=Array.isArray(pe);let tr;if(It){if(pe.length===0)throw Error("text array must be non-empty");if(Ce!==null){if(Array.isArray(Ce)){if(pe.length!==Ce.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");tr=pe.map((or,qt)=>this._encode_plus(or,{text_pair:Ce[qt],add_special_tokens:Fe,return_token_type_ids:kt}))}else tr=pe.map(or=>this._encode_plus(or,{add_special_tokens:Fe,return_token_type_ids:kt}))}else{if(pe==null)throw Error("text may not be null or undefined");if(Array.isArray(Ce))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");tr=[this._encode_plus(pe,{text_pair:Ce,add_special_tokens:Fe,return_token_type_ids:kt})]}if(Mt===null?Oe==="max_length"?Mt=this.model_max_length:Mt=(0,p.max)(tr.map(or=>or.input_ids.length))[0]:rt||console.warn("Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation=true` to explicitly truncate examples to max length."),Mt=Math.min(Mt,this.model_max_length??1/0),Oe||rt)for(let or=0;orMt?rt&&Lt(tr[or],Mt):Oe&&Et(tr[or],Mt,qt=>qt==="input_ids"?this.pad_token_id:0,this.padding_side));const Ar={};if(St){if(!(Oe&&rt)&&tr.some(qt=>{var _r;for(const Cn of Object.keys(qt))if(qt[Cn].length!==((_r=tr[0][Cn])==null?void 0:_r.length))return!0;return!1}))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");const or=[tr.length,tr[0].input_ids.length];for(const qt of Object.keys(tr[0]))Ar[qt]=new _.Tensor("int64",BigInt64Array.from(tr.flatMap(_r=>_r[qt]).map(BigInt)),or)}else{for(const or of Object.keys(tr[0]))Ar[or]=tr.map(qt=>qt[or]);if(!It)for(const or of Object.keys(Ar))Ar[or]=Ar[or][0]}return Ar}_encode_text(pe){return pe===null?null:(this.added_tokens_regex?pe.split(this.added_tokens_regex).filter(Oe=>Oe):[pe]).map((Oe,rt)=>{if(this.added_tokens.find(St=>St.content===Oe)!==void 0)return Oe;{if(this.remove_space===!0&&(Oe=Oe.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(Oe=I(Oe)),this.normalizer!==null&&(Oe=this.normalizer(Oe)),Oe.length===0)return[];const St=this.pre_tokenizer!==null?this.pre_tokenizer(Oe,{section_index:rt}):[Oe];return this.model(St)}}).flat()}_encode_plus(pe,{text_pair:Ce=null,add_special_tokens:Fe=!0,return_token_type_ids:Oe=null}={}){const{tokens:rt,token_type_ids:Mt}=this._tokenize_helper(pe,{pair:Ce,add_special_tokens:Fe}),St=this.model.convert_tokens_to_ids(rt),kt={input_ids:St,attention_mask:new Array(St.length).fill(1)};return(Oe??this.return_token_type_ids)&&Mt&&(kt.token_type_ids=Mt),kt}_tokenize_helper(pe,{pair:Ce=null,add_special_tokens:Fe=!1}={}){const Oe=this._encode_text(pe),rt=this._encode_text(Ce);return this.post_processor?this.post_processor(Oe,rt,{add_special_tokens:Fe}):{tokens:(0,a.mergeArrays)(Oe??[],rt??[])}}tokenize(pe,{pair:Ce=null,add_special_tokens:Fe=!1}={}){return this._tokenize_helper(pe,{pair:Ce,add_special_tokens:Fe}).tokens}encode(pe,{text_pair:Ce=null,add_special_tokens:Fe=!0,return_token_type_ids:Oe=null}={}){return this._encode_plus(pe,{text_pair:Ce,add_special_tokens:Fe,return_token_type_ids:Oe}).input_ids}batch_decode(pe,Ce={}){return pe instanceof _.Tensor&&(pe=pe.tolist()),pe.map(Fe=>this.decode(Fe,Ce))}decode(pe,Ce={}){if(pe instanceof _.Tensor&&(pe=C(pe)),!Array.isArray(pe)||pe.length===0||!(0,a.isIntegralNumber)(pe[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(pe,Ce)}decode_single(pe,{skip_special_tokens:Ce=!1,clean_up_tokenization_spaces:Fe=null}){let Oe=this.model.convert_ids_to_tokens(pe);Ce&&(Oe=Oe.filter(Mt=>!this.special_tokens.includes(Mt)));let rt=this.decoder?this.decoder(Oe):Oe.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(rt=rt.replaceAll(this.decoder.end_of_word_suffix," "),Ce&&(rt=rt.trim())),(Fe??this.clean_up_tokenization_spaces)&&(rt=w(rt)),rt}apply_chat_template(pe,{tools:Ce=null,documents:Fe=null,chat_template:Oe=null,add_generation_prompt:rt=!1,tokenize:Mt=!0,padding:St=!1,truncation:kt=!1,max_length:It=null,return_tensor:tr=!0,return_dict:Ar=!1,tokenizer_kwargs:or={},...qt}={}){if(this.chat_template&&typeof this.chat_template=="object"||this.chat_template===null){const ct=this.chat_template;if(Oe!==null&&Object.hasOwn(ct,Oe))Oe=ct[Oe];else if(Oe===null&&"default"in ct)Oe=ct.default;else if(Oe===null)throw Error(`This model has multiple chat templates with no default specified! Please either pass a chat template or the name of the template you wish to use to the 'chat_template' argument. Available template names are ${Object.keys(ct).sort()}.`)}else if(this.chat_template)Oe=this.chat_template;else throw Error("Cannot use apply_chat_template() because tokenizer.chat_template is not set and no template argument was passed! For information about writing templates and setting the tokenizer.chat_template attribute, please see the documentation at https://huggingface.co/docs/transformers/main/en/chat_templating");if(typeof Oe!="string")throw Error(`chat_template must be a string, but got ${typeof Oe}`);let _r=this._compiled_template_cache.get(Oe);_r===void 0&&(_r=new g.Template(Oe),this._compiled_template_cache.set(Oe,_r));const Cn=Object.create(null);for(const ct of bt){const Kn=this.getToken(ct);Kn&&(Cn[ct]=Kn)}const gn=_r.render({messages:pe,add_generation_prompt:rt,tools:Ce,documents:Fe,...Cn,...qt});if(Mt){const ct=this._call(gn,{add_special_tokens:!1,padding:St,truncation:kt,max_length:It,return_tensor:tr,...or});return Ar?ct:ct.input_ids}return gn}}class Ot extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Ut extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Xt extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Yt extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class rr extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Ht extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Pr extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Yr extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class $r extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class mt extends at{}class $t extends at{}class Bt extends at{constructor(pe,Ce){super(pe,Ce);He(this,"return_token_type_ids",!0);console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}}class un extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Bi extends at{}class Mi extends at{}class Gr extends at{}class wn extends at{constructor(W,pe){super(W,pe),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter(Ce=>this.languageRegex.test(Ce)),this.lang_to_token=Ce=>Ce}_build_translation_inputs(W,pe,Ce){return ki(this,W,pe,Ce)}}class Kr extends wn{}class pi extends at{}class Dr extends at{constructor(W,pe){var Oe,rt;const Ce=".,!?…。，、।۔،",Fe=(rt=(Oe=W.pre_tokenizer)==null?void 0:Oe.pretokenizers[0])==null?void 0:rt.pattern;Fe&&Fe.Regex===` ?[^(\\s|[${Ce}])]+`&&(Fe.Regex=` ?[^\\s${Ce}]+`),super(W,pe)}}const Ni="▁";class Ti extends at{constructor(pe,Ce){super(pe,Ce);He(this,"padding_side","left");this.legacy=Ce.legacy??!0,this.legacy||(this.normalizer=null,this.pre_tokenizer=new Re({replacement:Ni,add_prefix_space:!0,prepend_scheme:"first"}))}_encode_text(pe){if(pe===null)return null;if(this.legacy||pe.length===0)return super._encode_text(pe);let Ce=super._encode_text(Ni+pe.replaceAll(Ni," "));return Ce.length>1&&Ce[0]===Ni&&this.special_tokens.includes(Ce[1])&&(Ce=Ce.slice(1)),Ce}}class Cs extends at{}class Lo extends at{}class Ro extends at{}class Bo extends at{}class No extends at{}class ji extends at{}class Ps extends at{}class fo extends at{}class fi extends at{}function ki(Ue,W,pe,Ce){if(!("language_codes"in Ue)||!Array.isArray(Ue.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in Ue)||!(Ue.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in Ue)||typeof Ue.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const Fe=Ce.src_lang,Oe=Ce.tgt_lang;if(!Ue.language_codes.includes(Oe))throw new Error(`Target language code "${Oe}" is not valid. Must be one of: {${Ue.language_codes.join(", ")}}`);if(Fe!==void 0){if(!Ue.language_codes.includes(Fe))throw new Error(`Source language code "${Fe}" is not valid. Must be one of: {${Ue.language_codes.join(", ")}}`);for(const rt of Ue.post_processor.config.single)if("SpecialToken"in rt&&Ue.languageRegex.test(rt.SpecialToken.id)){rt.SpecialToken.id=Ue.lang_to_token(Fe);break}}return Ce.forced_bos_token_id=Ue.model.convert_tokens_to_ids([Ue.lang_to_token(Oe)])[0],Ue._call(W,pe)}class Si extends at{constructor(W,pe){super(W,pe),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(Ce=>this.languageRegex.test(Ce)),this.lang_to_token=Ce=>Ce}_build_translation_inputs(W,pe,Ce){return ki(this,W,pe,Ce)}}class Ji extends at{constructor(W,pe){super(W,pe),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(Ce=>this.languageRegex.test(Ce)).map(Ce=>Ce.slice(2,-2)),this.lang_to_token=Ce=>`__${Ce}__`}_build_translation_inputs(W,pe,Ce){return ki(this,W,pe,Ce)}}class ho extends at{get timestamp_begin(){return this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1}_decode_asr(W,{return_timestamps:pe=!1,return_language:Ce=!1,time_precision:Fe=null,force_full_sequences:Oe=!0}={}){if(Fe===null)throw Error("Must specify time_precision");let rt=null;const Mt=pe==="word";function St(){return{language:rt,timestamp:[null,null],text:""}}const kt=[];let It=St(),tr=0;const Ar=this.timestamp_begin;let or=[],qt=[],_r=!1,Cn=null;const gn=new Set(this.all_special_ids);for(const Tr of W){const cn=Tr.tokens,On=Mt?Tr.token_timestamps:null;let Jt=null,Un=Ar;if("stride"in Tr){const[Er,At,vr]=Tr.stride;if(tr-=At,Cn=Er-vr,At&&(Un=At/Fe+Ar),vr)for(let Lr=cn.length-1;Lr>=0;--Lr){const Xr=Number(cn[Lr]);if(Xr>=Ar){if(Jt!==null&&(Xr-Ar)*Fe=Ar){const vr=(At-Ar)*Fe+tr,Lr=(0,p.round)(vr,2);if(Jt!==null&&At>=Jt)_r=!0;else if(_r||or.length>0&&At0?(or.push(yn),Mt&&qt.push(Sr)):or.every(Er=>Er.length===0)&&(It=St(),or=[],yn=[],qt=[],Sr=[])}if(or.length>0){if(Oe&&pe)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. 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Please configure the dynamicRequireTargets or/and ignoreDynamicRequires option of @rollup/plugin-commonjs appropriately for this require call to work.')}var tx={exports:{}};/*! + +JSZip v3.10.1 - A JavaScript class for generating and reading zip files + + +(c) 2009-2016 Stuart Knightley +Dual licenced under the MIT license or GPLv3. See https://raw.github.com/Stuk/jszip/main/LICENSE.markdown. + +JSZip uses the library pako released under the MIT license : +https://github.com/nodeca/pako/blob/main/LICENSE +*/(function(e,t){(function(r){e.exports=r()})(function(){return function r(o,a,l){function p(g,M){if(!a[g]){if(!o[g]){var y=typeof ph=="function"&&ph;if(!M&&y)return y(g,!0);if(_)return _(g,!0);var E=new Error("Cannot find module '"+g+"'");throw E.code="MODULE_NOT_FOUND",E}var T=a[g]={exports:{}};o[g][0].call(T.exports,function(O){var S=o[g][1][O];return p(S||O)},T,T.exports,r,o,a,l)}return a[g].exports}for(var _=typeof ph=="function"&&ph,h=0;h>2,T=(3&g)<<4|M>>4,O=1>6:64,S=2>4,M=(15&E)<<4|(T=_.indexOf(h.charAt(S++)))>>2,y=(3&T)<<6|(O=_.indexOf(h.charAt(S++))),b[C++]=g,T!==64&&(b[C++]=M),O!==64&&(b[C++]=y);return b}},{"./support":30,"./utils":32}],2:[function(r,o,a){var l=r("./external"),p=r("./stream/DataWorker"),_=r("./stream/Crc32Probe"),h=r("./stream/DataLengthProbe");function g(M,y,E,T,O){this.compressedSize=M,this.uncompressedSize=y,this.crc32=E,this.compression=T,this.compressedContent=O}g.prototype={getContentWorker:function(){var M=new p(l.Promise.resolve(this.compressedContent)).pipe(this.compression.uncompressWorker()).pipe(new h("data_length")),y=this;return M.on("end",function(){if(this.streamInfo.data_length!==y.uncompressedSize)throw new Error("Bug : uncompressed data size mismatch")}),M},getCompressedWorker:function(){return new p(l.Promise.resolve(this.compressedContent)).withStreamInfo("compressedSize",this.compressedSize).withStreamInfo("uncompressedSize",this.uncompressedSize).withStreamInfo("crc32",this.crc32).withStreamInfo("compression",this.compression)}},g.createWorkerFrom=function(M,y,E){return M.pipe(new _).pipe(new h("uncompressedSize")).pipe(y.compressWorker(E)).pipe(new h("compressedSize")).withStreamInfo("compression",y)},o.exports=g},{"./external":6,"./stream/Crc32Probe":25,"./stream/DataLengthProbe":26,"./stream/DataWorker":27}],3:[function(r,o,a){var l=r("./stream/GenericWorker");a.STORE={magic:"\0\0",compressWorker:function(){return new l("STORE compression")},uncompressWorker:function(){return new l("STORE decompression")}},a.DEFLATE=r("./flate")},{"./flate":7,"./stream/GenericWorker":28}],4:[function(r,o,a){var l=r("./utils"),p=function(){for(var _,h=[],g=0;g<256;g++){_=g;for(var M=0;M<8;M++)_=1&_?3988292384^_>>>1:_>>>1;h[g]=_}return h}();o.exports=function(_,h){return _!==void 0&&_.length?l.getTypeOf(_)!=="string"?function(g,M,y,E){var T=p,O=E+y;g^=-1;for(var S=E;S>>8^T[255&(g^M[S])];return-1^g}(0|h,_,_.length,0):function(g,M,y,E){var T=p,O=E+y;g^=-1;for(var S=E;S>>8^T[255&(g^M.charCodeAt(S))];return-1^g}(0|h,_,_.length,0):0}},{"./utils":32}],5:[function(r,o,a){a.base64=!1,a.binary=!1,a.dir=!1,a.createFolders=!0,a.date=null,a.compression=null,a.compressionOptions=null,a.comment=null,a.unixPermissions=null,a.dosPermissions=null},{}],6:[function(r,o,a){var l=null;l=typeof Promise<"u"?Promise:r("lie"),o.exports={Promise:l}},{lie:37}],7:[function(r,o,a){var l=typeof Uint8Array<"u"&&typeof Uint16Array<"u"&&typeof Uint32Array<"u",p=r("pako"),_=r("./utils"),h=r("./stream/GenericWorker"),g=l?"uint8array":"array";function M(y,E){h.call(this,"FlateWorker/"+y),this._pako=null,this._pakoAction=y,this._pakoOptions=E,this.meta={}}a.magic="\b\0",_.inherits(M,h),M.prototype.processChunk=function(y){this.meta=y.meta,this._pako===null&&this._createPako(),this._pako.push(_.transformTo(g,y.data),!1)},M.prototype.flush=function(){h.prototype.flush.call(this),this._pako===null&&this._createPako(),this._pako.push([],!0)},M.prototype.cleanUp=function(){h.prototype.cleanUp.call(this),this._pako=null},M.prototype._createPako=function(){this._pako=new p[this._pakoAction]({raw:!0,level:this._pakoOptions.level||-1});var y=this;this._pako.onData=function(E){y.push({data:E,meta:y.meta})}},a.compressWorker=function(y){return new M("Deflate",y)},a.uncompressWorker=function(){return new M("Inflate",{})}},{"./stream/GenericWorker":28,"./utils":32,pako:38}],8:[function(r,o,a){function l(T,O){var S,C="";for(S=0;S>>=8;return C}function p(T,O,S,C,w,b){var I,U,z=T.file,B=T.compression,j=b!==g.utf8encode,N=_.transformTo("string",b(z.name)),ae=_.transformTo("string",g.utf8encode(z.name)),ce=z.comment,xe=_.transformTo("string",b(ce)),Y=_.transformTo("string",g.utf8encode(ce)),_e=ae.length!==z.name.length,L=Y.length!==ce.length,Se="",Xe="",me="",X=z.dir,ie=z.date,Me={crc32:0,compressedSize:0,uncompressedSize:0};O&&!S||(Me.crc32=T.crc32,Me.compressedSize=T.compressedSize,Me.uncompressedSize=T.uncompressedSize);var Q=0;O&&(Q|=8),j||!_e&&!L||(Q|=2048);var ge=0,Ke=0;X&&(ge|=16),w==="UNIX"?(Ke=798,ge|=function(Be,We){var st=Be;return Be||(st=We?16893:33204),(65535&st)<<16}(z.unixPermissions,X)):(Ke=20,ge|=function(Be){return 63&(Be||0)}(z.dosPermissions)),I=ie.getUTCHours(),I<<=6,I|=ie.getUTCMinutes(),I<<=5,I|=ie.getUTCSeconds()/2,U=ie.getUTCFullYear()-1980,U<<=4,U|=ie.getUTCMonth()+1,U<<=5,U|=ie.getUTCDate(),_e&&(Xe=l(1,1)+l(M(N),4)+ae,Se+="up"+l(Xe.length,2)+Xe),L&&(me=l(1,1)+l(M(xe),4)+Y,Se+="uc"+l(me.length,2)+me);var Le="";return Le+=` +\0`,Le+=l(Q,2),Le+=B.magic,Le+=l(I,2),Le+=l(U,2),Le+=l(Me.crc32,4),Le+=l(Me.compressedSize,4),Le+=l(Me.uncompressedSize,4),Le+=l(N.length,2),Le+=l(Se.length,2),{fileRecord:y.LOCAL_FILE_HEADER+Le+N+Se,dirRecord:y.CENTRAL_FILE_HEADER+l(Ke,2)+Le+l(xe.length,2)+"\0\0\0\0"+l(ge,4)+l(C,4)+N+Se+xe}}var _=r("../utils"),h=r("../stream/GenericWorker"),g=r("../utf8"),M=r("../crc32"),y=r("../signature");function E(T,O,S,C){h.call(this,"ZipFileWorker"),this.bytesWritten=0,this.zipComment=O,this.zipPlatform=S,this.encodeFileName=C,this.streamFiles=T,this.accumulate=!1,this.contentBuffer=[],this.dirRecords=[],this.currentSourceOffset=0,this.entriesCount=0,this.currentFile=null,this._sources=[]}_.inherits(E,h),E.prototype.push=function(T){var O=T.meta.percent||0,S=this.entriesCount,C=this._sources.length;this.accumulate?this.contentBuffer.push(T):(this.bytesWritten+=T.data.length,h.prototype.push.call(this,{data:T.data,meta:{currentFile:this.currentFile,percent:S?(O+100*(S-C-1))/S:100}}))},E.prototype.openedSource=function(T){this.currentSourceOffset=this.bytesWritten,this.currentFile=T.file.name;var O=this.streamFiles&&!T.file.dir;if(O){var S=p(T,O,!1,this.currentSourceOffset,this.zipPlatform,this.encodeFileName);this.push({data:S.fileRecord,meta:{percent:0}})}else this.accumulate=!0},E.prototype.closedSource=function(T){this.accumulate=!1;var O=this.streamFiles&&!T.file.dir,S=p(T,O,!0,this.currentSourceOffset,this.zipPlatform,this.encodeFileName);if(this.dirRecords.push(S.dirRecord),O)this.push({data:function(C){return y.DATA_DESCRIPTOR+l(C.crc32,4)+l(C.compressedSize,4)+l(C.uncompressedSize,4)}(T),meta:{percent:100}});else for(this.push({data:S.fileRecord,meta:{percent:0}});this.contentBuffer.length;)this.push(this.contentBuffer.shift());this.currentFile=null},E.prototype.flush=function(){for(var T=this.bytesWritten,O=0;O=this.index;h--)g=(g<<8)+this.byteAt(h);return this.index+=_,g},readString:function(_){return l.transformTo("string",this.readData(_))},readData:function(){},lastIndexOfSignature:function(){},readAndCheckSignature:function(){},readDate:function(){var _=this.readInt(4);return new Date(Date.UTC(1980+(_>>25&127),(_>>21&15)-1,_>>16&31,_>>11&31,_>>5&63,(31&_)<<1))}},o.exports=p},{"../utils":32}],19:[function(r,o,a){var l=r("./Uint8ArrayReader");function p(_){l.call(this,_)}r("../utils").inherits(p,l),p.prototype.readData=function(_){this.checkOffset(_);var h=this.data.slice(this.zero+this.index,this.zero+this.index+_);return this.index+=_,h},o.exports=p},{"../utils":32,"./Uint8ArrayReader":21}],20:[function(r,o,a){var l=r("./DataReader");function p(_){l.call(this,_)}r("../utils").inherits(p,l),p.prototype.byteAt=function(_){return this.data.charCodeAt(this.zero+_)},p.prototype.lastIndexOfSignature=function(_){return this.data.lastIndexOf(_)-this.zero},p.prototype.readAndCheckSignature=function(_){return _===this.readData(4)},p.prototype.readData=function(_){this.checkOffset(_);var h=this.data.slice(this.zero+this.index,this.zero+this.index+_);return this.index+=_,h},o.exports=p},{"../utils":32,"./DataReader":18}],21:[function(r,o,a){var l=r("./ArrayReader");function p(_){l.call(this,_)}r("../utils").inherits(p,l),p.prototype.readData=function(_){if(this.checkOffset(_),_===0)return new Uint8Array(0);var h=this.data.subarray(this.zero+this.index,this.zero+this.index+_);return this.index+=_,h},o.exports=p},{"../utils":32,"./ArrayReader":17}],22:[function(r,o,a){var l=r("../utils"),p=r("../support"),_=r("./ArrayReader"),h=r("./StringReader"),g=r("./NodeBufferReader"),M=r("./Uint8ArrayReader");o.exports=function(y){var E=l.getTypeOf(y);return l.checkSupport(E),E!=="string"||p.uint8array?E==="nodebuffer"?new g(y):p.uint8array?new M(l.transformTo("uint8array",y)):new _(l.transformTo("array",y)):new h(y)}},{"../support":30,"../utils":32,"./ArrayReader":17,"./NodeBufferReader":19,"./StringReader":20,"./Uint8ArrayReader":21}],23:[function(r,o,a){a.LOCAL_FILE_HEADER="PK",a.CENTRAL_FILE_HEADER="PK",a.CENTRAL_DIRECTORY_END="PK",a.ZIP64_CENTRAL_DIRECTORY_LOCATOR="PK\x07",a.ZIP64_CENTRAL_DIRECTORY_END="PK",a.DATA_DESCRIPTOR="PK\x07\b"},{}],24:[function(r,o,a){var l=r("./GenericWorker"),p=r("../utils");function _(h){l.call(this,"ConvertWorker to "+h),this.destType=h}p.inherits(_,l),_.prototype.processChunk=function(h){this.push({data:p.transformTo(this.destType,h.data),meta:h.meta})},o.exports=_},{"../utils":32,"./GenericWorker":28}],25:[function(r,o,a){var l=r("./GenericWorker"),p=r("../crc32");function _(){l.call(this,"Crc32Probe"),this.withStreamInfo("crc32",0)}r("../utils").inherits(_,l),_.prototype.processChunk=function(h){this.streamInfo.crc32=p(h.data,this.streamInfo.crc32||0),this.push(h)},o.exports=_},{"../crc32":4,"../utils":32,"./GenericWorker":28}],26:[function(r,o,a){var l=r("../utils"),p=r("./GenericWorker");function _(h){p.call(this,"DataLengthProbe for "+h),this.propName=h,this.withStreamInfo(h,0)}l.inherits(_,p),_.prototype.processChunk=function(h){if(h){var g=this.streamInfo[this.propName]||0;this.streamInfo[this.propName]=g+h.data.length}p.prototype.processChunk.call(this,h)},o.exports=_},{"../utils":32,"./GenericWorker":28}],27:[function(r,o,a){var l=r("../utils"),p=r("./GenericWorker");function _(h){p.call(this,"DataWorker");var g=this;this.dataIsReady=!1,this.index=0,this.max=0,this.data=null,this.type="",this._tickScheduled=!1,h.then(function(M){g.dataIsReady=!0,g.data=M,g.max=M&&M.length||0,g.type=l.getTypeOf(M),g.isPaused||g._tickAndRepeat()},function(M){g.error(M)})}l.inherits(_,p),_.prototype.cleanUp=function(){p.prototype.cleanUp.call(this),this.data=null},_.prototype.resume=function(){return!!p.prototype.resume.call(this)&&(!this._tickScheduled&&this.dataIsReady&&(this._tickScheduled=!0,l.delay(this._tickAndRepeat,[],this)),!0)},_.prototype._tickAndRepeat=function(){this._tickScheduled=!1,this.isPaused||this.isFinished||(this._tick(),this.isFinished||(l.delay(this._tickAndRepeat,[],this),this._tickScheduled=!0))},_.prototype._tick=function(){if(this.isPaused||this.isFinished)return!1;var h=null,g=Math.min(this.max,this.index+16384);if(this.index>=this.max)return this.end();switch(this.type){case"string":h=this.data.substring(this.index,g);break;case"uint8array":h=this.data.subarray(this.index,g);break;case"array":case"nodebuffer":h=this.data.slice(this.index,g)}return this.index=g,this.push({data:h,meta:{percent:this.max?this.index/this.max*100:0}})},o.exports=_},{"../utils":32,"./GenericWorker":28}],28:[function(r,o,a){function l(p){this.name=p||"default",this.streamInfo={},this.generatedError=null,this.extraStreamInfo={},this.isPaused=!0,this.isFinished=!1,this.isLocked=!1,this._listeners={data:[],end:[],error:[]},this.previous=null}l.prototype={push:function(p){this.emit("data",p)},end:function(){if(this.isFinished)return!1;this.flush();try{this.emit("end"),this.cleanUp(),this.isFinished=!0}catch(p){this.emit("error",p)}return!0},error:function(p){return!this.isFinished&&(this.isPaused?this.generatedError=p:(this.isFinished=!0,this.emit("error",p),this.previous&&this.previous.error(p),this.cleanUp()),!0)},on:function(p,_){return this._listeners[p].push(_),this},cleanUp:function(){this.streamInfo=this.generatedError=this.extraStreamInfo=null,this._listeners=[]},emit:function(p,_){if(this._listeners[p])for(var h=0;h "+p:p}},o.exports=l},{}],29:[function(r,o,a){var l=r("../utils"),p=r("./ConvertWorker"),_=r("./GenericWorker"),h=r("../base64"),g=r("../support"),M=r("../external"),y=null;if(g.nodestream)try{y=r("../nodejs/NodejsStreamOutputAdapter")}catch{}function E(O,S){return new M.Promise(function(C,w){var b=[],I=O._internalType,U=O._outputType,z=O._mimeType;O.on("data",function(B,j){b.push(B),S&&S(j)}).on("error",function(B){b=[],w(B)}).on("end",function(){try{var B=function(j,N,ae){switch(j){case"blob":return l.newBlob(l.transformTo("arraybuffer",N),ae);case"base64":return h.encode(N);default:return l.transformTo(j,N)}}(U,function(j,N){var ae,ce=0,xe=null,Y=0;for(ae=0;ae"u")a.blob=!1;else{var l=new ArrayBuffer(0);try{a.blob=new Blob([l],{type:"application/zip"}).size===0}catch{try{var p=new(self.BlobBuilder||self.WebKitBlobBuilder||self.MozBlobBuilder||self.MSBlobBuilder);p.append(l),a.blob=p.getBlob("application/zip").size===0}catch{a.blob=!1}}}try{a.nodestream=!!r("readable-stream").Readable}catch{a.nodestream=!1}},{"readable-stream":16}],31:[function(r,o,a){for(var l=r("./utils"),p=r("./support"),_=r("./nodejsUtils"),h=r("./stream/GenericWorker"),g=new Array(256),M=0;M<256;M++)g[M]=252<=M?6:248<=M?5:240<=M?4:224<=M?3:192<=M?2:1;g[254]=g[254]=1;function y(){h.call(this,"utf-8 decode"),this.leftOver=null}function E(){h.call(this,"utf-8 encode")}a.utf8encode=function(T){return p.nodebuffer?_.newBufferFrom(T,"utf-8"):function(O){var S,C,w,b,I,U=O.length,z=0;for(b=0;b>>6:(C<65536?S[I++]=224|C>>>12:(S[I++]=240|C>>>18,S[I++]=128|C>>>12&63),S[I++]=128|C>>>6&63),S[I++]=128|63&C);return S}(T)},a.utf8decode=function(T){return p.nodebuffer?l.transformTo("nodebuffer",T).toString("utf-8"):function(O){var S,C,w,b,I=O.length,U=new 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w=0;w>8;this.dir=!!(16&this.externalFileAttributes),T==0&&(this.dosPermissions=63&this.externalFileAttributes),T==3&&(this.unixPermissions=this.externalFileAttributes>>16&65535),this.dir||this.fileNameStr.slice(-1)!=="/"||(this.dir=!0)},parseZIP64ExtraField:function(){if(this.extraFields[1]){var T=l(this.extraFields[1].value);this.uncompressedSize===p.MAX_VALUE_32BITS&&(this.uncompressedSize=T.readInt(8)),this.compressedSize===p.MAX_VALUE_32BITS&&(this.compressedSize=T.readInt(8)),this.localHeaderOffset===p.MAX_VALUE_32BITS&&(this.localHeaderOffset=T.readInt(8)),this.diskNumberStart===p.MAX_VALUE_32BITS&&(this.diskNumberStart=T.readInt(4))}},readExtraFields:function(T){var O,S,C,w=T.index+this.extraFieldsLength;for(this.extraFields||(this.extraFields={});T.index+4>>6:(T<65536?E[C++]=224|T>>>12:(E[C++]=240|T>>>18,E[C++]=128|T>>>12&63),E[C++]=128|T>>>6&63),E[C++]=128|63&T);return E},a.buf2binstring=function(y){return M(y,y.length)},a.binstring2buf=function(y){for(var E=new 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Pe,se,re=A.max_chain_length,ye=A.strstart,R=A.prev_length,ee=A.nice_match,D=A.strstart>A.w_size-xe?A.strstart-(A.w_size-xe):0,ue=A.window,le=A.w_mask,ke=A.prev,Ne=A.strstart+ce,dt=ue[ye+R-1],Je=ue[ye+R];A.prev_length>=A.good_match&&(re>>=2),ee>A.lookahead&&(ee=A.lookahead);do if(ue[(Pe=$e)+R]===Je&&ue[Pe+R-1]===dt&&ue[Pe]===ue[ye]&&ue[++Pe]===ue[ye+1]){ye+=2,Pe++;do;while(ue[++ye]===ue[++Pe]&&ue[++ye]===ue[++Pe]&&ue[++ye]===ue[++Pe]&&ue[++ye]===ue[++Pe]&&ue[++ye]===ue[++Pe]&&ue[++ye]===ue[++Pe]&&ue[++ye]===ue[++Pe]&&ue[++ye]===ue[++Pe]&&yeD&&--re!=0);return R<=A.lookahead?R:A.lookahead}function We(A){var $e,Pe,se,re,ye,R,ee,D,ue,le,ke=A.w_size;do{if(re=A.window_size-A.lookahead-A.strstart,A.strstart>=ke+(ke-xe)){for(p.arraySet(A.window,A.window,ke,ke,0),A.match_start-=ke,A.strstart-=ke,A.block_start-=ke,$e=Pe=A.hash_size;se=A.head[--$e],A.head[$e]=ke<=se?se-ke:0,--Pe;);for($e=Pe=ke;se=A.prev[--$e],A.prev[$e]=ke<=se?se-ke:0,--Pe;);re+=ke}if(A.strm.avail_in===0)break;if(R=A.strm,ee=A.window,D=A.strstart+A.lookahead,ue=re,le=void 0,le=R.avail_in,ue=ae)for(ye=A.strstart-A.insert,A.ins_h=A.window[ye],A.ins_h=(A.ins_h<=ae&&(A.ins_h=(A.ins_h<=ae)if(se=_._tr_tally(A,A.strstart-A.match_start,A.match_length-ae),A.lookahead-=A.match_length,A.match_length<=A.max_lazy_match&&A.lookahead>=ae){for(A.match_length--;A.strstart++,A.ins_h=(A.ins_h<=ae&&(A.ins_h=(A.ins_h<=ae&&A.match_length<=A.prev_length){for(re=A.strstart+A.lookahead-ae,se=_._tr_tally(A,A.strstart-1-A.prev_match,A.prev_length-ae),A.lookahead-=A.prev_length-1,A.prev_length-=2;++A.strstart<=re&&(A.ins_h=(A.ins_h<A.pending_buf_size-5&&(Pe=A.pending_buf_size-5);;){if(A.lookahead<=1){if(We(A),A.lookahead===0&&$e===y)return L;if(A.lookahead===0)break}A.strstart+=A.lookahead,A.lookahead=0;var se=A.block_start+Pe;if((A.strstart===0||A.strstart>=se)&&(A.lookahead=A.strstart-se,A.strstart=se,ge(A,!1),A.strm.avail_out===0)||A.strstart-A.block_start>=A.w_size-xe&&(ge(A,!1),A.strm.avail_out===0))return L}return A.insert=0,$e===E?(ge(A,!0),A.strm.avail_out===0?Xe:me):(A.strstart>A.block_start&&(ge(A,!1),A.strm.avail_out),L)}),new Ge(4,4,8,4,st),new Ge(4,5,16,8,st),new Ge(4,6,32,32,st),new Ge(4,4,16,16,pt),new Ge(8,16,32,32,pt),new Ge(8,16,128,128,pt),new Ge(8,32,128,256,pt),new Ge(32,128,258,1024,pt),new Ge(32,258,258,4096,pt)],a.deflateInit=function(A,$e){return et(A,$e,b,15,8,0)},a.deflateInit2=et,a.deflateReset=Ye,a.deflateResetKeep=je,a.deflateSetHeader=function(A,$e){return A&&A.state?A.state.wrap!==2?O:(A.state.gzhead=$e,T):O},a.deflate=function(A,$e){var Pe,se,re,ye;if(!A||!A.state||5<$e||$e<0)return A?X(A,O):O;if(se=A.state,!A.output||!A.input&&A.avail_in!==0||se.status===666&&$e!==E)return X(A,A.avail_out===0?-5:O);if(se.strm=A,Pe=se.last_flush,se.last_flush=$e,se.status===Y)if(se.wrap===2)A.adler=0,Ke(se,31),Ke(se,139),Ke(se,8),se.gzhead?(Ke(se,(se.gzhead.text?1:0)+(se.gzhead.hcrc?2:0)+(se.gzhead.extra?4:0)+(se.gzhead.name?8:0)+(se.gzhead.comment?16:0)),Ke(se,255&se.gzhead.time),Ke(se,se.gzhead.time>>8&255),Ke(se,se.gzhead.time>>16&255),Ke(se,se.gzhead.time>>24&255),Ke(se,se.level===9?2:2<=se.strategy||se.level<2?4:0),Ke(se,255&se.gzhead.os),se.gzhead.extra&&se.gzhead.extra.length&&(Ke(se,255&se.gzhead.extra.length),Ke(se,se.gzhead.extra.length>>8&255)),se.gzhead.hcrc&&(A.adler=g(A.adler,se.pending_buf,se.pending,0)),se.gzindex=0,se.status=69):(Ke(se,0),Ke(se,0),Ke(se,0),Ke(se,0),Ke(se,0),Ke(se,se.level===9?2:2<=se.strategy||se.level<2?4:0),Ke(se,3),se.status=_e);else{var R=b+(se.w_bits-8<<4)<<8;R|=(2<=se.strategy||se.level<2?0:se.level<6?1:se.level===6?2:3)<<6,se.strstart!==0&&(R|=32),R+=31-R%31,se.status=_e,Le(se,R),se.strstart!==0&&(Le(se,A.adler>>>16),Le(se,65535&A.adler)),A.adler=1}if(se.status===69)if(se.gzhead.extra){for(re=se.pending;se.gzindex<(65535&se.gzhead.extra.length)&&(se.pending!==se.pending_buf_size||(se.gzhead.hcrc&&se.pending>re&&(A.adler=g(A.adler,se.pending_buf,se.pending-re,re)),Q(A),re=se.pending,se.pending!==se.pending_buf_size));)Ke(se,255&se.gzhead.extra[se.gzindex]),se.gzindex++;se.gzhead.hcrc&&se.pending>re&&(A.adler=g(A.adler,se.pending_buf,se.pending-re,re)),se.gzindex===se.gzhead.extra.length&&(se.gzindex=0,se.status=73)}else se.status=73;if(se.status===73)if(se.gzhead.name){re=se.pending;do{if(se.pending===se.pending_buf_size&&(se.gzhead.hcrc&&se.pending>re&&(A.adler=g(A.adler,se.pending_buf,se.pending-re,re)),Q(A),re=se.pending,se.pending===se.pending_buf_size)){ye=1;break}ye=se.gzindexre&&(A.adler=g(A.adler,se.pending_buf,se.pending-re,re)),ye===0&&(se.gzindex=0,se.status=91)}else se.status=91;if(se.status===91)if(se.gzhead.comment){re=se.pending;do{if(se.pending===se.pending_buf_size&&(se.gzhead.hcrc&&se.pending>re&&(A.adler=g(A.adler,se.pending_buf,se.pending-re,re)),Q(A),re=se.pending,se.pending===se.pending_buf_size)){ye=1;break}ye=se.gzindexre&&(A.adler=g(A.adler,se.pending_buf,se.pending-re,re)),ye===0&&(se.status=103)}else se.status=103;if(se.status===103&&(se.gzhead.hcrc?(se.pending+2>se.pending_buf_size&&Q(A),se.pending+2<=se.pending_buf_size&&(Ke(se,255&A.adler),Ke(se,A.adler>>8&255),A.adler=0,se.status=_e)):se.status=_e),se.pending!==0){if(Q(A),A.avail_out===0)return se.last_flush=-1,T}else if(A.avail_in===0&&ie($e)<=ie(Pe)&&$e!==E)return X(A,-5);if(se.status===666&&A.avail_in!==0)return X(A,-5);if(A.avail_in!==0||se.lookahead!==0||$e!==y&&se.status!==666){var ee=se.strategy===2?function(D,ue){for(var le;;){if(D.lookahead===0&&(We(D),D.lookahead===0)){if(ue===y)return L;break}if(D.match_length=0,le=_._tr_tally(D,0,D.window[D.strstart]),D.lookahead--,D.strstart++,le&&(ge(D,!1),D.strm.avail_out===0))return L}return D.insert=0,ue===E?(ge(D,!0),D.strm.avail_out===0?Xe:me):D.last_lit&&(ge(D,!1),D.strm.avail_out===0)?L:Se}(se,$e):se.strategy===3?function(D,ue){for(var le,ke,Ne,dt,Je=D.window;;){if(D.lookahead<=ce){if(We(D),D.lookahead<=ce&&ue===y)return L;if(D.lookahead===0)break}if(D.match_length=0,D.lookahead>=ae&&0D.lookahead&&(D.match_length=D.lookahead)}if(D.match_length>=ae?(le=_._tr_tally(D,1,D.match_length-ae),D.lookahead-=D.match_length,D.strstart+=D.match_length,D.match_length=0):(le=_._tr_tally(D,0,D.window[D.strstart]),D.lookahead--,D.strstart++),le&&(ge(D,!1),D.strm.avail_out===0))return L}return D.insert=0,ue===E?(ge(D,!0),D.strm.avail_out===0?Xe:me):D.last_lit&&(ge(D,!1),D.strm.avail_out===0)?L:Se}(se,$e):l[se.level].func(se,$e);if(ee!==Xe&&ee!==me||(se.status=666),ee===L||ee===Xe)return A.avail_out===0&&(se.last_flush=-1),T;if(ee===Se&&($e===1?_._tr_align(se):$e!==5&&(_._tr_stored_block(se,0,0,!1),$e===3&&(Me(se.head),se.lookahead===0&&(se.strstart=0,se.block_start=0,se.insert=0))),Q(A),A.avail_out===0))return se.last_flush=-1,T}return $e!==E?T:se.wrap<=0?1:(se.wrap===2?(Ke(se,255&A.adler),Ke(se,A.adler>>8&255),Ke(se,A.adler>>16&255),Ke(se,A.adler>>24&255),Ke(se,255&A.total_in),Ke(se,A.total_in>>8&255),Ke(se,A.total_in>>16&255),Ke(se,A.total_in>>24&255)):(Le(se,A.adler>>>16),Le(se,65535&A.adler)),Q(A),0=Pe.w_size&&(ye===0&&(Me(Pe.head),Pe.strstart=0,Pe.block_start=0,Pe.insert=0),ue=new p.Buf8(Pe.w_size),p.arraySet(ue,$e,le-Pe.w_size,Pe.w_size,0),$e=ue,le=Pe.w_size),R=A.avail_in,ee=A.next_in,D=A.input,A.avail_in=le,A.next_in=0,A.input=$e,We(Pe);Pe.lookahead>=ae;){for(se=Pe.strstart,re=Pe.lookahead-(ae-1);Pe.ins_h=(Pe.ins_h<>>=ae=N>>>24,I-=ae,(ae=N>>>16&255)===0)Se[M++]=65535&N;else{if(!(16&ae)){if(!(64&ae)){N=U[(65535&N)+(b&(1<>>=ae,I-=ae),I<15&&(b+=L[h++]<>>=ae=N>>>24,I-=ae,!(16&(ae=N>>>16&255))){if(!(64&ae)){N=z[(65535&N)+(b&(1<>>=ae,I-=ae,(ae=M-y)>3,b&=(1<<(I-=ce<<3))-1,l.next_in=h,l.next_out=M,l.avail_in=h>>24&255)+(Y>>>8&65280)+((65280&Y)<<8)+((255&Y)<<24)}function 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