Impressum ort.webgpu.mjs   Sprache: unbekannt

/*!
 * ONNX Runtime Web v1.20.1
 * Copyright (c) Microsoft Corporation. All rights reserved.
 * Licensed under the MIT License.
 */
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(this.isDownloading)throw new Error("The current tensor is being downloaded.");try{this.isDownloading=!0;let n=await this.downloader();return this.downloader=void 0,this.dataLocation="cpu",this.cpuData=n,t&&this.disposer&&(this.disposer(),this.disposer=void 0),n}finally{this.isDownloading=!1}}default:throw new Error(`cannot get data from location: ${this.dataLocation}`)}}dispose(){if(this.isDownloading)throw new Error("The current tensor is being downloaded.");this.disposer&&(this.disposer(),this.disposer=void 0),this.cpuData=void 0,this.gpuTextureData=void 0,this.gpuBufferData=void 0,this.mlTensorData=void 0,this.downloader=void 0,this.isDownloading=void 0,this.dataLocation="none"}ensureValid(){if(this.dataLocation==="none")throw new Error("The tensor is disposed.")}reshape(t){if(this.ensureValid(),this.downloader||this.disposer)throw new Error("Cannot reshape a tensor that owns GPU resource.");return Cr(this,t)}}});var me,xt=k(()=>{"use strict";vt();me=pe});var St,kr,_e,ye,_n=k(()=>{"use strict";bn();St=(e,t)=>{(typeof we.trace>"u"?!we.wasm.trace:!we.trace)||console.timeStamp(`${e}::ORT::${t}`)},kr=(e,t)=>{let n=new Error().stack?.split(/\r\n|\r|\n/g)||[],r=!1;for(let o=0;o<n.length;o++){if(r&&!n[o].includes("TRACE_FUNC")){let i=`FUNC_${e}::${n[o].trim().split(" ")[1]}`;t&&(i+=`::${t}`),St("CPU",i);return}n[o].includes("TRACE_FUNC")&&(r=!0)}},_e=e=>{(typeof we.trace>"u"?!we.wasm.trace:!we.trace)||kr("BEGIN",e)},ye=e=>{(typeof we.trace>"u"?!we.wasm.trace:!we.trace)||kr("END",e)}});var It,Er=k(()=>{"use strict";$t();xt();_n();It=class e{constructor(t){this.handler=t}async run(t,n,r){_e();let o={},i={};if(typeof t!="object"||t===null||t instanceof me||Array.isArray(t))throw new TypeError("'feeds' must be an object that use input names as keys and OnnxValue as corresponding values.");let s=!0;if(typeof n=="object"){if(n===null)throw new TypeError("Unexpected argument[1]: cannot be null.");if(n instanceof me)throw new TypeError("'fetches' cannot be a Tensor");if(Array.isArray(n)){if(n.length===0)throw new TypeError("'fetches' cannot be an empty array.");s=!1;for(let d of n){if(typeof d!="string")throw new TypeError("'fetches' must be a string array or an object.");if(this.outputNames.indexOf(d)===-1)throw new RangeError(`'fetches' contains invalid output name: ${d}.`);o[d]=null}if(typeof r=="object"&&r!==null)i=r;else if(typeof r<"u")throw new TypeError("'options' must be an object.")}else{let d=!1,l=Object.getOwnPropertyNames(n);for(let c of this.outputNames)if(l.indexOf(c)!==-1){let p=n[c];(p===null||p instanceof me)&&(d=!0,s=!1,o[c]=p)}if(d){if(typeof r=="object"&&r!==null)i=r;else if(typeof r<"u")throw new TypeError("'options' must be an object.")}else i=n}}else if(typeof n<"u")throw new TypeError("Unexpected argument[1]: must be 'fetches' or 'options'.");for(let d of this.inputNames)if(typeof t[d]>"u")throw new Error(`input '${d}' is missing in 'feeds'.`);if(s)for(let d of this.outputNames)o[d]=null;let a=await this.handler.run(t,o,i),u={};for(let d in a)if(Object.hasOwnProperty.call(a,d)){let l=a[d];l instanceof me?u[d]=l:u[d]=new me(l.type,l.data,l.dims)}return ye(),u}async release(){return this.handler.dispose()}static async create(t,n,r,o){_e();let i,s={};if(typeof t=="string"){if(i=t,typeof n=="object"&&n!==null)s=n;else if(typeof n<"u")throw new TypeError("'options' must be an object.")}else if(t instanceof Uint8Array){if(i=t,typeof n=="object"&&n!==null)s=n;else if(typeof n<"u")throw new TypeError("'options' must be an object.")}else if(t instanceof ArrayBuffer||typeof SharedArrayBuffer<"u"&&t instanceof SharedArrayBuffer){let l=t,c=0,p=t.byteLength;if(typeof n=="object"&&n!==null)s=n;else if(typeof n=="number"){if(c=n,!Number.isSafeInteger(c))throw new RangeError("'byteOffset' must be an integer.");if(c<0||c>=l.byteLength)throw new RangeError(`'byteOffset' is out of range [0, ${l.byteLength}).`);if(p=t.byteLength-c,typeof r=="number"){if(p=r,!Number.isSafeInteger(p))throw new RangeError("'byteLength' must be an integer.");if(p<=0||c+p>l.byteLength)throw new RangeError(`'byteLength' is out of range (0, ${l.byteLength-c}].`);if(typeof o=="object"&&o!==null)s=o;else if(typeof o<"u")throw new TypeError("'options' must be an object.")}else if(typeof r<"u")throw new TypeError("'byteLength' must be a number.")}else if(typeof n<"u")throw new TypeError("'options' must be an object.");i=new Uint8Array(l,c,p)}else throw new TypeError("Unexpected argument[0]: must be 'path' or 'buffer'.");let[a,u]=await _t(s),d=await a.createInferenceSessionHandler(i,u);return ye(),new e(d)}startProfiling(){this.handler.startProfiling()}endProfiling(){this.handler.endProfiling()}get inputNames(){return this.handler.inputNames}get outputNames(){return this.handler.outputNames}}});var $u,Pr=k(()=>{"use strict";Er();$u=It});var zr=k(()=>{"use strict"});var Br=k(()=>{"use strict"});var Dr=k(()=>{"use strict"});var Or=k(()=>{"use strict"});var vu,Tt,Rr=k(()=>{"use strict";$t();xt();vu="Training backend could not be resolved. Make 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 t<0?t+n:t}static normalizeAxes(t,n){return t.map(r=>this.normalizeAxis(r,n??t.length))}static sortBasedOnPerm(t,n){return n?n.map(r=>t[r]):t.slice().reverse()}static padShape(t,n){let r=t.length;return t.map((o,i)=>o+n[i]+n[i+r])}static areEqual(t,n){return t.length!==n.length?!1:t.every((r,o)=>r===n[o])}},Ke=class e{static adjustPoolAttributes(t,n,r,o,i,s){if(!t&&r.length!==n.length-2)throw new Error("length of specified kernel shapes should be 2 less than length of input dimensions");if(t)for(let a=0;a<n.length-2;a++)a>=r.length?r.push(n[a+2]):r[a]=n[a+2];for(let a=0;a<r.length;a++)if(a<o.length){if(o[a]<0)throw new Error("strides should be greater than or equal to 1")}else o.push(1);for(let a=0;a<r.length;a++)if(a<i.length){if(i[a]<0)throw new Error("dilations should be greater than or equal to 1")}else i.push(1);for(let a=0;a<r.length*2;a++)if(a<s.length){if(s[a]<0)throw new Error("pad should be greater than or equal to 1")}else s.push(0);for(let a=0;a<r.length;a++){if(r[a]<=0)throw new Error("kernel shapes need to be greater than 0");if(s[a]>=r[a]||s[a+r.length]>=r[a])throw new Error("pads should be smaller than kernel")}}static adjustPadsBasedOnAutoPad(t,n,r,o,i,s,a){if(a){if(i.length!==2*(t.length-2))throw new Error("length of pads should be twice the length of data dimensions");if(n.length!==t.length-2)throw new Error("length of strides should be the length of data dimensions");if(o.length!==t.length-2)throw new Error("length of kernel shapes should be the length of data dimensions");for(let u=0;u<t.length-2;u++)e.adjustPadAndReturnShape(t[u+(s?1:2)],n[u],r[u],o[u],i,u,u+t.length-2,a)}}static computePoolOutputShape(t,n,r,o,i,s,a){if(n.length<=0)throw new Error("input shape must be of size greater than 0");let u=[n[0],n[1]];return e.computeShapeHelper(t,n,u,r,o,i,s,a),u}static computeConvOutputShape(t,n,r,o,i,s,a){if(t.length<=0||n.length<=0)throw new Error("invalid input tensor dims or invalid filter tensor dims");let u=[t[0],n[0]];return e.computeShapeHelper(!1,t,u,r,o,i,s,a),u}static computeShapeHelper(t,n,r,o,i,s,a,u){if(t)for(let d=0;d<n.length-2;d++)r.push(1);else for(let d=0;d<n.length-2;d++)r.push(e.adjustPadAndReturnShape(n[d+2],o[d],i[d],s[d],a,d,d+n.length-2,u))}static adjustPadAndReturnShape(t,n,r,o,i,s,a,u){let d=r*(o-1)+1;if(u&&u!=="NOTSET")switch(u){case"VALID":return i[s]=0,i[a]=0,Math.floor((t-d)/n+1);case"SAME_LOWER":case"SAME_UPPER":if(r!==1)throw new Error("Dilation not supported for SAME_UPPER or SAME_LOWER");{let c=((t+n-1)/n-1)*n+o-t;return i[s]=Math.floor(u==="SAME_LOWER"?(c+1)/2:c/2),i[a]=c-i[s],Math.floor((t+c-o)/n+1)}default:throw new Error("Unsupported AutoPad type")}else return Math.floor((t+i[s]+i[a]-d)/n+1)}},Ht=class{static getShapeOfGemmResult(t,n,r,o,i){if(t.length!==2||r.length!==2)throw new Error("shape need to be of size 2");let s,a,u;n?(s=t[1],a=t[0]):(s=t[0],a=t[1]);let d=-1;if(o?(u=r[0],d=1):(u=r[1],d=0),r[d]!==a)throw new Error("dimension mismatch");if(s<=0||u<=0||a<=0)throw new Error("invalid shape specified");if(i&&!Ee.isValidBroadcast(i,[s,u]))throw new Error("gemm: invalid bias shape for broadcast");return[s,u,a]}},so=-34028234663852886e22,ao=34028234663852886e22});var je,On,Y,de,A,te,Rn,Xe,ke,B,Mn,S,C,qt,Dn,uo,Ye,W=k(()=>{"use strict";U();N();je=64,On=(e,t)=>{if(t===3)throw new Error("vec3 has same alignment as vec4, use vec4 instead");switch(e){case 10:return t>1?`vec${t}<f16>`:"f16";case 1:return t>1?`vec${t}<f32>`:"f32";case 6:return t>1?`vec${t}<i32>`:"i32";case 12:return t>1?`vec${t}<u32>`:"u32";case 7:if(t>1)throw new Error("currently not supported vecX of uint64 yet");return["vec2<u32>","i32"];case 13:if(t>1)throw new Error("currently not supported vecX of uint64 yet");return["vec2<u32>","u32"];case 9:if(t!==4)throw new Error("bool must be vec4");return["u32","vec4<bool>"];case 22:return"i32";case 21:return"u32";default:throw new Error(`Unknown data type: ${e}`)}},Y=(e,t=1)=>{let n=On(e,t);return typeof n=="string"?n:n[0]},de=(e,t=1)=>{let n=On(e,t);return typeof n=="string"?n:n[1]},A=(...e)=>{let t=[];return e.forEach(n=>{n.length!==0&&t.push({type:12,data:n},{type:12,data:x.computeStrides(n)})}),t},te=e=>e%4===0?4:e%2===0?2:1,Rn=(e="f32",t,n="0")=>!t||t===1?`${e}(${n})`:`vec${t}<${e}>(${n})`,Xe=(e,t,n)=>e==="f32"?n:t===1?`f32(${n})`:`vec${t}<f32>(${n})`,ke=(e,t)=>t===4?`(${e}.x + ${e}.y + ${e}.z + ${e}.w)`:t===2?`(${e}.x + ${e}.y)`:t===3?`(${e}.x + ${e}.y + ${e}.z)`:e,B=(e,t,n,r)=>e.startsWith("uniforms.")&&n>4?typeof t=="string"?r==="f16"?`${e}[(${t}) / 8][(${t}) % 8 / 4][(${t}) % 8 % 4]`:`${e}[(${t}) / 4][(${t}) % 4]`:r==="f16"?`${e}[${Math.floor(t/8)}][${Math.floor(t%8/4)}][${t%8%4}]`:`${e}[${Math.floor(t/4)}][${t%4}]`:n>1?`${e}[${t}]`:e,Mn=(e,t,n,r,o)=>{let i=typeof n=="number",s=i?n:n.length,a=[...new Array(s).keys()],u=s<2?"u32":s<=4?`vec${s}<u32>`:`array<u32, ${s}>`,d=On(t,o),l=typeof d=="string"?d:d[1],c=typeof d=="string"?d:d[0],p={indices:u,value:l,storage:c,tensor:t},h=E=>typeof E=="string"?E:`${E}u`,m={offsetToIndices:!1,indicesToOffset:!1,broadcastedIndicesToOffset:!1,set:!1,setByIndices:!1,get:!1,getByIndices:!1},f=i?"uniforms.":"",w=`${f}${e}_shape`,y=`${f}${e}_strides`,g="";for(let E=0;E<s-1;E++)g+=`
    let dim${E} = current / ${B(y,E,s)};
    let rest${E} = current % ${B(y,E,s)};
    indices[${E}] = dim${E};
    current = rest${E};
    `;g+=`indices[${s-1}] = current;`;let b=s<2?"":`
  fn o2i_${e}(offset: u32) -> ${p.indices} {
    var indices: ${p.indices};
    var current = offset;
    ${g}
    return indices;
  }`,_=E=>(m.offsetToIndices=!0,s<2?E:`o2i_${e}(${E})`),$=[];if(s>=2)for(let E=s-1;E>=0;E--)$.push(`${B(y,E,s)} * (indices[${E}])`);let v=s<2?"":`
  fn i2o_${e}(indices: ${p.indices}) -> u32 {
    return ${$.join("+")};
  }`,I=E=>(m.indicesToOffset=!0,s<2?E:`i2o_${e}(${E})`),T=(...E)=>s===0?"0u":`${p.indices}(${E.map(h).join(",")})`,P=(E,D)=>s<2?`${E}`:`${B(E,D,s)}`,z=(E,D,ne)=>s<2?`${E}=${ne};`:`${B(E,D,s)}=${ne};`,R={},Z=(E,D)=>{m.broadcastedIndicesToOffset=!0;let ne=`${D.name}broadcastedIndicesTo${e}Offset`;if(ne in R)return`${ne}(${E})`;let Ce=[];for(let fe=s-1;fe>=0;fe--){let Re=D.indicesGet("outputIndices",fe+D.rank-s);Ce.push(`${P(y,fe)} * (${Re} % ${P(w,fe)})`)}return R[ne]=`fn ${ne}(outputIndices: ${D.type.indices}) -> u32 {
             return ${Ce.length>0?Ce.join("+"):"0u"};
           }`,`${ne}(${E})`},G=(E,D)=>(()=>{if(p.storage===p.value)return`${e}[${E}]=${D};`;if(p.storage==="vec2<u32>"&&p.value==="i32")return`${e}[${E}]=vec2<u32>(u32(${D}), select(0u, 0xFFFFFFFFu, ${D} < 0));`;if(p.storage==="vec2<u32>"&&p.value==="u32")return`${e}[${E}]=vec2<u32>(u32(${D}), 0u);`;if(p.storage==="u32"&&p.value==="vec4<bool>")return`${e}[${E}]=dot(vec4<u32>(0x1, 0x100, 0x10000, 0x1000000), vec4<u32>(${D}));`;throw new Error(`not supported combination of storage type ${p.storage} and value type ${p.value} yet`)})(),K=E=>(()=>{if(p.storage===p.value)return`${e}[${E}]`;if(p.storage==="vec2<u32>"&&p.value==="i32")return`i32(${e}[${E}].x)`;if(p.storage==="vec2<u32>"&&p.value==="u32")return`u32(${e}[${E}].x)`;if(p.storage==="u32"&&p.value==="vec4<bool>")return`vec4<bool>(bool(${e}[${E}] & 0xFFu), bool(${e}[${E}] & 0xFF00u), bool(${e}[${E}] & 0xFF0000u), bool(${e}[${E}] & 0xFF000000u))`;throw new Error(`not supported combination of storage type ${p.storage} and value type ${p.value} yet`)})(),ie=s<2?"":`
  fn get_${e}ByIndices(indices: ${p.indices}) -> ${l} {
    return ${K(`i2o_${e}(indices)`)};
  }`,M=s<2?"":(()=>{let E=a.map(ne=>`d${ne}: u32`).join(", "),D=a.map(ne=>`d${ne}`).join(", ");return`
  fn get_${e}(${E}) -> ${l} {
    return get_${e}ByIndices(${T(D)});
  }`})(),Q=(...E)=>{if(E.length!==s)throw new Error(`indices length must be ${s}`);let D=E.map(h).join(",");return s===0?K("0u"):s===1?K(D[0]):(m.get=!0,m.getByIndices=!0,m.indicesToOffset=!0,`get_${e}(${D})`)},re=E=>s<2?K(E):(m.getByIndices=!0,m.indicesToOffset=!0,`get_${e}ByIndices(${E})`),O=s<2?"":`
  fn set_${e}ByIndices(indices: ${p.indices}, value: ${l}) {
    ${G(`i2o_${e}(indices)`,"value")}
  }`,j=s<2?"":(()=>{let E=a.map(ne=>`d${ne}: u32`).join(", "),D=a.map(ne=>`d${ne}`).join(", ");return`
  fn set_${e}(${E}, value: ${l}) {
    set_${e}ByIndices(${T(D)}, value);
  }`})();return{impl:()=>{let E=[],D=!1;return m.offsetToIndices&&(E.push(b),D=!0),m.indicesToOffset&&(E.push(v),D=!0),m.broadcastedIndicesToOffset&&(Object.values(R).forEach(ne=>E.push(ne)),D=!0),m.set&&(E.push(j),D=!0),m.setByIndices&&(E.push(O),D=!0),m.get&&(E.push(M),D=!0),m.getByIndices&&(E.push(ie),D=!0),!i&&D&&E.unshift(`const ${w} = ${p.indices}(${n.join(",")});`,`const ${y} = ${p.indices}(${x.computeStrides(n).join(",")});`),E.join(`
`)},type:p,offsetToIndices:_,indicesToOffset:I,broadcastedIndicesToOffset:Z,indices:T,indicesGet:P,indicesSet:z,set:(...E)=>{if(E.length!==s+1)throw new Error(`indices length must be ${s}`);let D=E[s];if(typeof D!="string")throw new Error("value must be string");let ne=E.slice(0,s).map(h).join(",");return s===0?G("0u",D):s===1?G(ne[0],D):(m.set=!0,m.setByIndices=!0,m.indicesToOffset=!0,`set_${e}(${ne}, ${D})`)},setByOffset:G,setByIndices:(E,D)=>s<2?G(E,D):(m.setByIndices=!0,m.indicesToOffset=!0,`set_${e}ByIndices(${E}, ${D});`),get:Q,getByOffset:K,getByIndices:re,usage:r,name:e,strides:y,shape:w,rank:s}},S=(e,t,n,r=1)=>Mn(e,t,n,"input",r),C=(e,t,n,r=1)=>Mn(e,t,n,"output",r),qt=(e,t,n,r=1)=>Mn(e,t,n,"internal",r),Dn=class{constructor(t,n){this.normalizedDispatchGroup=t;this.limits=n;this.internalVariables=[];this.variables=[];this.uniforms=[];this.variableIndex=0}guardAgainstOutOfBoundsWorkgroupSizes(t){return`if (global_idx >= ${typeof t=="number"?`${t}u`:t}) { return; }`}mainStart(t=je){let n=typeof t=="number"?t:t[0],r=typeof t=="number"?1:t[1],o=typeof t=="number"?1:t[2];if(n>this.limits.maxComputeWorkgroupSizeX||r>this.limits.maxComputeWorkgroupSizeY||o>this.limits.maxComputeWorkgroupSizeZ)throw new Error(`workgroup size [${n}, ${r}, ${o}] exceeds the maximum workgroup size [${this.limits.maxComputeWorkgroupSizeX}, ${this.limits.maxComputeWorkgroupSizeY}, ${this.limits.maxComputeWorkgroupSizeZ}].`);if(n*r*o>this.limits.maxComputeInvocationsPerWorkgroup)throw new Error(`workgroup size [${n}, ${r}, ${o}] exceeds the maximum workgroup invocations ${this.limits.maxComputeInvocationsPerWorkgroup}.`);let i=this.normalizedDispatchGroup[1]===1&&this.normalizedDispatchGroup[2]===1,s=i?`@builtin(global_invocation_id) global_id : vec3<u32>,
    @builtin(workgroup_id) workgroup_id : vec3<u32>,
    @builtin(local_invocation_index) local_idx : u32,
    @builtin(local_invocation_id) local_id : vec3<u32>`:`@builtin(global_invocation_id) global_id : vec3<u32>,
                                             @builtin(local_invocation_id) local_id : vec3<u32>,
    @builtin(local_invocation_index) local_idx : u32,
    @builtin(workgroup_id) workgroup_id : vec3<u32>,
    @builtin(num_workgroups) num_workgroups : vec3<u32>`,a=i?`let global_idx = global_id.x;
         let workgroup_index = workgroup_id.x;`:`let workgroup_index = workgroup_id.z * num_workgroups[0] * num_workgroups[1] +
             workgroup_id.y * num_workgroups[0] + workgroup_id.x;
         let global_idx = workgroup_index * ${n*r*o}u + local_idx;`;return`@compute @workgroup_size(${n}, ${r}, ${o})
  fn main(${s}) {
    ${a}
  `}appendVariableUniforms(t){t.rank!==0&&(t.shape.startsWith("uniforms.")&&this.uniforms.push({name:t.shape.replace("uniforms.",""),type:"u32",length:t.rank}),t.strides.startsWith("uniforms.")&&this.uniforms.push({name:t.strides.replace("uniforms.",""),type:"u32",length:t.rank}))}declareVariable(t,n){if(t.usage==="internal")throw new Error("cannot use internal variable with declareVariable(). use registerInternalVariables() instead.");this.variables.push(t),this.appendVariableUniforms(t);let r=t.usage==="input"?"read":"read_write",o=t.type.storage;return`@group(0) @binding(${n}) var<storage, ${r}> ${t.name}: array<${o}>;`}declareVariables(...t){return t.map(n=>this.declareVariable(n,this.variableIndex++)).join(`
`)}registerInternalVariable(t){if(t.usage!=="internal")throw new Error("cannot use input or output variable with registerInternalVariable(). use declareVariables() instead.");this.internalVariables.push(t),this.appendVariableUniforms(t)}registerInternalVariables(...t){return t.forEach(n=>this.registerInternalVariable(n)),this}registerUniform(t,n,r=1){return this.uniforms.push({name:t,type:n,length:r}),this}registerUniforms(t){return this.uniforms=this.uniforms.concat(t),this}uniformDeclaration(){if(this.uniforms.length===0)return"";let t=[];for(let{name:n,type:r,length:o}of this.uniforms)if(o&&o>4)r==="f16"?t.push(`@align(16) ${n}:array<mat2x4<${r}>, ${Math.ceil(o/8)}>`):t.push(`${n}:array<vec4<${r}>, ${Math.ceil(o/4)}>`);else{let i=o==null||o===1?r:`vec${o}<${r}>`;t.push(`${n}:${i}`)}return`
      struct Uniforms { ${t.join(", ")} };
      @group(0) @binding(${this.variableIndex}) var<uniform> uniforms: Uniforms;`}get additionalImplementations(){return this.uniformDeclaration()+this.variables.map(t=>t.impl()).join(`
`)+this.internalVariables.map(t=>t.impl()).join(`
`)}get variablesInfo(){if(this.uniforms.length===0)return;let t=n=>[12,10,1,6][["u32","f16","f32","i32"].indexOf(n)];return this.uniforms.map(n=>[t(n.type),n.length??1])}},uo=(e,t)=>new Dn(e,t),Ye=(e,t)=>{let n=e.length,r=[];for(let o=0;o<n;o++){let i=n-1-o,s=e[i]||1;(t[t.length-1-o]||1)>1&&s===1&&r.unshift(i)}return r}});var Lu,lo,Nu,Wu,Gu,le,co,po,Me=k(()=>{"use strict";U();N();ae();W();Lu=e=>{if(!e||e.length!==1)throw new Error("Transpose requires 1 input.")},lo=(e,t)=>t&&t.length!==e?[...new Array(e).keys()].reverse():t,Nu=(e,t)=>x.sortBasedOnPerm(e,lo(e.length,t)),Wu=(e,t,n,r)=>{let o=`fn perm(i: ${r.type.indices}) -> ${n.type.indices} {
    var a: ${n.type.indices};`;for(let i=0;i<t;++i)o+=n.indicesSet("a",e[i],`i[${i}]`);return o+="return a;}"},Gu=(e,t)=>{let n=[],r=[];for(let o=0;o<e.length;++o)e[o]!==1&&n.push(e[o]),e[t[o]]!==1&&r.push(t[o]);return{newShape:n,newPerm:r}},le=(e,t)=>{let n=e.dataType,r=e.dims.length,o=lo(r,t),i=Nu(e.dims,o),{newShape:s,newPerm:a}=Gu(e.dims,o),u=x.areEqual(a,[2,3,1]),d=x.areEqual(a,[3,1,2]),l=s.length===2&&a[0]>a[1]||u||d,c=l?s:e.dims,p=i;l&&(c=u?[s[0],s[1]*s[2]]:d?[s[0]*s[1],s[2]]:s,p=[c[1],c[0]]);let h=S("a",n,c.length),m=C("output",n,p.length),f=16,w;return l?w=y=>`
  ${y.registerUniform("output_size","u32").declareVariables(h,m)}
  var<workgroup> tile : array<array<${m.type.value}, ${f+1}>, ${f}>;
  ${y.mainStart([f,f,1])}
    let stride = (uniforms.output_shape[1] - 1) / ${f} + 1;
    let workgroup_id_x = workgroup_index % stride;
    let workgroup_id_y = workgroup_index / stride;
    let input_col = workgroup_id_y * ${f}u + local_id.x;
    let input_row = workgroup_id_x * ${f}u + local_id.y;
    if (input_row < uniforms.a_shape[0] && input_col < uniforms.a_shape[1]) {
      tile[local_id.y][local_id.x] = ${h.getByIndices(`${h.type.indices}(input_row, input_col)`)};
    }
    workgroupBarrier();

    let output_col = workgroup_id_x * ${f}u + local_id.x;
    let output_row = workgroup_id_y * ${f}u + local_id.y;
    if (output_row < uniforms.output_shape[0] && output_col < uniforms.output_shape[1]) {
      ${m.setByIndices(`${m.type.indices}(output_row, output_col)`,"tile[local_id.x][local_id.y]")}
    }
  }`:w=y=>`
  ${y.registerUniform("output_size","u32").declareVariables(h,m)}

  ${Wu(o,r,h,m)}

  ${y.mainStart()}
    ${y.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}

    let indices = ${m.offsetToIndices("global_idx")};
    let aIndices = perm(indices);

    ${m.setByOffset("global_idx",h.getByIndices("aIndices"))}
  }`,{name:l?"TransposeShared":"Transpose",shaderCache:{hint:`${t}`,inputDependencies:["rank"]},getRunData:()=>{let y=x.size(i);return{outputs:[{dims:i,dataType:e.dataType}],dispatchGroup:l?{x:Math.ceil(p[1]/f),y:Math.ceil(p[0]/f)}:{x:Math.ceil(y/64)},programUniforms:[{type:12,data:y},...A(c,p)]}},getShaderSource:w}},co=(e,t)=>{Lu(e.inputs),e.compute(le(e.inputs[0],t.perm))},po=e=>V({perm:e.perm})});var Hu,qu,Fu,Ku,ju,Xu,Zu,Qu,Yu,Ju,Pe,mo,fo,ho,go,yo,bo,wo,_o,$o,vo,xo=k(()=>{"use strict";U();N();W();Ft();Me();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"},qu={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"},Fu={max:"_A[offset]",min:"_A[offset]",mean:"0",sum:"0",prod:"1",sumSquare:"0",logSumExp:"0",l1:"0",l2:"0",logSum:"0"},Ku={max:"bestValue",min:"bestValue",sum:"bestValue",prod:"bestValue",sumSquare:"bestValue",logSumExp:"log(bestValue)",l1:"bestValue",l2:"sqrt(bestValue)",logSum:"log(bestValue)"},ju=(e,t)=>{let n=[];for(let r=t-e;r<t;++r)n.push(r);return n},Xu=(e,t)=>{let n=[],r=e.length;for(let i=0;i<r;i++)t.indexOf(i)===-1&&n.push(e[i]);let o=t.map(i=>e[i]);return[n,o]},Zu=(e,t)=>{let n=e.length+t.length,r=[],o=0;for(let i=0;i<n;i++)t.indexOf(i)===-1?r.push(e[o++]):r.push(1);return r},Qu=(e,t)=>{for(let n=0;n<e.length;++n)if(e[e.length-n-1]!==t-1-n)return!1;return!0},Yu=(e,t)=>{let n=[];if(!Qu(e,t)){for(let r=0;r<t;++r)e.indexOf(r)===-1&&n.push(r);e.forEach(r=>n.push(r))}return n},Ju=(e,t,n,r,o,i,s)=>{let a=n[0].dims,u=x.size(i),d=x.size(s),l=S("_A",n[0].dataType,a),c=C("output",o,i),p=32,h=`
          var<workgroup> aBestValues : array<f32, ${p}>;
       `;return{name:e,shaderCache:t,getShaderSource:f=>`
        ${f.registerUniform("reduceSize","u32").declareVariables(l,c)}
        ${h}
        fn DIV_CEIL(a : u32, b : u32) -> u32 {
          return ((a - 1u) / b + 1u);
         }
         ${f.mainStart(p)}

          let outputIndex = global_idx / ${p};
          let offset = outputIndex * uniforms.reduceSize;

          var bestValue = f32(${Fu[r]});
          let Length = uniforms.reduceSize;
          for (var k = local_idx; k < Length; k = k + ${p}) {
           let candidate = f32(${l.getByOffset("offset + k")});
           bestValue = ${Hu[r]};
          }
          aBestValues[local_idx] = bestValue;
          workgroupBarrier();

         var reduceSize = min(Length, ${p}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 = ${qu[r]};
            aBestValues[local_idx] = bestValue;
           }
           reduceSize = interval;
           workgroupBarrier();
         }

         if (local_idx == 0u) {
          ${c.setByOffset("outputIndex",`${r==="mean"?`${c.type.storage}(bestValue / f32(uniforms.reduceSize))`:`${c.type.storage}(${Ku[r]})`}`)};
         }
--> --------------------

--> maximum size reached

--> --------------------