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r=Object.keys(e),i=0;i>>3){case 1:d.tensorName=e.string();break;case 2:d.quantParameterTensorNames&&d.quantParameterTensorNames.length||(d.quantParameterTensorNames=[]),d.quantParameterTensorNames.push(o.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.tensorName!=null&&e.hasOwnProperty("tensorName")&&!l.isString(e.tensorName))return"tensorName: string expected";if(e.quantParameterTensorNames!=null&&e.hasOwnProperty("quantParameterTensorNames")){if(!Array.isArray(e.quantParameterTensorNames))return"quantParameterTensorNames: array expected";for(var r=0;r>>3){case 1:d.node&&d.node.length||(d.node=[]),d.node.push(o.onnx.NodeProto.decode(e,e.uint32()));break;case 2:d.name=e.string();break;case 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r=0;r>>3){case 1:if(d.dims&&d.dims.length||(d.dims=[]),(7&g)==2)for(var m=e.uint32()+e.pos;e.pos>>0,e.dims[i].high>>>0).toNumber())}if(e.dataType!=null&&(r.dataType=0|e.dataType),e.segment!=null){if(typeof e.segment!="object")throw TypeError(".onnx.TensorProto.segment: object expected");r.segment=o.onnx.TensorProto.Segment.fromObject(e.segment)}if(e.floatData){if(!Array.isArray(e.floatData))throw TypeError(".onnx.TensorProto.floatData: array expected");for(r.floatData=[],i=0;i>>0,e.int64Data[i].high>>>0).toNumber())}if(e.name!=null&&(r.name=String(e.name)),e.docString!=null&&(r.docString=String(e.docString)),e.rawData!=null&&(typeof e.rawData=="string"?l.base64.decode(e.rawData,r.rawData=l.newBuffer(l.base64.length(e.rawData)),0):e.rawData.length&&(r.rawData=e.rawData)),e.externalData){if(!Array.isArray(e.externalData))throw TypeError(".onnx.TensorProto.externalData: array expected");for(r.externalData=[],i=0;i>>0,e.uint64Data[i].high>>>0).toNumber(!0))}return r},t.toObject=function(e,r){r||(r={});var i={};if((r.arrays||r.defaults)&&(i.dims=[],i.floatData=[],i.int32Data=[],i.stringData=[],i.int64Data=[],i.doubleData=[],i.uint64Data=[],i.externalData=[]),r.defaults&&(i.dataType=0,i.segment=null,i.name="",r.bytes===String?i.rawData="":(i.rawData=[],r.bytes!==Array&&(i.rawData=l.newBuffer(i.rawData))),i.docString="",i.dataLocation=r.enums===String?"DEFAULT":0),e.dims&&e.dims.length){i.dims=[];for(var d=0;d>>0,e.dims[d].high>>>0).toNumber():e.dims[d]}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&(i.dataType=e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&(i.segment=o.onnx.TensorProto.Segment.toObject(e.segment,r)),e.floatData&&e.floatData.length)for(i.floatData=[],d=0;d>>0,e.int64Data[d].high>>>0).toNumber():e.int64Data[d];if(e.name!=null&&e.hasOwnProperty("name")&&(i.name=e.name),e.rawData!=null&&e.hasOwnProperty("rawData")&&(i.rawData=r.bytes===String?l.base64.encode(e.rawData,0,e.rawData.length):r.bytes===Array?Array.prototype.slice.call(e.rawData):e.rawData),e.doubleData&&e.doubleData.length)for(i.doubleData=[],d=0;d>>0,e.uint64Data[d].high>>>0).toNumber(!0):e.uint64Data[d];if(e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),e.externalData&&e.externalData.length)for(i.externalData=[],d=0;d>>3){case 1:g.begin=r.int64();break;case 2:g.end=r.int64();break;default:r.skipType(7&m)}}return g},e.decodeDelimited=function(r){return r instanceof h||(r=new h(r)),this.decode(r,r.uint32())},e.verify=function(r){return typeof r!="object"||r===null?"object expected":r.begin!=null&&r.hasOwnProperty("begin")&&!(l.isInteger(r.begin)||r.begin&&l.isInteger(r.begin.low)&&l.isInteger(r.begin.high))?"begin: integer|Long expected":r.end!=null&&r.hasOwnProperty("end")&&!(l.isInteger(r.end)||r.end&&l.isInteger(r.end.low)&&l.isInteger(r.end.high))?"end: integer|Long expected":null},e.fromObject=function(r){if(r instanceof o.onnx.TensorProto.Segment)return r;var i=new o.onnx.TensorProto.Segment;return r.begin!=null&&(l.Long?(i.begin=l.Long.fromValue(r.begin)).unsigned=!1:typeof r.begin=="string"?i.begin=parseInt(r.begin,10):typeof r.begin=="number"?i.begin=r.begin:typeof r.begin=="object"&&(i.begin=new l.LongBits(r.begin.low>>>0,r.begin.high>>>0).toNumber())),r.end!=null&&(l.Long?(i.end=l.Long.fromValue(r.end)).unsigned=!1:typeof r.end=="string"?i.end=parseInt(r.end,10):typeof r.end=="number"?i.end=r.end:typeof r.end=="object"&&(i.end=new 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this.constructor.toObject(this,s.util.toJSONOptions)},e}(),t.DataLocation=function(){var e={},r=Object.create(e);return r[e[0]="DEFAULT"]=0,r[e[1]="EXTERNAL"]=1,r}(),t}(),f.TensorShapeProto=function(){function t(e){if(this.dim=[],e)for(var r=Object.keys(e),i=0;i>>3==1?(d.dim&&d.dim.length||(d.dim=[]),d.dim.push(o.onnx.TensorShapeProto.Dimension.decode(e,e.uint32()))):e.skipType(7&g)}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.dim!=null&&e.hasOwnProperty("dim")){if(!Array.isArray(e.dim))return"dim: array expected";for(var r=0;r>>3){case 1:m.dimValue=i.int64();break;case 2:m.dimParam=i.string();break;case 3:m.denotation=i.string();break;default:i.skipType(7&_)}}return m},e.decodeDelimited=function(i){return i instanceof h||(i=new h(i)),this.decode(i,i.uint32())},e.verify=function(i){if(typeof i!="object"||i===null)return"object expected";var d={};if(i.dimValue!=null&&i.hasOwnProperty("dimValue")&&(d.value=1,!(l.isInteger(i.dimValue)||i.dimValue&&l.isInteger(i.dimValue.low)&&l.isInteger(i.dimValue.high))))return"dimValue: integer|Long expected";if(i.dimParam!=null&&i.hasOwnProperty("dimParam")){if(d.value===1)return"value: multiple values";if(d.value=1,!l.isString(i.dimParam))return"dimParam: string expected"}return i.denotation!=null&&i.hasOwnProperty("denotation")&&!l.isString(i.denotation)?"denotation: string expected":null},e.fromObject=function(i){if(i instanceof o.onnx.TensorShapeProto.Dimension)return i;var d=new o.onnx.TensorShapeProto.Dimension;return i.dimValue!=null&&(l.Long?(d.dimValue=l.Long.fromValue(i.dimValue)).unsigned=!1:typeof i.dimValue=="string"?d.dimValue=parseInt(i.dimValue,10):typeof i.dimValue=="number"?d.dimValue=i.dimValue:typeof i.dimValue=="object"&&(d.dimValue=new 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1:g.tensorType=o.onnx.TypeProto.Tensor.decode(r,r.uint32());break;case 6:g.denotation=r.string();break;default:r.skipType(7&m)}}return g},t.decodeDelimited=function(r){return r instanceof h||(r=new h(r)),this.decode(r,r.uint32())},t.verify=function(r){if(typeof r!="object"||r===null)return"object expected";if(r.tensorType!=null&&r.hasOwnProperty("tensorType")){var i=o.onnx.TypeProto.Tensor.verify(r.tensorType);if(i)return"tensorType."+i}return r.denotation!=null&&r.hasOwnProperty("denotation")&&!l.isString(r.denotation)?"denotation: string expected":null},t.fromObject=function(r){if(r instanceof o.onnx.TypeProto)return r;var i=new o.onnx.TypeProto;if(r.tensorType!=null){if(typeof r.tensorType!="object")throw TypeError(".onnx.TypeProto.tensorType: object expected");i.tensorType=o.onnx.TypeProto.Tensor.fromObject(r.tensorType)}return r.denotation!=null&&(i.denotation=String(r.denotation)),i},t.toObject=function(r,i){i||(i={});var d={};return 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e!="object"||e===null?"object expected":e.domain!=null&&e.hasOwnProperty("domain")&&!l.isString(e.domain)?"domain: string expected":e.version!=null&&e.hasOwnProperty("version")&&!(l.isInteger(e.version)||e.version&&l.isInteger(e.version.low)&&l.isInteger(e.version.high))?"version: integer|Long expected":null},t.fromObject=function(e){if(e instanceof o.onnx.OperatorSetIdProto)return e;var r=new o.onnx.OperatorSetIdProto;return e.domain!=null&&(r.domain=String(e.domain)),e.version!=null&&(l.Long?(r.version=l.Long.fromValue(e.version)).unsigned=!1:typeof e.version=="string"?r.version=parseInt(e.version,10):typeof e.version=="number"?r.version=e.version:typeof e.version=="object"&&(r.version=new l.LongBits(e.version.low>>>0,e.version.high>>>0).toNumber())),r},t.toObject=function(e,r){r||(r={});var i={};if(r.defaults)if(i.domain="",l.Long){var d=new l.Long(0,0,!1);i.version=r.longs===String?d.toString():r.longs===Number?d.toNumber():d}else i.version=r.longs===String?"0":0;return 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o.isPacked?this.getPackedOutputSamplingSnippet(o):this.getUnpackedOutputSamplingSnippet(o)}getPackedOutputSamplingSnippet(o){const t=o.unpackedShape,e=[o.width,o.height],r={},i="getOutputCoords";switch(t.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputPacked1DCoords(t,e);break;case 2:r[i]=this.getOutputPacked2DCoords(t,e);break;case 3:r[i]=this.getOutputPacked3DCoords(t,e);break;default:r[i]=this.getOutputPackedNDCoords(t,e)}const d=` + void setOutput(vec4 val) { + ${(0,f.getGlsl)(this.context.glContext.version).output} = val; + } + `;return r.floatTextureSetRGBA=new c.GlslLibRoutine(d),r}getUnpackedOutputSamplingSnippet(o){const t=o.unpackedShape,e=[o.width,o.height],r={},i="getOutputCoords";switch(t.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputUnpacked1DCoords(t,e);break;case 2:r[i]=this.getOutputUnpacked2DCoords(t,e);break;case 3:r[i]=this.getOutputUnpacked3DCoords(t,e);break;case 4:r[i]=this.getOutputUnpacked4DCoords(t,e);break;case 5:r[i]=this.getOutputUnpacked5DCoords(t,e);break;case 6:r[i]=this.getOutputUnpacked6DCoords(t,e);break;default:throw new Error(`Unsupported output dimensionality: ${t.length}`)}const d=` + void setOutput(float val) { + ${(0,f.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0); + } + `;return r.floatTextureSetR=new c.GlslLibRoutine(d),r}getOutputScalarCoords(){return new c.GlslLibRoutine(` + int getOutputCoords() { + return 0; + } + `)}getOutputPacked1DCoords(o,t){const e=t;let r="";return e[0]===1?(r=` + int getOutputCoords() { + return 2 * int(TexCoords.y * ${e[1]}.0); + } + `,new c.GlslLibRoutine(r)):e[1]===1?(r=` + int getOutputCoords() { + return 2 * int(TexCoords.x * ${e[0]}.0); + } + `,new c.GlslLibRoutine(r)):(r=` + int getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${e[0]}, ${e[1]})); + return 2 * (resTexRC.y * ${e[0]} + resTexRC.x); + } + `,new c.GlslLibRoutine(r))}getOutputPacked2DCoords(o,t){let e="";if(u.ArrayUtil.arraysEqual(o,t))return e=` + ivec2 getOutputCoords() { + return 2 * ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]})); + } + `,new c.GlslLibRoutine(e);const r=t,i=Math.ceil(o[1]/2);return e=` + ivec2 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${r[0]}, ${r[1]})); + + int index = resTexRC.y * ${r[0]} + resTexRC.x; + + // reverse r and c order for packed texture + int r = imod(index, ${i}) * 2; + int c = 2 * (index / ${i}); + + return ivec2(r, c); + } + `,new c.GlslLibRoutine(e)}getOutputPacked3DCoords(o,t){const e=[t[0],t[1]],r=Math.ceil(o[2]/2),i=r*Math.ceil(o[1]/2),d=` + ivec3 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${e[0]}, ${e[1]})); + int index = resTexRC.y * ${e[0]} + resTexRC.x; + + int b = index / ${i}; + index -= b * ${i}; + + // reverse r and c order for packed texture + int r = imod(index, ${r}) * 2; + int c = 2 * (index / ${r}); + + return ivec3(b, r, c); + } + `;return new c.GlslLibRoutine(d)}getOutputPackedNDCoords(o,t){const e=[t[0],t[1]],r=Math.ceil(o[o.length-1]/2),i=r*Math.ceil(o[o.length-2]/2);let d=i,g="",m="b, r, c";for(let y=2;y=0;--m)i[m]=i[m+1]*o[m+1];const d=["r","c","d"],g=i.map((m,_)=>`int ${d[_]} = index / ${m}; ${_===i.length-1?`int ${d[_+1]} = index - ${d[_]} * ${m}`:`index -= ${d[_]} * ${m}`};`).join("");return e=` + ivec3 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${t[0]}, ${t[1]})); + int index = resTexRC.y * ${t[0]} + resTexRC.x; + ${g} + return ivec3(r, c, d); + } + `,new c.GlslLibRoutine(e)}getOutputUnpacked4DCoords(o,t){let e="";const r=o.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=o[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*o[m+1];const d=["r","c","d","d2"],g=i.map((m,_)=>`int ${d[_]} = index / ${m}; ${_===i.length-1?`int ${d[_+1]} = index - ${d[_]} * ${m}`:`index -= ${d[_]} * ${m}`};`).join("");return e=` + ivec4 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${t[0]}, ${t[1]})); + int index = resTexRC.y * ${t[0]} + resTexRC.x; + ${g} + return ivec4(r, c, d, d2); + } + `,new c.GlslLibRoutine(e)}getOutputUnpacked5DCoords(o,t){let e="";const r=o.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=o[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*o[m+1];const d=["r","c","d","d2","d3"],g=i.map((m,_)=>`int ${d[_]} = index / ${m}; ${_===i.length-1?`int ${d[_+1]} = index - ${d[_]} * ${m}`:`index -= ${d[_]} * ${m}`};`).join("");return e=` + ivec5 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${t[0]}, ${t[1]})); + int index = resTexRC.y * ${t[0]} + resTexRC.x; + ${g} + return ivec5(r, c, d, d2, d3); + } + `,new c.GlslLibRoutine(e)}getOutputUnpacked6DCoords(o,t){let e="";const r=o.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=o[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*o[m+1];const d=["r","c","d","d2","d3","d4"],g=i.map((m,_)=>`int ${d[_]} = index / ${m}; ${_===i.length-1?`int ${d[_+1]} = index - ${d[_]} * ${m}`:`index -= ${d[_]} * ${m}`};`).join("");return e=` + ivec6 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${t[0]}, ${t[1]})); + int index = resTexRC.y * ${t[0]} + resTexRC.x; + ${g} + return ivec6(r, c, d, d2, d3, d4); + } + `,new c.GlslLibRoutine(e)}getCommonUtilFuncs(){const o={};let t="uvFromFlat";o[t]=new c.GlslLibRoutine(` + vec2 uvFromFlat(int texNumR, int texNumC, int index) { + int texC = index / texNumR; + int texR = index - texC * texNumR; + // TODO: swap texR, texC order in following function so row is corresponding to u and column is corresponding to + // v. + return (vec2(texR, texC) + halfCR) / vec2(texNumR, texNumC); + } + `),t="packedUVfrom1D",o[t]=new c.GlslLibRoutine(` + vec2 packedUVfrom1D(int texNumR, int texNumC, int index) { + int texelIndex = index / 2; + int texR = texelIndex / texNumC; + int texC = texelIndex - texR * texNumC; + return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR); + } + `),t="packedUVfrom2D",o[t]=new c.GlslLibRoutine(` + vec2 packedUVfrom2D(int texNumR, int texNumC, int texelsInLogicalRow, int row, int col) { + int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2); + int texR = texelIndex / texNumC; + int texC = texelIndex - texR * texNumC; + return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR); + } + `),t="packedUVfrom3D",o[t]=new c.GlslLibRoutine(` + vec2 packedUVfrom3D(int texNumR, int texNumC, + int texelsInBatch, int texelsInLogicalRow, int b, + int row, int col) { + int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2); + int texR = index / texNumC; + int texC = index - texR * texNumC; + return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR); + } + `),t="sampleTexture";const e=(0,f.getGlsl)(this.context.glContext.version);return o[t]=new c.GlslLibRoutine(` + float sampleTexture(sampler2D textureSampler, vec2 uv) { + return ${e.texture2D}(textureSampler, uv).r; + }`),o}getInputsSamplingSnippets(){const o={},t=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,r)=>{const i=this.context.inputTextureLayouts[r],d=(0,h.generateShaderFuncNameFromInputSamplerName)(e);i.isPacked?o[d]=this.getPackedSamplerFromInput(d,e,i):o[d]=this.getUnpackedSamplerFromInput(d,e,i);const g=(0,h.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(e);i.unpackedShape.length<=t.unpackedShape.length&&(i.isPacked?o[g]=this.getPackedSamplerAtOutputCoords(g,i,t,e):o[g]=this.getUnpackedSamplerAtOutputCoords(g,i,t,e))}),o}getPackedSamplerAtOutputCoords(o,t,e,r){const i=t.unpackedShape,d=e.unpackedShape,g=r,m=(0,h.generateShaderFuncNameFromInputSamplerName)(g),_=i.length,y=d.length,T=u.BroadcastUtil.getBroadcastDims(i,d),w=(0,h.getCoordsDataType)(y),S=y-_;let O;const E=(0,h.getGlChannels)();O=_===0?"":y<2&&T.length>=1?"coords = 0;":T.map(k=>`coords.${E[k+S]} = 0;`).join(` +`);let v="";v=y<2&&_>0?"coords":i.map((k,Y)=>`coords.${E[Y+S]}`).join(", ");let P="return outputValue;";const L=u.ShapeUtil.size(i)===1,V=u.ShapeUtil.size(d)===1;if(_!==1||L||V){if(L&&!V)P=y===1?` + return vec4(outputValue.x, outputValue.x, 0., 0.); + `:` + return vec4(outputValue.x); + `;else if(T.length){const k=_-2,Y=_-1;T.indexOf(k)>-1&&T.indexOf(Y)>-1?P="return vec4(outputValue.x);":T.indexOf(k)>-1?P="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":T.indexOf(Y)>-1&&(P="return vec4(outputValue.xx, outputValue.zz);")}}else P=` + return vec4(outputValue.xy, outputValue.xy); + `;const R=` + vec4 ${o}() { + ${w} coords = getOutputCoords(); + + int lastDim = coords.${E[y-1]}; + coords.${E[y-1]} = coords.${E[y-2]}; + coords.${E[y-2]} = lastDim; + + ${O} + vec4 outputValue = ${m}(${v}); + ${P} + } + `;return new c.GlslLibRoutine(R,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(o,t,e,r){const i=[e.width,e.height],d=[t.width,t.height],g=t.unpackedShape.length,m=e.unpackedShape.length,_=t.unpackedShape,y=e.unpackedShape,T=(0,h.generateShaderFuncNameFromInputSamplerName)(r);if(g===m&&u.ArrayUtil.arraysEqual(d,i)){const V=` + float ${o}() { + return sampleTexture(${r}, TexCoords); + } + `;return new c.GlslLibRoutine(V,["coordinates.sampleTexture"])}const w=(0,h.getCoordsDataType)(m),S=u.BroadcastUtil.getBroadcastDims(_,y),O=m-g;let E;const v=(0,h.getGlChannels)();E=g===0?"":m<2&&S.length>=1?"coords = 0;":S.map(V=>`coords.${v[V+O]} = 0;`).join(` +`);let P="";P=m<2&&g>0?"coords":t.unpackedShape.map((V,R)=>`coords.${v[R+O]}`).join(", ");const L=` + float ${o}() { + ${w} coords = getOutputCoords(); + ${E} + return ${T}(${P}); + } + `;return new c.GlslLibRoutine(L,["coordinates.getOutputCoords"])}getPackedSamplerFromInput(o,t,e){switch(e.unpackedShape.length){case 0:return this.getPackedSamplerScalar(o,t);case 1:return this.getPackedSampler1D(o,t,e);case 2:return this.getPackedSampler2D(o,t,e);case 3:return this.getPackedSampler3D(o,t,e);default:return this.getPackedSamplerND(o,t,e)}}getUnpackedSamplerFromInput(o,t,e){const r=e.unpackedShape;switch(r.length){case 0:return this.getUnpackedSamplerScalar(o,t,e);case 1:return this.getUnpackedSampler1D(o,t,e);case 2:return this.getUnpackedSampler2D(o,t,e);case 3:return this.getUnpackedSampler3D(o,t,e);case 4:return this.getUnpackedSampler4D(o,t,e);case 5:return this.getUnpackedSampler5D(o,t,e);case 6:return this.getUnpackedSampler6D(o,t,e);default:throw new Error(`Unsupported dimension ${r.length}-D`)}}getPackedSamplerScalar(o,t){const e=` + vec4 ${o}() { + return ${(0,f.getGlsl)(this.context.glContext.version).texture2D}(${t}, halfCR); + } + `;return new c.GlslLibRoutine(e)}getPackedSampler1D(o,t,e){const r=[e.width,e.height],i=[r[1],r[0]],d=(0,f.getGlsl)(this.context.glContext.version),g=`vec4 ${o}(int index) { + vec2 uv = packedUVfrom1D( + ${i[0]}, ${i[1]}, index); + return ${d.texture2D}(${t}, uv); + }`;return new c.GlslLibRoutine(g,["coordinates.packedUVfrom1D"])}getPackedSampler2D(o,t,e){const r=e.unpackedShape,i=[e.width,e.height],d=(0,f.getGlsl)(this.context.glContext.version),g=i[0],m=i[1];if(i!=null&&u.ArrayUtil.arraysEqual(r,i)){const w=`vec4 ${o}(int row, int col) { + vec2 uv = (vec2(col, row) + halfCR) / vec2(${m}.0, ${g}.0); + return ${d.texture2D}(${t}, uv); + }`;return new c.GlslLibRoutine(w)}const _=i,y=Math.ceil(r[1]/2),T=`vec4 ${o}(int row, int col) { + vec2 uv = packedUVfrom2D(${_[1]}, ${_[0]}, ${y}, row, col); + return ${d.texture2D}(${t}, uv); + }`;return new c.GlslLibRoutine(T,["coordinates.packedUVfrom2D"])}getPackedSampler3D(o,t,e){const r=e.unpackedShape,i=[e.width,e.height],d=[i[0],i[1]],g=(0,f.getGlsl)(this.context.glContext.version);if(r[0]===1){const w=r.slice(1),S=[1,2],O=(0,h.squeezeInputShape)(r,w),E=["b","row","col"],v=JSON.parse(JSON.stringify(e));v.unpackedShape=O;const P=this.getPackedSamplerFromInput(o,t,v),L=`${P.routineBody} + vec4 ${o}(int b, int row, int col) { + return ${o}(${(0,h.getSqueezedParams)(E,S)}); + } `;return new c.GlslLibRoutine(L,P.dependencies)}const m=d[0],_=d[1],y=Math.ceil(r[2]/2),T=`vec4 ${o}(int b, int row, int col) { + vec2 uv = packedUVfrom3D( + ${_}, ${m}, ${y*Math.ceil(r[1]/2)}, ${y}, b, row, col); + return ${g.texture2D}(${t}, uv);}`;return new c.GlslLibRoutine(T,["coordinates.packedUVfrom3D"])}getPackedSamplerND(o,t,e){const r=e.unpackedShape,i=r.length,d=[e.width,e.height],g=(0,f.getGlsl)(this.context.glContext.version),m=[d[0],d[1]],_=m[1],y=m[0],T=Math.ceil(r[i-1]/2);let w=T*Math.ceil(r[i-2]/2),S="int b, int row, int col",O=`b * ${w} + (row / 2) * ${T} + (col / 2)`;for(let v=2;v{const r=this.context.inputTextureLayouts[e],i=(r.unpackedShape.length>0?r.unpackedShape:r.shape).length;let d=`_${t}`;o[d]=new c.GlslLibRoutine(this.getValueFromSingle(t,i,r.width,r.height,!1),[`shapeUtils.indicesToOffset${d}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"]),d+="_T",o[d]=new c.GlslLibRoutine(this.getValueFromSingle(t,i,r.width,r.height,!0),[`shapeUtils.indicesToOffset${d}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"])}),o}getValueFromSingle(o,t,e,r,i){let d=`_${o}`;return i&&(d+="_T"),` + float ${d}(int m[${t}]) { + int offset = indicesToOffset${d}(m); + vec2 coords = offsetToCoords(offset, ${e}, ${r}); + float value = getColorAsFloat(${(0,f.getGlsl)(this.context.glContext.version).texture2D}(${o}, coords)); + return value; + } + `}getPackedValueFrom(o,t,e,r,i){let d=`_${o}_Pack`;return i&&(d+="_T"),` + vec4 ${d}(int m[${t}]) { + int offset = indicesToOffset_${o}(m); + vec2 coords = offsetToCoords(offset, ${e}, ${r}); + return ${(0,f.getGlsl)(this.context.glContext.version).texture2D}(${o}, coords); + } + `}}n.CoordsGlslLib=p},8520:(b,n)=>{var a;Object.defineProperty(n,"__esModule",{value:!0}),n.TopologicalSortGlslRoutines=n.GlslLibRoutineNode=n.GlslLibRoutine=n.GlslLib=n.GlslContext=n.FunctionType=void 0,(a=n.FunctionType||(n.FunctionType={}))[a.ValueBased=0]="ValueBased",a[a.Positional=1]="Positional",n.GlslContext=class{constructor(u,c,f,s){this.glContext=u,this.programInfo=c,this.inputTextureLayouts=f,this.outputTextureLayout=s}},n.GlslLib=class{constructor(u){this.context=u}},n.GlslLibRoutine=class{constructor(u,c){this.routineBody=u,this.dependencies=c}},n.GlslLibRoutineNode=class{constructor(u,c,f){this.name=u,this.dependencies=f||[],c&&(this.routineBody=c)}addDependency(u){u&&this.dependencies.push(u)}},n.TopologicalSortGlslRoutines=class{static returnOrderedNodes(u){if(!u||u.length===0)return[];if(u.length===1)return u;const c=new Set,f=new Set,s=new Array;return this.createOrderedNodes(u,c,f,s),s}static createOrderedNodes(u,c,f,s){for(let h=0;h0)for(let p=0;p{Object.defineProperty(n,"__esModule",{value:!0}),n.EncodingGlslLib=void 0;const u=a(8520);class c extends u.GlslLib{constructor(s){super(s)}getFunctions(){return Object.assign(Object.assign({},this.encodeFloat32()),this.decodeFloat32())}getCustomTypes(){return{}}encodeFloat32(){return{encode:new u.GlslLibRoutine(`highp vec4 encode(highp float f) { + return vec4(f, 0.0, 0.0, 0.0); + } + `)}}decodeFloat32(){return{decode:new u.GlslLibRoutine(`highp float decode(highp vec4 rgba) { + return rgba.r; + } + `)}}encodeUint8(){const s=c.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{encode:new u.GlslLibRoutine(` + highp vec4 encode(highp float f) { + highp float F = abs(f); + highp float Sign = step(0.0,-f); + highp float Exponent = floor(log2(F)); + highp float Mantissa = (exp2(- Exponent) * F); + Exponent = floor(log2(F) + 127.0) + floor(log2(Mantissa)); + highp vec4 rgba; + rgba[0] = 128.0 * Sign + floor(Exponent*exp2(-1.0)); + rgba[1] = 128.0 * mod(Exponent,2.0) + mod(floor(Mantissa*128.0),128.0); + rgba[2] = floor(mod(floor(Mantissa*exp2(23.0 -8.0)),exp2(8.0))); + rgba[3] = floor(exp2(23.0)*mod(Mantissa,exp2(-15.0))); + ${s} + rgba = rgba / 255.0; // values need to be normalized to [0,1] + return rgba; + } + `)}}decodeUint8(){const s=c.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{decode:new u.GlslLibRoutine(` + highp float decode(highp vec4 rgba) { + rgba = rgba * 255.0; // values need to be de-normalized from [0,1] to [0,255] + ${s} + highp float Sign = 1.0 - step(128.0,rgba[0])*2.0; + highp float Exponent = 2.0 * mod(rgba[0],128.0) + step(128.0,rgba[1]) - 127.0; + highp float Mantissa = mod(rgba[1],128.0)*65536.0 + rgba[2]*256.0 +rgba[3] + float(0x800000); + highp float Result = Sign * exp2(Exponent) * (Mantissa * exp2(-23.0 )); + return Result; + } + `)}}static isLittleEndian(){const s=new ArrayBuffer(4),h=new Uint32Array(s),p=new Uint8Array(s);if(h[0]=3735928559,p[0]===239)return!0;if(p[0]===222)return!1;throw new Error("unknown endianness")}}n.EncodingGlslLib=c},9894:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.FragColorGlslLib=void 0;const u=a(8520),c=a(5060);class f extends 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float variance = getColorAsFloat(${e.texture2D}(Variance, position)); + float b = getColorAsFloat(${e.texture2D}(B, position)); + + return scale * ( (_A(indices) - mean) / sqrt(variance + float(${t.epsilon})) ) + b; + }`;return Object.assign(Object.assign({},s),{output:{dims:o[0].dims,type:o[0].type,textureType:f.TextureType.unpacked},shaderSource:g})},p=l=>{if(!l||l.length!==5)throw new Error("BatchNormalization requires 5 inputs.");const o=l[0],t=l[1],e=l[2],r=l[3],i=l[4];if(o.dims.length<3||t.dims.length!==1||e.dims.length!==1||r.dims.length!==1||i.dims.length!==1)throw new Error("invalid input shape.");if(t.dims[0]!==o.dims[1]||e.dims[0]!==o.dims[1]||r.dims[0]!==o.dims[1]||i.dims[0]!==o.dims[1])throw new Error("invalid input shape.");if(o.type!=="float32"&&o.type!=="float64"||t.type!=="float32"&&t.type!=="float64"||e.type!=="float32"&&e.type!=="float64"||r.type!=="float32"&&r.type!=="float64"||i.type!=="float32"&&i.type!=="float64")throw new Error("invalid input tensor 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b; + } + vec4 ${w}(vec4 v1, vec4 v2) { + return v1 - v2; + } + `,name:w,type:c.FunctionType.ValueBased}}function t(){const w="equal_";return{body:` + float ${w}(float a, float b) { + return float(a == b); + } + vec4 ${w}(vec4 v1, vec4 v2) { + return vec4(equal(v1, v2)); + } + `,name:w,type:c.FunctionType.ValueBased}}function e(){const w="greater_";return{body:` + float ${w}(float a, float b) { + return float(a > b); + } + vec4 ${w}(vec4 v1, vec4 v2) { + return vec4( v1.r > v2.r , + v1.g > v2.g, + v1.b > v2.b, + v1.a > v2.a ); + } + `,name:w,type:c.FunctionType.ValueBased}}function r(){const w="less_";return{body:` + float ${w}(float a, float b) { + return float(a < b); + } + vec4 ${w}(vec4 v1, vec4 v2) { + return vec4( v1.r < v2.r , + v1.g < v2.g, + v1.b < v2.b, + v1.a < v2.a ); + } + `,name:w,type:c.FunctionType.ValueBased}}function i(){const w="and_";return{body:` + float ${w}(float a, float b) { + return float( bool(a) && bool(b) ); + } + vec4 ${w}(vec4 v1, vec4 v2) { + bvec4 b1 = bvec4(v1); + bvec4 b2 = bvec4(v2); + return vec4( b1.r && b2.r , + b1.g && b2.g, + b1.b && b2.b, + b1.a && b2.a ); + } + `,name:w,type:c.FunctionType.ValueBased}}function d(){const w="or_";return{body:` + float ${w}(float a, float b) { + return float( bool(a) || bool(b) ); + } + vec4 ${w}(vec4 v1, vec4 v2) { + bvec4 b1 = bvec4(v1); + bvec4 b2 = bvec4(v2); + return vec4( b1.r || b2.r , + b1.g || b2.g, + b1.b || b2.b, + b1.a || b2.a ); + } + `,name:w,type:c.FunctionType.ValueBased}}function g(){const w="xor_";return{body:` + float ${w}(float a, float b) { + return float( bool(a) ^^ bool(b) ); + } + vec4 ${w}(vec4 v1, vec4 v2) { + bvec4 b1 = bvec4(v1); + bvec4 b2 = bvec4(v2); + return vec4( b1.r ^^ b2.r , + b1.g ^^ b2.g, + b1.b ^^ b2.b, + b1.a ^^ b2.a ); + } + `,name:w,type:c.FunctionType.ValueBased}}function m(){return function(w){const S=`${w}_`;return{body:` + float ${S}(float a, float b) { + return ${w}(a, b); + } + vec4 ${S}(vec4 v1, vec4 v2) { + return ${w}(v1, v2); + } + `,name:S,type:c.FunctionType.ValueBased}}("pow")}function _(){const w="prelu_";return{body:` + float ${w}(float a, float b) { + return a < 0.0 ? a * b: a; + } + vec4 ${w}(vec4 v1, vec4 v2) { + return vec4( + v1.r < 0.0 ? v1.r * v2.r: v1.r, + v1.g < 0.0 ? v1.g * v2.g: v1.g, + v1.b < 0.0 ? v1.b * v2.b: v1.b, + v1.a < 0.0 ? v1.a * v2.a: v1.a + ); + } + `,name:w,type:c.FunctionType.ValueBased}}n.glslAdd=h,n.glslDiv=p,n.glslMul=l,n.glslSub=o,n.glslEqual=t,n.glslGreater=e,n.glslLess=r,n.glslAnd=i,n.glslOr=d,n.glslXor=g,n.glslPow=m,n.glslPRelu=_;const y=(w,S,O,E=S[0].type,v)=>{const P=w.session.pack?s.TextureType.packed:s.TextureType.unpacked;return{name:O.name,inputNames:["A","B"],inputTypes:[P,P],cacheHint:v,get:()=>T(w,S,O,E)}},T=(w,S,O,E=S[0].type)=>{const v=w.session.pack?s.TextureType.packed:s.TextureType.unpacked,P=!u.ShapeUtil.areEqual(S[0].dims,S[1].dims);let L=S[0].dims;const V=w.session.pack;if(P){const Y=u.BroadcastUtil.calcShape(S[0].dims,S[1].dims,!1);if(!Y)throw new 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$=(0,u.getGlsl)(i.session.backend.glContext.version),X=` + ${O} + float getValue(${v.map(z=>"int "+z)}) { + ${k} + } + + void main() { + ${S} coords = getOutputCoords(); + int lastDim = coords.${v[T-1]}; + coords.${v[T-1]} = coords.${v[T-2]}; + coords.${v[T-2]} = lastDim; + + vec4 result = vec4(getValue(${w}), 0., 0., 0.); + + ${w[T-1]} = ${w[T-1]} + 1; + if (${w[T-1]} < ${y[T-1]}) { + result.g = getValue(${w}); + } + + ${w[T-2]} = ${w[T-2]} + 1; + if (${w[T-2]} < ${y[T-2]}) { + result.a = getValue(${w}); + } + + ${w[T-1]} = ${w[T-1]} - 1; + if (${w[T-2]} < ${y[T-2]} && + ${w[T-1]} < ${y[T-1]}) { + result.b = getValue(${w}); + } + ${$.output} = result; + } + `;return Object.assign(Object.assign({},d),{output:{dims:y,type:g[0].type,textureType:c.TextureType.packed},shaderSource:X,hasMain:!0})})(p,t,l,o.axis)})};const h=(p,l,o)=>{const t=p.indexOf(l);return p.map((e,r)=>r===t?`${e} - 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+ for (int wHeight = 0; wHeight < ${T[2]}; wHeight++) { + int xHeight = xRCCorner.x + wHeight * ${m.dilations[0]}; + + if (xHeight < 0 || xHeight >= ${y[2]}) { + continue; + } + + for (int wWidth = 0; wWidth < ${T[3]}; wWidth++) { + int xWidth = xRCCorner.y + wWidth * ${m.dilations[1]}; + if (xWidth < 0 || xWidth >= ${y[3]}) { + continue; + } + + float xVal = getX(batch, input_channel, xWidth, xHeight); + float wVal = getW(output_channel, wInChannel, wWidth, wHeight); + value += xVal*wVal; + } + } + } + ${_} + ${v} + ${O.output} = vec4(value, .0, .0, .0); + } +`;return Object.assign(Object.assign({},g),{output:{dims:S,type:d[0].type,textureType:f.TextureType.unpacked},shaderSource:P,hasMain:!0})})(p,l,t,o)})}},1386:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.conv2DPacked=n.conv2DPackedPointwise=void 0;const u=a(8138),c=a(8555),f=a(708);n.conv2DPackedPointwise=(s,h,p)=>{const 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coords.x; + int output_channel = coords.y; + + ivec2 loc = coords.zw + pads; + + int group_id = output_channel / ${R}; + int wOutChannel = output_channel - group_id * ${R}; + + float value = ${P}; + for (int inChannelOffset = 0; inChannelOffset < ${k}; inChannelOffset++) { + int input_channel = group_id * ${k} + inChannelOffset; + for (int wWOff = 0; wWOff < ${V[2]}; wWOff++) { + for (int wHOff = 0; wHOff < ${V[3]}; wHOff++) { + ivec2 wOff = ivec2(wWOff * ${v.dilations[0]}, wHOff * ${v.dilations[1]}); + ivec2 wLoc = loc - wOff; + ivec2 wLocIn = wLoc / strides; + if ( + wLocIn * strides == wLoc && + wLocIn.x >= 0 && wLocIn.x < ${L[2]} && + wLocIn.y >= 0 && wLocIn.y < ${L[3]} + ) { + float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x); + float wVal = getW(input_channel, wOutChannel, wHOff, wWOff); + value += xVal * wVal; + } + } + } + } + ${X} + ${C.output} = vec4(value, .0, .0, .0); + } +`;return Object.assign(Object.assign({},E),{output:{dims:Y,type:O[0].type,textureType:f.TextureType.unpacked},shaderSource:z,hasMain:!0})})(g,m,y,_)})})(r,i,d),i),t=(r,i)=>{const d=r.kernelShape.slice();if(r.kernelShape.length===0)for(let y=2;y{const L=y.length-2,V=P.length===0;for(let R=0;R{const i=r.attributes,d=(0,s.parseInternalActivationAttributes)(i),g=i.getString("auto_pad","NOTSET"),m=i.getInts("dilations",[1,1]),_=i.getInt("group",1),y=i.getInts("kernel_shape",[]),T=i.getInts("output_padding",[0,0]),w=i.getInts("output_shape",[]),S=i.getInts("pads",[0,0,0,0]),O=i.getInts("strides",[1,1]);return(0,u.createAttributeWithCacheKey)(Object.assign({autoPad:g,dilations:m,group:_,kernelShape:y,outputPadding:T,outputShape:w,pads:S,strides:O},d))};const e=(r,i)=>{if(!r||r.length!==2&&r.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(r[0].dims.length!==4||r[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(r[0].dims[1]!==r[1].dims[0])throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");const d=r[1].dims[1]*i.group;if(r.length===3&&(r[2].dims.length!==1||r[2].dims[0]!==d))throw new Error("invalid bias");const g=r[0].dims.length-2;if(i.dilations.length!==g)throw new Error(`dilations should be ${g}D`);if(i.strides.length!==g)throw new Error(`strides should be ${g}D`);if(i.pads.length!==2*g)throw new Error(`pads should be ${2*g}D`);if(i.outputPadding.length!==g)throw new Error(`output_padding should be ${g}D`);if(i.kernelShape.length!==0&&i.kernelShape.length!==r[1].dims.length-2)throw new Error("invalid kernel shape");if(i.outputShape.length!==0&&i.outputShape.length!==r[0].dims.length-2)throw new Error("invalid output shape");if(r[0].type!=="float32"||r[1].type!=="float32")throw new Error("ConvTranspose input(X,W) should be float tensor");if(r.length===3&&r[2].type!=="float32")throw new Error("ConvTranspose input(bias) should be float tensor")}},8138:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConvAttributes=n.conv=n.calculateOutputShape=void 0;const u=a(246),c=a(2517),f=a(4770),s=a(1386),h=a(9828),p=a(2823),l=a(3248),o=a(5623);n.calculateOutputShape=(g,m,_,y,T)=>{const w=g[0],S=g.slice(2),O=S.length,E=m[0],v=m.slice(2).map((L,V)=>L+(L-1)*(_[V]-1)),P=S.map((L,V)=>L+y[V]+y[V+O]).map((L,V)=>Math.floor((L-v[V]+T[V])/T[V]));return[w,E].concat(...P)},n.conv=(g,m,_)=>(d(m,_),t(g,m,_));const t=(g,m,_)=>{const y=i(_,m),T=g.session.pack,w=y.kernelShape[0]===1&&y.kernelShape[1]===1;return y.group>1?[g.run((0,f.createUnpackedGroupedConvProgramInfoLoader)(g,m,y),m)]:w&&T?[e(g,m,y)]:T&&m[0].dims.length===4&&m[0].dims[0]===1&&!w?[(0,s.conv2DPacked)(g,m,y)]:[r(g,m,y)]},e=(g,m,_)=>{const y=m[0].dims,T=m[1].dims,w=(0,n.calculateOutputShape)(y,T,_.dilations,_.pads,_.strides),S=g.reshapeUnpacked(m[0],[y[1],y[2]*y[3]]),O=g.reshapeUnpacked(m[1],[T[0],T[1]]),E=m.length>2?[O,S,m[2]]:[O,S],v=g.run((0,o.createMatmulProgramInfoLoader)(E,_),E);return g.reshapeUnpacked(v,w)},r=(g,m,_)=>{const y=m[0].dims,T=m[1].dims,w=(0,n.calculateOutputShape)(y,T,_.dilations,_.pads,_.strides),S=g.run((0,l.createIm2ColProgramInfoLoader)(g,m[0],m[1],w,_),[m[0]]),O=m.length===3?[S,m[1],m[2]]:[S,m[1]];return g.run((0,h.createDotProductProgramInfoLoader)(g,m,w,_),O)},i=(g,m)=>{const _=g.kernelShape.slice();if(g.kernelShape.length===0)for(let w=2;w{const m=g.attributes,_=(0,p.parseInternalActivationAttributes)(m),y=m.getString("auto_pad","NOTSET"),T=m.getInts("dilations",[1,1]),w=m.getInt("group",1),S=m.getInts("kernel_shape",[]),O=m.getInts("pads",[0,0,0,0]),E=m.getInts("strides",[1,1]);return(0,u.createAttributeWithCacheKey)(Object.assign({autoPad:y,dilations:T,group:w,kernelShape:S,pads:O,strides:E},_))};const d=(g,m)=>{if(!g||g.length!==2&&g.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(g[0].dims.length!==4||g[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(g[0].dims[1]!==g[1].dims[1]*m.group)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(g.length===3&&(g[2].dims.length!==1||g[1].dims[0]!==g[2].dims[0]))throw new Error("invalid bias");const _=g[0].dims.length-2;if(m.dilations.length!==_)throw new Error(`dilations should be ${_}D`);if(m.strides.length!==_)throw new Error(`strides should be ${_}D`);if(m.pads.length!==2*_)throw new Error(`pads should be ${2*_}D`);if(m.kernelShape.length!==0&&m.kernelShape.length!==g[1].dims.length-2)throw new Error("invalid kernel shape");if(g[0].type!=="float32"||g[1].type!=="float32")throw new Error("Conv input(X,W) should be float tensor");if(g.length===3&&g[2].type!=="float32")throw new Error("Conv input(bias) should be float tensor")}},5193:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseDepthToSpaceAttributes=n.depthToSpace=void 0;const u=a(3738);n.depthToSpace=(f,s,h)=>{c(s);const p=h.blocksize,l=p*p,o=h.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],t=h.mode==="DCR"?[s[0].dims[0],p,p,s[0].dims[1]/l,s[0].dims[2],s[0].dims[3]]:[s[0].dims[0],s[0].dims[1]/l,p,p,s[0].dims[2],s[0].dims[3]],e=f.reshapeUnpacked(s[0],t),r={perm:o,cacheKey:`${o}`},[i]=(0,u.transpose)(f,[e],r),d=[s[0].dims[0],s[0].dims[1]/l,s[0].dims[2]*p,s[0].dims[3]*p];return[f.reshapeUnpacked(i,d)]},n.parseDepthToSpaceAttributes=f=>{const s=f.attributes.getInt("blocksize");if(s<1)throw new Error(`blocksize must be >= 1, but got : ${s} for DepthToSpace`);const h=f.attributes.getString("mode","DCR");if(h!=="DCR"&&h!=="CRD")throw new Error(`unrecognized mode: ${h} for DepthToSpace`);return{mode:h,blocksize:s}};const c=f=>{if(f.length!==1)throw new Error(`DepthToSpace expect 1 inputs, but got ${f.length}`);if(f[0].type==="string"||f[0].dims.length!==4)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}},9828:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createDotProductProgramInfoLoader=void 0;const u=a(2517),c=a(5060),f=a(2039),s=a(2823),h=a(3248);n.createDotProductProgramInfoLoader=(p,l,o,t)=>{const e=((r,i)=>({name:"ConvDotProduct",inputNames:r?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:r?[f.TextureType.unpacked,f.TextureType.packedLastDimension,f.TextureType.unpacked]:[f.TextureType.unpacked,f.TextureType.packedLastDimension],cacheKey:i.activationCacheKey}))(l.length>2,t);return Object.assign(Object.assign({},e),{get:()=>((r,i,d,g,m)=>{const _=d[0].dims,y=d[1].dims,T=[y[0],Math.ceil(_[1]*y[2]*y[3]/4)],w=(0,h.calculateIm2ColDims)(_,y,g),[S,O]=r.calculateTextureWidthAndHeight(T,f.TextureType.packedLastDimension),E=u.ShapeUtil.computeStrides(w),[v,P]=r.calculateTextureWidthAndHeight(w,f.TextureType.packedLastDimension),L=g.length,V=d.length<3?"0.0":"_B(b)",R=Math.ceil(_[1]*y[2]*y[3]/4),{activationFunction:k,applyActivation:Y}=(0,s.getActivationSnippet)(m),C=(0,c.getGlsl)(r.session.backend.glContext.version),$=` +${k} +float process(int indices[${L}]) { + int b[1]; + b[0] = indices[1]; + int im2col[4]; + im2col[0] = indices[0]; + im2col[1] = indices[2]; + im2col[2] = indices[3]; + int im2colOffset = im2col[0] * ${E[0]} + im2col[1] * ${E[1]} + im2col[2] * ${E[2]}; + int kernelOffset = indices[1] * ${T[1]}; + float value = ${V}; + for (int i = 0; i < ${R}; ++i) { + vec2 im2colCoords = offsetToCoords(im2colOffset, ${v}, ${P}); + vec2 kernelCoords = offsetToCoords(kernelOffset, ${S}, ${O}); + value += dot(${C.texture2D}(Im2Col, im2colCoords), ${C.texture2D}(K, kernelCoords)); + ++im2colOffset; + ++kernelOffset; + } + ${Y} + return value; +}`;return Object.assign(Object.assign({},i),{output:{dims:g,type:d[0].type,textureType:f.TextureType.unpacked},shaderSource:$})})(p,e,l,o,t)})}},7992:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseFlattenAttributes=n.flatten=void 0;const u=a(2517);n.flatten=(f,s,h)=>{c(s,h);const p=u.ShapeUtil.flattenShape(s[0].dims,h);return[f.reshapeUnpacked(s[0],p)]},n.parseFlattenAttributes=f=>f.attributes.getInt("axis",1);const c=(f,s)=>{if(!f||f.length!==1)throw new Error("Flatten requires 1 input.");const h=f[0].dims.length;if(h===0)throw new Error("scalar tensor is not supported.");if(s<-h||s>h)throw new Error("Invalid axis");if(f[0].type==="string")throw new Error("string tensor is not supported.")}},2823:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInternalActivationAttributes=n.getActivationSnippet=void 0;const u=a(2517),c=a(4909);n.getActivationSnippet=function(f){let s;switch(f.activation){case"Relu":s=(0,c.glslRelu)();break;case"Sigmoid":s=(0,c.glslSigmoid)();break;case"Clip":s=(0,c.glslClip)(f.clipMin,f.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const h=s.name;return{activationFunction:s.body,applyActivation:`value = ${h}_(value);`}},n.parseInternalActivationAttributes=f=>{const s=f.getString("activation","");if(s==="Clip"){const[h,p]=f.getFloats("activation_params",[u.MIN_CLIP,u.MAX_CLIP]);return{activation:s,clipMax:p,clipMin:h,activationCacheKey:`${s}:${h},${p}`}}return{activation:s,activationCacheKey:s}}},1253:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGatherAttributes=n.gather=void 0;const u=a(246),c=a(782),f=a(2517),s=a(2039);n.gather=(o,t,e)=>(l(t,e.axis),[o.run(p(o,t,e),t)]),n.parseGatherAttributes=o=>(0,u.createAttributeWithCacheKey)({axis:o.attributes.getInt("axis",0)});const h={name:"Gather",inputNames:["A","B"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked]},p=(o,t,e)=>{const r=Object.assign(Object.assign({},h),{cacheHint:e.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((i,d,g,m)=>{const _=g[0].dims.slice(),y=g[1].dims.slice(),T=new Array(_.length+y.length-1);m=f.ShapeUtil.normalizeAxis(m,_.length);const w=[];for(let O=0;O{if(!o||o.length!==2)throw new Error("Gather requires 2 inputs.");const e=o[0].dims.length;if(e<1)throw new Error("Invalid input shape.");if(t<-e||t>e-1)throw new Error("Invalid axis.");if(c.NUMBER_TYPES.indexOf(o[0].type)===-1)throw new Error("Invaid input type.");if(o[1].type!=="int32"&&o[1].type!=="int16")throw new Error("Invaid input type.")}},4776:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGemmAttributesV11=n.parseGemmAttributesV7=n.gemm=void 0;const u=a(246),c=a(2517),f=a(2039);n.gemm=(o,t,e)=>(l(t,e),[o.run(h(t,e),t)]);const s=(o,t)=>{const e=o.attributes.getInt("transA",0)!==0,r=o.attributes.getInt("transB",0)!==0,i=o.attributes.getFloat("alpha",1),d=o.attributes.getFloat("beta",1);return(0,u.createAttributeWithCacheKey)({transA:e,transB:r,alpha:i,beta:d,isOptionalC:t})};n.parseGemmAttributesV7=o=>s(o,!1),n.parseGemmAttributesV11=o=>s(o,!0);const h=(o,t)=>{const e={name:"Gemm",inputNames:o.length===3?["A","B","C"]:["A","B"],inputTypes:o.length===3?[f.TextureType.unpacked,f.TextureType.unpacked,f.TextureType.unpacked]:[f.TextureType.unpacked,f.TextureType.unpacked],key:t.cacheKey};return Object.assign(Object.assign({},e),{get:()=>p(e,o,t)})},p=(o,t,e)=>{const r=t[0].dims.slice(),i=t[1].dims.slice(),[d,g]=c.GemmUtil.getShapeOfGemmResult(r,e.transA,i,e.transB,t.length===3?t[2].dims:void 0),m=[d,g];if(!m)throw new Error("Can't use gemm on the given tensors");let _=r[r.length-1],y="";e.transA&&(_=r[0]),e.transA&&e.transB?y="value += _A_T(a) * _B_T(b);":e.transA&&!e.transB?y="value += _A_T(a) * _B(b);":!e.transA&&e.transB?y="value += _A(a) * _B_T(b);":e.transA||e.transB||(y="value += _A(a) * _B(b);");const T=m.length,w=` + float process(int indices[${T}]) { + int a[${T}]; + int b[${T}]; + ${t.length===3?`int c[${t[2].dims.length}];`:""} + + copyVec(indices, a); + copyVec(indices, b); + ${t.length===3?"bcastIndices_C(indices, c);":""} + + float value = 0.0; + for (int k=0; k<${_}; ++k) { + a[${T-1}] = k; + b[${T-2}] = k; + ${y} + } + + value = value * alpha; + ${t.length===3?"value += beta * _C(c);":""} + return value; + }`;return Object.assign(Object.assign({},o),{output:{dims:m,type:t[0].type,textureType:f.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:e.alpha},{name:"beta",type:"float",data:e.beta}],shaderSource:w})},l=(o,t)=>{if(!o)throw new Error("Input is missing");if(t.isOptionalC&&(o.length<2||o.length>3))throw new Error("Invaid input shape.");if(!t.isOptionalC&&o.length!==3)throw new Error("Gemm requires 3 inputs");if(o.length===3&&o[2].dims.length!==1&&o[2].dims.length!==2)throw new Error("Invalid input shape of C");if(o[0].type!=="float32"&&o[0].type!=="float64"||o[1].type!=="float32"&&o[1].type!=="float64"||o.length===3&&o[2].type!=="float32"&&o[2].type!=="float64")throw new Error("Invalid input type.");if(o[0].type!==o[1].type||o.length===3&&o[0].type!==o[2].type)throw new Error("Input types are mismatched")}},8555:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedIm2ColProgramInfoLoader=void 0;const u=a(5060),c=a(2039),f=a(2827);n.createPackedIm2ColProgramInfoLoader=(s,h,p,l,o)=>{const t=(e=o.cacheKey,{name:"Im2Col (packed)",inputNames:["A"],inputTypes:[c.TextureType.packed],cacheHint:e});var e;return Object.assign(Object.assign({},t),{get:()=>((r,i,d,g,m,_)=>{const y=d.dims,T=g.dims,w=m.length,S=[T[1]*T[2]*T[3],m[2]*m[3]],O=T[2]*T[3],E=(0,f.unpackFromChannel)(),v=(0,u.getGlsl)(r.session.backend.glContext.version);let P="";for(let V=0;V<=1;V++)for(let R=0;R<=1;R++)P+=` + blockIndex = rc.x + ${R}; + pos = rc.y + ${V}; + + if(blockIndex < ${S[1]} && pos < ${S[0]}) { + offsetY = int(blockIndex / (${m[w-1]})) * ${_.strides[0]} - + ${_.pads[0]}; + d0 = offsetY + ${_.dilations[0]} * (imod(pos, ${O}) / ${T[2]}); + + if(d0 < ${y[2]} && d0 >= 0) { + offsetX = imod(blockIndex, ${m[w-1]}) * ${_.strides[1]} - + ${_.pads[1]}; + d1 = offsetX + ${_.dilations[1]} * imod(imod(pos, ${O}), ${T[2]}); + + if(d1 < ${y[3]} && d1 >= 0) { + + ch = int(float(pos)/ ${O}.); + innerDims = vec2(d0, d1); + result[${2*V+R}] = getChannel( + getA(0, ch, int(innerDims.x), + int(innerDims.y)), innerDims); + } + } + } + + `;const L=` + ${E} + + void main() { + ivec2 rc = getOutputCoords(); + vec4 result = vec4(0.0); + int blockIndex, pos, offsetY, d0, offsetX, d1, ch; + vec2 innerDims; + ${P} + ${v.output} = result; + } + `;return Object.assign(Object.assign({},i),{output:{dims:S,type:d.type,textureType:c.TextureType.packed},shaderSource:L,hasMain:!0})})(s,t,h,p,l,o)})}},3248:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.calculateIm2ColDims=n.createIm2ColProgramInfoLoader=void 0;const u=a(2039);n.createIm2ColProgramInfoLoader=(c,f,s,h,p)=>{const l=(o=p.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[u.TextureType.unpacked],cacheHint:o});var o;return Object.assign(Object.assign({},l),{get:()=>((t,e,r,i,d,g)=>{const m=r.dims,_=i.dims,y=d.length,T=(0,n.calculateIm2ColDims)(m,_,d,4),w=` + const int XC = ${m[1]}; + const int XH = ${m[2]}; + const int XW = ${m[3]}; + const int KH = ${g.kernelShape[0]}; + const int KW = ${g.kernelShape[1]}; + const int dilationH = ${g.dilations[0]}; + const int dilationW = ${g.dilations[1]}; + const int strideH = ${g.strides[0]}; + const int strideW = ${g.strides[1]}; + const int padH = ${g.pads[0]}; + const int padW = ${g.pads[1]}; + const int KHKW = KH*KW; + const int XCKHKW = XC * KHKW; + const int outputChannels = 4; + vec4 process(int indices[${y}]) { + int b = indices[0]; // batch size + int oh = indices[1] * strideH - padH; //output height + int ow = indices[2] * strideW - padW; //output width + int p = indices[3] * outputChannels; //patch + vec4 value = vec4(0.0); + for(int i=0; i < outputChannels; ++i) { + if(p < XCKHKW) { + int patchC = p / KHKW; + int patchH = (p - patchC*KHKW) / KW; + int patchW = (p - patchC*KHKW) - patchH * KW; + int xh2 = oh + patchH * dilationH; + int xw2 = ow + patchW * dilationW; + int x[${m.length}]; + x[0] = b; + x[1] = patchC; + x[2] = xh2; + x[3] = xw2; + if(xh2 >= 0 && + xh2 < XH && + xw2 >= 0 && + xw2 < XW) { + value[i] = _X(x); + } + } + ++p; + } + return value; + } + `;return Object.assign(Object.assign({},e),{output:{dims:T,type:r.type,textureType:u.TextureType.packedLastDimension},shaderSource:w})})(0,l,f,s,h,p)})},n.calculateIm2ColDims=(c,f,s,h=4)=>[s[0],s[2],s[3],Math.ceil(c[1]*f[2]*f[3]/h)]},6572:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseImageScalerAttributes=n.imageScaler=void 0;const u=a(246),c=a(2039);n.imageScaler=(l,o,t)=>(p(o),[l.run(s(l,o,t),o)]),n.parseImageScalerAttributes=l=>{const o=l.attributes.getFloat("scale"),t=l.attributes.getFloats("bias");return(0,u.createAttributeWithCacheKey)({scale:o,bias:t})};const f={name:"ImageScaler",inputNames:["X"],inputTypes:[c.TextureType.unpacked]},s=(l,o,t)=>{const e=Object.assign(Object.assign({},f),{cacheHint:t.cacheKey});return Object.assign(Object.assign({},e),{get:()=>((r,i,d,g)=>{const m=d[0].dims.slice(),_=m.length,y=` + ${h(g.bias.length)} + float process(int indices[${_}]) { + return _X(indices) * scale + getBias(bias, indices[1]); + }`;return Object.assign(Object.assign({},i),{output:{dims:m,type:d[0].type,textureType:c.TextureType.unpacked},variables:[{name:"bias",type:"float",arrayLength:g.bias.length,data:g.bias},{name:"scale",type:"float",data:g.scale}],shaderSource:y})})(0,e,o,t)})},h=l=>{const o=[`float getBias(float bias[${l}], int channel) {`];for(let t=0;t{if(!l||l.length!==1)throw new Error("ImageScaler requires 1 input.");if(l[0].dims.length!==4)throw new Error("Invalid input shape.");if(l[0].type!=="float32"&&l[0].type!=="float64")throw new Error("Invalid input type.")}},3346:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInstanceNormalizationAttributes=n.instanceNormalization=void 0;const u=a(5060),c=a(2039);n.instanceNormalization=(o,t,e)=>{l(t);const r=o.run(s(t[0]),t);return[o.run(p(o,t[0],e,r.dims),[t[0],r,t[1],t[2]])]},n.parseInstanceNormalizationAttributes=o=>o.attributes.getFloat("epsilon",1e-5);const f={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[c.TextureType.unpacked]},s=o=>Object.assign(Object.assign({},f),{get:()=>((t,e)=>{const r=e.dims.slice(),i=r[1],d=r[2]*r[3],g=[r[0],i],m=` + vec4 process(int[2] indices) { + vec4 v = vec4(0.0); + int a[4]; + a[0] = indices[0]; + a[1] = indices[1]; + float temp = 0.0; + for(int a2=0; a2<${r[2]}; a2++) { + a[2] = a2; + for(int a3=0; a3<${r[3]}; a3++) { + a[3] = a3; + float x = _X(a); + temp += x; + } + } + float mean = temp / float(${d}); + temp = 0.0; + for(int a2=0; a2<${r[2]}; a2++) { + a[2] = a2; + for(int a3=0; a3<${r[3]}; a3++) { + a[3] = a3; + float x = _X(a); + temp += (x - mean) * (x - mean); + } + } + v.r = mean; + v.g = temp / float(${d}); + + return v; + }`;return Object.assign(Object.assign({},t),{output:{dims:g,type:e.type,textureType:c.TextureType.packedLastDimension},shaderSource:m})})(f,o)}),h={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[c.TextureType.unpacked,c.TextureType.packedLastDimension,c.TextureType.unpacked,c.TextureType.unpacked]},p=(o,t,e,r)=>{const i=Object.assign(Object.assign({},h),{cacheHint:`${e}`});return Object.assign(Object.assign({},i),{get:()=>((d,g,m,_,y)=>{const T=(0,u.getGlsl)(d.session.backend.glContext.version),[w,S]=d.calculateTextureWidthAndHeight(y,c.TextureType.packedLastDimension),[O,E]=[w/4,S],v=` + vec4 get_MeanAndVariance(int[2] mv) { + int offset = indicesToOffset_MeanAndVariance(mv); + vec2 coords = offsetToCoords(offset, ${O}, ${E}); + return ${T.texture2D}(MeanAndVariance, coords); + } + + float process(int[4] indices) { + int mv[2]; + mv[0] = indices[0]; + mv[1] = indices[1]; + vec4 mean_and_variance = get_MeanAndVariance(mv); + float mean = mean_and_variance.r; + float variance = mean_and_variance.g; + + int sb[1]; + sb[0] = indices[1]; + float scale = _Scale(sb); + float b = _B(sb); + + return scale * (_X(indices) - mean) / sqrt(variance + epsilon) + b; + }`;return Object.assign(Object.assign({},g),{output:{dims:m.dims,type:m.type,textureType:c.TextureType.unpacked},variables:[{name:"epsilon",type:"float",data:_}],shaderSource:v})})(o,i,t,e,r)})},l=o=>{if(!o||o.length!==3)throw new Error("InstanceNormalization requires 3 inputs.");const t=o[0],e=o[1],r=o[2];if(t.dims.length<3||e.dims.length!==1||r.dims.length!==1)throw new Error("Invalid input shape.");if(e.dims[0]!==t.dims[1]||r.dims[0]!==t.dims[1])throw new Error("Input shapes are mismatched.");if(t.type!=="float32"&&t.type!=="float64"||e.type!=="float32"&&e.type!=="float64"||r.type!=="float32"&&r.type!=="float64")throw new Error("Invalid input type.");if(o[0].dims.length!==4)throw new Error("Only support 4-D input 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outputValue = getA(${Ie}); + return outputValue; +} + +vec4 getBAtOutCoordsMatmul(int i) { + ${Te} coords = getOutputCoords(); + ${Ve} + ${Ge} + vec4 outputValue = getB(${Le}); + return outputValue; +}`}(k,C,m,O)}`:"",J=E?"getAAtOutCoordsMatmul(i)":`getA(${function(Te,se){let ye="";for(let be=0;be{Object.defineProperty(n,"__esModule",{value:!0}),n.getBiasForMatmul=n.createMatmulProgramInfoLoader=n.parseMatMulAttributes=n.matMul=void 0;const u=a(2517),c=a(2039),f=a(9390),s=a(2823),h=a(708);function p(t,e){const r=(i=t.length>2,d=e.activationCacheKey,{name:"MatMul",inputNames:i?["A","B","Bias"]:["A","B"],inputTypes:i?[c.TextureType.unpacked,c.TextureType.unpacked,c.TextureType.unpacked]:[c.TextureType.unpacked,c.TextureType.unpacked],cacheHint:d});var i,d;return Object.assign(Object.assign({},r),{get:()=>function(g,m,_){const y=m[0].dims,T=m[1].dims,w=u.BroadcastUtil.calcShape(y,T,!0);if(!w)throw new Error("Can't use matmul on the given tensors");const S=(0,f.getCoordsDataType)(w.length),O=(0,f.getGlChannels)(),{activationFunction:E,applyActivation:v}=(0,s.getActivationSnippet)(_),P=m.length>2,L=P?"value += getBiasForMatmul();":"",V=P?`${o(S,O,m[2].dims,w,!1)}`:"",R=w.length,k=y.length,Y=T.length,C=` + ${E} + ${V} + float process(int indices[${R}]) { + int a[${k}]; + int b[${Y}]; + bcastMatmulIndices_A(indices, a); + bcastMatmulIndices_B(indices, b); + + float value; + for (int k=0; k<${y[y.length-1]}; ++k) { + a[${k-1}] = k; + b[${Y-2}] = k; + value += _A(a) * _B(b); + } + ${L} + ${v} + return value; + }`;return Object.assign(Object.assign({},g),{output:{dims:w,type:m[0].type,textureType:c.TextureType.unpacked},shaderSource:C})}(r,t,e)})}n.matMul=(t,e,r)=>(l(e),t.session.pack?[t.run((0,h.createPackedMatmulProgramInfoLoader)(t,e,r),e)]:[t.run(p(e,r),e)]),n.parseMatMulAttributes=t=>(0,s.parseInternalActivationAttributes)(t.attributes),n.createMatmulProgramInfoLoader=p;const l=t=>{if(!t||t.length!==2)throw new Error("MatMul requires 2 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+}`}n.getBiasForMatmul=o},2403:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackProgramInfoLoader=void 0;const u=a(5060),c=a(2039),f=a(9390),s=a(2827),h={name:"pack",inputNames:["A"],inputTypes:[c.TextureType.unpackedReversed]};n.createPackProgramInfoLoader=(p,l)=>Object.assign(Object.assign({},h),{get:()=>((o,t)=>{const e=(0,u.getGlsl)(o.session.backend.glContext.version),r=t.dims,i=r.length,d=t.dims.length,g=(0,f.getCoordsDataType)(d),m=(0,s.getChannels)("rc",d),_=(y=d,T=m,w=r[r.length-2],S=r[r.length-1],y===0||y===1?"":` + int r = ${T[y-2]}; + int c = ${T[y-1]}; + int rp1 = ${T[y-2]} + 1; + int cp1 = ${T[y-1]} + 1; + bool rEdge = rp1 >= ${S}; + bool cEdge = cp1 >= ${w}; + `);var y,T,w,S;let O;O=i===0?[1,1]:i===1?[r[0],1]:[r[d-1],r[d-2]];const E=function(L,V,R){if(L===0)return"false";if(L===1)return`rc > ${V[0]}`;let k="";for(let Y=L-2;Y= ${V[Y-L+2]}`,Y= ${L[0]} ? 0. : getA(rc + 1), + 0, 0`;let k="";if(R>2)for(let Y=0;Y{Object.defineProperty(n,"__esModule",{value:!0}),n.unpackFromChannel=n.getChannels=n.getVecChannels=void 0;const u=a(9390);function c(f,s){return(0,u.getGlChannels)(s).map(h=>`${f}.${h}`)}n.getVecChannels=c,n.getChannels=function(f,s){return s===1?[f]:c(f,s)},n.unpackFromChannel=function(){return` + float getChannel(vec4 frag, int dim) { + int modCoord = imod(dim, 2); + return modCoord == 0 ? frag.r : frag.g; + } + + float getChannel(vec4 frag, vec2 innerDims) { + vec2 modCoord = mod(innerDims, 2.); + return modCoord.x == 0. ? + (modCoord.y == 0. ? frag.r : frag.g) : + (modCoord.y == 0. ? frag.b : frag.a); + } + `}},2870:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parsePadAttributesV11=n.padV11=n.parsePadAttributesV2=n.padV2=void 0;const 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indices) { + return padA(indices); + }`;return{name:"Pad",inputNames:["A"],inputTypes:[s.TextureType.unpacked],output:{dims:y,type:m.type,textureType:s.TextureType.unpacked},shaderSource:w}},o=g=>{if(!g||g.length!==1)throw new Error("Pad requires 1 input");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type.")},t=g=>{if(!g||g.length!==2&&g.length!==3)throw new Error("Pad requires 2 or 3 inputs");if(g[1].type!=="int32")throw new Error("Invalid input type.");if(g.length>=3&&g[2].type==="string")throw new Error("Invalid input type.")},e=(g,m,_)=>{const y=(0,f.getGlsl)(g.session.backend.glContext.version),[T,w]=g.calculateTextureWidthAndHeight(m.dims,s.TextureType.unpacked),S=c.ShapeUtil.computeStrides(m.dims);switch(_.mode){case"constant":return r(y,m.dims,S,T,w,_.pads,_.value);case"reflect":return i(y,m.dims,S,T,w,_.pads);case"edge":return d(y,m.dims,S,T,w,_.pads);default:throw new Error("Invalid mode")}},r=(g,m,_,y,T,w,S)=>{const O=m.length;let E="";for(let v=O-1;v>=0;--v)E+=` + k = m[${v}] - ${w[v]}; + if (k < 0) return constant; + if (k >= ${m[v]}) return constant; + offset += k * ${_[v]}; + `;return` + float padA(int m[${O}]) { + const float constant = float(${S}); + int offset = 0; + int k = 0; + ${E} + vec2 coords = offsetToCoords(offset, ${y}, ${T}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `},i=(g,m,_,y,T,w)=>{const S=m.length;let O="";for(let E=S-1;E>=0;--E)O+=` + k = m[${E}] - ${w[E]}; + if (k < 0) { k = -k; } + { + const int _2n_1 = ${2*(m[E]-1)}; + k = int( mod( float(k), float(_2n_1) ) ) ; + if(k >= ${m[E]}) { k = _2n_1 - k; } + } + offset += k * ${_[E]}; + `;return` + float padA(int m[${S}]) { + int offset = 0; + int k = 0; + ${O} + vec2 coords = offsetToCoords(offset, ${y}, ${T}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `},d=(g,m,_,y,T,w)=>{const S=m.length;let O="";for(let E=S-1;E>=0;--E)O+=` + k = m[${E}] - ${w[E]}; + if (k < 0) k = 0; + if (k >= ${m[E]}) k = ${m[E]-1}; + offset += k * ${_[E]}; + `;return` + float padA(int m[${S}]) { + int offset = 0; + int k = 0; + ${O} + vec2 coords = offsetToCoords(offset, ${y}, ${T}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `}},2143:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.globalMaxPool=n.parseMaxPoolAttributes=n.maxPool=n.parseGlobalAveragePoolAttributes=n.globalAveragePool=n.parseAveragePoolAttributes=n.averagePool=void 0;const u=a(246),c=a(2517),f=a(2039);n.averagePool=(d,g,m)=>{t(g);const _={name:"AveragePool",inputNames:["X"],inputTypes:[f.TextureType.unpacked],cacheHint:m.cacheKey};return[d.run(Object.assign(Object.assign({},_),{get:()=>s(g,_,!1,m)}),g)]},n.parseAveragePoolAttributes=d=>{const g=d.attributes.getString("auto_pad","NOTSET"),m=d.attributes.getInt("ceil_mode",0),_=d.attributes.getInt("count_include_pad",0)!==0,y=d.attributes.getInts("kernel_shape"),T=d.attributes.getInts("strides",[]),w=d.attributes.getInts("pads",[]);if(m!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,u.createAttributeWithCacheKey)({autoPad:g,ceilMode:m,countIncludePad:_,kernelShape:y,strides:T,pads:w})};const s=(d,g,m,_)=>{const[y,T]=p(d,_,m),w=c.ShapeUtil.size(y.kernelShape);let S="";y.countIncludePad?S+=`value /= float(${w});`:S+=`value /= float(${w} - pad);`;const O=` + ${e(d[0].dims,y,"value += _X(x);",S,"0.0")} + `;return Object.assign(Object.assign({},g),{output:{dims:T,type:d[0].type,textureType:f.TextureType.unpacked},shaderSource:O})};n.globalAveragePool=(d,g,m)=>{t(g);const _={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[f.TextureType.unpacked],cacheHint:`${m.countIncludePad}`};return[d.run(Object.assign(Object.assign({},_),{get:()=>s(g,_,!0,m)}),g)]},n.parseGlobalAveragePoolAttributes=d=>{const g=d.attributes.getInt("count_include_pad",0)!==0;return(0,u.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:g,kernelShape:[],strides:[],pads:[]})},n.maxPool=(d,g,m)=>{t(g);const _={name:"MaxPool",inputNames:["X"],inputTypes:[f.TextureType.unpacked],cacheHint:m.cacheKey};return[d.run(Object.assign(Object.assign({},_),{get:()=>h(g,_,!1,m)}),g)]},n.parseMaxPoolAttributes=d=>{const g=d.attributes.getString("auto_pad","NOTSET"),m=d.attributes.getInt("ceil_mode",0),_=d.attributes.getInts("kernel_shape"),y=d.attributes.getInts("strides",[]),T=d.attributes.getInts("pads",[]),w=d.attributes.getInt("storage_order",0),S=d.attributes.getInts("dilations",[]);if(w!==0)throw new Error("column major storage order is not yet supported for 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y?Object.assign(v,{kernelShape:T,strides:w,pads:O,dilations:S,cacheKey:g.cacheKey}):Object.assign(v,{kernelShape:T,strides:w,pads:O,cacheKey:g.cacheKey}),[v,E]},l={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},o={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[f.TextureType.unpacked]};n.globalMaxPool=(d,g)=>(t(g),[d.run(Object.assign(Object.assign({},o),{get:()=>h(g,o,!0,l)}),g)]);const t=d=>{if(!d||d.length!==1)throw new Error("Pool ops requires 1 input.");if(d[0].type!=="float32"&&d[0].type!=="float64")throw new Error("Invalid input type.")},e=(d,g,m,_,y)=>{const T=d.length;if(g.kernelShape.length<=2){const w=g.kernelShape[g.kernelShape.length-1],S=g.strides[g.strides.length-1],O=g.pads[g.pads.length/2-1],E=g.pads[g.pads.length-1],v=d[T-1];let P="",L="",V="";if(P=O+E!==0?` + for (int i = 0; i < ${w}; i++) { + x[${T} - 1] = indices[${T} - 1] * ${S} - ${O} + i; + if (x[${T} - 1] < 0 || x[${T} - 1] >= ${v}) { + pad++; + continue; + } + ${m} + }`:` + for (int i = 0; i < ${w}; i++) { + x[${T} - 1] = indices[${T} - 1] * ${S} - ${O} + i; + ${m} + }`,g.kernelShape.length===2){const R=g.kernelShape[g.kernelShape.length-2],k=g.strides[g.strides.length-2],Y=g.pads[g.pads.length/2-2],C=g.pads[g.pads.length-2],$=d[T-2];L=Y+C!==0?` + for (int j = 0; j < ${R}; j++) { + x[${T} - 2] = indices[${T} - 2] * ${k} - ${Y} + j; + if (x[${T} - 2] < 0 || x[${T} - 2] >= ${$}) { + pad+= ${w}; + continue; + } + `:` + for (int j = 0; j < ${R}; j++) { + x[${T} - 2] = indices[${T} - 2] * ${k} - ${Y} + j; + `,V=` + } + `}return` + float process(int indices[${T}]) { + int x[${T}]; + copyVec(indices, x); + + float value = ${y}; + int pad = 0; + ${L} + ${P} + ${V} + ${_} + return value; + } + `}{const w=c.ShapeUtil.size(g.kernelShape),S=c.ShapeUtil.computeStrides(g.kernelShape),O=S.length,E=g.pads.length,v=i(O),P=r(d,"inputDims"),L=r(g.pads,"pads"),V=r(S,"kernelStrides"),R=r(g.strides,"strides");let k="";return k=g.pads.reduce((Y,C)=>Y+C)?` + if (x[j] >= inputDims[j] || x[j] < 0) { + pad++; + isPad = true; + break; + } + } + if (!isPad) { + ${m} + }`:` + } + ${m} + `,` + ${v} + float process(int indices[${T}]) { + int x[${T}]; + copyVec(indices, x); + int offset[${O}]; + int pads[${E}]; + int inputDims[${T}]; + int kernelStrides[${O}]; + int strides[${O}]; + ${L} + ${P} + ${R} + ${V} + + float value = ${y}; + int pad = 0; + bool isPad = false; + for (int i = 0; i < ${w}; i++) { + offsetToIndices(i, kernelStrides, offset); + isPad = false; + for (int j = ${T} - ${O}; j < ${T}; j++) { + x[j] = indices[j] * strides[j - ${T} + ${O}] + + offset[j - ${T} + ${O}] - pads[j - 2]; + ${k} + } + ${_} + + return value; + } + `}},r=(d,g)=>{let m="";for(let _=0;_` + void offsetToIndices(int offset, int[${d}] strides, out int[${d}] indices) { + if (${d} == 0) { + return; + } + for (int i = 0; i < ${d} - 1; ++i) { + indices[i] = offset / strides[i]; + offset -= indices[i] * strides[i]; + } + indices[${d} - 1] = offset; + }`},4939:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.reduceLogSumSquare=n.reduceLogSum=n.reduceProd=n.reduceMin=n.reduceMax=n.reduceMean=n.reduceSum=n.parseReduceAttributes=void 0;const u=a(246),c=a(782),f=a(2517),s=a(2039),h=(o,t,e,r,i)=>{l(t);const d={name:r,inputNames:["A"],inputTypes:[s.TextureType.unpacked]};return[o.run(Object.assign(Object.assign({},d),{cacheHint:e.cacheKey,get:()=>p(o,t,e,r,i,d)}),t)]};n.parseReduceAttributes=o=>{const t=o.attributes.getInts("axes",[]),e=o.attributes.getInt("keepdims",1)===1;return(0,u.createAttributeWithCacheKey)({axes:t,keepDims:e})};const p=(o,t,e,r,i,d)=>{const g=[],m=t[0].dims.length||1,_=[],y=f.ShapeUtil.normalizeAxes(e.axes,t[0].dims.length),T=i(t,y);let w=T[1];for(let O=0;O=0||y.length===0?(e.keepDims&&g.push(1),w=` + for(int j${O} = 0; j${O} < ${t[0].dims[O]}; j${O}++) { + inputIdx[${O}] = j${O}; + ${w} + }`):(_.push(`inputIdx[${O}] = outputIdx[${g.length}];`),g.push(t[0].dims[O]));const S=` + float process(int outputIdx[${g.length||1}]) { + float value; // final result + int inputIdx[${m}]; // addressing input data + ${_.join(` +`)} + ${T[0]} // init ops for reduce max/min + ${w} + ${T[2]} // final computation for reduce mean + return value; + }`;return Object.assign(Object.assign({},d),{output:{dims:g,type:t[0].type,textureType:s.TextureType.unpacked},shaderSource:S})},l=o=>{if(!o||o.length!==1)throw new Error("Reduce op requires 1 input.");if(c.NUMBER_TYPES.indexOf(o[0].type)===-1)throw new Error("Invalid input type.")};n.reduceSum=(o,t,e)=>h(o,t,e,"ReduceSum",()=>["value = 0.0;","value += _A(inputIdx);",""]),n.reduceMean=(o,t,e)=>h(o,t,e,"ReduceMean",(r,i)=>{let d=1;for(let g=0;g=0||i.length===0)&&(d*=r[0].dims[g]);return["value = 0.0;","value += _A(inputIdx);",`value /= ${d}.;`]}),n.reduceMax=(o,t,e)=>h(o,t,e,"ReduceMax",(r,i)=>{const d=[];for(let g=0;g=0||i.length===0)&&d.push(`inputIdx[${g}] = 0;`);return[`${d.join(` +`)} +value = _A(inputIdx);`,"value = max(value, 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d=e.dims,g=i;let m="";for(let T=0;T<4;T++){let w="";switch(T){case 0:w="outputCoords = rc;";break;case 1:w="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:w="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:w="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}m+=` + ${w} + ${T>0?"if(outputCoords.y < rows && outputCoords.z < cols){":""} + int flattenedIndex = getFlattenedIndex(outputCoords); + + ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex); + vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z)); + + result[${T}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims); + + ${T>0?"}":""} + `}const _=(0,c.getGlsl)(t.session.backend.glContext.version),y=` + ${function(T){const w=u.ShapeUtil.computeStrides(T),S=["b","r","c"],O="index";return` + ivec3 inputCoordsFromReshapedOutCoords(int index) { + ${w.map((E,v)=>`int ${S[v]} = ${O} / ${E}; ${v===w.length-1?`int ${S[v+1]} = ${O} - ${S[v]} * ${E}`:`index -= ${S[v]} * ${E}`};`).join("")} + return ivec3(b, r, c); + } + `}(d)} + ${function(T){const w=u.ShapeUtil.computeStrides(T);return` + int getFlattenedIndex(ivec3 coords) { + // reverse y, z order + return coords.x * ${w[0]} + coords.z * ${w[1]} + coords.y; + } +`}(g)} + ${(0,s.unpackFromChannel)()} + + void main() { + ivec3 rc = getOutputCoords(); + + vec4 result = vec4(0.0); + + ivec3 outputCoords; + int rows = ${g[2]}; + int cols = ${g[1]}; + + ${m} + ${_.output} = result; + } + `;return Object.assign(Object.assign({},r),{output:{dims:g,type:e.type,textureType:f.TextureType.packed},shaderSource:y,hasMain:!0})})(h,p,o,l)})},n.processDims3D=function(h){if(h.length===0)return[1,1,1];let p=1;for(let l=0;l1?h[h.length-2]:1,h[h.length-1]]},n.isReshapeCheap=function(h,p){let l=!1;return l=h.length===0||p.length===0||(h.length<2||p.length<2?h[h.length-1]===p[p.length-1]:h[h.length-1]===p[p.length-1]&&h[h.length-2]===p[p.length-2]),l}},718:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.reshape=void 0;const u=a(2517);n.reshape=(c,f)=>{const s=u.ShapeUtil.calculateReshapedDims(f[0].dims,f[1].integerData);return c.session.pack?[c.reshapePacked(f[0],s)]:[c.reshapeUnpacked(f[0],s)]}},2268:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseResizeAttributesV11=n.parseResizeAttributesV10=n.resize=void 0;const u=a(5060),c=a(2039),f=a(9390),s=a(2827),h=a(9793),p={name:"Resize",inputNames:["A"],inputTypes:[c.TextureType.packed]};n.resize=(r,i,d)=>((0,h.validateInputs)(i,d),[r.run(Object.assign(Object.assign({},p),{cacheHint:d.cacheKey,get:()=>l(r,i,d)}),i)]),n.parseResizeAttributesV10=r=>(0,h.parseUpsampleAttributes)(r,10),n.parseResizeAttributesV11=r=>(0,h.parseUpsampleAttributes)(r,11);const l=(r,i,d)=>{const g=(0,u.getGlsl)(r.session.backend.glContext.version),[m,_]=o(i,d);if(m.every(k=>k===1)&&d.coordinateTransformMode!=="tf_crop_and_resize")return Object.assign(Object.assign({},p),{output:{dims:_,type:i[0].type,textureType:c.TextureType.packed},hasMain:!0,shaderSource:`void main() { + vec4 v = ${g.texture2D}(X, TexCoords); + ${g.output} = v; + }`});const y=_.length;if(y<2)throw new Error(`output dimension should be at least 2, but got ${y}`);const T=_[y-2],w=_[y-1],S=i[0].dims;if(y!==S.length)throw new Error(`output dimension should match input ${S.length}, but got ${y}`);const O=S[y-2],E=S[y-1],v=m[y-2],P=m[y-1];let L="";if(d.mode!=="linear")throw new Error(`resize (packed) does not support mode: '${d.mode}'`);switch(d.coordinateTransformMode){case"asymmetric":L=` + vec4 getSourceFracIndex(ivec4 coords) { + return vec4(coords) / scaleWHWH; + } + `;break;case"half_pixel":L=` + vec4 getSourceFracIndex(ivec4 coords) { + return (vec4(coords) + 0.5) / scaleWHWH - 0.5; + } + `;break;case"pytorch_half_pixel":L=` + vec4 getSourceFracIndex(ivec4 coords) { + vec4 fcoords = vec4(coords); + return vec4( + ${w}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0, + ${T}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0, + ${w}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0, + ${T}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0 + ); + } + `;break;case"align_corners":L=` + vec4 getSourceFracIndex(ivec4 coords) { + vec4 resized = vec4(${w}.0 - 1.0, ${T}.0 - 1.0, ${w}.0 - 1.0, + ${T}.0 - 1.0); + vec4 original = vec4(${E}.0 - 1.0, ${O}.0 - 1.0, ${E}.0 - 1.0, + ${O}.0 - 1.0); + vec4 new_scale = original / resized; + return vec4(coords) * new_scale; + } + `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode: '${d.coordinateTransformMode}'`)}const V=(0,f.getCoordsDataType)(y),R=` + const vec2 inputWH = vec2(${O}.0, ${E}.0); + const vec4 scaleWHWH = vec4(float(${v}), float(${P}), float(${v}), float(${P})); + ${(0,s.unpackFromChannel)()} + ${L} + float getAValue(int x10, int r, int c, int d) { + return getChannel(getA(x10, r, c, d), vec2(c, d)); + } + void main() { + ${V} rc = getOutputCoords(); + + int batch = rc[0]; + int depth = rc[1]; + + // retrieve the 4 coordinates that is used in the 4 packed output values. + ivec4 coords = ivec4(rc.wz, rc.w + 1, rc.z + 1); + + // calculate the source index in fraction + vec4 sourceFrac = getSourceFracIndex(coords); + + // get the lower and upper bound of the 4 values that will be packed into one texel. + ivec4 x00 = ivec4(max(sourceFrac.xy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xy))); + ivec4 x01 = ivec4(max(sourceFrac.xw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xw))); + ivec4 x10 = ivec4(max(sourceFrac.zy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zy))); + ivec4 x11 = ivec4(max(sourceFrac.zw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zw))); + + bool hasNextRow = rc.w < ${T-1}; + bool hasNextCol = rc.z < ${w-1}; + + // pack x00, x01, x10, x11's top-left corner into one vec4 structure + vec4 topLeft = vec4( + getAValue(batch, depth, x00.x, x00.y), + hasNextCol ? getAValue(batch, depth, x01.x, x01.y) : 0.0, + hasNextRow ? getAValue(batch, depth, x10.x, x10.y) : 0.0, + (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.y) : 0.0); + + // pack x00, x01, x10, x11's top-right corner into one vec4 structure + vec4 topRight = vec4( + getAValue(batch, depth, x00.x, x00.w), + hasNextCol ? getAValue(batch, depth, x01.x, x01.w) : 0.0, + hasNextRow ? getAValue(batch, depth, x10.x, x10.w) : 0.0, + (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.w) : 0.0); + + // pack x00, x01, x10, x11's bottom-left corner into one vec4 structure + vec4 bottomLeft = vec4( + getAValue(batch, depth, x00.z, x00.y), + hasNextCol ? getAValue(batch, depth, x01.z, x01.y) : 0.0, + hasNextRow ? getAValue(batch, depth, x10.z, x10.y) : 0.0, + (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.y) : 0.0); + + // pack x00, x01, x10, x11's bottom-right corner into one vec4 structure + vec4 bottomRight = vec4( + getAValue(batch, depth, x00.z, x00.w), + hasNextCol ? getAValue(batch, depth, x01.z, x01.w) : 0.0, + hasNextRow ? getAValue(batch, depth, x10.z, x10.w) : 0.0, + (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.w) : 0.0); + + // calculate the interpolation fraction on u and v direction + vec4 frac = vec4(sourceFrac) - floor(sourceFrac); + vec4 clampFrac = clamp(frac, vec4(0.0), vec4(1.0)); + + vec4 top = mix(topLeft, topRight, clampFrac.ywyw); + vec4 bottom = mix(bottomLeft, bottomRight, clampFrac.ywyw); + vec4 newValue = mix(top, bottom, clampFrac.xxzz); + + ${g.output} = vec4(newValue); + } + `;return Object.assign(Object.assign({},p),{output:{dims:_,type:i[0].type,textureType:c.TextureType.packed},hasMain:!0,shaderSource:R})},o=(r,i)=>{const d=r[0].dims;let g,m=i.scales;if(m.length===0){const y=r[i.scalesInputIdx];if(y&&y.size!==0){if(r[i.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");m=t(y,i.mode,i.isResize)}else{const T=r[i.sizesInputIdx];if(!T||T.size===0)throw new Error("Either scales or sizes MUST be provided as input.");g=Array.from(T.integerData),m=e(g,d,i.mode,i.isResize)}}else if(r[i.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");const _=g||d.map((y,T)=>Math.floor(y*m[T]));return[m,_]},t=(r,i,d)=>{const g=Array.from(r.floatData);return(0,h.scalesValidation)(g,i,d),g},e=(r,i,d,g)=>{const m=i.length,_=new Array(m);for(let y=0,T=m;y{Object.defineProperty(n,"__esModule",{value:!0}),n.shape=void 0;const u=a(9162);n.shape=(f,s)=>(c(s),[new u.Tensor([s[0].dims.length],"int32",void 0,void 0,new Int32Array(s[0].dims))]);const c=f=>{if(!f||f.length!==1)throw new Error("Shape requires 1 input.")}},2278:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.sliceV10=n.parseSliceAttributes=n.slice=void 0;const u=a(246),c=a(782),f=a(2517),s=a(2039),h={name:"Slice",inputNames:["A"],inputTypes:[s.TextureType.unpacked]};n.slice=(e,r,i)=>(l(r),[e.run(Object.assign(Object.assign({},h),{cacheHint:i.cacheKey,get:()=>p(e,r[0],i)}),r)]),n.parseSliceAttributes=e=>{const 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i=o(e,r);return[e.run(Object.assign(Object.assign({},h),{cacheHint:i.cacheKey,get:()=>p(e,r[0],i)}),[r[0]])]};const o=(e,r)=>{if(!e.session.isInitializer(r[1].dataId)||!e.session.isInitializer(r[2].dataId)||r.length>=4&&!e.session.isInitializer(r[3].dataId)||r.length>=5&&!e.session.isInitializer(r[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(r.length>=5&&r[4].integerData.some(m=>m!==1))throw new Error("currently non-1 steps is not supported for Slice");const i=Array.from(r[1].integerData),d=Array.from(r[2].integerData),g=r.length>=4?Array.from(r[3].integerData):[];return{starts:i,ends:d,axes:g,cacheKey:`${g};${i};${d}`}},t=e=>{if(!e||e.length<3||e.length>5)throw new Error("Invalid input number.");if(e[1].type!=="int32"||e[1].dims.length!==1)throw new Error("Invalid input type.");if(e[2].type!=="int32"||e[2].dims.length!==1)throw new Error("Invalid input type.");if(e.length>=4&&(e[3].type!=="int32"||e[3].dims.length!==1))throw new Error("Invalid input type.");if(e.length>=5&&(e[4].type!=="int32"||e[4].dims.length!==1))throw new Error("Invalid input type.")}},5524:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.softmaxV13=n.parseSoftmaxAttributesV13=n.parseSoftmaxAttributes=n.softmax=void 0;const u=a(246),c=a(2517),f=a(5060),s=a(2039),h=a(3738),p={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[s.TextureType.unpacked]},l={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked]},o={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked,s.TextureType.unpacked]};n.softmax=(g,m,_)=>{d(m);const y=m[0].dims.slice(),T=c.ShapeUtil.normalizeAxis(_.axis,y.length),w=c.ShapeUtil.sizeToDimension(y,T),S=c.ShapeUtil.sizeFromDimension(y,T);return t(g,m,_,w,S)},n.parseSoftmaxAttributes=g=>(0,u.createAttributeWithCacheKey)({axis:g.attributes.getInt("axis",1)}),n.parseSoftmaxAttributesV13=g=>(0,u.createAttributeWithCacheKey)({axis:g.attributes.getInt("axis",-1)}),n.softmaxV13=(g,m,_)=>{d(m);const y=m[0].dims.slice(),T=c.ShapeUtil.normalizeAxis(_.axis,y.length),w=y.length,S=T!==w-1,O=[];let E,v=[],P=[];S&&(v=Array.from({length:w}).map((k,Y)=>Y),v[T]=w-1,v[w-1]=T,v.map(k=>O.push(y[k])),E=(0,u.createAttributeWithCacheKey)({perm:v}),P=(0,h.transpose)(g,m,E));const L=S?c.ShapeUtil.sizeToDimension(O,w-1):c.ShapeUtil.sizeToDimension(y,w-1),V=S?c.ShapeUtil.sizeFromDimension(O,w-1):c.ShapeUtil.sizeFromDimension(y,w-1),R=t(g,S?P:m,_,L,V);return S?(0,h.transpose)(g,R,E):R};const t=(g,m,_,y,T)=>{const w=e(g,m[0],y,T,[y]),S=g.run(Object.assign(Object.assign({},p),{cacheHint:_.cacheKey,get:()=>w}),m),O=r(g,m[0],y,T,w.output.dims,[y]),E=g.run(Object.assign(Object.assign({},l),{cacheHint:_.cacheKey,get:()=>O}),[m[0],S]),v=i(g,m[0],y,T,w.output.dims,O.output.dims);return[g.run(Object.assign(Object.assign({},o),{cacheHint:_.cacheKey,get:()=>v}),[m[0],S,E])]},e=(g,m,_,y,T)=>{const[w,S]=g.calculateTextureWidthAndHeight(m.dims,s.TextureType.unpacked),O=T.length;if(_<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(T.length!==1)throw new Error("Dimensionality of the output should be 1");if(T[0]!==_)throw new Error("Shape of the output should be equal to logical row count");const E=(0,f.getGlsl)(g.session.backend.glContext.version),v=` + float process(int[${O}] indices) { + int logical_row_start_offset = indices[0] * ${y}; + + float max = getColorAsFloat(${E.texture2D}(A, offsetToCoords(logical_row_start_offset, ${w}, + ${S} ))); + for(int i=1; i<${y}; ++i) + { + float current = getColorAsFloat(${E.texture2D}(A, offsetToCoords(logical_row_start_offset + i, + ${w}, ${S}))); + if(current > max) + max = current; + } + + return max; + }`;return Object.assign(Object.assign({},p),{output:{dims:T,type:m.type,textureType:s.TextureType.unpacked},shaderSource:v})},r=(g,m,_,y,T,w)=>{const[S,O]=g.calculateTextureWidthAndHeight(m.dims,s.TextureType.unpacked),E=w.length;if(_<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(w.length!==1)throw new Error("Dimensionality of the output should be 1");if(w[0]!==_)throw new Error("Shape of the output should be equal to logical row count");if(T.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(T[0]!==_)throw new Error("Shape of the intermediate results should be equal to logical row count");const v=` + float process(int[${E}] indices) { + int logical_row_start_offset = indices[0] * ${y}; + + float norm_factor = 0.0; + float max = _Max(indices); + for(int i=0; i<${y}; ++i) + { + norm_factor += exp(getColorAsFloat(${(0,f.getGlsl)(g.session.backend.glContext.version).texture2D}(A, offsetToCoords(logical_row_start_offset + i, + ${S}, ${O}))) - max); + } + + return norm_factor; + }`;return Object.assign(Object.assign({},l),{output:{dims:w,type:m.type,textureType:s.TextureType.unpacked},shaderSource:v})},i=(g,m,_,y,T,w)=>{const[S,O]=g.calculateTextureWidthAndHeight(m.dims,s.TextureType.unpacked),E=m.dims.length;if(_<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(T.length!==1||w.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(T[0]!==_||w[0]!==_)throw new Error("Shape of the intermediate results should be equal to logical row count");const v=` + float process(int[${E}] indices) { + + // get offset of current logical tensor index from the 2-D texture coordinates (TexCoords) + int offset = coordsToOffset(TexCoords, ${S}, ${O}); + + //determine the logical row for this index + int logical_row_index[1]; + logical_row_index[0] = offset / ${y}; + + float norm_factor = _Norm(logical_row_index); + + // avoid possible division by 0 + // if norm_facor is 0, all elements are zero + // if so, return 0 + if(norm_factor == 0.0) + return 0.0; + + return exp(_A(indices) - _Max(logical_row_index)) / norm_factor; + }`;return Object.assign(Object.assign({},o),{output:{dims:m.dims,type:m.type,textureType:s.TextureType.unpacked},shaderSource:v})},d=g=>{if(!g||g.length!==1)throw new Error("Softmax requires 1 input.");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type")}},5975:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSplitAttributes=n.split=void 0;const u=a(246),c=a(2517),f=a(2039),s={name:"Split",inputNames:["A"],inputTypes:[f.TextureType.unpacked]};n.split=(o,t,e)=>{l(t);const 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int a[${m}]; + perm(a, indices); + return _A(a); + }`;return Object.assign(Object.assign({},s),{output:{dims:g,type:r.type,textureType:f.TextureType.unpacked},shaderSource:_})},p=(e,r)=>(r&&r.length!==e.length&&(r=[...e.keys()].reverse()),r),l=(e,r)=>(r=p(e,r),c.ShapeUtil.sortBasedOnPerm(e,r)),o=(e,r,i)=>{const d=[];d.push(`void ${e}(out int a[${i}], int src[${i}]) {`);for(let g=0;g{if(!e||e.length!==1)throw new Error("Transpose requires 1 input.");if(e[0].type!=="float32"&&e[0].type!=="float64")throw new Error("input should be float tensor")}},8710:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.encodeAsUint8=void 0;const u=a(5060),c=a(2039);n.encodeAsUint8=(f,s)=>{const h=s.shape,p=(0,u.getGlsl)(f.session.backend.glContext.version),l=` + const float FLOAT_MAX = 1.70141184e38; + const float FLOAT_MIN = 1.17549435e-38; + + bool isNaN(float val) { + return (val < 1.0 || 0.0 < val || val == 0.0) ? false : true; + } + + highp vec4 encodeAsUint8(highp float v) { + if (isNaN(v)) { + return vec4(255, 255, 255, 255); + } + + highp float av = abs(v); + + if(av < FLOAT_MIN) { + return vec4(0.0, 0.0, 0.0, 0.0); + } else if(v > FLOAT_MAX) { + return vec4(0.0, 0.0, 128.0, 127.0) / 255.0; + } else if(v < -FLOAT_MAX) { + return vec4(0.0, 0.0, 128.0, 255.0) / 255.0; + } + + highp vec4 c = vec4(0,0,0,0); + + highp float e = floor(log2(av)); + highp float m = exp2(fract(log2(av))) - 1.0; + + c[2] = floor(128.0 * m); + m -= c[2] / 128.0; + c[1] = floor(32768.0 * m); + m -= c[1] / 32768.0; + c[0] = floor(8388608.0 * m); + + highp float ebias = e + 127.0; + c[3] = floor(ebias / 2.0); + ebias -= c[3] * 2.0; + c[2] += floor(ebias) * 128.0; + + c[3] += 128.0 * step(0.0, -v); + + return c / 255.0; + } + + void main() { + float value = ${p.texture2D}(X,TexCoords).r; + ${p.output} = encodeAsUint8(value); + }`,o={name:"Uint8Encode",inputTypes:[c.TextureType.unpacked],inputNames:["X"],output:{dims:h,type:s.tensor.type,textureType:c.TextureType.downloadUint8AsFloat},shaderSource:l,hasMain:!0};return f.executeProgram(o,[s.tensor])}},4909:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.tanh=n.tan=n.sqrt=n.sin=n.sigmoid=n.relu=n.not=n.neg=n.log=n.parseLeakyReluAttributes=n.leakyRelu=n.identity=n.floor=n.exp=n.parseEluAttributes=n.elu=n.cos=n.ceil=n.clipV11=n.parseClipAttributes=n.clip=n.atan=n.asin=n.acos=n.abs=n.glslTanh=n.glslTan=n.glslSqrt=n.glslSigmoid=n.glslRelu=n.glslSin=n.glslNot=n.glslNeg=n.glslLog=n.glslLeakyRelu=n.glslIdentity=n.glslClip=n.glslFloor=n.glslExp=n.glslElu=n.glslCos=n.glslCeil=n.glslAtan=n.glslAsin=n.glslAcos=n.glslAbs=void 0;const u=a(246),c=a(2517),f=a(8520),s=a(5060),h=a(2039);function p(){return R("abs")}function l(){return R("acos")}function o(){return R("asin")}function t(){return R("atan")}function e(){return R("ceil")}function r(){return R("cos")}function i(C){const $="elu";return{body:` + const float alpha = float(${C}); + + float ${$}_(float a) { + return a >= 0.0 ? a: (exp(a) - 1.0) * alpha; + } + vec4 ${$}_(vec4 v) { + return vec4(${$}_(v.x), ${$}_(v.y), ${$}_(v.z), ${$}_(v.w)); + } + `,name:$,type:f.FunctionType.ValueBased}}function d(){return R("exp")}function g(){return R("floor")}function m(C,$){const X="clip";return{body:` + const float min = float(${C}); + const float max = float(${$}); + + float ${X}_(float a) { + return clamp(a, min, max); + } + vec4 ${X}_(vec4 v) { + return clamp(v, min, max); + } + `,name:X,type:f.FunctionType.ValueBased}}function _(){const C="indentity";return{body:` + float ${C}_(float a) { + return a; + } + vec4 ${C}_(vec4 v) { + return v; + } + `,name:C,type:f.FunctionType.ValueBased}}function y(C){const $="leakyRelu";return{body:` + const float alpha = float(${C}); + + float ${$}_(float a) { + return a < 0.0 ? a * alpha : a; + } + vec4 ${$}_(vec4 v) { + return vec4(${$}_(v.x), ${$}_(v.y), ${$}_(v.z), ${$}_(v.w)); + } + `,name:$,type:f.FunctionType.ValueBased}}function T(){return R("log")}function w(){const C="neg";return{body:` + float ${C}_(float a) { + return -a; + } + vec4 ${C}_(vec4 v) { + return -v; + } + `,name:C,type:f.FunctionType.ValueBased}}function S(){const C="not";return{body:` + float ${C}_(float a) { + return float( ! bool(a) ); + } + bool ${C}_(bool a) { + return !a; + } + vec4 ${C}_(vec4 v) { + return vec4(!bool(v.x), !bool(v.y), !bool(v.z), !bool(v.w)); + } + bvec4 ${C}_(bvec4 v) { + return bvec4(!v.x, !v.y, !v.z, !v.w); + } + `,name:C,type:f.FunctionType.ValueBased}}function O(){return R("sin")}function E(){const C="relu";return{body:` + float ${C}_(float a) { + return max( a, 0.0 ); + } + vec4 ${C}_(vec4 v) { + return max( v, 0.0 ); + } + `,name:C,type:f.FunctionType.ValueBased}}function v(){const C="sigmoid";return{body:` + float ${C}_(float a) { + return 1.0 / (1.0 + exp(-a)); + } + vec4 ${C}_(vec4 v) { + return 1.0 / (1.0 + exp(-v)); + } + `,name:C,type:f.FunctionType.ValueBased}}function P(){return R("sqrt")}function L(){return R("tan")}function V(){const C="tanh";return{body:` + float ${C}_(float a) { + a = clamp(a, -10., 10.); + a = exp(2.*a); + return (a - 1.) / (a + 1.); + } + vec4 ${C}_(vec4 v) { + v = clamp(v, -10., 10.); + v = exp(2.*v); + return (v - 1.) / (v + 1.); + } + `,name:C,type:f.FunctionType.ValueBased}}function R(C){return{body:` + float ${C}_(float a) { + return ${C}(a); + } + vec4 ${C}_(vec4 v) { + return ${C}(v); + } + `,name:C,type:f.FunctionType.ValueBased}}n.glslAbs=p,n.glslAcos=l,n.glslAsin=o,n.glslAtan=t,n.glslCeil=e,n.glslCos=r,n.glslElu=i,n.glslExp=d,n.glslFloor=g,n.glslClip=m,n.glslIdentity=_,n.glslLeakyRelu=y,n.glslLog=T,n.glslNeg=w,n.glslNot=S,n.glslSin=O,n.glslRelu=E,n.glslSigmoid=v,n.glslSqrt=P,n.glslTan=L,n.glslTanh=V;const k=(C,$,X,z)=>{const Z=C.session.pack?h.TextureType.packed:h.TextureType.unpacked,J={name:X.name,inputTypes:[Z],inputNames:["A"],cacheHint:z};return 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Object.assign(Object.assign({},h),{hasMain:!0,output:{dims:l.dims,type:l.type,textureType:c.TextureType.unpacked},shaderSource:m})},n.createUnpackProgramInfoLoader=(p,l)=>Object.assign(Object.assign({},h),{get:()=>(0,n.createUnpackProgramInfo)(p,l)})},8428:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseUnsqueezeAttributes=n.unsqueezeV13=n.unsqueeze=void 0;const u=a(2517);n.unsqueeze=(s,h,p)=>{c(h);const l=u.ShapeUtil.unsqueezeShape(h[0].dims,p);return[s.reshapeUnpacked(h[0],l)]},n.unsqueezeV13=(s,h)=>(f(h),(0,n.unsqueeze)(s,[h[0]],Array.from(h[1].integerData))),n.parseUnsqueezeAttributes=s=>s.attributes.getInts("axes");const c=s=>{if(!s||s.length!==1)throw new Error("Unsqueeze requires 1 input.");if(s[0].type==="string")throw new Error("invalid input tensor types.")},f=s=>{if(!s||s.length!==2)throw new Error("Unsqueeze requires 2 inputs.");if(s[1].type!=="int32")throw new Error("Invalid input 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l>10?p.inputs.length>2?(w=1,S=2,O=3):(S=1,O=2):l===9&&(S=1),(0,u.createAttributeWithCacheKey)({opset:l,isResize:o,mode:t,scales:e,extrapolationValue:r,coordinateTransformMode:i,useExtrapolation:g,needRoiInput:d,nearestMode:m,cubicCoefficientA:_,excludeOutside:y,useNearest2xOptimization:T,roiInputIdx:w,scalesInputIdx:S,sizesInputIdx:O})};const h=(p,l,o)=>{const t=(0,c.getGlsl)(p.session.backend.glContext.version),[e,r]=p.calculateTextureWidthAndHeight(l[0].dims,f.TextureType.unpacked),i=l[0].dims.map((O,E)=>Math.floor(O*o.scales[E])),[d,g]=p.calculateTextureWidthAndHeight(i,f.TextureType.unpacked),m=i.length,_=new Array(m),y=new Array(m);let T=` + int output_pitches[${m}]; + int input_pitches[${m}]; + `;for(let O=m-1;O>=0;O--)_[O]=O===m-1?1:_[O+1]*i[O+1],y[O]=O===m-1?1:y[O+1]*l[0].dims[O+1],T+=` + output_pitches[${O}] = ${_[O]}; + input_pitches[${O}] = ${y[O]}; + `;const w=` + float getInputFloat(int index) { + vec2 coords = offsetToCoords(index, ${e}, ${r}); + float value = getColorAsFloat(${t.texture2D}(X, coords)); + return value; + } + `,S=o.mode==="nearest"?` + ${w} + float process(int indices[${m}]) { + int input_index = 0; + int output_index = coordsToOffset(TexCoords, ${d}, ${g}); + + ${T} + + int d, m; + for (int dim = 0; dim < ${m}; ++dim) { + d = output_index / output_pitches[dim]; + m = output_index - d * output_pitches[dim]; + output_index = m; + + if (scales[dim] != 1 && d > 0) { + int d2 = d / scales[dim]; + m = d - d2 * scales[dim]; + d = d2; + } + input_index += input_pitches[dim] * d; + } + + return getInputFloat(input_index); + }`:m===4?` + ${w} + float process(int indices[4]) { + int input_index = 0; + int output_index = coordsToOffset(TexCoords, ${d}, ${g}); + + ${T} + + int m; + int index_of_dim0, index_of_dim1, index_of_dim2, index_of_dim3; + index_of_dim0 = output_index / output_pitches[0]; + m = output_index - index_of_dim0 * output_pitches[0]; + index_of_dim1 = m / output_pitches[1]; + m = m - index_of_dim1 * output_pitches[1]; + index_of_dim2 = m / output_pitches[2]; + m = m - index_of_dim2 * output_pitches[2]; + index_of_dim3 = m; + + int index_of_input_dim2, index_of_input_dim3, x_offset, y_offset; + index_of_input_dim2 = index_of_dim2 / scales[2]; + y_offset = index_of_dim2 - index_of_input_dim2 * scales[2]; + index_of_input_dim3 = index_of_dim3 / scales[3]; + x_offset = index_of_dim3 - index_of_input_dim3 * scales[3]; + + input_index = index_of_dim0 * input_pitches[0] + + index_of_dim1 * input_pitches[1] + + index_of_input_dim2 * input_pitches[2] + + index_of_input_dim3; + + float x00 = getInputFloat(input_index); + float x10, x01, x11; + + bool end_of_dim2 = false; + if (index_of_input_dim2 == (${l[0].dims[2]} - 1)) { + // It's the end in dimension 2 + x01 = x00; + end_of_dim2 = true; + } else { + x01 = getInputFloat(input_index + input_pitches[2]); + } + + if (index_of_input_dim3 == (input_pitches[2] - 1)) { + // It's the end in dimension 3 + x10 = x00; + x11 = x01; + } + else { + x10 = getInputFloat(input_index + 1); + x11 = end_of_dim2 ? x10 : getInputFloat(input_index + input_pitches[2] + 1); + } + + float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[2]); + float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[2]); + return y0 + float(x_offset) * (y1 - y0) / float(scales[3]); + }`:` + ${w} + float process(int indices[2]) { + int input_index = 0; + int output_index = coordsToOffset(TexCoords, ${d}, ${g}); + + ${T} + + int m; + int index_of_dim0, index_of_dim1; + index_of_dim0 = output_index / output_pitches[0]; + m = output_index - index_of_dim0 * output_pitches[0]; + index_of_dim1 = m; + + int index_of_input_dim0, index_of_input_dim1, x_offset, y_offset; + index_of_input_dim0 = index_of_dim0 / scales[0]; + y_offset = index_of_dim0 - index_of_input_dim0 * scales[0]; + index_of_input_dim1 = index_of_dim1 / scales[1]; + x_offset = index_of_dim1 - index_of_input_dim1 * scales[1]; + + input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1; + + float x00 = getInputFloat(input_index); + float x10, x01, x11; + + bool end_of_dim0 = false; + if (index_of_input_dim0 == (${l[0].dims[0]} - 1)) { + // It's the end in dimension 0 + x01 = x00; + end_of_dim0 = true; + } else { + x01 = getInputFloat(input_index + input_pitches[0]); + } + + if (index_of_input_dim1 == (input_pitches[0] - 1)) { + // It's the end in dimension 1 + x10 = x00; + x11 = x01; + } + else { + x10 = getInputFloat(input_index + 1); + x11 = end_of_dim0 ? x10 : getInputFloat(input_index + input_pitches[0] + 1); + } + + float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[0]); + float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[0]); + return y0 + float(x_offset) * (y1 - y0) / float(scales[1]); + }`;return Object.assign(Object.assign({},s),{output:{dims:i,type:l[0].type,textureType:f.TextureType.unpacked},shaderSource:S,variables:[{name:"scales",type:"int",arrayLength:o.scales.length,data:o.scales.map(O=>Math.ceil(O))}]})};n.validateInputs=(p,l)=>{if(!p||l.opset<9&&p.length!==1||l.opset>=9&&l.opset<11&&p.length!==2||l.opset>=11&&p.length<2)throw new Error("invalid inputs.");if(l.scales.length>0&&p[0].dims.length!==l.scales.length)throw new Error("Invalid input shape.");if(p[0].type==="string")throw new Error("Invalid input tensor types.")},n.scalesValidation=(p,l,o)=>{if(o){for(const t of p)if(t<=0)throw new Error("Scale value should be greater than 0.")}else for(const t of p)if(t<1)throw new Error("Scale value should be greater than or equal to 1.");if(!(l!=="linear"&&l!=="cubic"||p.length===2||p.length===4&&p[0]===1&&p[1]===1))throw new Error(`'Linear' mode and 'Cubic' mode only support 2-D inputs ('Bilinear', 'Bicubic') or 4-D inputs with the corresponding outermost 2 scale values 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r=this.bb.__offset(this.bb_pos,14);return r?this.bb.__string(this.bb.__vector(this.bb_pos+r)+4*t,e):null}inputsLength(){let t=this.bb.__offset(this.bb_pos,14);return t?this.bb.__vector_len(this.bb_pos+t):0}outputs(t,e){let r=this.bb.__offset(this.bb_pos,16);return r?this.bb.__string(this.bb.__vector(this.bb_pos+r)+4*t,e):null}outputsLength(){let t=this.bb.__offset(this.bb_pos,16);return t?this.bb.__vector_len(this.bb_pos+t):0}sparseInitializers(t,e){let r=this.bb.__offset(this.bb_pos,18);return r?(e||new s.experimental.fbs.SparseTensor).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}sparseInitializersLength(){let t=this.bb.__offset(this.bb_pos,18);return t?this.bb.__vector_len(this.bb_pos+t):0}static startGraph(t){t.startObject(8)}static addInitializers(t,e){t.addFieldOffset(0,e,0)}static createInitializersVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startInitializersVector(t,e){t.startVector(4,e,4)}static addNodeArgs(t,e){t.addFieldOffset(1,e,0)}static createNodeArgsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodeArgsVector(t,e){t.startVector(4,e,4)}static addNodes(t,e){t.addFieldOffset(2,e,0)}static createNodesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodesVector(t,e){t.startVector(4,e,4)}static addMaxNodeIndex(t,e){t.addFieldInt32(3,e,0)}static addNodeEdges(t,e){t.addFieldOffset(4,e,0)}static createNodeEdgesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodeEdgesVector(t,e){t.startVector(4,e,4)}static addInputs(t,e){t.addFieldOffset(5,e,0)}static createInputsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startInputsVector(t,e){t.startVector(4,e,4)}static addOutputs(t,e){t.addFieldOffset(6,e,0)}static createOutputsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startOutputsVector(t,e){t.startVector(4,e,4)}static addSparseInitializers(t,e){t.addFieldOffset(7,e,0)}static createSparseInitializersVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startSparseInitializersVector(t,e){t.startVector(4,e,4)}static endGraph(t){return t.endObject()}static createGraph(t,e,r,i,d,g,m,_,y){return l.startGraph(t),l.addInitializers(t,e),l.addNodeArgs(t,r),l.addNodes(t,i),l.addMaxNodeIndex(t,d),l.addNodeEdges(t,g),l.addInputs(t,m),l.addOutputs(t,_),l.addSparseInitializers(t,y),l.endGraph(t)}}p.Graph=l})(h.fbs||(h.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(h){(function(p){class l{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsModel(t,e){return(e||new l).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsModel(t,e){return t.setPosition(t.position()+u.flatbuffers.SIZE_PREFIX_LENGTH),(e||new l).__init(t.readInt32(t.position())+t.position(),t)}irVersion(){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}opsetImport(t,e){let r=this.bb.__offset(this.bb_pos,6);return r?(e||new s.experimental.fbs.OperatorSetId).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}opsetImportLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}producerName(t){let e=this.bb.__offset(this.bb_pos,8);return e?this.bb.__string(this.bb_pos+e,t):null}producerVersion(t){let e=this.bb.__offset(this.bb_pos,10);return e?this.bb.__string(this.bb_pos+e,t):null}domain(t){let e=this.bb.__offset(this.bb_pos,12);return e?this.bb.__string(this.bb_pos+e,t):null}modelVersion(){let t=this.bb.__offset(this.bb_pos,14);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}docString(t){let e=this.bb.__offset(this.bb_pos,16);return e?this.bb.__string(this.bb_pos+e,t):null}graph(t){let e=this.bb.__offset(this.bb_pos,18);return e?(t||new s.experimental.fbs.Graph).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}graphDocString(t){let e=this.bb.__offset(this.bb_pos,20);return e?this.bb.__string(this.bb_pos+e,t):null}static startModel(t){t.startObject(9)}static addIrVersion(t,e){t.addFieldInt64(0,e,t.createLong(0,0))}static addOpsetImport(t,e){t.addFieldOffset(1,e,0)}static createOpsetImportVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startOpsetImportVector(t,e){t.startVector(4,e,4)}static addProducerName(t,e){t.addFieldOffset(2,e,0)}static addProducerVersion(t,e){t.addFieldOffset(3,e,0)}static addDomain(t,e){t.addFieldOffset(4,e,0)}static addModelVersion(t,e){t.addFieldInt64(5,e,t.createLong(0,0))}static addDocString(t,e){t.addFieldOffset(6,e,0)}static addGraph(t,e){t.addFieldOffset(7,e,0)}static addGraphDocString(t,e){t.addFieldOffset(8,e,0)}static endModel(t){return t.endObject()}static createModel(t,e,r,i,d,g,m,_,y,T){return l.startModel(t),l.addIrVersion(t,e),l.addOpsetImport(t,r),l.addProducerName(t,i),l.addProducerVersion(t,d),l.addDomain(t,g),l.addModelVersion(t,m),l.addDocString(t,_),l.addGraph(t,y),l.addGraphDocString(t,T),l.endModel(t)}}p.Model=l})(h.fbs||(h.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(h){(function(p){class l{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsKernelCreateInfos(t,e){return(e||new l).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsKernelCreateInfos(t,e){return t.setPosition(t.position()+u.flatbuffers.SIZE_PREFIX_LENGTH),(e||new l).__init(t.readInt32(t.position())+t.position(),t)}nodeIndices(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.readUint32(this.bb.__vector(this.bb_pos+e)+4*t):0}nodeIndicesLength(){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.__vector_len(this.bb_pos+t):0}nodeIndicesArray(){let t=this.bb.__offset(this.bb_pos,4);return t?new Uint32Array(this.bb.bytes().buffer,this.bb.bytes().byteOffset+this.bb.__vector(this.bb_pos+t),this.bb.__vector_len(this.bb_pos+t)):null}kernelDefHashes(t){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.readUint64(this.bb.__vector(this.bb_pos+e)+8*t):this.bb.createLong(0,0)}kernelDefHashesLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}static startKernelCreateInfos(t){t.startObject(2)}static addNodeIndices(t,e){t.addFieldOffset(0,e,0)}static createNodeIndicesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addInt32(e[r]);return t.endVector()}static startNodeIndicesVector(t,e){t.startVector(4,e,4)}static addKernelDefHashes(t,e){t.addFieldOffset(1,e,0)}static createKernelDefHashesVector(t,e){t.startVector(8,e.length,8);for(let r=e.length-1;r>=0;r--)t.addInt64(e[r]);return t.endVector()}static startKernelDefHashesVector(t,e){t.startVector(8,e,8)}static endKernelCreateInfos(t){return t.endObject()}static createKernelCreateInfos(t,e,r){return l.startKernelCreateInfos(t),l.addNodeIndices(t,e),l.addKernelDefHashes(t,r),l.endKernelCreateInfos(t)}}p.KernelCreateInfos=l})(h.fbs||(h.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(h){(function(p){class l{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsSubGraphSessionState(t,e){return(e||new l).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSubGraphSessionState(t,e){return t.setPosition(t.position()+u.flatbuffers.SIZE_PREFIX_LENGTH),(e||new l).__init(t.readInt32(t.position())+t.position(),t)}graphId(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,t):null}sessionState(t){let e=this.bb.__offset(this.bb_pos,6);return e?(t||new s.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startSubGraphSessionState(t){t.startObject(2)}static addGraphId(t,e){t.addFieldOffset(0,e,0)}static addSessionState(t,e){t.addFieldOffset(1,e,0)}static endSubGraphSessionState(t){let e=t.endObject();return t.requiredField(e,4),e}static createSubGraphSessionState(t,e,r){return l.startSubGraphSessionState(t),l.addGraphId(t,e),l.addSessionState(t,r),l.endSubGraphSessionState(t)}}p.SubGraphSessionState=l})(h.fbs||(h.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(h){(function(p){class l{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsSessionState(t,e){return(e||new l).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSessionState(t,e){return t.setPosition(t.position()+u.flatbuffers.SIZE_PREFIX_LENGTH),(e||new l).__init(t.readInt32(t.position())+t.position(),t)}kernels(t){let e=this.bb.__offset(this.bb_pos,4);return e?(t||new s.experimental.fbs.KernelCreateInfos).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}subGraphSessionStates(t,e){let r=this.bb.__offset(this.bb_pos,6);return r?(e||new s.experimental.fbs.SubGraphSessionState).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}subGraphSessionStatesLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}static startSessionState(t){t.startObject(2)}static addKernels(t,e){t.addFieldOffset(0,e,0)}static addSubGraphSessionStates(t,e){t.addFieldOffset(1,e,0)}static createSubGraphSessionStatesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startSubGraphSessionStatesVector(t,e){t.startVector(4,e,4)}static endSessionState(t){return t.endObject()}static createSessionState(t,e,r){return l.startSessionState(t),l.addKernels(t,e),l.addSubGraphSessionStates(t,r),l.endSessionState(t)}}p.SessionState=l})(h.fbs||(h.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(h){(function(p){class l{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsInferenceSession(t,e){return(e||new l).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsInferenceSession(t,e){return t.setPosition(t.position()+u.flatbuffers.SIZE_PREFIX_LENGTH),(e||new l).__init(t.readInt32(t.position())+t.position(),t)}static bufferHasIdentifier(t){return t.__has_identifier("ORTM")}ortVersion(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,t):null}model(t){let e=this.bb.__offset(this.bb_pos,6);return e?(t||new s.experimental.fbs.Model).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}sessionState(t){let e=this.bb.__offset(this.bb_pos,8);return e?(t||new s.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startInferenceSession(t){t.startObject(3)}static addOrtVersion(t,e){t.addFieldOffset(0,e,0)}static addModel(t,e){t.addFieldOffset(1,e,0)}static addSessionState(t,e){t.addFieldOffset(2,e,0)}static endInferenceSession(t){return t.endObject()}static finishInferenceSessionBuffer(t,e){t.finish(e,"ORTM")}static finishSizePrefixedInferenceSessionBuffer(t,e){t.finish(e,"ORTM",!0)}static createInferenceSession(t,e,r,i){return l.startInferenceSession(t),l.addOrtVersion(t,e),l.addModel(t,r),l.addSessionState(t,i),l.endInferenceSession(t)}}p.InferenceSession=l})(h.fbs||(h.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={}))},7448:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.OnnxjsSessionHandler=void 0;const u=a(1670),c=a(9162);n.OnnxjsSessionHandler=class{constructor(f){this.session=f,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(f,s,h){const p=new Map;for(const t in f)if(Object.hasOwnProperty.call(f,t)){const e=f[t];p.set(t,new c.Tensor(e.dims,e.type,void 0,void 0,e.data))}const l=await this.session.run(p),o={};return l.forEach((t,e)=>{o[e]=new u.Tensor(t.type,t.data,t.dims)}),o}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(b,n,a)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Session=void 0;const u=a(7067),c=a(1296),f=a(7091),s=a(1036),h=a(6231),p=a(2644);n.Session=class{constructor(l={}){this._initialized=!1,this.backendHint=l.backendHint,this.profiler=h.Profiler.create(l.profiler),this.context={profiler:this.profiler,graphInputTypes:[],graphInputDims:[]}}get inputNames(){return this._model.graph.getInputNames()}get outputNames(){return this._model.graph.getOutputNames()}startProfiling(){this.profiler.start()}endProfiling(){this.profiler.stop()}async loadModel(l,o,t){await this.profiler.event("session","Session.loadModel",async()=>{const e=await(0,f.resolveBackend)(this.backendHint);if(this.sessionHandler=e.createSessionHandler(this.context),this._model=new p.Model,typeof l=="string"){const r=l.endsWith(".ort");if(typeof fetch>"u"){const i=await(0,c.promisify)(u.readFile)(l);this.initialize(i,r)}else{const i=await fetch(l),d=await i.arrayBuffer();this.initialize(new Uint8Array(d),r)}}else if(ArrayBuffer.isView(l))this.initialize(l);else{const r=new Uint8Array(l,o||0,t||l.byteLength);this.initialize(r)}})}initialize(l,o){if(this._initialized)throw new Error("already initialized");this.profiler.event("session","Session.initialize",()=>{const t=this.sessionHandler.transformGraph?this.sessionHandler:void 0;this._model.load(l,t,o),this.sessionHandler.onGraphInitialized&&this.sessionHandler.onGraphInitialized(this._model.graph),this.initializeOps(this._model.graph),this._executionPlan=new s.ExecutionPlan(this._model.graph,this._ops,this.profiler)}),this._initialized=!0}async run(l){if(!this._initialized)throw new Error("session not initialized yet");return this.profiler.event("session","Session.run",async()=>{const o=this.normalizeAndValidateInputs(l),t=await this._executionPlan.execute(this.sessionHandler,o);return this.createOutput(t)})}normalizeAndValidateInputs(l){const o=this._model.graph.getInputNames();if(Array.isArray(l)){if(l.length!==o.length)throw new Error(`incorrect input array length: expected ${o.length} but got ${l.length}`)}else{if(l.size!==o.length)throw new Error(`incorrect input map size: expected ${o.length} but got ${l.size}`);const t=new Array(l.size);let e=0;for(let r=0;rtypeof E=="string")))throw new TypeError("cache should be a string array");O&&(this.cache=new Array(S))}else{if(T!==void 0){const E=e(m);if(!(T instanceof E))throw new TypeError(`cache should be type ${E.name}`)}if(O){const E=new ArrayBuffer(S*function(v){switch(v){case"bool":case"int8":case"uint8":return 1;case"int16":case"uint16":return 2;case"int32":case"uint32":case"float32":return 4;case"float64":return 8;default:throw new Error(`cannot calculate sizeof() on type ${v}`)}}(m));this.cache=function(v,P){return new(e(P))(v)}(E,m)}}}static fromProto(g){if(!g)throw new Error("cannot construct Value from an empty tensor");const m=p.ProtoUtil.tensorDataTypeFromProto(g.dataType),_=p.ProtoUtil.tensorDimsFromProto(g.dims),y=new o(_,m);if(m==="string")g.stringData.forEach((T,w)=>{y.data[w]=(0,p.decodeUtf8String)(T)});else if(g.rawData&&typeof g.rawData.byteLength=="number"&&g.rawData.byteLength>0){const T=y.data,w=new DataView(g.rawData.buffer,g.rawData.byteOffset,g.rawData.byteLength),S=t(g.dataType),O=g.rawData.byteLength/S;if(g.rawData.byteLength%S!=0)throw new Error("invalid buffer length");if(T.length!==O)throw new Error("buffer length mismatch");for(let E=0;E0){const T=y.data,w=new DataView(g.rawDataArray().buffer,g.rawDataArray().byteOffset,g.rawDataLength()),S=t(g.dataType()),O=g.rawDataLength()/S;if(g.rawDataLength()%S!=0)throw new Error("invalid buffer length");if(T.length!==O)throw new Error("buffer length mismatch");for(let E=0;E1&&P>1)return;O[S-E]=Math.max(v,P)}return O}static index(m,_){const y=new Array(_.length);return l.fillIndex(m,_,y),y}static fillIndex(m,_,y){const T=m.length-_.length;for(let w=0;w<_.length;w++)y[w]=m[T+w]%_[w]}static calc(m,_,y,T,w){const S=l.calcShape(m.dims,_.dims);if(S){if(T&&!e.areEqual(S,m.dims))return;const O=e.size(S),E=T?m:new h.Tensor(S,w||m.type);if(S.length===0)E.set([],y(m.get([]),_.get([])));else{const v=new Array(S.length),P=new Array(m.dims.length),L=new Array(_.dims.length);let V,R=0,k=0,Y=!1,C=!1;m.dims.length===0&&(R=m.get([]),Y=!0),_.dims.length===0&&(k=_.get([]),C=!0);for(let $=0;$=0;X--)v[X]=V%S[X],V=Math.floor(V/S[X]);Y||(l.fillIndex(v,m.dims,P),R=m.get(P)),C||(l.fillIndex(v,_.dims,L),k=_.get(L)),E.set(v,y(R,k))}}return E}}static isValidBroadcast(m,_){const y=m.length,T=_.length;if(y>T)return!1;for(let w=1;w<=y;w++)if(m[y-w]!==1&&m[y-w]!==_[T-w])return!1;return!0}static getBroadcastDims(m,_){const y=m.length,T=[];for(let w=0;w1&&O===1&&T.unshift(S)}return T}}n.BroadcastUtil=l,n.arrayCopyHelper=function(g,m,_,y,T){if(y<0||y>=m.length)throw new Error("sourceIndex out of bounds");if(_<0||_>=g.length)throw new Error("targetIndex out of bounds");if(y+T>m.length)throw new Error("source indices to be copied are outside bounds");if(_+T>g.length)throw new Error("target array is too small to hold result");for(let w=0;wf.default.isLong(_)?_.toNumber():_)}static tensorValueTypeFromProto(m){return{tensorType:o.tensorDataTypeFromProto(m.elemType),shape:{dims:o.tensorDimsFromProto(m.shape.dim.map(_=>_.dimValue))}}}static tensorDimsFromORTFormat(m){const _=[];for(let y=0;ym.length)throw new Error(`invalid dimension of ${_} for sizeFromDimension as Tensor has ${m.length} dimensions.`);return e.getSizeFromDimensionRange(m,_,m.length)}static sizeToDimension(m,_){if(_<0||_>m.length)throw new Error(`invalid dimension of ${_} for sizeToDimension as Tensor has ${m.length} dimensions.`);return e.getSizeFromDimensionRange(m,0,_)}static getSizeFromDimensionRange(m,_,y){let T=1;for(let w=_;w=0;--T)y[T]=y[T+1]*m[T+1];return y}static transpose(m){return m.slice().reverse()}static indicesToOffset(m,_,y){y===void 0&&(y=m.length);let T=0;for(let w=0;w=_)throw new Error("unsupported axis for this operation.");return m<0?m+_:m}static normalizeAxes(m,_){return m.map(y=>this.normalizeAxis(y,_))}static 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readResponse(b,n){const a=b.headers.get("Content-Length");a===null&&console.warn("Unable to determine content-length from response headers. Will expand buffer when needed.");let u=parseInt(a??"0"),c=new Uint8Array(u),f=0;const s=b.body.getReader();async function h(){const{done:p,value:l}=await s.read();if(p)return;let o=f+l.length;if(o>u){u=o;let e=new Uint8Array(u);e.set(c),c=e}c.set(l,f),f=o;const t=f/u*100;return n({progress:t,loaded:f,total:u}),h()}return await h(),c}function pathJoin(...b){return b=b.map((n,a)=>(a&&(n=n.replace(new RegExp("^/"),"")),a!==b.length-1&&(n=n.replace(new RegExp("/$"),"")),n)),b.join("/")}function interpolate_data(b,[n,a,u],[c,f],s="bilinear",h=!1){const p=f/u,l=c/a,o=new b.constructor(c*f*n),t=a*u,e=c*f;for(let r=0;r=0;--h)c[h]=p,u[h]=n[a[h]],p*=u[h];const f=a.map((h,p)=>c[a.indexOf(p)]),s=new b.constructor(b.length);for(let h=0;h=0;--l)p+=o%n[l]*f[l],o=Math.floor(o/n[l]);s[p]=b[h]}return[s,u]}function softmax(b){const n=max(b)[0],a=b.map(f=>Math.exp(f-n)),u=a.reduce((f,s)=>f+s,0);return a.map(f=>f/u)}function log_softmax(b){return softmax(b).map(u=>Math.log(u))}function getTopItems(b,n=0){return b=Array.from(b).map((a,u)=>[u,a]).sort((a,u)=>u[1]-a[1]),n!==null&&n>0&&(b=b.slice(0,n)),b}function min(b){if(b.length===0)throw Error("Array must not be empty");let n=b[0],a=0;for(let u=1;un&&(n=b[u],a=u);return[Number(n),a]}function isPowerOfTwo(b){return b>0&&(b&b-1)===0}class P2FFT{constructor(n){if(this.size=n|0,this.size<=1||!isPowerOfTwo(this.size))throw new Error("FFT size must be a power of two larger than 1");this._csize=n<<1,this.table=new Float64Array(this.size*2);for(let u=0;uu;u<<=1)++a;this._width=a%2===0?a-1:a,this._bitrev=new Int32Array(1<>>c&3)<>>1);for(let c=0;c>>1]=n[c];return u}toComplexArray(n,a){const u=a||this.createComplexArray();for(let c=0;c>>1],u[c+1]=0;return u}completeSpectrum(n){const a=this._csize,u=a>>>1;for(let c=2;c>=2;s>=2;s>>=2){h=c/s<<1;const t=h>>>2;for(p=0;p>>1,s>>>1)}else for(p=0,l=0;p>>1,s>>>1,u)}for(s>>=2;s>=2;s>>=2){h=c/s<<1;const t=h>>>2;for(p=0;p>1;++o){const t=(o+1-n)**2/2,e=Math.sqrt(p**2+l**2)**t,r=t*Math.atan2(l,p),i=2*o;f[i]=e*Math.cos(r),f[i+1]=e*Math.sin(r),s[i]=f[i],s[i+1]=-f[i+1]}this._slicedChirpBuffer=f.subarray(a,u),this._f=new P2FFT(c>>1),this._f.transform(this._chirpBuffer,s)}_transform(n,a,u){const c=this._buffer1,f=this._buffer2,s=this._outBuffer1,h=this._outBuffer2,p=this._chirpBuffer,l=this._slicedChirpBuffer,o=this._a;if(u)for(let t=0;t>1,i=a[r];c[t]=i*l[t],c[e]=i*l[e]}else for(let t=0;t=b.length&&(p=2*(b.length-1)-p),u[s++]=b[p]}u.sort(),a[f]=u[c]}return a}const DataTypeMap=Object.freeze({float32:Float32Array,float64:Float64Array,string:Array,int8:Int8Array,uint8:Uint8Array,int16:Int16Array,uint16:Uint16Array,int32:Int32Array,uint32:Uint32Array,int64:BigInt64Array,uint64:BigUint64Array,bool:Uint8Array}),ONNXTensor$1=ONNX.Tensor;class Tensor{dims;type;data;size;constructor(...n){return n[0]instanceof ONNXTensor$1?Object.assign(this,n[0]):Object.assign(this,new ONNXTensor$1(n[0],n[1],n[2])),new Proxy(this,{get:(a,u)=>{if(typeof u=="string"){let c=Number(u);if(Number.isInteger(c))return a._getitem(c)}return a[u]},set:(a,u,c)=>a[u]=c})}*[Symbol.iterator](){const[n,...a]=this.dims;if(a.length>0){const u=a.reduce((c,f)=>c*f);for(let c=0;c0){const c=u.reduce((f,s)=>f*s);return this._subarray(n,c,u)}else return new Tensor(this.type,[this.data[n]],u)}indexOf(n){for(let a=0;al[1])throw new Error(`Invalid slice: ${l}`);let o=[Math.max(l[0],0),Math.min(l[1],this.dims[p])];u.push(o),a.push(o[1]-o[0])}else throw new Error(`Invalid slice: ${l}`)}let c=u.map(([p,l])=>l-p),f=c.reduce((p,l)=>p*l),s=new this.data.constructor(f);const h=this.stride();for(let p=0;p=0;--o){const e=c[o];l+=(t%e+u[o][0])*h[o],t=Math.floor(t/e)}s[p]=this.data[l]}return new Tensor(this.type,s,a)}transpose(...n){return transpose(this,n)}sum(n=null,a=!1){return this.norm(1,n,a)}norm(n="fro",a=null,u=!1){if(n==="fro")n=2;else if(typeof n=="string")throw Error(`Unsupported norm: ${n}`);if(a===null){let s=this.data.reduce((h,p)=>h+p**n,0)**(1/n);return new Tensor(this.type,[s],[])}a=safeIndex(a,this.dims.length);const c=this.dims.slice();c[a]=1;const f=new this.data.constructor(this.data.length/this.dims[a]);for(let s=0;s=0;--p){const t=this.dims[p];if(p!==a){const e=l%t;h+=e*o,o*=c[p]}l=Math.floor(l/t)}f[h]+=this.data[s]**n}if(n!==1)for(let s=0;s=0;--s){const l=this.dims[s];if(s!==a){const o=h%l;f+=o*p,p*=this.dims[s]}h=Math.floor(h/l)}this.data[c]/=u.data[f]}return this}normalize(n=2,a=1){return this.clone().normalize_(n,a)}stride(){return dimsToStride(this.dims)}squeeze(n=null){return new Tensor(this.type,this.data,calc_squeeze_dims(this.dims,n))}squeeze_(n=null){return this.dims=calc_squeeze_dims(this.dims,n),this}unsqueeze(n=null){return new Tensor(this.type,this.data,calc_unsqueeze_dims(this.dims,n))}unsqueeze_(n=null){return this.dims=calc_unsqueeze_dims(this.dims,n),this}flatten_(n=0,a=-1){a=(a+this.dims.length)%this.dims.length;let u=this.dims.slice(0,n),c=this.dims.slice(n,a+1),f=this.dims.slice(a+1);return this.dims=[...u,c.reduce((s,h)=>s*h,1),...f],this}flatten(n=0,a=-1){return this.clone().flatten_(n,a)}view(...n){let a=-1;for(let u=0;us!==a?c*f:c,1);n[a]=this.data.length/u}return new Tensor(this.type,this.data,n)}neg_(){for(let n=0;nf*s);if(a!==u)throw Error(`cannot reshape array of size ${a} into shape (${n})`);let c=b;for(let f=n.length-1;f>=0;f--)c=c.reduce((s,h)=>{let p=s[s.length-1];return p.lengtha!==1):typeof n=="number"?b[n]===1&&b.splice(n,1):Array.isArray(n)&&(b=b.filter((a,u)=>a!==1||!n.includes(u))),b}function calc_unsqueeze_dims(b,n){return n=safeIndex(n,b.length+1),b=b.slice(),b.splice(n,0,1),b}function safeIndex(b,n,a=null){if(b<-n||b>=n)throw new Error(`IndexError: index ${b} is out of bounds for dimension${a===null?"":" "+a} with size ${n}`);return b<0&&(b=(b%n+n)%n),b}function cat(b,n=0){n=safeIndex(n,b[0].dims.length);const a=b[0].dims.slice();a[n]=b.reduce((s,h)=>s+h.dims[n],0);const u=a.reduce((s,h)=>s*h,1),c=new b[0].data.constructor(u),f=b[0].type;if(n===0){let s=0;for(let h of b)c.set(h.data,s),s+=h.data.length}else{let s=0;for(let h=0;h=0;--t){const i=p.dims[t];let d=e%i;t===n&&(d+=s),o+=d*r,r*=a[t],e=Math.floor(e/i)}c[o]=p.data[l]}s+=p.dims[n]}}return new Tensor(f,c,a)}function stack(b,n=0){return cat(b.map(a=>a.unsqueeze(n)),n)}function std_mean(b,n=null,a=1,u=!1){if(n===null){const l=b.data.reduce((r,i)=>r+i,0)/b.data.length,o=Math.sqrt(b.data.reduce((r,i)=>r+(i-l)**2,0)/(b.data.length-a)),t=new Tensor(b.type,[l],[]);return[new Tensor(b.type,[o],[]),t]}n=safeIndex(n,b.dims.length);const c=mean(b,n,u),f=b.dims.slice();f[n]=1;const s=new b.data.constructor(b.data.length/b.dims[n]);for(let p=0;p=0;--o){const r=b.dims[o];if(o!==n){const i=t%r;l+=i*e,e*=f[o]}t=Math.floor(t/r)}s[l]+=(b.data[p]-c.data[l])**2}for(let p=0;ps+h,0);return new Tensor(b.type,[f/b.data.length],[])}n=safeIndex(n,b.dims.length);const u=b.dims.slice();u[n]=1;const c=new b.data.constructor(b.data.length/b.dims[n]);for(let f=0;f=0;--h){const o=b.dims[h];if(h!==n){const t=p%o;s+=t*l,l*=u[h]}p=Math.floor(p/o)}c[s]+=b.data[f]}if(b.dims[n]!==1)for(let f=0;f0||h>0;)switch(p.push(s-1),l.push(h-1),f[s][h].item()){case 0:--s,--h;break;case 1:--s;break;case 2:--h;break;default:throw new Error(`Internal error in dynamic time warping. Unexpected trace[${s}, ${h}]. Please file a bug report.`)}return p.reverse(),l.reverse(),[p,l]}function dimsToStride(b){const n=new Array(b.length);for(let a=b.length-1,u=1;a>=0;--a)n[a]=u,u*=b[a];return n}function ones(b){const n=b.reduce((a,u)=>a*u,1);return new Tensor("int64",new BigInt64Array(n).fill(1n),b)}function ones_like(b){return ones(b.dims)}var TOKEN_TYPES=Object.freeze({Text:"Text",NumericLiteral:"NumericLiteral",BooleanLiteral:"BooleanLiteral",StringLiteral:"StringLiteral",Identifier:"Identifier",Equals:"Equals",OpenParen:"OpenParen",CloseParen:"CloseParen",OpenStatement:"OpenStatement",CloseStatement:"CloseStatement",OpenExpression:"OpenExpression",CloseExpression:"CloseExpression",OpenSquareBracket:"OpenSquareBracket",CloseSquareBracket:"CloseSquareBracket",Comma:"Comma",Dot:"Dot",Colon:"Colon",Pipe:"Pipe",CallOperator:"CallOperator",AdditiveBinaryOperator:"AdditiveBinaryOperator",MultiplicativeBinaryOperator:"MultiplicativeBinaryOperator",ComparisonBinaryOperator:"ComparisonBinaryOperator",UnaryOperator:"UnaryOperator",Set:"Set",If:"If",For:"For",In:"In",NotIn:"NotIn",Else:"Else",EndIf:"EndIf",ElseIf:"ElseIf",EndFor:"EndFor",And:"And",Or:"Or",Not:"UnaryOperator"});Object.freeze({set:TOKEN_TYPES.Set,for:TOKEN_TYPES.For,in:TOKEN_TYPES.In,if:TOKEN_TYPES.If,else:TOKEN_TYPES.Else,endif:TOKEN_TYPES.EndIf,elif:TOKEN_TYPES.ElseIf,endfor:TOKEN_TYPES.EndFor,and:TOKEN_TYPES.And,or:TOKEN_TYPES.Or,not:TOKEN_TYPES.Not,"not in":TOKEN_TYPES.NotIn,true:TOKEN_TYPES.BooleanLiteral,false:TOKEN_TYPES.BooleanLiteral});TOKEN_TYPES.OpenStatement,TOKEN_TYPES.CloseStatement,TOKEN_TYPES.OpenExpression,TOKEN_TYPES.CloseExpression,TOKEN_TYPES.OpenParen,TOKEN_TYPES.CloseParen,TOKEN_TYPES.OpenSquareBracket,TOKEN_TYPES.CloseSquareBracket,TOKEN_TYPES.Comma,TOKEN_TYPES.Dot,TOKEN_TYPES.Colon,TOKEN_TYPES.Pipe,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.AdditiveBinaryOperator,TOKEN_TYPES.AdditiveBinaryOperator,TOKEN_TYPES.MultiplicativeBinaryOperator,TOKEN_TYPES.MultiplicativeBinaryOperator,TOKEN_TYPES.MultiplicativeBinaryOperator,TOKEN_TYPES.Equals;const BYTES_TO_UNICODE=(()=>{const b=[...Array.from({length:94},(c,f)=>f+33),...Array.from({length:12},(c,f)=>f+161),...Array.from({length:82},(c,f)=>f+174)],n=b.slice();let a=0;for(let c=0;c<256;++c)b.includes(c)||(b.push(c),n.push(256+a),a+=1);const u=n.map(c=>String.fromCharCode(c));return Object.fromEntries(b.map((c,f)=>[c,u[f]]))})();reverseDictionary(BYTES_TO_UNICODE);const WHISPER_LANGUAGES=[["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"]];new Map(WHISPER_LANGUAGES);async function loadConfig(b,n){return await getModelJSON(b,"config.json",!0,n)}class PretrainedConfig{constructor(n){this.model_type=null,this.is_encoder_decoder=!1,Object.assign(this,n)}static async from_pretrained(n,{progress_callback:a=null,config:u=null,cache_dir:c=null,local_files_only:f=!1,revision:s="main"}={}){let h=u??await loadConfig(n,{progress_callback:a,config:u,cache_dir:c,local_files_only:f,revision:s});return new this(h)}}class AutoConfig{static async from_pretrained(...n){return PretrainedConfig.from_pretrained(...n)}}class LogitsProcessorList extends Callable{constructor(){super(),this.processors=[]}push(n){this.processors.push(n)}extend(n){this.processors.push(...n)}_call(n,a){for(let u of a)this.processors.forEach(c=>c(n,u))}[Symbol.iterator](){return this.processors.values()}}class LogitsProcessor extends Callable{_call(n,a){throw Error("`_call` should be implemented in a subclass")}}class ForceTokensLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.force_token_map=Object.fromEntries(n??[])}_call(n,a){let u=this.force_token_map[n.length];return exists(u)&&(a.data.fill(-1/0),a.data[u]=0),a}}class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.bos_token_id=n}_call(n,a){return n.length===1&&(a.data.fill(-1/0),a.data[this.bos_token_id]=0),a}}class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(n,a){super(),this.max_length=n,this.forced_eos_token_id=a}_call(n,a){}}class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(n,a){super(),this.begin_suppress_tokens=n,this.begin_index=a}_call(n,a){if(n.length===this.begin_index)for(let u of this.begin_suppress_tokens)a.data[u]=-1/0;return a}}class WhisperTimeStampLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.eos_token_id=n.eos_token_id,this.no_timestamps_token_id=n.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(n.forced_decoder_ids||[]).length+2,n.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=n.max_initial_timestamp_index}_call(n,a){const u=a.data;if(u[this.no_timestamps_token_id]=-1/0,n.length===this.begin_index-1)return u.fill(-1/0),u[this.timestamp_begin]=0,a;const c=n.slice(this.begin_index),f=c.length>=1&&c[c.length-1]>=this.timestamp_begin,s=c.length<2||c[c.length-2]>=this.timestamp_begin;if(f&&(s?u.subarray(this.timestamp_begin).fill(-1/0):u.subarray(0,this.eos_token_id).fill(-1/0)),n.length===this.begin_index&&this.max_initial_timestamp_index!==null){const o=this.timestamp_begin+this.max_initial_timestamp_index;u.subarray(o+1).fill(-1/0)}const h=log_softmax(u),p=Math.log(h.subarray(this.timestamp_begin).map(Math.exp).reduce((o,t)=>o+t)),l=max(h.subarray(0,this.timestamp_begin))[0];return p>l&&u.subarray(0,this.timestamp_begin).fill(-1/0),a}}class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.no_repeat_ngram_size=n}getNgrams(n){const a=n.length,u=[];for(let f=0;f0&&(c=c.map(f=>f/this.generation_config.temperature)),c}randomSelect(n){let a=n.reduce((c,f)=>c+f,0),u=Math.random()*a;for(let c=0;c1)return new BeamSearchSampler(n);if(n.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${n.num_return_sequences}.`);return new GreedySampler(n)}}class GreedySampler extends Sampler{sample(n,a=-1){let u=this.getLogits(n,a);return[[max(u)[1],0]]}}class MultinomialSampler extends Sampler{sample(n,a=-1){let u=n.dims.at(-1);this.generation_config.top_k>0&&(u=Math.min(this.generation_config.top_k,u));const c=this.getLogits(n,a),f=getTopItems(c,u),s=softmax(f.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},()=>{const h=this.randomSelect(s);return[f[h][0],Math.log(s[h])]})}}class BeamSearchSampler extends Sampler{sample(n,a=-1){let u=n.dims.at(-1);this.generation_config.top_k>0&&(u=Math.min(this.generation_config.top_k,u));const c=this.getLogits(n,a),f=getTopItems(c,u),s=softmax(f.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},(h,p)=>[f[p][0],Math.log(s[p])])}}const{InferenceSession,Tensor:ONNXTensor,env}=ONNX,MODEL_TYPES={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4,MaskGeneration:5},MODEL_TYPE_MAPPING=new Map,MODEL_NAME_TO_CLASS_MAPPING=new Map,MODEL_CLASS_TO_NAME_MAPPING=new Map;async function constructSession(b,n,a){let u=`onnx/${n}${a.quantized?"_quantized":""}.onnx`,c=await getModelFile(b,u,!0,a);try{return await InferenceSession.create(c,{executionProviders})}catch(f){if(executionProviders.length===1&&executionProviders[0]==="wasm")throw f;return console.warn(f),console.warn("Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback. "),await InferenceSession.create(c,{executionProviders:["wasm"]})}}function validateInputs(b,n){const a=Object.create(null),u=[];for(const s of b.inputNames){const h=n[s];if(!(h instanceof Tensor)){u.push(s);continue}a[s]=env.wasm.proxy?h.clone():h}if(u.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${u.join(", ")}.`);const c=Object.keys(n).length,f=b.inputNames.length;if(c>f){let s=Object.keys(n).filter(h=>!b.inputNames.includes(h));console.warn(`WARNING: Too many inputs were provided (${c} > ${f}). The following inputs will be ignored: "${s.join(", ")}".`)}return a}async function sessionRun(b,n){const a=validateInputs(b,n);try{let u=await b.run(a);return u=replaceTensors(u),u}catch(u){throw console.error(`An error occurred during model execution: "${u}".`),console.error("Inputs given to model:",a),u}}function replaceTensors(b){for(let n in b)b[n]instanceof ONNXTensor?b[n]=new Tensor(b[n]):typeof b[n]=="object"&&replaceTensors(b[n]);return b}function toI64Tensor(b){if(b instanceof Tensor)return b;if(b.length===0)throw Error("items must be non-empty");if(Array.isArray(b[0])){if(b.some(n=>n.length!==b[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' and/or 'truncation=True' to have batched tensors with the same length.");return new Tensor("int64",BigInt64Array.from(b.flat().map(n=>BigInt(n))),[b.length,b[0].length])}else return new Tensor("int64",BigInt64Array.from(b.map(n=>BigInt(n))),[1,b.length])}function prepareAttentionMask(b,n){let a=b.config.pad_token_id??null,u=b.config.eos_token_id??null;isIntegralNumber(u)&&(u=[u]);let c=n.indexOf(a)!==-1,f=u===null||!u.includes(a);if(c&&f){let s=BigInt64Array.from(n.data.map(h=>h!=a));return new Tensor("int64",s,n.dims)}else return ones_like(n)}function preparePositionIds(b,n,a){if(!b.inputNames.includes("position_ids"))return;const u=new BigInt64Array(n.attention_mask.data.length);for(let c=0;c0&&c.push(new NoRepeatNGramLogitsProcessor(n.no_repeat_ngram_size)),n.bad_words_ids!==null&&c.push(new NoBadWordsLogitsProcessor(n.bad_words_ids,n.eos_token_id)),n.min_length!==null&&n.eos_token_id!==null&&n.min_length>0&&c.push(new MinLengthLogitsProcessor(n.min_length,n.eos_token_id)),n.min_new_tokens!==null&&n.eos_token_id!==null&&n.min_new_tokens>0&&c.push(new MinNewTokensLengthLogitsProcessor(a,n.min_new_tokens,n.eos_token_id)),n.forced_bos_token_id!==null&&c.push(new ForcedBOSTokenLogitsProcessor(n.forced_bos_token_id)),n.forced_eos_token_id!==null&&c.push(new ForcedEOSTokenLogitsProcessor(n.max_length,n.forced_eos_token_id)),n.begin_suppress_tokens!==null){let f=a>1||n.forced_bos_token_id===null?a:a+1;n.forced_decoder_ids!==null&&(f+=n.forced_decoder_ids[n.forced_decoder_ids.length-1][0]),c.push(new SuppressTokensAtBeginLogitsProcessor(n.begin_suppress_tokens,f))}return n.forced_decoder_ids!==null&&c.push(new ForceTokensLogitsProcessor(n.forced_decoder_ids)),u!==null&&c.extend(u),c}_get_generation_config(n){let a=new GenerationConfig(this.config);return"generation_config"in this&&Object.assign(a,this.generation_config),n!==null&&Object.assign(a,n),a}async generate(n,a=null,u=null,{inputs_attention_mask:c=null}={}){if(!this.can_generate){let g=`The current model class (${MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const m=this.config.model_type,_=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(m)??MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES.get(m)??MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES.get(m)??MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES.get(m);throw _&&(g+=` Please use the following class instead: '${_[0]}'`),Error(g)}if(!(n instanceof Tensor)&&!isTypedArray(n)&&!Array.isArray(n))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${n.constructor.name}".`);let f;if(this.config.is_encoder_decoder)f=0;else if(f=n instanceof Tensor?n.dims.at(-1):n.length,f===0)throw Error("Must supply a non-empty array of input token ids.");a=this._get_generation_config(a),u=u??new LogitsProcessorList,u=this._get_logits_processor(a,f,u);let s=a.eos_token_id;s!==null&&!Array.isArray(s)&&(s=[s]);let h=1;const p=h+(a.max_new_tokens??1/0),l=Number.isInteger(a.max_length)&&(a.max_new_tokens??null)===null;let o=Sampler.getSampler(a),t=this.getStartBeams(n,a,h,c);for(;t.some(d=>!d.done)&&h=a.max_length){g.done=!0,d.push(g);continue}let m=await this.runBeam(g);a.output_attentions&&this.addAttentionsToBeam(g,m),a.output_scores;let _=m.logits.slice(null,-1,null);u(g.output_token_ids,_);let y=o(_);for(let[T,w]of y){let S={...g};this.updateBeam(S,T),S.score+=w,s&&s.includes(T)&&(S.done=!0),d.push(S)}}++h,d=this.groupBeams(d).map(g=>g.sort((m,_)=>_.score-m.score).slice(0,a.num_beams)),t=d.flat(),a.callback_function&&a.callback_function(t)}const e=this.groupBeams(t),r=d=>e.map(g=>a.num_return_sequences>1?g.slice(0,a.num_return_sequences).map(m=>m[d]):[g[0][d]]).flat(),i=r("output_token_ids");if(a.return_dict_in_generate){const d=r("decoder_attentions"),g=r("cross_attentions");return{sequences:i,decoder_attentions:d,cross_attentions:g}}else return i}addAttentionsToBeam(n,a){if(this.config.is_encoder_decoder){if(!a.cross_attentions||a.cross_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce cross-attentions. This is most likely because the model was not exported with `output_attentions=True`.");n.cross_attentions||(n.cross_attentions=[]),n.cross_attentions.push(a.cross_attentions)}if(!a.decoder_attentions||a.decoder_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce decoder-attentions. This is most likely because the model was not exported with `output_attentions=True`.");n.decoder_attentions||(n.decoder_attentions=[]),n.decoder_attentions.push(a.decoder_attentions)}groupBeams(n){const a=Object.create(null);for(const u of n)a[u.id]===void 0?a[u.id]=[u]:a[u.id].push(u);return Object.values(a)}getPastKeyValues(n,a){const u=Object.create(null);for(const c in n)if(c.startsWith("present")){let f=c.replace("present","past_key_values");a&&c.includes("encoder")?u[f]=a[f]:u[f]=n[c]}return u}getAttentions(n){const a=Object.create(null);for(const u of["cross_attentions","decoder_attentions"]){const c=[];for(const f in n)if(f.startsWith(u)){const s=f.split(".").pop();c[s]=n[f]}a[u]=c}return a}addPastKeyValues(n,a){if(a)Object.assign(n,a);else if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??!0)){let c=[1,this.num_encoder_heads,0,this.encoder_dim_kv],f=[1,this.num_decoder_heads,0,this.decoder_dim_kv];for(let s=0;s{let o=Array.from({length:this.config.decoder_layers},(g,m)=>cat(l.map(_=>_[m]),2)),t=stack(a.map(([g,m])=>u?o[g].slice(null,m,null,[0,u]):o[g].slice(null,m)));t=t.transpose(1,0,2,3);let[e,r]=std_mean(t,-2,0,!0),i=t.clone();for(let g=0;gt[m+1]-t[m]),i=mergeArrays([1],r).map(g=>!!g),d=[];for(let g=0;gc*f,1);n.input_labels=new Tensor("int64",new BigInt64Array(u).fill(1n),a)}return await sessionRun(this.prompt_encoder_mask_decoder,{input_points:n.input_points,input_labels:n.input_labels,image_embeddings:n.image_embeddings,image_positional_embeddings:n.image_positional_embeddings})}async _call(n){return new SamImageSegmentationOutput(await super._call(n))}}class SamImageSegmentationOutput extends ModelOutput{constructor({iou_scores:n,pred_masks:a}){super(),this.iou_scores=n,this.pred_masks=a}}class MarianPreTrainedModel extends PreTrainedModel{}class MarianModel extends MarianPreTrainedModel{}class MarianMTModel extends MarianPreTrainedModel{constructor(n,a,u,c){super(n,a),this.decoder_merged_session=u,this.generation_config=c,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class M2M100PreTrainedModel extends PreTrainedModel{}class M2M100Model extends M2M100PreTrainedModel{}class M2M100ForConditionalGeneration extends M2M100PreTrainedModel{constructor(n,a,u,c){super(n,a),this.decoder_merged_session=u,this.generation_config=c,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class Wav2Vec2PreTrainedModel extends PreTrainedModel{}class Wav2Vec2Model extends Wav2Vec2PreTrainedModel{}class Wav2Vec2ForCTC extends Wav2Vec2PreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class Wav2Vec2ForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class Wav2Vec2BertPreTrainedModel extends PreTrainedModel{}class Wav2Vec2BertModel extends Wav2Vec2BertPreTrainedModel{}class Wav2Vec2BertForCTC extends Wav2Vec2BertPreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class Wav2Vec2BertForSequenceClassification extends Wav2Vec2BertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class HubertModel extends Wav2Vec2PreTrainedModel{}class HubertForCTC extends Wav2Vec2PreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class HubertForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class WavLMPreTrainedModel extends PreTrainedModel{}class WavLMModel extends WavLMPreTrainedModel{}class WavLMForCTC extends WavLMPreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class WavLMForSequenceClassification extends WavLMPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class SpeechT5PreTrainedModel extends PreTrainedModel{}class SpeechT5ForSpeechToText extends SpeechT5PreTrainedModel{}class SpeechT5ForTextToSpeech extends SpeechT5PreTrainedModel{constructor(n,a,u,c){super(n,a),this.decoder_merged_session=u,this.generation_config=c,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.hidden_size/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.hidden_size/this.num_encoder_heads}async generate_speech(n,a,{threshold:u=.5,minlenratio:c=0,maxlenratio:f=20,vocoder:s=null}={}){const h={input_ids:n},{encoder_outputs:p,encoder_attention_mask:l}=await encoderForward(this,h),o=p.dims[1]/this.config.reduction_factor,t=Math.floor(o*f),e=Math.floor(o*c),r=this.config.num_mel_bins;let i=[],d=null,g=null,m=0;for(;;){++m;const T=boolTensor(!!g);let w;g?w=g.output_sequence_out:w=new Tensor("float32",new Float32Array(r),[1,1,r]);let S={use_cache_branch:T,output_sequence:w,encoder_attention_mask:l,speaker_embeddings:a,encoder_hidden_states:p};this.addPastKeyValues(S,d),g=await sessionRun(this.decoder_merged_session,S),d=this.getPastKeyValues(g,d);const{prob:O,spectrum:E}=g;if(i.push(E),m>=e&&(Array.from(O.data).filter(v=>v>=u).length>0||m>=t))break}const _=cat(i),{waveform:y}=await sessionRun(s.session,{spectrogram:_});return{spectrogram:_,waveform:y}}}class SpeechT5HifiGan extends PreTrainedModel{main_input_name="spectrogram"}class TrOCRPreTrainedModel extends PreTrainedModel{constructor(n,a,u){super(n,a),this.generation_config=u,this.config.pad_token_id=this.config.eos_token_id,this.num_encoder_layers=this.num_decoder_layers=this.config.decoder_layers,this.num_encoder_heads=this.num_decoder_heads=this.config.decoder_attention_heads,this.encoder_dim_kv=this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads}}class TrOCRForCausalLM extends TrOCRPreTrainedModel{}class MistralPreTrainedModel extends PreTrainedModel{constructor(n,a,u){super(n,a),this.generation_config=u,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class MistralModel extends MistralPreTrainedModel{}class MistralForCausalLM extends MistralPreTrainedModel{}class FalconPreTrainedModel extends PreTrainedModel{constructor(n,a,u){super(n,a),this.generation_config=u,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class FalconModel extends FalconPreTrainedModel{}class FalconForCausalLM extends FalconPreTrainedModel{}class ClapPreTrainedModel extends PreTrainedModel{}class ClapModel extends ClapPreTrainedModel{}class ClapTextModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(n,a={}){return a.model_file_name??="text_model",super.from_pretrained(n,a)}}class ClapAudioModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(n,a={}){return a.model_file_name??="audio_model",super.from_pretrained(n,a)}}class VitsPreTrainedModel extends PreTrainedModel{}class VitsModel extends VitsPreTrainedModel{async _call(n){return new VitsModelOutput(await super._call(n))}}class SegformerPreTrainedModel extends PreTrainedModel{}class SegformerForImageClassification extends SegformerPreTrainedModel{}class SegformerForSemanticSegmentation extends SegformerPreTrainedModel{}class PretrainedMixin{static MODEL_CLASS_MAPPINGS=null;static BASE_IF_FAIL=!1;static async from_pretrained(n,{quantized:a=!0,progress_callback:u=null,config:c=null,cache_dir:f=null,local_files_only:s=!1,revision:h="main",model_file_name:p=null}={}){let l={quantized:a,progress_callback:u,config:c,cache_dir:f,local_files_only:s,revision:h,model_file_name:p};if(c=await AutoConfig.from_pretrained(n,l),l.config||(l.config=c),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let o of this.MODEL_CLASS_MAPPINGS){const t=o.get(c.model_type);if(t)return await t[1].from_pretrained(n,l)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${c.model_type}", attempting to construct from base class.`),await PreTrainedModel.from_pretrained(n,l);throw Error(`Unsupported model type: ${c.model_type}`)}}const MODEL_MAPPING_NAMES_ENCODER_ONLY=new Map([["bert",["BertModel",BertModel]],["roformer",["RoFormerModel",RoFormerModel]],["electra",["ElectraModel",ElectraModel]],["esm",["EsmModel",EsmModel]],["convbert",["ConvBertModel",ConvBertModel]],["camembert",["CamembertModel",CamembertModel]],["deberta",["DebertaModel",DebertaModel]],["deberta-v2",["DebertaV2Model",DebertaV2Model]],["mpnet",["MPNetModel",MPNetModel]],["albert",["AlbertModel",AlbertModel]],["distilbert",["DistilBertModel",DistilBertModel]],["roberta",["RobertaModel",RobertaModel]],["xlm",["XLMModel",XLMModel]],["xlm-roberta",["XLMRobertaModel",XLMRobertaModel]],["clap",["ClapModel",ClapModel]],["clip",["CLIPModel",CLIPModel]],["clipseg",["CLIPSegModel",CLIPSegModel]],["chinese_clip",["ChineseCLIPModel",ChineseCLIPModel]],["siglip",["SiglipModel",SiglipModel]],["mobilebert",["MobileBertModel",MobileBertModel]],["squeezebert",["SqueezeBertModel",SqueezeBertModel]],["wav2vec2",["Wav2Vec2Model",Wav2Vec2Model]],["wav2vec2-bert",["Wav2Vec2BertModel",Wav2Vec2BertModel]],["hubert",["HubertModel",HubertModel]],["wavlm",["WavLMModel",WavLMModel]],["audio-spectrogram-transformer",["ASTModel",ASTModel]],["vits",["VitsModel",VitsModel]],["detr",["DetrModel",DetrModel]],["table-transformer",["TableTransformerModel",TableTransformerModel]],["vit",["ViTModel",ViTModel]],["mobilevit",["MobileViTModel",MobileViTModel]],["owlvit",["OwlViTModel",OwlViTModel]],["beit",["BeitModel",BeitModel]],["deit",["DeiTModel",DeiTModel]],["convnext",["ConvNextModel",ConvNextModel]],["convnextv2",["ConvNextV2Model",ConvNextV2Model]],["dinov2",["Dinov2Model",Dinov2Model]],["resnet",["ResNetModel",ResNetModel]],["swin",["SwinModel",SwinModel]],["swin2sr",["Swin2SRModel",Swin2SRModel]],["donut-swin",["DonutSwinModel",DonutSwinModel]],["yolos",["YolosModel",YolosModel]],["dpt",["DPTModel",DPTModel]],["glpn",["GLPNModel",GLPNModel]],["hifigan",["SpeechT5HifiGan",SpeechT5HifiGan]]]),MODEL_MAPPING_NAMES_ENCODER_DECODER=new Map([["t5",["T5Model",T5Model]],["longt5",["LongT5Model",LongT5Model]],["mt5",["MT5Model",MT5Model]],["bart",["BartModel",BartModel]],["mbart",["MBartModel",MBartModel]],["marian",["MarianModel",MarianModel]],["whisper",["WhisperModel",WhisperModel]],["m2m_100",["M2M100Model",M2M100Model]],["blenderbot",["BlenderbotModel",BlenderbotModel]],["blenderbot-small",["BlenderbotSmallModel",BlenderbotSmallModel]]]),MODEL_MAPPING_NAMES_DECODER_ONLY=new Map([["bloom",["BloomModel",BloomModel]],["gpt2",["GPT2Model",GPT2Model]],["gptj",["GPTJModel",GPTJModel]],["gpt_bigcode",["GPTBigCodeModel",GPTBigCodeModel]],["gpt_neo",["GPTNeoModel",GPTNeoModel]],["gpt_neox",["GPTNeoXModel",GPTNeoXModel]],["codegen",["CodeGenModel",CodeGenModel]],["llama",["LlamaModel",LlamaModel]],["qwen2",["Qwen2Model",Qwen2Model]],["phi",["PhiModel",PhiModel]],["mpt",["MptModel",MptModel]],["opt",["OPTModel",OPTModel]],["mistral",["MistralModel",MistralModel]],["falcon",["FalconModel",FalconModel]]]),MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForSpeechToText",SpeechT5ForSpeechToText]],["whisper",["WhisperForConditionalGeneration",WhisperForConditionalGeneration]]]),MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForTextToSpeech",SpeechT5ForTextToSpeech]]]),MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES=new Map([["vits",["VitsModel",VitsModel]]]),MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForSequenceClassification",BertForSequenceClassification]],["roformer",["RoFormerForSequenceClassification",RoFormerForSequenceClassification]],["electra",["ElectraForSequenceClassification",ElectraForSequenceClassification]],["esm",["EsmForSequenceClassification",EsmForSequenceClassification]],["convbert",["ConvBertForSequenceClassification",ConvBertForSequenceClassification]],["camembert",["CamembertForSequenceClassification",CamembertForSequenceClassification]],["deberta",["DebertaForSequenceClassification",DebertaForSequenceClassification]],["deberta-v2",["DebertaV2ForSequenceClassification",DebertaV2ForSequenceClassification]],["mpnet",["MPNetForSequenceClassification",MPNetForSequenceClassification]],["albert",["AlbertForSequenceClassification",AlbertForSequenceClassification]],["distilbert",["DistilBertForSequenceClassification",DistilBertForSequenceClassification]],["roberta",["RobertaForSequenceClassification",RobertaForSequenceClassification]],["xlm",["XLMForSequenceClassification",XLMForSequenceClassification]],["xlm-roberta",["XLMRobertaForSequenceClassification",XLMRobertaForSequenceClassification]],["bart",["BartForSequenceClassification",BartForSequenceClassification]],["mbart",["MBartForSequenceClassification",MBartForSequenceClassification]],["mobilebert",["MobileBertForSequenceClassification",MobileBertForSequenceClassification]],["squeezebert",["SqueezeBertForSequenceClassification",SqueezeBertForSequenceClassification]]]),MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForTokenClassification",BertForTokenClassification]],["roformer",["RoFormerForTokenClassification",RoFormerForTokenClassification]],["electra",["ElectraForTokenClassification",ElectraForTokenClassification]],["esm",["EsmForTokenClassification",EsmForTokenClassification]],["convbert",["ConvBertForTokenClassification",ConvBertForTokenClassification]],["camembert",["CamembertForTokenClassification",CamembertForTokenClassification]],["deberta",["DebertaForTokenClassification",DebertaForTokenClassification]],["deberta-v2",["DebertaV2ForTokenClassification",DebertaV2ForTokenClassification]],["mpnet",["MPNetForTokenClassification",MPNetForTokenClassification]],["distilbert",["DistilBertForTokenClassification",DistilBertForTokenClassification]],["roberta",["RobertaForTokenClassification",RobertaForTokenClassification]],["xlm",["XLMForTokenClassification",XLMForTokenClassification]],["xlm-roberta",["XLMRobertaForTokenClassification",XLMRobertaForTokenClassification]]]),MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES=new Map([["t5",["T5ForConditionalGeneration",T5ForConditionalGeneration]],["longt5",["LongT5ForConditionalGeneration",LongT5ForConditionalGeneration]],["mt5",["MT5ForConditionalGeneration",MT5ForConditionalGeneration]],["bart",["BartForConditionalGeneration",BartForConditionalGeneration]],["mbart",["MBartForConditionalGeneration",MBartForConditionalGeneration]],["marian",["MarianMTModel",MarianMTModel]],["m2m_100",["M2M100ForConditionalGeneration",M2M100ForConditionalGeneration]],["blenderbot",["BlenderbotForConditionalGeneration",BlenderbotForConditionalGeneration]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",BlenderbotSmallForConditionalGeneration]]]),MODEL_WITH_LM_HEAD_MAPPING_NAMES=new Map([["bloom",["BloomForCausalLM",BloomForCausalLM]],["gpt2",["GPT2LMHeadModel",GPT2LMHeadModel]],["gptj",["GPTJForCausalLM",GPTJForCausalLM]],["gpt_bigcode",["GPTBigCodeForCausalLM",GPTBigCodeForCausalLM]],["gpt_neo",["GPTNeoForCausalLM",GPTNeoForCausalLM]],["gpt_neox",["GPTNeoXForCausalLM",GPTNeoXForCausalLM]],["codegen",["CodeGenForCausalLM",CodeGenForCausalLM]],["llama",["LlamaForCausalLM",LlamaForCausalLM]],["qwen2",["Qwen2ForCausalLM",Qwen2ForCausalLM]],["phi",["PhiForCausalLM",PhiForCausalLM]],["mpt",["MptForCausalLM",MptForCausalLM]],["opt",["OPTForCausalLM",OPTForCausalLM]],["mbart",["MBartForCausalLM",MBartForCausalLM]],["mistral",["MistralForCausalLM",MistralForCausalLM]],["falcon",["FalconForCausalLM",FalconForCausalLM]],["trocr",["TrOCRForCausalLM",TrOCRForCausalLM]]]),MODEL_FOR_MASKED_LM_MAPPING_NAMES=new Map([["bert",["BertForMaskedLM",BertForMaskedLM]],["roformer",["RoFormerForMaskedLM",RoFormerForMaskedLM]],["electra",["ElectraForMaskedLM",ElectraForMaskedLM]],["esm",["EsmForMaskedLM",EsmForMaskedLM]],["convbert",["ConvBertForMaskedLM",ConvBertForMaskedLM]],["camembert",["CamembertForMaskedLM",CamembertForMaskedLM]],["deberta",["DebertaForMaskedLM",DebertaForMaskedLM]],["deberta-v2",["DebertaV2ForMaskedLM",DebertaV2ForMaskedLM]],["mpnet",["MPNetForMaskedLM",MPNetForMaskedLM]],["albert",["AlbertForMaskedLM",AlbertForMaskedLM]],["distilbert",["DistilBertForMaskedLM",DistilBertForMaskedLM]],["roberta",["RobertaForMaskedLM",RobertaForMaskedLM]],["xlm",["XLMWithLMHeadModel",XLMWithLMHeadModel]],["xlm-roberta",["XLMRobertaForMaskedLM",XLMRobertaForMaskedLM]],["mobilebert",["MobileBertForMaskedLM",MobileBertForMaskedLM]],["squeezebert",["SqueezeBertForMaskedLM",SqueezeBertForMaskedLM]]]),MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES=new Map([["bert",["BertForQuestionAnswering",BertForQuestionAnswering]],["roformer",["RoFormerForQuestionAnswering",RoFormerForQuestionAnswering]],["electra",["ElectraForQuestionAnswering",ElectraForQuestionAnswering]],["convbert",["ConvBertForQuestionAnswering",ConvBertForQuestionAnswering]],["camembert",["CamembertForQuestionAnswering",CamembertForQuestionAnswering]],["deberta",["DebertaForQuestionAnswering",DebertaForQuestionAnswering]],["deberta-v2",["DebertaV2ForQuestionAnswering",DebertaV2ForQuestionAnswering]],["mpnet",["MPNetForQuestionAnswering",MPNetForQuestionAnswering]],["albert",["AlbertForQuestionAnswering",AlbertForQuestionAnswering]],["distilbert",["DistilBertForQuestionAnswering",DistilBertForQuestionAnswering]],["roberta",["RobertaForQuestionAnswering",RobertaForQuestionAnswering]],["xlm",["XLMForQuestionAnswering",XLMForQuestionAnswering]],["xlm-roberta",["XLMRobertaForQuestionAnswering",XLMRobertaForQuestionAnswering]],["mobilebert",["MobileBertForQuestionAnswering",MobileBertForQuestionAnswering]],["squeezebert",["SqueezeBertForQuestionAnswering",SqueezeBertForQuestionAnswering]]]),MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",VisionEncoderDecoderModel]]]),MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES=new Map([["vit",["ViTForImageClassification",ViTForImageClassification]],["mobilevit",["MobileViTForImageClassification",MobileViTForImageClassification]],["beit",["BeitForImageClassification",BeitForImageClassification]],["deit",["DeiTForImageClassification",DeiTForImageClassification]],["convnext",["ConvNextForImageClassification",ConvNextForImageClassification]],["convnextv2",["ConvNextV2ForImageClassification",ConvNextV2ForImageClassification]],["dinov2",["Dinov2ForImageClassification",Dinov2ForImageClassification]],["resnet",["ResNetForImageClassification",ResNetForImageClassification]],["swin",["SwinForImageClassification",SwinForImageClassification]],["segformer",["SegformerForImageClassification",SegformerForImageClassification]]]),MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES=new Map([["detr",["DetrForObjectDetection",DetrForObjectDetection]],["table-transformer",["TableTransformerForObjectDetection",TableTransformerForObjectDetection]],["yolos",["YolosForObjectDetection",YolosForObjectDetection]]]),MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES=new Map([["owlvit",["OwlViTForObjectDetection",OwlViTForObjectDetection]]]),MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES=new Map([["detr",["DetrForSegmentation",DetrForSegmentation]],["clipseg",["CLIPSegForImageSegmentation",CLIPSegForImageSegmentation]]]),MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES=new Map([["segformer",["SegformerForSemanticSegmentation",SegformerForSemanticSegmentation]]]),MODEL_FOR_MASK_GENERATION_MAPPING_NAMES=new Map([["sam",["SamModel",SamModel]]]),MODEL_FOR_CTC_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForCTC",Wav2Vec2ForCTC]],["wav2vec2-bert",["Wav2Vec2BertForCTC",Wav2Vec2BertForCTC]],["wavlm",["WavLMForCTC",WavLMForCTC]],["hubert",["HubertForCTC",HubertForCTC]]]),MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Wav2Vec2ForSequenceClassification]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",Wav2Vec2BertForSequenceClassification]],["wavlm",["WavLMForSequenceClassification",WavLMForSequenceClassification]],["hubert",["HubertForSequenceClassification",HubertForSequenceClassification]],["audio-spectrogram-transformer",["ASTForAudioClassification",ASTForAudioClassification]]]),MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES=new Map([["vitmatte",["VitMatteForImageMatting",VitMatteForImageMatting]]]),MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES=new Map([["swin2sr",["Swin2SRForImageSuperResolution",Swin2SRForImageSuperResolution]]]),MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES=new Map([["dpt",["DPTForDepthEstimation",DPTForDepthEstimation]],["depth_anything",["DepthAnythingForDepthEstimation",DepthAnythingForDepthEstimation]],["glpn",["GLPNForDepthEstimation",GLPNForDepthEstimation]]]),MODEL_CLASS_TYPE_MAPPING=[[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_TYPES.EncoderOnly],[MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_TYPES.EncoderDecoder],[MODEL_MAPPING_NAMES_DECODER_ONLY,MODEL_TYPES.DecoderOnly],[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_WITH_LM_HEAD_MAPPING_NAMES,MODEL_TYPES.DecoderOnly],[MODEL_FOR_MASKED_LM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Vision2Seq],[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_MASK_GENERATION_MAPPING_NAMES,MODEL_TYPES.MaskGeneration],[MODEL_FOR_CTC_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly]];for(const[b,n]of MODEL_CLASS_TYPE_MAPPING)for(const[a,u]of b.values())MODEL_TYPE_MAPPING.set(a,n),MODEL_CLASS_TO_NAME_MAPPING.set(u,a),MODEL_NAME_TO_CLASS_MAPPING.set(a,u);const CUSTOM_MAPPING=[["CLIPTextModelWithProjection",CLIPTextModelWithProjection,MODEL_TYPES.EncoderOnly],["CLIPVisionModelWithProjection",CLIPVisionModelWithProjection,MODEL_TYPES.EncoderOnly],["SiglipTextModel",SiglipTextModel,MODEL_TYPES.EncoderOnly],["SiglipVisionModel",SiglipVisionModel,MODEL_TYPES.EncoderOnly],["ClapTextModelWithProjection",ClapTextModelWithProjection,MODEL_TYPES.EncoderOnly],["ClapAudioModelWithProjection",ClapAudioModelWithProjection,MODEL_TYPES.EncoderOnly]];for(const[b,n,a]of CUSTOM_MAPPING)MODEL_TYPE_MAPPING.set(b,a),MODEL_CLASS_TO_NAME_MAPPING.set(n,b),MODEL_NAME_TO_CLASS_MAPPING.set(b,n);class AutoModel extends PretrainedMixin{static MODEL_CLASS_MAPPINGS=MODEL_CLASS_TYPE_MAPPING.map(n=>n[0]);static BASE_IF_FAIL=!0}class Seq2SeqLMOutput extends ModelOutput{constructor({logits:n,past_key_values:a,encoder_outputs:u,decoder_attentions:c=null,cross_attentions:f=null}){super(),this.logits=n,this.past_key_values=a,this.encoder_outputs=u,this.decoder_attentions=c,this.cross_attentions=f}}class SequenceClassifierOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class TokenClassifierOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class MaskedLMOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class QuestionAnsweringModelOutput extends ModelOutput{constructor({start_logits:n,end_logits:a}){super(),this.start_logits=n,this.end_logits=a}}class CausalLMOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class ImageMattingOutput extends ModelOutput{constructor({alphas:n}){super(),this.alphas=n}}class VitsModelOutput extends ModelOutput{constructor({waveform:n,spectrogram:a}){super(),this.waveform=n,this.spectrogram=a}}const BROWSER_ENV=typeof self<"u",WEBWORKER_ENV=BROWSER_ENV&&self.constructor.name==="DedicatedWorkerGlobalScope";let createCanvasFunction,ImageDataClass,loadImageFunction;if(BROWSER_ENV)createCanvasFunction=(b,n)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this browser.");return new self.OffscreenCanvas(b,n)},loadImageFunction=self.createImageBitmap,ImageDataClass=self.ImageData;else if(sharp)loadImageFunction=async b=>{const a=(await b.metadata()).channels;let{data:u,info:c}=await b.raw().toBuffer({resolveWithObject:!0});const f=new RawImage(new Uint8ClampedArray(u),c.width,c.height,c.channels);return a!==void 0&&a!==c.channels&&f.convert(a),f};else throw new Error("Unable to load image processing library.");const RESAMPLING_MAPPING={0:"nearest",1:"lanczos",2:"bilinear",3:"bicubic",4:"box",5:"hamming"},CONTENT_TYPE_MAP=new Map([["png","image/png"],["jpg","image/jpeg"],["jpeg","image/jpeg"],["gif","image/gif"]]);class RawImage{constructor(n,a,u,c){this.data=n,this.width=a,this.height=u,this.channels=c}get size(){return[this.width,this.height]}static async read(n){if(n instanceof RawImage)return n;if(typeof n=="string"||n instanceof URL)return await this.fromURL(n);throw new Error(`Unsupported input type: ${typeof n}`)}static async fromURL(n){let a=await getFile(n);if(a.status!==200)throw new Error(`Unable to read image from "${n}" (${a.status} ${a.statusText})`);let u=await a.blob();return this.fromBlob(u)}static async fromBlob(n){if(BROWSER_ENV){let a=await loadImageFunction(n);const u=createCanvasFunction(a.width,a.height).getContext("2d");return u.drawImage(a,0,0),new this(u.getImageData(0,0,a.width,a.height).data,a.width,a.height,4)}else{let a=sharp(await n.arrayBuffer());return await loadImageFunction(a)}}static fromTensor(n,a="CHW"){if(n.dims.length!==3)throw new Error(`Tensor should have 3 dimensions, but has ${n.dims.length} dimensions.`);if(a==="CHW")n=n.transpose(1,2,0);else if(a!=="HWC")throw new Error(`Unsupported channel format: ${a}`);if(!(n.data instanceof Uint8ClampedArray||n.data instanceof Uint8Array))throw new Error(`Unsupported tensor type: ${n.type}`);switch(n.dims[2]){case 1:case 2:case 3:case 4:return new RawImage(n.data,n.dims[1],n.dims[0],n.dims[2]);default:throw new Error(`Unsupported number of channels: ${n.dims[2]}`)}}grayscale(){if(this.channels===1)return this;let n=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let a=0,u=0;a=0?p=u:o=-u,c>=0?l=c:t=-c,h.drawImage(s,p,l,n,a,o,t,n,a),new RawImage(h.getImageData(0,0,n,a).data,n,a,4).convert(f)}else{let f=this.toSharp();if(u>=0&&c>=0)f=f.extract({left:Math.floor(u),top:Math.floor(c),width:n,height:a});else if(u<=0&&c<=0){let s=Math.floor(-c),h=Math.floor(-u);f=f.extend({top:s,left:h,right:n-this.width-h,bottom:a-this.height-s})}else{let s=[0,0],h=0;c<0?(s[0]=Math.floor(-c),s[1]=a-this.height-s[0]):h=Math.floor(c);let p=[0,0],l=0;u<0?(p[0]=Math.floor(-u),p[1]=n-this.width-p[0]):l=Math.floor(u),f=f.extend({top:s[0],bottom:s[1],left:p[0],right:p[1]}).extract({left:l,top:h,width:n,height:a})}return await loadImageFunction(f)}}async toBlob(n="image/png",a=1){if(!BROWSER_ENV)throw new Error("toBlob() is only supported in browser environments.");return await this.toCanvas().convertToBlob({type:n,quality:a})}toCanvas(){if(!BROWSER_ENV)throw new Error("toCanvas() is only supported in browser environments.");let n=this.clone().rgba(),a=createCanvasFunction(n.width,n.height),u=new ImageDataClass(n.data,n.width,n.height);return a.getContext("2d").putImageData(u,0,0),a}_update(n,a,u,c=null){return this.data=n,this.width=a,this.height=u,c!==null&&(this.channels=c),this}clone(){return new RawImage(this.data.slice(),this.width,this.height,this.channels)}convert(n){if(this.channels===n)return this;switch(n){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(n){if(BROWSER_ENV){if(WEBWORKER_ENV)throw new Error("Unable to save an image from a Web Worker.");const a=n.split(".").pop().toLowerCase(),u=CONTENT_TYPE_MAP.get(a)??"image/png",c=await this.toBlob(u),f=URL.createObjectURL(c),s=document.createElement("a");s.href=f,s.download=n,s.click(),s.remove()}else{if(env$1.useFS)return await this.toSharp().toFile(n);throw new Error("Unable to save the image because filesystem is disabled in this environment.")}}toSharp(){if(BROWSER_ENV)throw new Error("toSharp() is only supported in server-side environments.");return sharp(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}}function hanning(b){if(b<1)return new Float64Array;if(b===1)return new Float64Array([1]);const n=b-1,a=Math.PI/n,u=new Float64Array(b);for(let c=0;c2595*Math.log10(1+b/700),kaldi:b=>1127*Math.log(1+b/700),slaney:(b,n=1e3,a=15,u=27/Math.log(6.4))=>b>=n?a+Math.log(b/n)*u:3*b/200};function hertz_to_mel(b,n="htk"){const a=HERTZ_TO_MEL_MAPPING[n];if(!a)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return typeof b=="number"?a(b):b.map(u=>a(u))}const MEL_TO_HERTZ_MAPPING={htk:b=>700*(10**(b/2595)-1),kaldi:b=>700*(Math.exp(b/1127)-1),slaney:(b,n=1e3,a=15,u=Math.log(6.4)/27)=>b>=a?n*Math.exp(u*(b-a)):200*b/3};function mel_to_hertz(b,n="htk"){const a=MEL_TO_HERTZ_MAPPING[n];if(!a)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return typeof b=="number"?a(b):b.map(u=>a(u))}function _create_triangular_filter_bank(b,n){const a=Float64Array.from({length:n.length-1},(s,h)=>n[h+1]-n[h]),u=Array.from({length:b.length},()=>new Array(n.length));for(let s=0;snew Array(b.length));for(let s=0;sb+u*f)}function mel_filter_bank(b,n,a,u,c,f=null,s="htk",h=!1){if(f!==null&&f!=="slaney")throw new Error('norm must be one of null or "slaney"');const p=hertz_to_mel(a,s),l=hertz_to_mel(u,s),o=linspace(p,l,n+2);let t=mel_to_hertz(o,s),e;if(h){const i=c/(b*2);e=hertz_to_mel(Float64Array.from({length:b},(d,g)=>g*i),s),t=o}else e=linspace(0,Math.floor(c/2),b);const r=_create_triangular_filter_bank(e,t);if(f!==null&&f==="slaney")for(let i=0;ic)throw Error(`frame_length (${a}) may not be larger than fft_length (${c})`);if(T!==a)throw new Error(`Length of the window (${T}) must equal frame_length (${a})`);if(u<=0)throw new Error("hop_length must be greater than zero");if(s){if(h!=="reflect")throw new Error(`pad_mode="${h}" not implemented yet.`);const C=Math.floor((c-1)/2)+1;b=padReflect(b,C,C)}const w=Math.floor(1+Math.floor((b.length-a)/u)),S=p?Math.floor(c/2)+1:c;let O=w,E=w;m!==null&&(m>w?_&&(E=m):E=O=m);const v=new FFT(c),P=new Float64Array(c),L=new Float64Array(v.outputBufferSize),V=new Array(O);for(let C=0;C=1;--z)P[z]-=l*P[z-1];P[0]*=1-l}for(let z=0;zMath.pow(h,.85));break;default:throw new Error(`Unknown window type ${n}.`)}if(a&&(s=s.subarray(0,b)),u===null)return s;if(b>u)throw new Error(`Length of the window (${b}) may not be larger than frame_length (${u})`);return s}function center_to_corners_format([b,n,a,u]){return[b-a/2,n-u/2,b+a/2,n+u/2]}function post_process_object_detection(b,n=.5,a=null,u=!1){const c=b.logits,f=b.pred_boxes,[s,h,p]=c.dims;if(a!==null&&a.length!==s)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let l=[];for(let o=0;on&&m.push(y)}else{let y=max(g.data)[1];if(y===p-1)continue;m.push(y),_=softmax(g.data)}for(const y of m){let T=i[d].data;T=center_to_corners_format(T),t!==null&&(T=T.map((w,S)=>w*t[(S+1)%2])),e.boxes.push(T),e.classes.push(y),e.scores.push(_[y])}}l.push(e)}return l}function validate_audio_inputs(b,n){if(!(b instanceof Float32Array||b instanceof Float64Array))throw new Error(`${n} expects input to be a Float32Array or a Float64Array, but got ${b?.constructor?.name??typeof b} 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 constraint_to_multiple_of(b,n,a=0,u=null){let c=Math.round(b/n)*n;return u!==null&&c>u&&(c=Math.floor(b/n)*n),cf?l=Math.floor(f*p/c):f>c&&(p=Math.floor(c*l/f)),await n.resize(l,p,{resample:u}))}async crop_margin(n,a=200){const u=n.clone().grayscale(),c=min(u.data)[0],s=max(u.data)[0]-c;if(s===0)return n;const h=a/255;let p=u.width,l=u.height,o=0,t=0;for(let e=0;ethis.preprocess(f)));return{pixel_values:stack(u.map(f=>f.pixel_values),0),original_sizes:u.map(f=>f.original_size),reshaped_input_sizes:u.map(f=>f.reshaped_input_size)}}}class SegformerFeatureExtractor extends ImageFeatureExtractor{post_process_semantic_segmentation(n,a=null){const u=n.logits,c=u.dims[0];if(a!==null&&a.length!==c)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const f=[];for(let s=0;se[_]&&(e[_]=m[_],t.data[_]=g)}const r=new Array(p.dims[0]),i=t.data;for(let g=0;gg!==void 0);f.push({segmentation:t,labels:d})}return f}}class DPTImageProcessor extends ImageFeatureExtractor{}class BitImageProcessor extends ImageFeatureExtractor{}class DPTFeatureExtractor extends ImageFeatureExtractor{}class GLPNFeatureExtractor extends ImageFeatureExtractor{}class CLIPFeatureExtractor extends ImageFeatureExtractor{}class ChineseCLIPFeatureExtractor extends ImageFeatureExtractor{}class SiglipImageProcessor extends ImageFeatureExtractor{}class ConvNextFeatureExtractor extends ImageFeatureExtractor{constructor(n){super(n),this.crop_pct=this.config.crop_pct??224/256}async resize(n){const a=this.size?.shortest_edge;if(a===void 0)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(a<384){const u=Math.floor(a/this.crop_pct),[c,f]=this.get_resize_output_image_size(n,{shortest_edge:u});n=await n.resize(c,f,{resample:this.resample}),n=await n.center_crop(a,a)}else n=await n.resize(a,a,{resample:this.resample});return n}}class ConvNextImageProcessor extends ConvNextFeatureExtractor{}class ViTFeatureExtractor extends ImageFeatureExtractor{}class ViTImageProcessor extends ImageFeatureExtractor{}class MobileViTFeatureExtractor extends ImageFeatureExtractor{}class OwlViTFeatureExtractor extends ImageFeatureExtractor{post_process_object_detection(...n){return post_process_object_detection(...n)}}class DeiTFeatureExtractor extends ImageFeatureExtractor{}class BeitFeatureExtractor extends ImageFeatureExtractor{}class DonutFeatureExtractor extends ImageFeatureExtractor{pad_image(n,a,u,c={}){const[f,s,h]=a;let p=this.image_mean;Array.isArray(this.image_mean)||(p=new Array(h).fill(p));let l=this.image_std;Array.isArray(l)||(l=new Array(h).fill(p));const o=p.map((t,e)=>-t/this.image_std[e]);return super.pad_image(n,a,u,{center:!0,constant_values:o,...c})}}class NougatImageProcessor extends DonutFeatureExtractor{}class DetrFeatureExtractor extends ImageFeatureExtractor{async _call(n){const a=await super._call(n),u=[a.pixel_values.dims[0],64,64],c=new Tensor("int64",new BigInt64Array(u.reduce((f,s)=>f*s)).fill(1n),u);return{...a,pixel_mask:c}}post_process_object_detection(...n){return post_process_object_detection(...n)}remove_low_and_no_objects(n,a,u,c){let f=[],s=[],h=[];for(let p=0;pu&&(f.push(o),s.push(r),h.push(t))}return[f,s,h]}check_segment_validity(n,a,u,c=.5,f=.8){let s=[],h=0,p=0;for(let o=0;o=c&&++p;let l=h>0&&p>0;return l&&(l=h/p>f),[l,s]}compute_segments(n,a,u,c,f,s=null,h=null){let[p,l]=h??n[0].dims,o=new Tensor("int32",new Int32Array(p*l),[p,l]),t=[];if(h!==null)for(let d=0;dr[m]&&(e[m]=d,r[m]=n[d].data[m])}let i=0;for(let d=0;dc!==a.dims[f]))throw Error(`The first ${u.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new Tensor("int64",n.flat(1/0).map(BigInt),u)}async _call(n,a=null,u=null){const c=await super._call(n);if(a&&(c.input_points=this.reshape_input_points(a,c.original_sizes,c.reshaped_input_sizes)),u){if(!c.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");c.input_labels=this.add_input_labels(u,c.input_points)}return c}post_process_masks(n,a,u,{mask_threshold:c=0,binarize:f=!0,pad_size:s=null}={}){const h=[];s=s??this.pad_size;const p=[s.height,s.width];for(let l=0;lc&&(m[_]=1);g=new Tensor("bool",m,g.dims)}r.push(g)}h.push(stack(r))}return h}}class Swin2SRImageProcessor extends ImageFeatureExtractor{pad_image(n,a,u,c={}){const[f,s,h]=a;return super.pad_image(n,a,{width:f+(u-f%u)%u,height:s+(u-s%u)%u},{mode:"symmetric",center:!1,constant_values:-1,...c})}}class VitMatteImageProcessor extends ImageFeatureExtractor{async _call(n,a){Array.isArray(n)||(n=[n]),Array.isArray(a)||(a=[a]);const u=await Promise.all(n.map(s=>this.preprocess(s))),c=await Promise.all(a.map(s=>this.preprocess(s,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:stack(u.map((s,h)=>cat([s.pixel_values,c[h].pixel_values],0)),0),original_sizes:u.map(s=>s.original_size),reshaped_input_sizes:u.map(s=>s.reshaped_input_size)}}}class WhisperFeatureExtractor extends FeatureExtractor{constructor(n){super(n),this.config.mel_filters??=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=window_function(this.config.n_fft,"hann")}_extract_fbank_features(n){const{data:a,dims:u}=spectrogram(n,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}),c=max(a)[0];for(let f=0;fthis.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`."),a=n.slice(0,this.config.n_samples)):(a=new Float32Array(this.config.n_samples),a.set(n));const{data:u,dims:c}=this._extract_fbank_features(a);return{input_features:new Tensor("float32",u,[1,...c])}}}class Wav2Vec2FeatureExtractor extends FeatureExtractor{_zero_mean_unit_var_norm(n){const u=n.reduce((f,s)=>f+s,0)/n.length,c=n.reduce((f,s)=>f+(s-u)**2,0)/n.length;return n.map(f=>(f-u)/Math.sqrt(c+1e-7))}async _call(n){validate_audio_inputs(n,"Wav2Vec2FeatureExtractor"),n instanceof Float64Array&&(n=new Float32Array(n));let a=n;this.config.do_normalize&&(a=this._zero_mean_unit_var_norm(a));const u=[1,a.length];return{input_values:new Tensor("float32",a,u),attention_mask:new Tensor("int64",new BigInt64Array(a.length).fill(1n),u)}}}class SeamlessM4TFeatureExtractor extends FeatureExtractor{constructor(n){super(n);const a=this.config.sampling_rate,u=mel_filter_bank(256,this.config.num_mel_bins,20,Math.floor(a/2),a,null,"kaldi",!0);for(let c=0;cu*32768),spectrogram(n,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:a,transpose:!0})}async _call(n,{padding:a=!0,pad_to_multiple_of:u=2,do_normalize_per_mel_bins:c=!0,return_attention_mask:f=!0}={}){validate_audio_inputs(n,"SeamlessM4TFeatureExtractor");let s=this._extract_fbank_features(n,this.config.max_length);if(c){const[i,d]=s.dims;for(let g=0;g0){const m=new Float32Array(d*(i+g));m.set(s.data),m.fill(this.config.padding_value,s.data.length);const _=i+g;s={data:m,dims:[_,d]},f&&(h=new Tensor("int64",new BigInt64Array(_),[1,_]),h.data.fill(1n,0,i))}}const[p,l]=s.dims,o=this.config.stride;if(p%o!==0)throw new Error(`The number of frames (${p}) must be a multiple of the stride (${o}).`);const e=new Tensor("float32",s.data,s.dims).view(1,Math.floor(p/o),l*o),r={input_features:e};if(f){const i=e.dims[1],d=new Tensor("int64",new BigInt64Array(i),[1,i]);if(h)for(let g=1,m=0;g0)if(u==="rand_trunc"){s=!0;const p=Math.floor(Math.random()*(h+1));n=n.subarray(p,p+a),f=this._extract_fbank_features(n,this.mel_filters_slaney,this.config.nb_max_samples),f.dims=[1,...f.dims]}else throw new Error(`Truncation strategy "${u}" not implemented`);else{if(h<0){let p=new Float64Array(a);if(p.set(n),c==="repeat")for(let l=n.length;l{b.preventDefault(),predict(EXAMPLE_URL)});fileUpload.addEventListener("change",function(b){const n=b.target.files[0];if(!n)return;const a=new FileReader;a.onload=u=>predict(u.target.result),a.readAsDataURL(n)});async function predict(b){const n=await RawImage.fromURL(b);imageContainer.innerHTML="",imageContainer.style.backgroundImage=`url(${b})`;const a=n.width/n.height,[u,c]=a>720/480?[720,720/a]:[480*a,480];imageContainer.style.width=`${u}px`,imageContainer.style.height=`${c}px`,status.textContent="Analysing...";const{pixel_values:f}=await processor(n),{output:s}=await model({input:f}),h=await RawImage.fromTensor(s[0].mul(255).to("uint8")).resize(n.width,n.height),p=document.createElement("canvas");p.width=n.width,p.height=n.height;const l=p.getContext("2d");l.drawImage(n.toCanvas(),0,0);const o=l.getImageData(0,0,n.width,n.height);for(let t=0;t