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expected";if(e.opsetImport!=null&&e.hasOwnProperty("opsetImport")){if(!Array.isArray(e.opsetImport))return"opsetImport: array expected";for(var r=0;r>>0,e.irVersion.high>>>0).toNumber())),e.opsetImport){if(!Array.isArray(e.opsetImport))throw TypeError(".onnx.ModelProto.opsetImport: array expected");r.opsetImport=[];for(var i=0;i>>0,e.modelVersion.high>>>0).toNumber())),e.docString!=null&&(r.docString=String(e.docString)),e.graph!=null){if(typeof e.graph!="object")throw TypeError(".onnx.ModelProto.graph: object expected");r.graph=s.onnx.GraphProto.fromObject(e.graph)}if(e.metadataProps){if(!Array.isArray(e.metadataProps))throw TypeError(".onnx.ModelProto.metadataProps: array 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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(s.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(s.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=s.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=s.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 s.onnx.TensorProto.Segment)return r;var i=new s.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,a.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}(),p.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(s.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 s.onnx.TensorShapeProto.Dimension)return i;var d=new s.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=s.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=s.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 s.onnx.TypeProto)return r;var i=new s.onnx.TypeProto;if(r.tensorType!=null){if(typeof r.tensorType!="object")throw TypeError(".onnx.TypeProto.tensorType: object expected");i.tensorType=s.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 s.onnx.OperatorSetIdProto)return e;var r=new s.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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s.isPacked?this.getPackedOutputSamplingSnippet(s):this.getUnpackedOutputSamplingSnippet(s)}getPackedOutputSamplingSnippet(s){const t=s.unpackedShape,e=[s.width,s.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,p.getGlsl)(this.context.glContext.version).output} = val; } `;return r.floatTextureSetRGBA=new c.GlslLibRoutine(d),r}getUnpackedOutputSamplingSnippet(s){const t=s.unpackedShape,e=[s.width,s.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,p.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(s,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 * ${e[0]} + resTexRC.x); } `,new c.GlslLibRoutine(r))}getOutputPacked2DCoords(s,t){let e="";if(u.ArrayUtil.arraysEqual(s,t))return e=` ivec2 getOutputCoords() { return 2 * ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]})); } `,new c.GlslLibRoutine(e);const r=t,i=Math.ceil(s[1]/2);return e=` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(TexCoords.xy * vec2(${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 / ${i}); return ivec2(r, c); } `,new c.GlslLibRoutine(e)}getOutputPacked3DCoords(s,t){const e=[t[0],t[1]],r=Math.ceil(s[2]/2),i=r*Math.ceil(s[1]/2),d=` ivec3 getOutputCoords() { ivec2 resTexRC = ivec2(TexCoords.xy * vec2(${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(s,t){const e=[t[0],t[1]],r=Math.ceil(s[s.length-1]/2),i=r*Math.ceil(s[s.length-2]/2);let d=i,g="",m="b, r, c";for(let y=2;y=0;--m)i[m]=i[m+1]*s[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(s,t){let e="";const r=s.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=s[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*s[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(s,t){let e="";const r=s.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=s[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*s[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(s,t){let e="";const r=s.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=s[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*s[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]})); 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int texC = texelIndex - texR * texNumC; return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR); } `),t="packedUVfrom3D",s[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,p.getGlsl)(this.context.glContext.version);return s[t]=new c.GlslLibRoutine(` float sampleTexture(sampler2D textureSampler, vec2 uv) { return ${e.texture2D}(textureSampler, uv).r; }`),s}getInputsSamplingSnippets(){const s={},t=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,r)=>{const i=this.context.inputTextureLayouts[r],d=(0,h.generateShaderFuncNameFromInputSamplerName)(e);i.isPacked?s[d]=this.getPackedSamplerFromInput(d,e,i):s[d]=this.getUnpackedSamplerFromInput(d,e,i);const g=(0,h.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(e);i.unpackedShape.length<=t.unpackedShape.length&&(i.isPacked?s[g]=this.getPackedSamplerAtOutputCoords(g,i,t,e):s[g]=this.getUnpackedSamplerAtOutputCoords(g,i,t,e))}),s}getPackedSamplerAtOutputCoords(s,t,e,r){const i=t.unpackedShape,d=e.unpackedShape,g=r,m=(0,h.generateShaderFuncNameFromInputSamplerName)(g),_=i.length,y=d.length,w=u.BroadcastUtil.getBroadcastDims(i,d),v=(0,h.getCoordsDataType)(y),S=y-_;let A;const O=(0,h.getGlChannels)();A=_===0?"":y<2&&w.length>=1?"coords = 0;":w.map(F=>`coords.${O[F+S]} = 0;`).join(` `);let x="";x=y<2&&_>0?"coords":i.map((F,V)=>`coords.${O[V+S]}`).join(", ");let I="return outputValue;";const N=u.ShapeUtil.size(i)===1,R=u.ShapeUtil.size(d)===1;if(_!==1||N||R){if(N&&!R)I=y===1?` return 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this.getUnpackedSampler2D(s,t,e);case 3:return this.getUnpackedSampler3D(s,t,e);case 4:return this.getUnpackedSampler4D(s,t,e);case 5:return this.getUnpackedSampler5D(s,t,e);case 6:return this.getUnpackedSampler6D(s,t,e);default:throw new Error(`Unsupported dimension ${r.length}-D`)}}getPackedSamplerScalar(s,t){const e=` vec4 ${s}() { return ${(0,p.getGlsl)(this.context.glContext.version).texture2D}(${t}, halfCR); } `;return new c.GlslLibRoutine(e)}getPackedSampler1D(s,t,e){const r=[e.width,e.height],i=[r[1],r[0]],d=(0,p.getGlsl)(this.context.glContext.version),g=`vec4 ${s}(int index) { vec2 uv = packedUVfrom1D( ${i[0]}, ${i[1]}, index); return ${d.texture2D}(${t}, uv); }`;return new c.GlslLibRoutine(g,["coordinates.packedUVfrom1D"])}getPackedSampler2D(s,t,e){const r=e.unpackedShape,i=[e.width,e.height],d=(0,p.getGlsl)(this.context.glContext.version),g=i[0],m=i[1];if(i!=null&&u.ArrayUtil.arraysEqual(r,i)){const v=`vec4 ${s}(int row, int col) { vec2 uv = (vec2(col, row) + halfCR) / 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c.GlslLibRoutine(w,["coordinates.packedUVfrom3D"])}getPackedSamplerND(s,t,e){const r=e.unpackedShape,i=r.length,d=[e.width,e.height],g=(0,p.getGlsl)(this.context.glContext.version),m=[d[0],d[1]],_=m[1],y=m[0],w=Math.ceil(r[i-1]/2);let v=w*Math.ceil(r[i-2]/2),S="int b, int row, int col",A=`b * ${v} + (row / 2) * ${w} + (col / 2)`;for(let x=2;x{const r=this.context.inputTextureLayouts[e],i=(r.unpackedShape.length>0?r.unpackedShape:r.shape).length;let d=`_${t}`;s[d]=new c.GlslLibRoutine(this.getValueFromSingle(t,i,r.width,r.height,!1),[`shapeUtils.indicesToOffset${d}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"]),d+="_T",s[d]=new c.GlslLibRoutine(this.getValueFromSingle(t,i,r.width,r.height,!0),[`shapeUtils.indicesToOffset${d}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"])}),s}getValueFromSingle(s,t,e,r,i){let d=`_${s}`;return i&&(d+="_T"),` float ${d}(int m[${t}]) { int offset = indicesToOffset${d}(m); vec2 coords = offsetToCoords(offset, ${e}, ${r}); float 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Object.assign(Object.assign({},O),{output:{dims:V,type:A[0].type,textureType:p.TextureType.unpacked},shaderSource:X,hasMain:!0})})(g,m,y,_)})})(r,i,d),i),t=(r,i)=>{const d=r.kernelShape.slice();if(r.kernelShape.length===0)for(let y=2;y{const N=y.length-2,R=I.length===0;for(let L=0;L{const i=r.attributes,d=(0,a.parseInternalActivationAttributes)(i),g=i.getString("auto_pad","NOTSET"),m=i.getInts("dilations",[1,1]),_=i.getInt("group",1),y=i.getInts("kernel_shape",[]),w=i.getInts("output_padding",[0,0]),v=i.getInts("output_shape",[]),S=i.getInts("pads",[0,0,0,0]),A=i.getInts("strides",[1,1]);return(0,u.createAttributeWithCacheKey)(Object.assign({autoPad:g,dilations:m,group:_,kernelShape:y,outputPadding:w,outputShape:v,pads:S,strides:A},d))};const e=(r,i)=>{if(!r||r.length!==2&&r.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(r[0].dims.length!==4||r[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(r[0].dims[1]!==r[1].dims[0])throw new 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y=m[0].dims,w=m[1].dims,v=(0,n.calculateOutputShape)(y,w,_.dilations,_.pads,_.strides),S=g.reshapeUnpacked(m[0],[y[1],y[2]*y[3]]),A=g.reshapeUnpacked(m[1],[w[0],w[1]]),O=m.length>2?[A,S,m[2]]:[A,S],x=g.run((0,s.createMatmulProgramInfoLoader)(O,_),O);return g.reshapeUnpacked(x,v)},r=(g,m,_)=>{const y=m[0].dims,w=m[1].dims,v=(0,n.calculateOutputShape)(y,w,_.dilations,_.pads,_.strides),S=g.run((0,l.createIm2ColProgramInfoLoader)(g,m[0],m[1],v,_),[m[0]]),A=m.length===3?[S,m[1],m[2]]:[S,m[1]];return g.run((0,h.createDotProductProgramInfoLoader)(g,m,v,_),A)},i=(g,m)=>{const _=g.kernelShape.slice();if(g.kernelShape.length===0)for(let v=2;v{const 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${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,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseDepthToSpaceAttributes=n.depthToSpace=void 0;const u=o(3738);n.depthToSpace=(p,a,h)=>{c(a);const f=h.blocksize,l=f*f,s=h.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],t=h.mode==="DCR"?[a[0].dims[0],f,f,a[0].dims[1]/l,a[0].dims[2],a[0].dims[3]]:[a[0].dims[0],a[0].dims[1]/l,f,f,a[0].dims[2],a[0].dims[3]],e=p.reshapeUnpacked(a[0],t),r={perm:s,cacheKey:`${s}`},[i]=(0,u.transpose)(p,[e],r),d=[a[0].dims[0],a[0].dims[1]/l,a[0].dims[2]*f,a[0].dims[3]*f];return[p.reshapeUnpacked(i,d)]},n.parseDepthToSpaceAttributes=p=>{const a=p.attributes.getInt("blocksize");if(a<1)throw new Error(`blocksize must be >= 1, 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_=d[0].dims,y=d[1].dims,w=[y[0],Math.ceil(_[1]*y[2]*y[3]/4)],v=(0,h.calculateIm2ColDims)(_,y,g),[S,A]=r.calculateTextureWidthAndHeight(w,p.TextureType.packedLastDimension),O=u.ShapeUtil.computeStrides(v),[x,I]=r.calculateTextureWidthAndHeight(v,p.TextureType.packedLastDimension),N=g.length,R=d.length<3?"0.0":"_B(b)",L=Math.ceil(_[1]*y[2]*y[3]/4),{activationFunction:F,applyActivation:V}=(0,a.getActivationSnippet)(m),D=(0,c.getGlsl)(r.session.backend.glContext.version),j=` ${F} float process(int indices[${N}]) { 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] * ${O[0]} + im2col[1] * ${O[1]} + im2col[2] * ${O[2]}; int kernelOffset = indices[1] * ${w[1]}; float value = ${R}; for (int i = 0; i < ${L}; ++i) { vec2 im2colCoords = offsetToCoords(im2colOffset, ${x}, ${I}); vec2 kernelCoords = offsetToCoords(kernelOffset, ${S}, ${A}); value += dot(${D.texture2D}(Im2Col, im2colCoords), ${D.texture2D}(K, kernelCoords)); ++im2colOffset; ++kernelOffset; } ${V} return value; }`;return Object.assign(Object.assign({},i),{output:{dims:g,type:d[0].type,textureType:p.TextureType.unpacked},shaderSource:j})})(f,e,l,s,t)})}},7992:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseFlattenAttributes=n.flatten=void 0;const u=o(2517);n.flatten=(p,a,h)=>{c(a,h);const f=u.ShapeUtil.flattenShape(a[0].dims,h);return[p.reshapeUnpacked(a[0],f)]},n.parseFlattenAttributes=p=>p.attributes.getInt("axis",1);const c=(p,a)=>{if(!p||p.length!==1)throw new Error("Flatten requires 1 input.");const h=p[0].dims.length;if(h===0)throw new Error("scalar tensor is not supported.");if(a<-h||a>h)throw new Error("Invalid axis");if(p[0].type==="string")throw new Error("string tensor is not supported.")}},2823:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInternalActivationAttributes=n.getActivationSnippet=void 0;const u=o(2517),c=o(4909);n.getActivationSnippet=function(p){let a;switch(p.activation){case"Relu":a=(0,c.glslRelu)();break;case"Sigmoid":a=(0,c.glslSigmoid)();break;case"Clip":a=(0,c.glslClip)(p.clipMin,p.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const h=a.name;return{activationFunction:a.body,applyActivation:`value = ${h}_(value);`}},n.parseInternalActivationAttributes=p=>{const a=p.getString("activation","");if(a==="Clip"){const[h,f]=p.getFloats("activation_params",[u.MIN_CLIP,u.MAX_CLIP]);return{activation:a,clipMax:f,clipMin:h,activationCacheKey:`${a}:${h},${f}`}}return{activation:a,activationCacheKey:a}}},1253:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGatherAttributes=n.gather=void 0;const u=o(246),c=o(782),p=o(2517),a=o(2039);n.gather=(s,t,e)=>(l(t,e.axis),[s.run(f(s,t,e),t)]),n.parseGatherAttributes=s=>(0,u.createAttributeWithCacheKey)({axis:s.attributes.getInt("axis",0)});const h={name:"Gather",inputNames:["A","B"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked]},f=(s,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(),w=new Array(_.length+y.length-1);m=p.ShapeUtil.normalizeAxis(m,_.length);const v=[];for(let A=0;A{if(!s||s.length!==2)throw new Error("Gather requires 2 inputs.");const e=s[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(s[0].type)===-1)throw new Error("Invaid input type.");if(s[1].type!=="int32"&&s[1].type!=="int16")throw new Error("Invaid input type.")}},4776:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGemmAttributesV11=n.parseGemmAttributesV7=n.gemm=void 0;const u=o(246),c=o(2517),p=o(2039);n.gemm=(s,t,e)=>(l(t,e),[s.run(h(t,e),t)]);const a=(s,t)=>{const e=s.attributes.getInt("transA",0)!==0,r=s.attributes.getInt("transB",0)!==0,i=s.attributes.getFloat("alpha",1),d=s.attributes.getFloat("beta",1);return(0,u.createAttributeWithCacheKey)({transA:e,transB:r,alpha:i,beta:d,isOptionalC:t})};n.parseGemmAttributesV7=s=>a(s,!1),n.parseGemmAttributesV11=s=>a(s,!0);const h=(s,t)=>{const e={name:"Gemm",inputNames:s.length===3?["A","B","C"]:["A","B"],inputTypes:s.length===3?[p.TextureType.unpacked,p.TextureType.unpacked,p.TextureType.unpacked]:[p.TextureType.unpacked,p.TextureType.unpacked],key:t.cacheKey};return Object.assign(Object.assign({},e),{get:()=>f(e,s,t)})},f=(s,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 w=m.length,v=` float process(int indices[${w}]) { int a[${w}]; int b[${w}]; ${t.length===3?`int c[${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[${w-1}] = k; b[${w-2}] = k; ${y} } value = value * alpha; ${t.length===3?"value += beta * _C(c);":""} return value; }`;return Object.assign(Object.assign({},s),{output:{dims:m,type:t[0].type,textureType:p.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:e.alpha},{name:"beta",type:"float",data:e.beta}],shaderSource:v})},l=(s,t)=>{if(!s)throw new Error("Input is missing");if(t.isOptionalC&&(s.length<2||s.length>3))throw new Error("Invaid input shape.");if(!t.isOptionalC&&s.length!==3)throw new Error("Gemm requires 3 inputs");if(s.length===3&&s[2].dims.length!==1&&s[2].dims.length!==2)throw new Error("Invalid input shape of C");if(s[0].type!=="float32"&&s[0].type!=="float64"||s[1].type!=="float32"&&s[1].type!=="float64"||s.length===3&&s[2].type!=="float32"&&s[2].type!=="float64")throw new Error("Invalid input type.");if(s[0].type!==s[1].type||s.length===3&&s[0].type!==s[2].type)throw new Error("Input types are mismatched")}},8555:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedIm2ColProgramInfoLoader=void 0;const u=o(5060),c=o(2039),p=o(2827);n.createPackedIm2ColProgramInfoLoader=(a,h,f,l,s)=>{const t=(e=s.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,w=g.dims,v=m.length,S=[w[1]*w[2]*w[3],m[2]*m[3]],A=w[2]*w[3],O=(0,p.unpackFromChannel)(),x=(0,u.getGlsl)(r.session.backend.glContext.version);let I="";for(let R=0;R<=1;R++)for(let L=0;L<=1;L++)I+=` blockIndex = rc.x + ${L}; pos = rc.y + ${R}; if(blockIndex < ${S[1]} && pos < ${S[0]}) { offsetY = int(blockIndex / (${m[v-1]})) * ${_.strides[0]} - ${_.pads[0]}; d0 = offsetY + ${_.dilations[0]} * (imod(pos, ${A}) / ${w[2]}); if(d0 < ${y[2]} && d0 >= 0) { offsetX = imod(blockIndex, ${m[v-1]}) * ${_.strides[1]} - ${_.pads[1]}; d1 = offsetX + ${_.dilations[1]} * imod(imod(pos, ${A}), ${w[2]}); if(d1 < ${y[3]} && d1 >= 0) { ch = int(float(pos)/ ${A}.); innerDims = vec2(d0, d1); result[${2*R+L}] = getChannel( getA(0, ch, int(innerDims.x), int(innerDims.y)), innerDims); } } } `;const N=` ${O} void main() { ivec2 rc = getOutputCoords(); vec4 result = vec4(0.0); int blockIndex, pos, offsetY, d0, offsetX, d1, ch; vec2 innerDims; ${I} ${x.output} = result; } `;return Object.assign(Object.assign({},i),{output:{dims:S,type:d.type,textureType:c.TextureType.packed},shaderSource:N,hasMain:!0})})(a,t,h,f,l,s)})}},3248:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.calculateIm2ColDims=n.createIm2ColProgramInfoLoader=void 0;const u=o(2039);n.createIm2ColProgramInfoLoader=(c,p,a,h,f)=>{const l=(s=f.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[u.TextureType.unpacked],cacheHint:s});var s;return Object.assign(Object.assign({},l),{get:()=>((t,e,r,i,d,g)=>{const m=r.dims,_=i.dims,y=d.length,w=(0,n.calculateIm2ColDims)(m,_,d,4),v=` 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:w,type:r.type,textureType:u.TextureType.packedLastDimension},shaderSource:v})})(0,l,p,a,h,f)})},n.calculateIm2ColDims=(c,p,a,h=4)=>[a[0],a[2],a[3],Math.ceil(c[1]*p[2]*p[3]/h)]},6572:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseImageScalerAttributes=n.imageScaler=void 0;const u=o(246),c=o(2039);n.imageScaler=(l,s,t)=>(f(s),[l.run(a(l,s,t),s)]),n.parseImageScalerAttributes=l=>{const s=l.attributes.getFloat("scale"),t=l.attributes.getFloats("bias");return(0,u.createAttributeWithCacheKey)({scale:s,bias:t})};const p={name:"ImageScaler",inputNames:["X"],inputTypes:[c.TextureType.unpacked]},a=(l,s,t)=>{const e=Object.assign(Object.assign({},p),{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,s,t)})},h=l=>{const s=[`float getBias(float bias[${l}], int channel) {`];for(let t=0;t{if(!l||l.length!==1)throw new Error("ImageScaler requires 1 input.");if(l[0].dims.length!==4)throw new Error("Invalid input shape.");if(l[0].type!=="float32"&&l[0].type!=="float64")throw new Error("Invalid input type.")}},3346:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInstanceNormalizationAttributes=n.instanceNormalization=void 0;const u=o(5060),c=o(2039);n.instanceNormalization=(s,t,e)=>{l(t);const r=s.run(a(t[0]),t);return[s.run(f(s,t[0],e,r.dims),[t[0],r,t[1],t[2]])]},n.parseInstanceNormalizationAttributes=s=>s.attributes.getFloat("epsilon",1e-5);const p={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[c.TextureType.unpacked]},a=s=>Object.assign(Object.assign({},p),{get:()=>((t,e)=>{const r=e.dims.slice(),i=r[1],d=r[2]*r[3],g=[r[0],i],m=` vec4 process(int[2] indices) { vec4 v = vec4(0.0); int a[4]; a[0] = indices[0]; a[1] = indices[1]; float temp = 0.0; for(int a2=0; a2<${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(${d}); return v; }`;return Object.assign(Object.assign({},t),{output:{dims:g,type:e.type,textureType:c.TextureType.packedLastDimension},shaderSource:m})})(p,s)}),h={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[c.TextureType.unpacked,c.TextureType.packedLastDimension,c.TextureType.unpacked,c.TextureType.unpacked]},f=(s,t,e,r)=>{const i=Object.assign(Object.assign({},h),{cacheHint:`${e}`});return Object.assign(Object.assign({},i),{get:()=>((d,g,m,_,y)=>{const w=(0,u.getGlsl)(d.session.backend.glContext.version),[v,S]=d.calculateTextureWidthAndHeight(y,c.TextureType.packedLastDimension),[A,O]=[v/4,S],x=` vec4 get_MeanAndVariance(int[2] mv) { int offset = indicesToOffset_MeanAndVariance(mv); vec2 coords = offsetToCoords(offset, ${A}, ${O}); return ${w.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:x})})(s,i,t,e,r)})},l=s=>{if(!s||s.length!==3)throw new Error("InstanceNormalization requires 3 inputs.");const t=s[0],e=s[1],r=s[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(s[0].dims.length!==4)throw new Error("Only support 4-D input shape.")}},708:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedMatmulProgramInfoLoader=void 0;const u=o(2517),c=o(5060),p=o(2039),a=o(9390),h=o(2823),f=o(5623);n.createPackedMatmulProgramInfoLoader=(l,s,t)=>{const e=(r=s.length>2,i=t.activationCacheKey,{name:"MatMul (packed)",inputNames:r?["A","B","Bias"]:["A","B"],inputTypes:r?[p.TextureType.packed,p.TextureType.packed,p.TextureType.packed]:[p.TextureType.packed,p.TextureType.packed],cacheHint:i});var r,i;return Object.assign(Object.assign({},e),{get:()=>((d,g,m,_)=>{const y=m.length>2,w=y?"value += getBiasForMatmul();":"",v=m[0].dims,S=m[1].dims,A=u.BroadcastUtil.calcShape(v,S,!0),O=!u.ShapeUtil.areEqual(m[0].dims,m[1].dims);if(!A)throw new Error("Can't use matmul on the given tensors");const 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value = 0.0;","t = _A(inputIdx); value += t * t;",""])},7019:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.isReshapeCheap=n.processDims3D=n.createPackedReshape3DProgramInfoLoader=void 0;const u=o(2517),c=o(5060),p=o(2039),a=o(2827);n.createPackedReshape3DProgramInfoLoader=(h,f,l)=>{const s=(t=>({name:"Reshape (packed)",inputTypes:[p.TextureType.packed],inputNames:["A"],cacheHint:`${t}`}))(l);return Object.assign(Object.assign({},s),{get:()=>((t,e,r,i)=>{const d=e.dims,g=i;let m="";for(let w=0;w<4;w++){let v="";switch(w){case 0:v="outputCoords = rc;";break;case 1:v="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:v="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:v="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}m+=` ${v} ${w>0?"if(outputCoords.y < rows && outputCoords.z < cols){":""} int flattenedIndex = getFlattenedIndex(outputCoords); ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex); vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z)); result[${w}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims); ${w>0?"}":""} `}const _=(0,c.getGlsl)(t.session.backend.glContext.version),y=` ${function(w){const v=u.ShapeUtil.computeStrides(w),S=["b","r","c"],A="index";return` ivec3 inputCoordsFromReshapedOutCoords(int index) { ${v.map((O,x)=>`int ${S[x]} = ${A} / ${O}; ${x===v.length-1?`int ${S[x+1]} = ${A} - ${S[x]} * ${O}`:`index -= ${S[x]} * ${O}`};`).join("")} return ivec3(b, r, c); } `}(d)} ${function(w){const v=u.ShapeUtil.computeStrides(w);return` int getFlattenedIndex(ivec3 coords) { // reverse y, z order return coords.x * ${v[0]} + coords.z * ${v[1]} + coords.y; } `}(g)} ${(0,a.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:p.TextureType.packed},shaderSource:y,hasMain:!0})})(h,f,s,l)})},n.processDims3D=function(h){if(h.length===0)return[1,1,1];let f=1;for(let l=0;l1?h[h.length-2]:1,h[h.length-1]]},n.isReshapeCheap=function(h,f){let l=!1;return l=h.length===0||f.length===0||(h.length<2||f.length<2?h[h.length-1]===f[f.length-1]:h[h.length-1]===f[f.length-1]&&h[h.length-2]===f[f.length-2]),l}},718:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.reshape=void 0;const u=o(2517);n.reshape=(c,p)=>{const a=u.ShapeUtil.calculateReshapedDims(p[0].dims,p[1].integerData);return c.session.pack?[c.reshapePacked(p[0],a)]:[c.reshapeUnpacked(p[0],a)]}},2268:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseResizeAttributesV11=n.parseResizeAttributesV10=n.resize=void 0;const u=o(5060),c=o(2039),p=o(9390),a=o(2827),h=o(9793),f={name:"Resize",inputNames:["A"],inputTypes:[c.TextureType.packed]};n.resize=(r,i,d)=>((0,h.validateInputs)(i,d),[r.run(Object.assign(Object.assign({},f),{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,_]=s(i,d);if(m.every(F=>F===1)&&d.coordinateTransformMode!=="tf_crop_and_resize")return Object.assign(Object.assign({},f),{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 w=_[y-2],v=_[y-1],S=i[0].dims;if(y!==S.length)throw new Error(`output dimension should match input ${S.length}, but got ${y}`);const A=S[y-2],O=S[y-1],x=m[y-2],I=m[y-1];let N="";if(d.mode!=="linear")throw new Error(`resize (packed) does not support mode: '${d.mode}'`);switch(d.coordinateTransformMode){case"asymmetric":N=` vec4 getSourceFracIndex(ivec4 coords) { return vec4(coords) / scaleWHWH; } `;break;case"half_pixel":N=` vec4 getSourceFracIndex(ivec4 coords) { return (vec4(coords) + 0.5) / scaleWHWH - 0.5; } `;break;case"pytorch_half_pixel":N=` vec4 getSourceFracIndex(ivec4 coords) { vec4 fcoords = vec4(coords); return vec4( ${v}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0, ${w}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0, ${v}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0, ${w}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0 ); } `;break;case"align_corners":N=` vec4 getSourceFracIndex(ivec4 coords) { vec4 resized = vec4(${v}.0 - 1.0, ${w}.0 - 1.0, ${v}.0 - 1.0, ${w}.0 - 1.0); vec4 original = vec4(${O}.0 - 1.0, ${A}.0 - 1.0, ${O}.0 - 1.0, ${A}.0 - 1.0); vec4 new_scale = original / resized; return vec4(coords) * new_scale; } `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode: '${d.coordinateTransformMode}'`)}const R=(0,p.getCoordsDataType)(y),L=` const vec2 inputWH = vec2(${A}.0, ${O}.0); const vec4 scaleWHWH = vec4(float(${x}), float(${I}), float(${x}), float(${I})); ${(0,a.unpackFromChannel)()} ${N} float getAValue(int x10, int r, int c, int d) { return getChannel(getA(x10, r, c, d), vec2(c, d)); } void main() { ${R} 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 < ${w-1}; bool hasNextCol = rc.z < ${v-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({},f),{output:{dims:_,type:i[0].type,textureType:c.TextureType.packed},hasMain:!0,shaderSource:L})},s=(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 w=r[i.sizesInputIdx];if(!w||w.size===0)throw new Error("Either scales or sizes MUST be provided as input.");g=Array.from(w.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,w)=>Math.floor(y*m[w]));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,w=m;y{Object.defineProperty(n,"__esModule",{value:!0}),n.shape=void 0;const u=o(9162);n.shape=(p,a)=>(c(a),[new u.Tensor([a[0].dims.length],"int32",void 0,void 0,new Int32Array(a[0].dims))]);const c=p=>{if(!p||p.length!==1)throw new Error("Shape requires 1 input.")}},2278:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.sliceV10=n.parseSliceAttributes=n.slice=void 0;const u=o(246),c=o(782),p=o(2517),a=o(2039),h={name:"Slice",inputNames:["A"],inputTypes:[a.TextureType.unpacked]};n.slice=(e,r,i)=>(l(r),[e.run(Object.assign(Object.assign({},h),{cacheHint:i.cacheKey,get:()=>f(e,r[0],i)}),r)]),n.parseSliceAttributes=e=>{const r=e.attributes.getInts("starts"),i=e.attributes.getInts("ends"),d=e.attributes.getInts("axes",[]);return(0,u.createAttributeWithCacheKey)({starts:r,ends:i,axes:d})};const f=(e,r,i)=>{const d=i.axes.length===0?r.dims.slice(0).map((S,A)=>A):i.axes,g=p.ShapeUtil.normalizeAxes(d,r.dims.length),m=i.starts.map((S,A)=>S>r.dims[g[A]]-1?r.dims[g[A]]:p.ShapeUtil.normalizeAxis(S,r.dims[g[A]])),_=i.ends.map((S,A)=>S>r.dims[g[A]]-1?r.dims[g[A]]:p.ShapeUtil.normalizeAxis(S,r.dims[g[A]])),y=r.dims.slice(),w=[];for(let S=0;S0&&w.push(`outputIdx[${g[S]}] += ${m[S]};`);const v=` float process(int outputIdx[${y.length}]) { ${w.join(` `)} return _A(outputIdx); }`;return Object.assign(Object.assign({},h),{output:{dims:y,type:r.type,textureType:a.TextureType.unpacked},shaderSource:v})},l=e=>{if(!e||e.length!==1)throw new Error("Slice requires 1 input.");if(c.NUMBER_TYPES.indexOf(e[0].type)===-1)throw new Error("Invalid input type.")};n.sliceV10=(e,r)=>{t(r);const i=s(e,r);return[e.run(Object.assign(Object.assign({},h),{cacheHint:i.cacheKey,get:()=>f(e,r[0],i)}),[r[0]])]};const s=(e,r)=>{if(!e.session.isInitializer(r[1].dataId)||!e.session.isInitializer(r[2].dataId)||r.length>=4&&!e.session.isInitializer(r[3].dataId)||r.length>=5&&!e.session.isInitializer(r[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(r.length>=5&&r[4].integerData.some(m=>m!==1))throw new Error("currently non-1 steps is not supported for Slice");const i=Array.from(r[1].integerData),d=Array.from(r[2].integerData),g=r.length>=4?Array.from(r[3].integerData):[];return{starts:i,ends:d,axes:g,cacheKey:`${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,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.softmaxV13=n.parseSoftmaxAttributesV13=n.parseSoftmaxAttributes=n.softmax=void 0;const u=o(246),c=o(2517),p=o(5060),a=o(2039),h=o(3738),f={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[a.TextureType.unpacked]},l={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked]},s={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked,a.TextureType.unpacked]};n.softmax=(g,m,_)=>{d(m);const y=m[0].dims.slice(),w=c.ShapeUtil.normalizeAxis(_.axis,y.length),v=c.ShapeUtil.sizeToDimension(y,w),S=c.ShapeUtil.sizeFromDimension(y,w);return t(g,m,_,v,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(),w=c.ShapeUtil.normalizeAxis(_.axis,y.length),v=y.length,S=w!==v-1,A=[];let O,x=[],I=[];S&&(x=Array.from({length:v}).map((F,V)=>V),x[w]=v-1,x[v-1]=w,x.map(F=>A.push(y[F])),O=(0,u.createAttributeWithCacheKey)({perm:x}),I=(0,h.transpose)(g,m,O));const N=S?c.ShapeUtil.sizeToDimension(A,v-1):c.ShapeUtil.sizeToDimension(y,v-1),R=S?c.ShapeUtil.sizeFromDimension(A,v-1):c.ShapeUtil.sizeFromDimension(y,v-1),L=t(g,S?I:m,_,N,R);return S?(0,h.transpose)(g,L,O):L};const t=(g,m,_,y,w)=>{const v=e(g,m[0],y,w,[y]),S=g.run(Object.assign(Object.assign({},f),{cacheHint:_.cacheKey,get:()=>v}),m),A=r(g,m[0],y,w,v.output.dims,[y]),O=g.run(Object.assign(Object.assign({},l),{cacheHint:_.cacheKey,get:()=>A}),[m[0],S]),x=i(g,m[0],y,w,v.output.dims,A.output.dims);return[g.run(Object.assign(Object.assign({},s),{cacheHint:_.cacheKey,get:()=>x}),[m[0],S,O])]},e=(g,m,_,y,w)=>{const[v,S]=g.calculateTextureWidthAndHeight(m.dims,a.TextureType.unpacked),A=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");const O=(0,p.getGlsl)(g.session.backend.glContext.version),x=` float process(int[${A}] indices) { int logical_row_start_offset = indices[0] * ${y}; float max = getColorAsFloat(${O.texture2D}(A, offsetToCoords(logical_row_start_offset, ${v}, ${S} ))); for(int i=1; i<${y}; ++i) { float current = getColorAsFloat(${O.texture2D}(A, offsetToCoords(logical_row_start_offset + i, ${v}, ${S}))); if(current > max) max = current; } return max; }`;return Object.assign(Object.assign({},f),{output:{dims:w,type:m.type,textureType:a.TextureType.unpacked},shaderSource:x})},r=(g,m,_,y,w,v)=>{const[S,A]=g.calculateTextureWidthAndHeight(m.dims,a.TextureType.unpacked),O=v.length;if(_<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(v.length!==1)throw new Error("Dimensionality of the output should be 1");if(v[0]!==_)throw new Error("Shape of the output should be equal to logical row count");if(w.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(w[0]!==_)throw new Error("Shape of the intermediate results should be equal to logical row count");const x=` float process(int[${O}] 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,p.getGlsl)(g.session.backend.glContext.version).texture2D}(A, offsetToCoords(logical_row_start_offset + i, ${S}, ${A}))) - max); } return norm_factor; }`;return Object.assign(Object.assign({},l),{output:{dims:v,type:m.type,textureType:a.TextureType.unpacked},shaderSource:x})},i=(g,m,_,y,w,v)=>{const[S,A]=g.calculateTextureWidthAndHeight(m.dims,a.TextureType.unpacked),O=m.dims.length;if(_<1||y<1)throw new Error("Logical 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l>10?f.inputs.length>2?(v=1,S=2,A=3):(S=1,A=2):l===9&&(S=1),(0,u.createAttributeWithCacheKey)({opset:l,isResize:s,mode:t,scales:e,extrapolationValue:r,coordinateTransformMode:i,useExtrapolation:g,needRoiInput:d,nearestMode:m,cubicCoefficientA:_,excludeOutside:y,useNearest2xOptimization:w,roiInputIdx:v,scalesInputIdx:S,sizesInputIdx:A})};const h=(f,l,s)=>{const t=(0,c.getGlsl)(f.session.backend.glContext.version),[e,r]=f.calculateTextureWidthAndHeight(l[0].dims,p.TextureType.unpacked),i=l[0].dims.map((A,O)=>Math.floor(A*s.scales[O])),[d,g]=f.calculateTextureWidthAndHeight(i,p.TextureType.unpacked),m=i.length,_=new Array(m),y=new Array(m);let w=` int output_pitches[${m}]; int input_pitches[${m}]; `;for(let A=m-1;A>=0;A--)_[A]=A===m-1?1:_[A+1]*i[A+1],y[A]=A===m-1?1:y[A+1]*l[0].dims[A+1],w+=` output_pitches[${A}] = ${_[A]}; input_pitches[${A}] = ${y[A]}; `;const v=` float getInputFloat(int index) { vec2 coords = offsetToCoords(index, ${e}, ${r}); float value = 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output_pitches[2]; index_of_dim3 = m; int index_of_input_dim2, index_of_input_dim3, x_offset, y_offset; index_of_input_dim2 = index_of_dim2 / scales[2]; y_offset = index_of_dim2 - index_of_input_dim2 * scales[2]; index_of_input_dim3 = index_of_dim3 / scales[3]; x_offset = index_of_dim3 - index_of_input_dim3 * scales[3]; input_index = index_of_dim0 * input_pitches[0] + index_of_dim1 * input_pitches[1] + index_of_input_dim2 * input_pitches[2] + index_of_input_dim3; float x00 = getInputFloat(input_index); float x10, x01, x11; bool end_of_dim2 = false; if (index_of_input_dim2 == (${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]); }`:` ${v} float process(int indices[2]) { int input_index = 0; int output_index = coordsToOffset(TexCoords, ${d}, ${g}); ${w} int m; int index_of_dim0, index_of_dim1; index_of_dim0 = output_index / output_pitches[0]; m = output_index - index_of_dim0 * output_pitches[0]; index_of_dim1 = m; int index_of_input_dim0, index_of_input_dim1, x_offset, y_offset; index_of_input_dim0 = index_of_dim0 / scales[0]; y_offset = index_of_dim0 - index_of_input_dim0 * scales[0]; index_of_input_dim1 = index_of_dim1 / scales[1]; x_offset = index_of_dim1 - index_of_input_dim1 * scales[1]; input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1; float x00 = getInputFloat(input_index); float x10, x01, x11; bool end_of_dim0 = false; if (index_of_input_dim0 == (${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({},a),{output:{dims:i,type:l[0].type,textureType:p.TextureType.unpacked},shaderSource:S,variables:[{name:"scales",type:"int",arrayLength:s.scales.length,data:s.scales.map(A=>Math.ceil(A))}]})};n.validateInputs=(f,l)=>{if(!f||l.opset<9&&f.length!==1||l.opset>=9&&l.opset<11&&f.length!==2||l.opset>=11&&f.length<2)throw new Error("invalid inputs.");if(l.scales.length>0&&f[0].dims.length!==l.scales.length)throw new Error("Invalid input shape.");if(f[0].type==="string")throw new Error("Invalid input tensor types.")},n.scalesValidation=(f,l,s)=>{if(s){for(const t of f)if(t<=0)throw new Error("Scale value should be greater than 0.")}else for(const t of f)if(t<1)throw new Error("Scale value should be greater than or equal to 1.");if(!(l!=="linear"&&l!=="cubic"||f.length===2||f.length===4&&f[0]===1&&f[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 being 1 in the ${s?"Resize":"Upsample"} opeartor.`)}},1958:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.ProgramManager=void 0;const u=o(1670),c=o(6231),p=o(8879),a=o(5060);n.ProgramManager=class{constructor(h,f,l){this.profiler=h,this.glContext=f,this.textureLayoutStrategy=l,this.repo=new Map,this.attributesBound=!1}getArtifact(h){return this.repo.get(h)}setArtifact(h,f){this.repo.set(h,f)}run(h,f,l){var s;this.profiler.event("op",`ProgramManager.run ${(s=h.programInfo.name)!==null&&s!==void 0?s:"unknown kernel"}`,()=>{var t;const e=this.glContext.gl,r=h.program;e.useProgram(r);try{this.bindOutput(l),this.attributesBound||this.bindAttributes(h.attribLocations),this.bindUniforms(h.uniformLocations,(t=h.programInfo.variables)!==null&&t!==void 0?t:[],f)}catch(i){throw c.Logger.error("ProgramManager",h.programInfo.shaderSource),i}this.profiler.event("backend","GlContext.draw()",()=>{this.glContext.draw()})},this.glContext)}dispose(){this.vertexShader&&this.glContext.deleteShader(this.vertexShader),this.repo.forEach(h=>this.glContext.deleteProgram(h.program))}build(h,f,l){return this.profiler.event("backend","ProgramManager.build",()=>{const s=new 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type=${h.tensor.type}`),this.glContext.attachFramebuffer(h.texture,f,l)}bindAttributes(h){const f=h.position,l=h.textureCoord;this.glContext.setVertexAttributes(f,l),this.attributesBound=!0}bindUniforms(h,f,l){var s;const t=this.glContext.gl;let e=0;for(const{name:r,type:i,location:d,arrayLength:g}of h){const m=(s=f.find(_=>_.name===r))===null||s===void 0?void 0:s.data;if(i!=="sampler2D"&&!m)throw new Error(`variable '${r}' does not have data defined in program info`);switch(i){case"sampler2D":this.bindTexture(l[e],d,e),e++;break;case"float":g?t.uniform1fv(d,m):t.uniform1f(d,m);break;case"int":g?t.uniform1iv(d,m):t.uniform1i(d,m);break;default:throw new Error(`Uniform not implemented: ${i}`)}}}bindTexture(h,f,l){this.glContext.bindTextureToUniform(h.texture,l,f)}getAttribLocations(h){return{position:this.getAttribLocation(h,"position"),textureCoord:this.getAttribLocation(h,"textureCoord")}}getUniformLocations(h,f,l){const s=[];if(f)for(const t of f)s.push({name:t,type:"sampler2D",location:this.getUniformLocation(h,t)});if(l)for(const t of l)s.push(Object.assign(Object.assign({},t),{location:this.getUniformLocation(h,t.name)}));return s}getUniformLocation(h,f){const l=this.glContext.gl.getUniformLocation(h,f);if(l===null)throw new Error(`Uniform ${f} not found.`);return l}getAttribLocation(h,f){return this.glContext.gl.getAttribLocation(h,f)}}},6416:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.WebGLSessionHandler=void 0;const u=o(6231),c=o(1047),p=o(8316),a=o(1640),h=o(1958),f=o(7859),l=o(5702);n.WebGLSessionHandler=class{constructor(s,t){this.backend=s,this.context=t,this.layoutStrategy=new f.PreferLogicalStrategy(s.glContext.maxTextureSize),this.programManager=new h.ProgramManager(this.context.profiler,s.glContext,this.layoutStrategy),this.textureManager=new l.TextureManager(s.glContext,this.layoutStrategy,this.context.profiler,{reuseTextures:s.textureCacheMode==="full"}),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new Map,this.pack=s.pack,this.pack2unpackMap=new Map,this.unpack2packMap=new Map}createInferenceHandler(){return new p.WebGLInferenceHandler(this)}onGraphInitialized(s){const t=s.getValues().filter(e=>e.from===-1&&e.tensor).map(e=>e.tensor.dataId);this.initializers=new Set(t)}isInitializer(s){return!!this.initializers&&this.initializers.has(s)}addInitializer(s){this.initializers.add(s)}getTextureData(s,t){return t?this.packedTextureDataCache.get(s):this.unpackedTextureDataCache.get(s)}setTextureData(s,t,e=!1){u.Logger.verbose("WebGLSessionHandler","Storing Texture data in cache"),e?this.packedTextureDataCache.set(s,t):this.unpackedTextureDataCache.set(s,t)}dispose(){this.programManager.dispose(),this.textureManager.clearActiveTextures(),this.packedTextureDataCache.forEach(s=>this.textureManager.releaseTexture(s,!0)),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache.forEach(s=>this.textureManager.releaseTexture(s,!0)),this.unpackedTextureDataCache=new Map}resolve(s,t,e){const r=(0,c.resolveOperator)(s,t,a.WEBGL_OP_RESOLVE_RULES);return{impl:r.opImpl,context:r.opInit?r.opInit(s,e):s}}}},7769:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Uint8DataEncoder=n.RGBAFloatDataEncoder=n.RedFloat32DataEncoder=void 0;const u=o(6231);n.RedFloat32DataEncoder=class{constructor(c,p=1){if(p===1)this.internalFormat=c.R32F,this.format=c.RED,this.textureType=c.FLOAT,this.channelSize=p;else{if(p!==4)throw new Error(`Invalid number of channels: ${p}`);this.internalFormat=c.RGBA32F,this.format=c.RGBA,this.textureType=c.FLOAT,this.channelSize=p}}encode(c,p){let a,h;return c.constructor!==Float32Array&&(u.Logger.warning("Encoder","data was not of type Float32; creating new Float32Array"),h=new Float32Array(c)),p*this.channelSize>c.length?(u.Logger.warning("Encoder","Source data too small. Allocating larger array"),h=c,a=this.allocate(p*this.channelSize),h.forEach((f,l)=>a[l]=f)):(h=c,a=h),a}allocate(c){return new Float32Array(4*c)}decode(c,p){return this.channelSize===1?c.filter((a,h)=>h%4==0).subarray(0,p):c.subarray(0,p)}},n.RGBAFloatDataEncoder=class{constructor(c,p=1,a){if(p!==1&&p!==4)throw new Error(`Invalid number of channels: ${p}`);this.internalFormat=c.RGBA,this.format=c.RGBA,this.channelSize=p,this.textureType=a||c.FLOAT}encode(c,p){let a=c;return this.channelSize===1&&(u.Logger.verbose("Encoder","Exploding into a larger array"),a=this.allocate(p),c.forEach((h,f)=>a[4*f]=h)),a}allocate(c){return new Float32Array(4*c)}decode(c,p){return this.channelSize===1?c.filter((a,h)=>h%4==0).subarray(0,p):c.subarray(0,p)}},n.Uint8DataEncoder=class{constructor(c,p=1){if(this.channelSize=4,p===1)this.internalFormat=c.ALPHA,this.format=c.ALPHA,this.textureType=c.UNSIGNED_BYTE,this.channelSize=p;else{if(p!==4)throw new Error(`Invalid number of channels: ${p}`);this.internalFormat=c.RGBA,this.format=c.RGBA,this.textureType=c.UNSIGNED_BYTE,this.channelSize=p}}encode(c,p){return new Uint8Array(c.buffer,c.byteOffset,c.byteLength)}allocate(c){return new Uint8Array(c*this.channelSize)}decode(c,p){if(c instanceof Uint8Array)return c.subarray(0,p);throw new Error(`Invalid array type: ${c.constructor}`)}}},7859:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.getBatchDim=n.sizeToSquarishShape=n.getRowsCols=n.sizeFromShape=n.isInt=n.parseAxisParam=n.squeezeShape=n.PreferLogicalStrategy=n.AlwaysKeepOriginalSizeStrategy=void 0;const u=o(6231),c=o(2517);function p(s,t){const e=[],r=[],i=t!=null&&Array.isArray(t)&&t.length===0,d=t==null||i?null:a(t,s).sort();let g=0;for(let m=0;mm)&&s[m]===1&&(e.push(s[m]),r.push(m)),d[g]<=m&&g++}s[m]!==1&&(e.push(s[m]),r.push(m))}return{newShape:e,keptDims:r}}function a(s,t){const e=t.length;return s=s==null?t.map((r,i)=>i):[].concat(s),(0,c.assert)(s.every(r=>r>=-e&&r`All values in axis param must be 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r=this.maxTextureSize;if(t&&t.breakAxis!==void 0){const g=t.breakAxis>=s.length?1:s.slice(t.breakAxis).reduce((_,y)=>_*y),m=t.breakAxis<=0?1:s.slice(0,t.breakAxis).reduce((_,y)=>_*y);if(!(g>r||m>r))return[g,m];u.Logger.verbose("TextureLayout",`Given width/height preferences were unattainable: shape:${s}, breakAxis:${t.breakAxis}`)}let i=s.slice(0);e&&(r*=2,i=i.map((g,m)=>m>=i.length-2?i[m]%2==0?i[m]:i[m]+1:i[m]),i.length===1&&(i=[2,i[0]])),i.length!==2&&(i=p(i).newShape);const d=f(i);return i.length<=1&&d<=r?[1,d]:i.length===2&&i[0]<=r&&i[1]<=r?i:i.length===3&&i[0]*i[1]<=r&&i[2]<=r?[i[0]*i[1],i[2]]:i.length===3&&i[0]<=r&&i[1]*i[2]<=r?[i[0],i[1]*i[2]]:i.length===4&&i[0]*i[1]*i[2]<=r&&i[3]<=r?[i[0]*i[1]*i[2],i[3]]:i.length===4&&i[0]<=r&&i[1]*i[2]*i[3]<=r?[i[0],i[1]*i[2]*i[3]]:e?l(d/4).map(g=>2*g):l(d)}},n.squeezeShape=p,n.parseAxisParam=a,n.isInt=h,n.sizeFromShape=f,n.getRowsCols=function(s){if(s.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[s.length>1?s[s.length-2]:1,s[s.length-1]]},n.sizeToSquarishShape=l,n.getBatchDim=function(s,t=2){return f(s.slice(0,s.length-t))}},4057:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createTextureLayoutFromShape=n.calculateTextureWidthAndHeight=n.createTextureLayoutFromTextureType=void 0;const u=o(2517),c=o(2039);n.createTextureLayoutFromTextureType=(p,a,h)=>{const f=h===c.TextureType.unpacked||h===c.TextureType.unpackedReversed?1:4,l=h===c.TextureType.packed,s=h===c.TextureType.unpackedReversed||h===c.TextureType.packed,t=h===c.TextureType.packedLastDimension?a.length-1:void 0,e=h===c.TextureType.packedLastDimension?a.map((r,i)=>i===a.length-1?4*r:r):void 0;return(0,n.createTextureLayoutFromShape)(p,a,f,e,{isPacked:l,reverseWH:s,breakAxis:t})},n.calculateTextureWidthAndHeight=(p,a,h)=>{const f=(0,n.createTextureLayoutFromTextureType)(p,a,h);return[f.width,f.height]},n.createTextureLayoutFromShape=(p,a,h=1,f,l)=>{const s=!(!l||!l.isPacked),[t,e]=p.computeTextureWH(s&&f||a,l),r=a.length;let i=a.slice(0);if(r===0&&(i=[1]),h===1)f=a;else if(s){if(h!==4)throw new Error("a packed texture must be 4-channel");f=a,r>0&&(i[r-1]=Math.ceil(i[r-1]/2)),r>1&&(i[r-2]=Math.ceil(i[r-2]/2))}else if(!f)throw new Error("Unpacked shape is needed when using channels > 1");return{width:t,height:e,channels:h,isPacked:s,shape:i,strides:u.ShapeUtil.computeStrides(i),unpackedShape:f,reversedWH:l&&l.reverseWH}}},5702:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.TextureManager=void 0;const u=o(6231);n.TextureManager=class{constructor(c,p,a,h){this.glContext=c,this.layoutStrategy=p,this.profiler=a,this.config=h,this.pendingRead=new Map,h.reuseTextures&&(this.inUseTextures=new Map,this.idleTextures=new Map,this.textureLookup=new Map)}createTextureFromLayout(c,p,a,h){const f=this.toEncoderType(c),l=this.glContext.getEncoder(f,p.channels||1,h);if(p.isPacked&&h===1)throw new Error("not implemented");const s=p.width,t=p.height;let e,r;if(this.config.reuseTextures){e=`${s}x${t}_${l.format}_${l.internalFormat}_${l.textureType}`,r=this.inUseTextures.get(e),r||(r=[],this.inUseTextures.set(e,r));const d=this.idleTextures.get(e);if(d&&d.length>0){const g=d.pop();return r.push(g),h===1&&this.glContext.updateTexture(g,s,t,l,this.toTextureData(c,a)),g}}u.Logger.verbose("TextureManager",`Creating new texture of size ${p.width}x${p.height}`);const i=this.glContext.allocateTexture(s,t,l,this.toTextureData(c,a));return this.config.reuseTextures&&(r.push(i),this.textureLookup.set(i,e)),i}readTexture(c,p,a){return a||(a=1),this.profiler.event("backend","TextureManager.readTexture",()=>{const h=c.shape.reduce((l,s)=>l*s)*a,f=this.glContext.readTexture(c.texture,c.width,c.height,h,this.toEncoderType(p),a);return this.toTensorData(p,f)})}async readTextureAsync(c,p,a){const h=c.tensor.dataId;if(a||(a=1),this.pendingRead.has(h)){const f=this.pendingRead.get(h);return new Promise(l=>f==null?void 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l.startShape(t),l.addDim(t,e),l.endShape(t)}}f.Shape=l})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(f){class l{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsDimension(t,e){return(e||new l).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsDimension(t,e){return t.setPosition(t.position()+u.flatbuffers.SIZE_PREFIX_LENGTH),(e||new l).__init(t.readInt32(t.position())+t.position(),t)}value(t){let e=this.bb.__offset(this.bb_pos,4);return e?(t||new a.experimental.fbs.DimensionValue).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}denotation(t){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.__string(this.bb_pos+e,t):null}static startDimension(t){t.startObject(2)}static addValue(t,e){t.addFieldOffset(0,e,0)}static addDenotation(t,e){t.addFieldOffset(1,e,0)}static endDimension(t){return t.endObject()}static 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startDimensionValue(t){t.startObject(3)}static addDimType(t,e){t.addFieldInt8(0,e,a.experimental.fbs.DimensionValueType.UNKNOWN)}static addDimValue(t,e){t.addFieldInt64(1,e,t.createLong(0,0))}static addDimParam(t,e){t.addFieldOffset(2,e,0)}static endDimensionValue(t){return t.endObject()}static createDimensionValue(t,e,r,i){return l.startDimensionValue(t),l.addDimType(t,e),l.addDimValue(t,r),l.addDimParam(t,i),l.endDimensionValue(t)}}f.DimensionValue=l})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(f){class l{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsTensorTypeAndShape(t,e){return(e||new l).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsTensorTypeAndShape(t,e){return t.setPosition(t.position()+u.flatbuffers.SIZE_PREFIX_LENGTH),(e||new l).__init(t.readInt32(t.position())+t.position(),t)}elemType(){let 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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)}}f.Graph=l})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(f){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 a.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 a.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,w){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,w),l.endModel(t)}}f.Model=l})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(f){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)}}f.KernelCreateInfos=l})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(f){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 a.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)}}f.SubGraphSessionState=l})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(f){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 a.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 a.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)}}f.SessionState=l})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(f){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 a.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 a.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)}}f.InferenceSession=l})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={}))},7448:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.OnnxjsSessionHandler=void 0;const u=o(1670),c=o(9162);n.OnnxjsSessionHandler=class{constructor(p){this.session=p,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(p,a,h){const f=new Map;for(const t in p)if(Object.hasOwnProperty.call(p,t)){const e=p[t];f.set(t,new c.Tensor(e.dims,e.type,void 0,void 0,e.data))}const l=await this.session.run(f),s={};return l.forEach((t,e)=>{s[e]=new u.Tensor(t.type,t.data,t.dims)}),s}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(b,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Session=void 0;const u=o(7067),c=o(1296),p=o(7091),a=o(1036),h=o(6231),f=o(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,s,t){await this.profiler.event("session","Session.loadModel",async()=>{const e=await(0,p.resolveBackend)(this.backendHint);if(this.sessionHandler=e.createSessionHandler(this.context),this._model=new f.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,s||0,t||l.byteLength);this.initialize(r)}})}initialize(l,s){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,s),this.sessionHandler.onGraphInitialized&&this.sessionHandler.onGraphInitialized(this._model.graph),this.initializeOps(this._model.graph),this._executionPlan=new a.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 s=this.normalizeAndValidateInputs(l),t=await this._executionPlan.execute(this.sessionHandler,s);return this.createOutput(t)})}normalizeAndValidateInputs(l){const s=this._model.graph.getInputNames();if(Array.isArray(l)){if(l.length!==s.length)throw new Error(`incorrect input array length: expected ${s.length} but got ${l.length}`)}else{if(l.size!==s.length)throw new Error(`incorrect input map size: expected ${s.length} but got ${l.size}`);const t=new Array(l.size);let e=0;for(let r=0;rtypeof O=="string")))throw new TypeError("cache should be a string array");A&&(this.cache=new Array(S))}else{if(w!==void 0){const O=e(m);if(!(w instanceof O))throw new TypeError(`cache should be type ${O.name}`)}if(A){const O=new ArrayBuffer(S*function(x){switch(x){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 ${x}`)}}(m));this.cache=function(x,I){return new(e(I))(x)}(O,m)}}}static fromProto(g){if(!g)throw new Error("cannot construct Value from an empty tensor");const m=f.ProtoUtil.tensorDataTypeFromProto(g.dataType),_=f.ProtoUtil.tensorDimsFromProto(g.dims),y=new s(_,m);if(m==="string")g.stringData.forEach((w,v)=>{y.data[v]=(0,f.decodeUtf8String)(w)});else if(g.rawData&&typeof g.rawData.byteLength=="number"&&g.rawData.byteLength>0){const w=y.data,v=new DataView(g.rawData.buffer,g.rawData.byteOffset,g.rawData.byteLength),S=t(g.dataType),A=g.rawData.byteLength/S;if(g.rawData.byteLength%S!=0)throw new Error("invalid buffer length");if(w.length!==A)throw new Error("buffer length mismatch");for(let O=0;O0){const w=y.data,v=new DataView(g.rawDataArray().buffer,g.rawDataArray().byteOffset,g.rawDataLength()),S=t(g.dataType()),A=g.rawDataLength()/S;if(g.rawDataLength()%S!=0)throw new Error("invalid buffer length");if(w.length!==A)throw new Error("buffer length mismatch");for(let O=0;O1&&I>1)return;A[S-O]=Math.max(x,I)}return A}static index(m,_){const y=new Array(_.length);return l.fillIndex(m,_,y),y}static fillIndex(m,_,y){const w=m.length-_.length;for(let v=0;v<_.length;v++)y[v]=m[w+v]%_[v]}static calc(m,_,y,w,v){const S=l.calcShape(m.dims,_.dims);if(S){if(w&&!e.areEqual(S,m.dims))return;const A=e.size(S),O=w?m:new h.Tensor(S,v||m.type);if(S.length===0)O.set([],y(m.get([]),_.get([])));else{const x=new Array(S.length),I=new Array(m.dims.length),N=new Array(_.dims.length);let R,L=0,F=0,V=!1,D=!1;m.dims.length===0&&(L=m.get([]),V=!0),_.dims.length===0&&(F=_.get([]),D=!0);for(let j=0;j=0;Q--)x[Q]=R%S[Q],R=Math.floor(R/S[Q]);V||(l.fillIndex(x,m.dims,I),L=m.get(I)),D||(l.fillIndex(x,_.dims,N),F=_.get(N)),O.set(x,y(L,F))}}return O}}static isValidBroadcast(m,_){const y=m.length,w=_.length;if(y>w)return!1;for(let v=1;v<=y;v++)if(m[y-v]!==1&&m[y-v]!==_[w-v])return!1;return!0}static getBroadcastDims(m,_){const y=m.length,w=[];for(let v=0;v1&&A===1&&w.unshift(S)}return w}}n.BroadcastUtil=l,n.arrayCopyHelper=function(g,m,_,y,w){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+w>m.length)throw new Error("source indices to be copied are outside bounds");if(_+w>g.length)throw new Error("target array is too small to hold result");for(let v=0;vp.default.isLong(_)?_.toNumber():_)}static tensorValueTypeFromProto(m){return{tensorType:s.tensorDataTypeFromProto(m.elemType),shape:{dims:s.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 ${m.length} dimensions.`);return e.getSizeFromDimensionRange(m,0,_)}static getSizeFromDimensionRange(m,_,y){let w=1;for(let v=_;v=0;--w)y[w]=y[w+1]*m[w+1];return y}static transpose(m){return m.slice().reverse()}static indicesToOffset(m,_,y){y===void 0&&(y=m.length);let w=0;for(let v=0;v=_)throw new Error("unsupported axis for this operation.");return m<0?m+_:m}static normalizeAxes(m,_){return m.map(y=>this.normalizeAxis(y,_))}static incrementIndex(m,_,y){if(_.length===0||m.length===0)throw new Error("Index incrementing unsupported for scalar Tensor");if(y===void 0)y=_.length;else if(y<=0||y>_.length)throw new Error("Incorrect axis to increment on");for(let w=y-1;w>=0&&(m[w]++,!(m[w]<_[w]));--w)m[w]=0}static calculateReshapedDims(m,_){if(_.length===0){if(m.length===0||e.size(m)===1)return[];throw new Error("cannot reshape to a scalar Tensor")}const y=_.length,w=new Array(y);let v=-1,S=1;for(let O=0;O=m.length)throw new Error("the dimension with value zero exceeds the dimension size of the input tensor");w[O]=m[O]}else w[O]=_[O];S*=w[O]}}const A=e.size(m);if(v!==-1){if(A%S!=0)throw new Error(`the input tensor cannot be reshaped to the requested shape. Input shape: [${m}] Output shape: [${_}]`);w[v]=A/S}else if(S!==A)throw new Error("reshapedDims and originalDims don't have matching sizes");return w}static sortBasedOnPerm(m,_){return _?_.map(y=>m[y]):m.slice().reverse()}static padShape(m,_){const y=m.length;return m.map((w,v)=>w+_[v]+_[v+y])}static areEqual(m,_){return m.length===_.length&&m.every((y,w)=>y===_[w])}static validateDimsAndCalcSize(m){if(m.length>6)throw new TypeError("Only rank 0 to 6 is supported for tensor shape.");let _=1;for(const y of m){if(!Number.isInteger(y))throw new TypeError(`Invalid shape: ${y} is not an integer`);if(y<0||y>2147483647)throw new TypeError(`Invalid shape: length ${y} is not allowed`);_*=y}return _}static flattenShape(m,_){_<0&&(_+=m.length);const y=m.reduce((v,S)=>v*S,1),w=m.slice(_).reduce((v,S)=>v*S,1);return[y/w,w]}static squeezeShape(m,_){const y=new Array;_=e.normalizeAxes(_,m.length);for(let w=0;w=0;if(v&&m[w]!==1)throw new Error("squeeze an axis of size different than 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Error("`env.useCustomCache=true`, but `env.customCache` is not defined.");const p=u.revision??"main";let a=pathJoin(b,n),h=pathJoin(env.localModelPath,a),f=pathJoin(env.remoteHost,env.remotePathTemplate.replaceAll("{model}",b).replaceAll("{revision}",p),n),l=p==="main"?a:pathJoin(b,p,n),s,t=c instanceof FileCache?l:f,e=!1,r;if(c&&(r=await tryCache(c,h,t)),r===void 0){if(env.allowLocalModels)if(isValidHttpUrl(a)){if(u.local_files_only)throw new Error(`\`local_files_only=true\`, but attempted to load a remote file from: ${a}.`)}else try{r=await getFile(h),s=h}catch(g){console.warn(`Unable to load from local path "${h}": "${g}"`)}if(r===void 0||r.status===404){if(u.local_files_only||!env.allowRemoteModels){if(o)throw Error(`\`local_files_only=true\` or \`env.allowRemoteModels=false\` and file was not found locally at "${h}".`);return null}if(r=await getFile(f),r.status!==200)return handleError(r.status,f,o);s=t}e=c&&typeof Response<"u"&&r instanceof 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Will expand buffer when needed.");let u=parseInt(o??"0"),c=new Uint8Array(u),p=0;const a=b.body.getReader();async function h(){const{done:f,value:l}=await a.read();if(f)return;let s=p+l.length;if(s>u){u=s;let e=new Uint8Array(u);e.set(c),c=e}c.set(l,p),p=s;const t=p/u*100;return n({progress:t,loaded:p,total:u}),h()}return await h(),c}function pathJoin(...b){return b=b.map((n,o)=>(o&&(n=n.replace(new RegExp("^/"),"")),o!==b.length-1&&(n=n.replace(new RegExp("/$"),"")),n)),b.join("/")}function interpolate_data(b,[n,o,u],[c,p],a="bilinear",h=!1){const f=p/u,l=c/o,s=new b.constructor(c*p*n),t=o*u,e=c*p;for(let r=0;r=0;--h)c[h]=f,u[h]=n[o[h]],f*=u[h];const p=o.map((h,f)=>c[o.indexOf(f)]),a=new b.constructor(b.length);for(let h=0;h=0;--l)f+=s%n[l]*p[l],s=Math.floor(s/n[l]);a[f]=b[h]}return[a,u]}function softmax(b){const n=max(b)[0],o=b.map(p=>Math.exp(p-n)),u=o.reduce((p,a)=>p+a,0);return o.map(p=>p/u)}function log_softmax(b){return softmax(b).map(u=>Math.log(u))}function getTopItems(b,n=0){return b=Array.from(b).map((o,u)=>[u,o]).sort((o,u)=>u[1]-o[1]),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],o=0;for(let u=1;un&&(n=b[u],o=u);return[n,o]}function rfftfreq(b,n=1){if(!Number.isInteger(b))throw new TypeError(`n should be an integer, but ${b} given.`);const o=1/(b*n),u=Math.floor(b/2)+1,c=new Array(u);for(let p=0;pu;u<<=1)++o;this._width=o%2===0?o-1:o,this._bitrev=new Int32Array(1<>>c&3)<>>1);for(let c=0;c>>1]=n[c];return u}toComplexArray(n,o){const u=o||this.createComplexArray();for(let c=0;c>>1],u[c+1]=0;return u}completeSpectrum(n){const o=this._csize,u=o>>>1;for(let c=2;c>=2;a>=2;a>>=2){h=c/a<<1;let t=h>>>2;for(f=0;f>>1,a>>>1)}else for(f=0,l=0;f>>1,a>>>1,u)}for(a>>=2;a>=2;a>>=2){h=c/a<<1;const t=h>>>1,e=t>>>1,r=e>>>1;for(f=0;f=b.length&&(f=2*(b.length-1)-f),u[a++]=b[f]}u.sort(),o[p]=u[c]}return o}function round(b,n){const o=Math.pow(10,n);return Math.round(b*o)/o}const ONNXTensor$1=ONNX.Tensor;class Tensor extends ONNXTensor$1{constructor(...n){return n[0]instanceof ONNX.Tensor?super(n[0].type,n[0].data,n[0].dims):super(...n),new Proxy(this,{get:(o,u)=>{if(typeof u=="string"){let c=Number(u);if(Number.isInteger(c))return o._getitem(c)}return o[u]},set:(o,u,c)=>o[u]=c})}*[Symbol.iterator](){const[n,...o]=this.dims;if(o.length>0){const u=o.reduce((c,p)=>c*p);for(let c=0;c0){const c=u.reduce((p,a)=>p*a);return this._subarray(n,c,u)}else return new Tensor(this.type,[this.data[n]],u)}indexOf(n){for(let o=0;ol[1])throw new Error(`Invalid slice: ${l}`);let s=[Math.max(l[0],0),Math.min(l[1],this.dims[f])];u.push(s),o.push(s[1]-s[0])}else throw new Error(`Invalid slice: ${l}`)}let c=u.map(([f,l])=>l-f),p=c.reduce((f,l)=>f*l),a=new this.data.constructor(p);const h=this.stride();for(let f=0;f=0;--s){const e=c[s];l+=(t%e+u[s][0])*h[s],t=Math.floor(t/e)}a[f]=this.data[l]}return new Tensor(this.type,a,o)}transpose(...n){return transpose(this,n)}sum(n=null,o=!1){return this.norm(1,n,o)}norm(n="fro",o=null,u=!1){if(n==="fro")n=2;else if(typeof n=="string")throw Error(`Unsupported norm: ${n}`);if(o===null){let a=this.data.reduce((h,f)=>h+f**n,0)**(1/n);return new Tensor(this.type,[a],[])}o=safeIndex(o,this.dims.length);const c=this.dims.slice();c[o]=1;const p=new this.data.constructor(this.data.length/this.dims[o]);for(let a=0;a=0;--f){const t=this.dims[f];if(f!==o){const e=l%t;h+=e*s,s*=c[f]}l=Math.floor(l/t)}p[h]+=this.data[a]**n}if(n!==1)for(let a=0;a=0;--a){const l=this.dims[a];if(a!==o){const s=h%l;p+=s*f,f*=this.dims[a]}h=Math.floor(h/l)}this.data[c]/=u.data[p]}return this}normalize(n=2,o=1){return this.clone().normalize_(n,o)}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,o=-1){o=(o+this.dims.length)%this.dims.length;let u=this.dims.slice(0,n),c=this.dims.slice(n,o+1),p=this.dims.slice(o+1);return this.dims=[...u,c.reduce((a,h)=>a*h,1),...p],this}flatten(n=0,o=-1){return this.clone().flatten_(n,o)}view(...n){let o=-1;for(let u=0;ua!==o?c*p:c,1);n[o]=this.data.length/u}return new Tensor(this.type,this.data,n)}neg_(){for(let n=0;np*a);if(o!==u)throw Error(`cannot reshape array of size ${o} into shape (${n})`);let c=b;for(let p=n.length-1;p>=0;p--)c=c.reduce((a,h)=>{let f=a[a.length-1];return f.lengtho!==1):typeof n=="number"?b[n]===1&&b.splice(n,1):Array.isArray(n)&&(b=b.filter((o,u)=>o!==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,o=null){if(b<-n||b>=n)throw new Error(`IndexError: index ${b} is out of bounds for dimension${o===null?"":" "+o} with size ${n}`);return b<0&&(b=(b%n+n)%n),b}function cat(b,n=0){n=safeIndex(n,b[0].dims.length);const o=b[0].dims.slice();o[n]=b.reduce((a,h)=>a+h.dims[n],0);const u=o.reduce((a,h)=>a*h,1),c=new b[0].data.constructor(u),p=b[0].type;if(n===0){let a=0;for(let h of b)c.set(h.data,a),a+=h.data.length}else{let a=0;for(let h=0;h=0;--t){const i=f.dims[t];let d=e%i;t===n&&(d+=a),s+=d*r,r*=o[t],e=Math.floor(e/i)}c[s]=f.data[l]}a+=f.dims[n]}}return new Tensor(p,c,o)}function stack(b,n=0){return cat(b.map(o=>o.unsqueeze(n)),n)}function std_mean(b,n=null,o=1,u=!1){if(n===null){const l=b.data.reduce((r,i)=>r+i,0)/b.data.length,s=Math.sqrt(b.data.reduce((r,i)=>r+(i-l)**2,0)/(b.data.length-o)),t=new Tensor(b.type,[l],[]);return[new Tensor(b.type,[s],[]),t]}n=safeIndex(n,b.dims.length);const c=mean(b,n,u),p=b.dims.slice();p[n]=1;const a=new b.data.constructor(b.data.length/b.dims[n]);for(let f=0;f=0;--s){const r=b.dims[s];if(s!==n){const i=t%r;l+=i*e,e*=p[s]}t=Math.floor(t/r)}a[l]+=(b.data[f]-c.data[l])**2}for(let f=0;fa+h,0);return new Tensor(b.type,[p/b.data.length],[])}n=safeIndex(n,b.dims.length);const u=b.dims.slice();u[n]=1;const c=new b.data.constructor(b.data.length/b.dims[n]);for(let p=0;p=0;--h){const s=b.dims[h];if(h!==n){const t=f%s;a+=t*l,l*=u[h]}f=Math.floor(f/s)}c[a]+=b.data[p]}if(b.dims[n]!==1)for(let p=0;p0||h>0;)switch(f.push(a-1),l.push(h-1),p[a][h].item()){case 0:--a,--h;break;case 1:--a;break;case 2:--h;break;default:throw new Error(`Internal error in dynamic time warping. Unexpected trace[${a}, ${h}]. Please file a bug report.`)}return f.reverse(),l.reverse(),[f,l]}function dimsToStride(b){const n=new Array(b.length);for(let o=b.length-1,u=1;o>=0;--o)n[o]=u,u*=b[o];return n}class PriorityQueue{constructor(n=(o,u)=>o>u){this._heap=[],this._comparator=n}get size(){return this._heap.length}isEmpty(){return this.size===0}peek(){return this._heap[0]}push(...n){return this.extend(n)}extend(n){for(const o of n)this._heap.push(o),this._siftUp();return this.size}pop(){const n=this.peek(),o=this.size-1;return o>0&&this._swap(0,o),this._heap.pop(),this._siftDown(),n}replace(n){const o=this.peek();return this._heap[0]=n,this._siftDown(),o}_parent(n){return(n+1>>>1)-1}_left(n){return(n<<1)+1}_right(n){return n+1<<1}_greater(n,o){return this._comparator(this._heap[n],this._heap[o])}_swap(n,o){const u=this._heap[n];this._heap[n]=this._heap[o],this._heap[o]=u}_siftUp(){let n=this.size-1;for(;n>0&&this._greater(n,this._parent(n));)this._swap(n,this._parent(n)),n=this._parent(n)}_siftDown(){let n=0;for(;this._left(n)[]),this.endNodes=Array.from({length:this.len+1},()=>[]);const c=new TokenLatticeNode(this.bosTokenId,0,0,0,0),p=new TokenLatticeNode(this.eosTokenId,1,this.len,0,0);this.nodes.push(c.clone()),this.nodes.push(p.clone()),this.beginNodes[this.len].push(p),this.endNodes[0].push(c)}insert(n,o,u,c){const p=this.nodes.length,a=new TokenLatticeNode(c,p,n,o,u);this.beginNodes[n].push(a),this.endNodes[n+o].push(a),this.nodes.push(a)}viterbi(){const n=this.len;let o=0;for(;o<=n;){if(this.beginNodes[o].length==0)return[];for(let h of this.beginNodes[o]){h.prev=null;let f=0,l=null;for(let s of this.endNodes[o]){const t=s.backtraceScore+h.score;(l===null||t>f)&&(l=s.clone(),f=t)}if(l!==null)h.prev=l,h.backtraceScore=f;else return[]}++o}const u=[],p=this.beginNodes[n][0].prev;if(p===null)return[];let a=p.clone();for(;a.prev!==null;)u.push(a.clone()),a=a.clone().prev.clone();return u.reverse(),u}piece(n){return this.sentence.slice(n.pos,n.pos+n.length)}tokens(){return this.viterbi().map(o=>this.piece(o))}tokenIds(){return this.viterbi().map(o=>o.tokenId)}}class TokenLatticeNode{constructor(n,o,u,c,p){this.tokenId=n,this.nodeId=o,this.pos=u,this.length=c,this.score=p,this.prev=null,this.backtraceScore=0}clone(){const n=new TokenLatticeNode(this.tokenId,this.nodeId,this.pos,this.length,this.score);return n.prev=this.prev,n.backtraceScore=this.backtraceScore,n}}async function loadTokenizer(b,n){return await Promise.all([getModelJSON(b,"tokenizer.json",!0,n),getModelJSON(b,"tokenizer_config.json",!0,n)])}function createPattern(b,n=!0){return b.Regex!==void 0?new RegExp(n?b.Regex:`(${b.Regex})`,"gu"):b.String!==void 0?b.String:(console.warn("Unknown pattern type:",b),null)}function clean_up_tokenization(b){return b.replace(/ \./g,".").replace(/ \?/g,"?").replace(/ \!/g,"!").replace(/ ,/g,",").replace(/ \' /g,"'").replace(/ n\'t/g,"n't").replace(/ \'m/g,"'m").replace(/ \'s/g,"'s").replace(/ \'ve/g,"'ve").replace(/ \'re/g,"'re")}function fuse(b,n){let o=[],u=0;for(;uthis.tokens_to_ids.get(u)??this.unk_token_id);return this.fuse_unk&&(o=fuse(o,this.unk_token_id)),o}convert_ids_to_tokens(n){return n.map(o=>this.vocab[o]??this.unk_token)}}class WordPieceTokenizer extends TokenizerModel{constructor(n){super(n),this.tokens_to_ids=n.vocab,this.unk_token_id=this.tokens_to_ids.get(n.unk_token),this.unk_token=n.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[o,u]of this.tokens_to_ids)this.vocab[u]=o}encode(n){let o=[];for(let u of n){let c=[...u],p=!1,a=0,h=[];for(;a0&&(s=this.config.continuing_subword_prefix+s),this.tokens_to_ids.has(s)){l=s;break}--f}if(l===null){p=!0;break}h.push(l),a=f}p?o.push(this.unk_token):o.push(...h)}return o}}class Unigram extends TokenizerModel{constructor(n,o){super(n),this.vocab=new Array(n.vocab.size),this.scores=new Array(n.vocab.size);let u=0;n.vocab.forEach((c,p)=>{this.vocab[u]=p,this.scores[u]=c,++u}),this.unk_token_id=n.unk_id,this.unk_token=this.vocab[n.unk_id],this.tokens_to_ids=new Map(this.vocab.map((c,p)=>[c,p])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=o.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=min(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new CharTrie,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(n){const o=n.sentence,u=o.length;let c=0;for(;c{const b=[...Array.from({length:"~".charCodeAt(0)-"!".charCodeAt(0)+1},(c,p)=>p+"!".charCodeAt(0)),...Array.from({length:"¬".charCodeAt(0)-"¡".charCodeAt(0)+1},(c,p)=>p+"¡".charCodeAt(0)),...Array.from({length:"ÿ".charCodeAt(0)-"®".charCodeAt(0)+1},(c,p)=>p+"®".charCodeAt(0))];let n=b.slice(),o=0;for(let c=0;c<256;++c)b.includes(c)||(b.push(c),n.push(256+o),o+=1);let u=n.map(c=>String.fromCharCode(c));return Object.fromEntries(b.map((c,p)=>[c,u[p]]))})(),UNICODE_TO_BYTES=reverseDictionary(BYTES_TO_UNICODE);class BPE extends TokenizerModel{constructor(n){super(n),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=n.vocab,this.unk_token_id=this.tokens_to_ids.get(n.unk_token),this.unk_token=n.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[o,u]of this.tokens_to_ids)this.vocab[u]=o;this.bpe_ranks=new Map(n.merges.map((o,u)=>[o,u])),this.merges=n.merges.map(o=>o.split(this.BPE_SPLIT_TOKEN)),this.end_of_word_suffix=n.end_of_word_suffix,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.cache=new Map,this.fuse_unk??(this.fuse_unk=this.config.fuse_unk)}bpe(n){if(n.length===0)return[];const o=this.cache.get(n);if(o!==void 0)return o;const u=Array.from(n);this.end_of_word_suffix&&(u[u.length-1]+=this.end_of_word_suffix);let c=[];if(u.length>1){const p=new PriorityQueue((f,l)=>f.score`<0x${a.toString(16).toUpperCase().padStart(2,"0")}>`)):o.push(this.unk_token)}return o}}class LegacyTokenizerModel extends TokenizerModel{constructor(n,o){super(n),this.tokens_to_ids=o.target_lang?n.vocab.get(o.target_lang):n.vocab,this.bos_token=o.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=o.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=o.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=o.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=new Array(this.tokens_to_ids.size);for(const[u,c]of this.tokens_to_ids)this.vocab[c]=u}encode(n){return n}}class Normalizer extends Callable{constructor(n){super(),this.config=n}static fromConfig(n){if(n===null)return null;switch(n.type){case"BertNormalizer":return new BertNormalizer(n);case"Precompiled":return new Precompiled(n);case"Sequence":return new NormalizerSequence(n);case"Replace":return new Replace(n);case"NFC":return new NFC(n);case"NFKD":return new NFKD(n);case"Strip":return new StripNormalizer(n);case"StripAccents":return new StripAccents(n);case"Lowercase":return new Lowercase(n);case"Prepend":return new Prepend(n);default:throw new Error(`Unknown Normalizer type: ${n.type}`)}}normalize(n){throw Error("normalize should be implemented in subclass.")}_call(n){return this.normalize(n)}}class Replace extends Normalizer{normalize(n){let o=createPattern(this.config.pattern);return o===null||(n=n.replaceAll(o,this.config.content)),n}}class NFC extends Normalizer{normalize(n){return n=n.normalize("NFC"),n}}class NFKD extends Normalizer{normalize(n){return n=n.normalize("NFKD"),n}}class StripNormalizer extends Normalizer{normalize(n){return this.config.strip_left&&this.config.strip_right?n=n.trim():(this.config.strip_left&&(n=n.trimStart()),this.config.strip_right&&(n=n.trimEnd())),n}}class StripAccents extends Normalizer{normalize(n){return n=n.replace(/[\u0300-\u036f]/g,""),n}}class Lowercase extends Normalizer{normalize(n){return n=n.toLowerCase(),n}}class Prepend extends Normalizer{normalize(n){return n=this.config.prepend+n,n}}class NormalizerSequence extends Normalizer{constructor(n){super(n),this.normalizers=n.normalizers.map(o=>Normalizer.fromConfig(o))}normalize(n){return this.normalizers.reduce((o,u)=>u.normalize(o),n)}}class BertNormalizer extends Normalizer{_tokenize_chinese_chars(n){let o=[];for(let u=0;u=19968&&n<=40959||n>=13312&&n<=19903||n>=131072&&n<=173791||n>=173824&&n<=177983||n>=177984&&n<=178207||n>=178208&&n<=183983||n>=63744&&n<=64255||n>=194560&&n<=195103}stripAccents(n){return n.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}normalize(n){return this.config.handle_chinese_chars&&(n=this._tokenize_chinese_chars(n)),this.config.lowercase?(n=n.toLowerCase(),this.config.strip_accents!==!1&&(n=this.stripAccents(n))):this.config.strip_accents&&(n=this.stripAccents(n)),n}}class PreTokenizer extends Callable{static fromConfig(n){if(n===null)return null;switch(n.type){case"BertPreTokenizer":return new BertPreTokenizer(n);case"Sequence":return new PreTokenizerSequence(n);case"WhitespaceSplit":return new WhitespaceSplit(n);case"Metaspace":return new MetaspacePreTokenizer(n);case"ByteLevel":return new ByteLevelPreTokenizer(n);case"Split":return new SplitPreTokenizer(n);case"Punctuation":return new PunctuationPreTokenizer(n);case"Digits":return new DigitsPreTokenizer(n);default:throw new Error(`Unknown PreTokenizer type: ${n.type}`)}}pre_tokenize_text(n){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(n){let o=[];return Array.isArray(n)?o=n.map(u=>this.pre_tokenize_text(u)):o=this.pre_tokenize_text(n),o.flat()}_call(n){return this.pre_tokenize(n)}}class BertPreTokenizer extends PreTokenizer{constructor(n){super(),this.pattern=new RegExp(`[^\\s${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]`,"gu")}pre_tokenize_text(n){return n.trim().match(this.pattern)||[]}}class ByteLevelPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=/'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+/gu,this.byte_encoder=BYTES_TO_UNICODE,this.text_encoder=new TextEncoder}pre_tokenize_text(n){return(this.use_regex?n.match(this.pattern)||[]:[n]).map(u=>(this.add_prefix_space&&!u.startsWith(" ")&&(u=" "+u),u=Array.from(this.text_encoder.encode(u),c=>this.byte_encoder[c]).join(""),u))}}class SplitPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=createPattern(this.config.pattern,this.config.invert)}pre_tokenize_text(n){return this.pattern===null?[]:this.config.invert?n.match(this.pattern)||[]:n.split(this.pattern).filter(o=>o)}}class PunctuationPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=new RegExp(`[^${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]+`,"gu")}pre_tokenize_text(n){return n.match(this.pattern)||[]}}class DigitsPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n;const o=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(o,"gu")}pre_tokenize_text(n){return n.match(this.pattern)||[]}}class PostProcessor extends Callable{constructor(n){super(),this.config=n}static fromConfig(n){if(n===null)return null;switch(n.type){case"TemplateProcessing":return new TemplateProcessing(n);case"ByteLevel":return new ByteLevelPostProcessor(n);case"RobertaProcessing":return new RobertaProcessing(n);default:throw new Error(`Unknown PostProcessor type: ${n.type}`)}}post_process(n,...o){throw Error("post_process should be implemented in subclass.")}_call(n,...o){return this.post_process(n,...o)}}class RobertaProcessing extends PostProcessor{constructor(n){super(n),this.cls=n.cls[0],this.sep=n.sep[0]}post_process(n,o=null){return n=mergeArrays([this.cls],n,[this.sep]),o!==null&&(n=mergeArrays(n,[this.sep],o,[this.sep])),n}}class TemplateProcessing extends PostProcessor{constructor(n){super(n),this.single=n.single,this.pair=n.pair}post_process(n,o=null){let u=o===null?this.single:this.pair,c=[];for(let p of u)"SpecialToken"in p?c.push(p.SpecialToken.id):"Sequence"in p&&(p.Sequence.id==="A"?c=mergeArrays(c,n):p.Sequence.id==="B"&&(c=mergeArrays(c,o)));return c}}class ByteLevelPostProcessor extends PostProcessor{post_process(n){return n}}class Decoder extends Callable{constructor(n){super(),this.config=n,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=n.trim_offsets}static fromConfig(n){switch(n.type){case"WordPiece":return new WordPieceDecoder(n);case"Metaspace":return new MetaspaceDecoder(n);case"ByteLevel":return new ByteLevelDecoder(n);case"Replace":return new ReplaceDecoder(n);case"ByteFallback":return new ByteFallback(n);case"Fuse":return new FuseDecoder(n);case"Strip":return new StripDecoder(n);case"Sequence":return new DecoderSequence(n);case"CTC":return new CTCDecoder(n);default:throw new Error(`Unknown Decoder type: ${n.type}`)}}_call(n){return this.decode(n)}decode(n){return this.decode_chain(n).join("")}decode_chain(n){throw Error("`decode_chain` should be implemented in subclass.")}}class ReplaceDecoder extends Decoder{decode_chain(n){let o=createPattern(this.config.pattern);return o===null?n:n.map(u=>u.replaceAll(o,this.config.content))}}class ByteFallback extends Decoder{constructor(n){super(n),this.text_decoder=new TextDecoder}decode_chain(n){let o=[],u=[];for(let c of n){let p=null;if(c.length===6&&c.startsWith("<0x")&&c.endsWith(">")){let a=parseInt(c.slice(3,5),16);isNaN(a)||(p=a)}if(p!==null)u.push(p);else{if(u.length>0){let a=this.text_decoder.decode(Uint8Array.from(u));o.push(a),u=[]}o.push(c)}}if(u.length>0){let c=this.text_decoder.decode(Uint8Array.from(u));o.push(c),u=[]}return o}}class FuseDecoder extends Decoder{decode_chain(n){return[n.join("")]}}class StripDecoder extends Decoder{constructor(n){super(n),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(n){return n.map(o=>{let u=0;for(let p=0;p(u!==0&&(o.startsWith(this.config.prefix)?o=o.replace(this.config.prefix,""):o=" "+o),this.cleanup&&(o=clean_up_tokenization(o)),o))}}class ByteLevelDecoder extends Decoder{constructor(n){super(n),this.byte_decoder=UNICODE_TO_BYTES,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(n){let o=n.join(""),u=new Uint8Array([...o].map(p=>this.byte_decoder[p]));return this.text_decoder.decode(u)}decode_chain(n){let o=[],u=[];for(let c of n)this.added_tokens.includes(c)?(u.length>0&&(o.push(this.convert_tokens_to_string(u)),u=[]),o.push(c)):u.push(c);return u.length>0&&o.push(this.convert_tokens_to_string(u)),o}}class CTCDecoder extends Decoder{constructor(n){super(n),this.pad_token=this.config.pad_token,this.word_delimiter_token=this.config.word_delimiter_token,this.cleanup=this.config.cleanup}convert_tokens_to_string(n){if(n.length===0)return"";let o=[n[0]];for(let p=1;pp!==this.pad_token).join("");return this.cleanup&&(c=clean_up_tokenization(c).replaceAll(this.word_delimiter_token," ").trim()),c}decode_chain(n){return[this.convert_tokens_to_string(n)]}}class DecoderSequence extends Decoder{constructor(n){super(n),this.decoders=n.decoders.map(o=>Decoder.fromConfig(o))}decode_chain(n){return this.decoders.reduce((o,u)=>u.decode_chain(o),n)}}class MetaspacePreTokenizer extends PreTokenizer{constructor(n){super(),this.addPrefixSpace=n.add_prefix_space,this.replacement=n.replacement,this.strRep=n.str_rep||this.replacement}pre_tokenize(n){typeof n=="string"&&(n=n.trimStart().split(/\s+/));const o=[];for(let u of n){let c=u.replaceAll(" ",this.strRep);this.addPrefixSpace&&!c.startsWith(this.replacement)&&(c=this.strRep+c),o.push(c)}return o}}class MetaspaceDecoder extends Decoder{constructor(n){super(n),this.addPrefixSpace=n.add_prefix_space,this.replacement=n.replacement}decode_chain(n){let o=[];for(let u=0;uu.normalize("NFKC")).join("~"):n=n.normalize("NFKC"),n}}class PreTokenizerSequence extends PreTokenizer{constructor(n){super(),this.tokenizers=n.pretokenizers.map(o=>PreTokenizer.fromConfig(o))}pre_tokenize_text(n){return typeof n=="string"&&(n=[n]),this.tokenizers.reduce((o,u)=>u.pre_tokenize(o),n)}}class WhitespaceSplit extends PreTokenizer{constructor(n){super()}pre_tokenize_text(n){return whitespace_split(n)}}class PreTrainedTokenizer extends Callable{constructor(n,o){if(super(),this.normalizer=Normalizer.fromConfig(n.normalizer),this.pre_tokenizer=PreTokenizer.fromConfig(n.pre_tokenizer),n.model.vocab){Array.isArray(n.model.vocab)||(n.model.vocab=Object.entries(n.model.vocab)),n.model.vocab=new Map(n.model.vocab);for(const[u,c]of n.model.vocab)typeof c=="object"&&n.model.vocab.set(u,new Map(Object.entries(c)))}this.model=TokenizerModel.fromConfig(n.model,o),this.post_processor=PostProcessor.fromConfig(n.post_processor),this.decoder=Decoder.fromConfig(n.decoder),this.decoder.end_of_word_suffix=this.model.end_of_word_suffix,this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(let u of n.added_tokens){let c=u.id,p=u.content;this.added_tokens.push(p),this.model.tokens_to_ids.set(p,c),this.model.vocab[c]=p,u.special&&(this.special_tokens.push(p),this.all_special_ids.push(c))}this.special_tokens.push(...o.additional_special_tokens??[]),this.special_tokens=[...new Set(this.special_tokens)],this.decoder.added_tokens=this.added_tokens,this.added_tokens_regex=this.added_tokens.length>0?new RegExp("("+this.added_tokens.map(escapeRegExp).join("|")+")"):null,this.mask_token=this.getToken(o,"mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken(o,"pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken(o,"sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.model_max_length=o.model_max_length,this.remove_space=o.remove_space,this.clean_up_tokenization_spaces=o.clean_up_tokenization_spaces??!0,this.padding_side="right"}getToken(n,...o){for(let u of o){let c=n[u];if(c)if(typeof c=="object"){if(c.__type==="AddedToken")return c.content;throw Error(`Unknown token: ${c}`)}else return c}return null}static async from_pretrained(n,{progress_callback:o=null,config:u=null,cache_dir:c=null,local_files_only:p=!1,revision:a="main"}={}){let h=await loadTokenizer(n,{progress_callback:o,config:u,cache_dir:c,local_files_only:p,revision:a});return new this(...h)}prepare_model_inputs(n){return n}_call(n,{text_pair:o=null,padding:u=!1,truncation:c=null,max_length:p=null,return_tensor:a=!0}={}){let h;if(Array.isArray(n)){if(n.length===0)throw Error("text array must be non-empty");if(o!==null){if(Array.isArray(o)){if(n.length!==o.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");h=n.map((t,e)=>this.encode(t,o[e]))}else h=n.map(t=>this.encode(t))}else{if(n===null)throw Error("text may not be null");if(Array.isArray(o))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");h=[this.encode(n,o)]}let f=max(h.map(t=>t.length))[0];p===null&&(p=f),p=Math.min(p,this.model_max_length);let l=[];if(u||c)for(let t=0;tp)c&&(h[t]=h[t].slice(0,p)),l.push(new Array(h[t].length).fill(1));else if(u){let e=p-h[t].length;this.padding_side==="right"?(l.push(new Array(h[t].length).fill(1).concat(new Array(e).fill(0))),h[t].push(...new Array(e).fill(this.pad_token_id))):(l.push(new Array(e).fill(0).concat(new Array(h[t].length).fill(1))),h[t].unshift(...new Array(e).fill(this.pad_token_id)))}else l.push(new Array(h[t].length).fill(1));else l=h.map(t=>new Array(t.length).fill(1));if(a){if(!(u&&c)&&h.some(e=>e.length!==h[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");let t=[h.length,h[0].length];h=new Tensor("int64",BigInt64Array.from(h.flat().map(BigInt)),t),l=new Tensor("int64",BigInt64Array.from(l.flat().map(BigInt)),t)}else Array.isArray(n)||(h=h[0],l=l[0]);let s={input_ids:h,attention_mask:l};return s=this.prepare_model_inputs(s),s}_encode_text(n){return n===null?null:(this.added_tokens_regex?n.split(this.added_tokens_regex).filter(c=>c):[n]).map(c=>{if(this.added_tokens.includes(c))return c;{this.remove_space===!0&&(c=c.trim().split(/\s+/).join(" ")),this.normalizer!==null&&(c=this.normalizer(c));let p=this.pre_tokenizer!==null?this.pre_tokenizer(c):[c];return this.model(p)}}).flat()}encode(n,o=null){let u=this._encode_text(n),c=this._encode_text(o),p=this.post_processor!==null?this.post_processor(u,c):mergeArrays(u??[],c??[]);return this.model.convert_tokens_to_ids(p)}batch_decode(n,o={}){return n.map(u=>this.decode(u,o))}decode(n,o={}){if(!Array.isArray(n)||n.length===0||!isIntegralNumber(n[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(n,o)}decode_single(n,{skip_special_tokens:o=!1,clean_up_tokenization_spaces:u=null}){let c=this.model.convert_ids_to_tokens(n);o&&(c=c.filter(a=>!this.special_tokens.includes(a)));let p=this.decoder(c);return this.decoder.end_of_word_suffix&&(p=p.replaceAll(this.decoder.end_of_word_suffix," "),o&&(p=p.trim())),(u??this.clean_up_tokenization_spaces)&&(p=clean_up_tokenization(p)),p}}function add_token_types(b){if(b.input_ids instanceof Tensor)b.token_type_ids=new Tensor("int64",new BigInt64Array(b.input_ids.data.length),b.input_ids.dims);else if(Array.isArray(b.input_ids))Array.isArray(b.input_ids[0])?b.token_type_ids=b.input_ids.map(n=>new Array(n.length).fill(0)):b.token_type_ids=new Array(b.input_ids.length).fill(0);else throw new Error("Input ids must be a Tensor or an Array");return b}class BertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class AlbertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class MobileBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class SqueezeBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class DebertaTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class DebertaV2Tokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class DistilBertTokenizer extends PreTrainedTokenizer{}class T5Tokenizer extends PreTrainedTokenizer{}class GPT2Tokenizer extends PreTrainedTokenizer{}class BartTokenizer extends PreTrainedTokenizer{}class RobertaTokenizer extends PreTrainedTokenizer{}class BloomTokenizer extends PreTrainedTokenizer{}class LlamaTokenizer extends PreTrainedTokenizer{}class XLMRobertaTokenizer extends PreTrainedTokenizer{}class MPNetTokenizer extends PreTrainedTokenizer{}class FalconTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class GPTNeoXTokenizer extends PreTrainedTokenizer{}function _build_translation_inputs(b,n,o,u){if(!("language_codes"in b)||!Array.isArray(b.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in b)||!(b.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in b)||typeof b.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const c=u.src_lang,p=u.tgt_lang;if(!b.language_codes.includes(p))throw new Error(`Target language code "${p}" is not valid. Must be one of: {${b.language_codes.join(", ")}}`);if(c!==void 0){if(!b.language_codes.includes(c))throw new Error(`Source language code "${c}" is not valid. Must be one of: {${b.language_codes.join(", ")}}`);for(let a of b.post_processor.config.single)if("SpecialToken"in a&&b.languageRegex.test(a.SpecialToken.id)){a.SpecialToken.id=b.lang_to_token(c);break}}return u.forced_bos_token_id=b.model.convert_tokens_to_ids([b.lang_to_token(p)])[0],b._call(n,o)}class NllbTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(u=>this.languageRegex.test(u)),this.lang_to_token=u=>u}_build_translation_inputs(n,o,u){return _build_translation_inputs(this,n,o,u)}}class M2M100Tokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(u=>this.languageRegex.test(u)).map(u=>u.slice(2,-2)),this.lang_to_token=u=>`__${u}__`}_build_translation_inputs(n,o,u){return _build_translation_inputs(this,n,o,u)}}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"]],WHISPER_LANGUAGE_MAPPING=new Map(WHISPER_LANGUAGES),WHISPER_TO_LANGUAGE_CODE_MAPPING=new Map([...WHISPER_LANGUAGES.map(([b,n])=>[n,b]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);class WhisperTokenizer extends PreTrainedTokenizer{_decode_asr(n,{return_timestamps:o=!1,return_language:u=!1,time_precision:c=null,force_full_sequences:p=!0}={}){if(c===null)throw Error("Must specify time_precision");let a=null;const h=o==="word";function f(){return{language:a,timestamp:[null,null],text:""}}const l=[];let s=f(),t=0;const e=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let r=[],i=[],d=!1,g=null;const m=new Set(this.all_special_ids);for(let w of n){const v=w.tokens,S=h?w.token_timestamps:null;let A=null,O=e;if("stride"in w){const[N,R,L]=w.stride;if(t-=R,g=N-L,R&&(O=R/c+e),L)for(let F=v.length-1;F>=0;--F){const V=v[F];if(V>=e){if(A!==null&&(V-e)*c=e){const L=(R-e)*c+t,F=round(L,2);if(A!==null&&R>=A)d=!0;else if(d||r.length>0&&R0?(r.push(x),h&&i.push(I)):r.every(N=>N.length===0)&&(s=f(),r=[],x=[],i=[],I=[])}if(r.length>0){if(p&&o)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[w,v]=this.findLongestCommonSequence(r,i),S=this.decode(w);s.text=S,h&&(s.words=this.collateWordTimestamps(w,v,a)),l.push(s)}let _=Object.create(null);const y=l.map(w=>w.text).join("");if(o||u){for(let w=0;w0;let h=a?[]:null,f=a?o[0]:null;for(let l=1;lF===N[V]).length,L=R/w+v;R>1&&L>t&&(t=L,e=[S,A,x,I])}const[i,d,g,m]=e,_=Math.floor((d+i)/2),y=Math.floor((m+g)/2);p.push(...u.slice(0,_)),u=s.slice(y),c=u.length,a&&(h.push(...f.slice(0,_)),f=o[l].slice(y))}return p.push(...u),a?(h.push(...f),[p,h]):[p,[]]}collateWordTimestamps(n,o,u){let[c,p,a]=this.combineTokensIntoWords(n,u),h=[];for(let f=0;f=c){let h=(a-c)*u;h=round(h,2),p.push(`<|${h}|>`),p.push([])}else p[p.length-1].push(a);return p=p.map(a=>typeof a=="string"?a:super.decode(a,o)),p.join("")}splitTokensOnUnicode(n){const o=this.decode(n,{decode_with_timestamps:!0}),u="�";let c=[],p=[],a=[],h=[],f=[],l=0;for(let s=0;s=this.model.tokens_to_ids.get("<|endoftext|>"),i=s.startsWith(" "),d=s.trim(),g=f.test(d);if(r||i||g||p.length===0)p.push(s),a.push(t),h.push(e);else{const m=p.length-1;p[m]+=s,a[m].push(...t),h[m].push(...e)}}return[p,a,h]}mergePunctuations(n,o,u,c,p){let a=structuredClone(n),h=structuredClone(o),f=structuredClone(u),l=a.length-2,s=a.length-1;for(;l>=0;)a[l].startsWith(" ")&&c.includes(a[l].trim())?(a[s]=a[l]+a[s],h[s]=mergeArrays(h[l],h[s]),f[s]=mergeArrays(f[l],f[s]),a[l]="",h[l]=[],f[l]=[]):s=l,--l;for(l=0,s=1;st),h.filter(t=>t.length>0),f.filter(t=>t.length>0)]}get_decoder_prompt_ids({language:n=null,task:o=null,no_timestamps:u=!0}={}){let c=[];if(n){n=n.toLowerCase();let p=WHISPER_TO_LANGUAGE_CODE_MAPPING.get(n);if(p===void 0)if(WHISPER_LANGUAGE_MAPPING.has(n))p=n;else{const f=n.length===2?WHISPER_LANGUAGE_MAPPING.keys():WHISPER_LANGUAGE_MAPPING.values();throw new Error(`Language "${n}" is not supported. Must be one of: ${JSON.stringify(f)}`)}let a=this.model.tokens_to_ids.get(`<|${p}|>`);if(a===void 0)throw new Error(`Unable to find language "${p}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);c.push(a)}else c.push(null);if(o){if(o=o.toLowerCase(),o!=="transcribe"&&o!=="translate")throw new Error(`Task "${o}" is not supported. Must be one of: ["transcribe", "translate"]`);let p=this.model.tokens_to_ids.get(`<|${o}|>`);if(p===void 0)throw new Error(`Unable to find task "${o}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);c.push(p)}else c.push(null);if(u){let p=this.model.tokens_to_ids.get("<|notimestamps|>");if(p===void 0)throw new Error('Unable to find "<|notimestamps|>" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.');c.push(p)}return c.map((p,a)=>[a+1,p]).filter(p=>p[1]!==null)}}class CodeGenTokenizer extends PreTrainedTokenizer{}class CLIPTokenizer extends PreTrainedTokenizer{}class MarianTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter(u=>this.languageRegex.test(u)),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(n){if(n===null)return null;let[o,...u]=n.trim().split(this.languageRegex);if(u.length===0)return super._encode_text(o);if(u.length===2){let[c,p]=u;return this.supported_language_codes.includes(c)||console.warn(`Unsupported language code "${c}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),mergeArrays([c],super._encode_text(p))}}}class Wav2Vec2CTCTokenizer extends PreTrainedTokenizer{}class AutoTokenizer{static async from_pretrained(n,{quantized:o=!0,progress_callback:u=null,config:c=null,cache_dir:p=null,local_files_only:a=!1,revision:h="main"}={}){let[f,l]=await loadTokenizer(n,{quantized:o,progress_callback:u,config:c,cache_dir:p,local_files_only:a,revision:h}),s=l.tokenizer_class.replace(/Fast$/,""),t=this.TOKENIZER_CLASS_MAPPING[s];return t||(console.warn(`Unknown tokenizer class "${s}", attempting to construct from base class.`),t=PreTrainedTokenizer),new t(f,l)}}ve(AutoTokenizer,"TOKENIZER_CLASS_MAPPING",{T5Tokenizer,DistilBertTokenizer,DebertaTokenizer,DebertaV2Tokenizer,BertTokenizer,MobileBertTokenizer,SqueezeBertTokenizer,AlbertTokenizer,GPT2Tokenizer,BartTokenizer,RobertaTokenizer,WhisperTokenizer,CodeGenTokenizer,CLIPTokenizer,MarianTokenizer,BloomTokenizer,NllbTokenizer,M2M100Tokenizer,LlamaTokenizer,XLMRobertaTokenizer,MPNetTokenizer,FalconTokenizer,GPTNeoXTokenizer,Wav2Vec2CTCTokenizer,PreTrainedTokenizer});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:o=null,config:u=null,cache_dir:c=null,local_files_only:p=!1,revision:a="main"}={}){let h=u??await loadConfig(n,{progress_callback:o,config:u,cache_dir:c,local_files_only:p,revision:a});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,o){for(let u of o)this.processors.forEach(c=>c(n,u))}[Symbol.iterator](){return this.processors.values()}}class LogitsProcessor extends Callable{_call(n,o){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,o){let u=this.force_token_map[n.length];return exists(u)&&(o.data.fill(-1/0),o.data[u]=0),o}}class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.bos_token_id=n}_call(n,o){return n.length===1&&(o.data.fill(-1/0),o.data[this.bos_token_id]=0),o}}class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.max_length=n,this.forced_eos_token_id=o}_call(n,o){}}class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.begin_suppress_tokens=n,this.begin_index=o}_call(n,o){if(n.length===this.begin_index)for(let u of this.begin_suppress_tokens)o.data[u]=-1/0;return o}}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,o){if(o.data[this.no_timestamps_token_id]=-1/0,n.length===this.begin_index-1)return o.data.fill(-1/0),o.data[this.timestamp_begin]=0,o;const u=n.slice(this.begin_index),c=u.length>=1&&u[u.length-1]>=this.timestamp_begin,p=u.length<2||u[u.length-2]>=this.timestamp_begin;if(c&&(p?o.data.subarray(this.timestamp_begin).fill(-1/0):o.data.subarray(0,this.eos_token_id).fill(-1/0)),n.length===this.begin_index&&this.max_initial_timestamp_index!==null){const l=this.timestamp_begin+this.max_initial_timestamp_index;o.data.subarray(l+1).fill(-1/0)}const a=log_softmax(o.data),h=Math.log(a.subarray(this.timestamp_begin).map(Math.exp).reduce((l,s)=>l+s)),f=max(a.subarray(0,this.timestamp_begin))[0];return h>f&&o.data.subarray(0,this.timestamp_begin).fill(-1/0),o}}class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.no_repeat_ngram_size=n}getNgrams(n){const o=n.length,u=[];for(let p=0;p0&&(c=c.map(p=>p/this.generation_config.temperature)),c}randomSelect(n){let o=n.reduce((c,p)=>c+p,0),u=Math.random()*o;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 ${n.num_return_sequences}.`);return new GreedySampler(n)}}class GreedySampler extends Sampler{sample(n,o=-1){let u=this.getLogits(n,o);return[[max(u)[1],0]]}}class MultinomialSampler extends Sampler{sample(n,o=-1){let u=n.dims.at(-1);this.generation_config.top_k>0&&(u=Math.min(this.generation_config.top_k,u));const c=this.getLogits(n,o),p=getTopItems(c,u),a=softmax(p.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},()=>{const h=this.randomSelect(a);return[p[h][0],Math.log(a[h])]})}}class BeamSearchSampler extends Sampler{sample(n,o=-1){let u=n.dims.at(-1);this.generation_config.top_k>0&&(u=Math.min(this.generation_config.top_k,u));const c=this.getLogits(n,o),p=getTopItems(c,u),a=softmax(p.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},(h,f)=>[p[f][0],Math.log(a[f])])}}const{InferenceSession,Tensor:ONNXTensor}=ONNX;class ModelType{}class EncoderOnlyModelType extends ModelType{}class EncoderDecoderModelType extends ModelType{}class Seq2SeqModelType extends EncoderDecoderModelType{}class DecoderOnlyModelType extends ModelType{}const MODEL_TYPE_MAPPING=new Map([["CLIPTextModelWithProjection",EncoderOnlyModelType],["CLIPVisionModelWithProjection",EncoderOnlyModelType]]);async function forward(b,n){return MODEL_TYPE_MAPPING.get(b.constructor.name)===DecoderOnlyModelType?await decoderForward(b,n):await encoderForward(b,n)}async function constructSession(b,n,o){let u=`onnx/${n}${o.quantized?"_quantized":""}.onnx`,c=await getModelFile(b,u,!0,o);try{return await InferenceSession.create(c,{executionProviders})}catch(p){if(executionProviders.length===1&&executionProviders[0]==="wasm")throw p;return console.warn(p),console.warn("Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback. "),await InferenceSession.create(c,{executionProviders:["wasm"]})}}async function validateInputs(b,n){const o={},u=[];for(let a of b.inputNames)n[a]===void 0?u.push(a):o[a]=n[a];if(u.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${u.join(", ")}.`);const c=Object.keys(n).length,p=b.inputNames.length;if(c>p){let a=Object.keys(n).filter(h=>!b.inputNames.includes(h));console.warn(`WARNING: Too many inputs were provided (${c} > ${p}). The following inputs will be ignored: "${a.join(", ")}".`)}return o}async function sessionRun(b,n){const o=await validateInputs(b,n);try{let u=await b.run(o);return u=replaceTensors(u),u}catch(u){throw console.error(`An error occurred during model execution: "${u}".`),console.error("Inputs given to model:",o),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 o=b.config.pad_token_id??null,u=b.config.eos_token_id??null;isIntegralNumber(u)&&(u=[u]);let c=n.indexOf(o)!==-1,p=u===null||!u.includes(o);if(c&&p){let a=BigInt64Array.from(n.data.map(h=>h!=o));return new Tensor("int64",a,n.dims)}else return new Tensor("int64",new BigInt64Array(n.data.length).fill(1n),n.dims)}function boolTensor(b){return new Tensor("bool",[b],[1])}async function seq2seqForward(b,n,{add_decoder_pkv:o=!0}={}){let{encoder_outputs:u,past_key_values:c}=n;u||(u=(await encoderForward(b,n)).last_hidden_state);let p={input_ids:n.decoder_input_ids,encoder_hidden_states:u,use_cache_branch:boolTensor(!!c)};b.decoder_merged_session.inputNames.includes("encoder_attention_mask")&&(p.encoder_attention_mask=n.attention_mask),b.addPastKeyValues(p,c,o);const a=await sessionRun(b.decoder_merged_session,p);let h=a.logits;c=b.getPastKeyValues(a,c);const f=b.getAttentions(a);return new Seq2SeqLMOutput({logits:h,past_key_values:c,encoder_outputs:u,...f})}function seq2seqStartBeams(b,n,o,u=!0){let c=[],p=0,a=b.config.decoder_start_token_id;Array.isArray(a)||(a=[a]);for(let h of n){h.dims=[1,...h.dims];let f={inputs:h,encoder_outputs:null,prev_model_outputs:null,output_token_ids:a,done:!1,score:0,id:p++};u&&(f.attention_mask=prepareAttentionMask(b,h)),c.push(f)}return c}async function seq2seqRunBeam(b,n,{input_name:o="input_ids"}={}){var p;let u={[o]:n.inputs,decoder_input_ids:toI64Tensor(n.output_token_ids.slice(-1)),encoder_outputs:n.encoder_outputs,past_key_values:(p=n.prev_model_outputs)==null?void 0:p.past_key_values};n.attention_mask&&(u.attention_mask=n.attention_mask);let c=await b.forward(u);return n.prev_model_outputs=c,n.encoder_outputs=c.encoder_outputs,c}async function encoderForward(b,n){let o={};for(let u of b.session.inputNames)o[u]=n[u];return await sessionRun(b.session,o)}async function decoderForward(b,n){let{input_ids:o,past_key_values:u,attention_mask:c}=n,p={input_ids:o,attention_mask:c??prepareAttentionMask(b,o),use_cache_branch:boolTensor(u!==null)};b.addPastKeyValues(p,u);let a=await sessionRun(b.session,p),h=a.logits;return u=b.getPastKeyValues(a,u),{logits:h,past_key_values:u}}function decoderStartBeams(b,n,o,u){let c=[],p=0;for(let a of n){let h=a.tolist().map(Number);a.dims=[1,...a.dims];let f;u?(f=u[p],f.dims=[1,...f.dims]):f=prepareAttentionMask(b,a);let l={input:a,model_input_ids:a,attention_mask:f,prev_model_outputs:null,output_token_ids:h,num_output_tokens:o,done:!1,score:0,id:p++};c.push(l)}return c}async function decoderRunBeam(b,n){var p;let o=new BigInt64Array(n.output_token_ids.length).fill(1n),u={input_ids:n.model_input_ids,attention_mask:new Tensor("int64",o,[1,o.length]),past_key_values:(p=n.prev_model_outputs)==null?void 0:p.past_key_values},c=await b.forward(u);return n.prev_model_outputs=c,c}function decoderUpdatebeam(b,n){b.output_token_ids=[...b.output_token_ids,n],b.model_input_ids=new Tensor("int64",[BigInt(n)],[1,1])}class PreTrainedModel extends Callable{constructor(n,o){super(),this.config=n,this.session=o}async dispose(){let n=[];for(let o of Object.keys(this)){let u=this[o];u instanceof InferenceSession&&n.push(u.handler.dispose())}return await Promise.all(n)}static async from_pretrained(n,{quantized:o=!0,progress_callback:u=null,config:c=null,cache_dir:p=null,local_files_only:a=!1,revision:h="main",model_file_name:f=null}={}){let l={quantized:o,progress_callback:u,config:c,cache_dir:p,local_files_only:a,revision:h,model_file_name:f},s=MODEL_TYPE_MAPPING.get(this.name),t;return s===DecoderOnlyModelType?t=await Promise.all([AutoConfig.from_pretrained(n,l),constructSession(n,l.model_file_name??"decoder_model_merged",l)]):s===Seq2SeqModelType?t=await Promise.all([AutoConfig.from_pretrained(n,l),constructSession(n,"encoder_model",l),constructSession(n,"decoder_model_merged",l),getModelJSON(n,"generation_config.json",!1,l)]):s===EncoderDecoderModelType?t=await Promise.all([AutoConfig.from_pretrained(n,l),constructSession(n,"encoder_model",l),constructSession(n,"decoder_model_merged",l)]):(s!==EncoderOnlyModelType&&console.warn(`Model type for ${this.name} not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`),t=await Promise.all([AutoConfig.from_pretrained(n,l),constructSession(n,l.model_file_name??"model",l)])),new this(...t)}async _call(n){return await this.forward(n)}async forward(n){return await forward(this,n)}_get_logits_processor(n,o,u=null){const c=new LogitsProcessorList;if(n.repetition_penalty!==null&&n.repetition_penalty!==1&&c.push(new RepetitionPenaltyLogitsProcessor(n.repetition_penalty)),n.no_repeat_ngram_size!==null&&n.no_repeat_ngram_size>0&&c.push(new NoRepeatNGramLogitsProcessor(n.no_repeat_ngram_size)),n.forced_bos_token_id!==null&&c.push(new ForcedBOSTokenLogitsProcessor(n.forced_bos_token_id)),n.forced_eos_token_id!==null&&c.push(new ForcedEOSTokenLogitsProcessor(n.max_length,n.forced_eos_token_id)),n.begin_suppress_tokens!==null){let p=o>1||n.forced_bos_token_id===null?o:o+1;n.forced_decoder_ids!==null&&(p+=n.forced_decoder_ids[n.forced_decoder_ids.length-1][0]),c.push(new SuppressTokensAtBeginLogitsProcessor(n.begin_suppress_tokens,p))}return n.forced_decoder_ids!==null&&c.push(new ForceTokensLogitsProcessor(n.forced_decoder_ids)),u!==null&&c.extend(u),c}_get_generation_config(n){let o=new GenerationConfig;return"generation_config"in this&&Object.assign(o,this.generation_config),n!==null&&Object.assign(o,n),o}async generate(n,o=null,u=null,{inputs_attention_mask:c=null}={}){if(!(n instanceof Tensor)&&!isTypedArray(n)&&!Array.isArray(n))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${n.constructor.name}".`);let p;if(this.config.is_encoder_decoder)p=0;else if(p=n instanceof Tensor?n.dims[0]:n.length,p===0)throw Error("Must supply a non-empty array of input token ids.");o=this._get_generation_config(o),u=u??new LogitsProcessorList,u=this._get_logits_processor(o,p,u);let a=1;const h=a+(o.max_new_tokens??1/0),f=Number.isInteger(o.max_length)&&(o.max_new_tokens??null)===null;let l=Sampler.getSampler(o),s=this.getStartBeams(n,a,c);for(;s.some(i=>!i.done)&&a=o.max_length){d.done=!0,i.push(d);continue}let g=await this.runBeam(d);o.output_attentions&&this.addAttentionsToBeam(d,g),o.output_scores;let m=g.logits.slice(null,-1,null);u(d.output_token_ids,m);let _=l(m);for(let[y,w]of _){let v={...d};this.updateBeam(v,y),v.score+=w,y===this.config.eos_token_id&&(v.done=!0),i.push(v)}}++a,i=this.groupBeams(i).map(d=>d.sort((g,m)=>m.score-g.score).slice(0,o.num_beams)),s=i.flat(),o.callback_function&&o.callback_function(s)}const t=this.groupBeams(s),e=i=>t.map(d=>o.num_return_sequences>1?d.slice(0,o.num_return_sequences).map(g=>g[i]):[d[0][i]]).flat(),r=e("output_token_ids");if(o.return_dict_in_generate){const i=e("decoder_attentions"),d=e("cross_attentions");return{sequences:r,decoder_attentions:i,cross_attentions:d}}else return r}addAttentionsToBeam(n,o){if(this.config.is_encoder_decoder){if(!o.cross_attentions||o.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(o.cross_attentions)}if(!o.decoder_attentions||o.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(o.decoder_attentions)}groupBeams(n){const o=Object.create(null);for(const u of n)o[u.id]===void 0?o[u.id]=[u]:o[u.id].push(u);return Object.values(o)}getPastKeyValues(n,o){const u=Object.create(null);for(const c in n)if(c.startsWith("present")){let p=c.replace("present","past_key_values");o&&c.includes("encoder")?u[p]=o[p]:u[p]=n[c]}return u}getAttentions(n){const o=Object.create(null);for(const u of["cross_attentions","decoder_attentions"]){const c=[];for(const p in n)if(p.startsWith(u)){const a=p.split(".").pop();c[a]=n[p]}o[u]=c}return o}addPastKeyValues(n,o,u=!1){if(o)Object.assign(n,o);else if(u){let c=[1,this.num_encoder_heads,0,this.encoder_dim_kv];for(let a=0;a{let s=Array.from({length:this.config.decoder_layers},(g,m)=>cat(l.map(_=>_[m]),2)),t=stack(o.map(([g,m])=>u?s[g].slice(null,m,null,[0,u]):s[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;g{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 o=(await b.metadata()).channels;let{data:u,info:c}=await b.raw().toBuffer({resolveWithObject:!0});const p=new RawImage(new Uint8ClampedArray(u),c.width,c.height,c.channels);return o!==void 0&&o!==c.channels&&p.convert(o),p};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"};class RawImage{constructor(n,o,u,c){ve(this,"_CONTENT_TYPE_MAP",{png:"image/png",jpg:"image/jpeg",jpeg:"image/jpeg",gif:"image/gif"});this._update(n,o,u,c)}static async read(n){if(n instanceof RawImage)return n;if(isString(n)||n instanceof URL)return await this.fromURL(n);throw new Error(`Unsupported input type: ${typeof n}`)}static async fromURL(n){let o=await getFile(n);if(o.status!==200)throw new Error(`Unable to read image from "${n}" (${o.status} ${o.statusText})`);let u=await o.blob();return this.fromBlob(u)}static async fromBlob(n){if(BROWSER_ENV){let o=await loadImageFunction(n);const u=createCanvasFunction(o.width,o.height).getContext("2d");return u.drawImage(o,0,0),new this(u.getImageData(0,0,o.width,o.height).data,o.width,o.height,4)}else{let o=sharp(await n.arrayBuffer());return await loadImageFunction(o)}}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 o=0,u=0;o=0?f=u:s=-u,c>=0?l=c:t=-c,h.drawImage(a,f,l,n,o,s,t,n,o),new RawImage(h.getImageData(0,0,n,o).data,n,o,4).convert(p)}else{let p=this.toSharp();if(u>=0&&c>=0)p=p.extract({left:Math.floor(u),top:Math.floor(c),width:n,height:o});else if(u<=0&&c<=0){let a=Math.floor(-c),h=Math.floor(-u);p=p.extend({top:a,left:h,right:n-this.width-h,bottom:o-this.height-a})}else{let a=[0,0],h=0;c<0?(a[0]=Math.floor(-c),a[1]=o-this.height-a[0]):h=Math.floor(c);let f=[0,0],l=0;u<0?(f[0]=Math.floor(-u),f[1]=n-this.width-f[0]):l=Math.floor(u),p=p.extend({top:a[0],bottom:a[1],left:f[0],right:f[1]}).extract({left:l,top:h,width:n,height:o})}return await loadImageFunction(p)}}toCanvas(){if(!BROWSER_ENV)throw new Error("toCanvas() is only supported in browser environments.");let n=this.clone().rgba(),o=createCanvasFunction(n.width,n.height),u=new ImageDataClass(n.data,n.width,n.height);return o.getContext("2d").putImageData(u,0,0),o}_update(n,o,u,c=null){return this.data=n,this.width=o,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}save(n){if(BROWSER_ENV){const o=n.split(".").pop().toLowerCase(),u=this._CONTENT_TYPE_MAP[o]??"image/png",p=this.toCanvas().toDataURL(u),a=document.createElement("a");a.href=p,a.download=n,a.click(),a.remove()}else if(env.useFS)this.toSharp().toFile(n);else 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}})}}async function read_audio(b,n){if(typeof AudioContext>"u")throw Error("Unable to load audio from path/URL since `AudioContext` is not available in your environment. Instead, audio data should be passed directly to the pipeline/processor. For more information and some example code, see https://huggingface.co/docs/transformers.js/guides/node-audio-processing.");const o=await(await getFile(b)).arrayBuffer(),u=new AudioContext({sampleRate:n});typeof n>"u"&&console.warn(`No sampling rate provided, using default of ${u.sampleRate}Hz.`);const c=await u.decodeAudioData(o);let p;if(c.numberOfChannels===2){const a=Math.sqrt(2);let h=c.getChannelData(0),f=c.getChannelData(1);p=new Float32Array(h.length);for(let l=0;l=i?e[_]=r*Math.exp(d*(y-i)):e[_]=s+t*y,g[_]=p.map(w=>e[_]-w)}const m=e.slice(1).map((_,y)=>1/(_-e[y]));for(let _=0;_this.preprocess(c)));return o.forEach(c=>c.pixel_values.dims=[1,...c.pixel_values.dims]),{pixel_values:cat(o.map(c=>c.pixel_values)),original_sizes:o.map(c=>c.original_size),reshaped_input_sizes:o.map(c=>c.reshaped_input_size)}}}class ViTFeatureExtractor extends ImageFeatureExtractor{}class MobileViTFeatureExtractor extends ImageFeatureExtractor{}class DetrFeatureExtractor extends ImageFeatureExtractor{async _call(n){let o=await super._call(n),u=[o.pixel_values.dims[0],64,64];return o.pixel_mask=new Tensor("int64",new BigInt64Array(u.reduce((c,p)=>c*p)).fill(1n),u),o}center_to_corners_format([n,o,u,c]){return[n-u/2,o-c/2,n+u/2,o+c/2]}post_process_object_detection(n,o=.5,u=null){const c=n.logits,p=n.pred_boxes,[a,h,f]=c.dims;if(u!==null&&u.length!==a)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let l=[];for(let s=0;so){let w=i[d].data;w=this.center_to_corners_format(w),t!==null&&(w=w.map((v,S)=>v*t[(S+1)%2])),e.boxes.push(w),e.classes.push(m),e.scores.push(y)}}l.push(e)}return l}remove_low_and_no_objects(n,o,u,c){let p=[],a=[],h=[];for(let f=0;fu&&(p.push(s),a.push(r),h.push(t))}return[p,a,h]}check_segment_validity(n,o,u,c=.5,p=.8){let a=[],h=0,f=0;for(let s=0;s=c&&++f;let l=h>0&&f>0;return l&&(l=h/f>p),[l,a]}compute_segments(n,o,u,c,p,a=null,h=null){let[f,l]=h??n[0].dims,s=new Tensor("int32",new Int32Array(f*l),[f,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;dBigInt(Math.round(f)))),a);return{pixel_values:u,original_sizes:c,reshaped_input_sizes:p,input_points:h}}post_process_masks(n,o,u,{mask_threshold:c=0,binarize:p=!0,pad_size:a=null}={}){let h=[];a=a??this.pad_size;let f=[a.height,a.width];for(let l=0;l_>c),m.dims)),m.dims=[1,...m.dims],r.push(m)}let i=cat(r);h.push(i)}return h}}class WhisperFeatureExtractor extends FeatureExtractor{constructor(n){var o;super(n),(o=this.config).mel_filters??(o.mel_filters=getMelFilters(this.config.sampling_rate,this.config.n_fft,this.config.feature_size))}calcOffset(n,o){return Math.abs((n+o)%(2*o)-o)}padReflect(n,o,u){const c=new Float32Array(n.length+o+u),p=n.length-1;for(let a=0;a>1;++v){const S=(v+1-u)**2/2,A=Math.sqrt(m**2+_**2)**S,O=S*Math.atan2(_,m);let x=2*v;l[x]=A*Math.cos(O),l[x+1]=A*Math.sin(O),s[x]=l[x],s[x+1]=-l[x+1]}const y=l.subarray(c,p),w=new FFT(a>>1);w.transform(r,s);for(let v=0;v>1,N=S[I]*o[I];t[O]=N*y[O],t[x]=N*y[x]}w.transform(i,t);for(let O=0;Oc?a-c:0,l=a>1,l=new Float32Array(h*f);for(let m=0;mthis.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`.");let o=n.slice(0,this.config.n_samples),u=this._extract_fbank_features(o);return{input_features:new Tensor("float32",u.data,[1,...u.dims])}}}class Wav2Vec2FeatureExtractor extends FeatureExtractor{_zero_mean_unit_var_norm(n){const u=n.reduce((p,a)=>p+a,0)/n.length,c=n.reduce((p,a)=>p+(a-u)**2,0)/n.length;return n.map(p=>(p-u)/Math.sqrt(c+1e-7))}async _call(n){var c;if(!(n instanceof Float32Array||n instanceof Float64Array))throw new Error(`Wav2Vec2FeatureExtractor expects input to be a Float32Array or a Float64Array, but got ${((c=n==null?void 0:n.constructor)==null?void 0:c.name)??typeof n} 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.`);n instanceof Float64Array&&(n=new Float32Array(n));let o=n;this.config.do_normalize&&(o=this._zero_mean_unit_var_norm(o));const u=[1,o.length];return{input_values:new Tensor("float32",o,u),attention_mask:new Tensor("int64",new BigInt64Array(o.length).fill(1n),u)}}}class Processor extends Callable{constructor(n){super(),this.feature_extractor=n}async _call(n){return await this.feature_extractor(n)}}class SamProcessor extends Processor{async _call(n,o){return await this.feature_extractor(n,o)}post_process_masks(...n){return this.feature_extractor.post_process_masks(...n)}}class WhisperProcessor extends Processor{async _call(n){return await this.feature_extractor(n)}}class Wav2Vec2ProcessorWithLM extends Processor{async _call(n){return await this.feature_extractor(n)}}class AutoProcessor{static async from_pretrained(n,{progress_callback:o=null,config:u=null,cache_dir:c=null,local_files_only:p=!1,revision:a="main"}={}){let h=u??await getModelJSON(n,"preprocessor_config.json",!0,{progress_callback:o,config:u,cache_dir:c,local_files_only:p,revision:a}),f=h.feature_extractor_type??h.image_processor_type,l=this.FEATURE_EXTRACTOR_CLASS_MAPPING[f];if(!l)if(h.size!==void 0)console.warn("Feature extractor type not specified, assuming ImageFeatureExtractor due to size parameter in config."),l=ImageFeatureExtractor;else throw new Error(`Unknown Feature Extractor type: ${h.feature_extractor_type}`);let s=this.PROCESSOR_CLASS_MAPPING[h.processor_class]??Processor,t=new l(h);return new s(t)}}ve(AutoProcessor,"FEATURE_EXTRACTOR_CLASS_MAPPING",{WhisperFeatureExtractor,ViTFeatureExtractor,MobileViTFeatureExtractor,DetrFeatureExtractor,SamImageProcessor,Wav2Vec2FeatureExtractor}),ve(AutoProcessor,"PROCESSOR_CLASS_MAPPING",{WhisperProcessor,Wav2Vec2ProcessorWithLM,SamProcessor});async function prepareImages(b){return Array.isArray(b)||(b=[b]),b=await Promise.all(b.map(n=>RawImage.read(n))),b}class Pipeline extends Callable{constructor({task:n,model:o,tokenizer:u=null,processor:c=null}){super(),this.task=n,this.model=o,this.tokenizer=u,this.processor=c}async dispose(){await this.model.dispose()}async _call(n){let o=this.tokenizer(n,{padding:!0,truncation:!0}),u=await this.model(o);return[o,u]}}class TextClassificationPipeline extends Pipeline{async _call(n,{topk:o=1}={}){let u=this.model.config.problem_type==="multi_label_classification"?f=>f.sigmoid().data:f=>softmax(f.data),[c,p]=await super._call(n),a=this.model.config.id2label,h=[];for(let f of p.logits){let l=u(f),t=getTopItems(l,o).map(function(e){return{label:a[e[0]],score:e[1]}});o===1?h.push(...t):h.push(t)}return Array.isArray(n)||o===1?h:h[0]}}class TokenClassificationPipeline extends Pipeline{async _call(n,{ignore_labels:o=["O"]}={}){let u=Array.isArray(n);u||(n=[n]);let c=this.tokenizer,[p,a]=await super._call(n),h=a.logits,f=this.model.config.id2label,l=[];for(let s=0;s[r,i]).filter(r=>r[1]>l),t=Array.from(softmax(p.end_logits[h].data)).map((r,i)=>[r,i]).filter(r=>r[1]>l),e=product(s,t).filter(r=>r[0][1]<=r[1][1]).map(r=>[r[0][1],r[1][1],r[0][0]*r[1][0]]).sort((r,i)=>i[2]-r[2]);for(let r=0;r{let i=[...f];return i[l]=r[0],{score:r[1],token:r[0],token_str:p.model.vocab[r[0]],sequence:p.decode(i,{skip_special_tokens:!0})}}))}return Array.isArray(n)?a:a[0]}}class Text2TextGenerationPipeline extends Pipeline{constructor(){super(...arguments);ve(this,"_key",null)}async _call(o,u={}){Array.isArray(o)||(o=[o]),this.model.config.prefix&&(o=o.map(l=>this.model.config.prefix+l));let c=this.model.config.task_specific_params;c&&c[this.task]&&c[this.task].prefix&&(o=o.map(l=>c[this.task].prefix+l));let p={padding:!0,truncation:!0},a;this instanceof TranslationPipeline&&"_build_translation_inputs"in this.tokenizer?a=this.tokenizer._build_translation_inputs(o,p,u).input_ids:a=this.tokenizer(o,p).input_ids;let h=await this.model.generate(a,u),f=this.tokenizer.batch_decode(h,{skip_special_tokens:!0});return this._key!==null&&(f=f.map(l=>this._key===null?l:{[this._key]:l})),f}}class SummarizationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);ve(this,"_key","summary_text")}}class TranslationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);ve(this,"_key","translation_text")}}class TextGenerationPipeline extends Pipeline{async _call(n,o={}){let u=typeof n=="string"||n instanceof String;u&&(n=[n]),this.tokenizer.padding_side="left";let c=this.tokenizer(n,{padding:!0,truncation:!0}),p=c.input_ids,a=c.attention_mask,h=await this.model.generate(p,o,null,{inputs_attention_mask:a});const f=this.tokenizer.batch_decode(h,{skip_special_tokens:!0}),l=Array.from({length:n.length},s=>[]);for(let s=0;s[o.toLowerCase(),u])),this.entailment_id=this.label2id.entailment,this.entailment_id===void 0&&(console.warn("Could not find 'entailment' in label2id mapping. Using 2 as entailment_id."),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,this.contradiction_id===void 0&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(n,o,{hypothesis_template:u="This example is {}.",multi_label:c=!1}={}){let p=Array.isArray(n);p||(n=[n]),Array.isArray(o)||(o=[o]);let a=o.map(l=>u.replace("{}",l)),h=c||o.length===1,f=[];for(let l of n){let s=[];for(let r of a){let i=this.tokenizer(l,{text_pair:r,padding:!0,truncation:!0}),d=await this.model(i);h?s.push([d.logits.data[this.contradiction_id],d.logits.data[this.entailment_id]]):s.push(d.logits.data[this.entailment_id])}let t;h?t=s.map(r=>softmax(r)[1]):t=softmax(s);let e=t.map((r,i)=>[r,i]).sort((r,i)=>i[0]-r[0]);f.push({sequence:l,labels:e.map(r=>o[r[1]]),scores:e.map(r=>r[0])})}return p?f:f[0]}}class FeatureExtractionPipeline extends Pipeline{async _call(n,{pooling:o="none",normalize:u=!1}={}){let[c,p]=await super._call(n),a=p.last_hidden_state??p.logits;if(o!=="none")if(o==="mean")a=mean_pooling(a,c.attention_mask);else throw Error(`Pooling method '${o}' not supported.`);return u&&(a=a.normalize(2,-1)),a}}class AudioClassificationPipeline extends Pipeline{constructor(n){super(n)}async _preprocess(n,o){return isString(n)&&(n=await read_audio(n,o)),n}async _call(n,{topk:o=5}={}){let u=!Array.isArray(n);u&&(n=[n]);const c=this.model.config.id2label,p=this.processor.feature_extractor.config.sampling_rate;let a=[];for(let h of n){h=await this._preprocess(h,p);const f=await this.processor(h),s=(await this.model(f)).logits[0];let e=getTopItems(softmax(s.data),o).map(function(r){return{label:c[r[0]],score:r[1]}});o===1?a.push(...e):a.push(e)}return!u||o===1?a:a[0]}}class AutomaticSpeechRecognitionPipeline extends Pipeline{constructor(n){super(n)}async _preprocess(n,o){return isString(n)&&(n=await read_audio(n,o)),n}async _call(n,o={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(n,o);case"wav2vec2":return this._call_wav2vec2(n,o);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(n,o={}){o.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),o.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');let u=!Array.isArray(n);u&&(n=[n]);const c=this.processor.feature_extractor.config.sampling_rate;let p=[];for(let a of n){a=await this._preprocess(a,c);const h=await this.processor(a),l=(await this.model(h)).logits[0],s=[];for(let e of l)s.push(max(e.data)[1]);const t=this.tokenizer.decode(s);p.push({text:t})}return u?p[0]:p}async _call_whisper(n,o={}){let u=o.return_timestamps??!1,c=o.chunk_length_s??0,p=o.stride_length_s??null,a=o.chunk_callback??null,h=o.force_full_sequences??!1;u==="word"&&(o.return_token_timestamps=!0);let f=pop(o,"language",null),l=pop(o,"task",null);if(f||l||u){if(o.forced_decoder_ids)throw new Error("Cannot specify `language`/`task`/`return_timestamps` and `forced_decoder_ids` at the same time.");let d=this.tokenizer.get_decoder_prompt_ids({language:f,task:l,no_timestamps:!u});d.length>0&&(o.forced_decoder_ids=d)}let s=!Array.isArray(n);s&&(n=[n]);const t=this.processor.feature_extractor.config.sampling_rate,e=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,r=this.processor.feature_extractor.config.hop_length;let i=[];for(let d of n){d=await this._preprocess(d,t);let g=[];if(c>0){if(p===null)p=c/6;else if(c<=p)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const y=t*c,w=t*p,v=y-2*w;let S=0;for(;S=d.length;g.push({stride:[A.length,x?0:w,I?0:w],input_features:O.input_features,is_last:I}),S+=v}}else g=[{stride:[d.length,0,0],input_features:(await this.processor(d)).input_features,is_last:!0}];for(let y of g){o.num_frames=Math.floor(y.stride[0]/r);let w=await this.model.generate(y.input_features,o);u==="word"?(y.tokens=w.sequences[0],y.token_timestamps=w.token_timestamps.tolist()[0].map(v=>round(v,2))):y.tokens=w[0],y.stride=y.stride.map(v=>v/t),a!==null&&a(y)}let[m,_]=this.tokenizer._decode_asr(g,{time_precision:e,return_timestamps:u,force_full_sequences:h});i.push({text:m,..._})}return s?i[0]:i}}class ImageToTextPipeline extends Pipeline{constructor(n){super(n)}async _call(n,o={}){let u=Array.isArray(n);n=await prepareImages(n);let{pixel_values:c}=await this.processor(n),p=[];for(let a of c){a.dims=[1,...a.dims];let h=await this.model.generate(a,o),f=this.tokenizer.batch_decode(h,{skip_special_tokens:!0}).map(l=>({generated_text:l.trim()}));p.push(f)}return u?p:p[0]}}class ImageClassificationPipeline extends Pipeline{constructor(n){super(n)}async _call(n,{topk:o=1}={}){let u=Array.isArray(n);n=await prepareImages(n);let{pixel_values:c}=await this.processor(n),p=await this.model({pixel_values:c}),a=this.model.config.id2label,h=[];for(let f of p.logits){let s=getTopItems(softmax(f.data),o).map(function(t){return{label:a[t[0]],score:t[1]}});o===1?h.push(...s):h.push(s)}return u||o===1?h:h[0]}}class ImageSegmentationPipeline extends Pipeline{constructor(n){super(n),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(n,{threshold:o=.5,mask_threshold:u=.5,overlap_mask_area_threshold:c=.8,label_ids_to_fuse:p=null,target_sizes:a=null,subtask:h=null}={}){if(Array.isArray(n)&&n.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");n=await prepareImages(n);let l=n.map(d=>[d.height,d.width]),{pixel_values:s,pixel_mask:t}=await this.processor(n),e=await this.model({pixel_values:s,pixel_mask:t}),r=null;if(h!==null)r=this.subtasks_mapping[h];else for(let[d,g]of Object.entries(this.subtasks_mapping))if(g in this.processor.feature_extractor){r=this.processor.feature_extractor[g].bind(this.processor.feature_extractor),h=d;break}let i=[];if(h==="panoptic"||h==="instance"){let d=r(e,o,u,c,p,a??l)[0],g=d.segmentation,m=this.model.config.id2label;for(let _ of d.segments_info){let y=new Uint8ClampedArray(g.data.length);for(let v=0;vu.replace("{}",s)),a=this.tokenizer(p,{padding:!0,truncation:!0}),{pixel_values:h}=await this.processor(n),f=await this.model({...a,pixel_values:h}),l=[];for(let s of f.logits_per_image){let t=softmax(s.data);l.push([...t].map((e,r)=>({score:e,label:o[r]})))}return c?l:l[0]}}class ObjectDetectionPipeline extends Pipeline{constructor(n){super(n)}async _call(n,{threshold:o=.9,percentage:u=!1}={}){let c=Array.isArray(n);if(c&&n.length!==1)throw Error("Object detection pipeline currently only supports a batch size of 1.");n=await prepareImages(n);let p=u?null:n.map(e=>[e.height,e.width]),{pixel_values:a,pixel_mask:h}=await this.processor(n),f=await this.model({pixel_values:a,pixel_mask:h}),l=this.processor.feature_extractor.post_process_object_detection(f,o,p),s=this.model.config.id2label;const t=l.map(e=>e.boxes.map((r,i)=>({score:e.scores[i],label:s[e.classes[i]],box:this._get_bounding_box(r,!u)})));return c?t:t[0]}_get_bounding_box(n,o){o&&(n=n.map(h=>h|0));const[u,c,p,a]=n;return{xmin:u,ymin:c,xmax:p,ymax:a}}}const SUPPORTED_TASKS={"text-classification":{tokenizer:AutoTokenizer,pipeline:TextClassificationPipeline,model:AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:AutoTokenizer,pipeline:TokenClassificationPipeline,model:AutoModelForTokenClassification,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:AutoTokenizer,pipeline:QuestionAnsweringPipeline,model:AutoModelForQuestionAnswering,default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:AutoTokenizer,pipeline:FillMaskPipeline,model:AutoModelForMaskedLM,default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:AutoTokenizer,pipeline:SummarizationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:AutoTokenizer,pipeline:TranslationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:AutoTokenizer,pipeline:Text2TextGenerationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:AutoTokenizer,pipeline:TextGenerationPipeline,model:AutoModelForCausalLM,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotClassificationPipeline,model:AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:AudioClassificationPipeline,model:AutoModelForAudioClassification,processor:AutoProcessor,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"automatic-speech-recognition":{tokenizer:AutoTokenizer,pipeline:AutomaticSpeechRecognitionPipeline,model:[AutoModelForSeq2SeqLM,AutoModelForCTC],processor:AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"image-to-text":{tokenizer:AutoTokenizer,pipeline:ImageToTextPipeline,model:AutoModelForVision2Seq,processor:AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:ImageClassificationPipeline,model:AutoModelForImageClassification,processor:AutoProcessor,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:ImageSegmentationPipeline,model:AutoModelForImageSegmentation,processor:AutoProcessor,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotImageClassificationPipeline,model:AutoModel,processor:AutoProcessor,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:ObjectDetectionPipeline,model:AutoModelForObjectDetection,processor:AutoProcessor,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"feature-extraction":{tokenizer:AutoTokenizer,pipeline:FeatureExtractionPipeline,model:AutoModel,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"}},TASK_ALIASES={"sentiment-analysis":"text-classification",ner:"token-classification",vqa:"visual-question-answering",asr:"automatic-speech-recognition",embeddings:"feature-extraction"};async function pipeline(b,n=null,{quantized:o=!0,progress_callback:u=null,config:c=null,cache_dir:p=null,local_files_only:a=!1,revision:h="main"}={}){b=TASK_ALIASES[b]??b;let f=SUPPORTED_TASKS[b.split("_",1)[0]];if(!f)throw Error(`Unsupported pipeline: ${b}. Must be one of [${Object.keys(SUPPORTED_TASKS)}]`);n||(n=f.default.model,console.log(`No model specified. Using default model: "${n}".`));let l={quantized:o,progress_callback:u,config:c,cache_dir:p,local_files_only:a,revision:h};const s=new Map([["tokenizer",f.tokenizer],["model",f.model],["processor",f.processor]]);let t=await loadItems(s,n,l);t.task=b,dispatchCallback(u,{status:"ready",task:b,model:n});let e=f.pipeline;return new e(t)}async function loadItems(b,n,o){const u=Object.create(null),c=[];for(let[p,a]of b.entries()){if(!a)continue;let h;Array.isArray(a)?h=new Promise(async(f,l)=>{let s;for(let t of a)try{f(await t.from_pretrained(n,o));return}catch(e){s=e}l(s)}):h=a.from_pretrained(n,o),u[p]=h,c.push(h)}await Promise.all(c);for(let[p,a]of Object.entries(u))u[p]=await a;return u}env.allowLocalModels=!1;class PipelineFactory{constructor(n,o,u){this.tokenizer=n,this.model=o,this.quantized=u}static async getInstance(n=null){return this.instance===null&&(this.instance=pipeline(this.task,this.model,{quantized:this.quantized,progress_callback:n})),this.instance}}ve(PipelineFactory,"task",null),ve(PipelineFactory,"model",null),ve(PipelineFactory,"quantized",null),ve(PipelineFactory,"instance",null),self.addEventListener("message",async b=>{const n=b.data;let o=await transcribe(n.audio,n.model,n.multilingual,n.quantized,n.subtask,n.language);o!==null&&self.postMessage({status:"complete",task:"automatic-speech-recognition",data:o})});class AutomaticSpeechRecognitionPipelineFactory extends PipelineFactory{}ve(AutomaticSpeechRecognitionPipelineFactory,"task","automatic-speech-recognition"),ve(AutomaticSpeechRecognitionPipelineFactory,"model",null),ve(AutomaticSpeechRecognitionPipelineFactory,"quantized",null);const transcribe=async(b,n,o,u,c,p)=>{const a=`Xenova/whisper-${n}${o?"":".en"}`,h=AutomaticSpeechRecognitionPipelineFactory;(h.model!==a||h.quantized!==u)&&(h.model=a,h.quantized=u,h.instance!==null&&((await h.getInstance()).dispose(),h.instance=null));let f=await h.getInstance(i=>{self.postMessage(i)});const l=f.processor.feature_extractor.config.chunk_length/f.model.config.max_source_positions;let s=[{tokens:[],finalised:!1}];function t(i){let d=s[s.length-1];Object.assign(d,i),d.finalised=!0,i.is_last||s.push({tokens:[],finalised:!1})}function e(i){let d=s[s.length-1];d.tokens=[...i[0].output_token_ids];let g=f.tokenizer._decode_asr(s,{time_precision:l,return_timestamps:!0,force_full_sequences:!1});self.postMessage({status:"update",task:"automatic-speech-recognition",data:g})}return await f(b,{top_k:0,do_sample:!1,chunk_length_s:30,stride_length_s:5,language:p,task:c,return_timestamps:!0,force_full_sequences:!1,callback_function:e,chunk_callback:t}).catch(i=>(self.postMessage({status:"error",task:"automatic-speech-recognition",data:i}),null))}})();