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m=0;m>>0,e.ints[m].high>>>0).toNumber():e.ints[m];if(e.strings&&e.strings.length)for(i.strings=[],m=0;m>>3){case 1:d.name=e.string();break;case 2:d.type=s.onnx.TypeProto.decode(e,e.uint32());break;case 3:d.docString=e.string();break;default:e.skipType(7&m)}}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.name!=null&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(e.type!=null&&e.hasOwnProperty("type")){var r=s.onnx.TypeProto.verify(e.type);if(r)return"type."+r}return e.docString!=null&&e.hasOwnProperty("docString")&&!c.isString(e.docString)?"docString: string expected":null},t.fromObject=function(e){if(e instanceof s.onnx.ValueInfoProto)return e;var r=new s.onnx.ValueInfoProto;if(e.name!=null&&(r.name=String(e.name)),e.type!=null){if(typeof e.type!="object")throw TypeError(".onnx.ValueInfoProto.type: object expected");r.type=s.onnx.TypeProto.fromObject(e.type)}return e.docString!=null&&(r.docString=String(e.docString)),r},t.toObject=function(e,r){r||(r={});var i={};return r.defaults&&(i.name="",i.type=null,i.docString=""),e.name!=null&&e.hasOwnProperty("name")&&(i.name=e.name),e.type!=null&&e.hasOwnProperty("type")&&(i.type=s.onnx.TypeProto.toObject(e.type,r)),e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,u.util.toJSONOptions)},t}(),p.NodeProto=function(){function t(e){if(this.input=[],this.output=[],this.attribute=[],e)for(var r=Object.keys(e),i=0;i>>3){case 1:d.input&&d.input.length||(d.input=[]),d.input.push(e.string());break;case 2:d.output&&d.output.length||(d.output=[]),d.output.push(e.string());break;case 3:d.name=e.string();break;case 4:d.opType=e.string();break;case 7:d.domain=e.string();break;case 5:d.attribute&&d.attribute.length||(d.attribute=[]),d.attribute.push(s.onnx.AttributeProto.decode(e,e.uint32()));break;case 6:d.docString=e.string();break;default:e.skipType(7&m)}}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.input!=null&&e.hasOwnProperty("input")){if(!Array.isArray(e.input))return"input: array expected";for(var r=0;r>>3){case 1:d.irVersion=e.int64();break;case 8:d.opsetImport&&d.opsetImport.length||(d.opsetImport=[]),d.opsetImport.push(s.onnx.OperatorSetIdProto.decode(e,e.uint32()));break;case 2:d.producerName=e.string();break;case 3:d.producerVersion=e.string();break;case 4:d.domain=e.string();break;case 5:d.modelVersion=e.int64();break;case 6:d.docString=e.string();break;case 7:d.graph=s.onnx.GraphProto.decode(e,e.uint32());break;case 14:d.metadataProps&&d.metadataProps.length||(d.metadataProps=[]),d.metadataProps.push(s.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&m)}}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.irVersion!=null&&e.hasOwnProperty("irVersion")&&!(c.isInteger(e.irVersion)||e.irVersion&&c.isInteger(e.irVersion.low)&&c.isInteger(e.irVersion.high)))return"irVersion: integer|Long 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 expected");for(r.metadataProps=[],i=0;i>>0,e.irVersion.high>>>0).toNumber():e.irVersion),e.producerName!=null&&e.hasOwnProperty("producerName")&&(i.producerName=e.producerName),e.producerVersion!=null&&e.hasOwnProperty("producerVersion")&&(i.producerVersion=e.producerVersion),e.domain!=null&&e.hasOwnProperty("domain")&&(i.domain=e.domain),e.modelVersion!=null&&e.hasOwnProperty("modelVersion")&&(typeof e.modelVersion=="number"?i.modelVersion=r.longs===String?String(e.modelVersion):e.modelVersion:i.modelVersion=r.longs===String?c.Long.prototype.toString.call(e.modelVersion):r.longs===Number?new c.LongBits(e.modelVersion.low>>>0,e.modelVersion.high>>>0).toNumber():e.modelVersion),e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),e.graph!=null&&e.hasOwnProperty("graph")&&(i.graph=s.onnx.GraphProto.toObject(e.graph,r)),e.opsetImport&&e.opsetImport.length){i.opsetImport=[];for(var m=0;m>>3){case 1:d.key=e.string();break;case 2:d.value=e.string();break;default:e.skipType(7&m)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){return typeof e!="object"||e===null?"object expected":e.key!=null&&e.hasOwnProperty("key")&&!c.isString(e.key)?"key: string expected":e.value!=null&&e.hasOwnProperty("value")&&!c.isString(e.value)?"value: string expected":null},t.fromObject=function(e){if(e instanceof s.onnx.StringStringEntryProto)return e;var r=new s.onnx.StringStringEntryProto;return e.key!=null&&(r.key=String(e.key)),e.value!=null&&(r.value=String(e.value)),r},t.toObject=function(e,r){r||(r={});var i={};return r.defaults&&(i.key="",i.value=""),e.key!=null&&e.hasOwnProperty("key")&&(i.key=e.key),e.value!=null&&e.hasOwnProperty("value")&&(i.value=e.value),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,u.util.toJSONOptions)},t}(),p.TensorAnnotation=function(){function t(e){if(this.quantParameterTensorNames=[],e)for(var 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&m)}}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")&&!c.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 5:d.initializer&&d.initializer.length||(d.initializer=[]),d.initializer.push(s.onnx.TensorProto.decode(e,e.uint32()));break;case 10:d.docString=e.string();break;case 11:d.input&&d.input.length||(d.input=[]),d.input.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 12:d.output&&d.output.length||(d.output=[]),d.output.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 13:d.valueInfo&&d.valueInfo.length||(d.valueInfo=[]),d.valueInfo.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 14:d.quantizationAnnotation&&d.quantizationAnnotation.length||(d.quantizationAnnotation=[]),d.quantizationAnnotation.push(s.onnx.TensorAnnotation.decode(e,e.uint32()));break;default:e.skipType(7&m)}}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.node!=null&&e.hasOwnProperty("node")){if(!Array.isArray(e.node))return"node: array expected";for(var r=0;r>>3){case 1:if(d.dims&&d.dims.length||(d.dims=[]),(7&m)==2)for(var _=e.uint32()+e.pos;e.pos<_;)d.dims.push(e.int64());else d.dims.push(e.int64());break;case 2:d.dataType=e.int32();break;case 3:d.segment=s.onnx.TensorProto.Segment.decode(e,e.uint32());break;case 4:if(d.floatData&&d.floatData.length||(d.floatData=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.floatData.push(e.float());else d.floatData.push(e.float());break;case 5:if(d.int32Data&&d.int32Data.length||(d.int32Data=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.int32Data.push(e.int32());else d.int32Data.push(e.int32());break;case 6:d.stringData&&d.stringData.length||(d.stringData=[]),d.stringData.push(e.bytes());break;case 7:if(d.int64Data&&d.int64Data.length||(d.int64Data=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.int64Data.push(e.int64());else d.int64Data.push(e.int64());break;case 8:d.name=e.string();break;case 12:d.docString=e.string();break;case 9:d.rawData=e.bytes();break;case 13:d.externalData&&d.externalData.length||(d.externalData=[]),d.externalData.push(s.onnx.StringStringEntryProto.decode(e,e.uint32()));break;case 14:d.dataLocation=e.int32();break;case 10:if(d.doubleData&&d.doubleData.length||(d.doubleData=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.doubleData.push(e.double());else d.doubleData.push(e.double());break;case 11:if(d.uint64Data&&d.uint64Data.length||(d.uint64Data=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.uint64Data.push(e.uint64());else d.uint64Data.push(e.uint64());break;default:e.skipType(7&m)}}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.dims!=null&&e.hasOwnProperty("dims")){if(!Array.isArray(e.dims))return"dims: array expected";for(var r=0;r>>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"?c.base64.decode(e.rawData,r.rawData=c.newBuffer(c.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=c.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?c.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:m.begin=r.int64();break;case 2:m.end=r.int64();break;default:r.skipType(7&_)}}return m},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")&&!(c.isInteger(r.begin)||r.begin&&c.isInteger(r.begin.low)&&c.isInteger(r.begin.high))?"begin: integer|Long expected":r.end!=null&&r.hasOwnProperty("end")&&!(c.isInteger(r.end)||r.end&&c.isInteger(r.end.low)&&c.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&&(c.Long?(i.begin=c.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 c.LongBits(r.begin.low>>>0,r.begin.high>>>0).toNumber())),r.end!=null&&(c.Long?(i.end=c.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 c.LongBits(r.end.low>>>0,r.end.high>>>0).toNumber())),i},e.toObject=function(r,i){i||(i={});var d={};if(i.defaults){if(c.Long){var m=new c.Long(0,0,!1);d.begin=i.longs===String?m.toString():i.longs===Number?m.toNumber():m}else d.begin=i.longs===String?"0":0;c.Long?(m=new c.Long(0,0,!1),d.end=i.longs===String?m.toString():i.longs===Number?m.toNumber():m):d.end=i.longs===String?"0":0}return r.begin!=null&&r.hasOwnProperty("begin")&&(typeof r.begin=="number"?d.begin=i.longs===String?String(r.begin):r.begin:d.begin=i.longs===String?c.Long.prototype.toString.call(r.begin):i.longs===Number?new c.LongBits(r.begin.low>>>0,r.begin.high>>>0).toNumber():r.begin),r.end!=null&&r.hasOwnProperty("end")&&(typeof r.end=="number"?d.end=i.longs===String?String(r.end):r.end:d.end=i.longs===String?c.Long.prototype.toString.call(r.end):i.longs===Number?new c.LongBits(r.end.low>>>0,r.end.high>>>0).toNumber():r.end),d},e.prototype.toJSON=function(){return this.constructor.toObject(this,u.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&m)}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:_.dimValue=i.int64();break;case 2:_.dimParam=i.string();break;case 3:_.denotation=i.string();break;default:i.skipType(7&b)}}return _},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,!(c.isInteger(i.dimValue)||i.dimValue&&c.isInteger(i.dimValue.low)&&c.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,!c.isString(i.dimParam))return"dimParam: string expected"}return i.denotation!=null&&i.hasOwnProperty("denotation")&&!c.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&&(c.Long?(d.dimValue=c.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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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) { ${(0,p.getGlsl)(this.context.glContext.version).output} = val; } `;return r.floatTextureSetRGBA=new l.GlslLibRoutine(d),r}getUnpackedOutputSamplingSnippet(s){const t=s.unpackedShape,e=[s.width,s.height],r={},i="getOutputCoords";switch(t.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputUnpacked1DCoords(t,e);break;case 2:r[i]=this.getOutputUnpacked2DCoords(t,e);break;case 3:r[i]=this.getOutputUnpacked3DCoords(t,e);break;case 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e="";if(a.ArrayUtil.arraysEqual(s,t))return e=` ivec2 getOutputCoords() { return 2 * ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]})); } `,new l.GlslLibRoutine(e);const r=t,i=Math.ceil(s[1]/2);return e=` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(TexCoords.xy * vec2(${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 / ${i}); return ivec2(r, c); } `,new l.GlslLibRoutine(e)}getOutputPacked3DCoords(s,t){const e=[t[0],t[1]],r=Math.ceil(s[2]/2),i=r*Math.ceil(s[1]/2),d=` ivec3 getOutputCoords() { ivec2 resTexRC = ivec2(TexCoords.xy * vec2(${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 l.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,m="",_="b, r, c";for(let y=2;y=0;--_)i[_]=i[_+1]*s[_+1];const d=["r","c","d"],m=i.map((_,b)=>`int ${d[b]} = index / ${_}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${_}`:`index -= ${d[b]} * ${_}`};`).join("");return e=` ivec3 getOutputCoords() { ivec2 resTexRC = ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]})); int index = resTexRC.y * ${t[0]} + resTexRC.x; ${m} return ivec3(r, c, d); } `,new l.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 _=r-3;_>=0;--_)i[_]=i[_+1]*s[_+1];const d=["r","c","d","d2"],m=i.map((_,b)=>`int ${d[b]} = index / ${_}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${_}`:`index -= ${d[b]} * ${_}`};`).join("");return e=` ivec4 getOutputCoords() { ivec2 resTexRC = ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]})); int index = resTexRC.y * ${t[0]} + resTexRC.x; ${m} return ivec4(r, c, d, 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int texC = texelIndex - texR * texNumC; return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR); } `),t="packedUVfrom3D",s[t]=new l.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 l.GlslLibRoutine(` float sampleTexture(sampler2D textureSampler, vec2 uv) { return ${e.texture2D}(textureSampler, uv).r; }`),s}getInputsSamplingSnippets(){const s={},t=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,r)=>{const 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c=h[0].dims,s=h[1].dims,t=(0,a.calculateOutputShape)(c,s,g.dilations,g.pads,g.strides),e=u.reshapePacked(h[0],[c[1],c[2]*c[3]]),r=u.reshapePacked(h[1],[s[0],s[1]]),i=h.length>2?[r,e,h[2]]:[r,e],d=u.run((0,p.createPackedMatmulProgramInfoLoader)(u,i,g),i);return u.reshapePacked(d,t)},n.conv2DPacked=(u,h,g)=>{const c=h[0].dims,s=h[1].dims,t=(0,a.calculateOutputShape)(c,s,g.dilations,g.pads,g.strides),e=u.run((0,l.createPackedIm2ColProgramInfoLoader)(u,h[0],h[1],t,g),[h[0]]),r=u.reshapePacked(h[1],[s[0],s[1]*s[2]*s[3]]),i=h.length===3?[r,e,h[2]]:[r,e],d=u.run((0,p.createPackedMatmulProgramInfoLoader)(u,i,g),i);return u.reshapePacked(d,t)}},9663:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConvTransposeAttributes=n.convTranspose=void 0;const a=o(246),l=o(5060),p=o(2039),u=o(2823),h=(r,i,d,m,_,b)=>(r-1)*i+d+(m-1)*_+1-b,g=(r,i,d,m,_)=>{const b=Math.floor(r/2);i==="SAME_UPPER"?(d[m]=b,d[_]=r-b):i==="SAME_LOWER"&&(d[m]=r-b,d[_]=b)};n.convTranspose=(r,i,d)=>(e(i,d),c(r,i,d));const c=(r,i,d)=>{const m=t(d,i);return[s(r,i,m)]},s=(r,i,d)=>r.run(((m,_,b)=>{const y=(T=_.length>2,w=b.cacheKey,{name:"ConvTranspose",inputNames:T?["X","W","B"]:["X","W"],inputTypes:T?[p.TextureType.unpacked,p.TextureType.unpacked,p.TextureType.unpacked]:[p.TextureType.unpacked,p.TextureType.unpacked],cacheHint:w});var T,w;return Object.assign(Object.assign({},y),{get:()=>((S,E,O,v)=>{const M=E.length>2?"getB(output_channel)":"0.0",$=E[0].dims,D=E[1].dims,L=D[1],C=D[0]/v.group,U=[E[0].dims[0],E[1].dims[1]*v.group,...v.outputShape],N=(0,l.getGlsl)(S.session.backend.glContext.version),{activationFunction:j,applyActivation:J}=(0,u.getActivationSnippet)(v),Y=` const ivec2 strides = ivec2(${v.strides[0]}, ${v.strides[1]}); const ivec2 pads = ivec2(${v.pads[0]}, ${v.pads[1]}); ${j} void main() { ivec4 coords = getOutputCoords(); int batch = coords.x; int output_channel = coords.y; ivec2 loc = coords.zw + pads; int group_id = output_channel / ${L}; int wOutChannel = output_channel - group_id * ${L}; float value = ${M}; for (int inChannelOffset = 0; inChannelOffset < ${C}; inChannelOffset++) { int input_channel = group_id * ${C} + inChannelOffset; for (int wWOff = 0; wWOff < ${D[2]}; wWOff++) { for (int wHOff = 0; wHOff < ${D[3]}; wHOff++) { ivec2 wOff = ivec2(wWOff * ${v.dilations[0]}, wHOff * ${v.dilations[1]}); ivec2 wLoc = loc - wOff; ivec2 wLocIn = wLoc / strides; if ( wLocIn * strides == wLoc && wLocIn.x >= 0 && wLocIn.x < ${$[2]} && wLocIn.y >= 0 && wLocIn.y < ${$[3]} ) { float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x); float wVal = getW(input_channel, wOutChannel, wHOff, wWOff); value += xVal * wVal; } } } } ${J} ${N.output} = vec4(value, .0, .0, .0); } `;return Object.assign(Object.assign({},O),{output:{dims:U,type:E[0].type,textureType:p.TextureType.unpacked},shaderSource:Y,hasMain:!0})})(m,_,y,b)})})(r,i,d),i),t=(r,i)=>{const d=r.kernelShape.slice();if(r.kernelShape.length===0)for(let y=2;y{const $=y.length-2,D=M.length===0;for(let L=0;L<$;++L){const C=D?y[L+2]*O[L]:M[L],U=h(y[L+2],O[L],E[L],T[L],w[L],C);g(U,S,E,L,L+$),D&&M.push(O[L]*(y[L+2]-1)+v[L]+(T[L]-1)*w[L]+1-E[L]-E[L+$])}})(i[0].dims,d,r.dilations,r.autoPad,m,r.strides,r.outputPadding,_);const b=Object.assign({},r);return Object.assign(b,{kernelShape:d,pads:m,outputShape:_,cacheKey:r.cacheKey}),b};n.parseConvTransposeAttributes=r=>{const i=r.attributes,d=(0,u.parseInternalActivationAttributes)(i),m=i.getString("auto_pad","NOTSET"),_=i.getInts("dilations",[1,1]),b=i.getInt("group",1),y=i.getInts("kernel_shape",[]),T=i.getInts("output_padding",[0,0]),w=i.getInts("output_shape",[]),S=i.getInts("pads",[0,0,0,0]),E=i.getInts("strides",[1,1]);return(0,a.createAttributeWithCacheKey)(Object.assign({autoPad:m,dilations:_,group:b,kernelShape:y,outputPadding:T,outputShape:w,pads:S,strides:E},d))};const e=(r,i)=>{if(!r||r.length!==2&&r.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(r[0].dims.length!==4||r[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(r[0].dims[1]!==r[1].dims[0])throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");const d=r[1].dims[1]*i.group;if(r.length===3&&(r[2].dims.length!==1||r[2].dims[0]!==d))throw new Error("invalid bias");const m=r[0].dims.length-2;if(i.dilations.length!==m)throw new Error(`dilations should be ${m}D`);if(i.strides.length!==m)throw new Error(`strides should be ${m}D`);if(i.pads.length!==2*m)throw new Error(`pads should be ${2*m}D`);if(i.outputPadding.length!==m)throw new Error(`output_padding should be ${m}D`);if(i.kernelShape.length!==0&&i.kernelShape.length!==r[1].dims.length-2)throw new Error("invalid kernel shape");if(i.outputShape.length!==0&&i.outputShape.length!==r[0].dims.length-2)throw new Error("invalid output shape");if(r[0].type!=="float32"||r[1].type!=="float32")throw new Error("ConvTranspose input(X,W) should be float tensor");if(r.length===3&&r[2].type!=="float32")throw new Error("ConvTranspose input(bias) should be float tensor")}},8138:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConvAttributes=n.conv=n.calculateOutputShape=void 0;const a=o(246),l=o(2517),p=o(4770),u=o(1386),h=o(9828),g=o(2823),c=o(3248),s=o(5623);n.calculateOutputShape=(m,_,b,y,T)=>{const w=m[0],S=m.slice(2),E=S.length,O=_[0],v=_.slice(2).map(($,D)=>$+($-1)*(b[D]-1)),M=S.map(($,D)=>$+y[D]+y[D+E]).map(($,D)=>Math.floor(($-v[D]+T[D])/T[D]));return[w,O].concat(...M)},n.conv=(m,_,b)=>(d(_,b),t(m,_,b));const t=(m,_,b)=>{const y=i(b,_),T=m.session.pack,w=y.kernelShape[0]===1&&y.kernelShape[1]===1;return y.group>1?[m.run((0,p.createUnpackedGroupedConvProgramInfoLoader)(m,_,y),_)]:w&&T?[e(m,_,y)]:T&&_[0].dims.length===4&&_[0].dims[0]===1&&!w?[(0,u.conv2DPacked)(m,_,y)]:[r(m,_,y)]},e=(m,_,b)=>{const y=_[0].dims,T=_[1].dims,w=(0,n.calculateOutputShape)(y,T,b.dilations,b.pads,b.strides),S=m.reshapeUnpacked(_[0],[y[1],y[2]*y[3]]),E=m.reshapeUnpacked(_[1],[T[0],T[1]]),O=_.length>2?[E,S,_[2]]:[E,S],v=m.run((0,s.createMatmulProgramInfoLoader)(O,b),O);return m.reshapeUnpacked(v,w)},r=(m,_,b)=>{const y=_[0].dims,T=_[1].dims,w=(0,n.calculateOutputShape)(y,T,b.dilations,b.pads,b.strides),S=m.run((0,c.createIm2ColProgramInfoLoader)(m,_[0],_[1],w,b),[_[0]]),E=_.length===3?[S,_[1],_[2]]:[S,_[1]];return m.run((0,h.createDotProductProgramInfoLoader)(m,_,w,b),E)},i=(m,_)=>{const b=m.kernelShape.slice();if(m.kernelShape.length===0)for(let w=2;w<_[1].dims.length;++w)b.push(_[1].dims[w]);const y=m.pads.slice();l.PoolConvUtil.adjustPadsBasedOnAutoPad(_[0].dims,m.strides,m.dilations,b,y,m.autoPad);const T=Object.assign({},m);return Object.assign(T,{kernelShape:b,pads:y,cacheKey:m.cacheKey}),T};n.parseConvAttributes=m=>{const _=m.attributes,b=(0,g.parseInternalActivationAttributes)(_),y=_.getString("auto_pad","NOTSET"),T=_.getInts("dilations",[1,1]),w=_.getInt("group",1),S=_.getInts("kernel_shape",[]),E=_.getInts("pads",[0,0,0,0]),O=_.getInts("strides",[1,1]);return(0,a.createAttributeWithCacheKey)(Object.assign({autoPad:y,dilations:T,group:w,kernelShape:S,pads:E,strides:O},b))};const d=(m,_)=>{if(!m||m.length!==2&&m.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(m[0].dims.length!==4||m[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(m[0].dims[1]!==m[1].dims[1]*_.group)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(m.length===3&&(m[2].dims.length!==1||m[1].dims[0]!==m[2].dims[0]))throw new Error("invalid bias");const b=m[0].dims.length-2;if(_.dilations.length!==b)throw new Error(`dilations should be ${b}D`);if(_.strides.length!==b)throw new Error(`strides should be ${b}D`);if(_.pads.length!==2*b)throw new Error(`pads should be ${2*b}D`);if(_.kernelShape.length!==0&&_.kernelShape.length!==m[1].dims.length-2)throw new Error("invalid kernel shape");if(m[0].type!=="float32"||m[1].type!=="float32")throw new Error("Conv input(X,W) should be float tensor");if(m.length===3&&m[2].type!=="float32")throw new Error("Conv input(bias) should be float tensor")}},5193:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseDepthToSpaceAttributes=n.depthToSpace=void 0;const a=o(3738);n.depthToSpace=(p,u,h)=>{l(u);const g=h.blocksize,c=g*g,s=h.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],t=h.mode==="DCR"?[u[0].dims[0],g,g,u[0].dims[1]/c,u[0].dims[2],u[0].dims[3]]:[u[0].dims[0],u[0].dims[1]/c,g,g,u[0].dims[2],u[0].dims[3]],e=p.reshapeUnpacked(u[0],t),r={perm:s,cacheKey:`${s}`},[i]=(0,a.transpose)(p,[e],r),d=[u[0].dims[0],u[0].dims[1]/c,u[0].dims[2]*g,u[0].dims[3]*g];return[p.reshapeUnpacked(i,d)]},n.parseDepthToSpaceAttributes=p=>{const u=p.attributes.getInt("blocksize");if(u<1)throw new Error(`blocksize must be >= 1, but got : ${u} for DepthToSpace`);const h=p.attributes.getString("mode","DCR");if(h!=="DCR"&&h!=="CRD")throw new Error(`unrecognized mode: ${h} for DepthToSpace`);return{mode:h,blocksize:u}};const l=p=>{if(p.length!==1)throw new Error(`DepthToSpace expect 1 inputs, but got 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b=d[0].dims,y=d[1].dims,T=[y[0],Math.ceil(b[1]*y[2]*y[3]/4)],w=(0,h.calculateIm2ColDims)(b,y,m),[S,E]=r.calculateTextureWidthAndHeight(T,p.TextureType.packedLastDimension),O=a.ShapeUtil.computeStrides(w),[v,M]=r.calculateTextureWidthAndHeight(w,p.TextureType.packedLastDimension),$=m.length,D=d.length<3?"0.0":"_B(b)",L=Math.ceil(b[1]*y[2]*y[3]/4),{activationFunction:C,applyActivation:U}=(0,u.getActivationSnippet)(_),N=(0,l.getGlsl)(r.session.backend.glContext.version),j=` ${C} float process(int indices[${$}]) { 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] * ${T[1]}; float value = ${D}; for (int i = 0; i < ${L}; ++i) { vec2 im2colCoords = offsetToCoords(im2colOffset, ${v}, ${M}); vec2 kernelCoords = offsetToCoords(kernelOffset, ${S}, ${E}); value += dot(${N.texture2D}(Im2Col, im2colCoords), ${N.texture2D}(K, kernelCoords)); ++im2colOffset; ++kernelOffset; } ${U} return value; }`;return Object.assign(Object.assign({},i),{output:{dims:m,type:d[0].type,textureType:p.TextureType.unpacked},shaderSource:j})})(g,e,c,s,t)})}},7992:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseFlattenAttributes=n.flatten=void 0;const a=o(2517);n.flatten=(p,u,h)=>{l(u,h);const g=a.ShapeUtil.flattenShape(u[0].dims,h);return[p.reshapeUnpacked(u[0],g)]},n.parseFlattenAttributes=p=>p.attributes.getInt("axis",1);const l=(p,u)=>{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(u<-h||u>h)throw new Error("Invalid axis");if(p[0].type==="string")throw new Error("string tensor is not supported.")}},2823:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInternalActivationAttributes=n.getActivationSnippet=void 0;const 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h={name:"Gather",inputNames:["A","B"],inputTypes:[u.TextureType.unpacked,u.TextureType.unpacked]},g=(s,t,e)=>{const r=Object.assign(Object.assign({},h),{cacheHint:e.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((i,d,m,_)=>{const b=m[0].dims.slice(),y=m[1].dims.slice(),T=new Array(b.length+y.length-1);_=p.ShapeUtil.normalizeAxis(_,b.length);const w=[];for(let E=0;E{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(l.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:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGemmAttributesV11=n.parseGemmAttributesV7=n.gemm=void 0;const a=o(246),l=o(2517),p=o(2039);n.gemm=(s,t,e)=>(c(t,e),[s.run(h(t,e),t)]);const u=(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,a.createAttributeWithCacheKey)({transA:e,transB:r,alpha:i,beta:d,isOptionalC:t})};n.parseGemmAttributesV7=s=>u(s,!1),n.parseGemmAttributesV11=s=>u(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:()=>g(e,s,t)})},g=(s,t,e)=>{const r=t[0].dims.slice(),i=t[1].dims.slice(),[d,m]=l.GemmUtil.getShapeOfGemmResult(r,e.transA,i,e.transB,t.length===3?t[2].dims:void 0),_=[d,m];if(!_)throw new Error("Can't use gemm on the given tensors");let b=r[r.length-1],y="";e.transA&&(b=r[0]),e.transA&&e.transB?y="value += _A_T(a) * _B_T(b);":e.transA&&!e.transB?y="value += _A_T(a) * _B(b);":!e.transA&&e.transB?y="value += _A(a) * _B_T(b);":e.transA||e.transB||(y="value += _A(a) * _B(b);");const T=_.length,w=` float process(int indices[${T}]) { int a[${T}]; int b[${T}]; ${t.length===3?`int c[${t[2].dims.length}];`:""} copyVec(indices, a); copyVec(indices, b); ${t.length===3?"bcastIndices_C(indices, c);":""} float value = 0.0; for (int k=0; k<${b}; ++k) { a[${T-1}] = k; b[${T-2}] = k; ${y} } value = value * alpha; ${t.length===3?"value += beta * _C(c);":""} return value; }`;return Object.assign(Object.assign({},s),{output:{dims:_,type:t[0].type,textureType:p.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:e.alpha},{name:"beta",type:"float",data:e.beta}],shaderSource:w})},c=(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:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedIm2ColProgramInfoLoader=void 0;const a=o(5060),l=o(2039),p=o(2827);n.createPackedIm2ColProgramInfoLoader=(u,h,g,c,s)=>{const t=(e=s.cacheKey,{name:"Im2Col (packed)",inputNames:["A"],inputTypes:[l.TextureType.packed],cacheHint:e});var e;return Object.assign(Object.assign({},t),{get:()=>((r,i,d,m,_,b)=>{const y=d.dims,T=m.dims,w=_.length,S=[T[1]*T[2]*T[3],_[2]*_[3]],E=T[2]*T[3],O=(0,p.unpackFromChannel)(),v=(0,a.getGlsl)(r.session.backend.glContext.version);let M="";for(let D=0;D<=1;D++)for(let L=0;L<=1;L++)M+=` blockIndex = rc.x + ${L}; pos = rc.y + ${D}; if(blockIndex < ${S[1]} && pos < ${S[0]}) { offsetY = int(blockIndex / (${_[w-1]})) * ${b.strides[0]} - ${b.pads[0]}; d0 = offsetY + ${b.dilations[0]} * (imod(pos, ${E}) / ${T[2]}); if(d0 < ${y[2]} && d0 >= 0) { offsetX = imod(blockIndex, ${_[w-1]}) * ${b.strides[1]} - ${b.pads[1]}; d1 = offsetX + ${b.dilations[1]} * imod(imod(pos, ${E}), ${T[2]}); if(d1 < ${y[3]} && d1 >= 0) { ch = int(float(pos)/ ${E}.); innerDims = vec2(d0, d1); result[${2*D+L}] = getChannel( getA(0, ch, int(innerDims.x), int(innerDims.y)), innerDims); } } } `;const $=` ${O} void main() { ivec2 rc = getOutputCoords(); vec4 result = vec4(0.0); int blockIndex, pos, offsetY, d0, offsetX, d1, ch; vec2 innerDims; ${M} ${v.output} = result; } `;return Object.assign(Object.assign({},i),{output:{dims:S,type:d.type,textureType:l.TextureType.packed},shaderSource:$,hasMain:!0})})(u,t,h,g,c,s)})}},3248:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.calculateIm2ColDims=n.createIm2ColProgramInfoLoader=void 0;const a=o(2039);n.createIm2ColProgramInfoLoader=(l,p,u,h,g)=>{const c=(s=g.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[a.TextureType.unpacked],cacheHint:s});var s;return Object.assign(Object.assign({},c),{get:()=>((t,e,r,i,d,m)=>{const _=r.dims,b=i.dims,y=d.length,T=(0,n.calculateIm2ColDims)(_,b,d,4),w=` const int XC = ${_[1]}; const int XH = ${_[2]}; const int XW = ${_[3]}; const int KH = ${m.kernelShape[0]}; const int KW = ${m.kernelShape[1]}; const int dilationH = ${m.dilations[0]}; const int dilationW = ${m.dilations[1]}; const int strideH = ${m.strides[0]}; const int strideW = ${m.strides[1]}; const int padH = ${m.pads[0]}; const int padW = ${m.pads[1]}; const int KHKW = KH*KW; const int XCKHKW = XC * KHKW; const int outputChannels = 4; vec4 process(int indices[${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[${_.length}]; x[0] = b; x[1] = patchC; x[2] = xh2; x[3] = xw2; if(xh2 >= 0 && xh2 < XH && xw2 >= 0 && xw2 < XW) { value[i] = _X(x); } } ++p; } return value; } `;return Object.assign(Object.assign({},e),{output:{dims:T,type:r.type,textureType:a.TextureType.packedLastDimension},shaderSource:w})})(0,c,p,u,h,g)})},n.calculateIm2ColDims=(l,p,u,h=4)=>[u[0],u[2],u[3],Math.ceil(l[1]*p[2]*p[3]/h)]},6572:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseImageScalerAttributes=n.imageScaler=void 0;const a=o(246),l=o(2039);n.imageScaler=(c,s,t)=>(g(s),[c.run(u(c,s,t),s)]),n.parseImageScalerAttributes=c=>{const s=c.attributes.getFloat("scale"),t=c.attributes.getFloats("bias");return(0,a.createAttributeWithCacheKey)({scale:s,bias:t})};const p={name:"ImageScaler",inputNames:["X"],inputTypes:[l.TextureType.unpacked]},u=(c,s,t)=>{const e=Object.assign(Object.assign({},p),{cacheHint:t.cacheKey});return Object.assign(Object.assign({},e),{get:()=>((r,i,d,m)=>{const _=d[0].dims.slice(),b=_.length,y=` ${h(m.bias.length)} float process(int indices[${b}]) { return _X(indices) * scale + getBias(bias, indices[1]); }`;return Object.assign(Object.assign({},i),{output:{dims:_,type:d[0].type,textureType:l.TextureType.unpacked},variables:[{name:"bias",type:"float",arrayLength:m.bias.length,data:m.bias},{name:"scale",type:"float",data:m.scale}],shaderSource:y})})(0,e,s,t)})},h=c=>{const s=[`float getBias(float bias[${c}], int channel) {`];for(let t=0;t{if(!c||c.length!==1)throw new Error("ImageScaler requires 1 input.");if(c[0].dims.length!==4)throw new Error("Invalid input shape.");if(c[0].type!=="float32"&&c[0].type!=="float64")throw new Error("Invalid input type.")}},3346:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInstanceNormalizationAttributes=n.instanceNormalization=void 0;const a=o(5060),l=o(2039);n.instanceNormalization=(s,t,e)=>{c(t);const r=s.run(u(t[0]),t);return[s.run(g(s,t[0],e,r.dims),[t[0],r,t[1],t[2]])]},n.parseInstanceNormalizationAttributes=s=>s.attributes.getFloat("epsilon",1e-5);const p={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[l.TextureType.unpacked]},u=s=>Object.assign(Object.assign({},p),{get:()=>((t,e)=>{const r=e.dims.slice(),i=r[1],d=r[2]*r[3],m=[r[0],i],_=` vec4 process(int[2] indices) { vec4 v = vec4(0.0); int a[4]; a[0] = indices[0]; a[1] = indices[1]; float temp = 0.0; for(int a2=0; a2<${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(${d}); return v; }`;return Object.assign(Object.assign({},t),{output:{dims:m,type:e.type,textureType:l.TextureType.packedLastDimension},shaderSource:_})})(p,s)}),h={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[l.TextureType.unpacked,l.TextureType.packedLastDimension,l.TextureType.unpacked,l.TextureType.unpacked]},g=(s,t,e,r)=>{const i=Object.assign(Object.assign({},h),{cacheHint:`${e}`});return Object.assign(Object.assign({},i),{get:()=>((d,m,_,b,y)=>{const T=(0,a.getGlsl)(d.session.backend.glContext.version),[w,S]=d.calculateTextureWidthAndHeight(y,l.TextureType.packedLastDimension),[E,O]=[w/4,S],v=` vec4 get_MeanAndVariance(int[2] mv) { int offset = indicesToOffset_MeanAndVariance(mv); vec2 coords = offsetToCoords(offset, ${E}, ${O}); return ${T.texture2D}(MeanAndVariance, coords); } float process(int[4] indices) { int mv[2]; mv[0] = indices[0]; mv[1] = indices[1]; vec4 mean_and_variance = get_MeanAndVariance(mv); float mean = mean_and_variance.r; float variance = mean_and_variance.g; int sb[1]; sb[0] = indices[1]; float scale = _Scale(sb); float b = _B(sb); return scale * (_X(indices) - mean) / sqrt(variance + epsilon) + b; }`;return Object.assign(Object.assign({},m),{output:{dims:_.dims,type:_.type,textureType:l.TextureType.unpacked},variables:[{name:"epsilon",type:"float",data:b}],shaderSource:v})})(s,i,t,e,r)})},c=s=>{if(!s||s.length!==3)throw new Error("InstanceNormalization requires 3 inputs.");const t=s[0],e=s[1],r=s[2];if(t.dims.length<3||e.dims.length!==1||r.dims.length!==1)throw new Error("Invalid input shape.");if(e.dims[0]!==t.dims[1]||r.dims[0]!==t.dims[1])throw new Error("Input shapes are mismatched.");if(t.type!=="float32"&&t.type!=="float64"||e.type!=="float32"&&e.type!=="float64"||r.type!=="float32"&&r.type!=="float64")throw new Error("Invalid input type.");if(s[0].dims.length!==4)throw new Error("Only support 4-D input shape.")}},708:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedMatmulProgramInfoLoader=void 0;const a=o(2517),l=o(5060),p=o(2039),u=o(9390),h=o(2823),g=o(5623);n.createPackedMatmulProgramInfoLoader=(c,s,t)=>{const e=(r=s.length>2,i=t.activationCacheKey,{name:"MatMul (packed)",inputNames:r?["A","B","Bias"]:["A","B"],inputTypes:r?[p.TextureType.packed,p.TextureType.packed,p.TextureType.packed]:[p.TextureType.packed,p.TextureType.packed],cacheHint:i});var r,i;return Object.assign(Object.assign({},e),{get:()=>((d,m,_,b)=>{const y=_.length>2,T=y?"value += getBiasForMatmul();":"",w=_[0].dims,S=_[1].dims,E=a.BroadcastUtil.calcShape(w,S,!0),O=!a.ShapeUtil.areEqual(_[0].dims,_[1].dims);if(!E)throw new Error("Can't use matmul on the given tensors");const v=w[w.length-1],M=Math.ceil(v/2),$=w.length,D=S.length,L=(0,l.getGlsl)(d.session.backend.glContext.version),C=(0,u.getCoordsDataType)(E.length),U=E.length,N=(0,u.getGlChannels)(),{activationFunction:j,applyActivation:J}=(0,h.getActivationSnippet)(b),Y=y?`${(0,g.getBiasForMatmul)(C,N,_[2].dims,E,!0)}`:"",ee=O?`${function(Oe,he,xe,we){let $e=[],He=[];const Pe=xe[0].dims,Fe=xe[1].dims,Ce=Pe.length,Ae=Fe.length,ve=we.length,je=ve-Ce,Ve=ve-Ae;$e=Pe.map((Ee,Re)=>`coords.${he[Re+je]}`),$e[Ce-1]="i*2",$e.join(", "),He=Fe.map((Ee,Re)=>`coords.${he[Re+Ve]}`),He[Ae-2]="i*2",He.join(", ");const Ue=a.BroadcastUtil.getBroadcastDims(Pe,we),Ye=a.BroadcastUtil.getBroadcastDims(Fe,we),Qe=Ue.map(Ee=>`coords.${he[Ee+je]} = 0;`).join(` `),Ge=Ye.map(Ee=>`coords.${he[Ee+Ve]} = 0;`).join(` `),ze=`int lastDim = coords.${he[ve-1]}; coords.${he[ve-1]} = coords.${he[ve-2]}; coords.${he[ve-2]} = lastDim;`;return` vec4 getAAtOutCoordsMatmul(int i) { ${Oe} coords = getOutputCoords(); ${ze} ${Qe} vec4 outputValue = getA(${$e}); return outputValue; } vec4 getBAtOutCoordsMatmul(int i) { ${Oe} coords = getOutputCoords(); ${ze} ${Ge} vec4 outputValue = getB(${He}); return outputValue; }`}(C,N,_,E)}`:"",te=O?"getAAtOutCoordsMatmul(i)":`getA(${function(Oe,he){let xe="";for(let we=0;we{Object.defineProperty(n,"__esModule",{value:!0}),n.getBiasForMatmul=n.createMatmulProgramInfoLoader=n.parseMatMulAttributes=n.matMul=void 0;const a=o(2517),l=o(2039),p=o(9390),u=o(2823),h=o(708);function g(t,e){const r=(i=t.length>2,d=e.activationCacheKey,{name:"MatMul",inputNames:i?["A","B","Bias"]:["A","B"],inputTypes:i?[l.TextureType.unpacked,l.TextureType.unpacked,l.TextureType.unpacked]:[l.TextureType.unpacked,l.TextureType.unpacked],cacheHint:d});var i,d;return Object.assign(Object.assign({},r),{get:()=>function(m,_,b){const y=_[0].dims,T=_[1].dims,w=a.BroadcastUtil.calcShape(y,T,!0);if(!w)throw new Error("Can't use matmul on the given tensors");const S=(0,p.getCoordsDataType)(w.length),E=(0,p.getGlChannels)(),{activationFunction:O,applyActivation:v}=(0,u.getActivationSnippet)(b),M=_.length>2,$=M?"value += getBiasForMatmul();":"",D=M?`${s(S,E,_[2].dims,w,!1)}`:"",L=w.length,C=y.length,U=T.length,N=` ${O} ${D} float process(int indices[${L}]) { int a[${C}]; int b[${U}]; bcastMatmulIndices_A(indices, a); bcastMatmulIndices_B(indices, b); float value; for (int k=0; k<${y[y.length-1]}; ++k) { a[${C-1}] = k; b[${U-2}] = k; value += _A(a) * _B(b); } ${$} ${v} return value; }`;return Object.assign(Object.assign({},m),{output:{dims:w,type:_[0].type,textureType:l.TextureType.unpacked},shaderSource:N})}(r,t,e)})}n.matMul=(t,e,r)=>(c(e),t.session.pack?[t.run((0,h.createPackedMatmulProgramInfoLoader)(t,e,r),e)]:[t.run(g(e,r),e)]),n.parseMatMulAttributes=t=>(0,u.parseInternalActivationAttributes)(t.attributes),n.createMatmulProgramInfoLoader=g;const c=t=>{if(!t||t.length!==2)throw new Error("MatMul requires 2 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}`;return{name:"Pad",inputNames:["A"],inputTypes:[u.TextureType.unpacked],output:{dims:y,type:_.type,textureType:u.TextureType.unpacked},shaderSource:w}},s=m=>{if(!m||m.length!==1)throw new Error("Pad requires 1 input");if(m[0].type!=="float32"&&m[0].type!=="float64")throw new Error("Invalid input type.")},t=m=>{if(!m||m.length!==2&&m.length!==3)throw new Error("Pad requires 2 or 3 inputs");if(m[1].type!=="int32")throw new Error("Invalid input type.");if(m.length>=3&&m[2].type==="string")throw new Error("Invalid input type.")},e=(m,_,b)=>{const y=(0,p.getGlsl)(m.session.backend.glContext.version),[T,w]=m.calculateTextureWidthAndHeight(_.dims,u.TextureType.unpacked),S=l.ShapeUtil.computeStrides(_.dims);switch(b.mode){case"constant":return r(y,_.dims,S,T,w,b.pads,b.value);case"reflect":return i(y,_.dims,S,T,w,b.pads);case"edge":return d(y,_.dims,S,T,w,b.pads);default:throw new Error("Invalid mode")}},r=(m,_,b,y,T,w,S)=>{const E=_.length;let O="";for(let v=E-1;v>=0;--v)O+=` k = m[${v}] - ${w[v]}; if (k < 0) return constant; if (k >= ${_[v]}) return constant; offset += k * ${b[v]}; `;return` float padA(int m[${E}]) { const float constant = float(${S}); int offset = 0; int k = 0; ${O} vec2 coords = offsetToCoords(offset, ${y}, ${T}); float value = getColorAsFloat(${m.texture2D}(A, coords)); return value; } `},i=(m,_,b,y,T,w)=>{const S=_.length;let E="";for(let O=S-1;O>=0;--O)E+=` k = m[${O}] - ${w[O]}; if (k < 0) { k = -k; } { const int _2n_1 = ${2*(_[O]-1)}; k = int( mod( float(k), float(_2n_1) ) ) ; if(k >= ${_[O]}) { k = _2n_1 - k; } } offset += k * ${b[O]}; `;return` float padA(int m[${S}]) { int offset = 0; int k = 0; ${E} vec2 coords = offsetToCoords(offset, ${y}, ${T}); float value = getColorAsFloat(${m.texture2D}(A, coords)); return value; } `},d=(m,_,b,y,T,w)=>{const S=_.length;let E="";for(let O=S-1;O>=0;--O)E+=` k = m[${O}] - ${w[O]}; if (k < 0) k = 0; if (k >= ${_[O]}) k = ${_[O]-1}; offset += k * ${b[O]}; `;return` float padA(int m[${S}]) { int offset = 0; int k = 0; ${E} vec2 coords = offsetToCoords(offset, ${y}, ${T}); float value = getColorAsFloat(${m.texture2D}(A, coords)); return value; } `}},2143:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.globalMaxPool=n.parseMaxPoolAttributes=n.maxPool=n.parseGlobalAveragePoolAttributes=n.globalAveragePool=n.parseAveragePoolAttributes=n.averagePool=void 0;const a=o(246),l=o(2517),p=o(2039);n.averagePool=(d,m,_)=>{t(m);const b={name:"AveragePool",inputNames:["X"],inputTypes:[p.TextureType.unpacked],cacheHint:_.cacheKey};return[d.run(Object.assign(Object.assign({},b),{get:()=>u(m,b,!1,_)}),m)]},n.parseAveragePoolAttributes=d=>{const m=d.attributes.getString("auto_pad","NOTSET"),_=d.attributes.getInt("ceil_mode",0),b=d.attributes.getInt("count_include_pad",0)!==0,y=d.attributes.getInts("kernel_shape"),T=d.attributes.getInts("strides",[]),w=d.attributes.getInts("pads",[]);if(_!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,a.createAttributeWithCacheKey)({autoPad:m,ceilMode:_,countIncludePad:b,kernelShape:y,strides:T,pads:w})};const u=(d,m,_,b)=>{const[y,T]=g(d,b,_),w=l.ShapeUtil.size(y.kernelShape);let S="";y.countIncludePad?S+=`value /= float(${w});`:S+=`value /= float(${w} - pad);`;const E=` ${e(d[0].dims,y,"value += _X(x);",S,"0.0")} `;return Object.assign(Object.assign({},m),{output:{dims:T,type:d[0].type,textureType:p.TextureType.unpacked},shaderSource:E})};n.globalAveragePool=(d,m,_)=>{t(m);const b={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[p.TextureType.unpacked],cacheHint:`${_.countIncludePad}`};return[d.run(Object.assign(Object.assign({},b),{get:()=>u(m,b,!0,_)}),m)]},n.parseGlobalAveragePoolAttributes=d=>{const m=d.attributes.getInt("count_include_pad",0)!==0;return(0,a.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:m,kernelShape:[],strides:[],pads:[]})},n.maxPool=(d,m,_)=>{t(m);const b={name:"MaxPool",inputNames:["X"],inputTypes:[p.TextureType.unpacked],cacheHint:_.cacheKey};return[d.run(Object.assign(Object.assign({},b),{get:()=>h(m,b,!1,_)}),m)]},n.parseMaxPoolAttributes=d=>{const m=d.attributes.getString("auto_pad","NOTSET"),_=d.attributes.getInt("ceil_mode",0),b=d.attributes.getInts("kernel_shape"),y=d.attributes.getInts("strides",[]),T=d.attributes.getInts("pads",[]),w=d.attributes.getInt("storage_order",0),S=d.attributes.getInts("dilations",[]);if(w!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(_!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return(0,a.createAttributeWithCacheKey)({autoPad:m,ceilMode:_,countIncludePad:!1,kernelShape:b,strides:y,pads:T,storageOrder:w,dilations:S})};const h=(d,m,_,b)=>{const[y,T]=g(d,b,_),w=` ${e(d[0].dims,y,` value = max(_X(x), value); `,"","-1e5")} `;return Object.assign(Object.assign({},m),{output:{dims:T,type:d[0].type,textureType:p.TextureType.unpacked},shaderSource:w})},g=(d,m,_)=>{const b=d[0].dims.slice(),y=Object.hasOwnProperty.call(m,"dilations"),T=m.kernelShape.slice(),w=m.strides.slice(),S=y?m.dilations.slice():[],E=m.pads.slice();l.PoolConvUtil.adjustPoolAttributes(_,b,T,w,S,E);const O=l.PoolConvUtil.computePoolOutputShape(_,b,w,S,T,E,m.autoPad),v=Object.assign({},m);return y?Object.assign(v,{kernelShape:T,strides:w,pads:E,dilations:S,cacheKey:m.cacheKey}):Object.assign(v,{kernelShape:T,strides:w,pads:E,cacheKey:m.cacheKey}),[v,O]},c={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},s={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[p.TextureType.unpacked]};n.globalMaxPool=(d,m)=>(t(m),[d.run(Object.assign(Object.assign({},s),{get:()=>h(m,s,!0,c)}),m)]);const t=d=>{if(!d||d.length!==1)throw new Error("Pool ops requires 1 input.");if(d[0].type!=="float32"&&d[0].type!=="float64")throw new Error("Invalid input type.")},e=(d,m,_,b,y)=>{const T=d.length;if(m.kernelShape.length<=2){const w=m.kernelShape[m.kernelShape.length-1],S=m.strides[m.strides.length-1],E=m.pads[m.pads.length/2-1],O=m.pads[m.pads.length-1],v=d[T-1];let M="",$="",D="";if(M=E+O!==0?` for (int i = 0; i < ${w}; i++) { x[${T} - 1] = indices[${T} - 1] * ${S} - ${E} + i; if (x[${T} - 1] < 0 || x[${T} - 1] >= ${v}) { pad++; continue; } ${_} }`:` for (int i = 0; i < ${w}; i++) { x[${T} - 1] = indices[${T} - 1] * ${S} - ${E} + i; ${_} }`,m.kernelShape.length===2){const L=m.kernelShape[m.kernelShape.length-2],C=m.strides[m.strides.length-2],U=m.pads[m.pads.length/2-2],N=m.pads[m.pads.length-2],j=d[T-2];$=U+N!==0?` for (int j = 0; j < ${L}; j++) { x[${T} - 2] = indices[${T} - 2] * ${C} - ${U} + j; if (x[${T} - 2] < 0 || x[${T} - 2] >= ${j}) { pad+= ${w}; continue; } `:` for (int j = 0; j < ${L}; j++) { x[${T} - 2] = indices[${T} - 2] * ${C} - ${U} + j; `,D=` } `}return` float process(int indices[${T}]) { int x[${T}]; copyVec(indices, x); float value = ${y}; int pad = 0; ${$} ${M} ${D} ${b} return value; } `}{const w=l.ShapeUtil.size(m.kernelShape),S=l.ShapeUtil.computeStrides(m.kernelShape),E=S.length,O=m.pads.length,v=i(E),M=r(d,"inputDims"),$=r(m.pads,"pads"),D=r(S,"kernelStrides"),L=r(m.strides,"strides");let C="";return C=m.pads.reduce((U,N)=>U+N)?` if (x[j] >= inputDims[j] || x[j] < 0) { pad++; isPad = true; break; } } if (!isPad) { ${_} }`:` } ${_} `,` ${v} float process(int indices[${T}]) { int x[${T}]; copyVec(indices, x); int offset[${E}]; int pads[${O}]; int inputDims[${T}]; int kernelStrides[${E}]; int strides[${E}]; ${$} ${M} ${L} ${D} float value = ${y}; int pad = 0; bool isPad = false; for (int i = 0; i < ${w}; i++) { offsetToIndices(i, kernelStrides, offset); isPad = false; for (int j = ${T} - ${E}; j < ${T}; j++) { x[j] = indices[j] * strides[j - ${T} + ${E}] + offset[j - ${T} + ${E}] - pads[j - 2]; ${C} } ${b} return value; } `}},r=(d,m)=>{let _="";for(let b=0;b` void offsetToIndices(int offset, int[${d}] strides, out int[${d}] indices) { if (${d} == 0) { return; } for (int i = 0; i < ${d} - 1; ++i) { indices[i] = offset / strides[i]; offset -= indices[i] * strides[i]; } indices[${d} - 1] = offset; }`},4939:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.reduceLogSumSquare=n.reduceLogSum=n.reduceProd=n.reduceMin=n.reduceMax=n.reduceMean=n.reduceSum=n.parseReduceAttributes=void 0;const a=o(246),l=o(782),p=o(2517),u=o(2039),h=(s,t,e,r,i)=>{c(t);const d={name:r,inputNames:["A"],inputTypes:[u.TextureType.unpacked]};return[s.run(Object.assign(Object.assign({},d),{cacheHint:e.cacheKey,get:()=>g(s,t,e,r,i,d)}),t)]};n.parseReduceAttributes=s=>{const t=s.attributes.getInts("axes",[]),e=s.attributes.getInt("keepdims",1)===1;return(0,a.createAttributeWithCacheKey)({axes:t,keepDims:e})};const g=(s,t,e,r,i,d)=>{const m=[],_=t[0].dims.length||1,b=[],y=p.ShapeUtil.normalizeAxes(e.axes,t[0].dims.length),T=i(t,y);let w=T[1];for(let E=0;E=0||y.length===0?(e.keepDims&&m.push(1),w=` for(int j${E} = 0; j${E} < ${t[0].dims[E]}; j${E}++) { inputIdx[${E}] = j${E}; ${w} }`):(b.push(`inputIdx[${E}] = outputIdx[${m.length}];`),m.push(t[0].dims[E]));const S=` float process(int outputIdx[${m.length||1}]) { float value; // final result int inputIdx[${_}]; // addressing input data ${b.join(` `)} ${T[0]} // init ops for reduce max/min ${w} ${T[2]} // final computation for reduce mean return value; }`;return Object.assign(Object.assign({},d),{output:{dims:m,type:t[0].type,textureType:u.TextureType.unpacked},shaderSource:S})},c=s=>{if(!s||s.length!==1)throw new Error("Reduce op requires 1 input.");if(l.NUMBER_TYPES.indexOf(s[0].type)===-1)throw new Error("Invalid input type.")};n.reduceSum=(s,t,e)=>h(s,t,e,"ReduceSum",()=>["value = 0.0;","value += _A(inputIdx);",""]),n.reduceMean=(s,t,e)=>h(s,t,e,"ReduceMean",(r,i)=>{let d=1;for(let m=0;m=0||i.length===0)&&(d*=r[0].dims[m]);return["value = 0.0;","value += _A(inputIdx);",`value /= ${d}.;`]}),n.reduceMax=(s,t,e)=>h(s,t,e,"ReduceMax",(r,i)=>{const d=[];for(let m=0;m=0||i.length===0)&&d.push(`inputIdx[${m}] = 0;`);return[`${d.join(` `)} value = _A(inputIdx);`,"value = max(value, _A(inputIdx));",""]}),n.reduceMin=(s,t,e)=>h(s,t,e,"ReduceMin",(r,i)=>{const d=[];for(let m=0;m=0||i.length===0)&&d.push(`inputIdx[${m}] = 0;`);return[`${d.join(` `)} value = _A(inputIdx);`,"value = min(value, _A(inputIdx));",""]}),n.reduceProd=(s,t,e)=>h(s,t,e,"ReduceProd",()=>["value = 1.0;","value *= _A(inputIdx);",""]),n.reduceLogSum=(s,t,e)=>h(s,t,e,"ReduceLogSum",()=>["value = 0.0;","value += _A(inputIdx);","value = log(value);"]),n.reduceLogSumSquare=(s,t,e)=>h(s,t,e,"ReduceLogSumSquare",()=>["float t; value = 0.0;","t = _A(inputIdx); value += t * t;",""])},7019:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.isReshapeCheap=n.processDims3D=n.createPackedReshape3DProgramInfoLoader=void 0;const a=o(2517),l=o(5060),p=o(2039),u=o(2827);n.createPackedReshape3DProgramInfoLoader=(h,g,c)=>{const s=(t=>({name:"Reshape (packed)",inputTypes:[p.TextureType.packed],inputNames:["A"],cacheHint:`${t}`}))(c);return Object.assign(Object.assign({},s),{get:()=>((t,e,r,i)=>{const d=e.dims,m=i;let _="";for(let T=0;T<4;T++){let w="";switch(T){case 0:w="outputCoords = rc;";break;case 1:w="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:w="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:w="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}_+=` ${w} ${T>0?"if(outputCoords.y < rows && outputCoords.z < cols){":""} int flattenedIndex = getFlattenedIndex(outputCoords); ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex); vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z)); result[${T}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims); ${T>0?"}":""} `}const b=(0,l.getGlsl)(t.session.backend.glContext.version),y=` ${function(T){const w=a.ShapeUtil.computeStrides(T),S=["b","r","c"],E="index";return` ivec3 inputCoordsFromReshapedOutCoords(int index) { ${w.map((O,v)=>`int ${S[v]} = ${E} / ${O}; ${v===w.length-1?`int ${S[v+1]} = ${E} - ${S[v]} * ${O}`:`index -= ${S[v]} * ${O}`};`).join("")} return ivec3(b, r, c); } `}(d)} ${function(T){const w=a.ShapeUtil.computeStrides(T);return` int getFlattenedIndex(ivec3 coords) { // reverse y, z order return coords.x * ${w[0]} + coords.z * ${w[1]} + coords.y; } `}(m)} ${(0,u.unpackFromChannel)()} void main() { ivec3 rc = getOutputCoords(); vec4 result = vec4(0.0); ivec3 outputCoords; int rows = ${m[2]}; int cols = ${m[1]}; ${_} ${b.output} = result; } `;return Object.assign(Object.assign({},r),{output:{dims:m,type:e.type,textureType:p.TextureType.packed},shaderSource:y,hasMain:!0})})(h,g,s,c)})},n.processDims3D=function(h){if(h.length===0)return[1,1,1];let g=1;for(let c=0;c1?h[h.length-2]:1,h[h.length-1]]},n.isReshapeCheap=function(h,g){let c=!1;return c=h.length===0||g.length===0||(h.length<2||g.length<2?h[h.length-1]===g[g.length-1]:h[h.length-1]===g[g.length-1]&&h[h.length-2]===g[g.length-2]),c}},718:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.reshape=void 0;const a=o(2517);n.reshape=(l,p)=>{const u=a.ShapeUtil.calculateReshapedDims(p[0].dims,p[1].integerData);return l.session.pack?[l.reshapePacked(p[0],u)]:[l.reshapeUnpacked(p[0],u)]}},2268:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseResizeAttributesV11=n.parseResizeAttributesV10=n.resize=void 0;const a=o(5060),l=o(2039),p=o(9390),u=o(2827),h=o(9793),g={name:"Resize",inputNames:["A"],inputTypes:[l.TextureType.packed]};n.resize=(r,i,d)=>((0,h.validateInputs)(i,d),[r.run(Object.assign(Object.assign({},g),{cacheHint:d.cacheKey,get:()=>c(r,i,d)}),i)]),n.parseResizeAttributesV10=r=>(0,h.parseUpsampleAttributes)(r,10),n.parseResizeAttributesV11=r=>(0,h.parseUpsampleAttributes)(r,11);const c=(r,i,d)=>{const m=(0,a.getGlsl)(r.session.backend.glContext.version),[_,b]=s(i,d);if(_.every(C=>C===1)&&d.coordinateTransformMode!=="tf_crop_and_resize")return Object.assign(Object.assign({},g),{output:{dims:b,type:i[0].type,textureType:l.TextureType.packed},hasMain:!0,shaderSource:`void main() { vec4 v = ${m.texture2D}(X, TexCoords); ${m.output} = v; }`});const y=b.length;if(y<2)throw new Error(`output dimension should be at least 2, but got ${y}`);const T=b[y-2],w=b[y-1],S=i[0].dims;if(y!==S.length)throw new Error(`output dimension should match input ${S.length}, but got ${y}`);const E=S[y-2],O=S[y-1],v=_[y-2],M=_[y-1];let $="";if(d.mode!=="linear")throw new Error(`resize (packed) does not support mode: '${d.mode}'`);switch(d.coordinateTransformMode){case"asymmetric":$=` vec4 getSourceFracIndex(ivec4 coords) { return vec4(coords) / scaleWHWH; } `;break;case"half_pixel":$=` vec4 getSourceFracIndex(ivec4 coords) { return (vec4(coords) + 0.5) / scaleWHWH - 0.5; } `;break;case"pytorch_half_pixel":$=` vec4 getSourceFracIndex(ivec4 coords) { vec4 fcoords = vec4(coords); return vec4( ${w}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0, ${T}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0, ${w}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0, ${T}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0 ); } `;break;case"align_corners":$=` vec4 getSourceFracIndex(ivec4 coords) { vec4 resized = vec4(${w}.0 - 1.0, ${T}.0 - 1.0, ${w}.0 - 1.0, ${T}.0 - 1.0); vec4 original = vec4(${O}.0 - 1.0, ${E}.0 - 1.0, ${O}.0 - 1.0, ${E}.0 - 1.0); vec4 new_scale = original / resized; return vec4(coords) * new_scale; } `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode: '${d.coordinateTransformMode}'`)}const D=(0,p.getCoordsDataType)(y),L=` const vec2 inputWH = vec2(${E}.0, ${O}.0); const vec4 scaleWHWH = vec4(float(${v}), float(${M}), float(${v}), float(${M})); ${(0,u.unpackFromChannel)()} ${$} float getAValue(int x10, int r, int c, int d) { return getChannel(getA(x10, r, c, d), vec2(c, d)); } void main() { ${D} rc = getOutputCoords(); int batch = rc[0]; int depth = rc[1]; // retrieve the 4 coordinates that is used in the 4 packed output values. ivec4 coords = ivec4(rc.wz, rc.w + 1, rc.z + 1); // calculate the source index in fraction vec4 sourceFrac = getSourceFracIndex(coords); // get the lower and upper bound of the 4 values that will be packed into one texel. ivec4 x00 = ivec4(max(sourceFrac.xy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xy))); ivec4 x01 = ivec4(max(sourceFrac.xw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xw))); ivec4 x10 = ivec4(max(sourceFrac.zy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zy))); ivec4 x11 = ivec4(max(sourceFrac.zw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zw))); bool hasNextRow = rc.w < ${T-1}; bool hasNextCol = rc.z < ${w-1}; // pack x00, x01, x10, x11's top-left corner into one vec4 structure vec4 topLeft = vec4( getAValue(batch, depth, x00.x, x00.y), hasNextCol ? getAValue(batch, depth, x01.x, x01.y) : 0.0, hasNextRow ? getAValue(batch, depth, x10.x, x10.y) : 0.0, (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.y) : 0.0); // pack x00, x01, x10, x11's top-right corner into one vec4 structure vec4 topRight = vec4( getAValue(batch, depth, x00.x, x00.w), hasNextCol ? getAValue(batch, depth, x01.x, x01.w) : 0.0, hasNextRow ? getAValue(batch, depth, x10.x, x10.w) : 0.0, (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.w) : 0.0); // pack x00, x01, x10, x11's bottom-left corner into one vec4 structure vec4 bottomLeft = vec4( getAValue(batch, depth, x00.z, x00.y), hasNextCol ? getAValue(batch, depth, x01.z, x01.y) : 0.0, hasNextRow ? getAValue(batch, depth, x10.z, x10.y) : 0.0, (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.y) : 0.0); // pack x00, x01, x10, x11's bottom-right corner into one vec4 structure vec4 bottomRight = vec4( getAValue(batch, depth, x00.z, x00.w), hasNextCol ? getAValue(batch, depth, x01.z, x01.w) : 0.0, hasNextRow ? getAValue(batch, depth, x10.z, x10.w) : 0.0, (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.w) : 0.0); // calculate the interpolation fraction on u and v direction vec4 frac = vec4(sourceFrac) - floor(sourceFrac); vec4 clampFrac = clamp(frac, vec4(0.0), vec4(1.0)); vec4 top = mix(topLeft, topRight, clampFrac.ywyw); vec4 bottom = mix(bottomLeft, bottomRight, clampFrac.ywyw); vec4 newValue = mix(top, bottom, clampFrac.xxzz); ${m.output} = vec4(newValue); } `;return Object.assign(Object.assign({},g),{output:{dims:b,type:i[0].type,textureType:l.TextureType.packed},hasMain:!0,shaderSource:L})},s=(r,i)=>{const d=r[0].dims;let m,_=i.scales;if(_.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.");_=t(y,i.mode,i.isResize)}else{const T=r[i.sizesInputIdx];if(!T||T.size===0)throw new Error("Either scales or sizes MUST be provided as input.");m=Array.from(T.integerData),_=e(m,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 b=m||d.map((y,T)=>Math.floor(y*_[T]));return[_,b]},t=(r,i,d)=>{const m=Array.from(r.floatData);return(0,h.scalesValidation)(m,i,d),m},e=(r,i,d,m)=>{const _=i.length,b=new Array(_);for(let y=0,T=_;y{Object.defineProperty(n,"__esModule",{value:!0}),n.shape=void 0;const a=o(9162);n.shape=(p,u)=>(l(u),[new a.Tensor([u[0].dims.length],"int32",void 0,void 0,new Int32Array(u[0].dims))]);const l=p=>{if(!p||p.length!==1)throw new Error("Shape requires 1 input.")}},2278:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.sliceV10=n.parseSliceAttributes=n.slice=void 0;const a=o(246),l=o(782),p=o(2517),u=o(2039),h={name:"Slice",inputNames:["A"],inputTypes:[u.TextureType.unpacked]};n.slice=(e,r,i)=>(c(r),[e.run(Object.assign(Object.assign({},h),{cacheHint:i.cacheKey,get:()=>g(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,a.createAttributeWithCacheKey)({starts:r,ends:i,axes:d})};const g=(e,r,i)=>{const d=i.axes.length===0?r.dims.slice(0).map((S,E)=>E):i.axes,m=p.ShapeUtil.normalizeAxes(d,r.dims.length),_=i.starts.map((S,E)=>S>r.dims[m[E]]-1?r.dims[m[E]]:p.ShapeUtil.normalizeAxis(S,r.dims[m[E]])),b=i.ends.map((S,E)=>S>r.dims[m[E]]-1?r.dims[m[E]]:p.ShapeUtil.normalizeAxis(S,r.dims[m[E]])),y=r.dims.slice(),T=[];for(let S=0;S0&&T.push(`outputIdx[${m[S]}] += ${_[S]};`);const w=` float process(int outputIdx[${y.length}]) { ${T.join(` `)} return _A(outputIdx); }`;return Object.assign(Object.assign({},h),{output:{dims:y,type:r.type,textureType:u.TextureType.unpacked},shaderSource:w})},c=e=>{if(!e||e.length!==1)throw new Error("Slice requires 1 input.");if(l.NUMBER_TYPES.indexOf(e[0].type)===-1)throw new Error("Invalid input type.")};n.sliceV10=(e,r)=>{t(r);const i=s(e,r);return[e.run(Object.assign(Object.assign({},h),{cacheHint:i.cacheKey,get:()=>g(e,r[0],i)}),[r[0]])]};const s=(e,r)=>{if(!e.session.isInitializer(r[1].dataId)||!e.session.isInitializer(r[2].dataId)||r.length>=4&&!e.session.isInitializer(r[3].dataId)||r.length>=5&&!e.session.isInitializer(r[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(r.length>=5&&r[4].integerData.some(_=>_!==1))throw new Error("currently non-1 steps is not supported for Slice");const i=Array.from(r[1].integerData),d=Array.from(r[2].integerData),m=r.length>=4?Array.from(r[3].integerData):[];return{starts:i,ends:d,axes:m,cacheKey:`${m};${i};${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:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.softmaxV13=n.parseSoftmaxAttributesV13=n.parseSoftmaxAttributes=n.softmax=void 0;const a=o(246),l=o(2517),p=o(5060),u=o(2039),h=o(3738),g={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[u.TextureType.unpacked]},c={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[u.TextureType.unpacked,u.TextureType.unpacked]},s={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[u.TextureType.unpacked,u.TextureType.unpacked,u.TextureType.unpacked]};n.softmax=(m,_,b)=>{d(_);const y=_[0].dims.slice(),T=l.ShapeUtil.normalizeAxis(b.axis,y.length),w=l.ShapeUtil.sizeToDimension(y,T),S=l.ShapeUtil.sizeFromDimension(y,T);return t(m,_,b,w,S)},n.parseSoftmaxAttributes=m=>(0,a.createAttributeWithCacheKey)({axis:m.attributes.getInt("axis",1)}),n.parseSoftmaxAttributesV13=m=>(0,a.createAttributeWithCacheKey)({axis:m.attributes.getInt("axis",-1)}),n.softmaxV13=(m,_,b)=>{d(_);const y=_[0].dims.slice(),T=l.ShapeUtil.normalizeAxis(b.axis,y.length),w=y.length,S=T!==w-1,E=[];let O,v=[],M=[];S&&(v=Array.from({length:w}).map((C,U)=>U),v[T]=w-1,v[w-1]=T,v.map(C=>E.push(y[C])),O=(0,a.createAttributeWithCacheKey)({perm:v}),M=(0,h.transpose)(m,_,O));const $=S?l.ShapeUtil.sizeToDimension(E,w-1):l.ShapeUtil.sizeToDimension(y,w-1),D=S?l.ShapeUtil.sizeFromDimension(E,w-1):l.ShapeUtil.sizeFromDimension(y,w-1),L=t(m,S?M:_,b,$,D);return S?(0,h.transpose)(m,L,O):L};const t=(m,_,b,y,T)=>{const w=e(m,_[0],y,T,[y]),S=m.run(Object.assign(Object.assign({},g),{cacheHint:b.cacheKey,get:()=>w}),_),E=r(m,_[0],y,T,w.output.dims,[y]),O=m.run(Object.assign(Object.assign({},c),{cacheHint:b.cacheKey,get:()=>E}),[_[0],S]),v=i(m,_[0],y,T,w.output.dims,E.output.dims);return[m.run(Object.assign(Object.assign({},s),{cacheHint:b.cacheKey,get:()=>v}),[_[0],S,O])]},e=(m,_,b,y,T)=>{const[w,S]=m.calculateTextureWidthAndHeight(_.dims,u.TextureType.unpacked),E=T.length;if(b<1||y<1)throw new Error("Logical 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1");if(w.length!==1)throw new Error("Dimensionality of the output should be 1");if(w[0]!==b)throw new Error("Shape of the output should be equal to logical row count");if(T.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(T[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const v=` 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)(m.session.backend.glContext.version).texture2D}(A, offsetToCoords(logical_row_start_offset + i, ${S}, ${E}))) - max); } return norm_factor; }`;return Object.assign(Object.assign({},c),{output:{dims:w,type:_.type,textureType:u.TextureType.unpacked},shaderSource:v})},i=(m,_,b,y,T,w)=>{const[S,E]=m.calculateTextureWidthAndHeight(_.dims,u.TextureType.unpacked),O=_.dims.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(T.length!==1||w.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(T[0]!==b||w[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const v=` float process(int[${O}] indices) { // get offset of current logical tensor index from the 2-D texture coordinates (TexCoords) int offset = coordsToOffset(TexCoords, ${S}, ${E}); //determine the logical row for this index int logical_row_index[1]; logical_row_index[0] = offset / ${y}; float norm_factor = _Norm(logical_row_index); // avoid possible division by 0 // if norm_facor is 0, all elements are zero // if so, return 0 if(norm_factor == 0.0) return 0.0; return exp(_A(indices) - _Max(logical_row_index)) / norm_factor; }`;return Object.assign(Object.assign({},s),{output:{dims:_.dims,type:_.type,textureType:u.TextureType.unpacked},shaderSource:v})},d=m=>{if(!m||m.length!==1)throw new Error("Softmax requires 1 input.");if(m[0].type!=="float32"&&m[0].type!=="float64")throw new Error("Invalid input type")}},5975:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSplitAttributes=n.split=void 0;const a=o(246),l=o(2517),p=o(2039),u={name:"Split",inputNames:["A"],inputTypes:[p.TextureType.unpacked]};n.split=(s,t,e)=>{c(t);const r=l.ShapeUtil.normalizeAxis(e.axis,t[0].dims.length),i=h(s,t,r,e),d=[];for(let m=0;mg(s,t[0],e,r,m)}),t));return d},n.parseSplitAttributes=s=>{const t=s.attributes.getInt("axis",0),e=s.attributes.getInts("split",[]),r=s.outputs.length;return(0,a.createAttributeWithCacheKey)({axis:t,split:e,numOutputs:r})};const h=(s,t,e,r)=>{const[,i]=l.SplitUtil.splitShape(t[0].dims,e,r.split,r.numOutputs);return i.length},g=(s,t,e,r,i)=>{const[d,m]=l.SplitUtil.splitShape(t.dims,r,e.split,e.numOutputs),_=m[i],b=d[i],y=` float process(int indices[${b.length}]) { indices[${r}] += ${_}; return _A(indices); } `;return Object.assign(Object.assign({},u),{cacheHint:`${e.cacheKey}:${i}`,output:{dims:b,type:t.type,textureType:p.TextureType.unpacked},shaderSource:y})},c=s=>{if(!s||s.length!==1)throw new Error("Split requires one input.");if(s[0].type!=="int8"&&s[0].type!=="uint8"&&s[0].type!=="int16"&&s[0].type!=="uint16"&&s[0].type!=="int32"&&s[0].type!=="uint32"&&s[0].type!=="float32"&&s[0].type!=="float64"&&s[0].type!=="bool")throw new Error("Invalid input type.")}},3933:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSqueezeAttributes=n.squeezeV13=n.squeeze=void 0;const a=o(2517);n.squeeze=(u,h,g)=>{l(h);const c=a.ShapeUtil.squeezeShape(h[0].dims,g);return[u.reshapeUnpacked(h[0],c)]},n.squeezeV13=(u,h)=>(p(h),(0,n.squeeze)(u,[h[0]],Array.from(h[1].integerData))),n.parseSqueezeAttributes=u=>u.attributes.getInts("axes");const l=u=>{if(!u||u.length!==1)throw new Error("Squeeze requires 1 input.");if(u[0].type==="string")throw new Error("invalid input tensor 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a=o(246),l=o(2517),p=o(8520),u=o(5060),h=o(2039);function g(){return L("abs")}function c(){return L("acos")}function s(){return L("asin")}function t(){return L("atan")}function e(){return L("ceil")}function r(){return L("cos")}function i(N){const j="elu";return{body:` const float alpha = float(${N}); float ${j}_(float a) { return a >= 0.0 ? a: (exp(a) - 1.0) * alpha; } vec4 ${j}_(vec4 v) { return vec4(${j}_(v.x), ${j}_(v.y), ${j}_(v.z), ${j}_(v.w)); } `,name:j,type:p.FunctionType.ValueBased}}function d(){return L("exp")}function m(){return L("floor")}function _(N,j){const J="clip";return{body:` const float min = float(${N}); const float max = float(${j}); float ${J}_(float a) { return clamp(a, min, max); } vec4 ${J}_(vec4 v) { return clamp(v, min, max); } `,name:J,type:p.FunctionType.ValueBased}}function b(){const N="indentity";return{body:` float ${N}_(float a) { return a; } vec4 ${N}_(vec4 v) { return v; } `,name:N,type:p.FunctionType.ValueBased}}function y(N){const 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Promise(t=>{this.addItemToPoll(()=>s.isFencePassed(),()=>t())})}pollItems(){const s=c(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=s;++t){const{resolveFn:e}=this.itemsToPoll[t];e()}this.itemsToPoll=this.itemsToPoll.slice(s+1)}async addItemToPoll(s,t){this.itemsToPoll.push({isDoneFn:s,resolveFn:t}),this.itemsToPoll.length>1||await(0,g.repeatedTry)(()=>(this.pollItems(),this.itemsToPoll.length===0))}}},1036:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.ExecutionPlan=void 0;const a=o(6231);class l{constructor(u,h){this.op=u,this.node=h}}n.ExecutionPlan=class{constructor(p,u,h){this.graph=p,this.profiler=h,this.initialize(u)}initialize(p){this.profiler.event("session","ExecutionPlan.initialize",()=>{const u=this.graph.getNodes();if(u.length!==p.length)throw new Error("The size of nodes and OPs do not match.");this._ops=p.map((h,g)=>new l(h,u[g])),this.reset(),this._starter=[],this._ops.forEach((h,g)=>{let c=!0;for(const s of h.node.inputs)if(!this._values[s]&&this.graph.getInputIndices().indexOf(s)===-1){c=!1;break}c&&this._starter.push(g)})})}reset(){this._values=this.graph.getValues().map(p=>p.tensor)}async execute(p,u){return this.profiler.event("session","ExecutionPlan.execute",async()=>{this.reset();const h=p.createInferenceHandler(),g=this.graph.getInputIndices();if(u.length!==g.length)throw new Error(`number of input tensors don't match the number of inputs to the model: actual: ${u.length} expected: ${g.length}`);u.forEach((i,d)=>{const m=g[d];this._values[m]=i});const c=this._starter.slice(0),s=this.graph.getValues(),t=this.graph.getNodes();let e=0;for(;ethis._values[T]);if(m.indexOf(void 0)!==-1)throw new Error(`unresolved input detected: op: ${d.node}`);const _=m;a.Logger.verbose("ExecPlan",`Runing op:${d.node.name} (${_.map((T,w)=>`'${d.node.inputs[w]}': ${T.type}[${T.dims.join(",")}]`).join(", ")})`);const b=await this.profiler.event("node",d.node.name,async()=>d.op.impl(h,_,d.op.context));if(b.length!==d.node.outputs.length)throw new Error("the size of output does not match model definition.");b.forEach((T,w)=>{const S=d.node.outputs[w];if(this._values[S])throw new Error(`output [${S}] already has value: op:${d.node.name}`);this._values[S]=T});const y=new Set;b.forEach((T,w)=>{const S=d.node.outputs[w];for(const E of s[S].to){const O=t[E];let v=!0;for(const M of O.inputs)if(!this._values[M]){v=!1;break}v&&y.add(E)}}),c.push(...y)}const r=[];for(let i=0;i{Object.defineProperty(n,"__esModule",{value:!0}),n.Graph=void 0;const a=o(1446),l=o(7778),p=o(9395),u=o(9162),h=o(2517);var g=p.onnxruntime.experimental.fbs;n.Graph={from:(e,r)=>new t(e,r)};class c{constructor(r){this._from=void 0,this._to=[],this.tensor=void 0,this.type=void 0,r&&(this.type=h.ProtoUtil.tensorValueTypeFromProto(r.type.tensorType))}get from(){return this._from}get to(){return this._to}}class s{constructor(r,i){r instanceof 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c.startAttribute(t),c.addName(t,e),c.addDocString(t,r),c.addType(t,i),c.addF(t,d),c.addI(t,m),c.addS(t,_),c.addT(t,b),c.addG(t,y),c.addFloats(t,T),c.addInts(t,w),c.addStrings(t,S),c.addTensors(t,E),c.addGraphs(t,O),c.endAttribute(t)}}g.Attribute=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsGraph(t,e){return(e||new c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsGraph(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(t.readInt32(t.position())+t.position(),t)}initializers(t,e){let r=this.bb.__offset(this.bb_pos,4);return r?(e||new u.experimental.fbs.Tensor).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}initializersLength(){let t=this.bb.__offset(this.bb_pos,4);return 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r=this.bb.__offset(this.bb_pos,14);return r?this.bb.__string(this.bb.__vector(this.bb_pos+r)+4*t,e):null}inputsLength(){let t=this.bb.__offset(this.bb_pos,14);return t?this.bb.__vector_len(this.bb_pos+t):0}outputs(t,e){let r=this.bb.__offset(this.bb_pos,16);return r?this.bb.__string(this.bb.__vector(this.bb_pos+r)+4*t,e):null}outputsLength(){let t=this.bb.__offset(this.bb_pos,16);return t?this.bb.__vector_len(this.bb_pos+t):0}sparseInitializers(t,e){let r=this.bb.__offset(this.bb_pos,18);return r?(e||new u.experimental.fbs.SparseTensor).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}sparseInitializersLength(){let t=this.bb.__offset(this.bb_pos,18);return t?this.bb.__vector_len(this.bb_pos+t):0}static startGraph(t){t.startObject(8)}static addInitializers(t,e){t.addFieldOffset(0,e,0)}static createInitializersVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startInitializersVector(t,e){t.startVector(4,e,4)}static addNodeArgs(t,e){t.addFieldOffset(1,e,0)}static createNodeArgsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodeArgsVector(t,e){t.startVector(4,e,4)}static addNodes(t,e){t.addFieldOffset(2,e,0)}static createNodesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodesVector(t,e){t.startVector(4,e,4)}static addMaxNodeIndex(t,e){t.addFieldInt32(3,e,0)}static addNodeEdges(t,e){t.addFieldOffset(4,e,0)}static createNodeEdgesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodeEdgesVector(t,e){t.startVector(4,e,4)}static addInputs(t,e){t.addFieldOffset(5,e,0)}static createInputsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startInputsVector(t,e){t.startVector(4,e,4)}static addOutputs(t,e){t.addFieldOffset(6,e,0)}static createOutputsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startOutputsVector(t,e){t.startVector(4,e,4)}static addSparseInitializers(t,e){t.addFieldOffset(7,e,0)}static createSparseInitializersVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startSparseInitializersVector(t,e){t.startVector(4,e,4)}static endGraph(t){return t.endObject()}static createGraph(t,e,r,i,d,m,_,b,y){return c.startGraph(t),c.addInitializers(t,e),c.addNodeArgs(t,r),c.addNodes(t,i),c.addMaxNodeIndex(t,d),c.addNodeEdges(t,m),c.addInputs(t,_),c.addOutputs(t,b),c.addSparseInitializers(t,y),c.endGraph(t)}}g.Graph=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{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 c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsModel(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__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 u.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 u.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,m,_,b,y,T){return c.startModel(t),c.addIrVersion(t,e),c.addOpsetImport(t,r),c.addProducerName(t,i),c.addProducerVersion(t,d),c.addDomain(t,m),c.addModelVersion(t,_),c.addDocString(t,b),c.addGraph(t,y),c.addGraphDocString(t,T),c.endModel(t)}}g.Model=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{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 c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsKernelCreateInfos(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__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 c.startKernelCreateInfos(t),c.addNodeIndices(t,e),c.addKernelDefHashes(t,r),c.endKernelCreateInfos(t)}}g.KernelCreateInfos=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{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 c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSubGraphSessionState(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__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 u.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 c.startSubGraphSessionState(t),c.addGraphId(t,e),c.addSessionState(t,r),c.endSubGraphSessionState(t)}}g.SubGraphSessionState=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class 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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 c.startSessionState(t),c.addKernels(t,e),c.addSubGraphSessionStates(t,r),c.endSessionState(t)}}g.SessionState=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{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 c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsInferenceSession(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__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 u.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 u.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 c.startInferenceSession(t),c.addOrtVersion(t,e),c.addModel(t,r),c.addSessionState(t,i),c.endInferenceSession(t)}}g.InferenceSession=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={}))},7448:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.OnnxjsSessionHandler=void 0;const a=o(1670),l=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,u,h){const g=new Map;for(const t in p)if(Object.hasOwnProperty.call(p,t)){const e=p[t];g.set(t,new l.Tensor(e.dims,e.type,void 0,void 0,e.data))}const c=await this.session.run(g),s={};return c.forEach((t,e)=>{s[e]=new a.Tensor(t.type,t.data,t.dims)}),s}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Session=void 0;const a=o(7067),l=o(1296),p=o(7091),u=o(1036),h=o(6231),g=o(2644);n.Session=class{constructor(c={}){this._initialized=!1,this.backendHint=c.backendHint,this.profiler=h.Profiler.create(c.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(c,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 g.Model,typeof c=="string"){const r=c.endsWith(".ort");if(typeof fetch>"u"){const i=await(0,l.promisify)(a.readFile)(c);this.initialize(i,r)}else{const i=await fetch(c),d=await i.arrayBuffer();this.initialize(new Uint8Array(d),r)}}else if(ArrayBuffer.isView(c))this.initialize(c);else{const r=new 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${c.length}`)}else{if(c.size!==s.length)throw new Error(`incorrect input map size: expected ${s.length} but got ${c.size}`);const t=new Array(c.size);let e=0;for(let r=0;rtypeof O=="string")))throw new TypeError("cache should be a string array");E&&(this.cache=new Array(S))}else{if(T!==void 0){const O=e(_);if(!(T instanceof O))throw new TypeError(`cache should be type ${O.name}`)}if(E){const O=new ArrayBuffer(S*function(v){switch(v){case"bool":case"int8":case"uint8":return 1;case"int16":case"uint16":return 2;case"int32":case"uint32":case"float32":return 4;case"float64":return 8;default:throw new Error(`cannot calculate sizeof() on type ${v}`)}}(_));this.cache=function(v,M){return new(e(M))(v)}(O,_)}}}static fromProto(m){if(!m)throw new Error("cannot construct Value from an empty tensor");const _=g.ProtoUtil.tensorDataTypeFromProto(m.dataType),b=g.ProtoUtil.tensorDimsFromProto(m.dims),y=new s(b,_);if(_==="string")m.stringData.forEach((T,w)=>{y.data[w]=(0,g.decodeUtf8String)(T)});else 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in":TOKEN_TYPES.NotIn,true:TOKEN_TYPES.BooleanLiteral,false:TOKEN_TYPES.BooleanLiteral}),Token=class{constructor(f,n){this.value=f,this.type=n}};function isWord(f){return/\w/.test(f)}function isInteger(f){return/[0-9]/.test(f)}var ORDERED_MAPPING_TABLE=[["{%",TOKEN_TYPES.OpenStatement],["%}",TOKEN_TYPES.CloseStatement],["{{",TOKEN_TYPES.OpenExpression],["}}",TOKEN_TYPES.CloseExpression],["(",TOKEN_TYPES.OpenParen],[")",TOKEN_TYPES.CloseParen],["[",TOKEN_TYPES.OpenSquareBracket],["]",TOKEN_TYPES.CloseSquareBracket],[",",TOKEN_TYPES.Comma],[".",TOKEN_TYPES.Dot],[":",TOKEN_TYPES.Colon],["|",TOKEN_TYPES.Pipe],["<=",TOKEN_TYPES.ComparisonBinaryOperator],[">=",TOKEN_TYPES.ComparisonBinaryOperator],["==",TOKEN_TYPES.ComparisonBinaryOperator],["!=",TOKEN_TYPES.ComparisonBinaryOperator],["<",TOKEN_TYPES.ComparisonBinaryOperator],[">",TOKEN_TYPES.ComparisonBinaryOperator],["+",TOKEN_TYPES.AdditiveBinaryOperator],["-",TOKEN_TYPES.AdditiveBinaryOperator],["*",TOKEN_TYPES.MultiplicativeBinaryOperator],["/",TOKEN_TYPES.MultiplicativeBinaryOperator],["%",TOKEN_TYPES.MultiplicativeBinaryOperator],["=",TOKEN_TYPES.Equals]],ESCAPE_CHARACTERS=new Map([["n",` `],["t"," "],["r","\r"],["b","\b"],["f","\f"],["v","\v"],["'","'"],['"','"'],["\\","\\"]]);function tokenize(f){var p,u,h;const n=[],o=f;let a=0;const l=g=>{let c="";for(;g(o[a]);){if(o[a]==="\\"){if(++a,a>=o.length)throw new SyntaxError("Unexpected end of input");const s=o[a++],t=ESCAPE_CHARACTERS.get(s);if(t===void 0)throw new SyntaxError(`Unexpected escaped character: ${s}`);c+=t;continue}if(c+=o[a++],a>=o.length)throw new SyntaxError("Unexpected end of input")}return c};e:for(;a0){n.push(new Token(s,TOKEN_TYPES.Text));continue}}l(s=>/\s/.test(s));const c=o[a];if(c==="-"||c==="+"){const s=(u=n.at(-1))==null?void 0:u.type;if(s===TOKEN_TYPES.Text||s===void 0)throw new SyntaxError(`Unexpected character: ${c}`);switch(s){case TOKEN_TYPES.Identifier:case TOKEN_TYPES.NumericLiteral:case TOKEN_TYPES.BooleanLiteral:case TOKEN_TYPES.StringLiteral:case TOKEN_TYPES.CloseParen:case TOKEN_TYPES.CloseSquareBracket:break;default:{++a;const t=l(isInteger);n.push(new Token(`${c}${t}`,t.length>0?TOKEN_TYPES.NumericLiteral:TOKEN_TYPES.UnaryOperator));continue}}}for(const[s,t]of ORDERED_MAPPING_TABLE)if(o.slice(a,a+s.length)===s){n.push(new Token(s,t)),a+=s.length;continue e}if(c==="'"){++a;const s=l(t=>t!=="'");n.push(new Token(s,TOKEN_TYPES.StringLiteral)),++a;continue}if(isInteger(c)){const s=l(isInteger);n.push(new Token(s,TOKEN_TYPES.NumericLiteral));continue}if(isWord(c)){const s=l(isWord),t=Object.hasOwn(KEYWORDS,s)?KEYWORDS[s]:TOKEN_TYPES.Identifier;t===TOKEN_TYPES.In&&((h=n.at(-1))==null?void 0:h.type)===TOKEN_TYPES.Not?(n.pop(),n.push(new Token("not in",TOKEN_TYPES.NotIn))):n.push(new Token(s,t));continue}throw new SyntaxError(`Unexpected character: ${c}`)}return n}var Statement=class{constructor(){Z(this,"type","Statement")}},Program=class extends Statement{constructor(n){super();Z(this,"type","Program");this.body=n}},If=class extends Statement{constructor(n,o,a){super();Z(this,"type","If");this.test=n,this.body=o,this.alternate=a}},For=class extends Statement{constructor(n,o,a){super();Z(this,"type","For");this.loopvar=n,this.iterable=o,this.body=a}},SetStatement=class extends Statement{constructor(n,o){super();Z(this,"type","Set");this.assignee=n,this.value=o}},Expression=class extends Statement{constructor(){super(...arguments);Z(this,"type","Expression")}},MemberExpression=class extends Expression{constructor(n,o,a){super();Z(this,"type","MemberExpression");this.object=n,this.property=o,this.computed=a}},CallExpression=class extends Expression{constructor(n,o){super();Z(this,"type","CallExpression");this.callee=n,this.args=o}},Identifier=class extends Expression{constructor(n){super();Z(this,"type","Identifier");this.value=n}},Literal=class extends Expression{constructor(n){super();Z(this,"type","Literal");this.value=n}},NumericLiteral=class extends Literal{constructor(){super(...arguments);Z(this,"type","NumericLiteral")}},StringLiteral=class extends Literal{constructor(n){super(n);Z(this,"type","StringLiteral")}},BooleanLiteral=class extends Literal{constructor(){super(...arguments);Z(this,"type","BooleanLiteral")}},BinaryExpression=class extends Expression{constructor(n,o,a){super();Z(this,"type","BinaryExpression");this.operator=n,this.left=o,this.right=a}},FilterExpression=class extends Expression{constructor(n,o){super();Z(this,"type","FilterExpression");this.operand=n,this.filter=o}},UnaryExpression=class extends Expression{constructor(n,o){super();Z(this,"type","UnaryExpression");this.operator=n,this.argument=o}},SliceExpression=class extends Expression{constructor(n=void 0,o=void 0,a=void 0){super();Z(this,"type","SliceExpression");this.start=n,this.stop=o,this.step=a}};function parse(f){const n=new Program([]);let o=0;function a(D,L){const C=f[o++];if(!C||C.type!==D)throw new Error(`Parser Error: ${L}. ${C.type} !== ${D}.`);return C}function l(){switch(f[o].type){case TOKEN_TYPES.Text:return h();case TOKEN_TYPES.OpenStatement:return g();case TOKEN_TYPES.OpenExpression:return c();default:throw new SyntaxError(`Unexpected token type: ${f[o].type}`)}}function p(...D){return o+D.length<=f.length&&D.some((L,C)=>L!==f[o+C].type)}function u(...D){return o+D.length<=f.length&&D.every((L,C)=>L===f[o+C].type)}function h(){return new StringLiteral(a(TOKEN_TYPES.Text,"Expected text token").value)}function g(){a(TOKEN_TYPES.OpenStatement,"Expected opening statement token");let D;switch(f[o].type){case TOKEN_TYPES.Set:++o,D=s(),a(TOKEN_TYPES.CloseStatement,"Expected closing statement token");break;case TOKEN_TYPES.If:++o,D=t(),a(TOKEN_TYPES.OpenStatement,"Expected {% token"),a(TOKEN_TYPES.EndIf,"Expected endif token"),a(TOKEN_TYPES.CloseStatement,"Expected %} token");break;case TOKEN_TYPES.For:++o,D=e(),a(TOKEN_TYPES.OpenStatement,"Expected {% token"),a(TOKEN_TYPES.EndFor,"Expected endfor token"),a(TOKEN_TYPES.CloseStatement,"Expected %} token");break;default:throw new SyntaxError(`Unknown statement type: ${f[o].type}`)}return D}function c(){a(TOKEN_TYPES.OpenExpression,"Expected opening expression token");const D=r();return a(TOKEN_TYPES.CloseExpression,"Expected closing expression token"),D}function s(){const D=r();if(u(TOKEN_TYPES.Equals)){++o;const L=s();return new SetStatement(D,L)}return D}function t(){var U,N,j,J,Y,ee,te,de;const D=r();a(TOKEN_TYPES.CloseStatement,"Expected closing statement token");const L=[],C=[];for(;!(((U=f[o])==null?void 0:U.type)===TOKEN_TYPES.OpenStatement&&(((N=f[o+1])==null?void 0:N.type)===TOKEN_TYPES.ElseIf||((j=f[o+1])==null?void 0:j.type)===TOKEN_TYPES.Else||((J=f[o+1])==null?void 0:J.type)===TOKEN_TYPES.EndIf));)L.push(l());if(((Y=f[o])==null?void 0:Y.type)===TOKEN_TYPES.OpenStatement&&((ee=f[o+1])==null?void 0:ee.type)!==TOKEN_TYPES.EndIf)if(++o,u(TOKEN_TYPES.ElseIf))a(TOKEN_TYPES.ElseIf,"Expected elseif token"),C.push(t());else for(a(TOKEN_TYPES.Else,"Expected else token"),a(TOKEN_TYPES.CloseStatement,"Expected closing statement token");!(((te=f[o])==null?void 0:te.type)===TOKEN_TYPES.OpenStatement&&((de=f[o+1])==null?void 0:de.type)===TOKEN_TYPES.EndIf);)C.push(l());return new If(D,L,C)}function e(){const D=$();if(!(D instanceof Identifier))throw new SyntaxError("Expected identifier for the loop variable");a(TOKEN_TYPES.In,"Expected `in` keyword following loop variable");const L=r();a(TOKEN_TYPES.CloseStatement,"Expected closing statement token");const C=[];for(;p(TOKEN_TYPES.OpenStatement,TOKEN_TYPES.EndFor);)C.push(l());return new For(D,L,C)}function r(){return i()}function i(){let D=d();for(;u(TOKEN_TYPES.Or);){const L=f[o];++o;const C=d();D=new BinaryExpression(L,D,C)}return D}function d(){let D=m();for(;u(TOKEN_TYPES.And);){const L=f[o];++o;const C=m();D=new BinaryExpression(L,D,C)}return D}function m(){let D;for(;u(TOKEN_TYPES.Not);){const L=f[o];++o;const C=m();D=new UnaryExpression(L,C)}return D??_()}function _(){let D=b();for(;u(TOKEN_TYPES.ComparisonBinaryOperator)||u(TOKEN_TYPES.In)||u(TOKEN_TYPES.NotIn);){const L=f[o];++o;const C=b();D=new BinaryExpression(L,D,C)}return D}function b(){let D=v();for(;u(TOKEN_TYPES.AdditiveBinaryOperator);){const L=f[o];++o;const C=v();D=new BinaryExpression(L,D,C)}return D}function y(){const D=O();return u(TOKEN_TYPES.OpenParen)?T(D):D}function T(D){let L=new CallExpression(D,w());return u(TOKEN_TYPES.OpenParen)&&(L=T(L)),L}function w(){a(TOKEN_TYPES.OpenParen,"Expected opening parenthesis for arguments list");const D=u(TOKEN_TYPES.CloseParen)?[]:S();return a(TOKEN_TYPES.CloseParen,"Expected closing parenthesis for arguments list"),D}function S(){const D=[r()];for(;u(TOKEN_TYPES.Comma);)++o,D.push(r());return D}function E(){const D=[];let L=!1;for(;!u(TOKEN_TYPES.CloseSquareBracket);)u(TOKEN_TYPES.Colon)?(D.push(void 0),++o,L=!0):(D.push(r()),u(TOKEN_TYPES.Colon)&&(++o,L=!0));if(D.length===0)throw new SyntaxError("Expected at least one argument for member/slice expression");if(L){if(D.length>3)throw new SyntaxError("Expected 0-3 arguments for slice expression");return new SliceExpression(...D)}return D[0]}function O(){let D=$();for(;u(TOKEN_TYPES.Dot)||u(TOKEN_TYPES.OpenSquareBracket);){const L=f[o];++o;let C;const U=L.type!==TOKEN_TYPES.Dot;if(U)C=E(),a(TOKEN_TYPES.CloseSquareBracket,"Expected closing square bracket");else if(C=$(),C.type!=="Identifier")throw new SyntaxError("Expected identifier following dot operator");D=new MemberExpression(D,C,U)}return D}function v(){let D=M();for(;u(TOKEN_TYPES.MultiplicativeBinaryOperator);){const L=f[o];++o;const C=M();D=new BinaryExpression(L,D,C)}return D}function M(){let D=y();for(;u(TOKEN_TYPES.Pipe);){++o;const L=$();if(!(L instanceof Identifier))throw new SyntaxError("Expected identifier for the filter");D=new FilterExpression(D,L)}return D}function $(){const D=f[o];switch(D.type){case TOKEN_TYPES.NumericLiteral:return++o,new NumericLiteral(Number(D.value));case 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perform operation on null values");if(o instanceof NumericValue&&a instanceof NumericValue)switch(f.operator.value){case"+":return new NumericValue(o.value+a.value);case"-":return new NumericValue(o.value-a.value);case"*":return new NumericValue(o.value*a.value);case"/":return new NumericValue(o.value/a.value);case"%":return new NumericValue(o.value%a.value);case"<":return new BooleanValue(o.value":return new BooleanValue(o.value>a.value);case">=":return new BooleanValue(o.value>=a.value);case"<=":return new BooleanValue(o.value<=a.value)}else if(a instanceof ArrayValue){const l=a.value.find(p=>p.value===o.value)!==void 0;switch(f.operator.value){case"in":return new BooleanValue(l);case"not in":return new BooleanValue(!l)}}if(o instanceof StringValue||a instanceof StringValue)switch(f.operator.value){case"+":return new StringValue(o.value.toString()+a.value.toString())}if(o instanceof StringValue&&a instanceof StringValue)switch(f.operator.value){case"in":return new 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of f){const l=this.evaluate(a,n);l.type!=="NullValue"&&(o+=l.value)}return o=o.replace(/^\n/,""),new StringValue(o)}evaluateIdentifier(f,n){return n.lookupVariable(f.value)}evaluateCallExpression(f,n){const o=f.args.map(l=>this.evaluate(l,n)),a=this.evaluate(f.callee,n);if(a.type!=="FunctionValue")throw new Error(`Cannot call something that is not a function: got ${a.type}`);return a.value(o,n)}evaluateSliceExpression(f,n,o){if(!(f instanceof ArrayValue||f instanceof StringValue))throw new Error("Slice object must be an array or string");const a=this.evaluate(n.start,o),l=this.evaluate(n.stop,o),p=this.evaluate(n.step,o);if(!(a instanceof NumericValue||a instanceof UndefinedValue))throw new Error("Slice start must be numeric or undefined");if(!(l instanceof NumericValue||l instanceof UndefinedValue))throw new Error("Slice stop must be numeric or undefined");if(!(p instanceof NumericValue||p instanceof UndefinedValue))throw new Error("Slice step must be numeric or undefined");return f instanceof ArrayValue?new ArrayValue(slice(f.value,a.value,l.value,p.value)):new StringValue(slice(Array.from(f.value),a.value,l.value,p.value).join(""))}evaluateMemberExpression(f,n){const o=this.evaluate(f.object,n);let a;if(f.computed){if(f.property.type==="SliceExpression")return this.evaluateSliceExpression(o,f.property,n);a=this.evaluate(f.property,n)}else a=new StringValue(f.property.value);let l;if(o instanceof ObjectValue){if(!(a instanceof StringValue))throw new Error(`Cannot access property with non-string: got ${a.type}`);l=o.value.get(a.value)??o.builtins.get(a.value)}else if(o instanceof ArrayValue||o instanceof StringValue)if(a instanceof NumericValue)l=o.value.at(a.value),o instanceof StringValue&&(l=new StringValue(o.value.at(a.value)));else if(a instanceof StringValue)l=o.builtins.get(a.value);else throw new Error(`Cannot access property with non-string/non-number: got ${a.type}`);else{if(!(a instanceof StringValue))throw new Error(`Cannot access property with 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this.evaluateIf(f,n);case"For":return this.evaluateFor(f,n);case"NumericLiteral":return new NumericValue(Number(f.value));case"StringLiteral":return new StringValue(f.value);case"BooleanLiteral":return new BooleanValue(f.value);case"Identifier":return this.evaluateIdentifier(f,n);case"CallExpression":return this.evaluateCallExpression(f,n);case"MemberExpression":return this.evaluateMemberExpression(f,n);case"UnaryExpression":return this.evaluateUnaryExpression(f,n);case"BinaryExpression":return this.evaluateBinaryExpression(f,n);case"FilterExpression":return this.evaluateFilterExpression(f,n);default:throw new SyntaxError(`Unknown node type: ${f.type}`)}}};function convertToRuntimeValues(f){switch(typeof f){case"number":return new NumericValue(f);case"string":return new StringValue(f);case"boolean":return new BooleanValue(f);case"object":return f===null?new NullValue:Array.isArray(f)?new ArrayValue(f.map(convertToRuntimeValues)):new ObjectValue(new Map(Object.entries(f).map(([n,o])=>[n,convertToRuntimeValues(o)])));case"function":return new FunctionValue((n,o)=>{const a=f(...n.map(l=>l.value))??null;return convertToRuntimeValues(a)});default:throw new Error(`Cannot convert to runtime value: ${f}`)}}var Template=class{constructor(f){Z(this,"parsed");f=f.replace(/%}\s+{%/g,"%}{%");const n=tokenize(f);this.parsed=parse(n)}render(f){const n=new Environment;n.set("false",!1),n.set("true",!0),n.set("raise_exception",l=>{throw new Error(l)});for(const[l,p]of Object.entries(f))n.set(l,p);return new Interpreter(n).run(this.parsed).value}};async function loadTokenizer(f,n){const o=await Promise.all([getModelJSON(f,"tokenizer.json",!0,n),getModelJSON(f,"tokenizer_config.json",!0,n)]);return n.legacy!==null&&(o[1].legacy=n.legacy),o}function regexSplit(f,n){const o=[];let a=0;for(const l of f.matchAll(n)){const p=l[0];a0&&o.push(p),a=l.index+p.length}return athis.tokens_to_ids.get(o)??this.unk_token_id)}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=objectToMap(n.vocab),this.unk_token_id=this.tokens_to_ids.get(n.unk_token),this.unk_token=n.unk_token,this.max_input_chars_per_word=n.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[o,a]of this.tokens_to_ids)this.vocab[a]=o}encode(n){const o=[];for(const a of n){const l=[...a];if(l.length>this.max_input_chars_per_word){o.push(this.unk_token);continue}let p=!1,u=0;const h=[];for(;u0&&(s=this.config.continuing_subword_prefix+s),this.tokens_to_ids.has(s)){c=s;break}--g}if(c===null){p=!0;break}h.push(c),u=g}p?o.push(this.unk_token):o.push(...h)}return o}}class Unigram extends TokenizerModel{constructor(n,o){super(n);const a=n.vocab.length;this.vocab=new Array(a),this.scores=new Array(a);for(let l=0;l[l,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,a=o.length;let l=0;for(;l{const f=[...Array.from({length:"~".charCodeAt(0)-"!".charCodeAt(0)+1},(l,p)=>p+"!".charCodeAt(0)),...Array.from({length:"¬".charCodeAt(0)-"¡".charCodeAt(0)+1},(l,p)=>p+"¡".charCodeAt(0)),...Array.from({length:"ÿ".charCodeAt(0)-"®".charCodeAt(0)+1},(l,p)=>p+"®".charCodeAt(0))],n=f.slice();let o=0;for(let l=0;l<256;++l)f.includes(l)||(f.push(l),n.push(256+o),o+=1);const a=n.map(l=>String.fromCharCode(l));return Object.fromEntries(f.map((l,p)=>[l,a[p]]))})(),UNICODE_TO_BYTES=reverseDictionary(BYTES_TO_UNICODE);class BPE extends TokenizerModel{constructor(n){super(n),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=objectToMap(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,a]of this.tokens_to_ids)this.vocab[a]=o;this.bpe_ranks=new Map(n.merges.map((o,a)=>[o,a])),this.merges=n.merges.map(o=>o.split(this.BPE_SPLIT_TOKEN)),this.end_of_word_suffix=n.end_of_word_suffix,this.continuing_subword_suffix=n.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.cache=new Map}bpe(n){if(n.length===0)return[];const o=this.cache.get(n);if(o!==void 0)return o;const a=Array.from(n);this.end_of_word_suffix&&(a[a.length-1]+=this.end_of_word_suffix);let l=[];if(a.length>1){const p=new PriorityQueue((g,c)=>g.score`<0x${u.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=objectToMap(o.target_lang?n.vocab[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[a,l]of this.tokens_to_ids)this.vocab[l]=a}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"NFKC":return new NFKC(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: ${n.type}`)}}normalize(n){throw Error("normalize should be implemented in subclass.")}_call(n){return this.normalize(n)}}class Replace extends Normalizer{normalize(n){const o=createPattern(this.config.pattern);return o===null?n:n.replaceAll(o,this.config.content)}}class NFC extends Normalizer{normalize(n){return n=n.normalize("NFC"),n}}class NFKC extends Normalizer{normalize(n){return n=n.normalize("NFKC"),n}}class NFKD extends Normalizer{normalize(n){return n=n.normalize("NFKD"),n}}class StripNormalizer extends Normalizer{normalize(n){return this.config.strip_left&&this.config.strip_right?n=n.trim():(this.config.strip_left&&(n=n.trimStart()),this.config.strip_right&&(n=n.trimEnd())),n}}class StripAccents extends Normalizer{normalize(n){return n=remove_accents(n),n}}class Lowercase extends Normalizer{normalize(n){return n=n.toLowerCase(),n}}class Prepend extends Normalizer{normalize(n){return n=this.config.prepend+n,n}}class NormalizerSequence extends Normalizer{constructor(n){super(n),this.normalizers=n.normalizers.map(o=>Normalizer.fromConfig(o))}normalize(n){return this.normalizers.reduce((o,a)=>a.normalize(o),n)}}class BertNormalizer extends Normalizer{_tokenize_chinese_chars(n){const o=[];for(let a=0;a=19968&&n<=40959||n>=13312&&n<=19903||n>=131072&&n<=173791||n>=173824&&n<=177983||n>=177984&&n<=178207||n>=178208&&n<=183983||n>=63744&&n<=64255||n>=194560&&n<=195103}stripAccents(n){return n.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}_is_control(n){switch(n){case" ":case` `:case"\r":return!1;default:return/^\p{Cc}|\p{Cf}|\p{Co}|\p{Cs}$/u.test(n)}}_clean_text(n){const o=[];for(const a of n){const l=a.charCodeAt(0);l===0||l===65533||this._is_control(a)||(/^\s$/.test(a)?o.push(" "):o.push(a))}return o.join("")}normalize(n){return this.config.clean_text&&(n=this._clean_text(n)),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"Whitespace":return new WhitespacePreTokenizer(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);case"Replace":return new ReplacePreTokenizer(n);default:throw new Error(`Unknown PreTokenizer type: ${n.type}`)}}pre_tokenize_text(n,o){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(n,o){return(Array.isArray(n)?n.map(a=>this.pre_tokenize_text(a,o)):this.pre_tokenize_text(n,o)).flat()}_call(n,o){return this.pre_tokenize(n,o)}}class BertPreTokenizer extends PreTokenizer{constructor(n){super(),this.pattern=new RegExp(`[^\\s${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]`,"gu")}pre_tokenize_text(n,o){return n.trim().match(this.pattern)||[]}}class ByteLevelPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=/'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+/gu,this.byte_encoder=BYTES_TO_UNICODE,this.text_encoder=new TextEncoder}pre_tokenize_text(n,o){return this.add_prefix_space&&!n.startsWith(" ")&&(n=" "+n),(this.use_regex?n.match(this.pattern)||[]:[n]).map(l=>Array.from(this.text_encoder.encode(l),p=>this.byte_encoder[p]).join(""))}}class SplitPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=createPattern(this.config.pattern,this.config.invert)}pre_tokenize_text(n,o){return this.pattern===null?[]:this.config.invert?n.match(this.pattern)||[]:regexSplit(n,this.pattern)}}class PunctuationPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=new RegExp(`[^${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]+`,"gu")}pre_tokenize_text(n,o){return n.match(this.pattern)||[]}}class DigitsPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n;const o=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(o,"gu")}pre_tokenize_text(n,o){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);case"BertProcessing":return new BertProcessing(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 BertProcessing extends PostProcessor{constructor(n){super(n),this.cls=n.cls[0],this.sep=n.sep[0]}post_process(n,o=null,{add_special_tokens:a=!0}={}){a&&(n=mergeArrays([this.cls],n,[this.sep]));let l=new Array(n.length).fill(0);if(o!==null){const p=a&&this instanceof RobertaProcessing?[this.sep]:[],u=a?[this.sep]:[];n=mergeArrays(n,p,o,u),l=mergeArrays(l,new Array(o.length+p.length+u.length).fill(1))}return{tokens:n,token_type_ids:l}}}class RobertaProcessing extends BertProcessing{}class TemplateProcessing extends PostProcessor{constructor(n){super(n),this.single=n.single,this.pair=n.pair}post_process(n,o=null,{add_special_tokens:a=!0}={}){const l=o===null?this.single:this.pair;let p=[],u=[];for(const h of l)"SpecialToken"in h?a&&(p.push(h.SpecialToken.id),u.push(h.SpecialToken.type_id)):"Sequence"in h&&(h.Sequence.id==="A"?(p=mergeArrays(p,n),u=mergeArrays(u,new Array(n.length).fill(h.Sequence.type_id))):h.Sequence.id==="B"&&(p=mergeArrays(p,o),u=mergeArrays(u,new Array(o.length).fill(h.Sequence.type_id))));return{tokens:p,token_type_ids:u}}}class ByteLevelPostProcessor extends PostProcessor{post_process(n,o=null){return o&&(n=mergeArrays(n,o)),{tokens: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){if(n===null)return null;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);case"BPEDecoder":return new BPEDecoder(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){const o=createPattern(this.config.pattern);return o===null?n:n.map(a=>a.replaceAll(o,this.config.content))}}class ByteFallback extends Decoder{constructor(n){super(n),this.text_decoder=new TextDecoder}decode_chain(n){const o=[];let a=[];for(const l of n){let p=null;if(l.length===6&&l.startsWith("<0x")&&l.endsWith(">")){const u=parseInt(l.slice(3,5),16);isNaN(u)||(p=u)}if(p!==null)a.push(p);else{if(a.length>0){const u=this.text_decoder.decode(Uint8Array.from(a));o.push(u),a=[]}o.push(l)}}if(a.length>0){const l=this.text_decoder.decode(Uint8Array.from(a));o.push(l),a=[]}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 a=0;for(let p=0;p(a!==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){const o=n.join(""),a=new Uint8Array([...o].map(p=>this.byte_decoder[p]));return this.text_decoder.decode(a)}decode_chain(n){const o=[];let a=[];for(const l of n)this.added_tokens.find(p=>p.content===l)!==void 0?(a.length>0&&(o.push(this.convert_tokens_to_string(a)),a=[]),o.push(l)):a.push(l);return a.length>0&&o.push(this.convert_tokens_to_string(a)),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"";const o=[n[0]];for(let p=1;pp!==this.pad_token).join("");return this.cleanup&&(l=clean_up_tokenization(l).replaceAll(this.word_delimiter_token," ").trim()),l}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,a)=>a.decode_chain(o),n)}}class BPEDecoder extends Decoder{constructor(n){super(n),this.suffix=this.config.suffix}decode_chain(n){return n.map((o,a)=>o.replaceAll(this.suffix,a===n.length-1?"":" "))}}class VitsDecoder extends Decoder{decode_chain(n){let o="";for(let a=1;aa.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,o){return this.tokenizers.reduce((a,l)=>l.pre_tokenize(a,o),[n])}}class WhitespacePreTokenizer extends PreTokenizer{constructor(n){super()}pre_tokenize_text(n,o){return n.match(/\w+|[^\w\s]+/g)||[]}}class WhitespaceSplit extends PreTokenizer{constructor(n){super()}pre_tokenize_text(n,o){return whitespace_split(n)}}class ReplacePreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=createPattern(this.config.pattern),this.content=this.config.content}pre_tokenize_text(n,o){return this.pattern===null?[n]:[n.replaceAll(this.pattern,this.config.content)]}}const SPECIAL_TOKEN_ATTRIBUTES=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function padHelper(f,n,o,a){for(const l of Object.keys(f)){const p=n-f[l].length,u=o(l),h=new Array(p).fill(u);f[l]=a==="right"?mergeArrays(f[l],h):mergeArrays(h,f[l])}}function truncateHelper(f,n){for(const o of Object.keys(f))f[o].length=n}class PreTrainedTokenizer extends Callable{constructor(o,a){super();Z(this,"return_token_type_ids",!1);Z(this,"_default_chat_template",`{% for message in messages %}{{'<|im_start|>' + message['role'] + ' ' + message['content'] + '<|im_end|>' + ' '}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant ' }}{% endif %}`);this._tokenizer_config=a,this.normalizer=Normalizer.fromConfig(o.normalizer),this.pre_tokenizer=PreTokenizer.fromConfig(o.pre_tokenizer),this.model=TokenizerModel.fromConfig(o.model,a),this.post_processor=PostProcessor.fromConfig(o.post_processor),this.decoder=Decoder.fromConfig(o.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(const l of o.added_tokens){const p=new AddedToken(l);this.added_tokens.push(p),this.model.tokens_to_ids.set(p.content,p.id),this.model.vocab[p.id]=p.content,p.special&&(this.special_tokens.push(p.content),this.all_special_ids.push(p.id))}this.additional_special_tokens=a.additional_special_tokens??[],this.special_tokens.push(...this.additional_special_tokens),this.special_tokens=[...new Set(this.special_tokens)],this.decoder&&(this.decoder.added_tokens=this.added_tokens,this.decoder.end_of_word_suffix=this.model.end_of_word_suffix),this.added_tokens_regex=this.added_tokens.length>0?new RegExp(this.added_tokens.map(l=>`${l.lstrip?"\\s*":""}(${escapeRegExp(l.content)})${l.rstrip?"\\s*":""}`).join("|")):null,this.mask_token=this.getToken("mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken("pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken("sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.unk_token=this.getToken("unk_token"),this.unk_token_id=this.model.tokens_to_ids.get(this.unk_token),this.model_max_length=a.model_max_length,this.remove_space=a.remove_space,this.clean_up_tokenization_spaces=a.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=a.do_lowercase_and_remove_accent??!1,this.padding_side="right",this.legacy=!1,this.chat_template=a.chat_template??null,this._compiled_template_cache=new Map}getToken(...o){for(const a of o){const l=this._tokenizer_config[a];if(l)if(typeof l=="object"){if(l.__type==="AddedToken")return l.content;throw Error(`Unknown token: ${l}`)}else return l}return null}static async from_pretrained(o,{progress_callback:a=null,config:l=null,cache_dir:p=null,local_files_only:u=!1,revision:h="main",legacy:g=null}={}){const c=await loadTokenizer(o,{progress_callback:a,config:l,cache_dir:p,local_files_only:u,revision:h,legacy:g});return new this(...c)}_call(o,{text_pair:a=null,add_special_tokens:l=!0,padding:p=!1,truncation:u=null,max_length:h=null,return_tensor:g=!0}={}){const c=Array.isArray(o);let s;if(c){if(o.length===0)throw Error("text array must be non-empty");if(a!==null){if(Array.isArray(a)){if(o.length!==a.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");s=o.map((e,r)=>this._encode_plus(e,a[r],{add_special_tokens:l}))}else s=o.map(e=>this._encode_plus(e,null,{add_special_tokens:l}))}else{if(o===null)throw Error("text may not be null");if(Array.isArray(a))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");s=[this._encode_plus(o,a,{add_special_tokens:l})]}if(h===null?p==="max_length"?h=this.model_max_length:h=max(s.map(e=>e.input_ids.length))[0]:u||console.warn("Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation=true` to explicitly truncate examples to max length."),h=Math.min(h,this.model_max_length),p||u)for(let e=0;eh?u&&truncateHelper(s[e],h):p&&padHelper(s[e],h,r=>r==="input_ids"?this.pad_token_id:0,this.padding_side));const t={};if(g){if(!(p&&u)&&s.some(r=>{var i;for(const d of Object.keys(r))if(r[d].length!==((i=s[0][d])==null?void 0:i.length))return!0;return!1}))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");const e=[s.length,s[0].input_ids.length];for(const r of Object.keys(s[0]))t[r]=new Tensor("int64",BigInt64Array.from(s.flatMap(i=>i[r]).map(BigInt)),e)}else{for(const e of Object.keys(s[0]))t[e]=s.map(r=>r[e]);if(!c)for(const e of Object.keys(t))t[e]=t[e][0]}return t}_encode_text(o){return o===null?null:(this.added_tokens_regex?o.split(this.added_tokens_regex).filter(p=>p):[o]).map((p,u)=>{if(this.added_tokens.find(g=>g.content===p)!==void 0)return p;{if(this.remove_space===!0&&(p=p.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(p=lowercase_and_remove_accent(p)),this.normalizer!==null&&(p=this.normalizer(p)),p.length===0)return[];const g=this.pre_tokenizer!==null?this.pre_tokenizer(p,{section_index:u}):[p];return this.model(g)}}).flat()}_encode_plus(o,a=null,{add_special_tokens:l=!0}={}){const p=this._encode_text(o),u=this._encode_text(a),h=this.post_processor?this.post_processor(p,u,{add_special_tokens:l}):{tokens:mergeArrays(p??[],u??[])},g=this.model.convert_tokens_to_ids(h.tokens),c={input_ids:g,attention_mask:new Array(g.length).fill(1)};return this.return_token_type_ids&&h.token_type_ids&&(c.token_type_ids=h.token_type_ids),c}encode(o,a=null,{add_special_tokens:l=!0}={}){const{input_ids:p}=this._encode_plus(o,a,{add_special_tokens:l});return p}batch_decode(o,a={}){return o instanceof Tensor&&(o=o.tolist()),o.map(l=>this.decode(l,a))}decode(o,a={}){if(o instanceof Tensor&&(o=prepareTensorForDecode(o)),!Array.isArray(o)||o.length===0||!isIntegralNumber(o[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(o,a)}decode_single(o,{skip_special_tokens:a=!1,clean_up_tokenization_spaces:l=null}){let p=this.model.convert_ids_to_tokens(o);a&&(p=p.filter(h=>!this.special_tokens.includes(h)));let u=this.decoder?this.decoder(p):p.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(u=u.replaceAll(this.decoder.end_of_word_suffix," "),a&&(u=u.trim())),(l??this.clean_up_tokenization_spaces)&&(u=clean_up_tokenization(u)),u}get default_chat_template(){return this._warned_about_chat_template||(console.warn("No chat template is defined for this tokenizer - using a default chat template that implements the ChatML format. If the default is not appropriate for your model, please set `tokenizer.chat_template` to an appropriate template. See https://huggingface.co/docs/transformers/main/chat_templating for more information."),this._warned_about_chat_template=!0),this._default_chat_template}apply_chat_template(o,{chat_template:a=null,add_generation_prompt:l=!1,tokenize:p=!0,padding:u=!1,truncation:h=!1,max_length:g=null,return_tensor:c=!0}={}){a??(a=this.chat_template??this.default_chat_template);let s=this._compiled_template_cache.get(a);s===void 0&&(s=new Template(a),this._compiled_template_cache.set(a,s));const t=Object.create(null);for(const r of SPECIAL_TOKEN_ATTRIBUTES){const i=this.getToken(r);i&&(t[r]=i)}const e=s.render({messages:o,add_generation_prompt:l,...t});return p?this._call(e,{add_special_tokens:!1,padding:u,truncation:h,max_length:g,return_tensor:c}).input_ids:e}}class BertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class AlbertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class MobileBertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class SqueezeBertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class DebertaTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class DebertaV2Tokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class HerbertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class ConvBertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class RoFormerTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class DistilBertTokenizer extends PreTrainedTokenizer{}class CamembertTokenizer extends PreTrainedTokenizer{}class XLMTokenizer extends PreTrainedTokenizer{constructor(o,a){super(o,a);Z(this,"return_token_type_ids",!0);console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}}class ElectraTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class T5Tokenizer extends PreTrainedTokenizer{}class GPT2Tokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"_default_chat_template",'{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}')}}class BartTokenizer extends PreTrainedTokenizer{}class MBartTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter(a=>this.languageRegex.test(a)),this.lang_to_token=a=>a}_build_translation_inputs(n,o,a){return _build_translation_inputs(this,n,o,a)}}class MBart50Tokenizer extends MBartTokenizer{}class RobertaTokenizer extends PreTrainedTokenizer{}class BloomTokenizer extends GPT2Tokenizer{constructor(n,o){var p,u;const a=".,!?…。,、।۔،",l=(u=(p=n.pre_tokenizer)==null?void 0:p.pretokenizers[0])==null?void 0:u.pattern;l&&l.Regex===` ?[^(\\s|[${a}])]+`&&(l.Regex=` ?[^\\s${a}]+`),super(n,o)}}const SPIECE_UNDERLINE="▁";class LlamaTokenizer extends PreTrainedTokenizer{constructor(o,a){super(o,a);Z(this,"_default_chat_template",`{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif USE_DEFAULT_PROMPT == true and not '<>' in messages[0]['content'] %}{% set loop_messages = messages %}{% set system_message = 'DEFAULT_SYSTEM_MESSAGE' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<> ' + system_message + ' <> ' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'system' %}{{ '<> ' + content.strip() + ' <> ' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}`);Z(this,"DEFAULT_SYSTEM_PROMPT",`You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.`);this.use_default_system_prompt=a.use_default_system_prompt??!1,this.legacy=a.legacy??!0,this.legacy||(this.normalizer=null,this.pre_tokenizer=new MetaspacePreTokenizer({replacement:SPIECE_UNDERLINE,add_prefix_space:!0,prepend_scheme:"first"}))}_encode_text(o){if(o===null)return null;if(this.legacy||o.length===0)return super._encode_text(o);let a=super._encode_text(SPIECE_UNDERLINE+o.replaceAll(SPIECE_UNDERLINE," "));return a.length>1&&a[0]===SPIECE_UNDERLINE&&this.special_tokens.includes(a[1])&&(a=a.slice(1)),a}get default_chat_template(){return super.default_chat_template.replaceAll("USE_DEFAULT_PROMPT",this.use_default_system_prompt?"true":"false").replaceAll("DEFAULT_SYSTEM_MESSAGE",this.DEFAULT_SYSTEM_PROMPT.replaceAll(` `,"\\n").replaceAll("'","\\'"))}}class CodeLlamaTokenizer extends LlamaTokenizer{}class XLMRobertaTokenizer extends PreTrainedTokenizer{}class MPNetTokenizer extends PreTrainedTokenizer{}class FalconTokenizer extends PreTrainedTokenizer{}class GPTNeoXTokenizer extends PreTrainedTokenizer{}class EsmTokenizer extends PreTrainedTokenizer{}class Qwen2Tokenizer extends PreTrainedTokenizer{}class GemmaTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"_default_chat_template",`{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '' + role + ' ' + message['content'] | trim + ' ' }}{% endfor %}{% if add_generation_prompt %}{{'model '}}{% endif %}`)}}function _build_translation_inputs(f,n,o,a){if(!("language_codes"in f)||!Array.isArray(f.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in f)||!(f.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in f)||typeof f.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const l=a.src_lang,p=a.tgt_lang;if(!f.language_codes.includes(p))throw new Error(`Target language code "${p}" is not valid. Must be one of: {${f.language_codes.join(", ")}}`);if(l!==void 0){if(!f.language_codes.includes(l))throw new Error(`Source language code "${l}" is not valid. Must be one of: {${f.language_codes.join(", ")}}`);for(const u of f.post_processor.config.single)if("SpecialToken"in u&&f.languageRegex.test(u.SpecialToken.id)){u.SpecialToken.id=f.lang_to_token(l);break}}return a.forced_bos_token_id=f.model.convert_tokens_to_ids([f.lang_to_token(p)])[0],f._call(n,o)}class NllbTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(a=>this.languageRegex.test(a)),this.lang_to_token=a=>a}_build_translation_inputs(n,o,a){return _build_translation_inputs(this,n,o,a)}}class M2M100Tokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(a=>this.languageRegex.test(a)).map(a=>a.slice(2,-2)),this.lang_to_token=a=>`__${a}__`}_build_translation_inputs(n,o,a){return _build_translation_inputs(this,n,o,a)}}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(([f,n])=>[n,f]),["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{constructor(){super(...arguments);Z(this,"_default_chat_template",'{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}')}_decode_asr(o,{return_timestamps:a=!1,return_language:l=!1,time_precision:p=null,force_full_sequences:u=!0}={}){if(p===null)throw Error("Must specify time_precision");let h=null;const g=a==="word";function c(){return{language:h,timestamp:[null,null],text:""}}const s=[];let t=c(),e=0;const r=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let i=[],d=[],m=!1,_=null;const b=new Set(this.all_special_ids);for(const w of o){const S=w.tokens,E=g?w.token_timestamps:null;let O=null,v=r;if("stride"in w){const[D,L,C]=w.stride;if(e-=L,_=D-C,L&&(v=L/p+r),C)for(let U=S.length-1;U>=0;--U){const N=S[U];if(N>=r){if(O!==null&&(N-r)*p<_)break;O=N}}}let M=[],$=[];for(let D=0;D=r){const C=(L-r)*p+e,U=round(C,2);if(O!==null&&L>=O)m=!0;else if(m||i.length>0&&L0?(i.push(M),g&&d.push($)):i.every(D=>D.length===0)&&(t=c(),i=[],M=[],d=[],$=[])}if(i.length>0){if(u&&a)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,S]=this.findLongestCommonSequence(i,d),E=this.decode(w);t.text=E,g&&(t.words=this.collateWordTimestamps(w,S,h)),s.push(t)}let y=Object.create(null);const T=s.map(w=>w.text).join("");if(a||l){for(let w=0;w0;let g=h?[]:null,c=h?a[0]:null;for(let s=1;sU===D[N]).length,C=L/w+S;L>1&&C>e&&(e=C,r=[E,O,M,$])}const[d,m,_,b]=r,y=Math.floor((m+d)/2),T=Math.floor((b+_)/2);u.push(...l.slice(0,y)),l=t.slice(T),p=l.length,h&&(g.push(...c.slice(0,y)),c=a[s].slice(T))}return u.push(...l),h?(g.push(...c),[u,g]):[u,[]]}collateWordTimestamps(o,a,l){const[p,u,h]=this.combineTokensIntoWords(o,l),g=[];for(let c=0;c=p){const g=round((h-p)*l,2);u.push(`<|${g}|>`),u.push([])}else u[u.length-1].push(h);return u=u.map(h=>typeof h=="string"?h:super.decode(h,a)),u.join("")}splitTokensOnUnicode(o){const a=this.decode(o,{decode_with_timestamps:!0}),l="�",p=[],u=[],h=[];let g=[],c=[],s=0;for(let t=0;t=this.model.tokens_to_ids.get("<|endoftext|>"),d=t.startsWith(" "),m=t.trim(),_=c.test(m);if(i||d||_||u.length===0)u.push(t),h.push(e),g.push(r);else{const b=u.length-1;u[b]+=t,h[b].push(...e),g[b].push(...r)}}return[u,h,g]}mergePunctuations(o,a,l,p,u){const h=structuredClone(o),g=structuredClone(a),c=structuredClone(l);let s=h.length-2,t=h.length-1;for(;s>=0;)h[s].startsWith(" ")&&p.includes(h[s].trim())?(h[t]=h[s]+h[t],g[t]=mergeArrays(g[s],g[t]),c[t]=mergeArrays(c[s],c[t]),h[s]="",g[s]=[],c[s]=[]):t=s,--s;for(s=0,t=1;te),g.filter(e=>e.length>0),c.filter(e=>e.length>0)]}get_decoder_prompt_ids({language:o=null,task:a=null,no_timestamps:l=!0}={}){const p=[];if(o){o=o.toLowerCase();let u=WHISPER_TO_LANGUAGE_CODE_MAPPING.get(o);if(u===void 0)if(WHISPER_LANGUAGE_MAPPING.has(o))u=o;else{const c=o.length===2?WHISPER_LANGUAGE_MAPPING.keys():WHISPER_LANGUAGE_MAPPING.values();throw new Error(`Language "${o}" is not supported. Must be one of: ${JSON.stringify(c)}`)}const h=this.model.tokens_to_ids.get(`<|${u}|>`);if(h===void 0)throw new Error(`Unable to find language "${u}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);p.push(h)}else p.push(null);if(a){if(a=a.toLowerCase(),a!=="transcribe"&&a!=="translate")throw new Error(`Task "${a}" is not supported. Must be one of: ["transcribe", "translate"]`);const u=this.model.tokens_to_ids.get(`<|${a}|>`);if(u===void 0)throw new Error(`Unable to find task "${a}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);p.push(u)}else p.push(null);if(l){const u=this.model.tokens_to_ids.get("<|notimestamps|>");if(u===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.');p.push(u)}return p.map((u,h)=>[h+1,u]).filter(u=>u[1]!==null)}}class CodeGenTokenizer extends PreTrainedTokenizer{}class CLIPTokenizer extends PreTrainedTokenizer{}class SiglipTokenizer 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(a=>this.languageRegex.test(a)),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;const[o,...a]=n.trim().split(this.languageRegex);if(a.length===0)return super._encode_text(o);if(a.length===2){const[l,p]=a;return this.supported_language_codes.includes(l)||console.warn(`Unsupported language code "${l}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),mergeArrays([l],super._encode_text(p))}}}class Wav2Vec2CTCTokenizer extends PreTrainedTokenizer{}class BlenderbotTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"_default_chat_template","{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ ' ' }}{% endif %}{% endfor %}{{ eos_token }}")}}class BlenderbotSmallTokenizer extends BlenderbotTokenizer{}class SpeechT5Tokenizer extends PreTrainedTokenizer{}class NougatTokenizer extends PreTrainedTokenizer{}class VitsTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.decoder=new VitsDecoder({})}}class AutoTokenizer{static async from_pretrained(n,{quantized:o=!0,progress_callback:a=null,config:l=null,cache_dir:p=null,local_files_only:u=!1,revision:h="main",legacy:g=null}={}){var r;const[c,s]=await loadTokenizer(n,{quantized:o,progress_callback:a,config:l,cache_dir:p,local_files_only:u,revision:h,legacy:g}),t=((r=s.tokenizer_class)==null?void 0:r.replace(/Fast$/,""))??"PreTrainedTokenizer";let e=this.TOKENIZER_CLASS_MAPPING[t];return e||(console.warn(`Unknown tokenizer class "${t}", attempting to construct from base class.`),e=PreTrainedTokenizer),new e(c,s)}}Z(AutoTokenizer,"TOKENIZER_CLASS_MAPPING",{T5Tokenizer,DistilBertTokenizer,CamembertTokenizer,DebertaTokenizer,DebertaV2Tokenizer,BertTokenizer,HerbertTokenizer,ConvBertTokenizer,RoFormerTokenizer,XLMTokenizer,ElectraTokenizer,MobileBertTokenizer,SqueezeBertTokenizer,AlbertTokenizer,GPT2Tokenizer,BartTokenizer,MBartTokenizer,MBart50Tokenizer,RobertaTokenizer,WhisperTokenizer,CodeGenTokenizer,CLIPTokenizer,SiglipTokenizer,MarianTokenizer,BloomTokenizer,NllbTokenizer,M2M100Tokenizer,LlamaTokenizer,CodeLlamaTokenizer,XLMRobertaTokenizer,MPNetTokenizer,FalconTokenizer,GPTNeoXTokenizer,EsmTokenizer,Wav2Vec2CTCTokenizer,BlenderbotTokenizer,BlenderbotSmallTokenizer,SpeechT5Tokenizer,NougatTokenizer,VitsTokenizer,Qwen2Tokenizer,GemmaTokenizer,PreTrainedTokenizer});async function loadConfig(f,n){return await getModelJSON(f,"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:a=null,cache_dir:l=null,local_files_only:p=!1,revision:u="main"}={}){let h=a??await loadConfig(n,{progress_callback:o,config:a,cache_dir:l,local_files_only:p,revision:u});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 a of o)this.processors.forEach(l=>l(n,a))}[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 a=this.force_token_map[n.length];return exists(a)&&(o.data.fill(-1/0),o.data[a]=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 a of this.begin_suppress_tokens)o.data[a]=-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){const a=o.data;if(a[this.no_timestamps_token_id]=-1/0,n.length===this.begin_index-1)return a.fill(-1/0),a[this.timestamp_begin]=0,o;const l=n.slice(this.begin_index),p=l.length>=1&&l[l.length-1]>=this.timestamp_begin,u=l.length<2||l[l.length-2]>=this.timestamp_begin;if(p&&(u?a.subarray(this.timestamp_begin).fill(-1/0):a.subarray(0,this.eos_token_id).fill(-1/0)),n.length===this.begin_index&&this.max_initial_timestamp_index!==null){const s=this.timestamp_begin+this.max_initial_timestamp_index;a.subarray(s+1).fill(-1/0)}const h=log_softmax(a),g=Math.log(h.subarray(this.timestamp_begin).map(Math.exp).reduce((s,t)=>s+t)),c=max(h.subarray(0,this.timestamp_begin))[0];return g>c&&a.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,a=[];for(let p=0;p0&&(l=l.map(p=>p/this.generation_config.temperature)),l}randomSelect(n){let o=n.reduce((l,p)=>l+p,0),a=Math.random()*o;for(let l=0;l1)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 ${n.num_return_sequences}.`);return new GreedySampler(n)}}class GreedySampler extends Sampler{sample(n,o=-1){let a=this.getLogits(n,o);return[[max(a)[1],0]]}}class MultinomialSampler extends Sampler{sample(n,o=-1){let a=n.dims.at(-1);this.generation_config.top_k>0&&(a=Math.min(this.generation_config.top_k,a));const l=this.getLogits(n,o),p=getTopItems(l,a),u=softmax(p.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},()=>{const h=this.randomSelect(u);return[p[h][0],Math.log(u[h])]})}}class BeamSearchSampler extends Sampler{sample(n,o=-1){let a=n.dims.at(-1);this.generation_config.top_k>0&&(a=Math.min(this.generation_config.top_k,a));const l=this.getLogits(n,o),p=getTopItems(l,a),u=softmax(p.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},(h,g)=>[p[g][0],Math.log(u[g])])}}const{InferenceSession,Tensor:ONNXTensor,env}=ONNX,MODEL_TYPES={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4,MaskGeneration:5},MODEL_TYPE_MAPPING=new Map,MODEL_NAME_TO_CLASS_MAPPING=new Map,MODEL_CLASS_TO_NAME_MAPPING=new Map;async function constructSession(f,n,o){let a=`onnx/${n}${o.quantized?"_quantized":""}.onnx`,l=await getModelFile(f,a,!0,o);try{return await InferenceSession.create(l,{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(l,{executionProviders:["wasm"]})}}function validateInputs(f,n){const o=Object.create(null),a=[];for(const u of f.inputNames){const h=n[u];if(!(h instanceof Tensor)){a.push(u);continue}o[u]=env.wasm.proxy?h.clone():h}if(a.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${a.join(", ")}.`);const l=Object.keys(n).length,p=f.inputNames.length;if(l>p){let u=Object.keys(n).filter(h=>!f.inputNames.includes(h));console.warn(`WARNING: Too many inputs were provided (${l} > ${p}). The following inputs will be ignored: "${u.join(", ")}".`)}return o}async function sessionRun(f,n){const o=validateInputs(f,n);try{let a=await f.run(o);return a=replaceTensors(a),a}catch(a){throw console.error(`An error occurred during model execution: "${a}".`),console.error("Inputs given to model:",o),a}}function replaceTensors(f){for(let n in f)f[n]instanceof ONNXTensor?f[n]=new Tensor(f[n]):typeof f[n]=="object"&&replaceTensors(f[n]);return f}function toI64Tensor(f){if(f instanceof Tensor)return f;if(f.length===0)throw Error("items must be non-empty");if(Array.isArray(f[0])){if(f.some(n=>n.length!==f[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(f.flat().map(n=>BigInt(n))),[f.length,f[0].length])}else return new Tensor("int64",BigInt64Array.from(f.map(n=>BigInt(n))),[1,f.length])}function prepareAttentionMask(f,n){let o=f.config.pad_token_id??null,a=f.config.eos_token_id??null;isIntegralNumber(a)&&(a=[a]);let l=n.indexOf(o)!==-1,p=a===null||!a.includes(o);if(l&&p){let u=BigInt64Array.from(n.data.map(h=>h!=o));return new Tensor("int64",u,n.dims)}else return ones_like(n)}function preparePositionIds(f,n,o){if(!f.inputNames.includes("position_ids"))return;const a=new BigInt64Array(n.attention_mask.data.length);for(let l=0;l0&&p.push(new NoRepeatNGramLogitsProcessor(o.no_repeat_ngram_size)),o.bad_words_ids!==null&&p.push(new NoBadWordsLogitsProcessor(o.bad_words_ids,o.eos_token_id)),o.min_length!==null&&o.eos_token_id!==null&&o.min_length>0&&p.push(new MinLengthLogitsProcessor(o.min_length,o.eos_token_id)),o.min_new_tokens!==null&&o.eos_token_id!==null&&o.min_new_tokens>0&&p.push(new MinNewTokensLengthLogitsProcessor(a,o.min_new_tokens,o.eos_token_id)),o.forced_bos_token_id!==null&&p.push(new ForcedBOSTokenLogitsProcessor(o.forced_bos_token_id)),o.forced_eos_token_id!==null&&p.push(new ForcedEOSTokenLogitsProcessor(o.max_length,o.forced_eos_token_id)),o.begin_suppress_tokens!==null){let u=a>1||o.forced_bos_token_id===null?a:a+1;o.forced_decoder_ids!==null&&(u+=o.forced_decoder_ids[o.forced_decoder_ids.length-1][0]),p.push(new SuppressTokensAtBeginLogitsProcessor(o.begin_suppress_tokens,u))}return o.forced_decoder_ids!==null&&p.push(new ForceTokensLogitsProcessor(o.forced_decoder_ids)),l!==null&&p.extend(l),p}_get_generation_config(o){let a=new GenerationConfig(this.config);return"generation_config"in this&&Object.assign(a,this.generation_config),o!==null&&Object.assign(a,o),a}async generate(o,a=null,l=null,{inputs_attention_mask:p=null}={}){if(!this.can_generate){let _=`The current model class (${MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const b=this.config.model_type,y=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(b)??MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES.get(b)??MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES.get(b)??MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES.get(b);throw y&&(_+=` Please use the following class instead: '${y[0]}'`),Error(_)}if(!(o instanceof Tensor)&&!isTypedArray(o)&&!Array.isArray(o))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${o.constructor.name}".`);let u;if(this.config.is_encoder_decoder)u=0;else if(u=o instanceof Tensor?o.dims.at(-1):o.length,u===0)throw Error("Must supply a non-empty array of input token ids.");a=this._get_generation_config(a),l=l??new LogitsProcessorList,l=this._get_logits_processor(a,u,l);let h=a.eos_token_id;h!==null&&!Array.isArray(h)&&(h=[h]);let g=1;const c=g+(a.max_new_tokens??1/0),s=Number.isInteger(a.max_length)&&(a.max_new_tokens??null)===null;let t=Sampler.getSampler(a),e=this.getStartBeams(o,a,g,p);for(;e.some(m=>!m.done)&&g=a.max_length){_.done=!0,m.push(_);continue}let b=await this.runBeam(_);a.output_attentions&&this.addAttentionsToBeam(_,b),a.output_scores;let y=b.logits.slice(null,-1,null);l(_.output_token_ids,y);let T=t(y);for(let[w,S]of T){let E={..._};this.updateBeam(E,w),E.score+=S,h&&h.includes(w)&&(E.done=!0),m.push(E)}}++g,m=this.groupBeams(m).map(_=>_.sort((b,y)=>y.score-b.score).slice(0,a.num_beams)),e=m.flat(),a.callback_function&&a.callback_function(e)}const r=this.groupBeams(e),i=m=>r.map(_=>a.num_return_sequences>1?_.slice(0,a.num_return_sequences).map(b=>b[m]):[_[0][m]]).flat(),d=i("output_token_ids");if(a.return_dict_in_generate){const m=i("decoder_attentions"),_=i("cross_attentions");return{sequences:d,decoder_attentions:m,cross_attentions:_}}else return d}addAttentionsToBeam(o,a){if(this.config.is_encoder_decoder){if(!a.cross_attentions||a.cross_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce cross-attentions. This is most likely because the model was not exported with `output_attentions=True`.");o.cross_attentions||(o.cross_attentions=[]),o.cross_attentions.push(a.cross_attentions)}if(!a.decoder_attentions||a.decoder_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce decoder-attentions. This is most likely because the model was not exported with `output_attentions=True`.");o.decoder_attentions||(o.decoder_attentions=[]),o.decoder_attentions.push(a.decoder_attentions)}groupBeams(o){const a=Object.create(null);for(const l of o)a[l.id]===void 0?a[l.id]=[l]:a[l.id].push(l);return Object.values(a)}getPastKeyValues(o,a){const l=Object.create(null);for(const p in o)if(p.startsWith("present")){let u=p.replace("present","past_key_values");a&&p.includes("encoder")?l[u]=a[u]:l[u]=o[p]}return l}getAttentions(o){const a=Object.create(null);for(const l of["cross_attentions","decoder_attentions"]){const p=[];for(const u in o)if(u.startsWith(l)){const h=u.split(".").pop();p[h]=o[u]}a[l]=p}return a}addPastKeyValues(o,a){if(a)Object.assign(o,a);else if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??!0)){let p=[1,this.num_encoder_heads,0,this.encoder_dim_kv],u=[1,this.num_decoder_heads,0,this.decoder_dim_kv];for(let h=0;h{let t=Array.from({length:this.config.decoder_layers},(_,b)=>cat(s.map(y=>y[b]),2)),e=stack(a.map(([_,b])=>l?t[_].slice(null,b,null,[0,l]):t[_].slice(null,b)));e=e.transpose(1,0,2,3);let[r,i]=std_mean(e,-2,0,!0),d=e.clone();for(let _=0;_e[b+1]-e[b]),d=mergeArrays([1],i).map(_=>!!_),m=[];for(let _=0;_l*p,1);n.input_labels=new Tensor("int64",new BigInt64Array(a).fill(1n),o)}return await sessionRun(this.prompt_encoder_mask_decoder,{input_points:n.input_points,input_labels:n.input_labels,image_embeddings:n.image_embeddings,image_positional_embeddings:n.image_positional_embeddings})}async _call(n){return new SamImageSegmentationOutput(await super._call(n))}}class SamImageSegmentationOutput extends ModelOutput{constructor({iou_scores:n,pred_masks:o}){super(),this.iou_scores=n,this.pred_masks=o}}class MarianPreTrainedModel extends PreTrainedModel{}class MarianModel extends MarianPreTrainedModel{}class MarianMTModel extends MarianPreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class M2M100PreTrainedModel extends PreTrainedModel{}class M2M100Model extends M2M100PreTrainedModel{}class M2M100ForConditionalGeneration extends M2M100PreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class Wav2Vec2PreTrainedModel extends PreTrainedModel{}class Wav2Vec2Model extends Wav2Vec2PreTrainedModel{}class Wav2Vec2ForCTC extends Wav2Vec2PreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class Wav2Vec2ForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class Wav2Vec2BertPreTrainedModel extends PreTrainedModel{}class Wav2Vec2BertModel extends Wav2Vec2BertPreTrainedModel{}class Wav2Vec2BertForCTC extends Wav2Vec2BertPreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class Wav2Vec2BertForSequenceClassification extends Wav2Vec2BertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class HubertModel extends Wav2Vec2PreTrainedModel{}class HubertForCTC extends Wav2Vec2PreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class HubertForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class WavLMPreTrainedModel extends PreTrainedModel{}class WavLMModel extends WavLMPreTrainedModel{}class WavLMForCTC extends WavLMPreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class WavLMForSequenceClassification extends WavLMPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class SpeechT5PreTrainedModel extends PreTrainedModel{}class SpeechT5ForSpeechToText extends SpeechT5PreTrainedModel{}class SpeechT5ForTextToSpeech extends SpeechT5PreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.hidden_size/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.hidden_size/this.num_encoder_heads}async generate_speech(n,o,{threshold:a=.5,minlenratio:l=0,maxlenratio:p=20,vocoder:u=null}={}){const h={input_ids:n},{encoder_outputs:g,encoder_attention_mask:c}=await encoderForward(this,h),s=g.dims[1]/this.config.reduction_factor,t=Math.floor(s*p),e=Math.floor(s*l),r=this.config.num_mel_bins;let i=[],d=null,m=null,_=0;for(;;){++_;const T=boolTensor(!!m);let w;m?w=m.output_sequence_out:w=new Tensor("float32",new Float32Array(r),[1,1,r]);let S={use_cache_branch:T,output_sequence:w,encoder_attention_mask:c,speaker_embeddings:o,encoder_hidden_states:g};this.addPastKeyValues(S,d),m=await sessionRun(this.decoder_merged_session,S),d=this.getPastKeyValues(m,d);const{prob:E,spectrum:O}=m;if(i.push(O),_>=e&&(Array.from(E.data).filter(v=>v>=a).length>0||_>=t))break}const b=cat(i),{waveform:y}=await sessionRun(u.session,{spectrogram:b});return{spectrogram:b,waveform:y}}}class SpeechT5HifiGan extends PreTrainedModel{constructor(){super(...arguments);Z(this,"main_input_name","spectrogram")}}class TrOCRPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_encoder_layers=this.num_decoder_layers=this.config.decoder_layers,this.num_encoder_heads=this.num_decoder_heads=this.config.decoder_attention_heads,this.encoder_dim_kv=this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads}}class TrOCRForCausalLM extends TrOCRPreTrainedModel{}class MistralPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class MistralModel extends MistralPreTrainedModel{}class MistralForCausalLM extends MistralPreTrainedModel{}class FalconPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class FalconModel extends FalconPreTrainedModel{}class FalconForCausalLM extends FalconPreTrainedModel{}class ClapPreTrainedModel extends PreTrainedModel{}class ClapModel extends ClapPreTrainedModel{}class ClapTextModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(n,o={}){return o.model_file_name??(o.model_file_name="text_model"),super.from_pretrained(n,o)}}class ClapAudioModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(n,o={}){return o.model_file_name??(o.model_file_name="audio_model"),super.from_pretrained(n,o)}}class VitsPreTrainedModel extends PreTrainedModel{}class VitsModel extends VitsPreTrainedModel{async _call(n){return new VitsModelOutput(await super._call(n))}}class SegformerPreTrainedModel extends PreTrainedModel{}class SegformerForImageClassification extends SegformerPreTrainedModel{}class SegformerForSemanticSegmentation extends SegformerPreTrainedModel{}class PretrainedMixin{static async from_pretrained(n,{quantized:o=!0,progress_callback:a=null,config:l=null,cache_dir:p=null,local_files_only:u=!1,revision:h="main",model_file_name:g=null}={}){let c={quantized:o,progress_callback:a,config:l,cache_dir:p,local_files_only:u,revision:h,model_file_name:g};if(l=await AutoConfig.from_pretrained(n,c),c.config||(c.config=l),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let s of this.MODEL_CLASS_MAPPINGS){const t=s.get(l.model_type);if(t)return await t[1].from_pretrained(n,c)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${l.model_type}", attempting to construct from base class.`),await PreTrainedModel.from_pretrained(n,c);throw Error(`Unsupported model type: ${l.model_type}`)}}Z(PretrainedMixin,"MODEL_CLASS_MAPPINGS",null),Z(PretrainedMixin,"BASE_IF_FAIL",!1);const MODEL_MAPPING_NAMES_ENCODER_ONLY=new Map([["bert",["BertModel",BertModel]],["nomic_bert",["NomicBertModel",NomicBertModel]],["roformer",["RoFormerModel",RoFormerModel]],["electra",["ElectraModel",ElectraModel]],["esm",["EsmModel",EsmModel]],["convbert",["ConvBertModel",ConvBertModel]],["camembert",["CamembertModel",CamembertModel]],["deberta",["DebertaModel",DebertaModel]],["deberta-v2",["DebertaV2Model",DebertaV2Model]],["mpnet",["MPNetModel",MPNetModel]],["albert",["AlbertModel",AlbertModel]],["distilbert",["DistilBertModel",DistilBertModel]],["roberta",["RobertaModel",RobertaModel]],["xlm",["XLMModel",XLMModel]],["xlm-roberta",["XLMRobertaModel",XLMRobertaModel]],["clap",["ClapModel",ClapModel]],["clip",["CLIPModel",CLIPModel]],["clipseg",["CLIPSegModel",CLIPSegModel]],["chinese_clip",["ChineseCLIPModel",ChineseCLIPModel]],["siglip",["SiglipModel",SiglipModel]],["mobilebert",["MobileBertModel",MobileBertModel]],["squeezebert",["SqueezeBertModel",SqueezeBertModel]],["wav2vec2",["Wav2Vec2Model",Wav2Vec2Model]],["wav2vec2-bert",["Wav2Vec2BertModel",Wav2Vec2BertModel]],["hubert",["HubertModel",HubertModel]],["wavlm",["WavLMModel",WavLMModel]],["audio-spectrogram-transformer",["ASTModel",ASTModel]],["vits",["VitsModel",VitsModel]],["detr",["DetrModel",DetrModel]],["table-transformer",["TableTransformerModel",TableTransformerModel]],["vit",["ViTModel",ViTModel]],["mobilevit",["MobileViTModel",MobileViTModel]],["owlvit",["OwlViTModel",OwlViTModel]],["owlv2",["Owlv2Model",Owlv2Model]],["beit",["BeitModel",BeitModel]],["deit",["DeiTModel",DeiTModel]],["convnext",["ConvNextModel",ConvNextModel]],["convnextv2",["ConvNextV2Model",ConvNextV2Model]],["dinov2",["Dinov2Model",Dinov2Model]],["resnet",["ResNetModel",ResNetModel]],["swin",["SwinModel",SwinModel]],["swin2sr",["Swin2SRModel",Swin2SRModel]],["donut-swin",["DonutSwinModel",DonutSwinModel]],["yolos",["YolosModel",YolosModel]],["dpt",["DPTModel",DPTModel]],["glpn",["GLPNModel",GLPNModel]],["hifigan",["SpeechT5HifiGan",SpeechT5HifiGan]]]),MODEL_MAPPING_NAMES_ENCODER_DECODER=new Map([["t5",["T5Model",T5Model]],["longt5",["LongT5Model",LongT5Model]],["mt5",["MT5Model",MT5Model]],["bart",["BartModel",BartModel]],["mbart",["MBartModel",MBartModel]],["marian",["MarianModel",MarianModel]],["whisper",["WhisperModel",WhisperModel]],["m2m_100",["M2M100Model",M2M100Model]],["blenderbot",["BlenderbotModel",BlenderbotModel]],["blenderbot-small",["BlenderbotSmallModel",BlenderbotSmallModel]]]),MODEL_MAPPING_NAMES_DECODER_ONLY=new Map([["bloom",["BloomModel",BloomModel]],["gpt2",["GPT2Model",GPT2Model]],["gptj",["GPTJModel",GPTJModel]],["gpt_bigcode",["GPTBigCodeModel",GPTBigCodeModel]],["gpt_neo",["GPTNeoModel",GPTNeoModel]],["gpt_neox",["GPTNeoXModel",GPTNeoXModel]],["codegen",["CodeGenModel",CodeGenModel]],["llama",["LlamaModel",LlamaModel]],["qwen2",["Qwen2Model",Qwen2Model]],["phi",["PhiModel",PhiModel]],["mpt",["MptModel",MptModel]],["opt",["OPTModel",OPTModel]],["mistral",["MistralModel",MistralModel]],["falcon",["FalconModel",FalconModel]]]),MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForSpeechToText",SpeechT5ForSpeechToText]],["whisper",["WhisperForConditionalGeneration",WhisperForConditionalGeneration]]]),MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForTextToSpeech",SpeechT5ForTextToSpeech]]]),MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES=new Map([["vits",["VitsModel",VitsModel]]]),MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForSequenceClassification",BertForSequenceClassification]],["roformer",["RoFormerForSequenceClassification",RoFormerForSequenceClassification]],["electra",["ElectraForSequenceClassification",ElectraForSequenceClassification]],["esm",["EsmForSequenceClassification",EsmForSequenceClassification]],["convbert",["ConvBertForSequenceClassification",ConvBertForSequenceClassification]],["camembert",["CamembertForSequenceClassification",CamembertForSequenceClassification]],["deberta",["DebertaForSequenceClassification",DebertaForSequenceClassification]],["deberta-v2",["DebertaV2ForSequenceClassification",DebertaV2ForSequenceClassification]],["mpnet",["MPNetForSequenceClassification",MPNetForSequenceClassification]],["albert",["AlbertForSequenceClassification",AlbertForSequenceClassification]],["distilbert",["DistilBertForSequenceClassification",DistilBertForSequenceClassification]],["roberta",["RobertaForSequenceClassification",RobertaForSequenceClassification]],["xlm",["XLMForSequenceClassification",XLMForSequenceClassification]],["xlm-roberta",["XLMRobertaForSequenceClassification",XLMRobertaForSequenceClassification]],["bart",["BartForSequenceClassification",BartForSequenceClassification]],["mbart",["MBartForSequenceClassification",MBartForSequenceClassification]],["mobilebert",["MobileBertForSequenceClassification",MobileBertForSequenceClassification]],["squeezebert",["SqueezeBertForSequenceClassification",SqueezeBertForSequenceClassification]]]),MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForTokenClassification",BertForTokenClassification]],["roformer",["RoFormerForTokenClassification",RoFormerForTokenClassification]],["electra",["ElectraForTokenClassification",ElectraForTokenClassification]],["esm",["EsmForTokenClassification",EsmForTokenClassification]],["convbert",["ConvBertForTokenClassification",ConvBertForTokenClassification]],["camembert",["CamembertForTokenClassification",CamembertForTokenClassification]],["deberta",["DebertaForTokenClassification",DebertaForTokenClassification]],["deberta-v2",["DebertaV2ForTokenClassification",DebertaV2ForTokenClassification]],["mpnet",["MPNetForTokenClassification",MPNetForTokenClassification]],["distilbert",["DistilBertForTokenClassification",DistilBertForTokenClassification]],["roberta",["RobertaForTokenClassification",RobertaForTokenClassification]],["xlm",["XLMForTokenClassification",XLMForTokenClassification]],["xlm-roberta",["XLMRobertaForTokenClassification",XLMRobertaForTokenClassification]]]),MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES=new Map([["t5",["T5ForConditionalGeneration",T5ForConditionalGeneration]],["longt5",["LongT5ForConditionalGeneration",LongT5ForConditionalGeneration]],["mt5",["MT5ForConditionalGeneration",MT5ForConditionalGeneration]],["bart",["BartForConditionalGeneration",BartForConditionalGeneration]],["mbart",["MBartForConditionalGeneration",MBartForConditionalGeneration]],["marian",["MarianMTModel",MarianMTModel]],["m2m_100",["M2M100ForConditionalGeneration",M2M100ForConditionalGeneration]],["blenderbot",["BlenderbotForConditionalGeneration",BlenderbotForConditionalGeneration]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",BlenderbotSmallForConditionalGeneration]]]),MODEL_WITH_LM_HEAD_MAPPING_NAMES=new Map([["bloom",["BloomForCausalLM",BloomForCausalLM]],["gpt2",["GPT2LMHeadModel",GPT2LMHeadModel]],["gptj",["GPTJForCausalLM",GPTJForCausalLM]],["gpt_bigcode",["GPTBigCodeForCausalLM",GPTBigCodeForCausalLM]],["gpt_neo",["GPTNeoForCausalLM",GPTNeoForCausalLM]],["gpt_neox",["GPTNeoXForCausalLM",GPTNeoXForCausalLM]],["codegen",["CodeGenForCausalLM",CodeGenForCausalLM]],["llama",["LlamaForCausalLM",LlamaForCausalLM]],["qwen2",["Qwen2ForCausalLM",Qwen2ForCausalLM]],["phi",["PhiForCausalLM",PhiForCausalLM]],["mpt",["MptForCausalLM",MptForCausalLM]],["opt",["OPTForCausalLM",OPTForCausalLM]],["mbart",["MBartForCausalLM",MBartForCausalLM]],["mistral",["MistralForCausalLM",MistralForCausalLM]],["falcon",["FalconForCausalLM",FalconForCausalLM]],["trocr",["TrOCRForCausalLM",TrOCRForCausalLM]]]),MODEL_FOR_MASKED_LM_MAPPING_NAMES=new Map([["bert",["BertForMaskedLM",BertForMaskedLM]],["roformer",["RoFormerForMaskedLM",RoFormerForMaskedLM]],["electra",["ElectraForMaskedLM",ElectraForMaskedLM]],["esm",["EsmForMaskedLM",EsmForMaskedLM]],["convbert",["ConvBertForMaskedLM",ConvBertForMaskedLM]],["camembert",["CamembertForMaskedLM",CamembertForMaskedLM]],["deberta",["DebertaForMaskedLM",DebertaForMaskedLM]],["deberta-v2",["DebertaV2ForMaskedLM",DebertaV2ForMaskedLM]],["mpnet",["MPNetForMaskedLM",MPNetForMaskedLM]],["albert",["AlbertForMaskedLM",AlbertForMaskedLM]],["distilbert",["DistilBertForMaskedLM",DistilBertForMaskedLM]],["roberta",["RobertaForMaskedLM",RobertaForMaskedLM]],["xlm",["XLMWithLMHeadModel",XLMWithLMHeadModel]],["xlm-roberta",["XLMRobertaForMaskedLM",XLMRobertaForMaskedLM]],["mobilebert",["MobileBertForMaskedLM",MobileBertForMaskedLM]],["squeezebert",["SqueezeBertForMaskedLM",SqueezeBertForMaskedLM]]]),MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES=new Map([["bert",["BertForQuestionAnswering",BertForQuestionAnswering]],["roformer",["RoFormerForQuestionAnswering",RoFormerForQuestionAnswering]],["electra",["ElectraForQuestionAnswering",ElectraForQuestionAnswering]],["convbert",["ConvBertForQuestionAnswering",ConvBertForQuestionAnswering]],["camembert",["CamembertForQuestionAnswering",CamembertForQuestionAnswering]],["deberta",["DebertaForQuestionAnswering",DebertaForQuestionAnswering]],["deberta-v2",["DebertaV2ForQuestionAnswering",DebertaV2ForQuestionAnswering]],["mpnet",["MPNetForQuestionAnswering",MPNetForQuestionAnswering]],["albert",["AlbertForQuestionAnswering",AlbertForQuestionAnswering]],["distilbert",["DistilBertForQuestionAnswering",DistilBertForQuestionAnswering]],["roberta",["RobertaForQuestionAnswering",RobertaForQuestionAnswering]],["xlm",["XLMForQuestionAnswering",XLMForQuestionAnswering]],["xlm-roberta",["XLMRobertaForQuestionAnswering",XLMRobertaForQuestionAnswering]],["mobilebert",["MobileBertForQuestionAnswering",MobileBertForQuestionAnswering]],["squeezebert",["SqueezeBertForQuestionAnswering",SqueezeBertForQuestionAnswering]]]),MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",VisionEncoderDecoderModel]]]),MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES=new Map([["vit",["ViTForImageClassification",ViTForImageClassification]],["mobilevit",["MobileViTForImageClassification",MobileViTForImageClassification]],["beit",["BeitForImageClassification",BeitForImageClassification]],["deit",["DeiTForImageClassification",DeiTForImageClassification]],["convnext",["ConvNextForImageClassification",ConvNextForImageClassification]],["convnextv2",["ConvNextV2ForImageClassification",ConvNextV2ForImageClassification]],["dinov2",["Dinov2ForImageClassification",Dinov2ForImageClassification]],["resnet",["ResNetForImageClassification",ResNetForImageClassification]],["swin",["SwinForImageClassification",SwinForImageClassification]],["segformer",["SegformerForImageClassification",SegformerForImageClassification]]]),MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES=new Map([["detr",["DetrForObjectDetection",DetrForObjectDetection]],["table-transformer",["TableTransformerForObjectDetection",TableTransformerForObjectDetection]],["yolos",["YolosForObjectDetection",YolosForObjectDetection]]]),MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES=new Map([["owlvit",["OwlViTForObjectDetection",OwlViTForObjectDetection]],["owlv2",["Owlv2ForObjectDetection",Owlv2ForObjectDetection]]]),MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES=new Map([["detr",["DetrForSegmentation",DetrForSegmentation]],["clipseg",["CLIPSegForImageSegmentation",CLIPSegForImageSegmentation]]]),MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES=new Map([["segformer",["SegformerForSemanticSegmentation",SegformerForSemanticSegmentation]]]),MODEL_FOR_MASK_GENERATION_MAPPING_NAMES=new Map([["sam",["SamModel",SamModel]]]),MODEL_FOR_CTC_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForCTC",Wav2Vec2ForCTC]],["wav2vec2-bert",["Wav2Vec2BertForCTC",Wav2Vec2BertForCTC]],["wavlm",["WavLMForCTC",WavLMForCTC]],["hubert",["HubertForCTC",HubertForCTC]]]),MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Wav2Vec2ForSequenceClassification]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",Wav2Vec2BertForSequenceClassification]],["wavlm",["WavLMForSequenceClassification",WavLMForSequenceClassification]],["hubert",["HubertForSequenceClassification",HubertForSequenceClassification]],["audio-spectrogram-transformer",["ASTForAudioClassification",ASTForAudioClassification]]]),MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES=new Map([["vitmatte",["VitMatteForImageMatting",VitMatteForImageMatting]]]),MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES=new Map([["swin2sr",["Swin2SRForImageSuperResolution",Swin2SRForImageSuperResolution]]]),MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES=new Map([["dpt",["DPTForDepthEstimation",DPTForDepthEstimation]],["depth_anything",["DepthAnythingForDepthEstimation",DepthAnythingForDepthEstimation]],["glpn",["GLPNForDepthEstimation",GLPNForDepthEstimation]]]),MODEL_CLASS_TYPE_MAPPING=[[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_TYPES.EncoderOnly],[MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_TYPES.EncoderDecoder],[MODEL_MAPPING_NAMES_DECODER_ONLY,MODEL_TYPES.DecoderOnly],[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_WITH_LM_HEAD_MAPPING_NAMES,MODEL_TYPES.DecoderOnly],[MODEL_FOR_MASKED_LM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Vision2Seq],[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_MASK_GENERATION_MAPPING_NAMES,MODEL_TYPES.MaskGeneration],[MODEL_FOR_CTC_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly]];for(const[f,n]of MODEL_CLASS_TYPE_MAPPING)for(const[o,a]of f.values())MODEL_TYPE_MAPPING.set(o,n),MODEL_CLASS_TO_NAME_MAPPING.set(a,o),MODEL_NAME_TO_CLASS_MAPPING.set(o,a);const CUSTOM_MAPPING=[["CLIPTextModelWithProjection",CLIPTextModelWithProjection,MODEL_TYPES.EncoderOnly],["CLIPVisionModelWithProjection",CLIPVisionModelWithProjection,MODEL_TYPES.EncoderOnly],["SiglipTextModel",SiglipTextModel,MODEL_TYPES.EncoderOnly],["SiglipVisionModel",SiglipVisionModel,MODEL_TYPES.EncoderOnly],["ClapTextModelWithProjection",ClapTextModelWithProjection,MODEL_TYPES.EncoderOnly],["ClapAudioModelWithProjection",ClapAudioModelWithProjection,MODEL_TYPES.EncoderOnly]];for(const[f,n,o]of CUSTOM_MAPPING)MODEL_TYPE_MAPPING.set(f,o),MODEL_CLASS_TO_NAME_MAPPING.set(n,f),MODEL_NAME_TO_CLASS_MAPPING.set(f,n);class AutoModel extends PretrainedMixin{}Z(AutoModel,"MODEL_CLASS_MAPPINGS",MODEL_CLASS_TYPE_MAPPING.map(n=>n[0])),Z(AutoModel,"BASE_IF_FAIL",!0);class Seq2SeqLMOutput extends ModelOutput{constructor({logits:n,past_key_values:o,encoder_outputs:a,decoder_attentions:l=null,cross_attentions:p=null}){super(),this.logits=n,this.past_key_values=o,this.encoder_outputs=a,this.decoder_attentions=l,this.cross_attentions=p}}class SequenceClassifierOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class TokenClassifierOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class MaskedLMOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class QuestionAnsweringModelOutput extends ModelOutput{constructor({start_logits:n,end_logits:o}){super(),this.start_logits=n,this.end_logits=o}}class CausalLMOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class ImageMattingOutput extends ModelOutput{constructor({alphas:n}){super(),this.alphas=n}}class VitsModelOutput extends ModelOutput{constructor({waveform:n,spectrogram:o}){super(),this.waveform=n,this.spectrogram=o}}const BROWSER_ENV=typeof self<"u";if(!BROWSER_ENV){if(!sharp)throw new Error("Unable to load image processing library.")}env$1.allowLocalModels=!1;const TOKENIZER_MAPPINGS=new Map;self.addEventListener("message",async f=>{console.log(f.data);let n=f.data.model_id,o=TOKENIZER_MAPPINGS.get(f.data.model_id);o||(o=AutoTokenizer.from_pretrained(f.data.model_id),TOKENIZER_MAPPINGS.set(f.data.model_id,new Promise(s=>{o.then(t=>{switch(t.constructor.name){case"LlamaTokenizer":case"Grok1Tokenizer":t.decoder.decoders.pop();break;case"T5Tokenizer":t.decoder.addPrefixSpace=!1;break}s(t)})})));const a=await o,l=f.data.text,p=performance.now(),u=a.encode(l),h=performance.now();console.log("[INFO]",`Tokenized ${l.length} characters in ${(h-p).toFixed(2)}ms`);let g=u.map(s=>a.decode([s])),c=[];switch(a.constructor.name){case"BertTokenizer":c=g.map((s,t)=>t===0||s.startsWith("##")?0:8),g=g.map(s=>s.replace("##",""));break;case"T5Tokenizer":g.length>0&&g.length!==" "&&(g[0]=g[0].replace(/^ /,""));break}self.postMessage({model_id:n,token_ids:u,decoded:g,margins:c})})})();