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r=a.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 a.onnx.ValueInfoProto)return e;var r=new a.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=a.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=a.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,s.util.toJSONOptions)},t}(),d.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:h.input&&h.input.length||(h.input=[]),h.input.push(e.string());break;case 2:h.output&&h.output.length||(h.output=[]),h.output.push(e.string());break;case 3:h.name=e.string();break;case 4:h.opType=e.string();break;case 7:h.domain=e.string();break;case 5:h.attribute&&h.attribute.length||(h.attribute=[]),h.attribute.push(a.onnx.AttributeProto.decode(e,e.uint32()));break;case 6:h.docString=e.string();break;default:e.skipType(7&g)}}return h},t.decodeDelimited=function(e){return e instanceof p||(e=new p(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:h.irVersion=e.int64();break;case 8:h.opsetImport&&h.opsetImport.length||(h.opsetImport=[]),h.opsetImport.push(a.onnx.OperatorSetIdProto.decode(e,e.uint32()));break;case 2:h.producerName=e.string();break;case 3:h.producerVersion=e.string();break;case 4:h.domain=e.string();break;case 5:h.modelVersion=e.int64();break;case 6:h.docString=e.string();break;case 7:h.graph=a.onnx.GraphProto.decode(e,e.uint32());break;case 14:h.metadataProps&&h.metadataProps.length||(h.metadataProps=[]),h.metadataProps.push(a.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return h},t.decodeDelimited=function(e){return e instanceof p||(e=new p(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=a.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=a.onnx.GraphProto.toObject(e.graph,r)),e.opsetImport&&e.opsetImport.length){i.opsetImport=[];for(var g=0;g>>3){case 1:h.key=e.string();break;case 2:h.value=e.string();break;default:e.skipType(7&g)}}return h},t.decodeDelimited=function(e){return e instanceof p||(e=new p(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 a.onnx.StringStringEntryProto)return e;var r=new a.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,s.util.toJSONOptions)},t}(),d.TensorAnnotation=function(){function t(e){if(this.quantParameterTensorNames=[],e)for(var r=Object.keys(e),i=0;i>>3){case 1:h.tensorName=e.string();break;case 2:h.quantParameterTensorNames&&h.quantParameterTensorNames.length||(h.quantParameterTensorNames=[]),h.quantParameterTensorNames.push(a.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return h},t.decodeDelimited=function(e){return e instanceof p||(e=new p(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:h.node&&h.node.length||(h.node=[]),h.node.push(a.onnx.NodeProto.decode(e,e.uint32()));break;case 2:h.name=e.string();break;case 5:h.initializer&&h.initializer.length||(h.initializer=[]),h.initializer.push(a.onnx.TensorProto.decode(e,e.uint32()));break;case 10:h.docString=e.string();break;case 11:h.input&&h.input.length||(h.input=[]),h.input.push(a.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 12:h.output&&h.output.length||(h.output=[]),h.output.push(a.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 13:h.valueInfo&&h.valueInfo.length||(h.valueInfo=[]),h.valueInfo.push(a.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 14:h.quantizationAnnotation&&h.quantizationAnnotation.length||(h.quantizationAnnotation=[]),h.quantizationAnnotation.push(a.onnx.TensorAnnotation.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return h},t.decodeDelimited=function(e){return e instanceof p||(e=new p(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(h.dims&&h.dims.length||(h.dims=[]),(7&g)==2)for(var m=e.uint32()+e.pos;e.pos>>0,e.dims[i].high>>>0).toNumber())}if(e.dataType!=null&&(r.dataType=0|e.dataType),e.segment!=null){if(typeof e.segment!="object")throw TypeError(".onnx.TensorProto.segment: object expected");r.segment=a.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 h=0;h>>0,e.dims[h].high>>>0).toNumber():e.dims[h]}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&(i.dataType=e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&(i.segment=a.onnx.TensorProto.Segment.toObject(e.segment,r)),e.floatData&&e.floatData.length)for(i.floatData=[],h=0;h>>0,e.int64Data[h].high>>>0).toNumber():e.int64Data[h];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=[],h=0;h>>0,e.uint64Data[h].high>>>0).toNumber(!0):e.uint64Data[h];if(e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),e.externalData&&e.externalData.length)for(i.externalData=[],h=0;h>>3){case 1:g.begin=r.int64();break;case 2:g.end=r.int64();break;default:r.skipType(7&m)}}return g},e.decodeDelimited=function(r){return r instanceof p||(r=new p(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 a.onnx.TensorProto.Segment)return r;var i=new a.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 h={};if(i.defaults){if(c.Long){var g=new c.Long(0,0,!1);h.begin=i.longs===String?g.toString():i.longs===Number?g.toNumber():g}else h.begin=i.longs===String?"0":0;c.Long?(g=new c.Long(0,0,!1),h.end=i.longs===String?g.toString():i.longs===Number?g.toNumber():g):h.end=i.longs===String?"0":0}return r.begin!=null&&r.hasOwnProperty("begin")&&(typeof r.begin=="number"?h.begin=i.longs===String?String(r.begin):r.begin:h.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"?h.end=i.longs===String?String(r.end):r.end:h.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),h},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),t.DataLocation=function(){var e={},r=Object.create(e);return r[e[0]="DEFAULT"]=0,r[e[1]="EXTERNAL"]=1,r}(),t}(),d.TensorShapeProto=function(){function t(e){if(this.dim=[],e)for(var r=Object.keys(e),i=0;i>>3==1?(h.dim&&h.dim.length||(h.dim=[]),h.dim.push(a.onnx.TensorShapeProto.Dimension.decode(e,e.uint32()))):e.skipType(7&g)}return h},t.decodeDelimited=function(e){return e instanceof p||(e=new p(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.dim!=null&&e.hasOwnProperty("dim")){if(!Array.isArray(e.dim))return"dim: array expected";for(var r=0;r>>3){case 1:m.dimValue=i.int64();break;case 2:m.dimParam=i.string();break;case 3:m.denotation=i.string();break;default:i.skipType(7&b)}}return m},e.decodeDelimited=function(i){return i instanceof p||(i=new p(i)),this.decode(i,i.uint32())},e.verify=function(i){if(typeof i!="object"||i===null)return"object expected";var h={};if(i.dimValue!=null&&i.hasOwnProperty("dimValue")&&(h.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(h.value===1)return"value: multiple values";if(h.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 a.onnx.TensorShapeProto.Dimension)return i;var h=new a.onnx.TensorShapeProto.Dimension;return i.dimValue!=null&&(c.Long?(h.dimValue=c.Long.fromValue(i.dimValue)).unsigned=!1:typeof i.dimValue=="string"?h.dimValue=parseInt(i.dimValue,10):typeof i.dimValue=="number"?h.dimValue=i.dimValue:typeof i.dimValue=="object"&&(h.dimValue=new c.LongBits(i.dimValue.low>>>0,i.dimValue.high>>>0).toNumber())),i.dimParam!=null&&(h.dimParam=String(i.dimParam)),i.denotation!=null&&(h.denotation=String(i.denotation)),h},e.toObject=function(i,h){h||(h={});var g={};return h.defaults&&(g.denotation=""),i.dimValue!=null&&i.hasOwnProperty("dimValue")&&(typeof i.dimValue=="number"?g.dimValue=h.longs===String?String(i.dimValue):i.dimValue:g.dimValue=h.longs===String?c.Long.prototype.toString.call(i.dimValue):h.longs===Number?new c.LongBits(i.dimValue.low>>>0,i.dimValue.high>>>0).toNumber():i.dimValue,h.oneofs&&(g.value="dimValue")),i.dimParam!=null&&i.hasOwnProperty("dimParam")&&(g.dimParam=i.dimParam,h.oneofs&&(g.value="dimParam")),i.denotation!=null&&i.hasOwnProperty("denotation")&&(g.denotation=i.denotation),g},e.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},e}(),t}(),d.TypeProto=function(){function t(r){if(r)for(var i=Object.keys(r),h=0;h>>3){case 1:g.tensorType=a.onnx.TypeProto.Tensor.decode(r,r.uint32());break;case 6:g.denotation=r.string();break;default:r.skipType(7&m)}}return g},t.decodeDelimited=function(r){return r instanceof p||(r=new p(r)),this.decode(r,r.uint32())},t.verify=function(r){if(typeof r!="object"||r===null)return"object expected";if(r.tensorType!=null&&r.hasOwnProperty("tensorType")){var i=a.onnx.TypeProto.Tensor.verify(r.tensorType);if(i)return"tensorType."+i}return r.denotation!=null&&r.hasOwnProperty("denotation")&&!c.isString(r.denotation)?"denotation: string expected":null},t.fromObject=function(r){if(r instanceof a.onnx.TypeProto)return r;var i=new a.onnx.TypeProto;if(r.tensorType!=null){if(typeof r.tensorType!="object")throw TypeError(".onnx.TypeProto.tensorType: object expected");i.tensorType=a.onnx.TypeProto.Tensor.fromObject(r.tensorType)}return r.denotation!=null&&(i.denotation=String(r.denotation)),i},t.toObject=function(r,i){i||(i={});var h={};return i.defaults&&(h.denotation=""),r.tensorType!=null&&r.hasOwnProperty("tensorType")&&(h.tensorType=a.onnx.TypeProto.Tensor.toObject(r.tensorType,i),i.oneofs&&(h.value="tensorType")),r.denotation!=null&&r.hasOwnProperty("denotation")&&(h.denotation=r.denotation),h},t.prototype.toJSON=function(){return this.constructor.toObject(this,s.util.toJSONOptions)},t.Tensor=function(){function r(i){if(i)for(var h=Object.keys(i),g=0;g>>3){case 1:m.elemType=i.int32();break;case 2:m.shape=a.onnx.TensorShapeProto.decode(i,i.uint32());break;default:i.skipType(7&b)}}return m},r.decodeDelimited=function(i){return i instanceof p||(i=new p(i)),this.decode(i,i.uint32())},r.verify=function(i){if(typeof i!="object"||i===null)return"object expected";if(i.elemType!=null&&i.hasOwnProperty("elemType")&&!c.isInteger(i.elemType))return"elemType: integer expected";if(i.shape!=null&&i.hasOwnProperty("shape")){var h=a.onnx.TensorShapeProto.verify(i.shape);if(h)return"shape."+h}return null},r.fromObject=function(i){if(i 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getValueNoCheckFromOrtFormat(a){switch(a.type()){case p.AttributeType.FLOAT:return a.f();case p.AttributeType.INT:return a.i();case p.AttributeType.STRING:return a.s();case p.AttributeType.TENSOR:return a.t();case p.AttributeType.GRAPH:return a.g();case p.AttributeType.FLOATS:return a.floatsArray();case p.AttributeType.INTS:{const t=[];for(let e=0;e{Object.defineProperty(n,"__esModule",{value:!0}),n.resolveBackend=n.backend=void 0;const u=o(5038),l=new Map;async function d(s){const p=n.backend;if(p[s]!==void 0&&function(f){const c=f;return"initialize"in c&&typeof c.initialize=="function"&&"createSessionHandler"in c&&typeof c.createSessionHandler=="function"&&"dispose"in c&&typeof c.dispose=="function"}(p[s])){const f=p[s];let c=f.initialize();if(typeof c=="object"&&"then"in c&&(c=await c),c)return l.set(s,f),f}}n.backend={webgl:new u.WebGLBackend},n.resolveBackend=async function s(p){if(!p)return s(["webgl"]);{const f=typeof p=="string"?[p]:p;for(const c of f){const 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Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.offsetToCoords()),this.coordsToOffset()),this.toVec()),this.valueFrom()),this.getCommonUtilFuncs()),this.getInputsSamplingSnippets()),this.getOutputSamplingSnippet())}getCustomTypes(){return{}}offsetToCoords(){return{offsetToCoords:new l.GlslLibRoutine(` + vec2 offsetToCoords(int offset, int width, int height) { + int t = offset / width; + int s = offset - t*width; + vec2 coords = (vec2(s,t) + vec2(0.5,0.5)) / vec2(width, height); + return coords; + } + `)}}coordsToOffset(){return{coordsToOffset:new l.GlslLibRoutine(` + int coordsToOffset(vec2 coords, int width, int height) { + float s = coords.s * float(width); + float t = coords.t * float(height); + int offset = int(t) * width + int(s); + return offset; + } + `)}}getOutputSamplingSnippet(){const a=this.context.outputTextureLayout;return a.isPacked?this.getPackedOutputSamplingSnippet(a):this.getUnpackedOutputSamplingSnippet(a)}getPackedOutputSamplingSnippet(a){const t=a.unpackedShape,e=[a.width,a.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 h=` + void setOutput(vec4 val) { + ${(0,d.getGlsl)(this.context.glContext.version).output} = val; + } + `;return r.floatTextureSetRGBA=new l.GlslLibRoutine(h),r}getUnpackedOutputSamplingSnippet(a){const t=a.unpackedShape,e=[a.width,a.height],r={},i="getOutputCoords";switch(t.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputUnpacked1DCoords(t,e);break;case 2:r[i]=this.getOutputUnpacked2DCoords(t,e);break;case 3:r[i]=this.getOutputUnpacked3DCoords(t,e);break;case 4:r[i]=this.getOutputUnpacked4DCoords(t,e);break;case 5:r[i]=this.getOutputUnpacked5DCoords(t,e);break;case 6:r[i]=this.getOutputUnpacked6DCoords(t,e);break;default:throw new Error(`Unsupported output dimensionality: ${t.length}`)}const h=` + void setOutput(float val) { + ${(0,d.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0); + } + `;return r.floatTextureSetR=new l.GlslLibRoutine(h),r}getOutputScalarCoords(){return new l.GlslLibRoutine(` + int getOutputCoords() { + return 0; + } + `)}getOutputPacked1DCoords(a,t){const e=t;let r="";return e[0]===1?(r=` + int getOutputCoords() { + return 2 * int(TexCoords.y * ${e[1]}.0); + } + `,new l.GlslLibRoutine(r)):e[1]===1?(r=` + int getOutputCoords() { + return 2 * int(TexCoords.x * ${e[0]}.0); + } + `,new l.GlslLibRoutine(r)):(r=` + int getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${e[0]}, ${e[1]})); + return 2 * (resTexRC.y * ${e[0]} + resTexRC.x); + } + `,new l.GlslLibRoutine(r))}getOutputPacked2DCoords(a,t){let e="";if(u.ArrayUtil.arraysEqual(a,t))return e=` + ivec2 getOutputCoords() { + return 2 * ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]})); + } + `,new l.GlslLibRoutine(e);const r=t,i=Math.ceil(a[1]/2);return e=` + ivec2 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${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 / ${i}); + + return ivec2(r, c); + } + `,new l.GlslLibRoutine(e)}getOutputPacked3DCoords(a,t){const e=[t[0],t[1]],r=Math.ceil(a[2]/2),i=r*Math.ceil(a[1]/2),h=` + ivec3 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${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(h)}getOutputPackedNDCoords(a,t){const e=[t[0],t[1]],r=Math.ceil(a[a.length-1]/2),i=r*Math.ceil(a[a.length-2]/2);let h=i,g="",m="b, r, c";for(let y=2;y=0;--m)i[m]=i[m+1]*a[m+1];const h=["r","c","d"],g=i.map((m,b)=>`int ${h[b]} = index / ${m}; ${b===i.length-1?`int ${h[b+1]} = index - ${h[b]} * ${m}`:`index -= ${h[b]} * ${m}`};`).join("");return e=` + ivec3 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${t[0]}, ${t[1]})); + int index = resTexRC.y * ${t[0]} + resTexRC.x; + ${g} + return ivec3(r, c, d); + } + `,new l.GlslLibRoutine(e)}getOutputUnpacked4DCoords(a,t){let e="";const r=a.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=a[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*a[m+1];const h=["r","c","d","d2"],g=i.map((m,b)=>`int ${h[b]} = index / ${m}; ${b===i.length-1?`int ${h[b+1]} = index - ${h[b]} * ${m}`:`index -= ${h[b]} * ${m}`};`).join("");return e=` + ivec4 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${t[0]}, ${t[1]})); + int index = resTexRC.y * ${t[0]} + resTexRC.x; + ${g} + return ivec4(r, c, d, d2); + } + `,new l.GlslLibRoutine(e)}getOutputUnpacked5DCoords(a,t){let e="";const r=a.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=a[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*a[m+1];const h=["r","c","d","d2","d3"],g=i.map((m,b)=>`int ${h[b]} = index / ${m}; ${b===i.length-1?`int ${h[b+1]} = index - ${h[b]} * ${m}`:`index -= ${h[b]} * ${m}`};`).join("");return e=` + ivec5 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${t[0]}, ${t[1]})); + int index = resTexRC.y * ${t[0]} + resTexRC.x; + ${g} + return ivec5(r, c, d, d2, d3); + } + `,new l.GlslLibRoutine(e)}getOutputUnpacked6DCoords(a,t){let e="";const r=a.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=a[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*a[m+1];const h=["r","c","d","d2","d3","d4"],g=i.map((m,b)=>`int ${h[b]} = index / ${m}; ${b===i.length-1?`int ${h[b+1]} = index - ${h[b]} * ${m}`:`index -= ${h[b]} * ${m}`};`).join("");return e=` + ivec6 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${t[0]}, ${t[1]})); + int index = resTexRC.y * ${t[0]} + resTexRC.x; + ${g} + return ivec6(r, c, d, d2, d3, d4); + } + `,new l.GlslLibRoutine(e)}getCommonUtilFuncs(){const a={};let t="uvFromFlat";a[t]=new l.GlslLibRoutine(` + vec2 uvFromFlat(int texNumR, int texNumC, int index) { + int texC = index / texNumR; + int texR = index - texC * texNumR; + // TODO: swap texR, texC order in following function so row is corresponding to u and column is corresponding to + // v. + return (vec2(texR, texC) + halfCR) / vec2(texNumR, texNumC); + } + `),t="packedUVfrom1D",a[t]=new l.GlslLibRoutine(` + vec2 packedUVfrom1D(int texNumR, int texNumC, int index) { + int texelIndex = index / 2; + int texR = texelIndex / texNumC; + int texC = texelIndex - texR * texNumC; + return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR); + } + `),t="packedUVfrom2D",a[t]=new l.GlslLibRoutine(` + vec2 packedUVfrom2D(int texNumR, int texNumC, int texelsInLogicalRow, int row, int col) { + int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2); + int texR = texelIndex / texNumC; + int texC = texelIndex - texR * texNumC; + return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR); + } + `),t="packedUVfrom3D",a[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,d.getGlsl)(this.context.glContext.version);return a[t]=new l.GlslLibRoutine(` + float sampleTexture(sampler2D textureSampler, vec2 uv) { + return ${e.texture2D}(textureSampler, uv).r; + }`),a}getInputsSamplingSnippets(){const a={},t=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,r)=>{const i=this.context.inputTextureLayouts[r],h=(0,p.generateShaderFuncNameFromInputSamplerName)(e);i.isPacked?a[h]=this.getPackedSamplerFromInput(h,e,i):a[h]=this.getUnpackedSamplerFromInput(h,e,i);const g=(0,p.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(e);i.unpackedShape.length<=t.unpackedShape.length&&(i.isPacked?a[g]=this.getPackedSamplerAtOutputCoords(g,i,t,e):a[g]=this.getUnpackedSamplerAtOutputCoords(g,i,t,e))}),a}getPackedSamplerAtOutputCoords(a,t,e,r){const i=t.unpackedShape,h=e.unpackedShape,g=r,m=(0,p.generateShaderFuncNameFromInputSamplerName)(g),b=i.length,y=h.length,w=u.BroadcastUtil.getBroadcastDims(i,h),T=(0,p.getCoordsDataType)(y),S=y-b;let A;const O=(0,p.getGlChannels)();A=b===0?"":y<2&&w.length>=1?"coords = 0;":w.map(N=>`coords.${O[N+S]} = 0;`).join(` +`);let v="";v=y<2&&b>0?"coords":i.map((N,G)=>`coords.${O[G+S]}`).join(", ");let M="return outputValue;";const F=u.ShapeUtil.size(i)===1,R=u.ShapeUtil.size(h)===1;if(b!==1||F||R){if(F&&!R)M=y===1?` + return vec4(outputValue.x, outputValue.x, 0., 0.); + `:` + return vec4(outputValue.x); + `;else if(w.length){const N=b-2,G=b-1;w.indexOf(N)>-1&&w.indexOf(G)>-1?M="return vec4(outputValue.x);":w.indexOf(N)>-1?M="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":w.indexOf(G)>-1&&(M="return vec4(outputValue.xx, outputValue.zz);")}}else M=` + return vec4(outputValue.xy, outputValue.xy); + `;const $=` + vec4 ${a}() { + ${T} coords = getOutputCoords(); + + int lastDim = coords.${O[y-1]}; + coords.${O[y-1]} = coords.${O[y-2]}; + coords.${O[y-2]} = lastDim; + + ${A} + vec4 outputValue = ${m}(${v}); + ${M} + } + `;return new l.GlslLibRoutine($,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(a,t,e,r){const i=[e.width,e.height],h=[t.width,t.height],g=t.unpackedShape.length,m=e.unpackedShape.length,b=t.unpackedShape,y=e.unpackedShape,w=(0,p.generateShaderFuncNameFromInputSamplerName)(r);if(g===m&&u.ArrayUtil.arraysEqual(h,i)){const R=` + float ${a}() { + return sampleTexture(${r}, TexCoords); + } + `;return new l.GlslLibRoutine(R,["coordinates.sampleTexture"])}const T=(0,p.getCoordsDataType)(m),S=u.BroadcastUtil.getBroadcastDims(b,y),A=m-g;let O;const v=(0,p.getGlChannels)();O=g===0?"":m<2&&S.length>=1?"coords = 0;":S.map(R=>`coords.${v[R+A]} = 0;`).join(` +`);let M="";M=m<2&&g>0?"coords":t.unpackedShape.map((R,$)=>`coords.${v[$+A]}`).join(", ");const F=` + float ${a}() { + ${T} coords = getOutputCoords(); + ${O} + return ${w}(${M}); + } + `;return new l.GlslLibRoutine(F,["coordinates.getOutputCoords"])}getPackedSamplerFromInput(a,t,e){switch(e.unpackedShape.length){case 0:return this.getPackedSamplerScalar(a,t);case 1:return this.getPackedSampler1D(a,t,e);case 2:return this.getPackedSampler2D(a,t,e);case 3:return this.getPackedSampler3D(a,t,e);default:return this.getPackedSamplerND(a,t,e)}}getUnpackedSamplerFromInput(a,t,e){const r=e.unpackedShape;switch(r.length){case 0:return this.getUnpackedSamplerScalar(a,t,e);case 1:return this.getUnpackedSampler1D(a,t,e);case 2:return this.getUnpackedSampler2D(a,t,e);case 3:return this.getUnpackedSampler3D(a,t,e);case 4:return this.getUnpackedSampler4D(a,t,e);case 5:return this.getUnpackedSampler5D(a,t,e);case 6:return this.getUnpackedSampler6D(a,t,e);default:throw new Error(`Unsupported dimension ${r.length}-D`)}}getPackedSamplerScalar(a,t){const e=` + vec4 ${a}() { + return ${(0,d.getGlsl)(this.context.glContext.version).texture2D}(${t}, halfCR); + } + `;return new l.GlslLibRoutine(e)}getPackedSampler1D(a,t,e){const r=[e.width,e.height],i=[r[1],r[0]],h=(0,d.getGlsl)(this.context.glContext.version),g=`vec4 ${a}(int index) { + vec2 uv = packedUVfrom1D( + ${i[0]}, ${i[1]}, index); + return ${h.texture2D}(${t}, uv); + }`;return new l.GlslLibRoutine(g,["coordinates.packedUVfrom1D"])}getPackedSampler2D(a,t,e){const r=e.unpackedShape,i=[e.width,e.height],h=(0,d.getGlsl)(this.context.glContext.version),g=i[0],m=i[1];if(i!=null&&u.ArrayUtil.arraysEqual(r,i)){const T=`vec4 ${a}(int row, int col) { + vec2 uv = (vec2(col, row) + halfCR) / vec2(${m}.0, ${g}.0); + return ${h.texture2D}(${t}, uv); + }`;return new l.GlslLibRoutine(T)}const b=i,y=Math.ceil(r[1]/2),w=`vec4 ${a}(int row, int col) { + vec2 uv = packedUVfrom2D(${b[1]}, ${b[0]}, ${y}, row, col); + return ${h.texture2D}(${t}, uv); + }`;return new l.GlslLibRoutine(w,["coordinates.packedUVfrom2D"])}getPackedSampler3D(a,t,e){const r=e.unpackedShape,i=[e.width,e.height],h=[i[0],i[1]],g=(0,d.getGlsl)(this.context.glContext.version);if(r[0]===1){const T=r.slice(1),S=[1,2],A=(0,p.squeezeInputShape)(r,T),O=["b","row","col"],v=JSON.parse(JSON.stringify(e));v.unpackedShape=A;const M=this.getPackedSamplerFromInput(a,t,v),F=`${M.routineBody} + vec4 ${a}(int b, int row, int col) { + return ${a}(${(0,p.getSqueezedParams)(O,S)}); + } `;return new l.GlslLibRoutine(F,M.dependencies)}const m=h[0],b=h[1],y=Math.ceil(r[2]/2),w=`vec4 ${a}(int b, int row, int col) { + vec2 uv = packedUVfrom3D( + ${b}, ${m}, ${y*Math.ceil(r[1]/2)}, ${y}, b, row, col); + return ${g.texture2D}(${t}, uv);}`;return new l.GlslLibRoutine(w,["coordinates.packedUVfrom3D"])}getPackedSamplerND(a,t,e){const r=e.unpackedShape,i=r.length,h=[e.width,e.height],g=(0,d.getGlsl)(this.context.glContext.version),m=[h[0],h[1]],b=m[1],y=m[0],w=Math.ceil(r[i-1]/2);let T=w*Math.ceil(r[i-2]/2),S="int b, int row, int col",A=`b * ${T} + (row / 2) * ${w} + (col / 2)`;for(let v=2;v{const r=this.context.inputTextureLayouts[e],i=(r.unpackedShape.length>0?r.unpackedShape:r.shape).length;let h=`_${t}`;a[h]=new l.GlslLibRoutine(this.getValueFromSingle(t,i,r.width,r.height,!1),[`shapeUtils.indicesToOffset${h}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"]),h+="_T",a[h]=new 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b; + } + vec4 ${T}(vec4 v1, vec4 v2) { + return v1 - v2; + } + `,name:T,type:l.FunctionType.ValueBased}}function t(){const T="equal_";return{body:` + float ${T}(float a, float b) { + return float(a == b); + } + vec4 ${T}(vec4 v1, vec4 v2) { + return vec4(equal(v1, v2)); + } + `,name:T,type:l.FunctionType.ValueBased}}function e(){const T="greater_";return{body:` + float ${T}(float a, float b) { + return float(a > b); + } + vec4 ${T}(vec4 v1, vec4 v2) { + return vec4( v1.r > v2.r , + v1.g > v2.g, + v1.b > v2.b, + v1.a > v2.a ); + } + `,name:T,type:l.FunctionType.ValueBased}}function r(){const T="less_";return{body:` + float ${T}(float a, float b) { + return float(a < b); + } + vec4 ${T}(vec4 v1, vec4 v2) { + return vec4( v1.r < v2.r , + v1.g < v2.g, + v1.b < v2.b, + v1.a < v2.a ); + } + `,name:T,type:l.FunctionType.ValueBased}}function i(){const T="and_";return{body:` + float ${T}(float a, float b) { + return float( bool(a) && bool(b) ); + } + vec4 ${T}(vec4 v1, vec4 v2) { + bvec4 b1 = bvec4(v1); + bvec4 b2 = bvec4(v2); + return vec4( b1.r && b2.r , + b1.g && b2.g, + b1.b && b2.b, + b1.a && b2.a ); + } + `,name:T,type:l.FunctionType.ValueBased}}function h(){const T="or_";return{body:` + float ${T}(float a, float b) { + return float( bool(a) || bool(b) ); + } + vec4 ${T}(vec4 v1, vec4 v2) { + bvec4 b1 = bvec4(v1); + bvec4 b2 = bvec4(v2); + return vec4( b1.r || b2.r , + b1.g || b2.g, + b1.b || b2.b, + b1.a || b2.a ); + } + `,name:T,type:l.FunctionType.ValueBased}}function g(){const T="xor_";return{body:` + float ${T}(float a, float b) { + return float( bool(a) ^^ bool(b) ); + } + vec4 ${T}(vec4 v1, vec4 v2) { + bvec4 b1 = bvec4(v1); + bvec4 b2 = bvec4(v2); + return vec4( b1.r ^^ b2.r , + b1.g ^^ b2.g, + b1.b ^^ b2.b, + b1.a ^^ b2.a ); + } + `,name:T,type:l.FunctionType.ValueBased}}function m(){return function(T){const S=`${T}_`;return{body:` + float ${S}(float a, float b) { + return ${T}(a, b); + } + vec4 ${S}(vec4 v1, vec4 v2) { + return ${T}(v1, v2); + } + `,name:S,type:l.FunctionType.ValueBased}}("pow")}function b(){const T="prelu_";return{body:` + float ${T}(float a, float b) { + return a < 0.0 ? a * b: a; + } + vec4 ${T}(vec4 v1, vec4 v2) { + return vec4( + v1.r < 0.0 ? v1.r * v2.r: v1.r, + v1.g < 0.0 ? v1.g * v2.g: v1.g, + v1.b < 0.0 ? v1.b * v2.b: v1.b, + v1.a < 0.0 ? v1.a * v2.a: v1.a + ); + } + `,name:T,type:l.FunctionType.ValueBased}}n.glslAdd=p,n.glslDiv=f,n.glslMul=c,n.glslSub=a,n.glslEqual=t,n.glslGreater=e,n.glslLess=r,n.glslAnd=i,n.glslOr=h,n.glslXor=g,n.glslPow=m,n.glslPRelu=b;const y=(T,S,A,O=S[0].type,v)=>{const M=T.session.pack?s.TextureType.packed:s.TextureType.unpacked;return{name:A.name,inputNames:["A","B"],inputTypes:[M,M],cacheHint:v,get:()=>w(T,S,A,O)}},w=(T,S,A,O=S[0].type)=>{const v=T.session.pack?s.TextureType.packed:s.TextureType.unpacked,M=!u.ShapeUtil.areEqual(S[0].dims,S[1].dims);let F=S[0].dims;const R=T.session.pack;if(M){const G=u.BroadcastUtil.calcShape(S[0].dims,S[1].dims,!1);if(!G)throw new 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j=(0,u.getGlsl)(i.session.backend.glContext.version),Q=` + ${A} + float getValue(${v.map(X=>"int "+X)}) { + ${N} + } + + void main() { + ${S} coords = getOutputCoords(); + int lastDim = coords.${v[w-1]}; + coords.${v[w-1]} = coords.${v[w-2]}; + coords.${v[w-2]} = lastDim; + + vec4 result = vec4(getValue(${T}), 0., 0., 0.); + + ${T[w-1]} = ${T[w-1]} + 1; + if (${T[w-1]} < ${y[w-1]}) { + result.g = getValue(${T}); + } + + ${T[w-2]} = ${T[w-2]} + 1; + if (${T[w-2]} < ${y[w-2]}) { + result.a = getValue(${T}); + } + + ${T[w-1]} = ${T[w-1]} - 1; + if (${T[w-2]} < ${y[w-2]} && + ${T[w-1]} < ${y[w-1]}) { + result.b = getValue(${T}); + } + ${j.output} = result; + } + `;return Object.assign(Object.assign({},h),{output:{dims:y,type:g[0].type,textureType:l.TextureType.packed},shaderSource:Q,hasMain:!0})})(f,t,c,a.axis)})};const p=(f,c,a)=>{const t=f.indexOf(c);return f.map((e,r)=>r===t?`${e} - 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+ for (int wHeight = 0; wHeight < ${w[2]}; wHeight++) { + int xHeight = xRCCorner.x + wHeight * ${m.dilations[0]}; + + if (xHeight < 0 || xHeight >= ${y[2]}) { + continue; + } + + for (int wWidth = 0; wWidth < ${w[3]}; wWidth++) { + int xWidth = xRCCorner.y + wWidth * ${m.dilations[1]}; + if (xWidth < 0 || xWidth >= ${y[3]}) { + continue; + } + + float xVal = getX(batch, input_channel, xWidth, xHeight); + float wVal = getW(output_channel, wInChannel, wWidth, wHeight); + value += xVal*wVal; + } + } + } + ${b} + ${v} + ${A.output} = vec4(value, .0, .0, .0); + } +`;return Object.assign(Object.assign({},g),{output:{dims:S,type:h[0].type,textureType:d.TextureType.unpacked},shaderSource:M,hasMain:!0})})(f,c,t,a)})}},1386:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.conv2DPacked=n.conv2DPackedPointwise=void 0;const u=o(8138),l=o(8555),d=o(708);n.conv2DPackedPointwise=(s,p,f)=>{const 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b=Math.floor(r/2);i==="SAME_UPPER"?(h[g]=b,h[m]=r-b):i==="SAME_LOWER"&&(h[g]=r-b,h[m]=b)};n.convTranspose=(r,i,h)=>(e(i,h),c(r,i,h));const c=(r,i,h)=>{const g=t(h,i);return[a(r,i,g)]},a=(r,i,h)=>r.run(((g,m,b)=>{const y=(w=m.length>2,T=b.cacheKey,{name:"ConvTranspose",inputNames:w?["X","W","B"]:["X","W"],inputTypes:w?[d.TextureType.unpacked,d.TextureType.unpacked,d.TextureType.unpacked]:[d.TextureType.unpacked,d.TextureType.unpacked],cacheHint:T});var w,T;return Object.assign(Object.assign({},y),{get:()=>((S,A,O,v)=>{const M=A.length>2?"getB(output_channel)":"0.0",F=A[0].dims,R=A[1].dims,$=R[1],N=R[0]/v.group,G=[A[0].dims[0],A[1].dims[1]*v.group,...v.outputShape],D=(0,l.getGlsl)(S.session.backend.glContext.version),{activationFunction:j,applyActivation:Q}=(0,s.getActivationSnippet)(v),X=` + 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 / ${$}; + int wOutChannel = output_channel - group_id * ${$}; + + float value = ${M}; + for (int inChannelOffset = 0; inChannelOffset < ${N}; inChannelOffset++) { + int input_channel = group_id * ${N} + inChannelOffset; + for (int wWOff = 0; wWOff < ${R[2]}; wWOff++) { + for (int wHOff = 0; wHOff < ${R[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 < ${F[2]} && + wLocIn.y >= 0 && wLocIn.y < ${F[3]} + ) { + float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x); + float wVal = getW(input_channel, wOutChannel, wHOff, wWOff); + value += xVal * wVal; + } + } + } + } + ${Q} + ${D.output} = vec4(value, .0, .0, .0); + } +`;return Object.assign(Object.assign({},O),{output:{dims:G,type:A[0].type,textureType:d.TextureType.unpacked},shaderSource:X,hasMain:!0})})(g,m,y,b)})})(r,i,h),i),t=(r,i)=>{const h=r.kernelShape.slice();if(r.kernelShape.length===0)for(let y=2;y{const F=y.length-2,R=M.length===0;for(let $=0;${const i=r.attributes,h=(0,s.parseInternalActivationAttributes)(i),g=i.getString("auto_pad","NOTSET"),m=i.getInts("dilations",[1,1]),b=i.getInt("group",1),y=i.getInts("kernel_shape",[]),w=i.getInts("output_padding",[0,0]),T=i.getInts("output_shape",[]),S=i.getInts("pads",[0,0,0,0]),A=i.getInts("strides",[1,1]);return(0,u.createAttributeWithCacheKey)(Object.assign({autoPad:g,dilations:m,group:b,kernelShape:y,outputPadding:w,outputShape:T,pads:S,strides:A},h))};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 h=r[1].dims[1]*i.group;if(r.length===3&&(r[2].dims.length!==1||r[2].dims[0]!==h))throw new Error("invalid bias");const g=r[0].dims.length-2;if(i.dilations.length!==g)throw new Error(`dilations should be ${g}D`);if(i.strides.length!==g)throw new Error(`strides should be ${g}D`);if(i.pads.length!==2*g)throw new Error(`pads should be ${2*g}D`);if(i.outputPadding.length!==g)throw new Error(`output_padding should be ${g}D`);if(i.kernelShape.length!==0&&i.kernelShape.length!==r[1].dims.length-2)throw new Error("invalid kernel shape");if(i.outputShape.length!==0&&i.outputShape.length!==r[0].dims.length-2)throw new Error("invalid output shape");if(r[0].type!=="float32"||r[1].type!=="float32")throw new Error("ConvTranspose input(X,W) should be float tensor");if(r.length===3&&r[2].type!=="float32")throw new Error("ConvTranspose input(bias) should be float tensor")}},8138:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConvAttributes=n.conv=n.calculateOutputShape=void 0;const u=o(246),l=o(2517),d=o(4770),s=o(1386),p=o(9828),f=o(2823),c=o(3248),a=o(5623);n.calculateOutputShape=(g,m,b,y,w)=>{const T=g[0],S=g.slice(2),A=S.length,O=m[0],v=m.slice(2).map((F,R)=>F+(F-1)*(b[R]-1)),M=S.map((F,R)=>F+y[R]+y[R+A]).map((F,R)=>Math.floor((F-v[R]+w[R])/w[R]));return[T,O].concat(...M)},n.conv=(g,m,b)=>(h(m,b),t(g,m,b));const t=(g,m,b)=>{const y=i(b,m),w=g.session.pack,T=y.kernelShape[0]===1&&y.kernelShape[1]===1;return y.group>1?[g.run((0,d.createUnpackedGroupedConvProgramInfoLoader)(g,m,y),m)]:T&&w?[e(g,m,y)]:w&&m[0].dims.length===4&&m[0].dims[0]===1&&!T?[(0,s.conv2DPacked)(g,m,y)]:[r(g,m,y)]},e=(g,m,b)=>{const y=m[0].dims,w=m[1].dims,T=(0,n.calculateOutputShape)(y,w,b.dilations,b.pads,b.strides),S=g.reshapeUnpacked(m[0],[y[1],y[2]*y[3]]),A=g.reshapeUnpacked(m[1],[w[0],w[1]]),O=m.length>2?[A,S,m[2]]:[A,S],v=g.run((0,a.createMatmulProgramInfoLoader)(O,b),O);return g.reshapeUnpacked(v,T)},r=(g,m,b)=>{const y=m[0].dims,w=m[1].dims,T=(0,n.calculateOutputShape)(y,w,b.dilations,b.pads,b.strides),S=g.run((0,c.createIm2ColProgramInfoLoader)(g,m[0],m[1],T,b),[m[0]]),A=m.length===3?[S,m[1],m[2]]:[S,m[1]];return g.run((0,p.createDotProductProgramInfoLoader)(g,m,T,b),A)},i=(g,m)=>{const b=g.kernelShape.slice();if(g.kernelShape.length===0)for(let T=2;T{const m=g.attributes,b=(0,f.parseInternalActivationAttributes)(m),y=m.getString("auto_pad","NOTSET"),w=m.getInts("dilations",[1,1]),T=m.getInt("group",1),S=m.getInts("kernel_shape",[]),A=m.getInts("pads",[0,0,0,0]),O=m.getInts("strides",[1,1]);return(0,u.createAttributeWithCacheKey)(Object.assign({autoPad:y,dilations:w,group:T,kernelShape:S,pads:A,strides:O},b))};const h=(g,m)=>{if(!g||g.length!==2&&g.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(g[0].dims.length!==4||g[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(g[0].dims[1]!==g[1].dims[1]*m.group)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(g.length===3&&(g[2].dims.length!==1||g[1].dims[0]!==g[2].dims[0]))throw new Error("invalid bias");const b=g[0].dims.length-2;if(m.dilations.length!==b)throw new Error(`dilations should be ${b}D`);if(m.strides.length!==b)throw new Error(`strides should be ${b}D`);if(m.pads.length!==2*b)throw new Error(`pads should be ${2*b}D`);if(m.kernelShape.length!==0&&m.kernelShape.length!==g[1].dims.length-2)throw new Error("invalid kernel shape");if(g[0].type!=="float32"||g[1].type!=="float32")throw new Error("Conv input(X,W) should be float tensor");if(g.length===3&&g[2].type!=="float32")throw new Error("Conv input(bias) should be float tensor")}},5193:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseDepthToSpaceAttributes=n.depthToSpace=void 0;const u=o(3738);n.depthToSpace=(d,s,p)=>{l(s);const f=p.blocksize,c=f*f,a=p.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],t=p.mode==="DCR"?[s[0].dims[0],f,f,s[0].dims[1]/c,s[0].dims[2],s[0].dims[3]]:[s[0].dims[0],s[0].dims[1]/c,f,f,s[0].dims[2],s[0].dims[3]],e=d.reshapeUnpacked(s[0],t),r={perm:a,cacheKey:`${a}`},[i]=(0,u.transpose)(d,[e],r),h=[s[0].dims[0],s[0].dims[1]/c,s[0].dims[2]*f,s[0].dims[3]*f];return[d.reshapeUnpacked(i,h)]},n.parseDepthToSpaceAttributes=d=>{const s=d.attributes.getInt("blocksize");if(s<1)throw new Error(`blocksize must be >= 1, but got : ${s} for DepthToSpace`);const p=d.attributes.getString("mode","DCR");if(p!=="DCR"&&p!=="CRD")throw new Error(`unrecognized mode: ${p} for DepthToSpace`);return{mode:p,blocksize:s}};const l=d=>{if(d.length!==1)throw new Error(`DepthToSpace expect 1 inputs, but got ${d.length}`);if(d[0].type==="string"||d[0].dims.length!==4)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}},9828:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createDotProductProgramInfoLoader=void 0;const u=o(2517),l=o(5060),d=o(2039),s=o(2823),p=o(3248);n.createDotProductProgramInfoLoader=(f,c,a,t)=>{const e=((r,i)=>({name:"ConvDotProduct",inputNames:r?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:r?[d.TextureType.unpacked,d.TextureType.packedLastDimension,d.TextureType.unpacked]:[d.TextureType.unpacked,d.TextureType.packedLastDimension],cacheKey:i.activationCacheKey}))(c.length>2,t);return Object.assign(Object.assign({},e),{get:()=>((r,i,h,g,m)=>{const b=h[0].dims,y=h[1].dims,w=[y[0],Math.ceil(b[1]*y[2]*y[3]/4)],T=(0,p.calculateIm2ColDims)(b,y,g),[S,A]=r.calculateTextureWidthAndHeight(w,d.TextureType.packedLastDimension),O=u.ShapeUtil.computeStrides(T),[v,M]=r.calculateTextureWidthAndHeight(T,d.TextureType.packedLastDimension),F=g.length,R=h.length<3?"0.0":"_B(b)",$=Math.ceil(b[1]*y[2]*y[3]/4),{activationFunction:N,applyActivation:G}=(0,s.getActivationSnippet)(m),D=(0,l.getGlsl)(r.session.backend.glContext.version),j=` +${N} +float process(int indices[${F}]) { + int b[1]; + b[0] = indices[1]; + int im2col[4]; + im2col[0] = indices[0]; + im2col[1] = indices[2]; + im2col[2] = indices[3]; + int im2colOffset = im2col[0] * ${O[0]} + im2col[1] * ${O[1]} + im2col[2] * ${O[2]}; + int kernelOffset = indices[1] * ${w[1]}; + float value = ${R}; + for (int i = 0; i < ${$}; ++i) { + vec2 im2colCoords = offsetToCoords(im2colOffset, ${v}, ${M}); + vec2 kernelCoords = offsetToCoords(kernelOffset, ${S}, ${A}); + value += dot(${D.texture2D}(Im2Col, im2colCoords), ${D.texture2D}(K, kernelCoords)); + ++im2colOffset; + ++kernelOffset; + } + ${G} + return value; +}`;return Object.assign(Object.assign({},i),{output:{dims:g,type:h[0].type,textureType:d.TextureType.unpacked},shaderSource:j})})(f,e,c,a,t)})}},7992:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseFlattenAttributes=n.flatten=void 0;const u=o(2517);n.flatten=(d,s,p)=>{l(s,p);const f=u.ShapeUtil.flattenShape(s[0].dims,p);return[d.reshapeUnpacked(s[0],f)]},n.parseFlattenAttributes=d=>d.attributes.getInt("axis",1);const l=(d,s)=>{if(!d||d.length!==1)throw new Error("Flatten requires 1 input.");const p=d[0].dims.length;if(p===0)throw new Error("scalar tensor is not supported.");if(s<-p||s>p)throw new Error("Invalid axis");if(d[0].type==="string")throw new Error("string tensor is not supported.")}},2823:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInternalActivationAttributes=n.getActivationSnippet=void 0;const u=o(2517),l=o(4909);n.getActivationSnippet=function(d){let s;switch(d.activation){case"Relu":s=(0,l.glslRelu)();break;case"Sigmoid":s=(0,l.glslSigmoid)();break;case"Clip":s=(0,l.glslClip)(d.clipMin,d.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const p=s.name;return{activationFunction:s.body,applyActivation:`value = ${p}_(value);`}},n.parseInternalActivationAttributes=d=>{const s=d.getString("activation","");if(s==="Clip"){const[p,f]=d.getFloats("activation_params",[u.MIN_CLIP,u.MAX_CLIP]);return{activation:s,clipMax:f,clipMin:p,activationCacheKey:`${s}:${p},${f}`}}return{activation:s,activationCacheKey:s}}},1253:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGatherAttributes=n.gather=void 0;const u=o(246),l=o(782),d=o(2517),s=o(2039);n.gather=(a,t,e)=>(c(t,e.axis),[a.run(f(a,t,e),t)]),n.parseGatherAttributes=a=>(0,u.createAttributeWithCacheKey)({axis:a.attributes.getInt("axis",0)});const p={name:"Gather",inputNames:["A","B"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked]},f=(a,t,e)=>{const r=Object.assign(Object.assign({},p),{cacheHint:e.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((i,h,g,m)=>{const b=g[0].dims.slice(),y=g[1].dims.slice(),w=new Array(b.length+y.length-1);m=d.ShapeUtil.normalizeAxis(m,b.length);const T=[];for(let A=0;A{if(!a||a.length!==2)throw new Error("Gather requires 2 inputs.");const e=a[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(a[0].type)===-1)throw new Error("Invaid input type.");if(a[1].type!=="int32"&&a[1].type!=="int16")throw new Error("Invaid input type.")}},4776:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGemmAttributesV11=n.parseGemmAttributesV7=n.gemm=void 0;const u=o(246),l=o(2517),d=o(2039);n.gemm=(a,t,e)=>(c(t,e),[a.run(p(t,e),t)]);const s=(a,t)=>{const e=a.attributes.getInt("transA",0)!==0,r=a.attributes.getInt("transB",0)!==0,i=a.attributes.getFloat("alpha",1),h=a.attributes.getFloat("beta",1);return(0,u.createAttributeWithCacheKey)({transA:e,transB:r,alpha:i,beta:h,isOptionalC:t})};n.parseGemmAttributesV7=a=>s(a,!1),n.parseGemmAttributesV11=a=>s(a,!0);const p=(a,t)=>{const e={name:"Gemm",inputNames:a.length===3?["A","B","C"]:["A","B"],inputTypes:a.length===3?[d.TextureType.unpacked,d.TextureType.unpacked,d.TextureType.unpacked]:[d.TextureType.unpacked,d.TextureType.unpacked],key:t.cacheKey};return Object.assign(Object.assign({},e),{get:()=>f(e,a,t)})},f=(a,t,e)=>{const r=t[0].dims.slice(),i=t[1].dims.slice(),[h,g]=l.GemmUtil.getShapeOfGemmResult(r,e.transA,i,e.transB,t.length===3?t[2].dims:void 0),m=[h,g];if(!m)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 w=m.length,T=` + float process(int indices[${w}]) { + int a[${w}]; + int b[${w}]; + ${t.length===3?`int c[${t[2].dims.length}];`:""} + + copyVec(indices, a); + copyVec(indices, b); + ${t.length===3?"bcastIndices_C(indices, c);":""} + + float value = 0.0; + for (int k=0; k<${b}; ++k) { + a[${w-1}] = k; + b[${w-2}] = k; + ${y} + } + + value = value * alpha; + ${t.length===3?"value += beta * _C(c);":""} + return value; + }`;return Object.assign(Object.assign({},a),{output:{dims:m,type:t[0].type,textureType:d.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:e.alpha},{name:"beta",type:"float",data:e.beta}],shaderSource:T})},c=(a,t)=>{if(!a)throw new Error("Input is missing");if(t.isOptionalC&&(a.length<2||a.length>3))throw new Error("Invaid input shape.");if(!t.isOptionalC&&a.length!==3)throw new Error("Gemm requires 3 inputs");if(a.length===3&&a[2].dims.length!==1&&a[2].dims.length!==2)throw new Error("Invalid input shape of C");if(a[0].type!=="float32"&&a[0].type!=="float64"||a[1].type!=="float32"&&a[1].type!=="float64"||a.length===3&&a[2].type!=="float32"&&a[2].type!=="float64")throw new Error("Invalid input type.");if(a[0].type!==a[1].type||a.length===3&&a[0].type!==a[2].type)throw new Error("Input types are mismatched")}},8555:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedIm2ColProgramInfoLoader=void 0;const u=o(5060),l=o(2039),d=o(2827);n.createPackedIm2ColProgramInfoLoader=(s,p,f,c,a)=>{const t=(e=a.cacheKey,{name:"Im2Col (packed)",inputNames:["A"],inputTypes:[l.TextureType.packed],cacheHint:e});var e;return Object.assign(Object.assign({},t),{get:()=>((r,i,h,g,m,b)=>{const y=h.dims,w=g.dims,T=m.length,S=[w[1]*w[2]*w[3],m[2]*m[3]],A=w[2]*w[3],O=(0,d.unpackFromChannel)(),v=(0,u.getGlsl)(r.session.backend.glContext.version);let M="";for(let R=0;R<=1;R++)for(let $=0;$<=1;$++)M+=` + blockIndex = rc.x + ${$}; + pos = rc.y + ${R}; + + if(blockIndex < ${S[1]} && pos < ${S[0]}) { + offsetY = int(blockIndex / (${m[T-1]})) * ${b.strides[0]} - + ${b.pads[0]}; + d0 = offsetY + ${b.dilations[0]} * (imod(pos, ${A}) / ${w[2]}); + + if(d0 < ${y[2]} && d0 >= 0) { + offsetX = imod(blockIndex, ${m[T-1]}) * ${b.strides[1]} - + ${b.pads[1]}; + d1 = offsetX + ${b.dilations[1]} * imod(imod(pos, ${A}), ${w[2]}); + + if(d1 < ${y[3]} && d1 >= 0) { + + ch = int(float(pos)/ ${A}.); + innerDims = vec2(d0, d1); + result[${2*R+$}] = getChannel( + getA(0, ch, int(innerDims.x), + int(innerDims.y)), innerDims); + } + } + } + + `;const F=` + ${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:h.type,textureType:l.TextureType.packed},shaderSource:F,hasMain:!0})})(s,t,p,f,c,a)})}},3248:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.calculateIm2ColDims=n.createIm2ColProgramInfoLoader=void 0;const u=o(2039);n.createIm2ColProgramInfoLoader=(l,d,s,p,f)=>{const c=(a=f.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[u.TextureType.unpacked],cacheHint:a});var a;return Object.assign(Object.assign({},c),{get:()=>((t,e,r,i,h,g)=>{const m=r.dims,b=i.dims,y=h.length,w=(0,n.calculateIm2ColDims)(m,b,h,4),T=` + const int XC = ${m[1]}; + const int XH = ${m[2]}; + const int XW = ${m[3]}; + const int KH = ${g.kernelShape[0]}; + const int KW = ${g.kernelShape[1]}; + const int dilationH = ${g.dilations[0]}; + const int dilationW = ${g.dilations[1]}; + const int strideH = ${g.strides[0]}; + const int strideW = ${g.strides[1]}; + const int padH = ${g.pads[0]}; + const int padW = ${g.pads[1]}; + const int KHKW = KH*KW; + const int XCKHKW = XC * KHKW; + const int outputChannels = 4; + vec4 process(int indices[${y}]) { + int b = indices[0]; // batch size + int oh = indices[1] * strideH - padH; //output height + int ow = indices[2] * strideW - padW; //output width + int p = indices[3] * outputChannels; //patch + vec4 value = vec4(0.0); + for(int i=0; i < outputChannels; ++i) { + if(p < XCKHKW) { + int patchC = p / KHKW; + int patchH = (p - patchC*KHKW) / KW; + int patchW = (p - patchC*KHKW) - patchH * KW; + int xh2 = oh + patchH * dilationH; + int xw2 = ow + patchW * dilationW; + int x[${m.length}]; + x[0] = b; + x[1] = patchC; + x[2] = xh2; + x[3] = xw2; + if(xh2 >= 0 && + xh2 < XH && + xw2 >= 0 && + xw2 < XW) { + value[i] = _X(x); + } + } + ++p; + } + return value; + } + `;return Object.assign(Object.assign({},e),{output:{dims:w,type:r.type,textureType:u.TextureType.packedLastDimension},shaderSource:T})})(0,c,d,s,p,f)})},n.calculateIm2ColDims=(l,d,s,p=4)=>[s[0],s[2],s[3],Math.ceil(l[1]*d[2]*d[3]/p)]},6572:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseImageScalerAttributes=n.imageScaler=void 0;const u=o(246),l=o(2039);n.imageScaler=(c,a,t)=>(f(a),[c.run(s(c,a,t),a)]),n.parseImageScalerAttributes=c=>{const a=c.attributes.getFloat("scale"),t=c.attributes.getFloats("bias");return(0,u.createAttributeWithCacheKey)({scale:a,bias:t})};const d={name:"ImageScaler",inputNames:["X"],inputTypes:[l.TextureType.unpacked]},s=(c,a,t)=>{const e=Object.assign(Object.assign({},d),{cacheHint:t.cacheKey});return Object.assign(Object.assign({},e),{get:()=>((r,i,h,g)=>{const m=h[0].dims.slice(),b=m.length,y=` + ${p(g.bias.length)} + float process(int indices[${b}]) { + return _X(indices) * scale + getBias(bias, indices[1]); + }`;return Object.assign(Object.assign({},i),{output:{dims:m,type:h[0].type,textureType:l.TextureType.unpacked},variables:[{name:"bias",type:"float",arrayLength:g.bias.length,data:g.bias},{name:"scale",type:"float",data:g.scale}],shaderSource:y})})(0,e,a,t)})},p=c=>{const a=[`float getBias(float bias[${c}], int channel) {`];for(let t=0;t{if(!c||c.length!==1)throw new Error("ImageScaler requires 1 input.");if(c[0].dims.length!==4)throw new Error("Invalid input shape.");if(c[0].type!=="float32"&&c[0].type!=="float64")throw new Error("Invalid input type.")}},3346:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInstanceNormalizationAttributes=n.instanceNormalization=void 0;const u=o(5060),l=o(2039);n.instanceNormalization=(a,t,e)=>{c(t);const r=a.run(s(t[0]),t);return[a.run(f(a,t[0],e,r.dims),[t[0],r,t[1],t[2]])]},n.parseInstanceNormalizationAttributes=a=>a.attributes.getFloat("epsilon",1e-5);const d={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[l.TextureType.unpacked]},s=a=>Object.assign(Object.assign({},d),{get:()=>((t,e)=>{const r=e.dims.slice(),i=r[1],h=r[2]*r[3],g=[r[0],i],m=` + vec4 process(int[2] indices) { + vec4 v = vec4(0.0); + int a[4]; + a[0] = indices[0]; + a[1] = indices[1]; + float temp = 0.0; + for(int a2=0; a2<${r[2]}; a2++) { + a[2] = a2; + for(int a3=0; a3<${r[3]}; a3++) { + a[3] = a3; + float x = _X(a); + temp += x; + } + } + float mean = temp / float(${h}); + 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(${h}); + + return v; + }`;return Object.assign(Object.assign({},t),{output:{dims:g,type:e.type,textureType:l.TextureType.packedLastDimension},shaderSource:m})})(d,a)}),p={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[l.TextureType.unpacked,l.TextureType.packedLastDimension,l.TextureType.unpacked,l.TextureType.unpacked]},f=(a,t,e,r)=>{const i=Object.assign(Object.assign({},p),{cacheHint:`${e}`});return Object.assign(Object.assign({},i),{get:()=>((h,g,m,b,y)=>{const w=(0,u.getGlsl)(h.session.backend.glContext.version),[T,S]=h.calculateTextureWidthAndHeight(y,l.TextureType.packedLastDimension),[A,O]=[T/4,S],v=` + vec4 get_MeanAndVariance(int[2] mv) { + int offset = indicesToOffset_MeanAndVariance(mv); + vec2 coords = offsetToCoords(offset, ${A}, ${O}); + return ${w.texture2D}(MeanAndVariance, coords); + } + + float process(int[4] indices) { + int mv[2]; + mv[0] = indices[0]; + mv[1] = indices[1]; + vec4 mean_and_variance = get_MeanAndVariance(mv); + float mean = mean_and_variance.r; + float variance = mean_and_variance.g; + + int sb[1]; + sb[0] = indices[1]; + float scale = _Scale(sb); + float b = _B(sb); + + return scale * (_X(indices) - mean) / sqrt(variance + epsilon) + b; + }`;return Object.assign(Object.assign({},g),{output:{dims:m.dims,type:m.type,textureType:l.TextureType.unpacked},variables:[{name:"epsilon",type:"float",data:b}],shaderSource:v})})(a,i,t,e,r)})},c=a=>{if(!a||a.length!==3)throw new Error("InstanceNormalization requires 3 inputs.");const t=a[0],e=a[1],r=a[2];if(t.dims.length<3||e.dims.length!==1||r.dims.length!==1)throw new Error("Invalid input shape.");if(e.dims[0]!==t.dims[1]||r.dims[0]!==t.dims[1])throw new Error("Input shapes are mismatched.");if(t.type!=="float32"&&t.type!=="float64"||e.type!=="float32"&&e.type!=="float64"||r.type!=="float32"&&r.type!=="float64")throw new Error("Invalid input type.");if(a[0].dims.length!==4)throw new Error("Only support 4-D input shape.")}},708:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedMatmulProgramInfoLoader=void 0;const u=o(2517),l=o(5060),d=o(2039),s=o(9390),p=o(2823),f=o(5623);n.createPackedMatmulProgramInfoLoader=(c,a,t)=>{const e=(r=a.length>2,i=t.activationCacheKey,{name:"MatMul (packed)",inputNames:r?["A","B","Bias"]:["A","B"],inputTypes:r?[d.TextureType.packed,d.TextureType.packed,d.TextureType.packed]:[d.TextureType.packed,d.TextureType.packed],cacheHint:i});var r,i;return Object.assign(Object.assign({},e),{get:()=>((h,g,m,b)=>{const y=m.length>2,w=y?"value += getBiasForMatmul();":"",T=m[0].dims,S=m[1].dims,A=u.BroadcastUtil.calcShape(T,S,!0),O=!u.ShapeUtil.areEqual(m[0].dims,m[1].dims);if(!A)throw new Error("Can't use matmul on the given tensors");const v=T[T.length-1],M=Math.ceil(v/2),F=T.length,R=S.length,$=(0,l.getGlsl)(h.session.backend.glContext.version),N=(0,s.getCoordsDataType)(A.length),G=A.length,D=(0,s.getGlChannels)(),{activationFunction:j,applyActivation:Q}=(0,p.getActivationSnippet)(b),X=y?`${(0,f.getBiasForMatmul)(N,D,m[2].dims,A,!0)}`:"",Z=O?`${function(ve,oe,we,be){let ke=[],Le=[];const xe=we[0].dims,Fe=we[1].dims,Ce=xe.length,Pe=Fe.length,Oe=be.length,Be=Oe-Ce,Ge=Oe-Pe;ke=xe.map((Me,je)=>`coords.${oe[je+Be]}`),ke[Ce-1]="i*2",ke.join(", "),Le=Fe.map((Me,je)=>`coords.${oe[je+Ge]}`),Le[Pe-2]="i*2",Le.join(", ");const Ve=u.BroadcastUtil.getBroadcastDims(xe,be),Xe=u.BroadcastUtil.getBroadcastDims(Fe,be),Qe=Ve.map(Me=>`coords.${oe[Me+Be]} = 0;`).join(` +`),qe=Xe.map(Me=>`coords.${oe[Me+Ge]} = 0;`).join(` +`),Ue=`int lastDim = coords.${oe[Oe-1]}; + coords.${oe[Oe-1]} = coords.${oe[Oe-2]}; + coords.${oe[Oe-2]} = lastDim;`;return` +vec4 getAAtOutCoordsMatmul(int i) { + ${ve} coords = getOutputCoords(); + ${Ue} + ${Qe} + vec4 outputValue = getA(${ke}); + return outputValue; +} + +vec4 getBAtOutCoordsMatmul(int i) { + ${ve} coords = getOutputCoords(); + ${Ue} + ${qe} + vec4 outputValue = getB(${Le}); + return outputValue; +}`}(N,D,m,A)}`:"",ee=O?"getAAtOutCoordsMatmul(i)":`getA(${function(ve,oe){let we="";for(let be=0;be{Object.defineProperty(n,"__esModule",{value:!0}),n.getBiasForMatmul=n.createMatmulProgramInfoLoader=n.parseMatMulAttributes=n.matMul=void 0;const u=o(2517),l=o(2039),d=o(9390),s=o(2823),p=o(708);function f(t,e){const r=(i=t.length>2,h=e.activationCacheKey,{name:"MatMul",inputNames:i?["A","B","Bias"]:["A","B"],inputTypes:i?[l.TextureType.unpacked,l.TextureType.unpacked,l.TextureType.unpacked]:[l.TextureType.unpacked,l.TextureType.unpacked],cacheHint:h});var i,h;return Object.assign(Object.assign({},r),{get:()=>function(g,m,b){const y=m[0].dims,w=m[1].dims,T=u.BroadcastUtil.calcShape(y,w,!0);if(!T)throw new Error("Can't use matmul on the given tensors");const S=(0,d.getCoordsDataType)(T.length),A=(0,d.getGlChannels)(),{activationFunction:O,applyActivation:v}=(0,s.getActivationSnippet)(b),M=m.length>2,F=M?"value += getBiasForMatmul();":"",R=M?`${a(S,A,m[2].dims,T,!1)}`:"",$=T.length,N=y.length,G=w.length,D=` + ${O} + ${R} + float process(int indices[${$}]) { + int a[${N}]; + int b[${G}]; + bcastMatmulIndices_A(indices, a); + bcastMatmulIndices_B(indices, b); + + float value; + for (int k=0; k<${y[y.length-1]}; ++k) { + a[${N-1}] = k; + b[${G-2}] = k; + value += _A(a) * _B(b); + } + ${F} + ${v} + return value; + }`;return Object.assign(Object.assign({},g),{output:{dims:T,type:m[0].type,textureType:l.TextureType.unpacked},shaderSource:D})}(r,t,e)})}n.matMul=(t,e,r)=>(c(e),t.session.pack?[t.run((0,p.createPackedMatmulProgramInfoLoader)(t,e,r),e)]:[t.run(f(e,r),e)]),n.parseMatMulAttributes=t=>(0,s.parseInternalActivationAttributes)(t.attributes),n.createMatmulProgramInfoLoader=f;const c=t=>{if(!t||t.length!==2)throw new Error("MatMul requires 2 inputs.");if(t[0].dims[t[0].dims.length-1]!==t[1].dims[t[1].dims.length-2])throw new Error("shared dimension does not match.");if(t[0].type!=="float32"&&t[0].type!=="float64"||t[1].type!=="float32"&&t[1].type!=="float64")throw new Error("inputs should be float type");if(t[0].type!==t[1].type)throw new Error("inputs types should match")};function a(t,e,r,i,h){let g="";const m=r.length,b=i.length,y=b-m;g=b<2&&m>0?"coords":r.map((S,A)=>`coords.${e[A+y]}`).join(", ");const w=u.BroadcastUtil.getBroadcastDims(r,i).map(S=>`coords.${e[S+y]} = 0;`).join(` +`);let T="vec4(outputValue.xx, outputValue.yy)";return u.ShapeUtil.size(r)===1&&(T="vec4(outputValue.x)"),h?` +vec4 getBiasForMatmul() { + ${t} coords = getOutputCoords(); + ${w} + vec4 outputValue = getBias(${g}); + return ${T}; +}`:` +float getBiasForMatmul() { + ${t} coords = getOutputCoords(); + ${w} + return getBias(coords.x); +}`}n.getBiasForMatmul=a},2403:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackProgramInfoLoader=void 0;const u=o(5060),l=o(2039),d=o(9390),s=o(2827),p={name:"pack",inputNames:["A"],inputTypes:[l.TextureType.unpackedReversed]};n.createPackProgramInfoLoader=(f,c)=>Object.assign(Object.assign({},p),{get:()=>((a,t)=>{const e=(0,u.getGlsl)(a.session.backend.glContext.version),r=t.dims,i=r.length,h=t.dims.length,g=(0,d.getCoordsDataType)(h),m=(0,s.getChannels)("rc",h),b=(y=h,w=m,T=r[r.length-2],S=r[r.length-1],y===0||y===1?"":` + int r = ${w[y-2]}; + int c = ${w[y-1]}; + int rp1 = ${w[y-2]} + 1; + int cp1 = ${w[y-1]} + 1; + bool rEdge = rp1 >= ${S}; + bool cEdge = cp1 >= ${T}; + `);var y,w,T,S;let A;A=i===0?[1,1]:i===1?[r[0],1]:[r[h-1],r[h-2]];const O=function(F,R,$){if(F===0)return"false";if(F===1)return`rc > ${R[0]}`;let N="";for(let G=F-2;G= ${R[G-F+2]}`,G= ${F[0]} ? 0. : getA(rc + 1), + 0, 0`;let N="";if($>2)for(let G=0;G<$-2;++G)N+=`${R[G]},`;return`getA(${N}r, c), + rEdge ? 0. : getA(${N}rp1, c), + cEdge ? 0. : getA(${N}r, cp1), + rEdge || cEdge ? 0. : getA(${N}rp1, cp1)`}(r,m),M=` + void main() { + ${g} rc = getOutputCoords(); + + if(${O}) { + ${e.output} = vec4(0); + } else { + ${b} + + ${e.output} = vec4(${v}); + } + } + `;return Object.assign(Object.assign({},p),{hasMain:!0,output:{dims:t.dims,type:t.type,textureType:l.TextureType.packed},shaderSource:M})})(f,c)})},2827:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.unpackFromChannel=n.getChannels=n.getVecChannels=void 0;const u=o(9390);function l(d,s){return(0,u.getGlChannels)(s).map(p=>`${d}.${p}`)}n.getVecChannels=l,n.getChannels=function(d,s){return s===1?[d]:l(d,s)},n.unpackFromChannel=function(){return` + float getChannel(vec4 frag, int dim) { + int modCoord = imod(dim, 2); + return modCoord == 0 ? frag.r : frag.g; + } + + float getChannel(vec4 frag, vec2 innerDims) { + vec2 modCoord = mod(innerDims, 2.); + return modCoord.x == 0. ? + (modCoord.y == 0. ? frag.r : frag.g) : + (modCoord.y == 0. ? frag.b : frag.a); + } + `}},2870:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parsePadAttributesV11=n.padV11=n.parsePadAttributesV2=n.padV2=void 0;const u=o(246),l=o(2517),d=o(5060),s=o(2039),p={name:"Pad",inputNames:["A"],inputTypes:[s.TextureType.unpacked]};n.padV2=(g,m,b)=>(a(m),[g.run(Object.assign(Object.assign({},p),{cacheHint:b.cacheKey,get:()=>c(g,m[0],b)}),m)]),n.parsePadAttributesV2=g=>{const m=g.attributes.getString("mode","constant"),b=g.attributes.getFloat("value",0),y=g.attributes.getInts("pads");return(0,u.createAttributeWithCacheKey)({mode:m,value:b,pads:y})},n.padV11=(g,m,b)=>{t(m);const y=f(g,m,b);return(0,n.padV2)(g,[m[0]],y)},n.parsePadAttributesV11=g=>g.attributes.getString("mode","constant");const f=(g,m,b)=>{if(!g.session.isInitializer(m[1].dataId)||m.length>=3&&!g.session.isInitializer(m[2].dataId))throw new Error("dynamic pad attributes are not allowed");const y=Array.from(m[1].integerData),w=m.length>=3?m[2].floatData[0]:0;return(0,u.createAttributeWithCacheKey)({mode:b,pads:y,value:w})},c=(g,m,b)=>{const y=l.ShapeUtil.padShape(m.dims.slice(),b.pads),w=y.length,T=` + ${e(g,m,b)} + float process(int[${w}] indices) { + return padA(indices); + }`;return{name:"Pad",inputNames:["A"],inputTypes:[s.TextureType.unpacked],output:{dims:y,type:m.type,textureType:s.TextureType.unpacked},shaderSource:T}},a=g=>{if(!g||g.length!==1)throw new Error("Pad requires 1 input");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type.")},t=g=>{if(!g||g.length!==2&&g.length!==3)throw new Error("Pad requires 2 or 3 inputs");if(g[1].type!=="int32")throw new Error("Invalid input type.");if(g.length>=3&&g[2].type==="string")throw new Error("Invalid input type.")},e=(g,m,b)=>{const y=(0,d.getGlsl)(g.session.backend.glContext.version),[w,T]=g.calculateTextureWidthAndHeight(m.dims,s.TextureType.unpacked),S=l.ShapeUtil.computeStrides(m.dims);switch(b.mode){case"constant":return r(y,m.dims,S,w,T,b.pads,b.value);case"reflect":return i(y,m.dims,S,w,T,b.pads);case"edge":return h(y,m.dims,S,w,T,b.pads);default:throw new Error("Invalid mode")}},r=(g,m,b,y,w,T,S)=>{const A=m.length;let O="";for(let v=A-1;v>=0;--v)O+=` + k = m[${v}] - ${T[v]}; + if (k < 0) return constant; + if (k >= ${m[v]}) return constant; + offset += k * ${b[v]}; + `;return` + float padA(int m[${A}]) { + const float constant = float(${S}); + int offset = 0; + int k = 0; + ${O} + vec2 coords = offsetToCoords(offset, ${y}, ${w}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `},i=(g,m,b,y,w,T)=>{const S=m.length;let A="";for(let O=S-1;O>=0;--O)A+=` + k = m[${O}] - ${T[O]}; + if (k < 0) { k = -k; } + { + const int _2n_1 = ${2*(m[O]-1)}; + k = int( mod( float(k), float(_2n_1) ) ) ; + if(k >= ${m[O]}) { k = _2n_1 - k; } + } + offset += k * ${b[O]}; + `;return` + float padA(int m[${S}]) { + int offset = 0; + int k = 0; + ${A} + vec2 coords = offsetToCoords(offset, ${y}, ${w}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `},h=(g,m,b,y,w,T)=>{const S=m.length;let A="";for(let O=S-1;O>=0;--O)A+=` + k = m[${O}] - ${T[O]}; + if (k < 0) k = 0; + if (k >= ${m[O]}) k = ${m[O]-1}; + offset += k * ${b[O]}; + `;return` + float padA(int m[${S}]) { + int offset = 0; + int k = 0; + ${A} + vec2 coords = offsetToCoords(offset, ${y}, ${w}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `}},2143:(_,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 u=o(246),l=o(2517),d=o(2039);n.averagePool=(h,g,m)=>{t(g);const b={name:"AveragePool",inputNames:["X"],inputTypes:[d.TextureType.unpacked],cacheHint:m.cacheKey};return[h.run(Object.assign(Object.assign({},b),{get:()=>s(g,b,!1,m)}),g)]},n.parseAveragePoolAttributes=h=>{const g=h.attributes.getString("auto_pad","NOTSET"),m=h.attributes.getInt("ceil_mode",0),b=h.attributes.getInt("count_include_pad",0)!==0,y=h.attributes.getInts("kernel_shape"),w=h.attributes.getInts("strides",[]),T=h.attributes.getInts("pads",[]);if(m!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,u.createAttributeWithCacheKey)({autoPad:g,ceilMode:m,countIncludePad:b,kernelShape:y,strides:w,pads:T})};const s=(h,g,m,b)=>{const[y,w]=f(h,b,m),T=l.ShapeUtil.size(y.kernelShape);let S="";y.countIncludePad?S+=`value /= float(${T});`:S+=`value /= float(${T} - pad);`;const A=` + ${e(h[0].dims,y,"value += _X(x);",S,"0.0")} + `;return Object.assign(Object.assign({},g),{output:{dims:w,type:h[0].type,textureType:d.TextureType.unpacked},shaderSource:A})};n.globalAveragePool=(h,g,m)=>{t(g);const b={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[d.TextureType.unpacked],cacheHint:`${m.countIncludePad}`};return[h.run(Object.assign(Object.assign({},b),{get:()=>s(g,b,!0,m)}),g)]},n.parseGlobalAveragePoolAttributes=h=>{const g=h.attributes.getInt("count_include_pad",0)!==0;return(0,u.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:g,kernelShape:[],strides:[],pads:[]})},n.maxPool=(h,g,m)=>{t(g);const b={name:"MaxPool",inputNames:["X"],inputTypes:[d.TextureType.unpacked],cacheHint:m.cacheKey};return[h.run(Object.assign(Object.assign({},b),{get:()=>p(g,b,!1,m)}),g)]},n.parseMaxPoolAttributes=h=>{const g=h.attributes.getString("auto_pad","NOTSET"),m=h.attributes.getInt("ceil_mode",0),b=h.attributes.getInts("kernel_shape"),y=h.attributes.getInts("strides",[]),w=h.attributes.getInts("pads",[]),T=h.attributes.getInt("storage_order",0),S=h.attributes.getInts("dilations",[]);if(T!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(m!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return(0,u.createAttributeWithCacheKey)({autoPad:g,ceilMode:m,countIncludePad:!1,kernelShape:b,strides:y,pads:w,storageOrder:T,dilations:S})};const p=(h,g,m,b)=>{const[y,w]=f(h,b,m),T=` + ${e(h[0].dims,y,` + value = max(_X(x), value); + `,"","-1e5")} + `;return Object.assign(Object.assign({},g),{output:{dims:w,type:h[0].type,textureType:d.TextureType.unpacked},shaderSource:T})},f=(h,g,m)=>{const b=h[0].dims.slice(),y=Object.hasOwnProperty.call(g,"dilations"),w=g.kernelShape.slice(),T=g.strides.slice(),S=y?g.dilations.slice():[],A=g.pads.slice();l.PoolConvUtil.adjustPoolAttributes(m,b,w,T,S,A);const O=l.PoolConvUtil.computePoolOutputShape(m,b,T,S,w,A,g.autoPad),v=Object.assign({},g);return y?Object.assign(v,{kernelShape:w,strides:T,pads:A,dilations:S,cacheKey:g.cacheKey}):Object.assign(v,{kernelShape:w,strides:T,pads:A,cacheKey:g.cacheKey}),[v,O]},c={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},a={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[d.TextureType.unpacked]};n.globalMaxPool=(h,g)=>(t(g),[h.run(Object.assign(Object.assign({},a),{get:()=>p(g,a,!0,c)}),g)]);const t=h=>{if(!h||h.length!==1)throw new Error("Pool ops requires 1 input.");if(h[0].type!=="float32"&&h[0].type!=="float64")throw new Error("Invalid input type.")},e=(h,g,m,b,y)=>{const w=h.length;if(g.kernelShape.length<=2){const T=g.kernelShape[g.kernelShape.length-1],S=g.strides[g.strides.length-1],A=g.pads[g.pads.length/2-1],O=g.pads[g.pads.length-1],v=h[w-1];let M="",F="",R="";if(M=A+O!==0?` + for (int i = 0; i < ${T}; i++) { + x[${w} - 1] = indices[${w} - 1] * ${S} - ${A} + i; + if (x[${w} - 1] < 0 || x[${w} - 1] >= ${v}) { + pad++; + continue; + } + ${m} + }`:` + for (int i = 0; i < ${T}; i++) { + x[${w} - 1] = indices[${w} - 1] * ${S} - ${A} + i; + ${m} + }`,g.kernelShape.length===2){const $=g.kernelShape[g.kernelShape.length-2],N=g.strides[g.strides.length-2],G=g.pads[g.pads.length/2-2],D=g.pads[g.pads.length-2],j=h[w-2];F=G+D!==0?` + for (int j = 0; j < ${$}; j++) { + x[${w} - 2] = indices[${w} - 2] * ${N} - ${G} + j; + if (x[${w} - 2] < 0 || x[${w} - 2] >= ${j}) { + pad+= ${T}; + continue; + } + `:` + for (int j = 0; j < ${$}; j++) { + x[${w} - 2] = indices[${w} - 2] * ${N} - ${G} + j; + `,R=` + } + `}return` + float process(int indices[${w}]) { + int x[${w}]; + copyVec(indices, x); + + float value = ${y}; + int pad = 0; + ${F} + ${M} + ${R} + ${b} + return value; + } + `}{const T=l.ShapeUtil.size(g.kernelShape),S=l.ShapeUtil.computeStrides(g.kernelShape),A=S.length,O=g.pads.length,v=i(A),M=r(h,"inputDims"),F=r(g.pads,"pads"),R=r(S,"kernelStrides"),$=r(g.strides,"strides");let N="";return N=g.pads.reduce((G,D)=>G+D)?` + if (x[j] >= inputDims[j] || x[j] < 0) { + pad++; + isPad = true; + break; + } + } + if (!isPad) { + ${m} + }`:` + } + ${m} + `,` + ${v} + float process(int indices[${w}]) { + int x[${w}]; + copyVec(indices, x); + int offset[${A}]; + int pads[${O}]; + int inputDims[${w}]; + int kernelStrides[${A}]; + int strides[${A}]; + ${F} + ${M} + ${$} + ${R} + + float value = ${y}; + int pad = 0; + bool isPad = false; + for (int i = 0; i < ${T}; i++) { + offsetToIndices(i, kernelStrides, offset); + isPad = false; + for (int j = ${w} - ${A}; j < ${w}; j++) { + x[j] = indices[j] * strides[j - ${w} + ${A}] + + offset[j - ${w} + ${A}] - pads[j - 2]; + ${N} + } + ${b} + + return value; + } + `}},r=(h,g)=>{let m="";for(let b=0;b` + void offsetToIndices(int offset, int[${h}] strides, out int[${h}] indices) { + if (${h} == 0) { + return; + } + for (int i = 0; i < ${h} - 1; ++i) { + indices[i] = offset / strides[i]; + offset -= indices[i] * strides[i]; + } + indices[${h} - 1] = offset; + }`},4939:(_,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 u=o(246),l=o(782),d=o(2517),s=o(2039),p=(a,t,e,r,i)=>{c(t);const h={name:r,inputNames:["A"],inputTypes:[s.TextureType.unpacked]};return[a.run(Object.assign(Object.assign({},h),{cacheHint:e.cacheKey,get:()=>f(a,t,e,r,i,h)}),t)]};n.parseReduceAttributes=a=>{const t=a.attributes.getInts("axes",[]),e=a.attributes.getInt("keepdims",1)===1;return(0,u.createAttributeWithCacheKey)({axes:t,keepDims:e})};const f=(a,t,e,r,i,h)=>{const g=[],m=t[0].dims.length||1,b=[],y=d.ShapeUtil.normalizeAxes(e.axes,t[0].dims.length),w=i(t,y);let T=w[1];for(let A=0;A=0||y.length===0?(e.keepDims&&g.push(1),T=` + for(int j${A} = 0; j${A} < ${t[0].dims[A]}; j${A}++) { + inputIdx[${A}] = j${A}; + ${T} + }`):(b.push(`inputIdx[${A}] = outputIdx[${g.length}];`),g.push(t[0].dims[A]));const S=` + float process(int outputIdx[${g.length||1}]) { + float value; // final result + int inputIdx[${m}]; // addressing input data + ${b.join(` +`)} + ${w[0]} // init ops for reduce max/min + ${T} + ${w[2]} // final computation for reduce mean + return value; + }`;return Object.assign(Object.assign({},h),{output:{dims:g,type:t[0].type,textureType:s.TextureType.unpacked},shaderSource:S})},c=a=>{if(!a||a.length!==1)throw new Error("Reduce op requires 1 input.");if(l.NUMBER_TYPES.indexOf(a[0].type)===-1)throw new Error("Invalid input type.")};n.reduceSum=(a,t,e)=>p(a,t,e,"ReduceSum",()=>["value = 0.0;","value += _A(inputIdx);",""]),n.reduceMean=(a,t,e)=>p(a,t,e,"ReduceMean",(r,i)=>{let h=1;for(let g=0;g=0||i.length===0)&&(h*=r[0].dims[g]);return["value = 0.0;","value += _A(inputIdx);",`value /= ${h}.;`]}),n.reduceMax=(a,t,e)=>p(a,t,e,"ReduceMax",(r,i)=>{const h=[];for(let g=0;g=0||i.length===0)&&h.push(`inputIdx[${g}] = 0;`);return[`${h.join(` +`)} +value = _A(inputIdx);`,"value = max(value, _A(inputIdx));",""]}),n.reduceMin=(a,t,e)=>p(a,t,e,"ReduceMin",(r,i)=>{const h=[];for(let g=0;g=0||i.length===0)&&h.push(`inputIdx[${g}] = 0;`);return[`${h.join(` +`)} +value = _A(inputIdx);`,"value = min(value, _A(inputIdx));",""]}),n.reduceProd=(a,t,e)=>p(a,t,e,"ReduceProd",()=>["value = 1.0;","value *= _A(inputIdx);",""]),n.reduceLogSum=(a,t,e)=>p(a,t,e,"ReduceLogSum",()=>["value = 0.0;","value += _A(inputIdx);","value = log(value);"]),n.reduceLogSumSquare=(a,t,e)=>p(a,t,e,"ReduceLogSumSquare",()=>["float t; value = 0.0;","t = _A(inputIdx); value += t * t;",""])},7019:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.isReshapeCheap=n.processDims3D=n.createPackedReshape3DProgramInfoLoader=void 0;const u=o(2517),l=o(5060),d=o(2039),s=o(2827);n.createPackedReshape3DProgramInfoLoader=(p,f,c)=>{const a=(t=>({name:"Reshape (packed)",inputTypes:[d.TextureType.packed],inputNames:["A"],cacheHint:`${t}`}))(c);return Object.assign(Object.assign({},a),{get:()=>((t,e,r,i)=>{const h=e.dims,g=i;let m="";for(let w=0;w<4;w++){let T="";switch(w){case 0:T="outputCoords = rc;";break;case 1:T="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:T="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:T="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}m+=` + ${T} + ${w>0?"if(outputCoords.y < rows && outputCoords.z < cols){":""} + int flattenedIndex = getFlattenedIndex(outputCoords); + + ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex); + vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z)); + + result[${w}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims); + + ${w>0?"}":""} + `}const b=(0,l.getGlsl)(t.session.backend.glContext.version),y=` + ${function(w){const T=u.ShapeUtil.computeStrides(w),S=["b","r","c"],A="index";return` + ivec3 inputCoordsFromReshapedOutCoords(int index) { + ${T.map((O,v)=>`int ${S[v]} = ${A} / ${O}; ${v===T.length-1?`int ${S[v+1]} = ${A} - ${S[v]} * ${O}`:`index -= ${S[v]} * ${O}`};`).join("")} + return ivec3(b, r, c); + } + `}(h)} + ${function(w){const T=u.ShapeUtil.computeStrides(w);return` + int getFlattenedIndex(ivec3 coords) { + // reverse y, z order + return coords.x * ${T[0]} + coords.z * ${T[1]} + coords.y; + } +`}(g)} + ${(0,s.unpackFromChannel)()} + + void main() { + ivec3 rc = getOutputCoords(); + + vec4 result = vec4(0.0); + + ivec3 outputCoords; + int rows = ${g[2]}; + int cols = ${g[1]}; + + ${m} + ${b.output} = result; + } + `;return Object.assign(Object.assign({},r),{output:{dims:g,type:e.type,textureType:d.TextureType.packed},shaderSource:y,hasMain:!0})})(p,f,a,c)})},n.processDims3D=function(p){if(p.length===0)return[1,1,1];let f=1;for(let c=0;c1?p[p.length-2]:1,p[p.length-1]]},n.isReshapeCheap=function(p,f){let c=!1;return c=p.length===0||f.length===0||(p.length<2||f.length<2?p[p.length-1]===f[f.length-1]:p[p.length-1]===f[f.length-1]&&p[p.length-2]===f[f.length-2]),c}},718:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.reshape=void 0;const u=o(2517);n.reshape=(l,d)=>{const s=u.ShapeUtil.calculateReshapedDims(d[0].dims,d[1].integerData);return l.session.pack?[l.reshapePacked(d[0],s)]:[l.reshapeUnpacked(d[0],s)]}},2268:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseResizeAttributesV11=n.parseResizeAttributesV10=n.resize=void 0;const u=o(5060),l=o(2039),d=o(9390),s=o(2827),p=o(9793),f={name:"Resize",inputNames:["A"],inputTypes:[l.TextureType.packed]};n.resize=(r,i,h)=>((0,p.validateInputs)(i,h),[r.run(Object.assign(Object.assign({},f),{cacheHint:h.cacheKey,get:()=>c(r,i,h)}),i)]),n.parseResizeAttributesV10=r=>(0,p.parseUpsampleAttributes)(r,10),n.parseResizeAttributesV11=r=>(0,p.parseUpsampleAttributes)(r,11);const c=(r,i,h)=>{const g=(0,u.getGlsl)(r.session.backend.glContext.version),[m,b]=a(i,h);if(m.every(N=>N===1)&&h.coordinateTransformMode!=="tf_crop_and_resize")return Object.assign(Object.assign({},f),{output:{dims:b,type:i[0].type,textureType:l.TextureType.packed},hasMain:!0,shaderSource:`void main() { + vec4 v = ${g.texture2D}(X, TexCoords); + ${g.output} = v; + }`});const y=b.length;if(y<2)throw new Error(`output dimension should be at least 2, but got ${y}`);const w=b[y-2],T=b[y-1],S=i[0].dims;if(y!==S.length)throw new Error(`output dimension should match input ${S.length}, but got ${y}`);const A=S[y-2],O=S[y-1],v=m[y-2],M=m[y-1];let F="";if(h.mode!=="linear")throw new Error(`resize (packed) does not support mode: '${h.mode}'`);switch(h.coordinateTransformMode){case"asymmetric":F=` + vec4 getSourceFracIndex(ivec4 coords) { + return vec4(coords) / scaleWHWH; + } + `;break;case"half_pixel":F=` + vec4 getSourceFracIndex(ivec4 coords) { + return (vec4(coords) + 0.5) / scaleWHWH - 0.5; + } + `;break;case"pytorch_half_pixel":F=` + vec4 getSourceFracIndex(ivec4 coords) { + vec4 fcoords = vec4(coords); + return vec4( + ${T}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0, + ${w}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0, + ${T}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0, + ${w}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0 + ); + } + `;break;case"align_corners":F=` + vec4 getSourceFracIndex(ivec4 coords) { + vec4 resized = vec4(${T}.0 - 1.0, ${w}.0 - 1.0, ${T}.0 - 1.0, + ${w}.0 - 1.0); + vec4 original = vec4(${O}.0 - 1.0, ${A}.0 - 1.0, ${O}.0 - 1.0, + ${A}.0 - 1.0); + vec4 new_scale = original / resized; + return vec4(coords) * new_scale; + } + `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode: '${h.coordinateTransformMode}'`)}const R=(0,d.getCoordsDataType)(y),$=` + const vec2 inputWH = vec2(${A}.0, ${O}.0); + const vec4 scaleWHWH = vec4(float(${v}), float(${M}), float(${v}), float(${M})); + ${(0,s.unpackFromChannel)()} + ${F} + float getAValue(int x10, int r, int c, int d) { + return getChannel(getA(x10, r, c, d), vec2(c, d)); + } + void main() { + ${R} rc = getOutputCoords(); + + int batch = rc[0]; + int depth = rc[1]; + + // retrieve the 4 coordinates that is used in the 4 packed output values. + ivec4 coords = ivec4(rc.wz, rc.w + 1, rc.z + 1); + + // calculate the source index in fraction + vec4 sourceFrac = getSourceFracIndex(coords); + + // get the lower and upper bound of the 4 values that will be packed into one texel. + ivec4 x00 = ivec4(max(sourceFrac.xy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xy))); + ivec4 x01 = ivec4(max(sourceFrac.xw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xw))); + ivec4 x10 = ivec4(max(sourceFrac.zy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zy))); + ivec4 x11 = ivec4(max(sourceFrac.zw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zw))); + + bool hasNextRow = rc.w < ${w-1}; + bool hasNextCol = rc.z < ${T-1}; + + // pack x00, x01, x10, x11's top-left corner into one vec4 structure + vec4 topLeft = vec4( + getAValue(batch, depth, x00.x, x00.y), + hasNextCol ? getAValue(batch, depth, x01.x, x01.y) : 0.0, + hasNextRow ? getAValue(batch, depth, x10.x, x10.y) : 0.0, + (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.y) : 0.0); + + // pack x00, x01, x10, x11's top-right corner into one vec4 structure + vec4 topRight = vec4( + getAValue(batch, depth, x00.x, x00.w), + hasNextCol ? getAValue(batch, depth, x01.x, x01.w) : 0.0, + hasNextRow ? getAValue(batch, depth, x10.x, x10.w) : 0.0, + (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.w) : 0.0); + + // pack x00, x01, x10, x11's bottom-left corner into one vec4 structure + vec4 bottomLeft = vec4( + getAValue(batch, depth, x00.z, x00.y), + hasNextCol ? getAValue(batch, depth, x01.z, x01.y) : 0.0, + hasNextRow ? getAValue(batch, depth, x10.z, x10.y) : 0.0, + (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.y) : 0.0); + + // pack x00, x01, x10, x11's bottom-right corner into one vec4 structure + vec4 bottomRight = vec4( + getAValue(batch, depth, x00.z, x00.w), + hasNextCol ? getAValue(batch, depth, x01.z, x01.w) : 0.0, + hasNextRow ? getAValue(batch, depth, x10.z, x10.w) : 0.0, + (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.w) : 0.0); + + // calculate the interpolation fraction on u and v direction + vec4 frac = vec4(sourceFrac) - floor(sourceFrac); + vec4 clampFrac = clamp(frac, vec4(0.0), vec4(1.0)); + + vec4 top = mix(topLeft, topRight, clampFrac.ywyw); + vec4 bottom = mix(bottomLeft, bottomRight, clampFrac.ywyw); + vec4 newValue = mix(top, bottom, clampFrac.xxzz); + + ${g.output} = vec4(newValue); + } + `;return Object.assign(Object.assign({},f),{output:{dims:b,type:i[0].type,textureType:l.TextureType.packed},hasMain:!0,shaderSource:$})},a=(r,i)=>{const h=r[0].dims;let g,m=i.scales;if(m.length===0){const y=r[i.scalesInputIdx];if(y&&y.size!==0){if(r[i.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");m=t(y,i.mode,i.isResize)}else{const w=r[i.sizesInputIdx];if(!w||w.size===0)throw new Error("Either scales or sizes MUST be provided as input.");g=Array.from(w.integerData),m=e(g,h,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=g||h.map((y,w)=>Math.floor(y*m[w]));return[m,b]},t=(r,i,h)=>{const g=Array.from(r.floatData);return(0,p.scalesValidation)(g,i,h),g},e=(r,i,h,g)=>{const m=i.length,b=new Array(m);for(let y=0,w=m;y{Object.defineProperty(n,"__esModule",{value:!0}),n.shape=void 0;const u=o(9162);n.shape=(d,s)=>(l(s),[new u.Tensor([s[0].dims.length],"int32",void 0,void 0,new Int32Array(s[0].dims))]);const l=d=>{if(!d||d.length!==1)throw new Error("Shape requires 1 input.")}},2278:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.sliceV10=n.parseSliceAttributes=n.slice=void 0;const u=o(246),l=o(782),d=o(2517),s=o(2039),p={name:"Slice",inputNames:["A"],inputTypes:[s.TextureType.unpacked]};n.slice=(e,r,i)=>(c(r),[e.run(Object.assign(Object.assign({},p),{cacheHint:i.cacheKey,get:()=>f(e,r[0],i)}),r)]),n.parseSliceAttributes=e=>{const r=e.attributes.getInts("starts"),i=e.attributes.getInts("ends"),h=e.attributes.getInts("axes",[]);return(0,u.createAttributeWithCacheKey)({starts:r,ends:i,axes:h})};const f=(e,r,i)=>{const h=i.axes.length===0?r.dims.slice(0).map((S,A)=>A):i.axes,g=d.ShapeUtil.normalizeAxes(h,r.dims.length),m=i.starts.map((S,A)=>S>r.dims[g[A]]-1?r.dims[g[A]]:d.ShapeUtil.normalizeAxis(S,r.dims[g[A]])),b=i.ends.map((S,A)=>S>r.dims[g[A]]-1?r.dims[g[A]]:d.ShapeUtil.normalizeAxis(S,r.dims[g[A]])),y=r.dims.slice(),w=[];for(let S=0;S0&&w.push(`outputIdx[${g[S]}] += ${m[S]};`);const T=` + float process(int outputIdx[${y.length}]) { + ${w.join(` + `)} + return _A(outputIdx); + }`;return Object.assign(Object.assign({},p),{output:{dims:y,type:r.type,textureType:s.TextureType.unpacked},shaderSource:T})},c=e=>{if(!e||e.length!==1)throw new Error("Slice requires 1 input.");if(l.NUMBER_TYPES.indexOf(e[0].type)===-1)throw new Error("Invalid input type.")};n.sliceV10=(e,r)=>{t(r);const i=a(e,r);return[e.run(Object.assign(Object.assign({},p),{cacheHint:i.cacheKey,get:()=>f(e,r[0],i)}),[r[0]])]};const a=(e,r)=>{if(!e.session.isInitializer(r[1].dataId)||!e.session.isInitializer(r[2].dataId)||r.length>=4&&!e.session.isInitializer(r[3].dataId)||r.length>=5&&!e.session.isInitializer(r[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(r.length>=5&&r[4].integerData.some(m=>m!==1))throw new Error("currently non-1 steps is not supported for Slice");const i=Array.from(r[1].integerData),h=Array.from(r[2].integerData),g=r.length>=4?Array.from(r[3].integerData):[];return{starts:i,ends:h,axes:g,cacheKey:`${g};${i};${h}`}},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:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.softmaxV13=n.parseSoftmaxAttributesV13=n.parseSoftmaxAttributes=n.softmax=void 0;const u=o(246),l=o(2517),d=o(5060),s=o(2039),p=o(3738),f={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[s.TextureType.unpacked]},c={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked]},a={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[s.TextureType.unpacked,s.TextureType.unpacked,s.TextureType.unpacked]};n.softmax=(g,m,b)=>{h(m);const y=m[0].dims.slice(),w=l.ShapeUtil.normalizeAxis(b.axis,y.length),T=l.ShapeUtil.sizeToDimension(y,w),S=l.ShapeUtil.sizeFromDimension(y,w);return t(g,m,b,T,S)},n.parseSoftmaxAttributes=g=>(0,u.createAttributeWithCacheKey)({axis:g.attributes.getInt("axis",1)}),n.parseSoftmaxAttributesV13=g=>(0,u.createAttributeWithCacheKey)({axis:g.attributes.getInt("axis",-1)}),n.softmaxV13=(g,m,b)=>{h(m);const y=m[0].dims.slice(),w=l.ShapeUtil.normalizeAxis(b.axis,y.length),T=y.length,S=w!==T-1,A=[];let O,v=[],M=[];S&&(v=Array.from({length:T}).map((N,G)=>G),v[w]=T-1,v[T-1]=w,v.map(N=>A.push(y[N])),O=(0,u.createAttributeWithCacheKey)({perm:v}),M=(0,p.transpose)(g,m,O));const F=S?l.ShapeUtil.sizeToDimension(A,T-1):l.ShapeUtil.sizeToDimension(y,T-1),R=S?l.ShapeUtil.sizeFromDimension(A,T-1):l.ShapeUtil.sizeFromDimension(y,T-1),$=t(g,S?M:m,b,F,R);return S?(0,p.transpose)(g,$,O):$};const t=(g,m,b,y,w)=>{const T=e(g,m[0],y,w,[y]),S=g.run(Object.assign(Object.assign({},f),{cacheHint:b.cacheKey,get:()=>T}),m),A=r(g,m[0],y,w,T.output.dims,[y]),O=g.run(Object.assign(Object.assign({},c),{cacheHint:b.cacheKey,get:()=>A}),[m[0],S]),v=i(g,m[0],y,w,T.output.dims,A.output.dims);return[g.run(Object.assign(Object.assign({},a),{cacheHint:b.cacheKey,get:()=>v}),[m[0],S,O])]},e=(g,m,b,y,w)=>{const[T,S]=g.calculateTextureWidthAndHeight(m.dims,s.TextureType.unpacked),A=w.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(w.length!==1)throw new Error("Dimensionality of the output should be 1");if(w[0]!==b)throw new Error("Shape of the output should be equal to logical row count");const O=(0,d.getGlsl)(g.session.backend.glContext.version),v=` + float process(int[${A}] indices) { + int logical_row_start_offset = indices[0] * ${y}; + + float max = getColorAsFloat(${O.texture2D}(A, offsetToCoords(logical_row_start_offset, ${T}, + ${S} ))); + for(int i=1; i<${y}; ++i) + { + float current = getColorAsFloat(${O.texture2D}(A, offsetToCoords(logical_row_start_offset + i, + ${T}, ${S}))); + if(current > max) + max = current; + } + + return max; + }`;return Object.assign(Object.assign({},f),{output:{dims:w,type:m.type,textureType:s.TextureType.unpacked},shaderSource:v})},r=(g,m,b,y,w,T)=>{const[S,A]=g.calculateTextureWidthAndHeight(m.dims,s.TextureType.unpacked),O=T.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(T.length!==1)throw new Error("Dimensionality of the output should be 1");if(T[0]!==b)throw new Error("Shape of the output should be equal to logical row count");if(w.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(w[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const v=` + float process(int[${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,d.getGlsl)(g.session.backend.glContext.version).texture2D}(A, offsetToCoords(logical_row_start_offset + i, + ${S}, ${A}))) - max); + } + + return norm_factor; + }`;return Object.assign(Object.assign({},c),{output:{dims:T,type:m.type,textureType:s.TextureType.unpacked},shaderSource:v})},i=(g,m,b,y,w,T)=>{const[S,A]=g.calculateTextureWidthAndHeight(m.dims,s.TextureType.unpacked),O=m.dims.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(w.length!==1||T.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(w[0]!==b||T[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const v=` + float process(int[${O}] indices) { + + // get offset of current logical tensor index from the 2-D texture coordinates (TexCoords) + int offset = coordsToOffset(TexCoords, ${S}, ${A}); + + //determine the logical row for this index + int logical_row_index[1]; + logical_row_index[0] = offset / ${y}; + + float norm_factor = _Norm(logical_row_index); + + // avoid possible division by 0 + // if norm_facor is 0, all elements are zero + // if so, return 0 + if(norm_factor == 0.0) + return 0.0; + + return exp(_A(indices) - _Max(logical_row_index)) / norm_factor; + }`;return Object.assign(Object.assign({},a),{output:{dims:m.dims,type:m.type,textureType:s.TextureType.unpacked},shaderSource:v})},h=g=>{if(!g||g.length!==1)throw new Error("Softmax requires 1 input.");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type")}},5975:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSplitAttributes=n.split=void 0;const u=o(246),l=o(2517),d=o(2039),s={name:"Split",inputNames:["A"],inputTypes:[d.TextureType.unpacked]};n.split=(a,t,e)=>{c(t);const r=l.ShapeUtil.normalizeAxis(e.axis,t[0].dims.length),i=p(a,t,r,e),h=[];for(let g=0;gf(a,t[0],e,r,g)}),t));return h},n.parseSplitAttributes=a=>{const t=a.attributes.getInt("axis",0),e=a.attributes.getInts("split",[]),r=a.outputs.length;return(0,u.createAttributeWithCacheKey)({axis:t,split:e,numOutputs:r})};const p=(a,t,e,r)=>{const[,i]=l.SplitUtil.splitShape(t[0].dims,e,r.split,r.numOutputs);return i.length},f=(a,t,e,r,i)=>{const[h,g]=l.SplitUtil.splitShape(t.dims,r,e.split,e.numOutputs),m=g[i],b=h[i],y=` + float process(int indices[${b.length}]) { + indices[${r}] += ${m}; + return _A(indices); + } + `;return Object.assign(Object.assign({},s),{cacheHint:`${e.cacheKey}:${i}`,output:{dims:b,type:t.type,textureType:d.TextureType.unpacked},shaderSource:y})},c=a=>{if(!a||a.length!==1)throw new Error("Split requires one input.");if(a[0].type!=="int8"&&a[0].type!=="uint8"&&a[0].type!=="int16"&&a[0].type!=="uint16"&&a[0].type!=="int32"&&a[0].type!=="uint32"&&a[0].type!=="float32"&&a[0].type!=="float64"&&a[0].type!=="bool")throw new Error("Invalid input type.")}},3933:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSqueezeAttributes=n.squeezeV13=n.squeeze=void 0;const u=o(2517);n.squeeze=(s,p,f)=>{l(p);const c=u.ShapeUtil.squeezeShape(p[0].dims,f);return[s.reshapeUnpacked(p[0],c)]},n.squeezeV13=(s,p)=>(d(p),(0,n.squeeze)(s,[p[0]],Array.from(p[1].integerData))),n.parseSqueezeAttributes=s=>s.attributes.getInts("axes");const l=s=>{if(!s||s.length!==1)throw new Error("Squeeze requires 1 input.");if(s[0].type==="string")throw new Error("invalid input tensor types.")},d=s=>{if(!s||s.length!==2)throw new Error("Squeeze requires 2 inputs.");if(s[1].type!=="int32")throw new Error("Invalid input type.")}},6558:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.sum=void 0;const u=o(5060),l=o(2039);n.sum=(p,f)=>{s(f);const c={name:"Sum",inputNames:f.map((a,t)=>`X${t}`),inputTypes:new Array(f.length).fill(l.TextureType.unpacked)};return[p.run(Object.assign(Object.assign({},c),{get:()=>d(p,f,c)}),f)]};const d=(p,f,c)=>{const a=(0,u.getGlsl)(p.session.backend.glContext.version),t=f[0].dims.slice(),e=` + void main() { + vec4 result = ${f.map((r,i)=>`${a.texture2D}(X${i},TexCoords)`).join(" + ")}; + ${a.output} = result; + } + `;return Object.assign(Object.assign({},c),{output:{dims:t,type:f[0].type,textureType:l.TextureType.unpacked},hasMain:!0,shaderSource:e})},s=p=>{if(!p||p.length===0)throw new Error("Sum requires inputs.");const f=p[0].dims.length;for(let c=1;c{Object.defineProperty(n,"__esModule",{value:!0}),n.tile=void 0;const u=o(782),l=o(2039);n.tile=(p,f)=>{s(f);const c={name:"Tile",inputNames:["A"],inputTypes:[l.TextureType.unpacked]};return[p.run(Object.assign(Object.assign({},c),{get:()=>d(p,f,c)}),f)]};const d=(p,f,c)=>{const a=f[0].dims.slice(),t=new Array(a.length),e=[];for(let h=0;h{if(!p||p.length!==2)throw new Error("Tile requires 2 input.");if(p[1].dims.length!==1)throw new Error("The second input shape must 1 dimension.");if(p[1].dims[0]!==p[0].dims.length)throw new Error("Invalid input shape.");if(u.NUMBER_TYPES.indexOf(p[0].type)===-1)throw new Error("Invalid input type.");if(p[1].type!=="int32"&&p[1].type!=="int16")throw new Error("Invalid repeat type.")}},3738:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseTransposeAttributes=n.transpose=void 0;const u=o(246),l=o(2517),d=o(2039),s={name:"Transpose",inputNames:["A"],inputTypes:[d.TextureType.unpacked]};n.transpose=(e,r,i)=>(t(r),[e.run(Object.assign(Object.assign({},s),{cacheHint:i.cacheKey,get:()=>p(e,r[0],i.perm)}),r)]),n.parseTransposeAttributes=e=>(0,u.createAttributeWithCacheKey)({perm:e.attributes.getInts("perm",[])});const p=(e,r,i)=>{const h=r.dims;i=f(h,i);const g=c(h,i),m=h.length,b=` + ${a("perm",i,m)} + float process(int indices[${m}]) { + int a[${m}]; + perm(a, indices); + return _A(a); + }`;return Object.assign(Object.assign({},s),{output:{dims:g,type:r.type,textureType:d.TextureType.unpacked},shaderSource:b})},f=(e,r)=>(r&&r.length!==e.length&&(r=[...e.keys()].reverse()),r),c=(e,r)=>(r=f(e,r),l.ShapeUtil.sortBasedOnPerm(e,r)),a=(e,r,i)=>{const h=[];h.push(`void ${e}(out int a[${i}], int src[${i}]) {`);for(let g=0;g{if(!e||e.length!==1)throw new Error("Transpose requires 1 input.");if(e[0].type!=="float32"&&e[0].type!=="float64")throw new Error("input should be float tensor")}},8710:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.encodeAsUint8=void 0;const u=o(5060),l=o(2039);n.encodeAsUint8=(d,s)=>{const p=s.shape,f=(0,u.getGlsl)(d.session.backend.glContext.version),c=` + const float FLOAT_MAX = 1.70141184e38; + const float FLOAT_MIN = 1.17549435e-38; + + bool isNaN(float val) { + return (val < 1.0 || 0.0 < val || val == 0.0) ? false : true; + } + + highp vec4 encodeAsUint8(highp float v) { + if (isNaN(v)) { + return vec4(255, 255, 255, 255); + } + + highp float av = abs(v); + + if(av < FLOAT_MIN) { + return vec4(0.0, 0.0, 0.0, 0.0); + } else if(v > FLOAT_MAX) { + return vec4(0.0, 0.0, 128.0, 127.0) / 255.0; + } else if(v < -FLOAT_MAX) { + return vec4(0.0, 0.0, 128.0, 255.0) / 255.0; + } + + highp vec4 c = vec4(0,0,0,0); + + highp float e = floor(log2(av)); + highp float m = exp2(fract(log2(av))) - 1.0; + + c[2] = floor(128.0 * m); + m -= c[2] / 128.0; + c[1] = floor(32768.0 * m); + m -= c[1] / 32768.0; + c[0] = floor(8388608.0 * m); + + highp float ebias = e + 127.0; + c[3] = floor(ebias / 2.0); + ebias -= c[3] * 2.0; + c[2] += floor(ebias) * 128.0; + + c[3] += 128.0 * step(0.0, -v); + + return c / 255.0; + } + + void main() { + float value = ${f.texture2D}(X,TexCoords).r; + ${f.output} = encodeAsUint8(value); + }`,a={name:"Uint8Encode",inputTypes:[l.TextureType.unpacked],inputNames:["X"],output:{dims:p,type:s.tensor.type,textureType:l.TextureType.downloadUint8AsFloat},shaderSource:c,hasMain:!0};return d.executeProgram(a,[s.tensor])}},4909:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.tanh=n.tan=n.sqrt=n.sin=n.sigmoid=n.relu=n.not=n.neg=n.log=n.parseLeakyReluAttributes=n.leakyRelu=n.identity=n.floor=n.exp=n.parseEluAttributes=n.elu=n.cos=n.ceil=n.clipV11=n.parseClipAttributes=n.clip=n.atan=n.asin=n.acos=n.abs=n.glslTanh=n.glslTan=n.glslSqrt=n.glslSigmoid=n.glslRelu=n.glslSin=n.glslNot=n.glslNeg=n.glslLog=n.glslLeakyRelu=n.glslIdentity=n.glslClip=n.glslFloor=n.glslExp=n.glslElu=n.glslCos=n.glslCeil=n.glslAtan=n.glslAsin=n.glslAcos=n.glslAbs=void 0;const u=o(246),l=o(2517),d=o(8520),s=o(5060),p=o(2039);function f(){return $("abs")}function c(){return $("acos")}function a(){return $("asin")}function t(){return $("atan")}function e(){return $("ceil")}function r(){return $("cos")}function i(D){const j="elu";return{body:` + const float alpha = float(${D}); + + 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:d.FunctionType.ValueBased}}function h(){return $("exp")}function g(){return $("floor")}function m(D,j){const Q="clip";return{body:` + const float min = float(${D}); + const float max = float(${j}); + + float ${Q}_(float a) { + return clamp(a, min, max); + } + vec4 ${Q}_(vec4 v) { + return clamp(v, min, max); + } + `,name:Q,type:d.FunctionType.ValueBased}}function b(){const D="indentity";return{body:` + float ${D}_(float a) { + return a; + } + vec4 ${D}_(vec4 v) { + return v; + } + `,name:D,type:d.FunctionType.ValueBased}}function y(D){const j="leakyRelu";return{body:` + const float alpha = float(${D}); + + float ${j}_(float a) { + return a < 0.0 ? a * alpha : a; + } + vec4 ${j}_(vec4 v) { + return vec4(${j}_(v.x), ${j}_(v.y), ${j}_(v.z), ${j}_(v.w)); + } + `,name:j,type:d.FunctionType.ValueBased}}function w(){return $("log")}function T(){const D="neg";return{body:` + float ${D}_(float a) { + return -a; + } + vec4 ${D}_(vec4 v) { + return -v; + } + `,name:D,type:d.FunctionType.ValueBased}}function S(){const D="not";return{body:` + float ${D}_(float a) { + return float( ! bool(a) ); + } + bool ${D}_(bool a) { + return !a; + } + vec4 ${D}_(vec4 v) { + return vec4(!bool(v.x), !bool(v.y), !bool(v.z), !bool(v.w)); + } + bvec4 ${D}_(bvec4 v) { + return bvec4(!v.x, !v.y, !v.z, !v.w); + } + `,name:D,type:d.FunctionType.ValueBased}}function A(){return $("sin")}function O(){const D="relu";return{body:` + float ${D}_(float a) { + return max( a, 0.0 ); + } + vec4 ${D}_(vec4 v) { + return max( v, 0.0 ); + } + `,name:D,type:d.FunctionType.ValueBased}}function v(){const D="sigmoid";return{body:` + float ${D}_(float a) { + return 1.0 / (1.0 + exp(-a)); + } + vec4 ${D}_(vec4 v) { + return 1.0 / (1.0 + exp(-v)); + } + `,name:D,type:d.FunctionType.ValueBased}}function M(){return $("sqrt")}function F(){return $("tan")}function R(){const D="tanh";return{body:` + float ${D}_(float a) { + a = clamp(a, -10., 10.); + a = exp(2.*a); + return (a - 1.) / (a + 1.); + } + vec4 ${D}_(vec4 v) { + v = clamp(v, -10., 10.); + v = exp(2.*v); + return (v - 1.) / (v + 1.); + } + `,name:D,type:d.FunctionType.ValueBased}}function $(D){return{body:` + float ${D}_(float a) { + return ${D}(a); + } + vec4 ${D}_(vec4 v) { + return ${D}(v); + } + `,name:D,type:d.FunctionType.ValueBased}}n.glslAbs=f,n.glslAcos=c,n.glslAsin=a,n.glslAtan=t,n.glslCeil=e,n.glslCos=r,n.glslElu=i,n.glslExp=h,n.glslFloor=g,n.glslClip=m,n.glslIdentity=b,n.glslLeakyRelu=y,n.glslLog=w,n.glslNeg=T,n.glslNot=S,n.glslSin=A,n.glslRelu=O,n.glslSigmoid=v,n.glslSqrt=M,n.glslTan=F,n.glslTanh=R;const N=(D,j,Q,X)=>{const Z=D.session.pack?p.TextureType.packed:p.TextureType.unpacked,ee={name:Q.name,inputTypes:[Z],inputNames:["A"],cacheHint:X};return 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Q=j.length>=3?j[1].numberData[0]:l.MIN_CLIP,X=j.length>=3?j[2].numberData[0]:l.MAX_CLIP;return(0,u.createAttributeWithCacheKey)({min:Q,max:X})};n.ceil=(D,j)=>[D.run(N(D,j[0],e()),j)],n.cos=(D,j)=>[D.run(N(D,j[0],r()),j)],n.elu=(D,j,Q)=>[D.run(N(D,j[0],i(Q.alpha),Q.cacheKey),j)],n.parseEluAttributes=D=>(0,u.createAttributeWithCacheKey)({alpha:D.attributes.getFloat("alpha",1)}),n.exp=(D,j)=>[D.run(N(D,j[0],h()),j)],n.floor=(D,j)=>[D.run(N(D,j[0],g()),j)],n.identity=(D,j)=>[D.run(N(D,j[0],b()),j)],n.leakyRelu=(D,j,Q)=>[D.run(N(D,j[0],y(Q.alpha),Q.cacheKey),j)],n.parseLeakyReluAttributes=D=>(0,u.createAttributeWithCacheKey)({alpha:D.attributes.getFloat("alpha",.01)}),n.log=(D,j)=>[D.run(N(D,j[0],w()),j)],n.neg=(D,j)=>[D.run(N(D,j[0],T()),j)],n.not=(D,j)=>[D.run(N(D,j[0],S()),j)],n.relu=(D,j)=>[D.run(N(D,j[0],O()),j)],n.sigmoid=(D,j)=>[D.run(N(D,j[0],v()),j)],n.sin=(D,j)=>[D.run(N(D,j[0],A()),j)],n.sqrt=(D,j)=>[D.run(N(D,j[0],M()),j)],n.tan=(D,j)=>[D.run(N(D,j[0],F()),j)],n.tanh=(D,j)=>[D.run(N(D,j[0],R()),j)]},5611:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createUnpackProgramInfoLoader=n.createUnpackProgramInfo=void 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c>10?f.inputs.length>2?(T=1,S=2,A=3):(S=1,A=2):c===9&&(S=1),(0,u.createAttributeWithCacheKey)({opset:c,isResize:a,mode:t,scales:e,extrapolationValue:r,coordinateTransformMode:i,useExtrapolation:g,needRoiInput:h,nearestMode:m,cubicCoefficientA:b,excludeOutside:y,useNearest2xOptimization:w,roiInputIdx:T,scalesInputIdx:S,sizesInputIdx:A})};const p=(f,c,a)=>{const t=(0,l.getGlsl)(f.session.backend.glContext.version),[e,r]=f.calculateTextureWidthAndHeight(c[0].dims,d.TextureType.unpacked),i=c[0].dims.map((A,O)=>Math.floor(A*a.scales[O])),[h,g]=f.calculateTextureWidthAndHeight(i,d.TextureType.unpacked),m=i.length,b=new Array(m),y=new Array(m);let w=` + int output_pitches[${m}]; + int input_pitches[${m}]; + `;for(let A=m-1;A>=0;A--)b[A]=A===m-1?1:b[A+1]*i[A+1],y[A]=A===m-1?1:y[A+1]*c[0].dims[A+1],w+=` + output_pitches[${A}] = ${b[A]}; + input_pitches[${A}] = ${y[A]}; + `;const T=` + float getInputFloat(int index) { + vec2 coords = offsetToCoords(index, ${e}, ${r}); + float value = getColorAsFloat(${t.texture2D}(X, coords)); + return value; + } + `,S=a.mode==="nearest"?` + ${T} + float process(int indices[${m}]) { + int input_index = 0; + int output_index = coordsToOffset(TexCoords, ${h}, ${g}); + + ${w} + + int d, m; + for (int dim = 0; dim < ${m}; ++dim) { + d = output_index / output_pitches[dim]; + m = output_index - d * output_pitches[dim]; + output_index = m; + + if (scales[dim] != 1 && d > 0) { + int d2 = d / scales[dim]; + m = d - d2 * scales[dim]; + d = d2; + } + input_index += input_pitches[dim] * d; + } + + return getInputFloat(input_index); + }`:m===4?` + ${T} + float process(int indices[4]) { + int input_index = 0; + int output_index = coordsToOffset(TexCoords, ${h}, ${g}); + + ${w} + + int m; + int index_of_dim0, index_of_dim1, index_of_dim2, index_of_dim3; + index_of_dim0 = output_index / output_pitches[0]; + m = output_index - index_of_dim0 * output_pitches[0]; + index_of_dim1 = m / output_pitches[1]; + m = m - index_of_dim1 * output_pitches[1]; + index_of_dim2 = m / output_pitches[2]; + m = m - index_of_dim2 * output_pitches[2]; + index_of_dim3 = m; + + int index_of_input_dim2, index_of_input_dim3, x_offset, y_offset; + index_of_input_dim2 = index_of_dim2 / scales[2]; + y_offset = index_of_dim2 - index_of_input_dim2 * scales[2]; + index_of_input_dim3 = index_of_dim3 / scales[3]; + x_offset = index_of_dim3 - index_of_input_dim3 * scales[3]; + + input_index = index_of_dim0 * input_pitches[0] + + index_of_dim1 * input_pitches[1] + + index_of_input_dim2 * input_pitches[2] + + index_of_input_dim3; + + float x00 = getInputFloat(input_index); + float x10, x01, x11; + + bool end_of_dim2 = false; + if (index_of_input_dim2 == (${c[0].dims[2]} - 1)) { + // It's the end in dimension 2 + x01 = x00; + end_of_dim2 = true; + } else { + x01 = getInputFloat(input_index + input_pitches[2]); + } + + if (index_of_input_dim3 == (input_pitches[2] - 1)) { + // It's the end in dimension 3 + x10 = x00; + x11 = x01; + } + else { + x10 = getInputFloat(input_index + 1); + x11 = end_of_dim2 ? x10 : getInputFloat(input_index + input_pitches[2] + 1); + } + + float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[2]); + float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[2]); + return y0 + float(x_offset) * (y1 - y0) / float(scales[3]); + }`:` + ${T} + float process(int indices[2]) { + int input_index = 0; + int output_index = coordsToOffset(TexCoords, ${h}, ${g}); + + ${w} + + int m; + int index_of_dim0, index_of_dim1; + index_of_dim0 = output_index / output_pitches[0]; + m = output_index - index_of_dim0 * output_pitches[0]; + index_of_dim1 = m; + + int index_of_input_dim0, index_of_input_dim1, x_offset, y_offset; + index_of_input_dim0 = index_of_dim0 / scales[0]; + y_offset = index_of_dim0 - index_of_input_dim0 * scales[0]; + index_of_input_dim1 = index_of_dim1 / scales[1]; + x_offset = index_of_dim1 - index_of_input_dim1 * scales[1]; + + input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1; + + float x00 = getInputFloat(input_index); + float x10, x01, x11; + + bool end_of_dim0 = false; + if (index_of_input_dim0 == (${c[0].dims[0]} - 1)) { + // It's the end in dimension 0 + x01 = x00; + end_of_dim0 = true; + } else { + x01 = getInputFloat(input_index + input_pitches[0]); + } + + if (index_of_input_dim1 == (input_pitches[0] - 1)) { + // It's the end in dimension 1 + x10 = x00; + x11 = x01; + } + else { + x10 = getInputFloat(input_index + 1); + x11 = end_of_dim0 ? x10 : getInputFloat(input_index + input_pitches[0] + 1); + } + + float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[0]); + float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[0]); + return y0 + float(x_offset) * (y1 - y0) / float(scales[1]); + }`;return Object.assign(Object.assign({},s),{output:{dims:i,type:c[0].type,textureType:d.TextureType.unpacked},shaderSource:S,variables:[{name:"scales",type:"int",arrayLength:a.scales.length,data:a.scales.map(A=>Math.ceil(A))}]})};n.validateInputs=(f,c)=>{if(!f||c.opset<9&&f.length!==1||c.opset>=9&&c.opset<11&&f.length!==2||c.opset>=11&&f.length<2)throw new Error("invalid inputs.");if(c.scales.length>0&&f[0].dims.length!==c.scales.length)throw new Error("Invalid input shape.");if(f[0].type==="string")throw new Error("Invalid input tensor types.")},n.scalesValidation=(f,c,a)=>{if(a){for(const t of f)if(t<=0)throw new Error("Scale value should be greater than 0.")}else for(const t of f)if(t<1)throw new Error("Scale value should be greater than or equal to 1.");if(!(c!=="linear"&&c!=="cubic"||f.length===2||f.length===4&&f[0]===1&&f[1]===1))throw new Error(`'Linear' mode and 'Cubic' mode only support 2-D inputs ('Bilinear', 'Bicubic') or 4-D inputs with the corresponding outermost 2 scale values 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this.profiler.event("node",h.node.name,async()=>h.op.impl(p,m,h.op.context));if(b.length!==h.node.outputs.length)throw new Error("the size of output does not match model definition.");b.forEach((w,T)=>{const S=h.node.outputs[T];if(this._values[S])throw new Error(`output [${S}] already has value: op:${h.node.name}`);this._values[S]=w});const y=new Set;b.forEach((w,T)=>{const S=h.node.outputs[T];for(const A of a[S].to){const O=t[A];let v=!0;for(const M of O.inputs)if(!this._values[M]){v=!1;break}v&&y.add(A)}}),c.push(...y)}const r=[];for(let i=0;i{Object.defineProperty(n,"__esModule",{value:!0}),n.Graph=void 0;const u=o(1446),l=o(7778),d=o(9395),s=o(9162),p=o(2517);var f=d.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=p.ProtoUtil.tensorValueTypeFromProto(r.type.tensorType))}get from(){return this._from}get to(){return this._to}}class a{constructor(r,i){r instanceof 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r=this.bb.__offset(this.bb_pos,14);return r?this.bb.__string(this.bb.__vector(this.bb_pos+r)+4*t,e):null}inputsLength(){let t=this.bb.__offset(this.bb_pos,14);return t?this.bb.__vector_len(this.bb_pos+t):0}outputs(t,e){let r=this.bb.__offset(this.bb_pos,16);return r?this.bb.__string(this.bb.__vector(this.bb_pos+r)+4*t,e):null}outputsLength(){let t=this.bb.__offset(this.bb_pos,16);return t?this.bb.__vector_len(this.bb_pos+t):0}sparseInitializers(t,e){let r=this.bb.__offset(this.bb_pos,18);return r?(e||new s.experimental.fbs.SparseTensor).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}sparseInitializersLength(){let t=this.bb.__offset(this.bb_pos,18);return t?this.bb.__vector_len(this.bb_pos+t):0}static startGraph(t){t.startObject(8)}static addInitializers(t,e){t.addFieldOffset(0,e,0)}static createInitializersVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startInitializersVector(t,e){t.startVector(4,e,4)}static addNodeArgs(t,e){t.addFieldOffset(1,e,0)}static createNodeArgsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodeArgsVector(t,e){t.startVector(4,e,4)}static addNodes(t,e){t.addFieldOffset(2,e,0)}static createNodesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodesVector(t,e){t.startVector(4,e,4)}static addMaxNodeIndex(t,e){t.addFieldInt32(3,e,0)}static addNodeEdges(t,e){t.addFieldOffset(4,e,0)}static createNodeEdgesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startNodeEdgesVector(t,e){t.startVector(4,e,4)}static addInputs(t,e){t.addFieldOffset(5,e,0)}static createInputsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startInputsVector(t,e){t.startVector(4,e,4)}static addOutputs(t,e){t.addFieldOffset(6,e,0)}static createOutputsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startOutputsVector(t,e){t.startVector(4,e,4)}static addSparseInitializers(t,e){t.addFieldOffset(7,e,0)}static createSparseInitializersVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startSparseInitializersVector(t,e){t.startVector(4,e,4)}static endGraph(t){return t.endObject()}static createGraph(t,e,r,i,h,g,m,b,y){return c.startGraph(t),c.addInitializers(t,e),c.addNodeArgs(t,r),c.addNodes(t,i),c.addMaxNodeIndex(t,h),c.addNodeEdges(t,g),c.addInputs(t,m),c.addOutputs(t,b),c.addSparseInitializers(t,y),c.endGraph(t)}}f.Graph=c})(p.fbs||(p.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(p){(function(f){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()+u.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 s.experimental.fbs.OperatorSetId).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}opsetImportLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}producerName(t){let e=this.bb.__offset(this.bb_pos,8);return e?this.bb.__string(this.bb_pos+e,t):null}producerVersion(t){let e=this.bb.__offset(this.bb_pos,10);return e?this.bb.__string(this.bb_pos+e,t):null}domain(t){let e=this.bb.__offset(this.bb_pos,12);return e?this.bb.__string(this.bb_pos+e,t):null}modelVersion(){let t=this.bb.__offset(this.bb_pos,14);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}docString(t){let e=this.bb.__offset(this.bb_pos,16);return e?this.bb.__string(this.bb_pos+e,t):null}graph(t){let e=this.bb.__offset(this.bb_pos,18);return e?(t||new s.experimental.fbs.Graph).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}graphDocString(t){let e=this.bb.__offset(this.bb_pos,20);return e?this.bb.__string(this.bb_pos+e,t):null}static startModel(t){t.startObject(9)}static addIrVersion(t,e){t.addFieldInt64(0,e,t.createLong(0,0))}static addOpsetImport(t,e){t.addFieldOffset(1,e,0)}static createOpsetImportVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startOpsetImportVector(t,e){t.startVector(4,e,4)}static addProducerName(t,e){t.addFieldOffset(2,e,0)}static addProducerVersion(t,e){t.addFieldOffset(3,e,0)}static addDomain(t,e){t.addFieldOffset(4,e,0)}static addModelVersion(t,e){t.addFieldInt64(5,e,t.createLong(0,0))}static addDocString(t,e){t.addFieldOffset(6,e,0)}static addGraph(t,e){t.addFieldOffset(7,e,0)}static addGraphDocString(t,e){t.addFieldOffset(8,e,0)}static endModel(t){return t.endObject()}static createModel(t,e,r,i,h,g,m,b,y,w){return c.startModel(t),c.addIrVersion(t,e),c.addOpsetImport(t,r),c.addProducerName(t,i),c.addProducerVersion(t,h),c.addDomain(t,g),c.addModelVersion(t,m),c.addDocString(t,b),c.addGraph(t,y),c.addGraphDocString(t,w),c.endModel(t)}}f.Model=c})(p.fbs||(p.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(p){(function(f){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()+u.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)}}f.KernelCreateInfos=c})(p.fbs||(p.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(p){(function(f){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()+u.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 s.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startSubGraphSessionState(t){t.startObject(2)}static addGraphId(t,e){t.addFieldOffset(0,e,0)}static addSessionState(t,e){t.addFieldOffset(1,e,0)}static endSubGraphSessionState(t){let e=t.endObject();return t.requiredField(e,4),e}static createSubGraphSessionState(t,e,r){return c.startSubGraphSessionState(t),c.addGraphId(t,e),c.addSessionState(t,r),c.endSubGraphSessionState(t)}}f.SubGraphSessionState=c})(p.fbs||(p.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(p){(function(f){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)}}f.SessionState=c})(p.fbs||(p.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(s){(function(p){(function(f){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()+u.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 s.experimental.fbs.Model).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}sessionState(t){let e=this.bb.__offset(this.bb_pos,8);return e?(t||new s.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startInferenceSession(t){t.startObject(3)}static addOrtVersion(t,e){t.addFieldOffset(0,e,0)}static addModel(t,e){t.addFieldOffset(1,e,0)}static addSessionState(t,e){t.addFieldOffset(2,e,0)}static endInferenceSession(t){return t.endObject()}static finishInferenceSessionBuffer(t,e){t.finish(e,"ORTM")}static finishSizePrefixedInferenceSessionBuffer(t,e){t.finish(e,"ORTM",!0)}static createInferenceSession(t,e,r,i){return c.startInferenceSession(t),c.addOrtVersion(t,e),c.addModel(t,r),c.addSessionState(t,i),c.endInferenceSession(t)}}f.InferenceSession=c})(p.fbs||(p.fbs={}))})(s.experimental||(s.experimental={}))}(n.onnxruntime||(n.onnxruntime={}))},7448:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.OnnxjsSessionHandler=void 0;const u=o(1670),l=o(9162);n.OnnxjsSessionHandler=class{constructor(d){this.session=d,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(d,s,p){const f=new Map;for(const t in d)if(Object.hasOwnProperty.call(d,t)){const e=d[t];f.set(t,new l.Tensor(e.dims,e.type,void 0,void 0,e.data))}const c=await this.session.run(f),a={};return c.forEach((t,e)=>{a[e]=new u.Tensor(t.type,t.data,t.dims)}),a}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(_,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Session=void 0;const u=o(7067),l=o(1296),d=o(7091),s=o(1036),p=o(6231),f=o(2644);n.Session=class{constructor(c={}){this._initialized=!1,this.backendHint=c.backendHint,this.profiler=p.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,a,t){await this.profiler.event("session","Session.loadModel",async()=>{const e=await(0,d.resolveBackend)(this.backendHint);if(this.sessionHandler=e.createSessionHandler(this.context),this._model=new f.Model,typeof c=="string"){const r=c.endsWith(".ort");if(typeof fetch>"u"){const i=await(0,l.promisify)(u.readFile)(c);this.initialize(i,r)}else{const i=await fetch(c),h=await i.arrayBuffer();this.initialize(new Uint8Array(h),r)}}else if(ArrayBuffer.isView(c))this.initialize(c);else{const r=new 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${c.length}`)}else{if(c.size!==a.length)throw new Error(`incorrect input map size: expected ${a.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");A&&(this.cache=new Array(S))}else{if(w!==void 0){const O=e(m);if(!(w instanceof O))throw new TypeError(`cache should be type ${O.name}`)}if(A){const O=new ArrayBuffer(S*function(v){switch(v){case"bool":case"int8":case"uint8":return 1;case"int16":case"uint16":return 2;case"int32":case"uint32":case"float32":return 4;case"float64":return 8;default:throw new Error(`cannot calculate sizeof() on type ${v}`)}}(m));this.cache=function(v,M){return new(e(M))(v)}(O,m)}}}static fromProto(g){if(!g)throw new Error("cannot construct Value from an empty tensor");const m=f.ProtoUtil.tensorDataTypeFromProto(g.dataType),b=f.ProtoUtil.tensorDimsFromProto(g.dims),y=new a(b,m);if(m==="string")g.stringData.forEach((w,T)=>{y.data[T]=(0,f.decodeUtf8String)(w)});else 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Object.keys(_).length===0}globalThis.ReadableStream||(globalThis.ReadableStream=sharp.ReadableStream);class FileResponse{constructor(n){le(this,"_CONTENT_TYPE_MAP",{txt:"text/plain",html:"text/html",css:"text/css",js:"text/javascript",json:"application/json",png:"image/png",jpg:"image/jpeg",jpeg:"image/jpeg",gif:"image/gif"});if(this.filePath=n,this.headers=new Headers,this.exists=sharp.existsSync(n),this.exists){this.status=200,this.statusText="OK";let o=sharp.statSync(n);this.headers.set("content-length",o.size.toString()),this.updateContentType();let u=this;this.body=new ReadableStream({start(l){u.arrayBuffer().then(d=>{l.enqueue(new Uint8Array(d)),l.close()})}})}else this.status=404,this.statusText="Not Found",this.body=null}updateContentType(){const n=this.filePath.toString().split(".").pop().toLowerCase();this.headers.set("content-type",this._CONTENT_TYPE_MAP[n]??"application/octet-stream")}clone(){let n=new FileResponse(this.filePath);return 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f=(u=process.env)==null?void 0:u.HF_ACCESS_TOKEN;f&&s.set("Authorization",`Bearer ${f}`)}return fetch(_,{headers:s})}else return fetch(_)}const ERROR_MAPPING={400:"Bad request error occurred while trying to load file",401:"Unauthorized access to file",403:"Forbidden access to file",404:"Could not locate file",408:"Request timeout error occurred while trying to load file",500:"Internal server error error occurred while trying to load file",502:"Bad gateway error occurred while trying to load file",503:"Service unavailable error occurred while trying to load file",504:"Gateway timeout error occurred while trying to load file"};function handleError(_,n,o){if(!o)return null;const u=ERROR_MAPPING[_]??`Error (${_}) occurred while trying to load file`;throw Error(`${u}: "${n}".`)}class FileCache{constructor(n){this.path=n}async match(n){let o=sharp.join(this.path,n),u=new FileResponse(o);if(u.exists)return u}async put(n,o){const u=Buffer.from(await o.arrayBuffer());let l=sharp.join(this.path,n);try{await sharp.promises.mkdir(sharp.dirname(l),{recursive:!0}),await sharp.promises.writeFile(l,u)}catch(d){console.warn("An error occurred while writing the file to cache:",d)}}}async function tryCache(_,...n){for(let o of n)try{let u=await _.match(o);if(u)return u}catch{continue}}async function getModelFile(_,n,o=!0,u={}){if(!env.allowLocalModels&&u.local_files_only)throw Error("Invalid configuration detected: local models are disabled (`env.allowLocalModels=false`) but you have requested to only use local models (`local_files_only=true`).");dispatchCallback(u.progress_callback,{status:"initiate",name:_,file:n});let l;if(!l&&env.useBrowserCache){if(typeof caches>"u")throw Error("Browser cache is not available in this environment.");try{l=await caches.open("transformers-cache")}catch(h){console.warn("An error occurred while opening the browser cache:",h)}}if(!l&&env.useFSCache&&(l=new FileCache(u.cache_dir??env.cacheDir)),!l&&env.useCustomCache)throw Error("`env.useCustomCache=true`, but `env.customCache` is not defined.");const d=u.revision??"main";let s=pathJoin(_,n),p=pathJoin(env.localModelPath,s),f=pathJoin(env.remoteHost,env.remotePathTemplate.replaceAll("{model}",_).replaceAll("{revision}",d),n),c=d==="main"?s:pathJoin(_,d,n),a,t=l instanceof FileCache?c:f,e=!1,r;if(l&&(r=await tryCache(l,p,t)),r===void 0){if(env.allowLocalModels)if(isValidHttpUrl(s)){if(u.local_files_only)throw new Error(`\`local_files_only=true\`, but attempted to load a remote file from: ${s}.`)}else try{r=await getFile(p),a=p}catch(g){console.warn(`Unable to load from local path "${p}": "${g}"`)}if(r===void 0||r.status===404){if(u.local_files_only||!env.allowRemoteModels){if(o)throw Error(`\`local_files_only=true\` or \`env.allowRemoteModels=false\` and file was not found locally at "${p}".`);return null}if(r=await getFile(f),r.status!==200)return handleError(r.status,f,o);a=t}e=l&&typeof Response<"u"&&r instanceof Response&&r.status===200}dispatchCallback(u.progress_callback,{status:"download",name:_,file:n});const i=await readResponse(r,h=>{dispatchCallback(u.progress_callback,{status:"progress",...h,name:_,file:n})});return e&&a&&await l.match(a)===void 0&&await l.put(a,new Response(i,{headers:r.headers})).catch(h=>{console.warn(`Unable to add response to browser cache: ${h}.`)}),dispatchCallback(u.progress_callback,{status:"done",name:_,file:n}),i}async function getModelJSON(_,n,o=!0,u={}){let l=await getModelFile(_,n,o,u);if(l===null)return{};let s=new TextDecoder("utf-8").decode(l);return JSON.parse(s)}async function readResponse(_,n){const o=_.headers.get("Content-Length");o===null&&console.warn("Unable to determine content-length from response headers. 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o=Math.pow(10,n);return Math.round(_*o)/o}const ONNXTensor$1=ONNX.Tensor;class Tensor extends ONNXTensor$1{constructor(...n){return n[0]instanceof ONNX.Tensor?super(n[0].type,n[0].data,n[0].dims):super(...n),new Proxy(this,{get:(o,u)=>{if(typeof u=="string"){let l=Number(u);if(Number.isInteger(l))return o._getitem(l)}return o[u]},set:(o,u,l)=>o[u]=l})}*[Symbol.iterator](){const[n,...o]=this.dims;if(o.length>0){const u=o.reduce((l,d)=>l*d);for(let l=0;l0){const l=u.reduce((d,s)=>d*s);return this._subarray(n,l,u)}else return new Tensor(this.type,[this.data[n]],u)}indexOf(n){for(let o=0;oc[1])throw new Error(`Invalid slice: ${c}`);let a=[Math.max(c[0],0),Math.min(c[1],this.dims[f])];u.push(a),o.push(a[1]-a[0])}else throw new Error(`Invalid slice: ${c}`)}let l=u.map(([f,c])=>c-f),d=l.reduce((f,c)=>f*c),s=new this.data.constructor(d);const p=this.stride();for(let f=0;f=0;--a){const e=l[a];c+=(t%e+u[a][0])*p[a],t=Math.floor(t/e)}s[f]=this.data[c]}return new Tensor(this.type,s,o)}transpose(...n){return transpose(this,n)}sum(n=null,o=!1){return this.norm(1,n,o)}norm(n="fro",o=null,u=!1){if(n==="fro")n=2;else if(typeof n=="string")throw Error(`Unsupported norm: ${n}`);if(o===null){let s=this.data.reduce((p,f)=>p+f**n,0)**(1/n);return new Tensor(this.type,[s],[])}o=safeIndex(o,this.dims.length);const l=this.dims.slice();l[o]=1;const d=new this.data.constructor(this.data.length/this.dims[o]);for(let s=0;s=0;--f){const t=this.dims[f];if(f!==o){const e=c%t;p+=e*a,a*=l[f]}c=Math.floor(c/t)}d[p]+=this.data[s]**n}if(n!==1)for(let s=0;s=0;--s){const c=this.dims[s];if(s!==o){const a=p%c;d+=a*f,f*=this.dims[s]}p=Math.floor(p/c)}this.data[l]/=u.data[d]}return this}normalize(n=2,o=1){return this.clone().normalize_(n,o)}stride(){return dimsToStride(this.dims)}squeeze(n=null){return new Tensor(this.type,this.data,calc_squeeze_dims(this.dims,n))}squeeze_(n=null){return this.dims=calc_squeeze_dims(this.dims,n),this}unsqueeze(n=null){return new Tensor(this.type,this.data,calc_unsqueeze_dims(this.dims,n))}unsqueeze_(n=null){return this.dims=calc_unsqueeze_dims(this.dims,n),this}flatten_(n=0,o=-1){o=(o+this.dims.length)%this.dims.length;let u=this.dims.slice(0,n),l=this.dims.slice(n,o+1),d=this.dims.slice(o+1);return this.dims=[...u,l.reduce((s,p)=>s*p,1),...d],this}flatten(n=0,o=-1){return this.clone().flatten_(n,o)}view(...n){let o=-1;for(let u=0;us!==o?l*d:l,1);n[o]=this.data.length/u}return new Tensor(this.type,this.data,n)}neg_(){for(let n=0;nd*s);if(o!==u)throw Error(`cannot reshape array of size ${o} into shape (${n})`);let l=_;for(let d=n.length-1;d>=0;d--)l=l.reduce((s,p)=>{let f=s[s.length-1];return f.lengtho!==1):typeof n=="number"?_[n]===1&&_.splice(n,1):Array.isArray(n)&&(_=_.filter((o,u)=>o!==1||!n.includes(u))),_}function calc_unsqueeze_dims(_,n){return n=safeIndex(n,_.length+1),_=_.slice(),_.splice(n,0,1),_}function safeIndex(_,n,o=null){if(_<-n||_>=n)throw new Error(`IndexError: index ${_} is out of bounds for dimension${o===null?"":" "+o} with size ${n}`);return _<0&&(_=(_%n+n)%n),_}function cat(_,n=0){n=safeIndex(n,_[0].dims.length);const o=_[0].dims.slice();o[n]=_.reduce((s,p)=>s+p.dims[n],0);const u=o.reduce((s,p)=>s*p,1),l=new _[0].data.constructor(u),d=_[0].type;if(n===0){let s=0;for(let p of _)l.set(p.data,s),s+=p.data.length}else{let s=0;for(let p=0;p<_.length;++p){let f=_[p];for(let c=0;c=0;--t){const i=f.dims[t];let h=e%i;t===n&&(h+=s),a+=h*r,r*=o[t],e=Math.floor(e/i)}l[a]=f.data[c]}s+=f.dims[n]}}return new Tensor(d,l,o)}function stack(_,n=0){return cat(_.map(o=>o.unsqueeze(n)),n)}function std_mean(_,n=null,o=1,u=!1){if(n===null){const c=_.data.reduce((r,i)=>r+i,0)/_.data.length,a=Math.sqrt(_.data.reduce((r,i)=>r+(i-c)**2,0)/(_.data.length-o)),t=new Tensor(_.type,[c],[]);return[new Tensor(_.type,[a],[]),t]}n=safeIndex(n,_.dims.length);const l=mean(_,n,u),d=_.dims.slice();d[n]=1;const s=new _.data.constructor(_.data.length/_.dims[n]);for(let f=0;f<_.data.length;++f){let c=0;for(let a=_.dims.length-1,t=f,e=1;a>=0;--a){const r=_.dims[a];if(a!==n){const i=t%r;c+=i*e,e*=d[a]}t=Math.floor(t/r)}s[c]+=(_.data[f]-l.data[c])**2}for(let f=0;fs+p,0);return new Tensor(_.type,[d/_.data.length],[])}n=safeIndex(n,_.dims.length);const u=_.dims.slice();u[n]=1;const l=new _.data.constructor(_.data.length/_.dims[n]);for(let d=0;d<_.data.length;++d){let s=0;for(let p=_.dims.length-1,f=d,c=1;p>=0;--p){const a=_.dims[p];if(p!==n){const t=f%a;s+=t*c,c*=u[p]}f=Math.floor(f/a)}l[s]+=_.data[d]}if(_.dims[n]!==1)for(let d=0;d0||p>0;)switch(f.push(s-1),c.push(p-1),d[s][p].item()){case 0:--s,--p;break;case 1:--s;break;case 2:--p;break;default:throw new Error(`Internal error in dynamic time warping. Unexpected trace[${s}, ${p}]. Please file a bug report.`)}return f.reverse(),c.reverse(),[f,c]}function dimsToStride(_){const n=new Array(_.length);for(let o=_.length-1,u=1;o>=0;--o)n[o]=u,u*=_[o];return n}function ones(_){const n=_.reduce((o,u)=>o*u,1);return new Tensor("int64",new BigInt64Array(n).fill(1n),_)}function ones_like(_){return ones(_.dims)}class PriorityQueue{constructor(n=(o,u)=>o>u){this._heap=[],this._comparator=n}get size(){return this._heap.length}isEmpty(){return this.size===0}peek(){return this._heap[0]}push(...n){return this.extend(n)}extend(n){for(const o of n)this._heap.push(o),this._siftUp();return this.size}pop(){const n=this.peek(),o=this.size-1;return o>0&&this._swap(0,o),this._heap.pop(),this._siftDown(),n}replace(n){const o=this.peek();return this._heap[0]=n,this._siftDown(),o}_parent(n){return(n+1>>>1)-1}_left(n){return(n<<1)+1}_right(n){return n+1<<1}_greater(n,o){return this._comparator(this._heap[n],this._heap[o])}_swap(n,o){const u=this._heap[n];this._heap[n]=this._heap[o],this._heap[o]=u}_siftUp(){let n=this.size-1;for(;n>0&&this._greater(n,this._parent(n));)this._swap(n,this._parent(n)),n=this._parent(n)}_siftDown(){let n=0;for(;this._left(n)[]),this.endNodes=Array.from({length:this.len+1},()=>[]);const l=new TokenLatticeNode(this.bosTokenId,0,0,0,0),d=new TokenLatticeNode(this.eosTokenId,1,this.len,0,0);this.nodes.push(l.clone()),this.nodes.push(d.clone()),this.beginNodes[this.len].push(d),this.endNodes[0].push(l)}insert(n,o,u,l){const d=this.nodes.length,s=new TokenLatticeNode(l,d,n,o,u);this.beginNodes[n].push(s),this.endNodes[n+o].push(s),this.nodes.push(s)}viterbi(){const n=this.len;let o=0;for(;o<=n;){if(this.beginNodes[o].length==0)return[];for(let p of this.beginNodes[o]){p.prev=null;let f=0,c=null;for(let a of this.endNodes[o]){const t=a.backtraceScore+p.score;(c===null||t>f)&&(c=a.clone(),f=t)}if(c!==null)p.prev=c,p.backtraceScore=f;else return[]}++o}const u=[],d=this.beginNodes[n][0].prev;if(d===null)return[];let s=d.clone();for(;s.prev!==null;)u.push(s.clone()),s=s.clone().prev.clone();return u.reverse(),u}piece(n){return this.sentence.slice(n.pos,n.pos+n.length)}tokens(){return this.viterbi().map(o=>this.piece(o))}tokenIds(){return this.viterbi().map(o=>o.tokenId)}}class TokenLatticeNode{constructor(n,o,u,l,d){this.tokenId=n,this.nodeId=o,this.pos=u,this.length=l,this.score=d,this.prev=null,this.backtraceScore=0}clone(){const n=new TokenLatticeNode(this.tokenId,this.nodeId,this.pos,this.length,this.score);return n.prev=this.prev,n.backtraceScore=this.backtraceScore,n}}async function loadTokenizer(_,n){return await Promise.all([getModelJSON(_,"tokenizer.json",!0,n),getModelJSON(_,"tokenizer_config.json",!0,n)])}function createPattern(_,n=!0){return _.Regex!==void 0?new RegExp(n?_.Regex:`(${_.Regex})`,"gu"):_.String!==void 0?_.String:(console.warn("Unknown pattern type:",_),null)}function objectToMap(_){return new Map(Object.entries(_))}function clean_up_tokenization(_){return _.replace(/ \./g,".").replace(/ \?/g,"?").replace(/ \!/g,"!").replace(/ ,/g,",").replace(/ \' /g,"'").replace(/ n\'t/g,"n't").replace(/ \'m/g,"'m").replace(/ \'s/g,"'s").replace(/ \'ve/g,"'ve").replace(/ \'re/g,"'re")}function remove_accents(_){return _.replace(/[\u0300-\u036f]/g,"")}function lowercase_and_remove_accent(_){return remove_accents(_.toLowerCase())}function fuse(_,n){let o=[],u=0;for(;u<_.length;){if(o.push(_[u]),_[u]!==n){++u;continue}for(;u<_.length&&_[u]===n;)++u}return o}function whitespace_split(_){return _.match(/\S+/g)||[]}const PUNCTUATION_REGEX="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E";class TokenizerModel extends Callable{constructor(n){super(),this.config=n,this.vocab=[],this.tokens_to_ids=new Map,this.unk_token_id=void 0,this.unk_token=void 0,this.end_of_word_suffix=void 0,this.fuse_unk=this.config.fuse_unk??!1}static fromConfig(n,...o){switch(n.type){case"WordPiece":return new WordPieceTokenizer(n);case"Unigram":return new Unigram(n,...o);case"BPE":return new BPE(n);default:if(n.vocab)return new LegacyTokenizerModel(n,...o);throw new Error(`Unknown TokenizerModel type: ${n.type}`)}}_call(n){return this.encode(n)}encode(n){throw Error("encode should be implemented in subclass.")}convert_tokens_to_ids(n){let o=n.map(u=>this.tokens_to_ids.get(u)??this.unk_token_id);return this.fuse_unk&&(o=fuse(o,this.unk_token_id)),o}convert_ids_to_tokens(n){return n.map(o=>this.vocab[o]??this.unk_token)}}class WordPieceTokenizer extends TokenizerModel{constructor(n){super(n),this.tokens_to_ids=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,u]of this.tokens_to_ids)this.vocab[u]=o}encode(n){let o=[];for(let u of n){let l=[...u],d=!1,s=0,p=[];for(;s0&&(a=this.config.continuing_subword_prefix+a),this.tokens_to_ids.has(a)){c=a;break}--f}if(c===null){d=!0;break}p.push(c),s=f}d?o.push(this.unk_token):o.push(...p)}return o}}class Unigram extends TokenizerModel{constructor(n,o){super(n);const u=n.vocab.length;this.vocab=new Array(u),this.scores=new Array(u);for(let l=0;l[l,d])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=o.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=min(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new CharTrie,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(n){const o=n.sentence,u=o.length;let l=0;for(;l{const _=[...Array.from({length:"~".charCodeAt(0)-"!".charCodeAt(0)+1},(l,d)=>d+"!".charCodeAt(0)),...Array.from({length:"¬".charCodeAt(0)-"¡".charCodeAt(0)+1},(l,d)=>d+"¡".charCodeAt(0)),...Array.from({length:"ÿ".charCodeAt(0)-"®".charCodeAt(0)+1},(l,d)=>d+"®".charCodeAt(0))];let n=_.slice(),o=0;for(let l=0;l<256;++l)_.includes(l)||(_.push(l),n.push(256+o),o+=1);let u=n.map(l=>String.fromCharCode(l));return Object.fromEntries(_.map((l,d)=>[l,u[d]]))})(),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,u]of this.tokens_to_ids)this.vocab[u]=o;this.bpe_ranks=new Map(n.merges.map((o,u)=>[o,u])),this.merges=n.merges.map(o=>o.split(this.BPE_SPLIT_TOKEN)),this.end_of_word_suffix=n.end_of_word_suffix,this.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 u=Array.from(n);this.end_of_word_suffix&&(u[u.length-1]+=this.end_of_word_suffix);let l=[];if(u.length>1){const d=new PriorityQueue((f,c)=>f.score`<0x${s.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[u,l]of this.tokens_to_ids)this.vocab[l]=u}encode(n){return n}}class Normalizer extends Callable{constructor(n){super(),this.config=n}static fromConfig(n){if(n===null)return null;switch(n.type){case"BertNormalizer":return new BertNormalizer(n);case"Precompiled":return new Precompiled(n);case"Sequence":return new NormalizerSequence(n);case"Replace":return new Replace(n);case"NFC":return new NFC(n);case"NFKD":return new NFKD(n);case"Strip":return new StripNormalizer(n);case"StripAccents":return new StripAccents(n);case"Lowercase":return new Lowercase(n);case"Prepend":return new Prepend(n);default:throw new Error(`Unknown Normalizer type: ${n.type}`)}}normalize(n){throw Error("normalize should be implemented in subclass.")}_call(n){return this.normalize(n)}}class Replace extends Normalizer{normalize(n){let o=createPattern(this.config.pattern);return o===null||(n=n.replaceAll(o,this.config.content)),n}}class NFC extends Normalizer{normalize(n){return n=n.normalize("NFC"),n}}class NFKD extends Normalizer{normalize(n){return n=n.normalize("NFKD"),n}}class StripNormalizer extends Normalizer{normalize(n){return this.config.strip_left&&this.config.strip_right?n=n.trim():(this.config.strip_left&&(n=n.trimStart()),this.config.strip_right&&(n=n.trimEnd())),n}}class StripAccents extends Normalizer{normalize(n){return n=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,u)=>u.normalize(o),n)}}class BertNormalizer extends Normalizer{_tokenize_chinese_chars(n){let o=[];for(let u=0;u=19968&&n<=40959||n>=13312&&n<=19903||n>=131072&&n<=173791||n>=173824&&n<=177983||n>=177984&&n<=178207||n>=178208&&n<=183983||n>=63744&&n<=64255||n>=194560&&n<=195103}stripAccents(n){return n.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}normalize(n){return this.config.handle_chinese_chars&&(n=this._tokenize_chinese_chars(n)),this.config.lowercase?(n=n.toLowerCase(),this.config.strip_accents!==!1&&(n=this.stripAccents(n))):this.config.strip_accents&&(n=this.stripAccents(n)),n}}class PreTokenizer extends Callable{static fromConfig(n){if(n===null)return null;switch(n.type){case"BertPreTokenizer":return new BertPreTokenizer(n);case"Sequence":return new PreTokenizerSequence(n);case"WhitespaceSplit":return new WhitespaceSplit(n);case"Metaspace":return new MetaspacePreTokenizer(n);case"ByteLevel":return new ByteLevelPreTokenizer(n);case"Split":return new SplitPreTokenizer(n);case"Punctuation":return new PunctuationPreTokenizer(n);case"Digits":return new DigitsPreTokenizer(n);case"Replace":return new ReplacePreTokenizer(n);default:throw new Error(`Unknown PreTokenizer type: ${n.type}`)}}pre_tokenize_text(n){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(n){let o=[];return Array.isArray(n)?o=n.map(u=>this.pre_tokenize_text(u)):o=this.pre_tokenize_text(n),o.flat()}_call(n){return this.pre_tokenize(n)}}class BertPreTokenizer extends PreTokenizer{constructor(n){super(),this.pattern=new RegExp(`[^\\s${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]`,"gu")}pre_tokenize_text(n){return n.trim().match(this.pattern)||[]}}class ByteLevelPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=/'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+/gu,this.byte_encoder=BYTES_TO_UNICODE,this.text_encoder=new TextEncoder}pre_tokenize_text(n){return this.add_prefix_space&&!n.startsWith(" ")&&(n=" "+n),(this.use_regex?n.match(this.pattern)||[]:[n]).map(u=>Array.from(this.text_encoder.encode(u),l=>this.byte_encoder[l]).join(""))}}class SplitPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=createPattern(this.config.pattern,this.config.invert)}pre_tokenize_text(n){return this.pattern===null?[]:this.config.invert?n.match(this.pattern)||[]:n.split(this.pattern).filter(o=>o)}}class PunctuationPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=new RegExp(`[^${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]+`,"gu")}pre_tokenize_text(n){return n.match(this.pattern)||[]}}class DigitsPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n;const o=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(o,"gu")}pre_tokenize_text(n){return n.match(this.pattern)||[]}}class PostProcessor extends Callable{constructor(n){super(),this.config=n}static fromConfig(n){if(n===null)return null;switch(n.type){case"TemplateProcessing":return new TemplateProcessing(n);case"ByteLevel":return new ByteLevelPostProcessor(n);case"RobertaProcessing":return new RobertaProcessing(n);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){return n=mergeArrays([this.cls],n,[this.sep]),o!==null&&(n=mergeArrays(n,[this.sep],o,[this.sep])),n}}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){let u=o===null?this.single:this.pair,l=[];for(let d of u)"SpecialToken"in d?l.push(d.SpecialToken.id):"Sequence"in d&&(d.Sequence.id==="A"?l=mergeArrays(l,n):d.Sequence.id==="B"&&(l=mergeArrays(l,o)));return l}}class ByteLevelPostProcessor extends PostProcessor{post_process(n){return n}}class Decoder extends Callable{constructor(n){super(),this.config=n,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=n.trim_offsets}static fromConfig(n){switch(n.type){case"WordPiece":return new WordPieceDecoder(n);case"Metaspace":return new MetaspaceDecoder(n);case"ByteLevel":return new ByteLevelDecoder(n);case"Replace":return new ReplaceDecoder(n);case"ByteFallback":return new ByteFallback(n);case"Fuse":return new FuseDecoder(n);case"Strip":return new StripDecoder(n);case"Sequence":return new DecoderSequence(n);case"CTC":return new CTCDecoder(n);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){let o=createPattern(this.config.pattern);return o===null?n:n.map(u=>u.replaceAll(o,this.config.content))}}class ByteFallback extends Decoder{constructor(n){super(n),this.text_decoder=new TextDecoder}decode_chain(n){let o=[],u=[];for(let l of n){let d=null;if(l.length===6&&l.startsWith("<0x")&&l.endsWith(">")){let s=parseInt(l.slice(3,5),16);isNaN(s)||(d=s)}if(d!==null)u.push(d);else{if(u.length>0){let s=this.text_decoder.decode(Uint8Array.from(u));o.push(s),u=[]}o.push(l)}}if(u.length>0){let l=this.text_decoder.decode(Uint8Array.from(u));o.push(l),u=[]}return o}}class FuseDecoder extends Decoder{decode_chain(n){return[n.join("")]}}class StripDecoder extends Decoder{constructor(n){super(n),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(n){return n.map(o=>{let u=0;for(let d=0;d(u!==0&&(o.startsWith(this.config.prefix)?o=o.replace(this.config.prefix,""):o=" "+o),this.cleanup&&(o=clean_up_tokenization(o)),o))}}class ByteLevelDecoder extends Decoder{constructor(n){super(n),this.byte_decoder=UNICODE_TO_BYTES,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(n){let o=n.join(""),u=new Uint8Array([...o].map(d=>this.byte_decoder[d]));return this.text_decoder.decode(u)}decode_chain(n){let o=[],u=[];for(let l of n)this.added_tokens.includes(l)?(u.length>0&&(o.push(this.convert_tokens_to_string(u)),u=[]),o.push(l)):u.push(l);return u.length>0&&o.push(this.convert_tokens_to_string(u)),o}}class CTCDecoder extends Decoder{constructor(n){super(n),this.pad_token=this.config.pad_token,this.word_delimiter_token=this.config.word_delimiter_token,this.cleanup=this.config.cleanup}convert_tokens_to_string(n){if(n.length===0)return"";let o=[n[0]];for(let d=1;dd!==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,u)=>u.decode_chain(o),n)}}class BPEDecoder extends Decoder{constructor(n){super(n),this.suffix=this.config.suffix}decode_chain(n){return n.map((o,u)=>o.replaceAll(this.suffix,u===n.length-1?"":" "))}}class MetaspacePreTokenizer extends PreTokenizer{constructor(n){super(),this.addPrefixSpace=n.add_prefix_space,this.replacement=n.replacement,this.strRep=n.str_rep||this.replacement}pre_tokenize(n){typeof n=="string"&&(n=n.trimStart().split(/\s+/));const o=[];for(let u of n){let l=u.replaceAll(" ",this.strRep);this.addPrefixSpace&&!l.startsWith(this.replacement)&&(l=this.strRep+l),o.push(l)}return o}}class MetaspaceDecoder extends Decoder{constructor(n){super(n),this.addPrefixSpace=n.add_prefix_space,this.replacement=n.replacement}decode_chain(n){let o=[];for(let u=0;uu.normalize("NFKC")).join("～"):n=n.normalize("NFKC"),n}}class PreTokenizerSequence extends PreTokenizer{constructor(n){super(),this.tokenizers=n.pretokenizers.map(o=>PreTokenizer.fromConfig(o))}pre_tokenize_text(n){return typeof n=="string"&&(n=[n]),this.tokenizers.reduce((o,u)=>u.pre_tokenize(o),n)}}class WhitespaceSplit extends PreTokenizer{constructor(n){super()}pre_tokenize_text(n){return whitespace_split(n)}}class ReplacePreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=createPattern(this.config.pattern),this.content=this.config.content}pre_tokenize_text(n){return this.pattern===null?[n]:[n.replaceAll(this.pattern,this.config.content)]}}class PreTrainedTokenizer extends Callable{constructor(n,o){super(),this.normalizer=Normalizer.fromConfig(n.normalizer),this.pre_tokenizer=PreTokenizer.fromConfig(n.pre_tokenizer),this.model=TokenizerModel.fromConfig(n.model,o),this.post_processor=PostProcessor.fromConfig(n.post_processor),this.decoder=Decoder.fromConfig(n.decoder),this.decoder.end_of_word_suffix=this.model.end_of_word_suffix,this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(let u of n.added_tokens){let l=u.id,d=u.content;this.added_tokens.push(d),this.model.tokens_to_ids.set(d,l),this.model.vocab[l]=d,u.special&&(this.special_tokens.push(d),this.all_special_ids.push(l))}this.special_tokens.push(...o.additional_special_tokens??[]),this.special_tokens=[...new Set(this.special_tokens)],this.decoder.added_tokens=this.added_tokens,this.added_tokens_regex=this.added_tokens.length>0?new RegExp("("+this.added_tokens.map(escapeRegExp).join("|")+")"):null,this.mask_token=this.getToken(o,"mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken(o,"pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken(o,"sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.model_max_length=o.model_max_length,this.remove_space=o.remove_space,this.clean_up_tokenization_spaces=o.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=o.do_lowercase_and_remove_accent??!1,this.padding_side="right"}getToken(n,...o){for(let u of o){let l=n[u];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(n,{progress_callback:o=null,config:u=null,cache_dir:l=null,local_files_only:d=!1,revision:s="main"}={}){let p=await loadTokenizer(n,{progress_callback:o,config:u,cache_dir:l,local_files_only:d,revision:s});return new this(...p)}prepare_model_inputs(n){return n}_call(n,{text_pair:o=null,add_special_tokens:u=!0,padding:l=!1,truncation:d=null,max_length:s=null,return_tensor:p=!0}={}){let f;if(Array.isArray(n)){if(n.length===0)throw Error("text array must be non-empty");if(o!==null){if(Array.isArray(o)){if(n.length!==o.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");f=n.map((e,r)=>this.encode(e,o[r],{add_special_tokens:u}))}else f=n.map(e=>this.encode(e,null,{add_special_tokens:u}))}else{if(n===null)throw Error("text may not be null");if(Array.isArray(o))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");f=[this.encode(n,o,{add_special_tokens:u})]}let c=max(f.map(e=>e.length))[0];s===null&&(s=c),s=Math.min(s,this.model_max_length);let a=[];if(l||d)for(let e=0;es)d&&(f[e]=f[e].slice(0,s)),a.push(new Array(f[e].length).fill(1));else if(l){let r=s-f[e].length;this.padding_side==="right"?(a.push(new Array(f[e].length).fill(1).concat(new Array(r).fill(0))),f[e].push(...new Array(r).fill(this.pad_token_id))):(a.push(new Array(r).fill(0).concat(new Array(f[e].length).fill(1))),f[e].unshift(...new Array(r).fill(this.pad_token_id)))}else a.push(new Array(f[e].length).fill(1));else a=f.map(e=>new Array(e.length).fill(1));if(p){if(!(l&&d)&&f.some(r=>r.length!==f[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");let e=[f.length,f[0].length];f=new Tensor("int64",BigInt64Array.from(f.flat().map(BigInt)),e),a=new Tensor("int64",BigInt64Array.from(a.flat().map(BigInt)),e)}else Array.isArray(n)||(f=f[0],a=a[0]);let t={input_ids:f,attention_mask:a};return t=this.prepare_model_inputs(t),t}_encode_text(n){return n===null?null:(this.added_tokens_regex?n.split(this.added_tokens_regex).filter(l=>l):[n]).map(l=>{if(this.added_tokens.includes(l))return l;{this.remove_space===!0&&(l=l.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(l=lowercase_and_remove_accent(l)),this.normalizer!==null&&(l=this.normalizer(l));let d=this.pre_tokenizer!==null?this.pre_tokenizer(l):[l];return this.model(d)}}).flat()}encode(n,o=null,{add_special_tokens:u=!0}={}){let l=this._encode_text(n),d=this._encode_text(o),s=this.post_processor!==null&&u?this.post_processor(l,d):mergeArrays(l??[],d??[]);return this.model.convert_tokens_to_ids(s)}batch_decode(n,o={}){return n.map(u=>this.decode(u,o))}decode(n,o={}){if(!Array.isArray(n)||n.length===0||!isIntegralNumber(n[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(n,o)}decode_single(n,{skip_special_tokens:o=!1,clean_up_tokenization_spaces:u=null}){let l=this.model.convert_ids_to_tokens(n);o&&(l=l.filter(s=>!this.special_tokens.includes(s)));let d=this.decoder(l);return this.decoder.end_of_word_suffix&&(d=d.replaceAll(this.decoder.end_of_word_suffix," "),o&&(d=d.trim())),(u??this.clean_up_tokenization_spaces)&&(d=clean_up_tokenization(d)),d}}function add_token_types(_){if(_.input_ids instanceof Tensor)_.token_type_ids=new Tensor("int64",new BigInt64Array(_.input_ids.data.length),_.input_ids.dims);else if(Array.isArray(_.input_ids))Array.isArray(_.input_ids[0])?_.token_type_ids=_.input_ids.map(n=>new Array(n.length).fill(0)):_.token_type_ids=new Array(_.input_ids.length).fill(0);else throw new Error("Input ids must be a Tensor or an Array");return _}class BertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class AlbertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class MobileBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class SqueezeBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class DebertaTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class DebertaV2Tokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class HerbertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class DistilBertTokenizer extends PreTrainedTokenizer{}class CamembertTokenizer extends PreTrainedTokenizer{}class XLMTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}prepare_model_inputs(n){return add_token_types(n)}}class T5Tokenizer extends PreTrainedTokenizer{}class GPT2Tokenizer extends PreTrainedTokenizer{}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(u=>this.languageRegex.test(u)),this.lang_to_token=u=>u}_build_translation_inputs(n,o,u){return _build_translation_inputs(this,n,o,u)}}class MBart50Tokenizer extends MBartTokenizer{}class RobertaTokenizer extends PreTrainedTokenizer{}class BloomTokenizer extends PreTrainedTokenizer{constructor(n,o){var d,s;const u=".,!?…。，、।۔،",l=(s=(d=n.pre_tokenizer)==null?void 0:d.pretokenizers[0])==null?void 0:s.pattern;l&&l.Regex===` ?[^(\\s|[${u}])]+`&&(l.Regex=` ?[^\\s${u}]+`),super(n,o)}}class LlamaTokenizer extends PreTrainedTokenizer{}class CodeLlamaTokenizer extends PreTrainedTokenizer{}class XLMRobertaTokenizer extends PreTrainedTokenizer{}class MPNetTokenizer extends PreTrainedTokenizer{}class FalconTokenizer extends PreTrainedTokenizer{}class GPTNeoXTokenizer extends PreTrainedTokenizer{}function _build_translation_inputs(_,n,o,u){if(!("language_codes"in _)||!Array.isArray(_.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in _)||!(_.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in _)||typeof _.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const l=u.src_lang,d=u.tgt_lang;if(!_.language_codes.includes(d))throw new Error(`Target language code "${d}" is not valid. Must be one of: {${_.language_codes.join(", ")}}`);if(l!==void 0){if(!_.language_codes.includes(l))throw new Error(`Source language code "${l}" is not valid. Must be one of: {${_.language_codes.join(", ")}}`);for(let s of _.post_processor.config.single)if("SpecialToken"in s&&_.languageRegex.test(s.SpecialToken.id)){s.SpecialToken.id=_.lang_to_token(l);break}}return u.forced_bos_token_id=_.model.convert_tokens_to_ids([_.lang_to_token(d)])[0],_._call(n,o)}class NllbTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(u=>this.languageRegex.test(u)),this.lang_to_token=u=>u}_build_translation_inputs(n,o,u){return _build_translation_inputs(this,n,o,u)}}class M2M100Tokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(u=>this.languageRegex.test(u)).map(u=>u.slice(2,-2)),this.lang_to_token=u=>`__${u}__`}_build_translation_inputs(n,o,u){return _build_translation_inputs(this,n,o,u)}}const WHISPER_LANGUAGES=[["en","english"],["zh","chinese"],["de","german"],["es","spanish"],["ru","russian"],["ko","korean"],["fr","french"],["ja","japanese"],["pt","portuguese"],["tr","turkish"],["pl","polish"],["ca","catalan"],["nl","dutch"],["ar","arabic"],["sv","swedish"],["it","italian"],["id","indonesian"],["hi","hindi"],["fi","finnish"],["vi","vietnamese"],["he","hebrew"],["uk","ukrainian"],["el","greek"],["ms","malay"],["cs","czech"],["ro","romanian"],["da","danish"],["hu","hungarian"],["ta","tamil"],["no","norwegian"],["th","thai"],["ur","urdu"],["hr","croatian"],["bg","bulgarian"],["lt","lithuanian"],["la","latin"],["mi","maori"],["ml","malayalam"],["cy","welsh"],["sk","slovak"],["te","telugu"],["fa","persian"],["lv","latvian"],["bn","bengali"],["sr","serbian"],["az","azerbaijani"],["sl","slovenian"],["kn","kannada"],["et","estonian"],["mk","macedonian"],["br","breton"],["eu","basque"],["is","icelandic"],["hy","armenian"],["ne","nepali"],["mn","mongolian"],["bs","bosnian"],["kk","kazakh"],["sq","albanian"],["sw","swahili"],["gl","galician"],["mr","marathi"],["pa","punjabi"],["si","sinhala"],["km","khmer"],["sn","shona"],["yo","yoruba"],["so","somali"],["af","afrikaans"],["oc","occitan"],["ka","georgian"],["be","belarusian"],["tg","tajik"],["sd","sindhi"],["gu","gujarati"],["am","amharic"],["yi","yiddish"],["lo","lao"],["uz","uzbek"],["fo","faroese"],["ht","haitian creole"],["ps","pashto"],["tk","turkmen"],["nn","nynorsk"],["mt","maltese"],["sa","sanskrit"],["lb","luxembourgish"],["my","myanmar"],["bo","tibetan"],["tl","tagalog"],["mg","malagasy"],["as","assamese"],["tt","tatar"],["haw","hawaiian"],["ln","lingala"],["ha","hausa"],["ba","bashkir"],["jw","javanese"],["su","sundanese"]],WHISPER_LANGUAGE_MAPPING=new Map(WHISPER_LANGUAGES),WHISPER_TO_LANGUAGE_CODE_MAPPING=new Map([...WHISPER_LANGUAGES.map(([_,n])=>[n,_]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);class WhisperTokenizer extends PreTrainedTokenizer{_decode_asr(n,{return_timestamps:o=!1,return_language:u=!1,time_precision:l=null,force_full_sequences:d=!0}={}){if(l===null)throw Error("Must specify time_precision");let s=null;const p=o==="word";function f(){return{language:s,timestamp:[null,null],text:""}}const c=[];let a=f(),t=0;const e=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let r=[],i=[],h=!1,g=null;const m=new Set(this.all_special_ids);for(let w of n){const T=w.tokens,S=p?w.token_timestamps:null;let A=null,O=e;if("stride"in w){const[F,R,$]=w.stride;if(t-=R,g=F-$,R&&(O=R/l+e),$)for(let N=T.length-1;N>=0;--N){const G=T[N];if(G>=e){if(A!==null&&(G-e)*l=e){const $=(R-e)*l+t,N=round($,2);if(A!==null&&R>=A)h=!0;else if(h||r.length>0&&R0?(r.push(v),p&&i.push(M)):r.every(F=>F.length===0)&&(a=f(),r=[],v=[],i=[],M=[])}if(r.length>0){if(d&&o)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[w,T]=this.findLongestCommonSequence(r,i),S=this.decode(w);a.text=S,p&&(a.words=this.collateWordTimestamps(w,T,s)),c.push(a)}let b=Object.create(null);const y=c.map(w=>w.text).join("");if(o||u){for(let w=0;w0;let p=s?[]:null,f=s?o[0]:null;for(let c=1;cN===F[G]).length,$=R/w+T;R>1&&$>t&&(t=$,e=[S,A,v,M])}const[i,h,g,m]=e,b=Math.floor((h+i)/2),y=Math.floor((m+g)/2);d.push(...u.slice(0,b)),u=a.slice(y),l=u.length,s&&(p.push(...f.slice(0,b)),f=o[c].slice(y))}return d.push(...u),s?(p.push(...f),[d,p]):[d,[]]}collateWordTimestamps(n,o,u){let[l,d,s]=this.combineTokensIntoWords(n,u),p=[];for(let f=0;f=l){let p=(s-l)*u;p=round(p,2),d.push(`<|${p}|>`),d.push([])}else d[d.length-1].push(s);return d=d.map(s=>typeof s=="string"?s:super.decode(s,o)),d.join("")}splitTokensOnUnicode(n){const o=this.decode(n,{decode_with_timestamps:!0}),u="�";let l=[],d=[],s=[],p=[],f=[],c=0;for(let a=0;a=this.model.tokens_to_ids.get("<|endoftext|>"),i=a.startsWith(" "),h=a.trim(),g=f.test(h);if(r||i||g||d.length===0)d.push(a),s.push(t),p.push(e);else{const m=d.length-1;d[m]+=a,s[m].push(...t),p[m].push(...e)}}return[d,s,p]}mergePunctuations(n,o,u,l,d){let s=structuredClone(n),p=structuredClone(o),f=structuredClone(u),c=s.length-2,a=s.length-1;for(;c>=0;)s[c].startsWith(" ")&&l.includes(s[c].trim())?(s[a]=s[c]+s[a],p[a]=mergeArrays(p[c],p[a]),f[a]=mergeArrays(f[c],f[a]),s[c]="",p[c]=[],f[c]=[]):a=c,--c;for(c=0,a=1;at),p.filter(t=>t.length>0),f.filter(t=>t.length>0)]}get_decoder_prompt_ids({language:n=null,task:o=null,no_timestamps:u=!0}={}){let l=[];if(n){n=n.toLowerCase();let d=WHISPER_TO_LANGUAGE_CODE_MAPPING.get(n);if(d===void 0)if(WHISPER_LANGUAGE_MAPPING.has(n))d=n;else{const f=n.length===2?WHISPER_LANGUAGE_MAPPING.keys():WHISPER_LANGUAGE_MAPPING.values();throw new Error(`Language "${n}" is not supported. Must be one of: ${JSON.stringify(f)}`)}let s=this.model.tokens_to_ids.get(`<|${d}|>`);if(s===void 0)throw new Error(`Unable to find language "${d}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);l.push(s)}else l.push(null);if(o){if(o=o.toLowerCase(),o!=="transcribe"&&o!=="translate")throw new Error(`Task "${o}" is not supported. Must be one of: ["transcribe", "translate"]`);let d=this.model.tokens_to_ids.get(`<|${o}|>`);if(d===void 0)throw new Error(`Unable to find task "${o}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);l.push(d)}else l.push(null);if(u){let d=this.model.tokens_to_ids.get("<|notimestamps|>");if(d===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.');l.push(d)}return l.map((d,s)=>[s+1,d]).filter(d=>d[1]!==null)}}class CodeGenTokenizer extends PreTrainedTokenizer{}class CLIPTokenizer extends PreTrainedTokenizer{}class MarianTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter(u=>this.languageRegex.test(u)),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(n){if(n===null)return null;let[o,...u]=n.trim().split(this.languageRegex);if(u.length===0)return super._encode_text(o);if(u.length===2){let[l,d]=u;return this.supported_language_codes.includes(l)||console.warn(`Unsupported language code "${l}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),mergeArrays([l],super._encode_text(d))}}}class Wav2Vec2CTCTokenizer extends PreTrainedTokenizer{}class BlenderbotTokenizer extends PreTrainedTokenizer{}class BlenderbotSmallTokenizer extends PreTrainedTokenizer{}class SpeechT5Tokenizer extends PreTrainedTokenizer{}class AutoTokenizer{static async from_pretrained(n,{quantized:o=!0,progress_callback:u=null,config:l=null,cache_dir:d=null,local_files_only:s=!1,revision:p="main"}={}){let[f,c]=await loadTokenizer(n,{quantized:o,progress_callback:u,config:l,cache_dir:d,local_files_only:s,revision:p}),a=c.tokenizer_class.replace(/Fast$/,""),t=this.TOKENIZER_CLASS_MAPPING[a];return t||(console.warn(`Unknown tokenizer class "${a}", attempting to construct from base class.`),t=PreTrainedTokenizer),new t(f,c)}}le(AutoTokenizer,"TOKENIZER_CLASS_MAPPING",{T5Tokenizer,DistilBertTokenizer,CamembertTokenizer,DebertaTokenizer,DebertaV2Tokenizer,BertTokenizer,HerbertTokenizer,XLMTokenizer,MobileBertTokenizer,SqueezeBertTokenizer,AlbertTokenizer,GPT2Tokenizer,BartTokenizer,MBartTokenizer,MBart50Tokenizer,RobertaTokenizer,WhisperTokenizer,CodeGenTokenizer,CLIPTokenizer,MarianTokenizer,BloomTokenizer,NllbTokenizer,M2M100Tokenizer,LlamaTokenizer,CodeLlamaTokenizer,XLMRobertaTokenizer,MPNetTokenizer,FalconTokenizer,GPTNeoXTokenizer,Wav2Vec2CTCTokenizer,BlenderbotTokenizer,BlenderbotSmallTokenizer,SpeechT5Tokenizer,PreTrainedTokenizer});async function loadConfig(_,n){return await getModelJSON(_,"config.json",!0,n)}class PretrainedConfig{constructor(n){this.model_type=null,this.is_encoder_decoder=!1,Object.assign(this,n)}static async from_pretrained(n,{progress_callback:o=null,config:u=null,cache_dir:l=null,local_files_only:d=!1,revision:s="main"}={}){let p=u??await loadConfig(n,{progress_callback:o,config:u,cache_dir:l,local_files_only:d,revision:s});return new this(p)}}class AutoConfig{static async from_pretrained(...n){return PretrainedConfig.from_pretrained(...n)}}class LogitsProcessorList extends Callable{constructor(){super(),this.processors=[]}push(n){this.processors.push(n)}extend(n){this.processors.push(...n)}_call(n,o){for(let u of o)this.processors.forEach(l=>l(n,u))}[Symbol.iterator](){return this.processors.values()}}class LogitsProcessor extends Callable{_call(n,o){throw Error("`_call` should be implemented in a subclass")}}class ForceTokensLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.force_token_map=Object.fromEntries(n??[])}_call(n,o){let u=this.force_token_map[n.length];return exists(u)&&(o.data.fill(-1/0),o.data[u]=0),o}}class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.bos_token_id=n}_call(n,o){return n.length===1&&(o.data.fill(-1/0),o.data[this.bos_token_id]=0),o}}class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.max_length=n,this.forced_eos_token_id=o}_call(n,o){}}class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.begin_suppress_tokens=n,this.begin_index=o}_call(n,o){if(n.length===this.begin_index)for(let u of this.begin_suppress_tokens)o.data[u]=-1/0;return o}}class WhisperTimeStampLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.eos_token_id=n.eos_token_id,this.no_timestamps_token_id=n.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(n.forced_decoder_ids||[]).length+2,n.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=n.max_initial_timestamp_index}_call(n,o){if(o.data[this.no_timestamps_token_id]=-1/0,n.length===this.begin_index-1)return o.data.fill(-1/0),o.data[this.timestamp_begin]=0,o;const u=n.slice(this.begin_index),l=u.length>=1&&u[u.length-1]>=this.timestamp_begin,d=u.length<2||u[u.length-2]>=this.timestamp_begin;if(l&&(d?o.data.subarray(this.timestamp_begin).fill(-1/0):o.data.subarray(0,this.eos_token_id).fill(-1/0)),n.length===this.begin_index&&this.max_initial_timestamp_index!==null){const c=this.timestamp_begin+this.max_initial_timestamp_index;o.data.subarray(c+1).fill(-1/0)}const s=log_softmax(o.data),p=Math.log(s.subarray(this.timestamp_begin).map(Math.exp).reduce((c,a)=>c+a)),f=max(s.subarray(0,this.timestamp_begin))[0];return p>f&&o.data.subarray(0,this.timestamp_begin).fill(-1/0),o}}class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.no_repeat_ngram_size=n}getNgrams(n){const o=n.length,u=[];for(let d=0;d0&&(l=l.map(d=>d/this.generation_config.temperature)),l}randomSelect(n){let o=n.reduce((l,d)=>l+d,0),u=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 ${n.num_return_sequences}.`);return new GreedySampler(n)}}class GreedySampler extends Sampler{sample(n,o=-1){let u=this.getLogits(n,o);return[[max(u)[1],0]]}}class MultinomialSampler extends Sampler{sample(n,o=-1){let u=n.dims.at(-1);this.generation_config.top_k>0&&(u=Math.min(this.generation_config.top_k,u));const l=this.getLogits(n,o),d=getTopItems(l,u),s=softmax(d.map(p=>p[1]));return Array.from({length:this.generation_config.num_beams},()=>{const p=this.randomSelect(s);return[d[p][0],Math.log(s[p])]})}}class BeamSearchSampler extends Sampler{sample(n,o=-1){let u=n.dims.at(-1);this.generation_config.top_k>0&&(u=Math.min(this.generation_config.top_k,u));const l=this.getLogits(n,o),d=getTopItems(l,u),s=softmax(d.map(p=>p[1]));return Array.from({length:this.generation_config.num_beams},(p,f)=>[d[f][0],Math.log(s[f])])}}const{InferenceSession,Tensor:ONNXTensor}=ONNX,MODEL_TYPES={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4},MODEL_TYPE_MAPPING=new Map,MODEL_NAME_TO_CLASS_MAPPING=new Map,MODEL_CLASS_TO_NAME_MAPPING=new Map;async function constructSession(_,n,o){let u=`onnx/${n}${o.quantized?"_quantized":""}.onnx`,l=await getModelFile(_,u,!0,o);try{return await InferenceSession.create(l,{executionProviders})}catch(d){if(executionProviders.length===1&&executionProviders[0]==="wasm")throw d;return console.warn(d),console.warn("Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback. "),await InferenceSession.create(l,{executionProviders:["wasm"]})}}async function validateInputs(_,n){const o={},u=[];for(let s of _.inputNames)n[s]===void 0?u.push(s):o[s]=n[s];if(u.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${u.join(", ")}.`);const l=Object.keys(n).length,d=_.inputNames.length;if(l>d){let s=Object.keys(n).filter(p=>!_.inputNames.includes(p));console.warn(`WARNING: Too many inputs were provided (${l} > ${d}). The following inputs will be ignored: "${s.join(", ")}".`)}return o}async function sessionRun(_,n){const o=await validateInputs(_,n);try{let u=await _.run(o);return u=replaceTensors(u),u}catch(u){throw console.error(`An error occurred during model execution: "${u}".`),console.error("Inputs given to model:",o),u}}function replaceTensors(_){for(let n in _)_[n]instanceof ONNXTensor?_[n]=new Tensor(_[n]):typeof _[n]=="object"&&replaceTensors(_[n]);return _}function toI64Tensor(_){if(_ instanceof Tensor)return _;if(_.length===0)throw Error("items must be non-empty");if(Array.isArray(_[0])){if(_.some(n=>n.length!==_[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(_.flat().map(n=>BigInt(n))),[_.length,_[0].length])}else return new Tensor("int64",BigInt64Array.from(_.map(n=>BigInt(n))),[1,_.length])}function prepareAttentionMask(_,n){let o=_.config.pad_token_id??null,u=_.config.eos_token_id??null;isIntegralNumber(u)&&(u=[u]);let l=n.indexOf(o)!==-1,d=u===null||!u.includes(o);if(l&&d){let s=BigInt64Array.from(n.data.map(p=>p!=o));return new Tensor("int64",s,n.dims)}else return ones_like(n)}function boolTensor(_){return new Tensor("bool",[_],[1])}async function seq2seqForward(_,n){let{encoder_outputs:o,past_key_values:u}=n;o||(o=(await encoderForward(_,n)).last_hidden_state);let l={input_ids:n.decoder_input_ids,encoder_hidden_states:o,use_cache_branch:boolTensor(!!u)};_.decoder_merged_session.inputNames.includes("encoder_attention_mask")&&(l.encoder_attention_mask=n.attention_mask),_.addPastKeyValues(l,u);const d=await sessionRun(_.decoder_merged_session,l);let s=d.logits;u=_.getPastKeyValues(d,u);const p=_.getAttentions(d);return new Seq2SeqLMOutput({logits:s,past_key_values:u,encoder_outputs:o,...p})}function seq2seqStartBeams(_,n,o,u){let l=[],d=0;const s=_.requires_attention_mask??!0;let p=o.decoder_input_ids??o.decoder_start_token_id??o.bos_token_id??o.eos_token_id;p instanceof Tensor?p=p.tolist().flat():Array.isArray(p)||(p=[p]);for(let f of n){f.dims=[1,...f.dims];let c={inputs:f,encoder_outputs:null,prev_model_outputs:null,output_token_ids:p,done:!1,score:0,id:d++};s&&(c.attention_mask=prepareAttentionMask(_,f)),l.push(c)}return l}async function seq2seqRunBeam(_,n){var s;const o=_.main_input_name;let u=n.output_token_ids;n.prev_model_outputs&&(u=u.slice(-1));let l={[o]:n.inputs,decoder_input_ids:toI64Tensor(u),encoder_outputs:n.encoder_outputs,past_key_values:(s=n.prev_model_outputs)==null?void 0:s.past_key_values};n.attention_mask&&(l.attention_mask=n.attention_mask);let d=await _.forward(l);return n.prev_model_outputs=d,n.encoder_outputs=d.encoder_outputs,d}function seq2seqUpdatebeam(_,n){_.output_token_ids=[..._.output_token_ids,n]}async function encoderForward(_,n){let o={};for(let u of _.session.inputNames)o[u]=n[u];return await sessionRun(_.session,o)}async function decoderForward(_,n){let{input_ids:o,past_key_values:u,attention_mask:l}=n,d={input_ids:o,attention_mask:l??prepareAttentionMask(_,o),use_cache_branch:boolTensor(!!u)};_.addPastKeyValues(d,u);let s=await sessionRun(_.session,d),p=s.logits;return u=_.getPastKeyValues(s,u),{logits:p,past_key_values:u}}function decoderStartBeams(_,n,o,u,l){let d=[],s=0;for(let p of n){let f=p.tolist().map(Number);p.dims=[1,...p.dims];let c;l?(c=l[s],c.dims=[1,...c.dims]):c=prepareAttentionMask(_,p);let a={input:p,model_input_ids:p,attention_mask:c,prev_model_outputs:null,output_token_ids:f,num_output_tokens:u,done:!1,score:0,id:s++};d.push(a)}return d}async function decoderRunBeam(_,n){var d;let o=new BigInt64Array(n.output_token_ids.length).fill(1n),u={input_ids:n.model_input_ids,attention_mask:new Tensor("int64",o,[1,o.length]),past_key_values:(d=n.prev_model_outputs)==null?void 0:d.past_key_values},l=await _.forward(u);return n.prev_model_outputs=l,l}function decoderUpdatebeam(_,n){_.output_token_ids=[..._.output_token_ids,n],_.model_input_ids=new Tensor("int64",[BigInt(n)],[1,1])}class PreTrainedModel extends Callable{constructor(o,u){super();le(this,"main_input_name","input_ids");this.config=o,this.session=u;const l=MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor),d=MODEL_TYPE_MAPPING.get(l);this.can_generate=!1,this._runBeam=null,this._getStartBeams=null,this._updateBeam=null,this._forward=null,d===MODEL_TYPES.DecoderOnly?(this.can_generate=!0,this._runBeam=decoderRunBeam,this._getStartBeams=decoderStartBeams,this._updateBeam=decoderUpdatebeam,this._forward=decoderForward):d===MODEL_TYPES.Seq2Seq||d===MODEL_TYPES.Vision2Seq?(this.can_generate=!0,this._runBeam=seq2seqRunBeam,this._getStartBeams=seq2seqStartBeams,this._updateBeam=seq2seqUpdatebeam,this._forward=seq2seqForward):d===MODEL_TYPES.EncoderDecoder?this._forward=encoderForward:this._forward=encoderForward}async dispose(){let o=[];for(let u of Object.keys(this)){let l=this[u];l instanceof InferenceSession&&o.push(l.handler.dispose())}return await Promise.all(o)}static async from_pretrained(o,{quantized:u=!0,progress_callback:l=null,config:d=null,cache_dir:s=null,local_files_only:p=!1,revision:f="main",model_file_name:c=null}={}){let a={quantized:u,progress_callback:l,config:d,cache_dir:s,local_files_only:p,revision:f,model_file_name:c};const t=MODEL_CLASS_TO_NAME_MAPPING.get(this),e=MODEL_TYPE_MAPPING.get(t);let r;return e===MODEL_TYPES.DecoderOnly?r=await Promise.all([AutoConfig.from_pretrained(o,a),constructSession(o,a.model_file_name??"decoder_model_merged",a),getModelJSON(o,"generation_config.json",!1,a)]):e===MODEL_TYPES.Seq2Seq||e===MODEL_TYPES.Vision2Seq?r=await Promise.all([AutoConfig.from_pretrained(o,a),constructSession(o,"encoder_model",a),constructSession(o,"decoder_model_merged",a),getModelJSON(o,"generation_config.json",!1,a)]):e===MODEL_TYPES.EncoderDecoder?r=await Promise.all([AutoConfig.from_pretrained(o,a),constructSession(o,"encoder_model",a),constructSession(o,"decoder_model_merged",a)]):(e!==MODEL_TYPES.EncoderOnly&&console.warn(`Model type for '${t}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`),r=await Promise.all([AutoConfig.from_pretrained(o,a),constructSession(o,a.model_file_name??"model",a)])),new this(...r)}async _call(o){return await this.forward(o)}async forward(o){return await this._forward(this,o)}_get_logits_processor(o,u,l=null){const d=new LogitsProcessorList;if(o.repetition_penalty!==null&&o.repetition_penalty!==1&&d.push(new RepetitionPenaltyLogitsProcessor(o.repetition_penalty)),o.no_repeat_ngram_size!==null&&o.no_repeat_ngram_size>0&&d.push(new NoRepeatNGramLogitsProcessor(o.no_repeat_ngram_size)),o.min_length!==null&&o.eos_token_id!==null&&o.min_length>0&&d.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&&d.push(new MinNewTokensLengthLogitsProcessor(u,o.min_new_tokens,o.eos_token_id)),o.forced_bos_token_id!==null&&d.push(new ForcedBOSTokenLogitsProcessor(o.forced_bos_token_id)),o.forced_eos_token_id!==null&&d.push(new ForcedEOSTokenLogitsProcessor(o.max_length,o.forced_eos_token_id)),o.begin_suppress_tokens!==null){let s=u>1||o.forced_bos_token_id===null?u:u+1;o.forced_decoder_ids!==null&&(s+=o.forced_decoder_ids[o.forced_decoder_ids.length-1][0]),d.push(new SuppressTokensAtBeginLogitsProcessor(o.begin_suppress_tokens,s))}return o.forced_decoder_ids!==null&&d.push(new ForceTokensLogitsProcessor(o.forced_decoder_ids)),l!==null&&d.extend(l),d}_get_generation_config(o){let u=new GenerationConfig(this.config);return"generation_config"in this&&Object.assign(u,this.generation_config),o!==null&&Object.assign(u,o),u}async generate(o,u=null,l=null,{inputs_attention_mask:d=null}={}){if(!this.can_generate){let m=`The current model class (${MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const b=this.config.model_type,y=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(b)??MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES.get(b)??MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES.get(b)??MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES.get(b);throw y&&(m+=` Please use the following class instead: '${y[0]}'`),Error(m)}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 s;if(this.config.is_encoder_decoder)s=0;else if(s=o instanceof Tensor?o.dims.at(-1):o.length,s===0)throw Error("Must supply a non-empty array of input token ids.");u=this._get_generation_config(u),l=l??new LogitsProcessorList,l=this._get_logits_processor(u,s,l);let p=u.eos_token_id;p!==null&&!Array.isArray(p)&&(p=[p]);let f=1;const c=f+(u.max_new_tokens??1/0),a=Number.isInteger(u.max_length)&&(u.max_new_tokens??null)===null;let t=Sampler.getSampler(u),e=this.getStartBeams(o,u,f,d);for(;e.some(g=>!g.done)&&f=u.max_length){m.done=!0,g.push(m);continue}let b=await this.runBeam(m);u.output_attentions&&this.addAttentionsToBeam(m,b),u.output_scores;let y=b.logits.slice(null,-1,null);l(m.output_token_ids,y);let w=t(y);for(let[T,S]of w){let A={...m};this.updateBeam(A,T),A.score+=S,p&&p.includes(T)&&(A.done=!0),g.push(A)}}++f,g=this.groupBeams(g).map(m=>m.sort((b,y)=>y.score-b.score).slice(0,u.num_beams)),e=g.flat(),u.callback_function&&u.callback_function(e)}const r=this.groupBeams(e),i=g=>r.map(m=>u.num_return_sequences>1?m.slice(0,u.num_return_sequences).map(b=>b[g]):[m[0][g]]).flat(),h=i("output_token_ids");if(u.return_dict_in_generate){const g=i("decoder_attentions"),m=i("cross_attentions");return{sequences:h,decoder_attentions:g,cross_attentions:m}}else return h}addAttentionsToBeam(o,u){if(this.config.is_encoder_decoder){if(!u.cross_attentions||u.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(u.cross_attentions)}if(!u.decoder_attentions||u.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(u.decoder_attentions)}groupBeams(o){const u=Object.create(null);for(const l of o)u[l.id]===void 0?u[l.id]=[l]:u[l.id].push(l);return Object.values(u)}getPastKeyValues(o,u){const l=Object.create(null);for(const d in o)if(d.startsWith("present")){let s=d.replace("present","past_key_values");u&&d.includes("encoder")?l[s]=u[s]:l[s]=o[d]}return l}getAttentions(o){const u=Object.create(null);for(const l of["cross_attentions","decoder_attentions"]){const d=[];for(const s in o)if(s.startsWith(l)){const p=s.split(".").pop();d[p]=o[s]}u[l]=d}return u}addPastKeyValues(o,u){if(u)Object.assign(o,u);else if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??!0)){let l=[1,this.num_encoder_heads,0,this.encoder_dim_kv],d=[1,this.num_decoder_heads,0,this.decoder_dim_kv];for(let s=0;s{let t=Array.from({length:this.config.decoder_layers},(m,b)=>cat(a.map(y=>y[b]),2)),e=stack(u.map(([m,b])=>l?t[m].slice(null,b,null,[0,l]):t[m].slice(null,b)));e=e.transpose(1,0,2,3);let[r,i]=std_mean(e,-2,0,!0),h=e.clone();for(let m=0;me[b+1]-e[b]),h=mergeArrays([1],i).map(m=>!!m),g=[];for(let m=0;m=e&&(Array.from(A.data).filter(v=>v>=u).length>0||m>=t))break}const b=cat(i),{waveform:y}=await sessionRun(s.session,{spectrogram:b});return{spectrogram:b,waveform:y}}}class SpeechT5HifiGan extends PreTrainedModel{constructor(){super(...arguments);le(this,"main_input_name","spectrogram")}}class PretrainedMixin{static async from_pretrained(n,{quantized:o=!0,progress_callback:u=null,config:l=null,cache_dir:d=null,local_files_only:s=!1,revision:p="main",model_file_name:f=null}={}){let c={quantized:o,progress_callback:u,config:l,cache_dir:d,local_files_only:s,revision:p,model_file_name:f};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 a of this.MODEL_CLASS_MAPPINGS){const t=a.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}`)}}le(PretrainedMixin,"MODEL_CLASS_MAPPINGS",null),le(PretrainedMixin,"BASE_IF_FAIL",!1);const MODEL_MAPPING_NAMES_ENCODER_ONLY=new Map([["bert",["BertModel",BertModel]],["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]],["clip",["CLIPModel",CLIPModel]],["mobilebert",["MobileBertModel",MobileBertModel]],["squeezebert",["SqueezeBertModel",SqueezeBertModel]],["wav2vec2",["Wav2Vec2Model",Wav2Vec2Model]],["wavlm",["WavLMModel",WavLMModel]],["detr",["DetrModel",DetrModel]],["vit",["ViTModel",ViTModel]],["mobilevit",["MobileViTModel",MobileViTModel]],["beit",["BeitModel",BeitModel]],["deit",["DeiTModel",DeiTModel]],["resnet",["ResNetModel",ResNetModel]],["swin",["SwinModel",SwinModel]],["donut-swin",["DonutSwinModel",DonutSwinModel]],["yolos",["YolosModel",YolosModel]],["hifigan",["SpeechT5HifiGan",SpeechT5HifiGan]],["sam",["SamModel",SamModel]]]),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]],["mpt",["MptModel",MptModel]],["opt",["OPTModel",OPTModel]]]),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_SEQUENCE_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForSequenceClassification",BertForSequenceClassification]],["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]],["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]],["mpt",["MptForCausalLM",MptForCausalLM]],["opt",["OPTForCausalLM",OPTForCausalLM]],["mbart",["MBartForCausalLM",MBartForCausalLM]]]),MODEL_FOR_MASKED_LM_MAPPING_NAMES=new Map([["bert",["BertForMaskedLM",BertForMaskedLM]],["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]],["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_DOCUMENT_QUESTION_ANSWERING_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]],["resnet",["ResNetForImageClassification",ResNetForImageClassification]],["swin",["SwinForImageClassification",SwinForImageClassification]]]),MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES=new Map([["detr",["DetrForObjectDetection",DetrForObjectDetection]],["yolos",["YolosForObjectDetection",YolosForObjectDetection]]]),MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES=new Map([["detr",["DetrForSegmentation",DetrForSegmentation]]]),MODEL_FOR_MASK_GENERATION_MAPPING_NAMES=new Map([["sam",["SamModel",SamModel]]]),MODEL_FOR_CTC_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForCTC",Wav2Vec2ForCTC]],["wavlm",["WavLMForCTC",WavLMForCTC]]]),MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Wav2Vec2ForSequenceClassification]],["wavlm",["WavLMForSequenceClassification",WavLMForSequenceClassification]]]),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_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_MASK_GENERATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[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]];for(const[_,n]of MODEL_CLASS_TYPE_MAPPING)for(const[o,u]of _.values())MODEL_TYPE_MAPPING.set(o,n),MODEL_CLASS_TO_NAME_MAPPING.set(u,o),MODEL_NAME_TO_CLASS_MAPPING.set(o,u);const CUSTOM_MAPPING=[["CLIPTextModelWithProjection",CLIPTextModelWithProjection,MODEL_TYPES.EncoderOnly],["CLIPVisionModelWithProjection",CLIPVisionModelWithProjection,MODEL_TYPES.EncoderOnly]];for(const[_,n,o]of CUSTOM_MAPPING)MODEL_TYPE_MAPPING.set(_,o),MODEL_CLASS_TO_NAME_MAPPING.set(n,_),MODEL_NAME_TO_CLASS_MAPPING.set(_,n);class AutoModel extends PretrainedMixin{}le(AutoModel,"MODEL_CLASS_MAPPINGS",[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_MAPPING_NAMES_DECODER_ONLY]),le(AutoModel,"BASE_IF_FAIL",!0);class AutoModelForSequenceClassification extends PretrainedMixin{}le(AutoModelForSequenceClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForTokenClassification extends PretrainedMixin{}le(AutoModelForTokenClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForSeq2SeqLM extends PretrainedMixin{}le(AutoModelForSeq2SeqLM,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES]);class AutoModelForSpeechSeq2Seq extends PretrainedMixin{}le(AutoModelForSpeechSeq2Seq,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES]);class AutoModelForTextToSpectrogram extends PretrainedMixin{}le(AutoModelForTextToSpectrogram,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES]);class AutoModelForCausalLM extends PretrainedMixin{}le(AutoModelForCausalLM,"MODEL_CLASS_MAPPINGS",[MODEL_WITH_LM_HEAD_MAPPING_NAMES]);class AutoModelForMaskedLM extends PretrainedMixin{}le(AutoModelForMaskedLM,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_MASKED_LM_MAPPING_NAMES]);class AutoModelForQuestionAnswering extends PretrainedMixin{}le(AutoModelForQuestionAnswering,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES]);class AutoModelForVision2Seq extends PretrainedMixin{}le(AutoModelForVision2Seq,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES]);class AutoModelForImageClassification extends PretrainedMixin{}le(AutoModelForImageClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForImageSegmentation extends PretrainedMixin{}le(AutoModelForImageSegmentation,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES]);class AutoModelForObjectDetection extends PretrainedMixin{}le(AutoModelForObjectDetection,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES]);class AutoModelForCTC extends PretrainedMixin{}le(AutoModelForCTC,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_CTC_MAPPING_NAMES]);class AutoModelForAudioClassification extends PretrainedMixin{}le(AutoModelForAudioClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForDocumentQuestionAnswering extends PretrainedMixin{}le(AutoModelForDocumentQuestionAnswering,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES]);class Seq2SeqLMOutput extends ModelOutput{constructor({logits:n,past_key_values:o,encoder_outputs:u,decoder_attentions:l=null,cross_attentions:d=null}){super(),this.logits=n,this.past_key_values=o,this.encoder_outputs=u,this.decoder_attentions=l,this.cross_attentions=d}}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}}const BROWSER_ENV=typeof self<"u";let createCanvasFunction,ImageDataClass,loadImageFunction;if(BROWSER_ENV)createCanvasFunction=(_,n)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this browser.");return new self.OffscreenCanvas(_,n)},loadImageFunction=self.createImageBitmap,ImageDataClass=self.ImageData;else if(sharp)loadImageFunction=async _=>{const o=(await _.metadata()).channels;let{data:u,info:l}=await _.raw().toBuffer({resolveWithObject:!0});const d=new RawImage(new Uint8ClampedArray(u),l.width,l.height,l.channels);return o!==void 0&&o!==l.channels&&d.convert(o),d};else throw new Error("Unable to load image processing library.");const RESAMPLING_MAPPING={0:"nearest",1:"lanczos",2:"bilinear",3:"bicubic",4:"box",5:"hamming"};class RawImage{constructor(n,o,u,l){le(this,"_CONTENT_TYPE_MAP",{png:"image/png",jpg:"image/jpeg",jpeg:"image/jpeg",gif:"image/gif"});this.data=n,this.width=o,this.height=u,this.channels=l}static async read(n){if(n instanceof RawImage)return n;if(isString(n)||n instanceof URL)return await this.fromURL(n);throw new Error(`Unsupported input type: ${typeof n}`)}static async fromURL(n){let o=await getFile(n);if(o.status!==200)throw new Error(`Unable to read image from "${n}" (${o.status} ${o.statusText})`);let u=await o.blob();return this.fromBlob(u)}static async fromBlob(n){if(BROWSER_ENV){let o=await loadImageFunction(n);const u=createCanvasFunction(o.width,o.height).getContext("2d");return u.drawImage(o,0,0),new this(u.getImageData(0,0,o.width,o.height).data,o.width,o.height,4)}else{let o=sharp(await n.arrayBuffer());return await loadImageFunction(o)}}grayscale(){if(this.channels===1)return this;let n=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let o=0,u=0;o=0?f=u:a=-u,l>=0?c=l:t=-l,p.drawImage(s,f,c,n,o,a,t,n,o),new RawImage(p.getImageData(0,0,n,o).data,n,o,4).convert(d)}else{let d=this.toSharp();if(u>=0&&l>=0)d=d.extract({left:Math.floor(u),top:Math.floor(l),width:n,height:o});else if(u<=0&&l<=0){let s=Math.floor(-l),p=Math.floor(-u);d=d.extend({top:s,left:p,right:n-this.width-p,bottom:o-this.height-s})}else{let s=[0,0],p=0;l<0?(s[0]=Math.floor(-l),s[1]=o-this.height-s[0]):p=Math.floor(l);let f=[0,0],c=0;u<0?(f[0]=Math.floor(-u),f[1]=n-this.width-f[0]):c=Math.floor(u),d=d.extend({top:s[0],bottom:s[1],left:f[0],right:f[1]}).extract({left:c,top:p,width:n,height:o})}return await loadImageFunction(d)}}toCanvas(){if(!BROWSER_ENV)throw new Error("toCanvas() is only supported in browser environments.");let n=this.clone().rgba(),o=createCanvasFunction(n.width,n.height),u=new ImageDataClass(n.data,n.width,n.height);return o.getContext("2d").putImageData(u,0,0),o}_update(n,o,u,l=null){return this.data=n,this.width=o,this.height=u,l!==null&&(this.channels=l),this}clone(){return new RawImage(this.data.slice(),this.width,this.height,this.channels)}convert(n){if(this.channels===n)return this;switch(n){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}save(n){if(BROWSER_ENV){const o=n.split(".").pop().toLowerCase(),u=this._CONTENT_TYPE_MAP[o]??"image/png",d=this.toCanvas().toDataURL(u),s=document.createElement("a");s.href=d,s.download=n,s.click(),s.remove()}else if(env.useFS)this.toSharp().toFile(n);else throw new Error("Unable to save the image because filesystem is disabled in this environment.")}toSharp(){if(BROWSER_ENV)throw new Error("toSharp() is only supported in server-side environments.");return sharp(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}}async function read_audio(_,n){if(typeof AudioContext>"u")throw Error("Unable to load audio from path/URL since `AudioContext` is not available in your environment. Instead, audio data should be passed directly to the pipeline/processor. For more information and some example code, see https://huggingface.co/docs/transformers.js/guides/node-audio-processing.");const o=await(await getFile(_)).arrayBuffer(),u=new AudioContext({sampleRate:n});typeof n>"u"&&console.warn(`No sampling rate provided, using default of ${u.sampleRate}Hz.`);const l=await u.decodeAudioData(o);let d;if(l.numberOfChannels===2){const s=Math.sqrt(2);let p=l.getChannelData(0),f=l.getChannelData(1);d=new Float32Array(p.length);for(let c=0;c=i?e[b]=r*Math.exp(h*(y-i)):e[b]=a+t*y,g[b]=d.map(w=>e[b]-w)}const m=e.slice(1).map((b,y)=>1/(b-e[y]));for(let b=0;bn){let y=r[i].data;y=center_to_corners_format(y),a!==null&&(y=y.map((w,T)=>w*a[(T+1)%2])),t.boxes.push(y),t.classes.push(g),t.scores.push(b)}}f.push(t)}return f}class FeatureExtractor extends Callable{constructor(n){super(),this.config=n}}class ImageFeatureExtractor extends FeatureExtractor{constructor(n){super(n),this.image_mean=this.config.image_mean,this.image_std=this.config.image_std,this.resample=this.config.resample??2,this.do_rescale=this.config.do_rescale??!0,this.rescale_factor=this.config.rescale_factor??1/255,this.do_normalize=this.config.do_normalize,this.do_resize=this.config.do_resize,this.do_thumbnail=this.config.do_thumbnail,this.size=this.config.size,this.do_center_crop=this.config.do_center_crop,this.crop_size=this.config.crop_size,this.do_convert_rgb=this.config.do_convert_rgb??!0,this.pad_size=this.config.pad_size,this.do_pad=this.config.do_pad,this.do_pad&&!this.pad_size&&this.size.width!==void 0&&this.size.height!==void 0&&(this.pad_size=this.size)}async thumbnail(n,o,u=2){const l=n.height,d=n.width,s=o.height,p=o.width;let f=Math.min(l,s),c=Math.min(d,p);return f===l&&c===d?n:(l>d?c=Math.floor(d*f/l):d>l&&(f=Math.floor(l*c/d)),await n.resize(c,f,{resample:u}))}async preprocess(n){this.do_convert_rgb&&(n=n.rgb());const o=n.width,u=n.height;if(this.do_resize){let c,a;if(this.do_thumbnail){const{height:t,width:e}=this.size;c=Math.min(t,e)}else Number.isInteger(this.size)?(c=this.size,a=this.config.max_size??c):(c=this.size.shortest_edge,a=this.size.longest_edge);if(c!==void 0||a!==void 0){const t=c===void 0?1:Math.max(c/o,c/u),e=o*t,r=u*t,i=a===void 0?1:Math.min(a/e,a/r),h=Math.floor(Number((e*i).toFixed(2))),g=Math.floor(Number((r*i).toFixed(2)));n=await n.resize(h,g,{resample:this.resample})}else if(this.size.width!==void 0&&this.size.height!==void 0)n=await n.resize(this.size.width,this.size.height,{resample:this.resample});else throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(this.size)}`)}if(this.do_thumbnail&&(n=await this.thumbnail(n,this.size,this.resample)),this.do_center_crop){let c,a;Number.isInteger(this.crop_size)?(c=this.crop_size,a=this.crop_size):(c=this.crop_size.width,a=this.crop_size.height),n=await n.center_crop(c,a)}let l=[n.height,n.width];if(this.do_pad&&this.pad_size){let c=0,a=this.pad_size.width-n.width,t=0,e=this.pad_size.height-n.height;n=await n.pad([c,a,t,e])}const d=Float32Array.from(n.data);if(this.do_rescale)for(let c=0;cthis.preprocess(d)));return u.forEach(d=>d.pixel_values.dims=[1,...d.pixel_values.dims]),{pixel_values:cat(u.map(d=>d.pixel_values)),original_sizes:u.map(d=>d.original_size),reshaped_input_sizes:u.map(d=>d.reshaped_input_size)}}}class ConvNextFeatureExtractor extends ImageFeatureExtractor{}class ViTFeatureExtractor extends ImageFeatureExtractor{}class MobileViTFeatureExtractor extends ImageFeatureExtractor{}class DeiTFeatureExtractor extends ImageFeatureExtractor{}class BeitFeatureExtractor extends ImageFeatureExtractor{}class DonutFeatureExtractor extends ImageFeatureExtractor{}class DetrFeatureExtractor extends ImageFeatureExtractor{async _call(n){const o=await super._call(n),u=[o.pixel_values.dims[0],64,64],l=new Tensor("int64",new BigInt64Array(u.reduce((d,s)=>d*s)).fill(1n),u);return{...o,pixel_mask:l}}post_process_object_detection(...n){return post_process_object_detection(...n)}remove_low_and_no_objects(n,o,u,l){let d=[],s=[],p=[];for(let f=0;fu&&(d.push(a),s.push(r),p.push(t))}return[d,s,p]}check_segment_validity(n,o,u,l=.5,d=.8){let s=[],p=0,f=0;for(let a=0;a=l&&++f;let c=p>0&&f>0;return c&&(c=p/f>d),[c,s]}compute_segments(n,o,u,l,d,s=null,p=null){let[f,c]=p??n[0].dims,a=new Tensor("int32",new Int32Array(f*c),[f,c]),t=[];if(p!==null)for(let h=0;hr[m]&&(e[m]=h,r[m]=n[h].data[m])}let i=0;for(let h=0;hBigInt(Math.round(f)))),s);return{pixel_values:u,original_sizes:l,reshaped_input_sizes:d,input_points:p}}post_process_masks(n,o,u,{mask_threshold:l=0,binarize:d=!0,pad_size:s=null}={}){let p=[];s=s??this.pad_size;let f=[s.height,s.width];for(let c=0;cb>l),m.dims)),m.dims=[1,...m.dims],r.push(m)}let i=cat(r);p.push(i)}return p}}class WhisperFeatureExtractor extends FeatureExtractor{constructor(n){var o;super(n),(o=this.config).mel_filters??(o.mel_filters=getMelFilters(this.config.sampling_rate,this.config.n_fft,this.config.feature_size))}calcOffset(n,o){return Math.abs((n+o)%(2*o)-o)}padReflect(n,o,u){const l=new Float32Array(n.length+o+u),d=n.length-1;for(let s=0;s>1;++T){const S=(T+1-u)**2/2,A=Math.sqrt(m**2+b**2)**S,O=S*Math.atan2(b,m);let v=2*T;c[v]=A*Math.cos(O),c[v+1]=A*Math.sin(O),a[v]=c[v],a[v+1]=-c[v+1]}const y=c.subarray(l,d),w=new FFT(s>>1);w.transform(r,a);for(let T=0;T>1,F=S[M]*o[M];t[O]=F*y[O],t[v]=F*y[v]}w.transform(i,t);for(let O=0;Ol?s-l:0,c=s>1,c=new Float32Array(p*f);for(let m=0;mthis.config.n_samples&&console.warn("Attempting to extract features for audio longer than 30 seconds. If using a pipeline to extract transcript from a long audio clip, remember to specify `chunk_length_s` and/or `stride_length_s`.");let o=n.slice(0,this.config.n_samples),u=this._extract_fbank_features(o);return{input_features:new Tensor("float32",u.data,[1,...u.dims])}}}class Wav2Vec2FeatureExtractor extends FeatureExtractor{_zero_mean_unit_var_norm(n){const u=n.reduce((d,s)=>d+s,0)/n.length,l=n.reduce((d,s)=>d+(s-u)**2,0)/n.length;return n.map(d=>(d-u)/Math.sqrt(l+1e-7))}async _call(n){var l;if(!(n instanceof Float32Array||n instanceof Float64Array))throw new Error(`Wav2Vec2FeatureExtractor expects input to be a Float32Array or a Float64Array, but got ${((l=n==null?void 0:n.constructor)==null?void 0:l.name)??typeof n} instead.If using the feature extractor directly, remember to use \`read_audio(url, sampling_rate)\` to obtain the raw audio data of the file/url.`);n instanceof Float64Array&&(n=new Float32Array(n));let o=n;this.config.do_normalize&&(o=this._zero_mean_unit_var_norm(o));const u=[1,o.length];return{input_values:new Tensor("float32",o,u),attention_mask:new Tensor("int64",new BigInt64Array(o.length).fill(1n),u)}}}class SpeechT5FeatureExtractor extends FeatureExtractor{}class Processor extends Callable{constructor(n){super(),this.feature_extractor=n}async _call(n,...o){return await this.feature_extractor(n)}}class SamProcessor extends Processor{async _call(n,o){return await this.feature_extractor(n,o)}post_process_masks(...n){return this.feature_extractor.post_process_masks(...n)}}class WhisperProcessor extends Processor{async _call(n){return await this.feature_extractor(n)}}class Wav2Vec2ProcessorWithLM extends Processor{async _call(n){return await this.feature_extractor(n)}}class SpeechT5Processor extends Processor{async _call(n){return await this.feature_extractor(n)}}class AutoProcessor{static async from_pretrained(n,{progress_callback:o=null,config:u=null,cache_dir:l=null,local_files_only:d=!1,revision:s="main"}={}){let p=u??await getModelJSON(n,"preprocessor_config.json",!0,{progress_callback:o,config:u,cache_dir:l,local_files_only:d,revision:s}),f=p.feature_extractor_type??p.image_processor_type,c=this.FEATURE_EXTRACTOR_CLASS_MAPPING[f];if(!c)if(p.size!==void 0)console.warn(`Feature extractor type "${f}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),c=ImageFeatureExtractor;else throw new Error(`Unknown Feature Extractor type: ${f}`);let a=this.PROCESSOR_CLASS_MAPPING[p.processor_class]??Processor,t=new c(p);return new a(t)}}le(AutoProcessor,"FEATURE_EXTRACTOR_CLASS_MAPPING",{WhisperFeatureExtractor,ViTFeatureExtractor,MobileViTFeatureExtractor,ConvNextFeatureExtractor,BeitFeatureExtractor,DeiTFeatureExtractor,DetrFeatureExtractor,YolosFeatureExtractor,DonutFeatureExtractor,SamImageProcessor,Wav2Vec2FeatureExtractor,SpeechT5FeatureExtractor}),le(AutoProcessor,"PROCESSOR_CLASS_MAPPING",{WhisperProcessor,Wav2Vec2ProcessorWithLM,SamProcessor,SpeechT5Processor});async function prepareImages(_){return Array.isArray(_)||(_=[_]),_=await Promise.all(_.map(n=>RawImage.read(n))),_}class Pipeline extends Callable{constructor({task:n,model:o,tokenizer:u=null,processor:l=null}){super(),this.task=n,this.model=o,this.tokenizer=u,this.processor=l}async dispose(){await this.model.dispose()}async _call(n,...o){let u=this.tokenizer(n,{padding:!0,truncation:!0}),l=await this.model(u);return[u,l]}}class TextClassificationPipeline extends Pipeline{async _call(n,{topk:o=1}={}){let u=this.model.config.problem_type==="multi_label_classification"?f=>f.sigmoid().data:f=>softmax(f.data),[l,d]=await super._call(n),s=this.model.config.id2label,p=[];for(let f of d.logits){let c=u(f),t=getTopItems(c,o).map(function(e){return{label:s[e[0]],score:e[1]}});o===1?p.push(...t):p.push(t)}return Array.isArray(n)||o===1?p:p[0]}}class TokenClassificationPipeline extends Pipeline{async _call(n,{ignore_labels:o=["O"]}={}){let u=Array.isArray(n);u||(n=[n]);let l=this.tokenizer,[d,s]=await super._call(n),p=s.logits,f=this.model.config.id2label,c=[];for(let a=0;a[r,i]).filter(r=>r[1]>c),t=Array.from(softmax(d.end_logits[p].data)).map((r,i)=>[r,i]).filter(r=>r[1]>c),e=product(a,t).filter(r=>r[0][1]<=r[1][1]).map(r=>[r[0][1],r[1][1],r[0][0]*r[1][0]]).sort((r,i)=>i[2]-r[2]);for(let r=0;r{let i=[...f];return i[c]=r[0],{score:r[1],token:r[0],token_str:d.model.vocab[r[0]],sequence:d.decode(i,{skip_special_tokens:!0})}}))}return Array.isArray(n)?s:s[0]}}class Text2TextGenerationPipeline extends Pipeline{constructor(){super(...arguments);le(this,"_key",null)}async _call(o,u={}){Array.isArray(o)||(o=[o]),this.model.config.prefix&&(o=o.map(c=>this.model.config.prefix+c));let l=this.model.config.task_specific_params;l&&l[this.task]&&l[this.task].prefix&&(o=o.map(c=>l[this.task].prefix+c));let d={padding:!0,truncation:!0},s;this instanceof TranslationPipeline&&"_build_translation_inputs"in this.tokenizer?s=this.tokenizer._build_translation_inputs(o,d,u).input_ids:s=this.tokenizer(o,d).input_ids;let p=await this.model.generate(s,u),f=this.tokenizer.batch_decode(p,{skip_special_tokens:!0});return this._key!==null&&(f=f.map(c=>this._key===null?c:{[this._key]:c})),f}}class SummarizationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);le(this,"_key","summary_text")}}class TranslationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);le(this,"_key","translation_text")}}class TextGenerationPipeline extends Pipeline{async _call(n,o={}){let u=typeof n=="string"||n instanceof String;u&&(n=[n]),this.tokenizer.padding_side="left";let l=this.tokenizer(n,{padding:!0,truncation:!0}),d=l.input_ids,s=l.attention_mask,p=await this.model.generate(d,o,null,{inputs_attention_mask:s});const f=this.tokenizer.batch_decode(p,{skip_special_tokens:!0}),c=Array.from({length:n.length},a=>[]);for(let a=0;a[o.toLowerCase(),u])),this.entailment_id=this.label2id.entailment,this.entailment_id===void 0&&(console.warn("Could not find 'entailment' in label2id mapping. Using 2 as entailment_id."),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,this.contradiction_id===void 0&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(n,o,{hypothesis_template:u="This example is {}.",multi_label:l=!1}={}){let d=Array.isArray(n);d||(n=[n]),Array.isArray(o)||(o=[o]);let s=o.map(c=>u.replace("{}",c)),p=l||o.length===1,f=[];for(let c of n){let a=[];for(let r of s){let i=this.tokenizer(c,{text_pair:r,padding:!0,truncation:!0}),h=await this.model(i);p?a.push([h.logits.data[this.contradiction_id],h.logits.data[this.entailment_id]]):a.push(h.logits.data[this.entailment_id])}let t;p?t=a.map(r=>softmax(r)[1]):t=softmax(a);let e=t.map((r,i)=>[r,i]).sort((r,i)=>i[0]-r[0]);f.push({sequence:c,labels:e.map(r=>o[r[1]]),scores:e.map(r=>r[0])})}return d?f:f[0]}}class FeatureExtractionPipeline extends Pipeline{async _call(n,{pooling:o="none",normalize:u=!1}={}){let[l,d]=await super._call(n),s=d.last_hidden_state??d.logits;if(o!=="none")if(o==="mean")s=mean_pooling(s,l.attention_mask);else throw Error(`Pooling method '${o}' not supported.`);return u&&(s=s.normalize(2,-1)),s}}class AudioClassificationPipeline extends Pipeline{constructor(n){super(n)}async _preprocess(n,o){return isString(n)&&(n=await read_audio(n,o)),n}async _call(n,{topk:o=5}={}){let u=!Array.isArray(n);u&&(n=[n]);const l=this.model.config.id2label,d=this.processor.feature_extractor.config.sampling_rate;let s=[];for(let p of n){p=await this._preprocess(p,d);const f=await this.processor(p),a=(await this.model(f)).logits[0];let e=getTopItems(softmax(a.data),o).map(function(r){return{label:l[r[0]],score:r[1]}});o===1?s.push(...e):s.push(e)}return!u||o===1?s:s[0]}}class AutomaticSpeechRecognitionPipeline extends Pipeline{constructor(n){super(n)}async _preprocess(n,o){return isString(n)&&(n=await read_audio(n,o)),n}async _call(n,o={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(n,o);case"wav2vec2":return this._call_wav2vec2(n,o);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(n,o={}){o.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),o.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');let u=!Array.isArray(n);u&&(n=[n]);const l=this.processor.feature_extractor.config.sampling_rate;let d=[];for(let s of n){s=await this._preprocess(s,l);const p=await this.processor(s),c=(await this.model(p)).logits[0],a=[];for(let e of c)a.push(max(e.data)[1]);const t=this.tokenizer.decode(a);d.push({text:t})}return u?d[0]:d}async _call_whisper(n,o={}){let u=o.return_timestamps??!1,l=o.chunk_length_s??0,d=o.stride_length_s??null,s=o.chunk_callback??null,p=o.force_full_sequences??!1;u==="word"&&(o.return_token_timestamps=!0);let f=pop(o,"language",null),c=pop(o,"task",null);if(f||c||u){if(o.forced_decoder_ids)throw new Error("Cannot specify `language`/`task`/`return_timestamps` and `forced_decoder_ids` at the same time.");let h=this.tokenizer.get_decoder_prompt_ids({language:f,task:c,no_timestamps:!u});h.length>0&&(o.forced_decoder_ids=h)}let a=!Array.isArray(n);a&&(n=[n]);const t=this.processor.feature_extractor.config.sampling_rate,e=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,r=this.processor.feature_extractor.config.hop_length;let i=[];for(let h of n){h=await this._preprocess(h,t);let g=[];if(l>0){if(d===null)d=l/6;else if(l<=d)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const y=t*l,w=t*d,T=y-2*w;let S=0;for(;S=h.length;g.push({stride:[A.length,v?0:w,M?0:w],input_features:O.input_features,is_last:M}),S+=T}}else g=[{stride:[h.length,0,0],input_features:(await this.processor(h)).input_features,is_last:!0}];for(let y of g){o.num_frames=Math.floor(y.stride[0]/r);let w=await this.model.generate(y.input_features,o);u==="word"?(y.tokens=w.sequences[0],y.token_timestamps=w.token_timestamps.tolist()[0].map(T=>round(T,2))):y.tokens=w[0],y.stride=y.stride.map(T=>T/t),s!==null&&s(y)}let[m,b]=this.tokenizer._decode_asr(g,{time_precision:e,return_timestamps:u,force_full_sequences:p});i.push({text:m,...b})}return a?i[0]:i}}class ImageToTextPipeline extends Pipeline{constructor(n){super(n)}async _call(n,o={}){let u=Array.isArray(n);n=await prepareImages(n);let{pixel_values:l}=await this.processor(n),d=[];for(let s of l){s.dims=[1,...s.dims];let p=await this.model.generate(s,o),f=this.tokenizer.batch_decode(p,{skip_special_tokens:!0}).map(c=>({generated_text:c.trim()}));d.push(f)}return u?d:d[0]}}class ImageClassificationPipeline extends Pipeline{constructor(n){super(n)}async _call(n,{topk:o=1}={}){let u=Array.isArray(n);n=await prepareImages(n);let{pixel_values:l}=await this.processor(n),d=await this.model({pixel_values:l}),s=this.model.config.id2label,p=[];for(let f of d.logits){let a=getTopItems(softmax(f.data),o).map(function(t){return{label:s[t[0]],score:t[1]}});o===1?p.push(...a):p.push(a)}return u||o===1?p:p[0]}}class ImageSegmentationPipeline extends Pipeline{constructor(n){super(n),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(n,{threshold:o=.5,mask_threshold:u=.5,overlap_mask_area_threshold:l=.8,label_ids_to_fuse:d=null,target_sizes:s=null,subtask:p=null}={}){if(Array.isArray(n)&&n.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");n=await prepareImages(n);let c=n.map(h=>[h.height,h.width]),{pixel_values:a,pixel_mask:t}=await this.processor(n),e=await this.model({pixel_values:a,pixel_mask:t}),r=null;if(p!==null)r=this.subtasks_mapping[p];else for(let[h,g]of Object.entries(this.subtasks_mapping))if(g in this.processor.feature_extractor){r=this.processor.feature_extractor[g].bind(this.processor.feature_extractor),p=h;break}let i=[];if(p==="panoptic"||p==="instance"){let h=r(e,o,u,l,d,s??c)[0],g=h.segmentation,m=this.model.config.id2label;for(let b of h.segments_info){let y=new Uint8ClampedArray(g.data.length);for(let T=0;Tu.replace("{}",a)),s=this.tokenizer(d,{padding:!0,truncation:!0}),{pixel_values:p}=await this.processor(n),f=await this.model({...s,pixel_values:p}),c=[];for(let a of f.logits_per_image){let t=softmax(a.data);c.push([...t].map((e,r)=>({score:e,label:o[r]})))}return l?c:c[0]}}class ObjectDetectionPipeline extends Pipeline{constructor(n){super(n)}async _call(n,{threshold:o=.9,percentage:u=!1}={}){let l=Array.isArray(n);if(l&&n.length!==1)throw Error("Object detection pipeline currently only supports a batch size of 1.");n=await prepareImages(n);let d=u?null:n.map(e=>[e.height,e.width]),{pixel_values:s,pixel_mask:p}=await this.processor(n),f=await this.model({pixel_values:s,pixel_mask:p}),c=this.processor.feature_extractor.post_process_object_detection(f,o,d),a=this.model.config.id2label;const t=c.map(e=>e.boxes.map((r,i)=>({score:e.scores[i],label:a[e.classes[i]],box:this._get_bounding_box(r,!u)})));return l?t:t[0]}_get_bounding_box(n,o){o&&(n=n.map(p=>p|0));const[u,l,d,s]=n;return{xmin:u,ymin:l,xmax:d,ymax:s}}}class DocumentQuestionAnsweringPipeline extends Pipeline{constructor(n){super(n)}async _call(n,o,u={}){n=(await prepareImages(n))[0];const{pixel_values:l}=await this.processor(n),d=`${o}`,s=this.tokenizer(d,{add_special_tokens:!1,padding:!0,truncation:!0}).input_ids,p=await this.model.generate(l,{...u,decoder_input_ids:s,max_length:this.model.config.decoder.max_position_embeddings}),c=this.tokenizer.batch_decode(p)[0].match(/(.*?)<\/s_answer>/);let a=null;return c&&c.length>=2&&(a=c[1].trim()),[{answer:a}]}}class TextToAudioPipeline extends Pipeline{constructor(o){super(o);le(this,"DEFAULT_VOCODER_ID","Xenova/speecht5_hifigan");this.vocoder=o.vocoder??null}async _call(o,{speaker_embeddings:u=null}={}){if(this.vocoder||(console.log("No vocoder specified, using default HifiGan vocoder."),this.vocoder=await AutoModel.from_pretrained(this.DEFAULT_VOCODER_ID,{quantized:!1})),(typeof u=="string"||u instanceof URL)&&(u=new Float32Array(await(await fetch(u)).arrayBuffer())),u instanceof Float32Array)u=new Tensor("float32",u,[1,u.length]);else if(!(u instanceof Tensor))throw new Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");const{input_ids:l}=this.tokenizer(o,{padding:!0,truncation:!0}),{waveform:d}=await this.model.generate_speech(l,u,{vocoder:this.vocoder}),s=this.processor.feature_extractor.config.sampling_rate;return{audio:d.data,sampling_rate:s}}}const SUPPORTED_TASKS={"text-classification":{tokenizer:AutoTokenizer,pipeline:TextClassificationPipeline,model:AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:AutoTokenizer,pipeline:TokenClassificationPipeline,model:AutoModelForTokenClassification,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:AutoTokenizer,pipeline:QuestionAnsweringPipeline,model:AutoModelForQuestionAnswering,default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:AutoTokenizer,pipeline:FillMaskPipeline,model:AutoModelForMaskedLM,default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:AutoTokenizer,pipeline:SummarizationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:AutoTokenizer,pipeline:TranslationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:AutoTokenizer,pipeline:Text2TextGenerationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:AutoTokenizer,pipeline:TextGenerationPipeline,model:AutoModelForCausalLM,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotClassificationPipeline,model:AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:AudioClassificationPipeline,model:AutoModelForAudioClassification,processor:AutoProcessor,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"automatic-speech-recognition":{tokenizer:AutoTokenizer,pipeline:AutomaticSpeechRecognitionPipeline,model:[AutoModelForSpeechSeq2Seq,AutoModelForCTC],processor:AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:AutoTokenizer,pipeline:TextToAudioPipeline,model:[AutoModelForTextToSpectrogram],processor:AutoProcessor,default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:AutoTokenizer,pipeline:ImageToTextPipeline,model:AutoModelForVision2Seq,processor:AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:ImageClassificationPipeline,model:AutoModelForImageClassification,processor:AutoProcessor,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:ImageSegmentationPipeline,model:AutoModelForImageSegmentation,processor:AutoProcessor,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotImageClassificationPipeline,model:AutoModel,processor:AutoProcessor,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:ObjectDetectionPipeline,model:AutoModelForObjectDetection,processor:AutoProcessor,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"document-question-answering":{tokenizer:AutoTokenizer,pipeline:DocumentQuestionAnsweringPipeline,model:AutoModelForDocumentQuestionAnswering,processor:AutoProcessor,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"feature-extraction":{tokenizer:AutoTokenizer,pipeline:FeatureExtractionPipeline,model:AutoModel,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"}},TASK_ALIASES={"sentiment-analysis":"text-classification",ner:"token-classification",vqa:"visual-question-answering",asr:"automatic-speech-recognition","text-to-speech":"text-to-audio",embeddings:"feature-extraction"};async function pipeline(_,n=null,{quantized:o=!0,progress_callback:u=null,config:l=null,cache_dir:d=null,local_files_only:s=!1,revision:p="main"}={}){_=TASK_ALIASES[_]??_;let f=SUPPORTED_TASKS[_.split("_",1)[0]];if(!f)throw Error(`Unsupported pipeline: ${_}. Must be one of [${Object.keys(SUPPORTED_TASKS)}]`);n||(n=f.default.model,console.log(`No model specified. Using default model: "${n}".`));let c={quantized:o,progress_callback:u,config:l,cache_dir:d,local_files_only:s,revision:p};const a=new Map([["tokenizer",f.tokenizer],["model",f.model],["processor",f.processor]]);let t=await loadItems(a,n,c);t.task=_,dispatchCallback(u,{status:"ready",task:_,model:n});let e=f.pipeline;return new e(t)}async function loadItems(_,n,o){const u=Object.create(null),l=[];for(let[d,s]of _.entries()){if(!s)continue;let p;Array.isArray(s)?p=new Promise(async(f,c)=>{let a;for(let t of s)try{f(await t.from_pretrained(n,o));return}catch(e){a=e}c(a)}):p=s.from_pretrained(n,o),u[d]=p,l.push(p)}await Promise.all(l);for(let[d,s]of Object.entries(u))u[d]=await s;return u}env.allowLocalModels=!1;class PipelineFactory{constructor(n,o,u){this.tokenizer=n,this.model=o,this.quantized=u}static async getInstance(n=null){return this.instance===null&&(this.instance=pipeline(this.task,this.model,{quantized:this.quantized,progress_callback:n,revision:this.model.includes("/whisper-medium")?"no_attentions":"main"})),this.instance}}le(PipelineFactory,"task",null),le(PipelineFactory,"model",null),le(PipelineFactory,"quantized",null),le(PipelineFactory,"instance",null),self.addEventListener("message",async _=>{const n=_.data;let o=await transcribe(n.audio,n.model,n.multilingual,n.quantized,n.subtask,n.language);o!==null&&self.postMessage({status:"complete",task:"automatic-speech-recognition",data:o})});class AutomaticSpeechRecognitionPipelineFactory extends PipelineFactory{}le(AutomaticSpeechRecognitionPipelineFactory,"task","automatic-speech-recognition"),le(AutomaticSpeechRecognitionPipelineFactory,"model",null),le(AutomaticSpeechRecognitionPipelineFactory,"quantized",null);const transcribe=async(_,n,o,u,l,d)=>{const s=n.startsWith("distil-whisper/");let p=n;!s&&!o&&(p+=".en");const f=AutomaticSpeechRecognitionPipelineFactory;(f.model!==p||f.quantized!==u)&&(f.model=p,f.quantized=u,f.instance!==null&&((await f.getInstance()).dispose(),f.instance=null));let c=await f.getInstance(h=>{self.postMessage(h)});const a=c.processor.feature_extractor.config.chunk_length/c.model.config.max_source_positions;let t=[{tokens:[],finalised:!1}];function e(h){let g=t[t.length-1];Object.assign(g,h),g.finalised=!0,h.is_last||t.push({tokens:[],finalised:!1})}function r(h){let g=t[t.length-1];g.tokens=[...h[0].output_token_ids];let m=c.tokenizer._decode_asr(t,{time_precision:a,return_timestamps:!0,force_full_sequences:!1});self.postMessage({status:"update",task:"automatic-speech-recognition",data:m})}return await c(_,{top_k:0,do_sample:!1,chunk_length_s:s?20:30,stride_length_s:s?3:5,language:d,task:l,return_timestamps:!0,force_full_sequences:!1,callback_function:r,chunk_callback:e}).catch(h=>(self.postMessage({status:"error",task:"automatic-speech-recognition",data:h}),null))}})();