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expected");r.type=l.onnx.TypeProto.fromObject(e.type)}return e.docString!=null&&(r.docString=String(e.docString)),r},n.toObject=function(e,r){r||(r={});var o={};return r.defaults&&(o.name="",o.type=null,o.docString=""),e.name!=null&&e.hasOwnProperty("name")&&(o.name=e.name),e.type!=null&&e.hasOwnProperty("type")&&(o.type=l.onnx.TypeProto.toObject(e.type,r)),e.docString!=null&&e.hasOwnProperty("docString")&&(o.docString=e.docString),o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n}(),d.NodeProto=function(){function n(e){if(this.input=[],this.output=[],this.attribute=[],e)for(var r=Object.keys(e),o=0;o>>3){case 1:p.input&&p.input.length||(p.input=[]),p.input.push(e.string());break;case 2:p.output&&p.output.length||(p.output=[]),p.output.push(e.string());break;case 3:p.name=e.string();break;case 4:p.opType=e.string();break;case 7:p.domain=e.string();break;case 5:p.attribute&&p.attribute.length||(p.attribute=[]),p.attribute.push(l.onnx.AttributeProto.decode(e,e.uint32()));break;case 6:p.docString=e.string();break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.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:p.irVersion=e.int64();break;case 8:p.opsetImport&&p.opsetImport.length||(p.opsetImport=[]),p.opsetImport.push(l.onnx.OperatorSetIdProto.decode(e,e.uint32()));break;case 2:p.producerName=e.string();break;case 3:p.producerVersion=e.string();break;case 4:p.domain=e.string();break;case 5:p.modelVersion=e.int64();break;case 6:p.docString=e.string();break;case 7:p.graph=l.onnx.GraphProto.decode(e,e.uint32());break;case 14:p.metadataProps&&p.metadataProps.length||(p.metadataProps=[]),p.metadataProps.push(l.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.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 o=0;o>>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=l.onnx.GraphProto.fromObject(e.graph)}if(e.metadataProps){if(!Array.isArray(e.metadataProps))throw TypeError(".onnx.ModelProto.metadataProps: array expected");for(r.metadataProps=[],o=0;o>>0,e.irVersion.high>>>0).toNumber():e.irVersion),e.producerName!=null&&e.hasOwnProperty("producerName")&&(o.producerName=e.producerName),e.producerVersion!=null&&e.hasOwnProperty("producerVersion")&&(o.producerVersion=e.producerVersion),e.domain!=null&&e.hasOwnProperty("domain")&&(o.domain=e.domain),e.modelVersion!=null&&e.hasOwnProperty("modelVersion")&&(typeof e.modelVersion=="number"?o.modelVersion=r.longs===String?String(e.modelVersion):e.modelVersion:o.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")&&(o.docString=e.docString),e.graph!=null&&e.hasOwnProperty("graph")&&(o.graph=l.onnx.GraphProto.toObject(e.graph,r)),e.opsetImport&&e.opsetImport.length){o.opsetImport=[];for(var g=0;g>>3){case 1:p.key=e.string();break;case 2:p.value=e.string();break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.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},n.fromObject=function(e){if(e instanceof l.onnx.StringStringEntryProto)return e;var r=new l.onnx.StringStringEntryProto;return e.key!=null&&(r.key=String(e.key)),e.value!=null&&(r.value=String(e.value)),r},n.toObject=function(e,r){r||(r={});var o={};return r.defaults&&(o.key="",o.value=""),e.key!=null&&e.hasOwnProperty("key")&&(o.key=e.key),e.value!=null&&e.hasOwnProperty("value")&&(o.value=e.value),o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n}(),d.TensorAnnotation=function(){function n(e){if(this.quantParameterTensorNames=[],e)for(var r=Object.keys(e),o=0;o>>3){case 1:p.tensorName=e.string();break;case 2:p.quantParameterTensorNames&&p.quantParameterTensorNames.length||(p.quantParameterTensorNames=[]),p.quantParameterTensorNames.push(l.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.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:p.node&&p.node.length||(p.node=[]),p.node.push(l.onnx.NodeProto.decode(e,e.uint32()));break;case 2:p.name=e.string();break;case 5:p.initializer&&p.initializer.length||(p.initializer=[]),p.initializer.push(l.onnx.TensorProto.decode(e,e.uint32()));break;case 10:p.docString=e.string();break;case 11:p.input&&p.input.length||(p.input=[]),p.input.push(l.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 12:p.output&&p.output.length||(p.output=[]),p.output.push(l.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 13:p.valueInfo&&p.valueInfo.length||(p.valueInfo=[]),p.valueInfo.push(l.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 14:p.quantizationAnnotation&&p.quantizationAnnotation.length||(p.quantizationAnnotation=[]),p.quantizationAnnotation.push(l.onnx.TensorAnnotation.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.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(p.dims&&p.dims.length||(p.dims=[]),(7&g)==2)for(var _=e.uint32()+e.pos;e.pos<_;)p.dims.push(e.int64());else p.dims.push(e.int64());break;case 2:p.dataType=e.int32();break;case 3:p.segment=l.onnx.TensorProto.Segment.decode(e,e.uint32());break;case 4:if(p.floatData&&p.floatData.length||(p.floatData=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.floatData.push(e.float());else p.floatData.push(e.float());break;case 5:if(p.int32Data&&p.int32Data.length||(p.int32Data=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.int32Data.push(e.int32());else p.int32Data.push(e.int32());break;case 6:p.stringData&&p.stringData.length||(p.stringData=[]),p.stringData.push(e.bytes());break;case 7:if(p.int64Data&&p.int64Data.length||(p.int64Data=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.int64Data.push(e.int64());else p.int64Data.push(e.int64());break;case 8:p.name=e.string();break;case 12:p.docString=e.string();break;case 9:p.rawData=e.bytes();break;case 13:p.externalData&&p.externalData.length||(p.externalData=[]),p.externalData.push(l.onnx.StringStringEntryProto.decode(e,e.uint32()));break;case 14:p.dataLocation=e.int32();break;case 10:if(p.doubleData&&p.doubleData.length||(p.doubleData=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.doubleData.push(e.double());else p.doubleData.push(e.double());break;case 11:if(p.uint64Data&&p.uint64Data.length||(p.uint64Data=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.uint64Data.push(e.uint64());else p.uint64Data.push(e.uint64());break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.dims!=null&&e.hasOwnProperty("dims")){if(!Array.isArray(e.dims))return"dims: array expected";for(var r=0;r>>0,e.dims[o].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=l.onnx.TensorProto.Segment.fromObject(e.segment)}if(e.floatData){if(!Array.isArray(e.floatData))throw TypeError(".onnx.TensorProto.floatData: array expected");for(r.floatData=[],o=0;o>>0,e.int64Data[o].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=[],o=0;o>>0,e.uint64Data[o].high>>>0).toNumber(!0))}return r},n.toObject=function(e,r){r||(r={});var o={};if((r.arrays||r.defaults)&&(o.dims=[],o.floatData=[],o.int32Data=[],o.stringData=[],o.int64Data=[],o.doubleData=[],o.uint64Data=[],o.externalData=[]),r.defaults&&(o.dataType=0,o.segment=null,o.name="",r.bytes===String?o.rawData="":(o.rawData=[],r.bytes!==Array&&(o.rawData=c.newBuffer(o.rawData))),o.docString="",o.dataLocation=r.enums===String?"DEFAULT":0),e.dims&&e.dims.length){o.dims=[];for(var p=0;p>>0,e.dims[p].high>>>0).toNumber():e.dims[p]}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&(o.dataType=e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&(o.segment=l.onnx.TensorProto.Segment.toObject(e.segment,r)),e.floatData&&e.floatData.length)for(o.floatData=[],p=0;p>>0,e.int64Data[p].high>>>0).toNumber():e.int64Data[p];if(e.name!=null&&e.hasOwnProperty("name")&&(o.name=e.name),e.rawData!=null&&e.hasOwnProperty("rawData")&&(o.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(o.doubleData=[],p=0;p>>0,e.uint64Data[p].high>>>0).toNumber(!0):e.uint64Data[p];if(e.docString!=null&&e.hasOwnProperty("docString")&&(o.docString=e.docString),e.externalData&&e.externalData.length)for(o.externalData=[],p=0;p>>3){case 1:g.begin=r.int64();break;case 2:g.end=r.int64();break;default:r.skipType(7&_)}}return g},e.decodeDelimited=function(r){return r instanceof h||(r=new h(r)),this.decode(r,r.uint32())},e.verify=function(r){return typeof r!="object"||r===null?"object expected":r.begin!=null&&r.hasOwnProperty("begin")&&!(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 l.onnx.TensorProto.Segment)return r;var o=new l.onnx.TensorProto.Segment;return r.begin!=null&&(c.Long?(o.begin=c.Long.fromValue(r.begin)).unsigned=!1:typeof r.begin=="string"?o.begin=parseInt(r.begin,10):typeof r.begin=="number"?o.begin=r.begin:typeof r.begin=="object"&&(o.begin=new c.LongBits(r.begin.low>>>0,r.begin.high>>>0).toNumber())),r.end!=null&&(c.Long?(o.end=c.Long.fromValue(r.end)).unsigned=!1:typeof r.end=="string"?o.end=parseInt(r.end,10):typeof r.end=="number"?o.end=r.end:typeof r.end=="object"&&(o.end=new c.LongBits(r.end.low>>>0,r.end.high>>>0).toNumber())),o},e.toObject=function(r,o){o||(o={});var p={};if(o.defaults){if(c.Long){var g=new c.Long(0,0,!1);p.begin=o.longs===String?g.toString():o.longs===Number?g.toNumber():g}else p.begin=o.longs===String?"0":0;c.Long?(g=new c.Long(0,0,!1),p.end=o.longs===String?g.toString():o.longs===Number?g.toNumber():g):p.end=o.longs===String?"0":0}return r.begin!=null&&r.hasOwnProperty("begin")&&(typeof r.begin=="number"?p.begin=o.longs===String?String(r.begin):r.begin:p.begin=o.longs===String?c.Long.prototype.toString.call(r.begin):o.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"?p.end=o.longs===String?String(r.end):r.end:p.end=o.longs===String?c.Long.prototype.toString.call(r.end):o.longs===Number?new c.LongBits(r.end.low>>>0,r.end.high>>>0).toNumber():r.end),p},e.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},e}(),n.DataLocation=function(){var e={},r=Object.create(e);return r[e[0]="DEFAULT"]=0,r[e[1]="EXTERNAL"]=1,r}(),n}(),d.TensorShapeProto=function(){function n(e){if(this.dim=[],e)for(var r=Object.keys(e),o=0;o>>3==1?(p.dim&&p.dim.length||(p.dim=[]),p.dim.push(l.onnx.TensorShapeProto.Dimension.decode(e,e.uint32()))):e.skipType(7&g)}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.dim!=null&&e.hasOwnProperty("dim")){if(!Array.isArray(e.dim))return"dim: array expected";for(var r=0;r>>3){case 1:_.dimValue=o.int64();break;case 2:_.dimParam=o.string();break;case 3:_.denotation=o.string();break;default:o.skipType(7&b)}}return _},e.decodeDelimited=function(o){return o instanceof h||(o=new h(o)),this.decode(o,o.uint32())},e.verify=function(o){if(typeof o!="object"||o===null)return"object expected";var p={};if(o.dimValue!=null&&o.hasOwnProperty("dimValue")&&(p.value=1,!(c.isInteger(o.dimValue)||o.dimValue&&c.isInteger(o.dimValue.low)&&c.isInteger(o.dimValue.high))))return"dimValue: integer|Long expected";if(o.dimParam!=null&&o.hasOwnProperty("dimParam")){if(p.value===1)return"value: multiple values";if(p.value=1,!c.isString(o.dimParam))return"dimParam: string expected"}return o.denotation!=null&&o.hasOwnProperty("denotation")&&!c.isString(o.denotation)?"denotation: string expected":null},e.fromObject=function(o){if(o instanceof l.onnx.TensorShapeProto.Dimension)return o;var p=new l.onnx.TensorShapeProto.Dimension;return o.dimValue!=null&&(c.Long?(p.dimValue=c.Long.fromValue(o.dimValue)).unsigned=!1:typeof o.dimValue=="string"?p.dimValue=parseInt(o.dimValue,10):typeof o.dimValue=="number"?p.dimValue=o.dimValue:typeof o.dimValue=="object"&&(p.dimValue=new c.LongBits(o.dimValue.low>>>0,o.dimValue.high>>>0).toNumber())),o.dimParam!=null&&(p.dimParam=String(o.dimParam)),o.denotation!=null&&(p.denotation=String(o.denotation)),p},e.toObject=function(o,p){p||(p={});var g={};return p.defaults&&(g.denotation=""),o.dimValue!=null&&o.hasOwnProperty("dimValue")&&(typeof o.dimValue=="number"?g.dimValue=p.longs===String?String(o.dimValue):o.dimValue:g.dimValue=p.longs===String?c.Long.prototype.toString.call(o.dimValue):p.longs===Number?new c.LongBits(o.dimValue.low>>>0,o.dimValue.high>>>0).toNumber():o.dimValue,p.oneofs&&(g.value="dimValue")),o.dimParam!=null&&o.hasOwnProperty("dimParam")&&(g.dimParam=o.dimParam,p.oneofs&&(g.value="dimParam")),o.denotation!=null&&o.hasOwnProperty("denotation")&&(g.denotation=o.denotation),g},e.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},e}(),n}(),d.TypeProto=function(){function n(r){if(r)for(var o=Object.keys(r),p=0;p>>3){case 1:g.tensorType=l.onnx.TypeProto.Tensor.decode(r,r.uint32());break;case 6:g.denotation=r.string();break;default:r.skipType(7&_)}}return g},n.decodeDelimited=function(r){return r instanceof h||(r=new h(r)),this.decode(r,r.uint32())},n.verify=function(r){if(typeof r!="object"||r===null)return"object expected";if(r.tensorType!=null&&r.hasOwnProperty("tensorType")){var o=l.onnx.TypeProto.Tensor.verify(r.tensorType);if(o)return"tensorType."+o}return r.denotation!=null&&r.hasOwnProperty("denotation")&&!c.isString(r.denotation)?"denotation: string expected":null},n.fromObject=function(r){if(r instanceof l.onnx.TypeProto)return r;var o=new l.onnx.TypeProto;if(r.tensorType!=null){if(typeof r.tensorType!="object")throw TypeError(".onnx.TypeProto.tensorType: object expected");o.tensorType=l.onnx.TypeProto.Tensor.fromObject(r.tensorType)}return r.denotation!=null&&(o.denotation=String(r.denotation)),o},n.toObject=function(r,o){o||(o={});var p={};return 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s.onnx.AttributeProto?e.map(a.decodeUtf8String):e}static getValueNoCheck(l){return l instanceof s.onnx.AttributeProto?this.getValueNoCheckFromOnnxFormat(l):this.getValueNoCheckFromOrtFormat(l)}static getValueNoCheckFromOnnxFormat(l){switch(l.type){case s.onnx.AttributeProto.AttributeType.FLOAT:return l.f;case s.onnx.AttributeProto.AttributeType.INT:return l.i;case s.onnx.AttributeProto.AttributeType.STRING:return l.s;case s.onnx.AttributeProto.AttributeType.TENSOR:return l.t;case s.onnx.AttributeProto.AttributeType.GRAPH:return l.g;case s.onnx.AttributeProto.AttributeType.FLOATS:return l.floats;case s.onnx.AttributeProto.AttributeType.INTS:return l.ints;case s.onnx.AttributeProto.AttributeType.STRINGS:return l.strings;case s.onnx.AttributeProto.AttributeType.TENSORS:return l.tensors;case s.onnx.AttributeProto.AttributeType.GRAPHS:return l.graphs;default:throw new Error(`unsupported attribute type: ${s.onnx.AttributeProto.AttributeType[l.type]}`)}}static getValueNoCheckFromOrtFormat(l){switch(l.type()){case h.AttributeType.FLOAT:return l.f();case h.AttributeType.INT:return l.i();case h.AttributeType.STRING:return l.s();case h.AttributeType.TENSOR:return l.t();case h.AttributeType.GRAPH:return l.g();case h.AttributeType.FLOATS:return l.floatsArray();case h.AttributeType.INTS:{const n=[];for(let e=0;e{Object.defineProperty(t,"__esModule",{value:!0}),t.resolveBackend=t.backend=void 0;const s=i(5038),u=new Map;async function d(a){const h=t.backend;if(h[a]!==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"}(h[a])){const f=h[a];let c=f.initialize();if(typeof c=="object"&&"then"in c&&(c=await c),c)return u.set(a,f),f}}t.backend={webgl:new s.WebGLBackend},t.resolveBackend=async function a(h){if(!h)return a(["webgl"]);{const f=typeof h=="string"?[h]:h;for(const c of f){const l=u.get(c);if(l)return l;const n=await d(c);if(n)return n}}throw new Error("no available backend to use")}},5038:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.WebGLBackend=void 0;const s=i(1670),u=i(6231),d=i(6416),a=i(7305);t.WebGLBackend=class{get contextId(){return s.env.webgl.contextId}set contextId(h){s.env.webgl.contextId=h}get matmulMaxBatchSize(){return s.env.webgl.matmulMaxBatchSize}set matmulMaxBatchSize(h){s.env.webgl.matmulMaxBatchSize=h}get textureCacheMode(){return s.env.webgl.textureCacheMode}set textureCacheMode(h){s.env.webgl.textureCacheMode=h}get pack(){return s.env.webgl.pack}set pack(h){s.env.webgl.pack=h}get async(){return s.env.webgl.async}set async(h){s.env.webgl.async=h}initialize(){try{return this.glContext=(0,a.createWebGLContext)(this.contextId),typeof this.matmulMaxBatchSize!="number"&&(this.matmulMaxBatchSize=16),typeof this.textureCacheMode!="string"&&(this.textureCacheMode="full"),typeof this.pack!="boolean"&&(this.pack=!1),typeof this.async!="boolean"&&(this.async=!1),u.Logger.setWithEnv(s.env),u.Logger.verbose("WebGLBackend",`Created WebGLContext: ${typeof this.glContext} with matmulMaxBatchSize: ${this.matmulMaxBatchSize}; textureCacheMode: ${this.textureCacheMode}; pack: ${this.pack}; async: ${this.async}.`),!0}catch(h){return u.Logger.warning("WebGLBackend",`Unable to initialize WebGLBackend. ${h}`),!1}}createSessionHandler(h){return new d.WebGLSessionHandler(this,h)}dispose(){this.glContext.dispose()}}},5107:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.CoordsGlslLib=void 0;const s=i(2517),u=i(8520),d=i(5060),a=i(7859),h=i(9390);class f extends u.GlslLib{constructor(l){super(l)}getFunctions(){return 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 u.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 u.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 l=this.context.outputTextureLayout;return l.isPacked?this.getPackedOutputSamplingSnippet(l):this.getUnpackedOutputSamplingSnippet(l)}getPackedOutputSamplingSnippet(l){const n=l.unpackedShape,e=[l.width,l.height],r={},o="getOutputCoords";switch(n.length){case 0:r[o]=this.getOutputScalarCoords();break;case 1:r[o]=this.getOutputPacked1DCoords(n,e);break;case 2:r[o]=this.getOutputPacked2DCoords(n,e);break;case 3:r[o]=this.getOutputPacked3DCoords(n,e);break;default:r[o]=this.getOutputPackedNDCoords(n,e)}const p=` + void setOutput(vec4 val) { + ${(0,d.getGlsl)(this.context.glContext.version).output} = val; + } + `;return r.floatTextureSetRGBA=new u.GlslLibRoutine(p),r}getUnpackedOutputSamplingSnippet(l){const n=l.unpackedShape,e=[l.width,l.height],r={},o="getOutputCoords";switch(n.length){case 0:r[o]=this.getOutputScalarCoords();break;case 1:r[o]=this.getOutputUnpacked1DCoords(n,e);break;case 2:r[o]=this.getOutputUnpacked2DCoords(n,e);break;case 3:r[o]=this.getOutputUnpacked3DCoords(n,e);break;case 4:r[o]=this.getOutputUnpacked4DCoords(n,e);break;case 5:r[o]=this.getOutputUnpacked5DCoords(n,e);break;case 6:r[o]=this.getOutputUnpacked6DCoords(n,e);break;default:throw new Error(`Unsupported output dimensionality: ${n.length}`)}const p=` + void setOutput(float val) { + ${(0,d.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0); + } + `;return r.floatTextureSetR=new u.GlslLibRoutine(p),r}getOutputScalarCoords(){return new u.GlslLibRoutine(` + int getOutputCoords() { + return 0; + } + `)}getOutputPacked1DCoords(l,n){const e=n;let r="";return e[0]===1?(r=` + int getOutputCoords() { + return 2 * int(TexCoords.y * ${e[1]}.0); + } + `,new u.GlslLibRoutine(r)):e[1]===1?(r=` + int getOutputCoords() { + return 2 * int(TexCoords.x * ${e[0]}.0); + } + `,new u.GlslLibRoutine(r)):(r=` + int getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${e[0]}, ${e[1]})); + return 2 * (resTexRC.y * ${e[0]} + resTexRC.x); + } + `,new u.GlslLibRoutine(r))}getOutputPacked2DCoords(l,n){let e="";if(s.ArrayUtil.arraysEqual(l,n))return e=` + ivec2 getOutputCoords() { + return 2 * ivec2(TexCoords.xy * vec2(${n[0]}, ${n[1]})); + } + `,new u.GlslLibRoutine(e);const r=n,o=Math.ceil(l[1]/2);return e=` + ivec2 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${r[0]}, ${r[1]})); + + int index = resTexRC.y * ${r[0]} + resTexRC.x; + + // reverse r and c order for packed texture + int r = imod(index, ${o}) * 2; + int c = 2 * (index / ${o}); + + return ivec2(r, c); + } + `,new u.GlslLibRoutine(e)}getOutputPacked3DCoords(l,n){const e=[n[0],n[1]],r=Math.ceil(l[2]/2),o=r*Math.ceil(l[1]/2),p=` + ivec3 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${e[0]}, ${e[1]})); + int index = resTexRC.y * ${e[0]} + resTexRC.x; + + int b = index / ${o}; + index -= b * ${o}; + + // 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 u.GlslLibRoutine(p)}getOutputPackedNDCoords(l,n){const e=[n[0],n[1]],r=Math.ceil(l[l.length-1]/2),o=r*Math.ceil(l[l.length-2]/2);let p=o,g="",_="b, r, c";for(let y=2;y=0;--_)o[_]=o[_+1]*l[_+1];const p=["r","c","d"],g=o.map((_,b)=>`int ${p[b]} = index / ${_}; ${b===o.length-1?`int ${p[b+1]} = index - ${p[b]} * ${_}`:`index -= ${p[b]} * ${_}`};`).join("");return e=` + ivec3 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${n[0]}, ${n[1]})); + int index = resTexRC.y * ${n[0]} + resTexRC.x; + ${g} + return ivec3(r, c, d); + } + `,new u.GlslLibRoutine(e)}getOutputUnpacked4DCoords(l,n){let e="";const r=l.length;let o=null;r<2&&(o=[]),o=new Array(r-1),o[r-2]=l[r-1];for(let _=r-3;_>=0;--_)o[_]=o[_+1]*l[_+1];const p=["r","c","d","d2"],g=o.map((_,b)=>`int ${p[b]} = index / ${_}; ${b===o.length-1?`int ${p[b+1]} = index - ${p[b]} * ${_}`:`index -= ${p[b]} * ${_}`};`).join("");return e=` + ivec4 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${n[0]}, ${n[1]})); + int index = resTexRC.y * ${n[0]} + resTexRC.x; + ${g} + return ivec4(r, c, d, d2); + } + `,new u.GlslLibRoutine(e)}getOutputUnpacked5DCoords(l,n){let e="";const r=l.length;let o=null;r<2&&(o=[]),o=new Array(r-1),o[r-2]=l[r-1];for(let _=r-3;_>=0;--_)o[_]=o[_+1]*l[_+1];const p=["r","c","d","d2","d3"],g=o.map((_,b)=>`int ${p[b]} = index / ${_}; ${b===o.length-1?`int ${p[b+1]} = index - ${p[b]} * ${_}`:`index -= ${p[b]} * ${_}`};`).join("");return e=` + ivec5 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${n[0]}, ${n[1]})); + int index = resTexRC.y * ${n[0]} + resTexRC.x; + ${g} + return ivec5(r, c, d, d2, d3); + } + `,new u.GlslLibRoutine(e)}getOutputUnpacked6DCoords(l,n){let e="";const r=l.length;let o=null;r<2&&(o=[]),o=new Array(r-1),o[r-2]=l[r-1];for(let _=r-3;_>=0;--_)o[_]=o[_+1]*l[_+1];const p=["r","c","d","d2","d3","d4"],g=o.map((_,b)=>`int ${p[b]} = index / ${_}; ${b===o.length-1?`int ${p[b+1]} = index - ${p[b]} * ${_}`:`index -= ${p[b]} * ${_}`};`).join("");return e=` + ivec6 getOutputCoords() { + ivec2 resTexRC = ivec2(TexCoords.xy * + vec2(${n[0]}, ${n[1]})); + int index = resTexRC.y * ${n[0]} + resTexRC.x; + ${g} + return ivec6(r, c, d, d2, d3, d4); + } + `,new u.GlslLibRoutine(e)}getCommonUtilFuncs(){const l={};let n="uvFromFlat";l[n]=new u.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); + } + `),n="packedUVfrom1D",l[n]=new u.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); + } + `),n="packedUVfrom2D",l[n]=new u.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); + } + `),n="packedUVfrom3D",l[n]=new u.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); + } + `),n="sampleTexture";const e=(0,d.getGlsl)(this.context.glContext.version);return l[n]=new u.GlslLibRoutine(` + float sampleTexture(sampler2D textureSampler, vec2 uv) { + return ${e.texture2D}(textureSampler, uv).r; + }`),l}getInputsSamplingSnippets(){const l={},n=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,r)=>{const o=this.context.inputTextureLayouts[r],p=(0,h.generateShaderFuncNameFromInputSamplerName)(e);o.isPacked?l[p]=this.getPackedSamplerFromInput(p,e,o):l[p]=this.getUnpackedSamplerFromInput(p,e,o);const g=(0,h.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(e);o.unpackedShape.length<=n.unpackedShape.length&&(o.isPacked?l[g]=this.getPackedSamplerAtOutputCoords(g,o,n,e):l[g]=this.getUnpackedSamplerAtOutputCoords(g,o,n,e))}),l}getPackedSamplerAtOutputCoords(l,n,e,r){const o=n.unpackedShape,p=e.unpackedShape,g=r,_=(0,h.generateShaderFuncNameFromInputSamplerName)(g),b=o.length,y=p.length,w=s.BroadcastUtil.getBroadcastDims(o,p),T=(0,h.getCoordsDataType)(y),S=y-b;let A;const P=(0,h.getGlChannels)();A=b===0?"":y<2&&w.length>=1?"coords = 0;":w.map(C=>`coords.${P[C+S]} = 0;`).join(` +`);let x="";x=y<2&&b>0?"coords":o.map((C,G)=>`coords.${P[G+S]}`).join(", ");let M="return outputValue;";const N=s.ShapeUtil.size(o)===1,z=s.ShapeUtil.size(p)===1;if(b!==1||N||z){if(N&&!z)M=y===1?` + return vec4(outputValue.x, outputValue.x, 0., 0.); + `:` + return vec4(outputValue.x); + `;else if(w.length){const C=b-2,G=b-1;w.indexOf(C)>-1&&w.indexOf(G)>-1?M="return vec4(outputValue.x);":w.indexOf(C)>-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 ${l}() { + ${T} coords = getOutputCoords(); + + int lastDim = coords.${P[y-1]}; + coords.${P[y-1]} = coords.${P[y-2]}; + coords.${P[y-2]} = lastDim; + + ${A} + vec4 outputValue = ${_}(${x}); + ${M} + } + `;return new u.GlslLibRoutine($,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(l,n,e,r){const o=[e.width,e.height],p=[n.width,n.height],g=n.unpackedShape.length,_=e.unpackedShape.length,b=n.unpackedShape,y=e.unpackedShape,w=(0,h.generateShaderFuncNameFromInputSamplerName)(r);if(g===_&&s.ArrayUtil.arraysEqual(p,o)){const z=` + float ${l}() { + return sampleTexture(${r}, TexCoords); + } + `;return new u.GlslLibRoutine(z,["coordinates.sampleTexture"])}const T=(0,h.getCoordsDataType)(_),S=s.BroadcastUtil.getBroadcastDims(b,y),A=_-g;let P;const x=(0,h.getGlChannels)();P=g===0?"":_<2&&S.length>=1?"coords = 0;":S.map(z=>`coords.${x[z+A]} = 0;`).join(` +`);let M="";M=_<2&&g>0?"coords":n.unpackedShape.map((z,$)=>`coords.${x[$+A]}`).join(", ");const N=` + float ${l}() { + ${T} coords = getOutputCoords(); + ${P} + return ${w}(${M}); + } + `;return new u.GlslLibRoutine(N,["coordinates.getOutputCoords"])}getPackedSamplerFromInput(l,n,e){switch(e.unpackedShape.length){case 0:return this.getPackedSamplerScalar(l,n);case 1:return this.getPackedSampler1D(l,n,e);case 2:return this.getPackedSampler2D(l,n,e);case 3:return this.getPackedSampler3D(l,n,e);default:return this.getPackedSamplerND(l,n,e)}}getUnpackedSamplerFromInput(l,n,e){const r=e.unpackedShape;switch(r.length){case 0:return this.getUnpackedSamplerScalar(l,n,e);case 1:return this.getUnpackedSampler1D(l,n,e);case 2:return this.getUnpackedSampler2D(l,n,e);case 3:return this.getUnpackedSampler3D(l,n,e);case 4:return this.getUnpackedSampler4D(l,n,e);case 5:return this.getUnpackedSampler5D(l,n,e);case 6:return this.getUnpackedSampler6D(l,n,e);default:throw new Error(`Unsupported dimension ${r.length}-D`)}}getPackedSamplerScalar(l,n){const e=` + vec4 ${l}() { + return ${(0,d.getGlsl)(this.context.glContext.version).texture2D}(${n}, halfCR); + } + `;return new u.GlslLibRoutine(e)}getPackedSampler1D(l,n,e){const r=[e.width,e.height],o=[r[1],r[0]],p=(0,d.getGlsl)(this.context.glContext.version),g=`vec4 ${l}(int index) { + vec2 uv = packedUVfrom1D( + ${o[0]}, ${o[1]}, index); + return ${p.texture2D}(${n}, uv); + }`;return new u.GlslLibRoutine(g,["coordinates.packedUVfrom1D"])}getPackedSampler2D(l,n,e){const r=e.unpackedShape,o=[e.width,e.height],p=(0,d.getGlsl)(this.context.glContext.version),g=o[0],_=o[1];if(o!=null&&s.ArrayUtil.arraysEqual(r,o)){const T=`vec4 ${l}(int row, int col) { + vec2 uv = (vec2(col, row) + halfCR) / vec2(${_}.0, ${g}.0); + return ${p.texture2D}(${n}, uv); + }`;return new u.GlslLibRoutine(T)}const b=o,y=Math.ceil(r[1]/2),w=`vec4 ${l}(int row, int col) { + vec2 uv = packedUVfrom2D(${b[1]}, ${b[0]}, ${y}, row, col); + return ${p.texture2D}(${n}, uv); + }`;return new u.GlslLibRoutine(w,["coordinates.packedUVfrom2D"])}getPackedSampler3D(l,n,e){const r=e.unpackedShape,o=[e.width,e.height],p=[o[0],o[1]],g=(0,d.getGlsl)(this.context.glContext.version);if(r[0]===1){const T=r.slice(1),S=[1,2],A=(0,h.squeezeInputShape)(r,T),P=["b","row","col"],x=JSON.parse(JSON.stringify(e));x.unpackedShape=A;const M=this.getPackedSamplerFromInput(l,n,x),N=`${M.routineBody} + vec4 ${l}(int b, int row, int col) { + return ${l}(${(0,h.getSqueezedParams)(P,S)}); + } `;return new u.GlslLibRoutine(N,M.dependencies)}const _=p[0],b=p[1],y=Math.ceil(r[2]/2),w=`vec4 ${l}(int b, int row, int col) { + vec2 uv = packedUVfrom3D( + ${b}, ${_}, ${y*Math.ceil(r[1]/2)}, ${y}, b, row, col); + return ${g.texture2D}(${n}, uv);}`;return new u.GlslLibRoutine(w,["coordinates.packedUVfrom3D"])}getPackedSamplerND(l,n,e){const r=e.unpackedShape,o=r.length,p=[e.width,e.height],g=(0,d.getGlsl)(this.context.glContext.version),_=[p[0],p[1]],b=_[1],y=_[0],w=Math.ceil(r[o-1]/2);let T=w*Math.ceil(r[o-2]/2),S="int b, int row, int col",A=`b * ${T} + (row / 2) * ${w} + (col / 2)`;for(let x=2;x{const r=this.context.inputTextureLayouts[e],o=(r.unpackedShape.length>0?r.unpackedShape:r.shape).length;let p=`_${n}`;l[p]=new u.GlslLibRoutine(this.getValueFromSingle(n,o,r.width,r.height,!1),[`shapeUtils.indicesToOffset${p}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"]),p+="_T",l[p]=new u.GlslLibRoutine(this.getValueFromSingle(n,o,r.width,r.height,!0),[`shapeUtils.indicesToOffset${p}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"])}),l}getValueFromSingle(l,n,e,r,o){let p=`_${l}`;return o&&(p+="_T"),` + float ${p}(int m[${n}]) { + int offset = indicesToOffset${p}(m); + vec2 coords = offsetToCoords(offset, ${e}, ${r}); + float value = getColorAsFloat(${(0,d.getGlsl)(this.context.glContext.version).texture2D}(${l}, coords)); + return value; + } + `}getPackedValueFrom(l,n,e,r,o){let p=`_${l}_Pack`;return o&&(p+="_T"),` + vec4 ${p}(int m[${n}]) { + int offset = indicesToOffset_${l}(m); + vec2 coords = offsetToCoords(offset, ${e}, ${r}); + return ${(0,d.getGlsl)(this.context.glContext.version).texture2D}(${l}, coords); + } + `}}t.CoordsGlslLib=f},8520:(m,t)=>{var i;Object.defineProperty(t,"__esModule",{value:!0}),t.TopologicalSortGlslRoutines=t.GlslLibRoutineNode=t.GlslLibRoutine=t.GlslLib=t.GlslContext=t.FunctionType=void 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Object.assign(Object.assign({},this.encodeFloat32()),this.decodeFloat32())}getCustomTypes(){return{}}encodeFloat32(){return{encode:new s.GlslLibRoutine(`highp vec4 encode(highp float f) { + return vec4(f, 0.0, 0.0, 0.0); + } + `)}}decodeFloat32(){return{decode:new s.GlslLibRoutine(`highp float decode(highp vec4 rgba) { + return rgba.r; + } + `)}}encodeUint8(){const a=u.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{encode:new s.GlslLibRoutine(` + highp vec4 encode(highp float f) { + highp float F = abs(f); + highp float Sign = step(0.0,-f); + highp float Exponent = floor(log2(F)); + highp float Mantissa = (exp2(- Exponent) * F); + Exponent = floor(log2(F) + 127.0) + floor(log2(Mantissa)); + highp vec4 rgba; + rgba[0] = 128.0 * Sign + floor(Exponent*exp2(-1.0)); + rgba[1] = 128.0 * mod(Exponent,2.0) + mod(floor(Mantissa*128.0),128.0); + rgba[2] = floor(mod(floor(Mantissa*exp2(23.0 -8.0)),exp2(8.0))); + rgba[3] = floor(exp2(23.0)*mod(Mantissa,exp2(-15.0))); + ${a} + rgba = rgba / 255.0; // values need to be normalized to [0,1] + return rgba; + } + `)}}decodeUint8(){const a=u.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{decode:new s.GlslLibRoutine(` + highp float decode(highp vec4 rgba) { + rgba = rgba * 255.0; // values need to be de-normalized from [0,1] to [0,255] + ${a} + highp float Sign = 1.0 - step(128.0,rgba[0])*2.0; + highp float Exponent = 2.0 * mod(rgba[0],128.0) + step(128.0,rgba[1]) - 127.0; + highp float Mantissa = mod(rgba[1],128.0)*65536.0 + rgba[2]*256.0 +rgba[3] + float(0x800000); + highp float Result = Sign * exp2(Exponent) * (Mantissa * exp2(-23.0 )); + return Result; + } + `)}}static isLittleEndian(){const a=new ArrayBuffer(4),h=new Uint32Array(a),f=new Uint8Array(a);if(h[0]=3735928559,f[0]===239)return!0;if(f[0]===222)return!1;throw new Error("unknown endianness")}}t.EncodingGlslLib=u},9894:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.FragColorGlslLib=void 0;const s=i(8520),u=i(5060);class d extends 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${u(d).output} = result; + } + `}},3891:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.VecGlslLib=void 0;const s=i(8520);class u extends s.GlslLib{constructor(a){super(a)}getCustomTypes(){return{}}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign({},this.binaryVecFunctions()),this.copyVec()),this.setVecItem()),this.getVecItem())}binaryVecFunctions(){const a=this.context.outputTextureLayout.shape.length,h={add:"+=",sub:"-=",mul:"*=",div:"/="},f={};for(const c in h){const l=`${c}Vec`;let n="";for(let r=0;r{Object.defineProperty(t,"__esModule",{value:!0}),t.WebGLInferenceHandler=void 0;const s=i(6231),u=i(9162),d=i(2517),a=i(2403),h=i(7019),f=i(8710),c=i(5611),l=i(4057),n=i(2039);t.WebGLInferenceHandler=class{constructor(e){this.session=e,this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new 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b; + } + vec4 ${T}(vec4 v1, vec4 v2) { + return v1 - v2; + } + `,name:T,type:u.FunctionType.ValueBased}}function n(){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:u.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:u.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:u.FunctionType.ValueBased}}function o(){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:u.FunctionType.ValueBased}}function p(){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:u.FunctionType.ValueBased}}function g(){const T="xor_";return{body:` + float ${T}(float a, float b) { + return float( bool(a) ^^ bool(b) ); + } + vec4 ${T}(vec4 v1, vec4 v2) { + bvec4 b1 = bvec4(v1); + bvec4 b2 = bvec4(v2); + return vec4( b1.r ^^ b2.r , + b1.g ^^ b2.g, + b1.b ^^ b2.b, + b1.a ^^ b2.a ); + } + `,name:T,type:u.FunctionType.ValueBased}}function _(){return function(T){const S=`${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:u.FunctionType.ValueBased}}("pow")}function b(){const T="prelu_";return{body:` + float ${T}(float a, float b) { + return a < 0.0 ? a * b: a; + } + vec4 ${T}(vec4 v1, vec4 v2) { + return vec4( + v1.r < 0.0 ? v1.r * v2.r: v1.r, + v1.g < 0.0 ? v1.g * v2.g: v1.g, + v1.b < 0.0 ? v1.b * v2.b: v1.b, + v1.a < 0.0 ? v1.a * v2.a: v1.a + ); + } + `,name:T,type:u.FunctionType.ValueBased}}t.glslAdd=h,t.glslDiv=f,t.glslMul=c,t.glslSub=l,t.glslEqual=n,t.glslGreater=e,t.glslLess=r,t.glslAnd=o,t.glslOr=p,t.glslXor=g,t.glslPow=_,t.glslPRelu=b;const y=(T,S,A,P=S[0].type,x)=>{const M=T.session.pack?a.TextureType.packed:a.TextureType.unpacked;return{name:A.name,inputNames:["A","B"],inputTypes:[M,M],cacheHint:x,get:()=>w(T,S,A,P)}},w=(T,S,A,P=S[0].type)=>{const x=T.session.pack?a.TextureType.packed:a.TextureType.unpacked,M=!s.ShapeUtil.areEqual(S[0].dims,S[1].dims);let N=S[0].dims;const z=T.session.pack;if(M){const G=s.BroadcastUtil.calcShape(S[0].dims,S[1].dims,!1);if(!G)throw new 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${A.name}(v1, v2); + ${$.output} = result; + } + `;return{name:A.name,inputNames:["A","B"],inputTypes:[x,x],output:{dims:S[0].dims,type:P,textureType:x},shaderSource:C,hasMain:!0}};t.add=(T,S)=>[T.run(y(T,S,h()),S)],t.and=(T,S)=>[T.run(y(T,S,o(),"bool"),S)],t.div=(T,S)=>[T.run(y(T,S,f()),S)],t.equal=(T,S)=>[T.run(y(T,S,n(),"bool"),S)],t.greater=(T,S)=>[T.run(y(T,S,e(),"bool"),S)],t.less=(T,S)=>[T.run(y(T,S,r(),"bool"),S)],t.mul=(T,S)=>[T.run(y(T,S,c()),S)],t.or=(T,S)=>[T.run(y(T,S,p(),"bool"),S)],t.pow=(T,S)=>[T.run(y(T,S,_()),S)],t.pRelu=(T,S)=>[T.run(y(T,S,b()),S)],t.sub=(T,S)=>[T.run(y(T,S,l()),S)],t.xor=(T,S)=>[T.run(y(T,S,g(),"bool"),S)]},4196:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseCastAttributes=t.cast=void 0;const s=i(2517);t.cast=(d,a,h)=>(u(a),[d.cast(a[0],h)]),t.parseCastAttributes=d=>s.ProtoUtil.tensorDataTypeFromProto(d.attributes.getInt("to"));const u=d=>{if(!d||d.length!==1)throw new Error("Cast requires 1 input.");if(d[0].type==="string")throw 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R=(0,s.getGlsl)(o.session.backend.glContext.version),Y=` + ${A} + float getValue(${x.map(V=>"int "+V)}) { + ${C} + } + + void main() { + ${S} coords = getOutputCoords(); + int lastDim = coords.${x[w-1]}; + coords.${x[w-1]} = coords.${x[w-2]}; + coords.${x[w-2]} = lastDim; + + vec4 result = vec4(getValue(${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}); + } + ${R.output} = result; + } + `;return Object.assign(Object.assign({},p),{output:{dims:y,type:g[0].type,textureType:u.TextureType.packed},shaderSource:Y,hasMain:!0})})(f,n,c,l.axis)})};const h=(f,c,l)=>{const n=f.indexOf(c);return f.map((e,r)=>r===n?`${e} - 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Object.assign(Object.assign({},n),{get:()=>((o,p,g,_)=>{const b=p.length>2?"value += getBias(output_channel);":"",y=p[0].dims.slice(),w=p[1].dims.slice(),T=w[0]/_.group;s.Logger.verbose("GroupedConv",`autpPad:${_.autoPad}, dilations:${_.dilations}, group:${_.group}, kernelShape:${_.kernelShape}, pads:${_.pads}, strides:${_.strides}`);const S=(0,a.calculateOutputShape)(y,w,_.dilations,_.pads,_.strides),A=(0,u.getGlsl)(o.session.backend.glContext.version),{activationFunction:P,applyActivation:x}=(0,h.getActivationSnippet)(_),M=` + const ivec2 strides = ivec2(${_.strides[0]}, ${_.strides[1]}); + const ivec2 pads = ivec2(${_.pads[0]}, ${_.pads[1]}); + ${P} + void main() { + ivec4 coords = getOutputCoords(); + int batch = coords.x; + int output_channel = coords.y; + ivec2 xRCCorner = coords.zw * strides - pads; + int group_id = output_channel / ${T}; + + float value = 0.0; + for (int wInChannel = 0; wInChannel < ${w[1]}; wInChannel++) { + int input_channel = group_id * ${w[1]} + wInChannel; + for (int wHeight = 0; wHeight < ${w[2]}; wHeight++) { + int xHeight = xRCCorner.x + wHeight * ${_.dilations[0]}; + + if (xHeight < 0 || xHeight >= ${y[2]}) { + continue; + } + + for (int wWidth = 0; wWidth < ${w[3]}; wWidth++) { + int xWidth = xRCCorner.y + wWidth * ${_.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} + ${x} + ${A.output} = vec4(value, .0, .0, .0); + } +`;return Object.assign(Object.assign({},g),{output:{dims:S,type:p[0].type,textureType:d.TextureType.unpacked},shaderSource:M,hasMain:!0})})(f,c,n,l)})}},1386:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.conv2DPacked=t.conv2DPackedPointwise=void 0;const s=i(8138),u=i(8555),d=i(708);t.conv2DPackedPointwise=(a,h,f)=>{const c=h[0].dims,l=h[1].dims,n=(0,s.calculateOutputShape)(c,l,f.dilations,f.pads,f.strides),e=a.reshapePacked(h[0],[c[1],c[2]*c[3]]),r=a.reshapePacked(h[1],[l[0],l[1]]),o=h.length>2?[r,e,h[2]]:[r,e],p=a.run((0,d.createPackedMatmulProgramInfoLoader)(a,o,f),o);return a.reshapePacked(p,n)},t.conv2DPacked=(a,h,f)=>{const c=h[0].dims,l=h[1].dims,n=(0,s.calculateOutputShape)(c,l,f.dilations,f.pads,f.strides),e=a.run((0,u.createPackedIm2ColProgramInfoLoader)(a,h[0],h[1],n,f),[h[0]]),r=a.reshapePacked(h[1],[l[0],l[1]*l[2]*l[3]]),o=h.length===3?[r,e,h[2]]:[r,e],p=a.run((0,d.createPackedMatmulProgramInfoLoader)(a,o,f),o);return a.reshapePacked(p,n)}},9663:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseConvTransposeAttributes=t.convTranspose=void 0;const s=i(246),u=i(5060),d=i(2039),a=i(2823),h=(r,o,p,g,_,b)=>(r-1)*o+p+(g-1)*_+1-b,f=(r,o,p,g,_)=>{const b=Math.floor(r/2);o==="SAME_UPPER"?(p[g]=b,p[_]=r-b):o==="SAME_LOWER"&&(p[g]=r-b,p[_]=b)};t.convTranspose=(r,o,p)=>(e(o,p),c(r,o,p));const c=(r,o,p)=>{const g=n(p,o);return[l(r,o,g)]},l=(r,o,p)=>r.run(((g,_,b)=>{const y=(w=_.length>2,T=b.cacheKey,{name:"ConvTranspose",inputNames:w?["X","W","B"]:["X","W"],inputTypes:w?[d.TextureType.unpacked,d.TextureType.unpacked,d.TextureType.unpacked]:[d.TextureType.unpacked,d.TextureType.unpacked],cacheHint:T});var w,T;return Object.assign(Object.assign({},y),{get:()=>((S,A,P,x)=>{const M=A.length>2?"getB(output_channel)":"0.0",N=A[0].dims,z=A[1].dims,$=z[1],C=z[0]/x.group,G=[A[0].dims[0],A[1].dims[1]*x.group,...x.outputShape],D=(0,u.getGlsl)(S.session.backend.glContext.version),{activationFunction:R,applyActivation:Y}=(0,a.getActivationSnippet)(x),V=` + const ivec2 strides = ivec2(${x.strides[0]}, ${x.strides[1]}); + const ivec2 pads = ivec2(${x.pads[0]}, ${x.pads[1]}); + ${R} + 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 < ${C}; inChannelOffset++) { + int input_channel = group_id * ${C} + inChannelOffset; + for (int wWOff = 0; wWOff < ${z[2]}; wWOff++) { + for (int wHOff = 0; wHOff < ${z[3]}; wHOff++) { + ivec2 wOff = ivec2(wWOff * ${x.dilations[0]}, wHOff * ${x.dilations[1]}); + ivec2 wLoc = loc - wOff; + ivec2 wLocIn = wLoc / strides; + if ( + wLocIn * strides == wLoc && + wLocIn.x >= 0 && wLocIn.x < ${N[2]} && + wLocIn.y >= 0 && wLocIn.y < ${N[3]} + ) { + float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x); + float wVal = getW(input_channel, wOutChannel, wHOff, wWOff); + value += xVal * wVal; + } + } + } + } + ${Y} + ${D.output} = vec4(value, .0, .0, .0); + } +`;return Object.assign(Object.assign({},P),{output:{dims:G,type:A[0].type,textureType:d.TextureType.unpacked},shaderSource:V,hasMain:!0})})(g,_,y,b)})})(r,o,p),o),n=(r,o)=>{const p=r.kernelShape.slice();if(r.kernelShape.length===0)for(let y=2;y{const N=y.length-2,z=M.length===0;for(let $=0;${const o=r.attributes,p=(0,a.parseInternalActivationAttributes)(o),g=o.getString("auto_pad","NOTSET"),_=o.getInts("dilations",[1,1]),b=o.getInt("group",1),y=o.getInts("kernel_shape",[]),w=o.getInts("output_padding",[0,0]),T=o.getInts("output_shape",[]),S=o.getInts("pads",[0,0,0,0]),A=o.getInts("strides",[1,1]);return(0,s.createAttributeWithCacheKey)(Object.assign({autoPad:g,dilations:_,group:b,kernelShape:y,outputPadding:w,outputShape:T,pads:S,strides:A},p))};const e=(r,o)=>{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 p=r[1].dims[1]*o.group;if(r.length===3&&(r[2].dims.length!==1||r[2].dims[0]!==p))throw new Error("invalid bias");const g=r[0].dims.length-2;if(o.dilations.length!==g)throw new Error(`dilations should be ${g}D`);if(o.strides.length!==g)throw new Error(`strides should be ${g}D`);if(o.pads.length!==2*g)throw new Error(`pads should be ${2*g}D`);if(o.outputPadding.length!==g)throw new Error(`output_padding should be ${g}D`);if(o.kernelShape.length!==0&&o.kernelShape.length!==r[1].dims.length-2)throw new Error("invalid kernel shape");if(o.outputShape.length!==0&&o.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:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseConvAttributes=t.conv=t.calculateOutputShape=void 0;const s=i(246),u=i(2517),d=i(4770),a=i(1386),h=i(9828),f=i(2823),c=i(3248),l=i(5623);t.calculateOutputShape=(g,_,b,y,w)=>{const T=g[0],S=g.slice(2),A=S.length,P=_[0],x=_.slice(2).map((N,z)=>N+(N-1)*(b[z]-1)),M=S.map((N,z)=>N+y[z]+y[z+A]).map((N,z)=>Math.floor((N-x[z]+w[z])/w[z]));return[T,P].concat(...M)},t.conv=(g,_,b)=>(p(_,b),n(g,_,b));const n=(g,_,b)=>{const y=o(b,_),w=g.session.pack,T=y.kernelShape[0]===1&&y.kernelShape[1]===1;return y.group>1?[g.run((0,d.createUnpackedGroupedConvProgramInfoLoader)(g,_,y),_)]:T&&w?[e(g,_,y)]:w&&_[0].dims.length===4&&_[0].dims[0]===1&&!T?[(0,a.conv2DPacked)(g,_,y)]:[r(g,_,y)]},e=(g,_,b)=>{const y=_[0].dims,w=_[1].dims,T=(0,t.calculateOutputShape)(y,w,b.dilations,b.pads,b.strides),S=g.reshapeUnpacked(_[0],[y[1],y[2]*y[3]]),A=g.reshapeUnpacked(_[1],[w[0],w[1]]),P=_.length>2?[A,S,_[2]]:[A,S],x=g.run((0,l.createMatmulProgramInfoLoader)(P,b),P);return g.reshapeUnpacked(x,T)},r=(g,_,b)=>{const y=_[0].dims,w=_[1].dims,T=(0,t.calculateOutputShape)(y,w,b.dilations,b.pads,b.strides),S=g.run((0,c.createIm2ColProgramInfoLoader)(g,_[0],_[1],T,b),[_[0]]),A=_.length===3?[S,_[1],_[2]]:[S,_[1]];return g.run((0,h.createDotProductProgramInfoLoader)(g,_,T,b),A)},o=(g,_)=>{const b=g.kernelShape.slice();if(g.kernelShape.length===0)for(let T=2;T<_[1].dims.length;++T)b.push(_[1].dims[T]);const y=g.pads.slice();u.PoolConvUtil.adjustPadsBasedOnAutoPad(_[0].dims,g.strides,g.dilations,b,y,g.autoPad);const w=Object.assign({},g);return Object.assign(w,{kernelShape:b,pads:y,cacheKey:g.cacheKey}),w};t.parseConvAttributes=g=>{const _=g.attributes,b=(0,f.parseInternalActivationAttributes)(_),y=_.getString("auto_pad","NOTSET"),w=_.getInts("dilations",[1,1]),T=_.getInt("group",1),S=_.getInts("kernel_shape",[]),A=_.getInts("pads",[0,0,0,0]),P=_.getInts("strides",[1,1]);return(0,s.createAttributeWithCacheKey)(Object.assign({autoPad:y,dilations:w,group:T,kernelShape:S,pads:A,strides:P},b))};const p=(g,_)=>{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]*_.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(_.dilations.length!==b)throw new Error(`dilations should be ${b}D`);if(_.strides.length!==b)throw new Error(`strides should be ${b}D`);if(_.pads.length!==2*b)throw new Error(`pads should be ${2*b}D`);if(_.kernelShape.length!==0&&_.kernelShape.length!==g[1].dims.length-2)throw new Error("invalid kernel shape");if(g[0].type!=="float32"||g[1].type!=="float32")throw new Error("Conv input(X,W) should be float tensor");if(g.length===3&&g[2].type!=="float32")throw new Error("Conv input(bias) should be float tensor")}},5193:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseDepthToSpaceAttributes=t.depthToSpace=void 0;const s=i(3738);t.depthToSpace=(d,a,h)=>{u(a);const f=h.blocksize,c=f*f,l=h.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],n=h.mode==="DCR"?[a[0].dims[0],f,f,a[0].dims[1]/c,a[0].dims[2],a[0].dims[3]]:[a[0].dims[0],a[0].dims[1]/c,f,f,a[0].dims[2],a[0].dims[3]],e=d.reshapeUnpacked(a[0],n),r={perm:l,cacheKey:`${l}`},[o]=(0,s.transpose)(d,[e],r),p=[a[0].dims[0],a[0].dims[1]/c,a[0].dims[2]*f,a[0].dims[3]*f];return[d.reshapeUnpacked(o,p)]},t.parseDepthToSpaceAttributes=d=>{const a=d.attributes.getInt("blocksize");if(a<1)throw new Error(`blocksize must be >= 1, but got : ${a} for DepthToSpace`);const h=d.attributes.getString("mode","DCR");if(h!=="DCR"&&h!=="CRD")throw new Error(`unrecognized mode: ${h} for DepthToSpace`);return{mode:h,blocksize:a}};const u=d=>{if(d.length!==1)throw new Error(`DepthToSpace expect 1 inputs, but got ${d.length}`);if(d[0].type==="string"||d[0].dims.length!==4)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}},9828:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createDotProductProgramInfoLoader=void 0;const s=i(2517),u=i(5060),d=i(2039),a=i(2823),h=i(3248);t.createDotProductProgramInfoLoader=(f,c,l,n)=>{const e=((r,o)=>({name:"ConvDotProduct",inputNames:r?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:r?[d.TextureType.unpacked,d.TextureType.packedLastDimension,d.TextureType.unpacked]:[d.TextureType.unpacked,d.TextureType.packedLastDimension],cacheKey:o.activationCacheKey}))(c.length>2,n);return Object.assign(Object.assign({},e),{get:()=>((r,o,p,g,_)=>{const b=p[0].dims,y=p[1].dims,w=[y[0],Math.ceil(b[1]*y[2]*y[3]/4)],T=(0,h.calculateIm2ColDims)(b,y,g),[S,A]=r.calculateTextureWidthAndHeight(w,d.TextureType.packedLastDimension),P=s.ShapeUtil.computeStrides(T),[x,M]=r.calculateTextureWidthAndHeight(T,d.TextureType.packedLastDimension),N=g.length,z=p.length<3?"0.0":"_B(b)",$=Math.ceil(b[1]*y[2]*y[3]/4),{activationFunction:C,applyActivation:G}=(0,a.getActivationSnippet)(_),D=(0,u.getGlsl)(r.session.backend.glContext.version),R=` +${C} +float process(int indices[${N}]) { + int b[1]; + b[0] = indices[1]; + int im2col[4]; + im2col[0] = indices[0]; + im2col[1] = indices[2]; + im2col[2] = indices[3]; + int im2colOffset = im2col[0] * ${P[0]} + im2col[1] * ${P[1]} + im2col[2] * ${P[2]}; + int kernelOffset = indices[1] * ${w[1]}; + float value = ${z}; + for (int i = 0; i < ${$}; ++i) { + vec2 im2colCoords = offsetToCoords(im2colOffset, ${x}, ${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({},o),{output:{dims:g,type:p[0].type,textureType:d.TextureType.unpacked},shaderSource:R})})(f,e,c,l,n)})}},7992:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseFlattenAttributes=t.flatten=void 0;const s=i(2517);t.flatten=(d,a,h)=>{u(a,h);const f=s.ShapeUtil.flattenShape(a[0].dims,h);return[d.reshapeUnpacked(a[0],f)]},t.parseFlattenAttributes=d=>d.attributes.getInt("axis",1);const u=(d,a)=>{if(!d||d.length!==1)throw new Error("Flatten requires 1 input.");const h=d[0].dims.length;if(h===0)throw new Error("scalar tensor is not supported.");if(a<-h||a>h)throw new Error("Invalid axis");if(d[0].type==="string")throw new Error("string tensor is not supported.")}},2823:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseInternalActivationAttributes=t.getActivationSnippet=void 0;const s=i(2517),u=i(4909);t.getActivationSnippet=function(d){let a;switch(d.activation){case"Relu":a=(0,u.glslRelu)();break;case"Sigmoid":a=(0,u.glslSigmoid)();break;case"Clip":a=(0,u.glslClip)(d.clipMin,d.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const h=a.name;return{activationFunction:a.body,applyActivation:`value = ${h}_(value);`}},t.parseInternalActivationAttributes=d=>{const a=d.getString("activation","");if(a==="Clip"){const[h,f]=d.getFloats("activation_params",[s.MIN_CLIP,s.MAX_CLIP]);return{activation:a,clipMax:f,clipMin:h,activationCacheKey:`${a}:${h},${f}`}}return{activation:a,activationCacheKey:a}}},1253:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseGatherAttributes=t.gather=void 0;const s=i(246),u=i(782),d=i(2517),a=i(2039);t.gather=(l,n,e)=>(c(n,e.axis),[l.run(f(l,n,e),n)]),t.parseGatherAttributes=l=>(0,s.createAttributeWithCacheKey)({axis:l.attributes.getInt("axis",0)});const h={name:"Gather",inputNames:["A","B"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked]},f=(l,n,e)=>{const r=Object.assign(Object.assign({},h),{cacheHint:e.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((o,p,g,_)=>{const b=g[0].dims.slice(),y=g[1].dims.slice(),w=new Array(b.length+y.length-1);_=d.ShapeUtil.normalizeAxis(_,b.length);const T=[];for(let A=0;A{if(!l||l.length!==2)throw new Error("Gather requires 2 inputs.");const e=l[0].dims.length;if(e<1)throw new Error("Invalid input shape.");if(n<-e||n>e-1)throw new Error("Invalid axis.");if(u.NUMBER_TYPES.indexOf(l[0].type)===-1)throw new Error("Invaid input type.");if(l[1].type!=="int32"&&l[1].type!=="int16")throw new Error("Invaid input type.")}},4776:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseGemmAttributesV11=t.parseGemmAttributesV7=t.gemm=void 0;const s=i(246),u=i(2517),d=i(2039);t.gemm=(l,n,e)=>(c(n,e),[l.run(h(n,e),n)]);const a=(l,n)=>{const e=l.attributes.getInt("transA",0)!==0,r=l.attributes.getInt("transB",0)!==0,o=l.attributes.getFloat("alpha",1),p=l.attributes.getFloat("beta",1);return(0,s.createAttributeWithCacheKey)({transA:e,transB:r,alpha:o,beta:p,isOptionalC:n})};t.parseGemmAttributesV7=l=>a(l,!1),t.parseGemmAttributesV11=l=>a(l,!0);const h=(l,n)=>{const e={name:"Gemm",inputNames:l.length===3?["A","B","C"]:["A","B"],inputTypes:l.length===3?[d.TextureType.unpacked,d.TextureType.unpacked,d.TextureType.unpacked]:[d.TextureType.unpacked,d.TextureType.unpacked],key:n.cacheKey};return Object.assign(Object.assign({},e),{get:()=>f(e,l,n)})},f=(l,n,e)=>{const r=n[0].dims.slice(),o=n[1].dims.slice(),[p,g]=u.GemmUtil.getShapeOfGemmResult(r,e.transA,o,e.transB,n.length===3?n[2].dims:void 0),_=[p,g];if(!_)throw new Error("Can't use gemm on the given tensors");let b=r[r.length-1],y="";e.transA&&(b=r[0]),e.transA&&e.transB?y="value += _A_T(a) * _B_T(b);":e.transA&&!e.transB?y="value += _A_T(a) * _B(b);":!e.transA&&e.transB?y="value += _A(a) * _B_T(b);":e.transA||e.transB||(y="value += _A(a) * _B(b);");const w=_.length,T=` + float process(int indices[${w}]) { + int a[${w}]; + int b[${w}]; + ${n.length===3?`int c[${n[2].dims.length}];`:""} + + copyVec(indices, a); + copyVec(indices, b); + ${n.length===3?"bcastIndices_C(indices, c);":""} + + float value = 0.0; + for (int k=0; k<${b}; ++k) { + a[${w-1}] = k; + b[${w-2}] = k; + ${y} + } + + value = value * alpha; + ${n.length===3?"value += beta * _C(c);":""} + return value; + }`;return Object.assign(Object.assign({},l),{output:{dims:_,type:n[0].type,textureType:d.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:e.alpha},{name:"beta",type:"float",data:e.beta}],shaderSource:T})},c=(l,n)=>{if(!l)throw new Error("Input is missing");if(n.isOptionalC&&(l.length<2||l.length>3))throw new Error("Invaid input shape.");if(!n.isOptionalC&&l.length!==3)throw new Error("Gemm requires 3 inputs");if(l.length===3&&l[2].dims.length!==1&&l[2].dims.length!==2)throw new Error("Invalid input shape of C");if(l[0].type!=="float32"&&l[0].type!=="float64"||l[1].type!=="float32"&&l[1].type!=="float64"||l.length===3&&l[2].type!=="float32"&&l[2].type!=="float64")throw new Error("Invalid input type.");if(l[0].type!==l[1].type||l.length===3&&l[0].type!==l[2].type)throw new Error("Input types are mismatched")}},8555:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createPackedIm2ColProgramInfoLoader=void 0;const s=i(5060),u=i(2039),d=i(2827);t.createPackedIm2ColProgramInfoLoader=(a,h,f,c,l)=>{const n=(e=l.cacheKey,{name:"Im2Col (packed)",inputNames:["A"],inputTypes:[u.TextureType.packed],cacheHint:e});var e;return Object.assign(Object.assign({},n),{get:()=>((r,o,p,g,_,b)=>{const y=p.dims,w=g.dims,T=_.length,S=[w[1]*w[2]*w[3],_[2]*_[3]],A=w[2]*w[3],P=(0,d.unpackFromChannel)(),x=(0,s.getGlsl)(r.session.backend.glContext.version);let M="";for(let z=0;z<=1;z++)for(let $=0;$<=1;$++)M+=` + blockIndex = rc.x + ${$}; + pos = rc.y + ${z}; + + if(blockIndex < ${S[1]} && pos < ${S[0]}) { + offsetY = int(blockIndex / (${_[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, ${_[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*z+$}] = getChannel( + getA(0, ch, int(innerDims.x), + int(innerDims.y)), innerDims); + } + } + } + + `;const N=` + ${P} + + void main() { + ivec2 rc = getOutputCoords(); + vec4 result = vec4(0.0); + int blockIndex, pos, offsetY, d0, offsetX, d1, ch; + vec2 innerDims; + ${M} + ${x.output} = result; + } + `;return Object.assign(Object.assign({},o),{output:{dims:S,type:p.type,textureType:u.TextureType.packed},shaderSource:N,hasMain:!0})})(a,n,h,f,c,l)})}},3248:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.calculateIm2ColDims=t.createIm2ColProgramInfoLoader=void 0;const s=i(2039);t.createIm2ColProgramInfoLoader=(u,d,a,h,f)=>{const c=(l=f.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[s.TextureType.unpacked],cacheHint:l});var l;return Object.assign(Object.assign({},c),{get:()=>((n,e,r,o,p,g)=>{const _=r.dims,b=o.dims,y=p.length,w=(0,t.calculateIm2ColDims)(_,b,p,4),T=` + const int XC = ${_[1]}; + const int XH = ${_[2]}; + const int XW = ${_[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[${_.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:s.TextureType.packedLastDimension},shaderSource:T})})(0,c,d,a,h,f)})},t.calculateIm2ColDims=(u,d,a,h=4)=>[a[0],a[2],a[3],Math.ceil(u[1]*d[2]*d[3]/h)]},6572:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseImageScalerAttributes=t.imageScaler=void 0;const s=i(246),u=i(2039);t.imageScaler=(c,l,n)=>(f(l),[c.run(a(c,l,n),l)]),t.parseImageScalerAttributes=c=>{const l=c.attributes.getFloat("scale"),n=c.attributes.getFloats("bias");return(0,s.createAttributeWithCacheKey)({scale:l,bias:n})};const d={name:"ImageScaler",inputNames:["X"],inputTypes:[u.TextureType.unpacked]},a=(c,l,n)=>{const e=Object.assign(Object.assign({},d),{cacheHint:n.cacheKey});return Object.assign(Object.assign({},e),{get:()=>((r,o,p,g)=>{const _=p[0].dims.slice(),b=_.length,y=` + ${h(g.bias.length)} + float process(int indices[${b}]) { + return _X(indices) * scale + getBias(bias, indices[1]); + }`;return Object.assign(Object.assign({},o),{output:{dims:_,type:p[0].type,textureType:u.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,l,n)})},h=c=>{const l=[`float getBias(float bias[${c}], int channel) {`];for(let n=0;n{if(!c||c.length!==1)throw new Error("ImageScaler requires 1 input.");if(c[0].dims.length!==4)throw new Error("Invalid input shape.");if(c[0].type!=="float32"&&c[0].type!=="float64")throw new Error("Invalid input type.")}},3346:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseInstanceNormalizationAttributes=t.instanceNormalization=void 0;const s=i(5060),u=i(2039);t.instanceNormalization=(l,n,e)=>{c(n);const r=l.run(a(n[0]),n);return[l.run(f(l,n[0],e,r.dims),[n[0],r,n[1],n[2]])]},t.parseInstanceNormalizationAttributes=l=>l.attributes.getFloat("epsilon",1e-5);const d={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[u.TextureType.unpacked]},a=l=>Object.assign(Object.assign({},d),{get:()=>((n,e)=>{const r=e.dims.slice(),o=r[1],p=r[2]*r[3],g=[r[0],o],_=` + vec4 process(int[2] indices) { + vec4 v = vec4(0.0); + int a[4]; + a[0] = indices[0]; + a[1] = indices[1]; + float temp = 0.0; + for(int a2=0; a2<${r[2]}; a2++) { + a[2] = a2; + for(int a3=0; a3<${r[3]}; a3++) { + a[3] = a3; + float x = _X(a); + temp += x; + } + } + float mean = temp / float(${p}); + 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(${p}); + + return v; + }`;return Object.assign(Object.assign({},n),{output:{dims:g,type:e.type,textureType:u.TextureType.packedLastDimension},shaderSource:_})})(d,l)}),h={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[u.TextureType.unpacked,u.TextureType.packedLastDimension,u.TextureType.unpacked,u.TextureType.unpacked]},f=(l,n,e,r)=>{const o=Object.assign(Object.assign({},h),{cacheHint:`${e}`});return Object.assign(Object.assign({},o),{get:()=>((p,g,_,b,y)=>{const w=(0,s.getGlsl)(p.session.backend.glContext.version),[T,S]=p.calculateTextureWidthAndHeight(y,u.TextureType.packedLastDimension),[A,P]=[T/4,S],x=` + vec4 get_MeanAndVariance(int[2] mv) { + int offset = indicesToOffset_MeanAndVariance(mv); + vec2 coords = offsetToCoords(offset, ${A}, ${P}); + return ${w.texture2D}(MeanAndVariance, coords); + } + + float process(int[4] indices) { + int mv[2]; + mv[0] = indices[0]; + mv[1] = indices[1]; + vec4 mean_and_variance = get_MeanAndVariance(mv); + float mean = mean_and_variance.r; + float variance = mean_and_variance.g; + + int sb[1]; + sb[0] = indices[1]; + float scale = _Scale(sb); + float b = _B(sb); + + return scale * (_X(indices) - mean) / sqrt(variance + epsilon) + b; + }`;return Object.assign(Object.assign({},g),{output:{dims:_.dims,type:_.type,textureType:u.TextureType.unpacked},variables:[{name:"epsilon",type:"float",data:b}],shaderSource:x})})(l,o,n,e,r)})},c=l=>{if(!l||l.length!==3)throw new Error("InstanceNormalization requires 3 inputs.");const n=l[0],e=l[1],r=l[2];if(n.dims.length<3||e.dims.length!==1||r.dims.length!==1)throw new Error("Invalid input shape.");if(e.dims[0]!==n.dims[1]||r.dims[0]!==n.dims[1])throw new Error("Input shapes are mismatched.");if(n.type!=="float32"&&n.type!=="float64"||e.type!=="float32"&&e.type!=="float64"||r.type!=="float32"&&r.type!=="float64")throw new Error("Invalid input type.");if(l[0].dims.length!==4)throw new Error("Only support 4-D input shape.")}},708:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createPackedMatmulProgramInfoLoader=void 0;const s=i(2517),u=i(5060),d=i(2039),a=i(9390),h=i(2823),f=i(5623);t.createPackedMatmulProgramInfoLoader=(c,l,n)=>{const e=(r=l.length>2,o=n.activationCacheKey,{name:"MatMul (packed)",inputNames:r?["A","B","Bias"]:["A","B"],inputTypes:r?[d.TextureType.packed,d.TextureType.packed,d.TextureType.packed]:[d.TextureType.packed,d.TextureType.packed],cacheHint:o});var r,o;return Object.assign(Object.assign({},e),{get:()=>((p,g,_,b)=>{const y=_.length>2,w=y?"value += getBiasForMatmul();":"",T=_[0].dims,S=_[1].dims,A=s.BroadcastUtil.calcShape(T,S,!0),P=!s.ShapeUtil.areEqual(_[0].dims,_[1].dims);if(!A)throw new Error("Can't use matmul on the given tensors");const x=T[T.length-1],M=Math.ceil(x/2),N=T.length,z=S.length,$=(0,u.getGlsl)(p.session.backend.glContext.version),C=(0,a.getCoordsDataType)(A.length),G=A.length,D=(0,a.getGlChannels)(),{activationFunction:R,applyActivation:Y}=(0,h.getActivationSnippet)(b),V=y?`${(0,f.getBiasForMatmul)(C,D,_[2].dims,A,!0)}`:"",J=P?`${function(xe,se,we,be){let ke=[],Le=[];const ve=we[0].dims,$e=we[1].dims,Fe=ve.length,Me=$e.length,Pe=be.length,Be=Pe-Fe,Ge=Pe-Me;ke=ve.map((Ee,ze)=>`coords.${se[ze+Be]}`),ke[Fe-1]="i*2",ke.join(", "),Le=$e.map((Ee,ze)=>`coords.${se[ze+Ge]}`),Le[Me-2]="i*2",Le.join(", ");const Ve=s.BroadcastUtil.getBroadcastDims(ve,be),Xe=s.BroadcastUtil.getBroadcastDims($e,be),Qe=Ve.map(Ee=>`coords.${se[Ee+Be]} = 0;`).join(` +`),qe=Xe.map(Ee=>`coords.${se[Ee+Ge]} = 0;`).join(` +`),Ue=`int lastDim = coords.${se[Pe-1]}; + coords.${se[Pe-1]} = coords.${se[Pe-2]}; + coords.${se[Pe-2]} = lastDim;`;return` +vec4 getAAtOutCoordsMatmul(int i) { + ${xe} coords = getOutputCoords(); + ${Ue} + ${Qe} + vec4 outputValue = getA(${ke}); + return outputValue; +} + +vec4 getBAtOutCoordsMatmul(int i) { + ${xe} coords = getOutputCoords(); + ${Ue} + ${qe} + vec4 outputValue = getB(${Le}); + return outputValue; +}`}(C,D,_,A)}`:"",Z=P?"getAAtOutCoordsMatmul(i)":`getA(${function(xe,se){let we="";for(let be=0;be{Object.defineProperty(t,"__esModule",{value:!0}),t.getBiasForMatmul=t.createMatmulProgramInfoLoader=t.parseMatMulAttributes=t.matMul=void 0;const s=i(2517),u=i(2039),d=i(9390),a=i(2823),h=i(708);function f(n,e){const r=(o=n.length>2,p=e.activationCacheKey,{name:"MatMul",inputNames:o?["A","B","Bias"]:["A","B"],inputTypes:o?[u.TextureType.unpacked,u.TextureType.unpacked,u.TextureType.unpacked]:[u.TextureType.unpacked,u.TextureType.unpacked],cacheHint:p});var o,p;return Object.assign(Object.assign({},r),{get:()=>function(g,_,b){const y=_[0].dims,w=_[1].dims,T=s.BroadcastUtil.calcShape(y,w,!0);if(!T)throw new Error("Can't use matmul on the given tensors");const S=(0,d.getCoordsDataType)(T.length),A=(0,d.getGlChannels)(),{activationFunction:P,applyActivation:x}=(0,a.getActivationSnippet)(b),M=_.length>2,N=M?"value += getBiasForMatmul();":"",z=M?`${l(S,A,_[2].dims,T,!1)}`:"",$=T.length,C=y.length,G=w.length,D=` + ${P} + ${z} + float process(int indices[${$}]) { + int a[${C}]; + int b[${G}]; + bcastMatmulIndices_A(indices, a); + bcastMatmulIndices_B(indices, b); + + float value; + for (int k=0; k<${y[y.length-1]}; ++k) { + a[${C-1}] = k; + b[${G-2}] = k; + value += _A(a) * _B(b); + } + ${N} + ${x} + return value; + }`;return Object.assign(Object.assign({},g),{output:{dims:T,type:_[0].type,textureType:u.TextureType.unpacked},shaderSource:D})}(r,n,e)})}t.matMul=(n,e,r)=>(c(e),n.session.pack?[n.run((0,h.createPackedMatmulProgramInfoLoader)(n,e,r),e)]:[n.run(f(e,r),e)]),t.parseMatMulAttributes=n=>(0,a.parseInternalActivationAttributes)(n.attributes),t.createMatmulProgramInfoLoader=f;const c=n=>{if(!n||n.length!==2)throw new Error("MatMul requires 2 inputs.");if(n[0].dims[n[0].dims.length-1]!==n[1].dims[n[1].dims.length-2])throw new Error("shared dimension does not match.");if(n[0].type!=="float32"&&n[0].type!=="float64"||n[1].type!=="float32"&&n[1].type!=="float64")throw new Error("inputs should be float type");if(n[0].type!==n[1].type)throw new Error("inputs types should match")};function l(n,e,r,o,p){let g="";const _=r.length,b=o.length,y=b-_;g=b<2&&_>0?"coords":r.map((S,A)=>`coords.${e[A+y]}`).join(", ");const w=s.BroadcastUtil.getBroadcastDims(r,o).map(S=>`coords.${e[S+y]} = 0;`).join(` +`);let T="vec4(outputValue.xx, outputValue.yy)";return s.ShapeUtil.size(r)===1&&(T="vec4(outputValue.x)"),p?` +vec4 getBiasForMatmul() { + ${n} coords = getOutputCoords(); + ${w} + vec4 outputValue = getBias(${g}); + return ${T}; +}`:` +float getBiasForMatmul() { + ${n} coords = getOutputCoords(); + ${w} + return getBias(coords.x); +}`}t.getBiasForMatmul=l},2403:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createPackProgramInfoLoader=void 0;const s=i(5060),u=i(2039),d=i(9390),a=i(2827),h={name:"pack",inputNames:["A"],inputTypes:[u.TextureType.unpackedReversed]};t.createPackProgramInfoLoader=(f,c)=>Object.assign(Object.assign({},h),{get:()=>((l,n)=>{const e=(0,s.getGlsl)(l.session.backend.glContext.version),r=n.dims,o=r.length,p=n.dims.length,g=(0,d.getCoordsDataType)(p),_=(0,a.getChannels)("rc",p),b=(y=p,w=_,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 >= ${T}; + `);var y,w,T,S;let A;A=o===0?[1,1]:o===1?[r[0],1]:[r[p-1],r[p-2]];const P=function(N,z,$){if(N===0)return"false";if(N===1)return`rc > ${z[0]}`;let C="";for(let G=N-2;G= ${z[G-N+2]}`,G= ${N[0]} ? 0. : getA(rc + 1), + 0, 0`;let C="";if($>2)for(let G=0;G<$-2;++G)C+=`${z[G]},`;return`getA(${C}r, c), + rEdge ? 0. : getA(${C}rp1, c), + cEdge ? 0. : getA(${C}r, cp1), + rEdge || cEdge ? 0. : getA(${C}rp1, cp1)`}(r,_),M=` + void main() { + ${g} rc = getOutputCoords(); + + if(${P}) { + ${e.output} = vec4(0); + } else { + ${b} + + ${e.output} = vec4(${x}); + } + } + `;return Object.assign(Object.assign({},h),{hasMain:!0,output:{dims:n.dims,type:n.type,textureType:u.TextureType.packed},shaderSource:M})})(f,c)})},2827:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.unpackFromChannel=t.getChannels=t.getVecChannels=void 0;const s=i(9390);function u(d,a){return(0,s.getGlChannels)(a).map(h=>`${d}.${h}`)}t.getVecChannels=u,t.getChannels=function(d,a){return a===1?[d]:u(d,a)},t.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:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parsePadAttributesV11=t.padV11=t.parsePadAttributesV2=t.padV2=void 0;const s=i(246),u=i(2517),d=i(5060),a=i(2039),h={name:"Pad",inputNames:["A"],inputTypes:[a.TextureType.unpacked]};t.padV2=(g,_,b)=>(l(_),[g.run(Object.assign(Object.assign({},h),{cacheHint:b.cacheKey,get:()=>c(g,_[0],b)}),_)]),t.parsePadAttributesV2=g=>{const _=g.attributes.getString("mode","constant"),b=g.attributes.getFloat("value",0),y=g.attributes.getInts("pads");return(0,s.createAttributeWithCacheKey)({mode:_,value:b,pads:y})},t.padV11=(g,_,b)=>{n(_);const y=f(g,_,b);return(0,t.padV2)(g,[_[0]],y)},t.parsePadAttributesV11=g=>g.attributes.getString("mode","constant");const f=(g,_,b)=>{if(!g.session.isInitializer(_[1].dataId)||_.length>=3&&!g.session.isInitializer(_[2].dataId))throw new Error("dynamic pad attributes are not allowed");const y=Array.from(_[1].integerData),w=_.length>=3?_[2].floatData[0]:0;return(0,s.createAttributeWithCacheKey)({mode:b,pads:y,value:w})},c=(g,_,b)=>{const y=u.ShapeUtil.padShape(_.dims.slice(),b.pads),w=y.length,T=` + ${e(g,_,b)} + float process(int[${w}] indices) { + return padA(indices); + }`;return{name:"Pad",inputNames:["A"],inputTypes:[a.TextureType.unpacked],output:{dims:y,type:_.type,textureType:a.TextureType.unpacked},shaderSource:T}},l=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.")},n=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,_,b)=>{const y=(0,d.getGlsl)(g.session.backend.glContext.version),[w,T]=g.calculateTextureWidthAndHeight(_.dims,a.TextureType.unpacked),S=u.ShapeUtil.computeStrides(_.dims);switch(b.mode){case"constant":return r(y,_.dims,S,w,T,b.pads,b.value);case"reflect":return o(y,_.dims,S,w,T,b.pads);case"edge":return p(y,_.dims,S,w,T,b.pads);default:throw new Error("Invalid mode")}},r=(g,_,b,y,w,T,S)=>{const A=_.length;let P="";for(let x=A-1;x>=0;--x)P+=` + k = m[${x}] - ${T[x]}; + if (k < 0) return constant; + if (k >= ${_[x]}) return constant; + offset += k * ${b[x]}; + `;return` + float padA(int m[${A}]) { + const float constant = float(${S}); + int offset = 0; + int k = 0; + ${P} + vec2 coords = offsetToCoords(offset, ${y}, ${w}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `},o=(g,_,b,y,w,T)=>{const S=_.length;let A="";for(let P=S-1;P>=0;--P)A+=` + k = m[${P}] - ${T[P]}; + if (k < 0) { k = -k; } + { + const int _2n_1 = ${2*(_[P]-1)}; + k = int( mod( float(k), float(_2n_1) ) ) ; + if(k >= ${_[P]}) { k = _2n_1 - k; } + } + offset += k * ${b[P]}; + `;return` + float padA(int m[${S}]) { + int offset = 0; + int k = 0; + ${A} + vec2 coords = offsetToCoords(offset, ${y}, ${w}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `},p=(g,_,b,y,w,T)=>{const S=_.length;let A="";for(let P=S-1;P>=0;--P)A+=` + k = m[${P}] - ${T[P]}; + if (k < 0) k = 0; + if (k >= ${_[P]}) k = ${_[P]-1}; + offset += k * ${b[P]}; + `;return` + float padA(int m[${S}]) { + int offset = 0; + int k = 0; + ${A} + vec2 coords = offsetToCoords(offset, ${y}, ${w}); + float value = getColorAsFloat(${g.texture2D}(A, coords)); + return value; + } + `}},2143:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.globalMaxPool=t.parseMaxPoolAttributes=t.maxPool=t.parseGlobalAveragePoolAttributes=t.globalAveragePool=t.parseAveragePoolAttributes=t.averagePool=void 0;const s=i(246),u=i(2517),d=i(2039);t.averagePool=(p,g,_)=>{n(g);const b={name:"AveragePool",inputNames:["X"],inputTypes:[d.TextureType.unpacked],cacheHint:_.cacheKey};return[p.run(Object.assign(Object.assign({},b),{get:()=>a(g,b,!1,_)}),g)]},t.parseAveragePoolAttributes=p=>{const g=p.attributes.getString("auto_pad","NOTSET"),_=p.attributes.getInt("ceil_mode",0),b=p.attributes.getInt("count_include_pad",0)!==0,y=p.attributes.getInts("kernel_shape"),w=p.attributes.getInts("strides",[]),T=p.attributes.getInts("pads",[]);if(_!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,s.createAttributeWithCacheKey)({autoPad:g,ceilMode:_,countIncludePad:b,kernelShape:y,strides:w,pads:T})};const a=(p,g,_,b)=>{const[y,w]=f(p,b,_),T=u.ShapeUtil.size(y.kernelShape);let S="";y.countIncludePad?S+=`value /= float(${T});`:S+=`value /= float(${T} - pad);`;const A=` + ${e(p[0].dims,y,"value += _X(x);",S,"0.0")} + `;return Object.assign(Object.assign({},g),{output:{dims:w,type:p[0].type,textureType:d.TextureType.unpacked},shaderSource:A})};t.globalAveragePool=(p,g,_)=>{n(g);const b={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[d.TextureType.unpacked],cacheHint:`${_.countIncludePad}`};return[p.run(Object.assign(Object.assign({},b),{get:()=>a(g,b,!0,_)}),g)]},t.parseGlobalAveragePoolAttributes=p=>{const g=p.attributes.getInt("count_include_pad",0)!==0;return(0,s.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:g,kernelShape:[],strides:[],pads:[]})},t.maxPool=(p,g,_)=>{n(g);const b={name:"MaxPool",inputNames:["X"],inputTypes:[d.TextureType.unpacked],cacheHint:_.cacheKey};return[p.run(Object.assign(Object.assign({},b),{get:()=>h(g,b,!1,_)}),g)]},t.parseMaxPoolAttributes=p=>{const g=p.attributes.getString("auto_pad","NOTSET"),_=p.attributes.getInt("ceil_mode",0),b=p.attributes.getInts("kernel_shape"),y=p.attributes.getInts("strides",[]),w=p.attributes.getInts("pads",[]),T=p.attributes.getInt("storage_order",0),S=p.attributes.getInts("dilations",[]);if(T!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(_!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return(0,s.createAttributeWithCacheKey)({autoPad:g,ceilMode:_,countIncludePad:!1,kernelShape:b,strides:y,pads:w,storageOrder:T,dilations:S})};const h=(p,g,_,b)=>{const[y,w]=f(p,b,_),T=` + ${e(p[0].dims,y,` + value = max(_X(x), value); + `,"","-1e5")} + `;return Object.assign(Object.assign({},g),{output:{dims:w,type:p[0].type,textureType:d.TextureType.unpacked},shaderSource:T})},f=(p,g,_)=>{const b=p[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();u.PoolConvUtil.adjustPoolAttributes(_,b,w,T,S,A);const P=u.PoolConvUtil.computePoolOutputShape(_,b,T,S,w,A,g.autoPad),x=Object.assign({},g);return y?Object.assign(x,{kernelShape:w,strides:T,pads:A,dilations:S,cacheKey:g.cacheKey}):Object.assign(x,{kernelShape:w,strides:T,pads:A,cacheKey:g.cacheKey}),[x,P]},c={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},l={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[d.TextureType.unpacked]};t.globalMaxPool=(p,g)=>(n(g),[p.run(Object.assign(Object.assign({},l),{get:()=>h(g,l,!0,c)}),g)]);const n=p=>{if(!p||p.length!==1)throw new Error("Pool ops requires 1 input.");if(p[0].type!=="float32"&&p[0].type!=="float64")throw new Error("Invalid input type.")},e=(p,g,_,b,y)=>{const w=p.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],P=g.pads[g.pads.length-1],x=p[w-1];let M="",N="",z="";if(M=A+P!==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] >= ${x}) { + pad++; + continue; + } + ${_} + }`:` + for (int i = 0; i < ${T}; i++) { + x[${w} - 1] = indices[${w} - 1] * ${S} - ${A} + i; + ${_} + }`,g.kernelShape.length===2){const $=g.kernelShape[g.kernelShape.length-2],C=g.strides[g.strides.length-2],G=g.pads[g.pads.length/2-2],D=g.pads[g.pads.length-2],R=p[w-2];N=G+D!==0?` + for (int j = 0; j < ${$}; j++) { + x[${w} - 2] = indices[${w} - 2] * ${C} - ${G} + j; + if (x[${w} - 2] < 0 || x[${w} - 2] >= ${R}) { + pad+= ${T}; + continue; + } + `:` + for (int j = 0; j < ${$}; j++) { + x[${w} - 2] = indices[${w} - 2] * ${C} - ${G} + j; + `,z=` + } + `}return` + float process(int indices[${w}]) { + int x[${w}]; + copyVec(indices, x); + + float value = ${y}; + int pad = 0; + ${N} + ${M} + ${z} + ${b} + return value; + } + `}{const T=u.ShapeUtil.size(g.kernelShape),S=u.ShapeUtil.computeStrides(g.kernelShape),A=S.length,P=g.pads.length,x=o(A),M=r(p,"inputDims"),N=r(g.pads,"pads"),z=r(S,"kernelStrides"),$=r(g.strides,"strides");let C="";return C=g.pads.reduce((G,D)=>G+D)?` + if (x[j] >= inputDims[j] || x[j] < 0) { + pad++; + isPad = true; + break; + } + } + if (!isPad) { + ${_} + }`:` + } + ${_} + `,` + ${x} + float process(int indices[${w}]) { + int x[${w}]; + copyVec(indices, x); + int offset[${A}]; + int pads[${P}]; + int inputDims[${w}]; + int kernelStrides[${A}]; + int strides[${A}]; + ${N} + ${M} + ${$} + ${z} + + 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]; + ${C} + } + ${b} + + return value; + } + `}},r=(p,g)=>{let _="";for(let b=0;b` + void offsetToIndices(int offset, int[${p}] strides, out int[${p}] indices) { + if (${p} == 0) { + return; + } + for (int i = 0; i < ${p} - 1; ++i) { + indices[i] = offset / strides[i]; + offset -= indices[i] * strides[i]; + } + indices[${p} - 1] = offset; + }`},4939:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.reduceLogSumSquare=t.reduceLogSum=t.reduceProd=t.reduceMin=t.reduceMax=t.reduceMean=t.reduceSum=t.parseReduceAttributes=void 0;const s=i(246),u=i(782),d=i(2517),a=i(2039),h=(l,n,e,r,o)=>{c(n);const p={name:r,inputNames:["A"],inputTypes:[a.TextureType.unpacked]};return[l.run(Object.assign(Object.assign({},p),{cacheHint:e.cacheKey,get:()=>f(l,n,e,r,o,p)}),n)]};t.parseReduceAttributes=l=>{const n=l.attributes.getInts("axes",[]),e=l.attributes.getInt("keepdims",1)===1;return(0,s.createAttributeWithCacheKey)({axes:n,keepDims:e})};const f=(l,n,e,r,o,p)=>{const g=[],_=n[0].dims.length||1,b=[],y=d.ShapeUtil.normalizeAxes(e.axes,n[0].dims.length),w=o(n,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} < ${n[0].dims[A]}; j${A}++) { + inputIdx[${A}] = j${A}; + ${T} + }`):(b.push(`inputIdx[${A}] = outputIdx[${g.length}];`),g.push(n[0].dims[A]));const S=` + float process(int outputIdx[${g.length||1}]) { + float value; // final result + int inputIdx[${_}]; // 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({},p),{output:{dims:g,type:n[0].type,textureType:a.TextureType.unpacked},shaderSource:S})},c=l=>{if(!l||l.length!==1)throw new Error("Reduce op requires 1 input.");if(u.NUMBER_TYPES.indexOf(l[0].type)===-1)throw new Error("Invalid input type.")};t.reduceSum=(l,n,e)=>h(l,n,e,"ReduceSum",()=>["value = 0.0;","value += _A(inputIdx);",""]),t.reduceMean=(l,n,e)=>h(l,n,e,"ReduceMean",(r,o)=>{let p=1;for(let g=0;g=0||o.length===0)&&(p*=r[0].dims[g]);return["value = 0.0;","value += _A(inputIdx);",`value /= ${p}.;`]}),t.reduceMax=(l,n,e)=>h(l,n,e,"ReduceMax",(r,o)=>{const p=[];for(let g=0;g=0||o.length===0)&&p.push(`inputIdx[${g}] = 0;`);return[`${p.join(` +`)} +value = _A(inputIdx);`,"value = max(value, _A(inputIdx));",""]}),t.reduceMin=(l,n,e)=>h(l,n,e,"ReduceMin",(r,o)=>{const p=[];for(let g=0;g=0||o.length===0)&&p.push(`inputIdx[${g}] = 0;`);return[`${p.join(` +`)} +value = _A(inputIdx);`,"value = min(value, _A(inputIdx));",""]}),t.reduceProd=(l,n,e)=>h(l,n,e,"ReduceProd",()=>["value = 1.0;","value *= _A(inputIdx);",""]),t.reduceLogSum=(l,n,e)=>h(l,n,e,"ReduceLogSum",()=>["value = 0.0;","value += _A(inputIdx);","value = log(value);"]),t.reduceLogSumSquare=(l,n,e)=>h(l,n,e,"ReduceLogSumSquare",()=>["float t; value = 0.0;","t = _A(inputIdx); value += t * t;",""])},7019:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.isReshapeCheap=t.processDims3D=t.createPackedReshape3DProgramInfoLoader=void 0;const s=i(2517),u=i(5060),d=i(2039),a=i(2827);t.createPackedReshape3DProgramInfoLoader=(h,f,c)=>{const l=(n=>({name:"Reshape (packed)",inputTypes:[d.TextureType.packed],inputNames:["A"],cacheHint:`${n}`}))(c);return Object.assign(Object.assign({},l),{get:()=>((n,e,r,o)=>{const p=e.dims,g=o;let _="";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}_+=` + ${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,u.getGlsl)(n.session.backend.glContext.version),y=` + ${function(w){const T=s.ShapeUtil.computeStrides(w),S=["b","r","c"],A="index";return` + ivec3 inputCoordsFromReshapedOutCoords(int index) { + ${T.map((P,x)=>`int ${S[x]} = ${A} / ${P}; ${x===T.length-1?`int ${S[x+1]} = ${A} - ${S[x]} * ${P}`:`index -= ${S[x]} * ${P}`};`).join("")} + return ivec3(b, r, c); + } + `}(p)} + ${function(w){const T=s.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,a.unpackFromChannel)()} + + void main() { + ivec3 rc = getOutputCoords(); + + vec4 result = vec4(0.0); + + ivec3 outputCoords; + int rows = ${g[2]}; + int cols = ${g[1]}; + + ${_} + ${b.output} = result; + } + `;return Object.assign(Object.assign({},r),{output:{dims:g,type:e.type,textureType:d.TextureType.packed},shaderSource:y,hasMain:!0})})(h,f,l,c)})},t.processDims3D=function(h){if(h.length===0)return[1,1,1];let f=1;for(let c=0;c1?h[h.length-2]:1,h[h.length-1]]},t.isReshapeCheap=function(h,f){let c=!1;return c=h.length===0||f.length===0||(h.length<2||f.length<2?h[h.length-1]===f[f.length-1]:h[h.length-1]===f[f.length-1]&&h[h.length-2]===f[f.length-2]),c}},718:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.reshape=void 0;const s=i(2517);t.reshape=(u,d)=>{const a=s.ShapeUtil.calculateReshapedDims(d[0].dims,d[1].integerData);return u.session.pack?[u.reshapePacked(d[0],a)]:[u.reshapeUnpacked(d[0],a)]}},2268:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseResizeAttributesV11=t.parseResizeAttributesV10=t.resize=void 0;const s=i(5060),u=i(2039),d=i(9390),a=i(2827),h=i(9793),f={name:"Resize",inputNames:["A"],inputTypes:[u.TextureType.packed]};t.resize=(r,o,p)=>((0,h.validateInputs)(o,p),[r.run(Object.assign(Object.assign({},f),{cacheHint:p.cacheKey,get:()=>c(r,o,p)}),o)]),t.parseResizeAttributesV10=r=>(0,h.parseUpsampleAttributes)(r,10),t.parseResizeAttributesV11=r=>(0,h.parseUpsampleAttributes)(r,11);const c=(r,o,p)=>{const g=(0,s.getGlsl)(r.session.backend.glContext.version),[_,b]=l(o,p);if(_.every(C=>C===1)&&p.coordinateTransformMode!=="tf_crop_and_resize")return Object.assign(Object.assign({},f),{output:{dims:b,type:o[0].type,textureType:u.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=o[0].dims;if(y!==S.length)throw new Error(`output dimension should match input ${S.length}, but got ${y}`);const A=S[y-2],P=S[y-1],x=_[y-2],M=_[y-1];let N="";if(p.mode!=="linear")throw new Error(`resize (packed) does not support mode: '${p.mode}'`);switch(p.coordinateTransformMode){case"asymmetric":N=` + vec4 getSourceFracIndex(ivec4 coords) { + return vec4(coords) / scaleWHWH; + } + `;break;case"half_pixel":N=` + vec4 getSourceFracIndex(ivec4 coords) { + return (vec4(coords) + 0.5) / scaleWHWH - 0.5; + } + `;break;case"pytorch_half_pixel":N=` + vec4 getSourceFracIndex(ivec4 coords) { + vec4 fcoords = vec4(coords); + return vec4( + ${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, + ${w}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0 + ); + } + `;break;case"align_corners":N=` + vec4 getSourceFracIndex(ivec4 coords) { + vec4 resized = vec4(${T}.0 - 1.0, ${w}.0 - 1.0, ${T}.0 - 1.0, + ${w}.0 - 1.0); + vec4 original = vec4(${P}.0 - 1.0, ${A}.0 - 1.0, ${P}.0 - 1.0, + ${A}.0 - 1.0); + vec4 new_scale = original / resized; + return vec4(coords) * new_scale; + } + `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode: '${p.coordinateTransformMode}'`)}const z=(0,d.getCoordsDataType)(y),$=` + const vec2 inputWH = vec2(${A}.0, ${P}.0); + const vec4 scaleWHWH = vec4(float(${x}), float(${M}), float(${x}), float(${M})); + ${(0,a.unpackFromChannel)()} + ${N} + float getAValue(int x10, int r, int c, int d) { + return getChannel(getA(x10, r, c, d), vec2(c, d)); + } + void main() { + ${z} 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); + + ${g.output} = vec4(newValue); + } + `;return Object.assign(Object.assign({},f),{output:{dims:b,type:o[0].type,textureType:u.TextureType.packed},hasMain:!0,shaderSource:$})},l=(r,o)=>{const p=r[0].dims;let g,_=o.scales;if(_.length===0){const y=r[o.scalesInputIdx];if(y&&y.size!==0){if(r[o.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");_=n(y,o.mode,o.isResize)}else{const w=r[o.sizesInputIdx];if(!w||w.size===0)throw new Error("Either scales or sizes MUST be provided as input.");g=Array.from(w.integerData),_=e(g,p,o.mode,o.isResize)}}else if(r[o.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");const b=g||p.map((y,w)=>Math.floor(y*_[w]));return[_,b]},n=(r,o,p)=>{const g=Array.from(r.floatData);return(0,h.scalesValidation)(g,o,p),g},e=(r,o,p,g)=>{const _=o.length,b=new Array(_);for(let y=0,w=_;y{Object.defineProperty(t,"__esModule",{value:!0}),t.shape=void 0;const s=i(9162);t.shape=(d,a)=>(u(a),[new s.Tensor([a[0].dims.length],"int32",void 0,void 0,new Int32Array(a[0].dims))]);const u=d=>{if(!d||d.length!==1)throw new Error("Shape requires 1 input.")}},2278:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.sliceV10=t.parseSliceAttributes=t.slice=void 0;const s=i(246),u=i(782),d=i(2517),a=i(2039),h={name:"Slice",inputNames:["A"],inputTypes:[a.TextureType.unpacked]};t.slice=(e,r,o)=>(c(r),[e.run(Object.assign(Object.assign({},h),{cacheHint:o.cacheKey,get:()=>f(e,r[0],o)}),r)]),t.parseSliceAttributes=e=>{const r=e.attributes.getInts("starts"),o=e.attributes.getInts("ends"),p=e.attributes.getInts("axes",[]);return(0,s.createAttributeWithCacheKey)({starts:r,ends:o,axes:p})};const f=(e,r,o)=>{const p=o.axes.length===0?r.dims.slice(0).map((S,A)=>A):o.axes,g=d.ShapeUtil.normalizeAxes(p,r.dims.length),_=o.starts.map((S,A)=>S>r.dims[g[A]]-1?r.dims[g[A]]:d.ShapeUtil.normalizeAxis(S,r.dims[g[A]])),b=o.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]}] += ${_[S]};`);const T=` + float process(int outputIdx[${y.length}]) { + ${w.join(` + `)} + return _A(outputIdx); + }`;return Object.assign(Object.assign({},h),{output:{dims:y,type:r.type,textureType:a.TextureType.unpacked},shaderSource:T})},c=e=>{if(!e||e.length!==1)throw new Error("Slice requires 1 input.");if(u.NUMBER_TYPES.indexOf(e[0].type)===-1)throw new Error("Invalid input type.")};t.sliceV10=(e,r)=>{n(r);const o=l(e,r);return[e.run(Object.assign(Object.assign({},h),{cacheHint:o.cacheKey,get:()=>f(e,r[0],o)}),[r[0]])]};const l=(e,r)=>{if(!e.session.isInitializer(r[1].dataId)||!e.session.isInitializer(r[2].dataId)||r.length>=4&&!e.session.isInitializer(r[3].dataId)||r.length>=5&&!e.session.isInitializer(r[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(r.length>=5&&r[4].integerData.some(_=>_!==1))throw new Error("currently non-1 steps is not supported for Slice");const o=Array.from(r[1].integerData),p=Array.from(r[2].integerData),g=r.length>=4?Array.from(r[3].integerData):[];return{starts:o,ends:p,axes:g,cacheKey:`${g};${o};${p}`}},n=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:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.softmaxV13=t.parseSoftmaxAttributesV13=t.parseSoftmaxAttributes=t.softmax=void 0;const s=i(246),u=i(2517),d=i(5060),a=i(2039),h=i(3738),f={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[a.TextureType.unpacked]},c={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked]},l={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked,a.TextureType.unpacked]};t.softmax=(g,_,b)=>{p(_);const y=_[0].dims.slice(),w=u.ShapeUtil.normalizeAxis(b.axis,y.length),T=u.ShapeUtil.sizeToDimension(y,w),S=u.ShapeUtil.sizeFromDimension(y,w);return n(g,_,b,T,S)},t.parseSoftmaxAttributes=g=>(0,s.createAttributeWithCacheKey)({axis:g.attributes.getInt("axis",1)}),t.parseSoftmaxAttributesV13=g=>(0,s.createAttributeWithCacheKey)({axis:g.attributes.getInt("axis",-1)}),t.softmaxV13=(g,_,b)=>{p(_);const y=_[0].dims.slice(),w=u.ShapeUtil.normalizeAxis(b.axis,y.length),T=y.length,S=w!==T-1,A=[];let P,x=[],M=[];S&&(x=Array.from({length:T}).map((C,G)=>G),x[w]=T-1,x[T-1]=w,x.map(C=>A.push(y[C])),P=(0,s.createAttributeWithCacheKey)({perm:x}),M=(0,h.transpose)(g,_,P));const N=S?u.ShapeUtil.sizeToDimension(A,T-1):u.ShapeUtil.sizeToDimension(y,T-1),z=S?u.ShapeUtil.sizeFromDimension(A,T-1):u.ShapeUtil.sizeFromDimension(y,T-1),$=n(g,S?M:_,b,N,z);return S?(0,h.transpose)(g,$,P):$};const n=(g,_,b,y,w)=>{const T=e(g,_[0],y,w,[y]),S=g.run(Object.assign(Object.assign({},f),{cacheHint:b.cacheKey,get:()=>T}),_),A=r(g,_[0],y,w,T.output.dims,[y]),P=g.run(Object.assign(Object.assign({},c),{cacheHint:b.cacheKey,get:()=>A}),[_[0],S]),x=o(g,_[0],y,w,T.output.dims,A.output.dims);return[g.run(Object.assign(Object.assign({},l),{cacheHint:b.cacheKey,get:()=>x}),[_[0],S,P])]},e=(g,_,b,y,w)=>{const[T,S]=g.calculateTextureWidthAndHeight(_.dims,a.TextureType.unpacked),A=w.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(w.length!==1)throw new Error("Dimensionality of the output should be 1");if(w[0]!==b)throw new Error("Shape of the output should be equal to logical row count");const P=(0,d.getGlsl)(g.session.backend.glContext.version),x=` + float process(int[${A}] indices) { + int logical_row_start_offset = indices[0] * ${y}; + + float max = getColorAsFloat(${P.texture2D}(A, offsetToCoords(logical_row_start_offset, ${T}, + ${S} ))); + for(int i=1; i<${y}; ++i) + { + float current = getColorAsFloat(${P.texture2D}(A, offsetToCoords(logical_row_start_offset + i, + ${T}, ${S}))); + if(current > max) + max = current; + } + + return max; + }`;return Object.assign(Object.assign({},f),{output:{dims:w,type:_.type,textureType:a.TextureType.unpacked},shaderSource:x})},r=(g,_,b,y,w,T)=>{const[S,A]=g.calculateTextureWidthAndHeight(_.dims,a.TextureType.unpacked),P=T.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(T.length!==1)throw new Error("Dimensionality of the output should be 1");if(T[0]!==b)throw new Error("Shape of the output should be equal to logical row count");if(w.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(w[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const x=` + float process(int[${P}] 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}, ${A}))) - max); + } + + return norm_factor; + }`;return Object.assign(Object.assign({},c),{output:{dims:T,type:_.type,textureType:a.TextureType.unpacked},shaderSource:x})},o=(g,_,b,y,w,T)=>{const[S,A]=g.calculateTextureWidthAndHeight(_.dims,a.TextureType.unpacked),P=_.dims.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(w.length!==1||T.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(w[0]!==b||T[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const x=` + float process(int[${P}] 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 / ${y}; + + float norm_factor = _Norm(logical_row_index); + + // avoid possible division by 0 + // if norm_facor is 0, all elements are zero + // if so, return 0 + if(norm_factor == 0.0) + return 0.0; + + return exp(_A(indices) - _Max(logical_row_index)) / norm_factor; + }`;return Object.assign(Object.assign({},l),{output:{dims:_.dims,type:_.type,textureType:a.TextureType.unpacked},shaderSource:x})},p=g=>{if(!g||g.length!==1)throw new Error("Softmax requires 1 input.");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type")}},5975:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseSplitAttributes=t.split=void 0;const s=i(246),u=i(2517),d=i(2039),a={name:"Split",inputNames:["A"],inputTypes:[d.TextureType.unpacked]};t.split=(l,n,e)=>{c(n);const r=u.ShapeUtil.normalizeAxis(e.axis,n[0].dims.length),o=h(l,n,r,e),p=[];for(let g=0;gf(l,n[0],e,r,g)}),n));return p},t.parseSplitAttributes=l=>{const n=l.attributes.getInt("axis",0),e=l.attributes.getInts("split",[]),r=l.outputs.length;return(0,s.createAttributeWithCacheKey)({axis:n,split:e,numOutputs:r})};const h=(l,n,e,r)=>{const[,o]=u.SplitUtil.splitShape(n[0].dims,e,r.split,r.numOutputs);return o.length},f=(l,n,e,r,o)=>{const[p,g]=u.SplitUtil.splitShape(n.dims,r,e.split,e.numOutputs),_=g[o],b=p[o],y=` + float process(int indices[${b.length}]) { + indices[${r}] += ${_}; + return _A(indices); + } + `;return Object.assign(Object.assign({},a),{cacheHint:`${e.cacheKey}:${o}`,output:{dims:b,type:n.type,textureType:d.TextureType.unpacked},shaderSource:y})},c=l=>{if(!l||l.length!==1)throw new Error("Split requires one input.");if(l[0].type!=="int8"&&l[0].type!=="uint8"&&l[0].type!=="int16"&&l[0].type!=="uint16"&&l[0].type!=="int32"&&l[0].type!=="uint32"&&l[0].type!=="float32"&&l[0].type!=="float64"&&l[0].type!=="bool")throw new Error("Invalid input type.")}},3933:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseSqueezeAttributes=t.squeezeV13=t.squeeze=void 0;const s=i(2517);t.squeeze=(a,h,f)=>{u(h);const c=s.ShapeUtil.squeezeShape(h[0].dims,f);return[a.reshapeUnpacked(h[0],c)]},t.squeezeV13=(a,h)=>(d(h),(0,t.squeeze)(a,[h[0]],Array.from(h[1].integerData))),t.parseSqueezeAttributes=a=>a.attributes.getInts("axes");const u=a=>{if(!a||a.length!==1)throw new Error("Squeeze requires 1 input.");if(a[0].type==="string")throw new Error("invalid input tensor types.")},d=a=>{if(!a||a.length!==2)throw new Error("Squeeze requires 2 inputs.");if(a[1].type!=="int32")throw new Error("Invalid input type.")}},6558:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.sum=void 0;const s=i(5060),u=i(2039);t.sum=(h,f)=>{a(f);const c={name:"Sum",inputNames:f.map((l,n)=>`X${n}`),inputTypes:new Array(f.length).fill(u.TextureType.unpacked)};return[h.run(Object.assign(Object.assign({},c),{get:()=>d(h,f,c)}),f)]};const d=(h,f,c)=>{const l=(0,s.getGlsl)(h.session.backend.glContext.version),n=f[0].dims.slice(),e=` + void main() { + vec4 result = ${f.map((r,o)=>`${l.texture2D}(X${o},TexCoords)`).join(" + ")}; + ${l.output} = result; + } + `;return Object.assign(Object.assign({},c),{output:{dims:n,type:f[0].type,textureType:u.TextureType.unpacked},hasMain:!0,shaderSource:e})},a=h=>{if(!h||h.length===0)throw new Error("Sum requires inputs.");const f=h[0].dims.length;for(let c=1;c{Object.defineProperty(t,"__esModule",{value:!0}),t.tile=void 0;const s=i(782),u=i(2039);t.tile=(h,f)=>{a(f);const c={name:"Tile",inputNames:["A"],inputTypes:[u.TextureType.unpacked]};return[h.run(Object.assign(Object.assign({},c),{get:()=>d(h,f,c)}),f)]};const d=(h,f,c)=>{const l=f[0].dims.slice(),n=new Array(l.length),e=[];for(let p=0;p{if(!h||h.length!==2)throw new Error("Tile requires 2 input.");if(h[1].dims.length!==1)throw new Error("The second input shape must 1 dimension.");if(h[1].dims[0]!==h[0].dims.length)throw new Error("Invalid input shape.");if(s.NUMBER_TYPES.indexOf(h[0].type)===-1)throw new Error("Invalid input type.");if(h[1].type!=="int32"&&h[1].type!=="int16")throw new Error("Invalid repeat type.")}},3738:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseTransposeAttributes=t.transpose=void 0;const s=i(246),u=i(2517),d=i(2039),a={name:"Transpose",inputNames:["A"],inputTypes:[d.TextureType.unpacked]};t.transpose=(e,r,o)=>(n(r),[e.run(Object.assign(Object.assign({},a),{cacheHint:o.cacheKey,get:()=>h(e,r[0],o.perm)}),r)]),t.parseTransposeAttributes=e=>(0,s.createAttributeWithCacheKey)({perm:e.attributes.getInts("perm",[])});const h=(e,r,o)=>{const p=r.dims;o=f(p,o);const g=c(p,o),_=p.length,b=` + ${l("perm",o,_)} + float process(int indices[${_}]) { + int a[${_}]; + perm(a, indices); + return _A(a); + }`;return Object.assign(Object.assign({},a),{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),u.ShapeUtil.sortBasedOnPerm(e,r)),l=(e,r,o)=>{const p=[];p.push(`void ${e}(out int a[${o}], int src[${o}]) {`);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:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.encodeAsUint8=void 0;const s=i(5060),u=i(2039);t.encodeAsUint8=(d,a)=>{const h=a.shape,f=(0,s.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); + }`,l={name:"Uint8Encode",inputTypes:[u.TextureType.unpacked],inputNames:["X"],output:{dims:h,type:a.tensor.type,textureType:u.TextureType.downloadUint8AsFloat},shaderSource:c,hasMain:!0};return d.executeProgram(l,[a.tensor])}},4909:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.tanh=t.tan=t.sqrt=t.sin=t.sigmoid=t.relu=t.not=t.neg=t.log=t.parseLeakyReluAttributes=t.leakyRelu=t.identity=t.floor=t.exp=t.parseEluAttributes=t.elu=t.cos=t.ceil=t.clipV11=t.parseClipAttributes=t.clip=t.atan=t.asin=t.acos=t.abs=t.glslTanh=t.glslTan=t.glslSqrt=t.glslSigmoid=t.glslRelu=t.glslSin=t.glslNot=t.glslNeg=t.glslLog=t.glslLeakyRelu=t.glslIdentity=t.glslClip=t.glslFloor=t.glslExp=t.glslElu=t.glslCos=t.glslCeil=t.glslAtan=t.glslAsin=t.glslAcos=t.glslAbs=void 0;const s=i(246),u=i(2517),d=i(8520),a=i(5060),h=i(2039);function f(){return $("abs")}function c(){return $("acos")}function l(){return $("asin")}function n(){return $("atan")}function e(){return $("ceil")}function r(){return $("cos")}function o(D){const R="elu";return{body:` + const float alpha = float(${D}); + + float ${R}_(float a) { + return a >= 0.0 ? a: (exp(a) - 1.0) * alpha; + } + vec4 ${R}_(vec4 v) { + return vec4(${R}_(v.x), ${R}_(v.y), ${R}_(v.z), ${R}_(v.w)); + } + `,name:R,type:d.FunctionType.ValueBased}}function p(){return $("exp")}function g(){return $("floor")}function _(D,R){const Y="clip";return{body:` + const float min = float(${D}); + const float max = float(${R}); + + float ${Y}_(float a) { + return clamp(a, min, max); + } + vec4 ${Y}_(vec4 v) { + return clamp(v, min, max); + } + `,name:Y,type:d.FunctionType.ValueBased}}function b(){const D="indentity";return{body:` + float ${D}_(float a) { + return a; + } + vec4 ${D}_(vec4 v) { + return v; + } + `,name:D,type:d.FunctionType.ValueBased}}function y(D){const R="leakyRelu";return{body:` + const float alpha = float(${D}); + + float ${R}_(float a) { + return a < 0.0 ? a * alpha : a; + } + vec4 ${R}_(vec4 v) { + return vec4(${R}_(v.x), ${R}_(v.y), ${R}_(v.z), ${R}_(v.w)); + } + `,name:R,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 P(){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 x(){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 N(){return $("tan")}function z(){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}}t.glslAbs=f,t.glslAcos=c,t.glslAsin=l,t.glslAtan=n,t.glslCeil=e,t.glslCos=r,t.glslElu=o,t.glslExp=p,t.glslFloor=g,t.glslClip=_,t.glslIdentity=b,t.glslLeakyRelu=y,t.glslLog=w,t.glslNeg=T,t.glslNot=S,t.glslSin=A,t.glslRelu=P,t.glslSigmoid=x,t.glslSqrt=M,t.glslTan=N,t.glslTanh=z;const C=(D,R,Y,V)=>{const J=D.session.pack?h.TextureType.packed:h.TextureType.unpacked,Z={name:Y.name,inputTypes:[J],inputNames:["A"],cacheHint:V};return Object.assign(Object.assign({},Z),{get:()=>((le,Ae,xe,se)=>{const we=le.session.pack?h.TextureType.packed:h.TextureType.unpacked,be=(0,a.getGlsl)(le.session.backend.glContext.version);return Object.assign(Object.assign({},Ae),{output:{dims:xe.dims,type:xe.type,textureType:we},shaderSource:` + ${se.body} + void main() { + vec4 v = ${be.texture2D}(A, TexCoords); + v = ${se.name}_(v); + ${be.output} = v; + } + `,hasMain:!0})})(D,Z,R,Y)})};t.abs=(D,R)=>[D.run(C(D,R[0],f()),R)],t.acos=(D,R)=>[D.run(C(D,R[0],c()),R)],t.asin=(D,R)=>[D.run(C(D,R[0],l()),R)],t.atan=(D,R)=>[D.run(C(D,R[0],n()),R)],t.clip=(D,R,Y)=>[D.run(C(D,R[0],_(Y.min,Y.max),Y.cacheKey),R)],t.parseClipAttributes=D=>(0,s.createAttributeWithCacheKey)({min:D.attributes.getFloat("min",u.MIN_CLIP),max:D.attributes.getFloat("max",u.MAX_CLIP)}),t.clipV11=(D,R)=>{const Y=G(D,R);return(0,t.clip)(D,[R[0]],Y)};const G=(D,R)=>{if(R.length>=3&&(!D.session.isInitializer(R[1].dataId)||!D.session.isInitializer(R[2].dataId)))throw new Error("dynamic clip attributes are not allowed");const Y=R.length>=3?R[1].numberData[0]:u.MIN_CLIP,V=R.length>=3?R[2].numberData[0]:u.MAX_CLIP;return(0,s.createAttributeWithCacheKey)({min:Y,max:V})};t.ceil=(D,R)=>[D.run(C(D,R[0],e()),R)],t.cos=(D,R)=>[D.run(C(D,R[0],r()),R)],t.elu=(D,R,Y)=>[D.run(C(D,R[0],o(Y.alpha),Y.cacheKey),R)],t.parseEluAttributes=D=>(0,s.createAttributeWithCacheKey)({alpha:D.attributes.getFloat("alpha",1)}),t.exp=(D,R)=>[D.run(C(D,R[0],p()),R)],t.floor=(D,R)=>[D.run(C(D,R[0],g()),R)],t.identity=(D,R)=>[D.run(C(D,R[0],b()),R)],t.leakyRelu=(D,R,Y)=>[D.run(C(D,R[0],y(Y.alpha),Y.cacheKey),R)],t.parseLeakyReluAttributes=D=>(0,s.createAttributeWithCacheKey)({alpha:D.attributes.getFloat("alpha",.01)}),t.log=(D,R)=>[D.run(C(D,R[0],w()),R)],t.neg=(D,R)=>[D.run(C(D,R[0],T()),R)],t.not=(D,R)=>[D.run(C(D,R[0],S()),R)],t.relu=(D,R)=>[D.run(C(D,R[0],P()),R)],t.sigmoid=(D,R)=>[D.run(C(D,R[0],x()),R)],t.sin=(D,R)=>[D.run(C(D,R[0],A()),R)],t.sqrt=(D,R)=>[D.run(C(D,R[0],M()),R)],t.tan=(D,R)=>[D.run(C(D,R[0],N()),R)],t.tanh=(D,R)=>[D.run(C(D,R[0],z()),R)]},5611:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createUnpackProgramInfoLoader=t.createUnpackProgramInfo=void 0;const s=i(5060),u=i(2039),d=i(9390),a=i(2827),h={name:"unpack",inputNames:["A"],inputTypes:[u.TextureType.packed]};t.createUnpackProgramInfo=(f,c)=>{const l=c.dims.length,n=(0,a.getChannels)("rc",l),e=n.slice(-2),r=(0,d.getCoordsDataType)(l),o=(0,a.unpackFromChannel)(),p=c.dims.length===0?"":function(b,y){if(b===1)return"rc";let w="";for(let T=0;TObject.assign(Object.assign({},h),{get:()=>(0,t.createUnpackProgramInfo)(f,c)})},8428:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseUnsqueezeAttributes=t.unsqueezeV13=t.unsqueeze=void 0;const s=i(2517);t.unsqueeze=(a,h,f)=>{u(h);const c=s.ShapeUtil.unsqueezeShape(h[0].dims,f);return[a.reshapeUnpacked(h[0],c)]},t.unsqueezeV13=(a,h)=>(d(h),(0,t.unsqueeze)(a,[h[0]],Array.from(h[1].integerData))),t.parseUnsqueezeAttributes=a=>a.attributes.getInts("axes");const u=a=>{if(!a||a.length!==1)throw new Error("Unsqueeze requires 1 input.");if(a[0].type==="string")throw new Error("invalid input tensor 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r=f.attributes.getFloat("extrapolation_value",0),o=c>10?f.attributes.getString("coordinate_transformation_mode","half_pixel"):"asymmetric";if(["asymmetric","pytorch_half_pixel","tf_half_pixel_for_nn","align_corners","tf_crop_and_resize","half_pixel"].indexOf(o)===-1)throw new Error(`coordinate_transform_mode '${o}' is not supported`);const p=o==="tf_crop_and_resize",g=p,_=n==="nearest"&&c>=11?f.attributes.getString("nearest_mode","round_prefer_floor"):"";if(["round_prefer_floor","round_prefer_ceil","floor","ceil",""].indexOf(_)===-1)throw new Error(`nearest_mode '${_}' is not supported`);const b=f.attributes.getFloat("cubic_coeff_a",-.75),y=f.attributes.getInt("exclude_outside",0)!==0;if(y&&n!=="cubic")throw new Error("exclude_outside can be set to 1 only when mode is CUBIC.");const w=c<11||n==="nearest"&&o==="asymmetric"&&_==="floor";let T=0,S=0,A=0;return c>10?f.inputs.length>2?(T=1,S=2,A=3):(S=1,A=2):c===9&&(S=1),(0,s.createAttributeWithCacheKey)({opset:c,isResize:l,mode:n,scales:e,extrapolationValue:r,coordinateTransformMode:o,useExtrapolation:g,needRoiInput:p,nearestMode:_,cubicCoefficientA:b,excludeOutside:y,useNearest2xOptimization:w,roiInputIdx:T,scalesInputIdx:S,sizesInputIdx:A})};const h=(f,c,l)=>{const n=(0,u.getGlsl)(f.session.backend.glContext.version),[e,r]=f.calculateTextureWidthAndHeight(c[0].dims,d.TextureType.unpacked),o=c[0].dims.map((A,P)=>Math.floor(A*l.scales[P])),[p,g]=f.calculateTextureWidthAndHeight(o,d.TextureType.unpacked),_=o.length,b=new Array(_),y=new Array(_);let w=` + int output_pitches[${_}]; + int input_pitches[${_}]; + `;for(let A=_-1;A>=0;A--)b[A]=A===_-1?1:b[A+1]*o[A+1],y[A]=A===_-1?1:y[A+1]*c[0].dims[A+1],w+=` + output_pitches[${A}] = ${b[A]}; + input_pitches[${A}] = ${y[A]}; + `;const T=` + float getInputFloat(int index) { + vec2 coords = offsetToCoords(index, ${e}, ${r}); + float value = getColorAsFloat(${n.texture2D}(X, coords)); + return value; + } + `,S=l.mode==="nearest"?` + ${T} + float process(int indices[${_}]) { + int input_index = 0; + int output_index = coordsToOffset(TexCoords, ${p}, ${g}); + + ${w} + + int d, m; + for (int dim = 0; dim < ${_}; ++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); + }`:_===4?` + ${T} + float process(int indices[4]) { + int input_index = 0; + int output_index = coordsToOffset(TexCoords, ${p}, ${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, ${p}, ${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({},a),{output:{dims:o,type:c[0].type,textureType:d.TextureType.unpacked},shaderSource:S,variables:[{name:"scales",type:"int",arrayLength:l.scales.length,data:l.scales.map(A=>Math.ceil(A))}]})};t.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.")},t.scalesValidation=(f,c,l)=>{if(l){for(const n of f)if(n<=0)throw new Error("Scale value should be greater than 0.")}else for(const n of f)if(n<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 being 1 in the ${l?"Resize":"Upsample"} opeartor.`)}},1958:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ProgramManager=void 0;const s=i(1670),u=i(6231),d=i(8879),a=i(5060);t.ProgramManager=class{constructor(h,f,c){this.profiler=h,this.glContext=f,this.textureLayoutStrategy=c,this.repo=new Map,this.attributesBound=!1}getArtifact(h){return this.repo.get(h)}setArtifact(h,f){this.repo.set(h,f)}run(h,f,c){var l;this.profiler.event("op",`ProgramManager.run ${(l=h.programInfo.name)!==null&&l!==void 0?l:"unknown kernel"}`,()=>{var n;const e=this.glContext.gl,r=h.program;e.useProgram(r);try{this.bindOutput(c),this.attributesBound||this.bindAttributes(h.attribLocations),this.bindUniforms(h.uniformLocations,(n=h.programInfo.variables)!==null&&n!==void 0?n:[],f)}catch(o){throw 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f=this.glContext.compileShader(h,this.glContext.gl.FRAGMENT_SHADER),c=this.glContext.createProgram(this.vertexShader,f);return this.glContext.deleteShader(f),c}bindOutput(h){const f=h.width,c=h.height;u.Logger.verbose("ProrgramManager",`Binding output texture to Framebuffer: w/h=${f}/${c}, shape=${h.shape}, type=${h.tensor.type}`),this.glContext.attachFramebuffer(h.texture,f,c)}bindAttributes(h){const f=h.position,c=h.textureCoord;this.glContext.setVertexAttributes(f,c),this.attributesBound=!0}bindUniforms(h,f,c){var l;const n=this.glContext.gl;let e=0;for(const{name:r,type:o,location:p,arrayLength:g}of h){const _=(l=f.find(b=>b.name===r))===null||l===void 0?void 0:l.data;if(o!=="sampler2D"&&!_)throw new Error(`variable '${r}' does not have data defined in program info`);switch(o){case"sampler2D":this.bindTexture(c[e],p,e),e++;break;case"float":g?n.uniform1fv(p,_):n.uniform1f(p,_);break;case"int":g?n.uniform1iv(p,_):n.uniform1i(p,_);break;default:throw new Error(`Uniform not implemented: ${o}`)}}}bindTexture(h,f,c){this.glContext.bindTextureToUniform(h.texture,c,f)}getAttribLocations(h){return{position:this.getAttribLocation(h,"position"),textureCoord:this.getAttribLocation(h,"textureCoord")}}getUniformLocations(h,f,c){const l=[];if(f)for(const n of f)l.push({name:n,type:"sampler2D",location:this.getUniformLocation(h,n)});if(c)for(const n of c)l.push(Object.assign(Object.assign({},n),{location:this.getUniformLocation(h,n.name)}));return l}getUniformLocation(h,f){const c=this.glContext.gl.getUniformLocation(h,f);if(c===null)throw new Error(`Uniform ${f} not found.`);return c}getAttribLocation(h,f){return this.glContext.gl.getAttribLocation(h,f)}}},6416:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.WebGLSessionHandler=void 0;const s=i(6231),u=i(1047),d=i(8316),a=i(1640),h=i(1958),f=i(7859),c=i(5702);t.WebGLSessionHandler=class{constructor(l,n){this.backend=l,this.context=n,this.layoutStrategy=new f.PreferLogicalStrategy(l.glContext.maxTextureSize),this.programManager=new h.ProgramManager(this.context.profiler,l.glContext,this.layoutStrategy),this.textureManager=new c.TextureManager(l.glContext,this.layoutStrategy,this.context.profiler,{reuseTextures:l.textureCacheMode==="full"}),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new Map,this.pack=l.pack,this.pack2unpackMap=new Map,this.unpack2packMap=new Map}createInferenceHandler(){return new d.WebGLInferenceHandler(this)}onGraphInitialized(l){const n=l.getValues().filter(e=>e.from===-1&&e.tensor).map(e=>e.tensor.dataId);this.initializers=new Set(n)}isInitializer(l){return!!this.initializers&&this.initializers.has(l)}addInitializer(l){this.initializers.add(l)}getTextureData(l,n){return n?this.packedTextureDataCache.get(l):this.unpackedTextureDataCache.get(l)}setTextureData(l,n,e=!1){s.Logger.verbose("WebGLSessionHandler","Storing Texture data in 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r=this.maxTextureSize;if(n&&n.breakAxis!==void 0){const g=n.breakAxis>=l.length?1:l.slice(n.breakAxis).reduce((b,y)=>b*y),_=n.breakAxis<=0?1:l.slice(0,n.breakAxis).reduce((b,y)=>b*y);if(!(g>r||_>r))return[g,_];s.Logger.verbose("TextureLayout",`Given width/height preferences were unattainable: shape:${l}, breakAxis:${n.breakAxis}`)}let o=l.slice(0);e&&(r*=2,o=o.map((g,_)=>_>=o.length-2?o[_]%2==0?o[_]:o[_]+1:o[_]),o.length===1&&(o=[2,o[0]])),o.length!==2&&(o=d(o).newShape);const p=f(o);return o.length<=1&&p<=r?[1,p]:o.length===2&&o[0]<=r&&o[1]<=r?o:o.length===3&&o[0]*o[1]<=r&&o[2]<=r?[o[0]*o[1],o[2]]:o.length===3&&o[0]<=r&&o[1]*o[2]<=r?[o[0],o[1]*o[2]]:o.length===4&&o[0]*o[1]*o[2]<=r&&o[3]<=r?[o[0]*o[1]*o[2],o[3]]:o.length===4&&o[0]<=r&&o[1]*o[2]*o[3]<=r?[o[0],o[1]*o[2]*o[3]]:e?c(p/4).map(g=>2*g):c(p)}},t.squeezeShape=d,t.parseAxisParam=a,t.isInt=h,t.sizeFromShape=f,t.getRowsCols=function(l){if(l.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[l.length>1?l[l.length-2]:1,l[l.length-1]]},t.sizeToSquarishShape=c,t.getBatchDim=function(l,n=2){return f(l.slice(0,l.length-n))}},4057:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createTextureLayoutFromShape=t.calculateTextureWidthAndHeight=t.createTextureLayoutFromTextureType=void 0;const s=i(2517),u=i(2039);t.createTextureLayoutFromTextureType=(d,a,h)=>{const f=h===u.TextureType.unpacked||h===u.TextureType.unpackedReversed?1:4,c=h===u.TextureType.packed,l=h===u.TextureType.unpackedReversed||h===u.TextureType.packed,n=h===u.TextureType.packedLastDimension?a.length-1:void 0,e=h===u.TextureType.packedLastDimension?a.map((r,o)=>o===a.length-1?4*r:r):void 0;return(0,t.createTextureLayoutFromShape)(d,a,f,e,{isPacked:c,reverseWH:l,breakAxis:n})},t.calculateTextureWidthAndHeight=(d,a,h)=>{const f=(0,t.createTextureLayoutFromTextureType)(d,a,h);return[f.width,f.height]},t.createTextureLayoutFromShape=(d,a,h=1,f,c)=>{const 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0:f.push(c))}return this.profiler.event("backend","TextureManager.readTextureAsync",async()=>{this.pendingRead.set(h,[]);const f=u.shape.reduce((e,r)=>e*r)*a;await this.glContext.createAndWaitForFence();const c=this.glContext.readTexture(u.texture,u.width,u.height,f,this.toEncoderType(d),a),l=this.toTensorData(d,c),n=this.pendingRead.get(h);return this.pendingRead.delete(h),n==null||n.forEach(e=>e(l)),l})}readUint8TextureAsFloat(u){return this.profiler.event("backend","TextureManager.readUint8TextureAsFloat",()=>{const d=u.shape.reduce((h,f)=>h*f),a=this.glContext.readTexture(u.texture,u.width,u.height,4*d,"byte",4);return new Float32Array(a.buffer,a.byteOffset,d)})}releaseTexture(u,d){let a;if(this.config.reuseTextures&&(a=this.textureLookup.get(u.texture),a)){d&&this.textureLookup.delete(a);const h=this.inUseTextures.get(a);if(h){const f=h.indexOf(u.texture);if(f!==-1){h.splice(f,1);let c=this.idleTextures.get(a);c||(c=[],this.idleTextures.set(a,c)),c.push(u.texture)}}}a&&!d||(s.Logger.verbose("TextureManager",`Deleting texture of size ${u.width}x${u.height}`),this.glContext.deleteTexture(u.texture))}toTensorData(u,d){switch(u){case"int16":return d instanceof Int16Array?d:Int16Array.from(d);case"int32":return d instanceof Int32Array?d:Int32Array.from(d);case"int8":return d instanceof Int8Array?d:Int8Array.from(d);case"uint16":return d instanceof Uint16Array?d:Uint16Array.from(d);case"uint32":return d instanceof Uint32Array?d:Uint32Array.from(d);case"uint8":case"bool":return d instanceof Uint8Array?d:Uint8Array.from(d);case"float32":return d instanceof Float32Array?d:Float32Array.from(d);case"float64":return d instanceof Float64Array?d:Float64Array.from(d);default:throw new Error(`TensorData type ${u} is not supported`)}}toTextureData(u,d){if(d)return d instanceof Float32Array?d:new Float32Array(d)}toEncoderType(u){return"float"}clearActiveTextures(){this.glContext.clearActiveTextures()}}},2039:(m,t)=>{var i;Object.defineProperty(t,"__esModule",{value:!0}),t.TextureType=void 0,(i=t.TextureType||(t.TextureType={}))[i.unpacked=0]="unpacked",i[i.unpackedReversed=1]="unpackedReversed",i[i.packed=2]="packed",i[i.downloadUint8AsFloat=3]="downloadUint8AsFloat",i[i.packedLastDimension=4]="packedLastDimension"},9390:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.getGlChannels=t.getCoordsDataType=t.getSqueezedParams=t.squeezeInputShape=t.generateShaderFuncNameFromInputSamplerNameAtOutCoords=t.generateShaderFuncNameFromInputSamplerName=t.repeatedTry=t.getPackedShape=void 0;const s=i(2517);t.getPackedShape=function(u){const d=u.length;return u.slice(0,d-1).concat(u[d-1]/4)},t.repeatedTry=async function(u,d=h=>0,a){return new Promise((h,f)=>{let c=0;const l=()=>{if(u())return void h();c++;const 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Error: ${n}`)}throw new Error("WebGL is not supported")}t.createWebGLContext=function h(f){let c;f&&f!=="webgl2"||!("webgl2"in d)?f&&f!=="webgl"||!("webgl"in d)||(c=d.webgl):c=d.webgl2,c=c||a(f),f=f||c.version===1?"webgl":"webgl2";const l=c.gl;return d[f]=c,l.isContextLost()?(delete d[f],h(f)):(l.disable(l.DEPTH_TEST),l.disable(l.STENCIL_TEST),l.disable(l.BLEND),l.disable(l.DITHER),l.disable(l.POLYGON_OFFSET_FILL),l.disable(l.SAMPLE_COVERAGE),l.enable(l.SCISSOR_TEST),l.enable(l.CULL_FACE),l.cullFace(l.BACK),c)},t.createNewWebGLContext=a},1713:function(m,t,i){var s=this&&this.__createBinding||(Object.create?function(l,n,e,r){r===void 0&&(r=e);var o=Object.getOwnPropertyDescriptor(n,e);o&&!("get"in o?!n.__esModule:o.writable||o.configurable)||(o={enumerable:!0,get:function(){return n[e]}}),Object.defineProperty(l,r,o)}:function(l,n,e,r){r===void 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Promise(n=>{this.addItemToPoll(()=>l.isFencePassed(),()=>n())})}pollItems(){const l=c(this.itemsToPoll.map(n=>n.isDoneFn));for(let n=0;n<=l;++n){const{resolveFn:e}=this.itemsToPoll[n];e()}this.itemsToPoll=this.itemsToPoll.slice(l+1)}async addItemToPoll(l,n){this.itemsToPoll.push({isDoneFn:l,resolveFn:n}),this.itemsToPoll.length>1||await(0,f.repeatedTry)(()=>(this.pollItems(),this.itemsToPoll.length===0))}}},1036:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ExecutionPlan=void 0;const s=i(6231);class u{constructor(a,h){this.op=a,this.node=h}}t.ExecutionPlan=class{constructor(d,a,h){this.graph=d,this.profiler=h,this.initialize(a)}initialize(d){this.profiler.event("session","ExecutionPlan.initialize",()=>{const a=this.graph.getNodes();if(a.length!==d.length)throw new Error("The size of nodes and OPs do not match.");this._ops=d.map((h,f)=>new u(h,a[f])),this.reset(),this._starter=[],this._ops.forEach((h,f)=>{let c=!0;for(const l of 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c{constructor(){this.bb=null,this.bb_pos=0}__init(n,e){return this.bb_pos=n,this.bb=e,this}static getRootAsModel(n,e){return(e||new c).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsModel(n,e){return n.setPosition(n.position()+s.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(n.readInt32(n.position())+n.position(),n)}irVersion(){let n=this.bb.__offset(this.bb_pos,4);return n?this.bb.readInt64(this.bb_pos+n):this.bb.createLong(0,0)}opsetImport(n,e){let r=this.bb.__offset(this.bb_pos,6);return r?(e||new a.experimental.fbs.OperatorSetId).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*n),this.bb):null}opsetImportLength(){let n=this.bb.__offset(this.bb_pos,6);return n?this.bb.__vector_len(this.bb_pos+n):0}producerName(n){let e=this.bb.__offset(this.bb_pos,8);return e?this.bb.__string(this.bb_pos+e,n):null}producerVersion(n){let e=this.bb.__offset(this.bb_pos,10);return e?this.bb.__string(this.bb_pos+e,n):null}domain(n){let e=this.bb.__offset(this.bb_pos,12);return e?this.bb.__string(this.bb_pos+e,n):null}modelVersion(){let n=this.bb.__offset(this.bb_pos,14);return n?this.bb.readInt64(this.bb_pos+n):this.bb.createLong(0,0)}docString(n){let e=this.bb.__offset(this.bb_pos,16);return e?this.bb.__string(this.bb_pos+e,n):null}graph(n){let e=this.bb.__offset(this.bb_pos,18);return e?(n||new a.experimental.fbs.Graph).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}graphDocString(n){let e=this.bb.__offset(this.bb_pos,20);return e?this.bb.__string(this.bb_pos+e,n):null}static startModel(n){n.startObject(9)}static addIrVersion(n,e){n.addFieldInt64(0,e,n.createLong(0,0))}static addOpsetImport(n,e){n.addFieldOffset(1,e,0)}static createOpsetImportVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startOpsetImportVector(n,e){n.startVector(4,e,4)}static addProducerName(n,e){n.addFieldOffset(2,e,0)}static 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getSizePrefixedRootAsKernelCreateInfos(n,e){return n.setPosition(n.position()+s.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(n.readInt32(n.position())+n.position(),n)}nodeIndices(n){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.readUint32(this.bb.__vector(this.bb_pos+e)+4*n):0}nodeIndicesLength(){let n=this.bb.__offset(this.bb_pos,4);return n?this.bb.__vector_len(this.bb_pos+n):0}nodeIndicesArray(){let n=this.bb.__offset(this.bb_pos,4);return n?new Uint32Array(this.bb.bytes().buffer,this.bb.bytes().byteOffset+this.bb.__vector(this.bb_pos+n),this.bb.__vector_len(this.bb_pos+n)):null}kernelDefHashes(n){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.readUint64(this.bb.__vector(this.bb_pos+e)+8*n):this.bb.createLong(0,0)}kernelDefHashesLength(){let n=this.bb.__offset(this.bb_pos,6);return n?this.bb.__vector_len(this.bb_pos+n):0}static startKernelCreateInfos(n){n.startObject(2)}static addNodeIndices(n,e){n.addFieldOffset(0,e,0)}static createNodeIndicesVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addInt32(e[r]);return n.endVector()}static startNodeIndicesVector(n,e){n.startVector(4,e,4)}static addKernelDefHashes(n,e){n.addFieldOffset(1,e,0)}static createKernelDefHashesVector(n,e){n.startVector(8,e.length,8);for(let r=e.length-1;r>=0;r--)n.addInt64(e[r]);return n.endVector()}static startKernelDefHashesVector(n,e){n.startVector(8,e,8)}static endKernelCreateInfos(n){return n.endObject()}static createKernelCreateInfos(n,e,r){return c.startKernelCreateInfos(n),c.addNodeIndices(n,e),c.addKernelDefHashes(n,r),c.endKernelCreateInfos(n)}}f.KernelCreateInfos=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(a){(function(h){(function(f){class c{constructor(){this.bb=null,this.bb_pos=0}__init(n,e){return this.bb_pos=n,this.bb=e,this}static getRootAsSubGraphSessionState(n,e){return(e||new c).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsSubGraphSessionState(n,e){return n.setPosition(n.position()+s.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(n.readInt32(n.position())+n.position(),n)}graphId(n){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,n):null}sessionState(n){let e=this.bb.__offset(this.bb_pos,6);return e?(n||new a.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startSubGraphSessionState(n){n.startObject(2)}static addGraphId(n,e){n.addFieldOffset(0,e,0)}static addSessionState(n,e){n.addFieldOffset(1,e,0)}static endSubGraphSessionState(n){let e=n.endObject();return n.requiredField(e,4),e}static createSubGraphSessionState(n,e,r){return c.startSubGraphSessionState(n),c.addGraphId(n,e),c.addSessionState(n,r),c.endSubGraphSessionState(n)}}f.SubGraphSessionState=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(a){(function(h){(function(f){class 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e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,n):null}model(n){let e=this.bb.__offset(this.bb_pos,6);return e?(n||new a.experimental.fbs.Model).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}sessionState(n){let e=this.bb.__offset(this.bb_pos,8);return e?(n||new a.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startInferenceSession(n){n.startObject(3)}static addOrtVersion(n,e){n.addFieldOffset(0,e,0)}static addModel(n,e){n.addFieldOffset(1,e,0)}static addSessionState(n,e){n.addFieldOffset(2,e,0)}static endInferenceSession(n){return n.endObject()}static finishInferenceSessionBuffer(n,e){n.finish(e,"ORTM")}static finishSizePrefixedInferenceSessionBuffer(n,e){n.finish(e,"ORTM",!0)}static createInferenceSession(n,e,r,o){return c.startInferenceSession(n),c.addOrtVersion(n,e),c.addModel(n,r),c.addSessionState(n,o),c.endInferenceSession(n)}}f.InferenceSession=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={}))},7448:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.OnnxjsSessionHandler=void 0;const s=i(1670),u=i(9162);t.OnnxjsSessionHandler=class{constructor(d){this.session=d,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(d,a,h){const f=new Map;for(const n in d)if(Object.hasOwnProperty.call(d,n)){const e=d[n];f.set(n,new u.Tensor(e.dims,e.type,void 0,void 0,e.data))}const c=await this.session.run(f),l={};return c.forEach((n,e)=>{l[e]=new s.Tensor(n.type,n.data,n.dims)}),l}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.Session=void 0;const 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define_process_env_default={};globalThis.ReadableStream||(globalThis.ReadableStream=sharp.ReadableStream);class FileResponse{constructor(t){he(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=t,this.headers=new Headers,this.exists=sharp.existsSync(t),this.exists){this.status=200,this.statusText="OK";let i=sharp.statSync(t);this.headers.set("content-length",i.size.toString()),this.updateContentType();let s=this;this.body=new ReadableStream({start(u){s.arrayBuffer().then(d=>{u.enqueue(new Uint8Array(d)),u.close()})}})}else this.status=404,this.statusText="Not Found",this.body=null}updateContentType(){const t=this.filePath.toString().split(".").pop().toLowerCase();this.headers.set("content-type",this._CONTENT_TYPE_MAP[t]??"application/octet-stream")}clone(){let t=new FileResponse(this.filePath);return t.exists=this.exists,t.status=this.status,t.statusText=this.statusText,t.headers=new Headers(this.headers),t}async arrayBuffer(){return(await sharp.promises.readFile(this.filePath)).buffer}async blob(){const t=await sharp.promises.readFile(this.filePath);return new Blob([t],{type:this.headers.get("content-type")})}async text(){return await sharp.promises.readFile(this.filePath,"utf8")}async json(){return JSON.parse(await this.text())}}function isValidHttpUrl(m,t=null){let i;try{i=new URL(m)}catch{return!1}return t&&!t.includes(i.hostname)?!1:i.protocol==="http:"||i.protocol==="https:"}async function getFile(m){var t;if(env$1.useFS&&!isValidHttpUrl(m))return new FileResponse(m);if(typeof process<"u"&&((t=process==null?void 0:process.release)==null?void 0:t.name)==="node"){const i=!!(define_process_env_default!=null&&define_process_env_default.TESTING_REMOTELY),s=env$1.version,u=new Headers;if(u.set("User-Agent",`transformers.js/${s}; is_ci/${i};`),isValidHttpUrl(m,["huggingface.co","hf.co"])){const a=(define_process_env_default==null?void 0:define_process_env_default.HF_TOKEN)??(define_process_env_default==null?void 0:define_process_env_default.HF_ACCESS_TOKEN);a&&u.set("Authorization",`Bearer ${a}`)}return fetch(m,{headers:u})}else return fetch(m)}const ERROR_MAPPING={400:"Bad request error occurred while trying to load file",401:"Unauthorized access to file",403:"Forbidden access to file",404:"Could not locate file",408:"Request timeout error occurred while trying to load file",500:"Internal server error error occurred while trying to load file",502:"Bad gateway error occurred while trying to load file",503:"Service unavailable error occurred while trying to load file",504:"Gateway timeout error occurred while trying to load file"};function handleError(m,t,i){if(!i)return null;const s=ERROR_MAPPING[m]??`Error (${m}) occurred while trying to load file`;throw Error(`${s}: "${t}".`)}class FileCache{constructor(t){this.path=t}async match(t){let i=sharp.join(this.path,t),s=new FileResponse(i);if(s.exists)return s}async put(t,i){const s=Buffer.from(await i.arrayBuffer());let u=sharp.join(this.path,t);try{await sharp.promises.mkdir(sharp.dirname(u),{recursive:!0}),await sharp.promises.writeFile(u,s)}catch(d){console.warn("An error occurred while writing the file to cache:",d)}}}async function tryCache(m,...t){for(let i of t)try{let s=await m.match(i);if(s)return s}catch{continue}}async function getModelFile(m,t,i=!0,s={}){dispatchCallback(s.progress_callback,{status:"initiate",name:m,file:t});let u;if(!u&&env$1.useBrowserCache){if(typeof caches>"u")throw Error("Browser cache is not available in this environment.");try{u=await caches.open("transformers-cache")}catch(_){console.warn("An error occurred while opening the browser cache:",_)}}if(!u&&env$1.useFSCache&&(u=new FileCache(s.cache_dir??env$1.cacheDir)),!u&&env$1.useCustomCache)throw Error("`env.useCustomCache=true`, 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Response&&r.status===200}dispatchCallback(s.progress_callback,{status:"download",name:m,file:t});const p={status:"progress",name:m,file:t};let g;return s.progress_callback?o&&typeof navigator<"u"&&/firefox/i.test(navigator.userAgent)?(g=new Uint8Array(await r.arrayBuffer()),dispatchCallback(s.progress_callback,{...p,progress:100,loaded:g.length,total:g.length})):g=await readResponse(r,_=>{dispatchCallback(s.progress_callback,{...p,..._})}):g=new Uint8Array(await r.arrayBuffer()),e&&l&&await u.match(l)===void 0&&await u.put(l,new Response(g,{headers:r.headers})).catch(_=>{console.warn(`Unable to add response to browser cache: ${_}.`)}),dispatchCallback(s.progress_callback,{status:"done",name:m,file:t}),g}async function getModelJSON(m,t,i=!0,s={}){let u=await getModelFile(m,t,i,s);if(u===null)return{};let a=new TextDecoder("utf-8").decode(u);return JSON.parse(a)}async function readResponse(m,t){const i=m.headers.get("Content-Length");i===null&&console.warn("Unable to determine content-length from response headers. Will expand buffer when needed.");let s=parseInt(i??"0"),u=new Uint8Array(s),d=0;const a=m.body.getReader();async function h(){const{done:f,value:c}=await a.read();if(f)return;let l=d+c.length;if(l>s){s=l;let e=new Uint8Array(s);e.set(u),u=e}u.set(c,d),d=l;const n=d/s*100;return t({progress:n,loaded:d,total:s}),h()}return await h(),u}function pathJoin(...m){return m=m.map((t,i)=>(i&&(t=t.replace(new RegExp("^/"),"")),i!==m.length-1&&(t=t.replace(new RegExp("/$"),"")),t)),m.join("/")}function interpolate_data(m,[t,i,s],[u,d],a="bilinear",h=!1){const f=d/s,c=u/i,l=new m.constructor(u*d*t),n=i*s,e=u*d;for(let r=0;r=0;--h)u[h]=f,s[h]=t[i[h]],f*=s[h];const d=i.map((h,f)=>u[i.indexOf(f)]),a=new m.constructor(m.length);for(let h=0;h=0;--c)f+=l%t[c]*d[c],l=Math.floor(l/t[c]);a[f]=m[h]}return[a,s]}function softmax(m){const t=max(m)[0],i=m.map(d=>Math.exp(d-t)),s=i.reduce((d,a)=>d+a,0);return i.map(d=>d/s)}function log_softmax(m){return softmax(m).map(s=>Math.log(s))}function getTopItems(m,t=0){return m=Array.from(m).map((i,s)=>[s,i]).sort((i,s)=>s[1]-i[1]),t>0&&(m=m.slice(0,t)),m}function min(m){if(m.length===0)throw Error("Array must not be empty");let t=m[0],i=0;for(let s=1;st&&(t=m[s],i=s);return[t,i]}function isPowerOfTwo(m){return m>0&&(m&m-1)===0}class P2FFT{constructor(t){if(this.size=t|0,this.size<=1||!isPowerOfTwo(this.size))throw new Error("FFT size must be a power of two larger than 1");this._csize=t<<1,this.table=new Float64Array(this.size*2);for(let s=0;ss;s<<=1)++i;this._width=i%2===0?i-1:i,this._bitrev=new Int32Array(1<>>u&3)<>>1);for(let u=0;u>>1]=t[u];return s}toComplexArray(t,i){const s=i||this.createComplexArray();for(let u=0;u>>1],s[u+1]=0;return s}completeSpectrum(t){const i=this._csize,s=i>>>1;for(let u=2;u>=2;a>=2;a>>=2){h=u/a<<1;const n=h>>>2;for(f=0;f>>1,a>>>1)}else for(f=0,c=0;f>>1,a>>>1,s)}for(a>>=2;a>=2;a>>=2){h=u/a<<1;const n=h>>>2;for(f=0;f>1;++l){const n=(l+1-t)**2/2,e=Math.sqrt(f**2+c**2)**n,r=n*Math.atan2(c,f),o=2*l;d[o]=e*Math.cos(r),d[o+1]=e*Math.sin(r),a[o]=d[o],a[o+1]=-d[o+1]}this._slicedChirpBuffer=d.subarray(i,s),this._f=new P2FFT(u>>1),this._f.transform(this._chirpBuffer,a)}_transform(t,i,s){const u=this._buffer1,d=this._buffer2,a=this._outBuffer1,h=this._outBuffer2,f=this._chirpBuffer,c=this._slicedChirpBuffer,l=this._a;if(s)for(let n=0;n>1,o=i[r];u[n]=o*c[n],u[e]=o*c[e]}else for(let n=0;n=m.length&&(f=2*(m.length-1)-f),s[a++]=m[f]}s.sort(),i[d]=s[u]}return i}function round(m,t){const i=Math.pow(10,t);return Math.round(m*i)/i}const DataTypeMap=new Map([["bool",Uint8Array],["float32",Float32Array],["float64",Float64Array],["string",Array],["int8",Int8Array],["uint8",Uint8Array],["int16",Int16Array],["uint16",Uint16Array],["int32",Int32Array],["uint32",Uint32Array],["int64",BigInt64Array]]),ONNXTensor$1=ONNX.Tensor;class Tensor extends ONNXTensor$1{constructor(...t){return t[0]instanceof ONNX.Tensor?super(t[0].type,t[0].data,t[0].dims):super(...t),new Proxy(this,{get:(i,s)=>{if(typeof s=="string"){let u=Number(s);if(Number.isInteger(u))return i._getitem(u)}return i[s]},set:(i,s,u)=>i[s]=u})}*[Symbol.iterator](){const[t,...i]=this.dims;if(i.length>0){const s=i.reduce((u,d)=>u*d);for(let u=0;u0){const u=s.reduce((d,a)=>d*a);return this._subarray(t,u,s)}else return new Tensor(this.type,[this.data[t]],s)}indexOf(t){for(let i=0;ic[1])throw new Error(`Invalid slice: ${c}`);let l=[Math.max(c[0],0),Math.min(c[1],this.dims[f])];s.push(l),i.push(l[1]-l[0])}else throw new Error(`Invalid slice: ${c}`)}let u=s.map(([f,c])=>c-f),d=u.reduce((f,c)=>f*c),a=new this.data.constructor(d);const h=this.stride();for(let f=0;f=0;--l){const e=u[l];c+=(n%e+s[l][0])*h[l],n=Math.floor(n/e)}a[f]=this.data[c]}return new Tensor(this.type,a,i)}transpose(...t){return transpose(this,t)}sum(t=null,i=!1){return this.norm(1,t,i)}norm(t="fro",i=null,s=!1){if(t==="fro")t=2;else if(typeof t=="string")throw Error(`Unsupported norm: ${t}`);if(i===null){let a=this.data.reduce((h,f)=>h+f**t,0)**(1/t);return new Tensor(this.type,[a],[])}i=safeIndex(i,this.dims.length);const u=this.dims.slice();u[i]=1;const d=new this.data.constructor(this.data.length/this.dims[i]);for(let a=0;a=0;--f){const n=this.dims[f];if(f!==i){const e=c%n;h+=e*l,l*=u[f]}c=Math.floor(c/n)}d[h]+=this.data[a]**t}if(t!==1)for(let a=0;a=0;--a){const c=this.dims[a];if(a!==i){const l=h%c;d+=l*f,f*=this.dims[a]}h=Math.floor(h/c)}this.data[u]/=s.data[d]}return this}normalize(t=2,i=1){return this.clone().normalize_(t,i)}stride(){return dimsToStride(this.dims)}squeeze(t=null){return new Tensor(this.type,this.data,calc_squeeze_dims(this.dims,t))}squeeze_(t=null){return this.dims=calc_squeeze_dims(this.dims,t),this}unsqueeze(t=null){return new Tensor(this.type,this.data,calc_unsqueeze_dims(this.dims,t))}unsqueeze_(t=null){return this.dims=calc_unsqueeze_dims(this.dims,t),this}flatten_(t=0,i=-1){i=(i+this.dims.length)%this.dims.length;let s=this.dims.slice(0,t),u=this.dims.slice(t,i+1),d=this.dims.slice(i+1);return this.dims=[...s,u.reduce((a,h)=>a*h,1),...d],this}flatten(t=0,i=-1){return this.clone().flatten_(t,i)}view(...t){let i=-1;for(let s=0;sa!==i?u*d:u,1);t[i]=this.data.length/s}return new Tensor(this.type,this.data,t)}neg_(){for(let t=0;td*a);if(i!==s)throw Error(`cannot reshape array of size ${i} into shape (${t})`);let u=m;for(let d=t.length-1;d>=0;d--)u=u.reduce((a,h)=>{let f=a[a.length-1];return f.lengthi!==1):typeof t=="number"?m[t]===1&&m.splice(t,1):Array.isArray(t)&&(m=m.filter((i,s)=>i!==1||!t.includes(s))),m}function calc_unsqueeze_dims(m,t){return t=safeIndex(t,m.length+1),m=m.slice(),m.splice(t,0,1),m}function safeIndex(m,t,i=null){if(m<-t||m>=t)throw new Error(`IndexError: index ${m} is out of bounds for dimension${i===null?"":" "+i} with size ${t}`);return m<0&&(m=(m%t+t)%t),m}function cat(m,t=0){t=safeIndex(t,m[0].dims.length);const i=m[0].dims.slice();i[t]=m.reduce((a,h)=>a+h.dims[t],0);const s=i.reduce((a,h)=>a*h,1),u=new m[0].data.constructor(s),d=m[0].type;if(t===0){let a=0;for(let h of m)u.set(h.data,a),a+=h.data.length}else{let a=0;for(let h=0;h=0;--n){const o=f.dims[n];let p=e%o;n===t&&(p+=a),l+=p*r,r*=i[n],e=Math.floor(e/o)}u[l]=f.data[c]}a+=f.dims[t]}}return new Tensor(d,u,i)}function stack(m,t=0){return cat(m.map(i=>i.unsqueeze(t)),t)}function std_mean(m,t=null,i=1,s=!1){if(t===null){const c=m.data.reduce((r,o)=>r+o,0)/m.data.length,l=Math.sqrt(m.data.reduce((r,o)=>r+(o-c)**2,0)/(m.data.length-i)),n=new Tensor(m.type,[c],[]);return[new Tensor(m.type,[l],[]),n]}t=safeIndex(t,m.dims.length);const u=mean(m,t,s),d=m.dims.slice();d[t]=1;const a=new m.data.constructor(m.data.length/m.dims[t]);for(let f=0;f=0;--l){const r=m.dims[l];if(l!==t){const o=n%r;c+=o*e,e*=d[l]}n=Math.floor(n/r)}a[c]+=(m.data[f]-u.data[c])**2}for(let f=0;fa+h,0);return new Tensor(m.type,[d/m.data.length],[])}t=safeIndex(t,m.dims.length);const s=m.dims.slice();s[t]=1;const u=new m.data.constructor(m.data.length/m.dims[t]);for(let d=0;d=0;--h){const l=m.dims[h];if(h!==t){const n=f%l;a+=n*c,c*=s[h]}f=Math.floor(f/l)}u[a]+=m.data[d]}if(m.dims[t]!==1)for(let d=0;d0||h>0;)switch(f.push(a-1),c.push(h-1),d[a][h].item()){case 0:--a,--h;break;case 1:--a;break;case 2:--h;break;default:throw new Error(`Internal error in dynamic time warping. Unexpected trace[${a}, ${h}]. Please file a bug report.`)}return f.reverse(),c.reverse(),[f,c]}function dimsToStride(m){const t=new Array(m.length);for(let i=m.length-1,s=1;i>=0;--i)t[i]=s,s*=m[i];return t}function ones(m){const t=m.reduce((i,s)=>i*s,1);return new Tensor("int64",new BigInt64Array(t).fill(1n),m)}function ones_like(m){return ones(m.dims)}class PriorityQueue{constructor(t=(i,s)=>i>s){this._heap=[],this._comparator=t}get size(){return this._heap.length}isEmpty(){return this.size===0}peek(){return this._heap[0]}push(...t){return this.extend(t)}extend(t){for(const i of t)this._heap.push(i),this._siftUp();return this.size}pop(){const t=this.peek(),i=this.size-1;return i>0&&this._swap(0,i),this._heap.pop(),this._siftDown(),t}replace(t){const i=this.peek();return this._heap[0]=t,this._siftDown(),i}_parent(t){return(t+1>>>1)-1}_left(t){return(t<<1)+1}_right(t){return t+1<<1}_greater(t,i){return this._comparator(this._heap[t],this._heap[i])}_swap(t,i){const s=this._heap[t];this._heap[t]=this._heap[i],this._heap[i]=s}_siftUp(){let t=this.size-1;for(;t>0&&this._greater(t,this._parent(t));)this._swap(t,this._parent(t)),t=this._parent(t)}_siftDown(){let t=0;for(;this._left(t)[]),this.endNodes=Array.from({length:this.len+1},()=>[]);const u=new TokenLatticeNode(this.bosTokenId,0,0,0,0),d=new TokenLatticeNode(this.eosTokenId,1,this.len,0,0);this.nodes.push(u.clone()),this.nodes.push(d.clone()),this.beginNodes[this.len].push(d),this.endNodes[0].push(u)}insert(t,i,s,u){const d=this.nodes.length,a=new TokenLatticeNode(u,d,t,i,s);this.beginNodes[t].push(a),this.endNodes[t+i].push(a),this.nodes.push(a)}viterbi(){const t=this.len;let i=0;for(;i<=t;){if(this.beginNodes[i].length==0)return[];for(let h of this.beginNodes[i]){h.prev=null;let f=0,c=null;for(let l of this.endNodes[i]){const n=l.backtraceScore+h.score;(c===null||n>f)&&(c=l.clone(),f=n)}if(c!==null)h.prev=c,h.backtraceScore=f;else return[]}++i}const s=[],d=this.beginNodes[t][0].prev;if(d===null)return[];let a=d.clone();for(;a.prev!==null;)s.push(a.clone()),a=a.clone().prev.clone();return s.reverse(),s}piece(t){return this.sentence.slice(t.pos,t.pos+t.length)}tokens(){return this.viterbi().map(i=>this.piece(i))}tokenIds(){return this.viterbi().map(i=>i.tokenId)}}class TokenLatticeNode{constructor(t,i,s,u,d){this.tokenId=t,this.nodeId=i,this.pos=s,this.length=u,this.score=d,this.prev=null,this.backtraceScore=0}clone(){const t=new TokenLatticeNode(this.tokenId,this.nodeId,this.pos,this.length,this.score);return t.prev=this.prev,t.backtraceScore=this.backtraceScore,t}}async function loadTokenizer(m,t){return await Promise.all([getModelJSON(m,"tokenizer.json",!0,t),getModelJSON(m,"tokenizer_config.json",!0,t)])}function regexSplit(m,t){const i=[];let s=0;for(const u of m.matchAll(t)){const d=u[0];s0&&i.push(d),s=u.index+d.length}return sthis.tokens_to_ids.get(s)??this.unk_token_id);return this.fuse_unk&&(i=fuse(i,this.unk_token_id)),i}convert_ids_to_tokens(t){return t.map(i=>this.vocab[i]??this.unk_token)}}class WordPieceTokenizer extends TokenizerModel{constructor(t){super(t),this.tokens_to_ids=objectToMap(t.vocab),this.unk_token_id=this.tokens_to_ids.get(t.unk_token),this.unk_token=t.unk_token,this.max_input_chars_per_word=t.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[i,s]of this.tokens_to_ids)this.vocab[s]=i}encode(t){let i=[];for(let s of t){let u=[...s];if(u.length>this.max_input_chars_per_word){i.push(this.unk_token);continue}let d=!1,a=0,h=[];for(;a0&&(l=this.config.continuing_subword_prefix+l),this.tokens_to_ids.has(l)){c=l;break}--f}if(c===null){d=!0;break}h.push(c),a=f}d?i.push(this.unk_token):i.push(...h)}return i}}class Unigram extends TokenizerModel{constructor(t,i){super(t);const s=t.vocab.length;this.vocab=new Array(s),this.scores=new Array(s);for(let u=0;u[u,d])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=i.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(t){const i=t.sentence,s=i.length;let u=0;for(;u{const m=[...Array.from({length:94},(u,d)=>d+33),...Array.from({length:12},(u,d)=>d+161),...Array.from({length:82},(u,d)=>d+174)];let t=m.slice(),i=0;for(let u=0;u<256;++u)m.includes(u)||(m.push(u),t.push(256+i),i+=1);let s=t.map(u=>String.fromCharCode(u));return Object.fromEntries(m.map((u,d)=>[u,s[d]]))})(),UNICODE_TO_BYTES=reverseDictionary(BYTES_TO_UNICODE);class BPE extends TokenizerModel{constructor(t){super(t),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=objectToMap(t.vocab),this.unk_token_id=this.tokens_to_ids.get(t.unk_token),this.unk_token=t.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[i,s]of this.tokens_to_ids)this.vocab[s]=i;this.bpe_ranks=new Map(t.merges.map((i,s)=>[i,s])),this.merges=t.merges.map(i=>i.split(this.BPE_SPLIT_TOKEN)),this.end_of_word_suffix=t.end_of_word_suffix,this.continuing_subword_suffix=t.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(t){if(t.length===0)return[];const i=this.cache.get(t);if(i!==void 0)return i;const s=Array.from(t);this.end_of_word_suffix&&(s[s.length-1]+=this.end_of_word_suffix);let u=[];if(s.length>1){const d=new PriorityQueue((f,c)=>f.score`<0x${a.toString(16).toUpperCase().padStart(2,"0")}>`)):i.push(this.unk_token)}return i}}class LegacyTokenizerModel extends TokenizerModel{constructor(t,i){super(t),this.tokens_to_ids=objectToMap(i.target_lang?t.vocab[i.target_lang]:t.vocab),this.bos_token=i.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=i.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=i.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=i.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[s,u]of this.tokens_to_ids)this.vocab[u]=s}encode(t){return t}}class Normalizer extends Callable{constructor(t){super(),this.config=t}static fromConfig(t){if(t===null)return null;switch(t.type){case"BertNormalizer":return new BertNormalizer(t);case"Precompiled":return new Precompiled(t);case"Sequence":return new NormalizerSequence(t);case"Replace":return new Replace(t);case"NFC":return new NFC(t);case"NFKC":return new NFKC(t);case"NFKD":return new NFKD(t);case"Strip":return new StripNormalizer(t);case"StripAccents":return new StripAccents(t);case"Lowercase":return new Lowercase(t);case"Prepend":return new Prepend(t);default:throw new Error(`Unknown Normalizer type: ${t.type}`)}}normalize(t){throw Error("normalize should be implemented in subclass.")}_call(t){return this.normalize(t)}}class Replace extends Normalizer{normalize(t){let i=createPattern(this.config.pattern);return i===null||(t=t.replaceAll(i,this.config.content)),t}}class NFC extends Normalizer{normalize(t){return t=t.normalize("NFC"),t}}class NFKC extends Normalizer{normalize(t){return t=t.normalize("NFKC"),t}}class NFKD extends Normalizer{normalize(t){return t=t.normalize("NFKD"),t}}class StripNormalizer extends Normalizer{normalize(t){return this.config.strip_left&&this.config.strip_right?t=t.trim():(this.config.strip_left&&(t=t.trimStart()),this.config.strip_right&&(t=t.trimEnd())),t}}class StripAccents extends Normalizer{normalize(t){return t=remove_accents(t),t}}class Lowercase extends Normalizer{normalize(t){return t=t.toLowerCase(),t}}class Prepend extends Normalizer{normalize(t){return t=this.config.prepend+t,t}}class NormalizerSequence extends Normalizer{constructor(t){super(t),this.normalizers=t.normalizers.map(i=>Normalizer.fromConfig(i))}normalize(t){return this.normalizers.reduce((i,s)=>s.normalize(i),t)}}class BertNormalizer extends Normalizer{_tokenize_chinese_chars(t){let i=[];for(let s=0;s=19968&&t<=40959||t>=13312&&t<=19903||t>=131072&&t<=173791||t>=173824&&t<=177983||t>=177984&&t<=178207||t>=178208&&t<=183983||t>=63744&&t<=64255||t>=194560&&t<=195103}stripAccents(t){return t.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}normalize(t){return this.config.handle_chinese_chars&&(t=this._tokenize_chinese_chars(t)),this.config.lowercase?(t=t.toLowerCase(),this.config.strip_accents!==!1&&(t=this.stripAccents(t))):this.config.strip_accents&&(t=this.stripAccents(t)),t}}class PreTokenizer extends Callable{static fromConfig(t){if(t===null)return null;switch(t.type){case"BertPreTokenizer":return new BertPreTokenizer(t);case"Sequence":return new PreTokenizerSequence(t);case"WhitespaceSplit":return new WhitespaceSplit(t);case"Metaspace":return new MetaspacePreTokenizer(t);case"ByteLevel":return new ByteLevelPreTokenizer(t);case"Split":return new SplitPreTokenizer(t);case"Punctuation":return new PunctuationPreTokenizer(t);case"Digits":return new DigitsPreTokenizer(t);case"Replace":return new ReplacePreTokenizer(t);default:throw new Error(`Unknown PreTokenizer type: ${t.type}`)}}pre_tokenize_text(t){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(t){let i=[];return Array.isArray(t)?i=t.map(s=>this.pre_tokenize_text(s)):i=this.pre_tokenize_text(t),i.flat()}_call(t){return this.pre_tokenize(t)}}class BertPreTokenizer extends PreTokenizer{constructor(t){super(),this.pattern=new RegExp(`[^\\s${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]`,"gu")}pre_tokenize_text(t){return t.trim().match(this.pattern)||[]}}class ByteLevelPreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=new RegExp("'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)|\\s+","gu"),this.byte_encoder=BYTES_TO_UNICODE,this.text_encoder=new TextEncoder}pre_tokenize_text(t){return this.add_prefix_space&&!t.startsWith(" ")&&(t=" "+t),(this.use_regex?t.match(this.pattern)||[]:[t]).map(s=>Array.from(this.text_encoder.encode(s),u=>this.byte_encoder[u]).join(""))}}class SplitPreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t,this.pattern=createPattern(this.config.pattern,this.config.invert)}pre_tokenize_text(t){return this.pattern===null?[]:this.config.invert?t.match(this.pattern)||[]:regexSplit(t,this.pattern)}}class PunctuationPreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t,this.pattern=new RegExp(`[^${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]+`,"gu")}pre_tokenize_text(t){return t.match(this.pattern)||[]}}class DigitsPreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t;const i=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(i,"gu")}pre_tokenize_text(t){return t.match(this.pattern)||[]}}class PostProcessor extends Callable{constructor(t){super(),this.config=t}static fromConfig(t){if(t===null)return null;switch(t.type){case"TemplateProcessing":return new TemplateProcessing(t);case"ByteLevel":return new ByteLevelPostProcessor(t);case"RobertaProcessing":return new RobertaProcessing(t);case"BertProcessing":return new BertProcessing(t);default:throw new Error(`Unknown PostProcessor type: ${t.type}`)}}post_process(t,...i){throw Error("post_process should be implemented in subclass.")}_call(t,...i){return this.post_process(t,...i)}}class BertProcessing extends PostProcessor{constructor(t){super(t),this.cls=t.cls[0],this.sep=t.sep[0]}post_process(t,i=null){return t=mergeArrays([this.cls],t,[this.sep]),i!==null&&(t=mergeArrays(t,[this.sep],i,[this.sep])),t}}class RobertaProcessing extends BertProcessing{}class TemplateProcessing extends PostProcessor{constructor(t){super(t),this.single=t.single,this.pair=t.pair}post_process(t,i=null){let s=i===null?this.single:this.pair,u=[];for(let d of s)"SpecialToken"in d?u.push(d.SpecialToken.id):"Sequence"in d&&(d.Sequence.id==="A"?u=mergeArrays(u,t):d.Sequence.id==="B"&&(u=mergeArrays(u,i)));return u}}class ByteLevelPostProcessor extends PostProcessor{post_process(t){return t}}class Decoder extends Callable{constructor(t){super(),this.config=t,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=t.trim_offsets}static fromConfig(t){switch(t.type){case"WordPiece":return new WordPieceDecoder(t);case"Metaspace":return new MetaspaceDecoder(t);case"ByteLevel":return new ByteLevelDecoder(t);case"Replace":return new ReplaceDecoder(t);case"ByteFallback":return new ByteFallback(t);case"Fuse":return new FuseDecoder(t);case"Strip":return new StripDecoder(t);case"Sequence":return new DecoderSequence(t);case"CTC":return new CTCDecoder(t);case"BPEDecoder":return new BPEDecoder(t);default:throw new Error(`Unknown Decoder type: ${t.type}`)}}_call(t){return this.decode(t)}decode(t){return this.decode_chain(t).join("")}decode_chain(t){throw Error("`decode_chain` should be implemented in subclass.")}}class ReplaceDecoder extends Decoder{decode_chain(t){let i=createPattern(this.config.pattern);return i===null?t:t.map(s=>s.replaceAll(i,this.config.content))}}class ByteFallback extends Decoder{constructor(t){super(t),this.text_decoder=new TextDecoder}decode_chain(t){let i=[],s=[];for(let u of t){let d=null;if(u.length===6&&u.startsWith("<0x")&&u.endsWith(">")){let a=parseInt(u.slice(3,5),16);isNaN(a)||(d=a)}if(d!==null)s.push(d);else{if(s.length>0){let a=this.text_decoder.decode(Uint8Array.from(s));i.push(a),s=[]}i.push(u)}}if(s.length>0){let u=this.text_decoder.decode(Uint8Array.from(s));i.push(u),s=[]}return i}}class FuseDecoder extends Decoder{decode_chain(t){return[t.join("")]}}class StripDecoder extends Decoder{constructor(t){super(t),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(t){return t.map(i=>{let s=0;for(let d=0;d(s!==0&&(i.startsWith(this.config.prefix)?i=i.replace(this.config.prefix,""):i=" "+i),this.cleanup&&(i=clean_up_tokenization(i)),i))}}class ByteLevelDecoder extends Decoder{constructor(t){super(t),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(t){let i=t.join(""),s=new Uint8Array([...i].map(d=>this.byte_decoder[d]));return this.text_decoder.decode(s)}decode_chain(t){let i=[],s=[];for(let u of t)this.added_tokens.includes(u)?(s.length>0&&(i.push(this.convert_tokens_to_string(s)),s=[]),i.push(u)):s.push(u);return s.length>0&&i.push(this.convert_tokens_to_string(s)),i}}class CTCDecoder extends Decoder{constructor(t){super(t),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(t){if(t.length===0)return"";let i=[t[0]];for(let d=1;dd!==this.pad_token).join("");return this.cleanup&&(u=clean_up_tokenization(u).replaceAll(this.word_delimiter_token," ").trim()),u}decode_chain(t){return[this.convert_tokens_to_string(t)]}}class DecoderSequence extends Decoder{constructor(t){super(t),this.decoders=t.decoders.map(i=>Decoder.fromConfig(i))}decode_chain(t){return this.decoders.reduce((i,s)=>s.decode_chain(i),t)}}class BPEDecoder extends Decoder{constructor(t){super(t),this.suffix=this.config.suffix}decode_chain(t){return t.map((i,s)=>i.replaceAll(this.suffix,s===t.length-1?"":" "))}}class MetaspacePreTokenizer extends PreTokenizer{constructor(t){super(),this.addPrefixSpace=t.add_prefix_space,this.replacement=t.replacement,this.strRep=t.str_rep||this.replacement}pre_tokenize(t){typeof t=="string"&&(t=t.trimStart().split(/\s+/));const i=[];for(let s of t){let u=s.replaceAll(" ",this.strRep);this.addPrefixSpace&&!u.startsWith(this.replacement)&&(u=this.strRep+u),i.push(u)}return i}}class MetaspaceDecoder extends Decoder{constructor(t){super(t),this.addPrefixSpace=t.add_prefix_space,this.replacement=t.replacement}decode_chain(t){let i=[];for(let s=0;ss.normalize("NFKC")).join("～"):t=t.normalize("NFKC"),t}}class PreTokenizerSequence extends PreTokenizer{constructor(t){super(),this.tokenizers=t.pretokenizers.map(i=>PreTokenizer.fromConfig(i))}pre_tokenize_text(t){return typeof t=="string"&&(t=[t]),this.tokenizers.reduce((i,s)=>s.pre_tokenize(i),t)}}class WhitespaceSplit extends PreTokenizer{constructor(t){super()}pre_tokenize_text(t){return whitespace_split(t)}}class ReplacePreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t,this.pattern=createPattern(this.config.pattern),this.content=this.config.content}pre_tokenize_text(t){return this.pattern===null?[t]:[t.replaceAll(this.pattern,this.config.content)]}}class PreTrainedTokenizer extends Callable{constructor(t,i){super(),this.normalizer=Normalizer.fromConfig(t.normalizer),this.pre_tokenizer=PreTokenizer.fromConfig(t.pre_tokenizer),this.model=TokenizerModel.fromConfig(t.model,i),this.post_processor=PostProcessor.fromConfig(t.post_processor),this.decoder=Decoder.fromConfig(t.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 s of t.added_tokens){let u=s.id,d=s.content;this.added_tokens.push(d),this.model.tokens_to_ids.set(d,u),this.model.vocab[u]=d,s.special&&(this.special_tokens.push(d),this.all_special_ids.push(u))}this.special_tokens.push(...i.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(i,"mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken(i,"pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken(i,"sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.unk_token=this.getToken(i,"unk_token"),this.unk_token_id=this.model.tokens_to_ids.get(this.unk_token),this.model_max_length=i.model_max_length,this.remove_space=i.remove_space,this.clean_up_tokenization_spaces=i.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=i.do_lowercase_and_remove_accent??!1,this.padding_side="right"}getToken(t,...i){for(let s of i){let u=t[s];if(u)if(typeof u=="object"){if(u.__type==="AddedToken")return u.content;throw Error(`Unknown token: ${u}`)}else return u}return null}static async from_pretrained(t,{progress_callback:i=null,config:s=null,cache_dir:u=null,local_files_only:d=!1,revision:a="main"}={}){let h=await loadTokenizer(t,{progress_callback:i,config:s,cache_dir:u,local_files_only:d,revision:a});return new this(...h)}prepare_model_inputs(t){return t}_call(t,{text_pair:i=null,add_special_tokens:s=!0,padding:u=!1,truncation:d=null,max_length:a=null,return_tensor:h=!0}={}){let f;if(Array.isArray(t)){if(t.length===0)throw Error("text array must be non-empty");if(i!==null){if(Array.isArray(i)){if(t.length!==i.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");f=t.map((e,r)=>this.encode(e,i[r],{add_special_tokens:s}))}else f=t.map(e=>this.encode(e,null,{add_special_tokens:s}))}else{if(t===null)throw Error("text may not be null");if(Array.isArray(i))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(t,i,{add_special_tokens:s})]}let c=max(f.map(e=>e.length))[0];a===null&&(a=c),a=Math.min(a,this.model_max_length);let l=[];if(u||d)for(let e=0;ea)d&&(f[e]=f[e].slice(0,a)),l.push(new Array(f[e].length).fill(1));else if(u){let r=a-f[e].length;this.padding_side==="right"?(l.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))):(l.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 l.push(new Array(f[e].length).fill(1));else l=f.map(e=>new Array(e.length).fill(1));if(h){if(!(u&&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),l=new Tensor("int64",BigInt64Array.from(l.flat().map(BigInt)),e)}else Array.isArray(t)||(f=f[0],l=l[0]);let n={input_ids:f,attention_mask:l};return n=this.prepare_model_inputs(n),n}_encode_text(t){return t===null?null:(this.added_tokens_regex?t.split(this.added_tokens_regex).filter(u=>u):[t]).map(u=>{if(this.added_tokens.includes(u))return u;{this.remove_space===!0&&(u=u.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(u=lowercase_and_remove_accent(u)),this.normalizer!==null&&(u=this.normalizer(u));let d=this.pre_tokenizer!==null?this.pre_tokenizer(u):[u];return this.model(d)}}).flat()}encode(t,i=null,{add_special_tokens:s=!0}={}){let u=this._encode_text(t),d=this._encode_text(i),a=this.post_processor!==null&&s?this.post_processor(u,d):mergeArrays(u??[],d??[]);return this.model.convert_tokens_to_ids(a)}batch_decode(t,i={}){return t instanceof Tensor&&(t=t.tolist()),t.map(s=>this.decode(s,i))}decode(t,i={}){if(t instanceof Tensor&&(t=prepareTensorForDecode(t)),!Array.isArray(t)||t.length===0||!isIntegralNumber(t[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(t,i)}decode_single(t,{skip_special_tokens:i=!1,clean_up_tokenization_spaces:s=null}){let u=this.model.convert_ids_to_tokens(t);i&&(u=u.filter(a=>!this.special_tokens.includes(a)));let d=this.decoder(u);return this.decoder.end_of_word_suffix&&(d=d.replaceAll(this.decoder.end_of_word_suffix," "),i&&(d=d.trim())),(s??this.clean_up_tokenization_spaces)&&(d=clean_up_tokenization(d)),d}}function add_token_types(m){if(m.input_ids instanceof Tensor)m.token_type_ids=new Tensor("int64",new BigInt64Array(m.input_ids.data.length),m.input_ids.dims);else if(Array.isArray(m.input_ids))Array.isArray(m.input_ids[0])?m.token_type_ids=m.input_ids.map(t=>new Array(t.length).fill(0)):m.token_type_ids=new Array(m.input_ids.length).fill(0);else throw new Error("Input ids must be a Tensor or an Array");return m}class BertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class AlbertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class MobileBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class SqueezeBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class DebertaTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class DebertaV2Tokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class HerbertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class DistilBertTokenizer extends PreTrainedTokenizer{}class CamembertTokenizer extends PreTrainedTokenizer{}class XLMTokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),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(t){return add_token_types(t)}}class T5Tokenizer extends PreTrainedTokenizer{}class GPT2Tokenizer extends PreTrainedTokenizer{}class BartTokenizer extends PreTrainedTokenizer{}class MBartTokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter(s=>this.languageRegex.test(s)),this.lang_to_token=s=>s}_build_translation_inputs(t,i,s){return _build_translation_inputs(this,t,i,s)}}class MBart50Tokenizer extends MBartTokenizer{}class RobertaTokenizer extends PreTrainedTokenizer{}class BloomTokenizer extends PreTrainedTokenizer{constructor(t,i){var d,a;const s=".,!?…。，、।۔،",u=(a=(d=t.pre_tokenizer)==null?void 0:d.pretokenizers[0])==null?void 0:a.pattern;u&&u.Regex===` ?[^(\\s|[${s}])]+`&&(u.Regex=` ?[^\\s${s}]+`),super(t,i)}}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(m,t,i,s){if(!("language_codes"in m)||!Array.isArray(m.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in m)||!(m.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in m)||typeof m.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const u=s.src_lang,d=s.tgt_lang;if(!m.language_codes.includes(d))throw new Error(`Target language code "${d}" is not valid. Must be one of: {${m.language_codes.join(", ")}}`);if(u!==void 0){if(!m.language_codes.includes(u))throw new Error(`Source language code "${u}" is not valid. Must be one of: {${m.language_codes.join(", ")}}`);for(let a of m.post_processor.config.single)if("SpecialToken"in a&&m.languageRegex.test(a.SpecialToken.id)){a.SpecialToken.id=m.lang_to_token(u);break}}return s.forced_bos_token_id=m.model.convert_tokens_to_ids([m.lang_to_token(d)])[0],m._call(t,i)}class NllbTokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(s=>this.languageRegex.test(s)),this.lang_to_token=s=>s}_build_translation_inputs(t,i,s){return _build_translation_inputs(this,t,i,s)}}class M2M100Tokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(s=>this.languageRegex.test(s)).map(s=>s.slice(2,-2)),this.lang_to_token=s=>`__${s}__`}_build_translation_inputs(t,i,s){return _build_translation_inputs(this,t,i,s)}}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(([m,t])=>[t,m]),["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(t,{return_timestamps:i=!1,return_language:s=!1,time_precision:u=null,force_full_sequences:d=!0}={}){if(u===null)throw Error("Must specify time_precision");let a=null;const h=i==="word";function f(){return{language:a,timestamp:[null,null],text:""}}const c=[];let l=f(),n=0;const e=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let r=[],o=[],p=!1,g=null;const _=new Set(this.all_special_ids);for(let w of t){const T=w.tokens,S=h?w.token_timestamps:null;let A=null,P=e;if("stride"in w){const[N,z,$]=w.stride;if(n-=z,g=N-$,z&&(P=z/u+e),$)for(let C=T.length-1;C>=0;--C){const G=T[C];if(G>=e){if(A!==null&&(G-e)*u=e){const $=(z-e)*u+n,C=round($,2);if(A!==null&&z>=A)p=!0;else if(p||r.length>0&&z0?(r.push(x),h&&o.push(M)):r.every(N=>N.length===0)&&(l=f(),r=[],x=[],o=[],M=[])}if(r.length>0){if(d&&i)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,o),S=this.decode(w);l.text=S,h&&(l.words=this.collateWordTimestamps(w,T,a)),c.push(l)}let b=Object.create(null);const y=c.map(w=>w.text).join("");if(i||s){for(let w=0;w0;let h=a?[]:null,f=a?i[0]:null;for(let c=1;cC===N[G]).length,$=z/w+T;z>1&&$>n&&(n=$,e=[S,A,x,M])}const[o,p,g,_]=e,b=Math.floor((p+o)/2),y=Math.floor((_+g)/2);d.push(...s.slice(0,b)),s=l.slice(y),u=s.length,a&&(h.push(...f.slice(0,b)),f=i[c].slice(y))}return d.push(...s),a?(h.push(...f),[d,h]):[d,[]]}collateWordTimestamps(t,i,s){let[u,d,a]=this.combineTokensIntoWords(t,s),h=[];for(let f=0;f=u){let h=(a-u)*s;h=round(h,2),d.push(`<|${h}|>`),d.push([])}else d[d.length-1].push(a);return d=d.map(a=>typeof a=="string"?a:super.decode(a,i)),d.join("")}splitTokensOnUnicode(t){const i=this.decode(t,{decode_with_timestamps:!0}),s="�";let u=[],d=[],a=[],h=[],f=[],c=0;for(let l=0;l=this.model.tokens_to_ids.get("<|endoftext|>"),o=l.startsWith(" "),p=l.trim(),g=f.test(p);if(r||o||g||d.length===0)d.push(l),a.push(n),h.push(e);else{const _=d.length-1;d[_]+=l,a[_].push(...n),h[_].push(...e)}}return[d,a,h]}mergePunctuations(t,i,s,u,d){let a=structuredClone(t),h=structuredClone(i),f=structuredClone(s),c=a.length-2,l=a.length-1;for(;c>=0;)a[c].startsWith(" ")&&u.includes(a[c].trim())?(a[l]=a[c]+a[l],h[l]=mergeArrays(h[c],h[l]),f[l]=mergeArrays(f[c],f[l]),a[c]="",h[c]=[],f[c]=[]):l=c,--c;for(c=0,l=1;ln),h.filter(n=>n.length>0),f.filter(n=>n.length>0)]}get_decoder_prompt_ids({language:t=null,task:i=null,no_timestamps:s=!0}={}){let u=[];if(t){t=t.toLowerCase();let d=WHISPER_TO_LANGUAGE_CODE_MAPPING.get(t);if(d===void 0)if(WHISPER_LANGUAGE_MAPPING.has(t))d=t;else{const f=t.length===2?WHISPER_LANGUAGE_MAPPING.keys():WHISPER_LANGUAGE_MAPPING.values();throw new Error(`Language "${t}" is not supported. Must be one of: ${JSON.stringify(f)}`)}let a=this.model.tokens_to_ids.get(`<|${d}|>`);if(a===void 0)throw new Error(`Unable to find language "${d}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);u.push(a)}else u.push(null);if(i){if(i=i.toLowerCase(),i!=="transcribe"&&i!=="translate")throw new Error(`Task "${i}" is not supported. Must be one of: ["transcribe", "translate"]`);let d=this.model.tokens_to_ids.get(`<|${i}|>`);if(d===void 0)throw new Error(`Unable to find task "${i}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);u.push(d)}else u.push(null);if(s){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.');u.push(d)}return u.map((d,a)=>[a+1,d]).filter(d=>d[1]!==null)}}class CodeGenTokenizer extends PreTrainedTokenizer{}class CLIPTokenizer extends PreTrainedTokenizer{}class MarianTokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter(s=>this.languageRegex.test(s)),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(t){if(t===null)return null;let[i,...s]=t.trim().split(this.languageRegex);if(s.length===0)return super._encode_text(i);if(s.length===2){let[u,d]=s;return this.supported_language_codes.includes(u)||console.warn(`Unsupported language code "${u}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),mergeArrays([u],super._encode_text(d))}}}class Wav2Vec2CTCTokenizer extends PreTrainedTokenizer{}class BlenderbotTokenizer extends PreTrainedTokenizer{}class BlenderbotSmallTokenizer extends PreTrainedTokenizer{}class SpeechT5Tokenizer extends PreTrainedTokenizer{}class NougatTokenizer extends PreTrainedTokenizer{}class AutoTokenizer{static async from_pretrained(t,{quantized:i=!0,progress_callback:s=null,config:u=null,cache_dir:d=null,local_files_only:a=!1,revision:h="main"}={}){let[f,c]=await loadTokenizer(t,{quantized:i,progress_callback:s,config:u,cache_dir:d,local_files_only:a,revision:h}),l=c.tokenizer_class.replace(/Fast$/,""),n=this.TOKENIZER_CLASS_MAPPING[l];return n||(console.warn(`Unknown tokenizer class "${l}", attempting to construct from base class.`),n=PreTrainedTokenizer),new n(f,c)}}he(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,NougatTokenizer,PreTrainedTokenizer});async function loadConfig(m,t){return await getModelJSON(m,"config.json",!0,t)}class PretrainedConfig{constructor(t){this.model_type=null,this.is_encoder_decoder=!1,Object.assign(this,t)}static async from_pretrained(t,{progress_callback:i=null,config:s=null,cache_dir:u=null,local_files_only:d=!1,revision:a="main"}={}){let h=s??await loadConfig(t,{progress_callback:i,config:s,cache_dir:u,local_files_only:d,revision:a});return new this(h)}}class AutoConfig{static async from_pretrained(...t){return PretrainedConfig.from_pretrained(...t)}}class LogitsProcessorList extends Callable{constructor(){super(),this.processors=[]}push(t){this.processors.push(t)}extend(t){this.processors.push(...t)}_call(t,i){for(let s of i)this.processors.forEach(u=>u(t,s))}[Symbol.iterator](){return this.processors.values()}}class LogitsProcessor extends Callable{_call(t,i){throw Error("`_call` should be implemented in a subclass")}}class ForceTokensLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.force_token_map=Object.fromEntries(t??[])}_call(t,i){let s=this.force_token_map[t.length];return exists(s)&&(i.data.fill(-1/0),i.data[s]=0),i}}class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.bos_token_id=t}_call(t,i){return t.length===1&&(i.data.fill(-1/0),i.data[this.bos_token_id]=0),i}}class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(t,i){super(),this.max_length=t,this.forced_eos_token_id=i}_call(t,i){}}class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(t,i){super(),this.begin_suppress_tokens=t,this.begin_index=i}_call(t,i){if(t.length===this.begin_index)for(let s of this.begin_suppress_tokens)i.data[s]=-1/0;return i}}class WhisperTimeStampLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.eos_token_id=t.eos_token_id,this.no_timestamps_token_id=t.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(t.forced_decoder_ids||[]).length+2,t.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=t.max_initial_timestamp_index}_call(t,i){if(i.data[this.no_timestamps_token_id]=-1/0,t.length===this.begin_index-1)return i.data.fill(-1/0),i.data[this.timestamp_begin]=0,i;const s=t.slice(this.begin_index),u=s.length>=1&&s[s.length-1]>=this.timestamp_begin,d=s.length<2||s[s.length-2]>=this.timestamp_begin;if(u&&(d?i.data.subarray(this.timestamp_begin).fill(-1/0):i.data.subarray(0,this.eos_token_id).fill(-1/0)),t.length===this.begin_index&&this.max_initial_timestamp_index!==null){const c=this.timestamp_begin+this.max_initial_timestamp_index;i.data.subarray(c+1).fill(-1/0)}const a=log_softmax(i.data),h=Math.log(a.subarray(this.timestamp_begin).map(Math.exp).reduce((c,l)=>c+l)),f=max(a.subarray(0,this.timestamp_begin))[0];return h>f&&i.data.subarray(0,this.timestamp_begin).fill(-1/0),i}}class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.no_repeat_ngram_size=t}getNgrams(t){const i=t.length,s=[];for(let d=0;d0&&(u=u.map(d=>d/this.generation_config.temperature)),u}randomSelect(t){let i=t.reduce((u,d)=>u+d,0),s=Math.random()*i;for(let u=0;u1)return new BeamSearchSampler(t);if(t.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${t.num_return_sequences}.`);return new GreedySampler(t)}}class GreedySampler extends Sampler{sample(t,i=-1){let s=this.getLogits(t,i);return[[max(s)[1],0]]}}class MultinomialSampler extends Sampler{sample(t,i=-1){let s=t.dims.at(-1);this.generation_config.top_k>0&&(s=Math.min(this.generation_config.top_k,s));const u=this.getLogits(t,i),d=getTopItems(u,s),a=softmax(d.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},()=>{const h=this.randomSelect(a);return[d[h][0],Math.log(a[h])]})}}class BeamSearchSampler extends Sampler{sample(t,i=-1){let s=t.dims.at(-1);this.generation_config.top_k>0&&(s=Math.min(this.generation_config.top_k,s));const u=this.getLogits(t,i),d=getTopItems(u,s),a=softmax(d.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},(h,f)=>[d[f][0],Math.log(a[f])])}}const{InferenceSession,Tensor:ONNXTensor,env}=ONNX,MODEL_TYPES={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4},MODEL_TYPE_MAPPING=new Map,MODEL_NAME_TO_CLASS_MAPPING=new Map,MODEL_CLASS_TO_NAME_MAPPING=new Map;async function constructSession(m,t,i){let s=`onnx/${t}${i.quantized?"_quantized":""}.onnx`,u=await getModelFile(m,s,!0,i);try{return await InferenceSession.create(u,{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(u,{executionProviders:["wasm"]})}}function validateInputs(m,t){const i=Object.create(null),s=[];for(const a of m.inputNames){const h=t[a];if(!(h instanceof Tensor)){s.push(a);continue}i[a]=env.wasm.proxy?h.clone():h}if(s.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${s.join(", ")}.`);const u=Object.keys(t).length,d=m.inputNames.length;if(u>d){let a=Object.keys(t).filter(h=>!m.inputNames.includes(h));console.warn(`WARNING: Too many inputs were provided (${u} > ${d}). The following inputs will be ignored: "${a.join(", ")}".`)}return i}async function sessionRun(m,t){const i=validateInputs(m,t);try{let s=await m.run(i);return s=replaceTensors(s),s}catch(s){throw console.error(`An error occurred during model execution: "${s}".`),console.error("Inputs given to model:",i),s}}function replaceTensors(m){for(let t in m)m[t]instanceof ONNXTensor?m[t]=new Tensor(m[t]):typeof m[t]=="object"&&replaceTensors(m[t]);return m}function toI64Tensor(m){if(m instanceof Tensor)return m;if(m.length===0)throw Error("items must be non-empty");if(Array.isArray(m[0])){if(m.some(t=>t.length!==m[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(m.flat().map(t=>BigInt(t))),[m.length,m[0].length])}else return new Tensor("int64",BigInt64Array.from(m.map(t=>BigInt(t))),[1,m.length])}function prepareAttentionMask(m,t){let i=m.config.pad_token_id??null,s=m.config.eos_token_id??null;isIntegralNumber(s)&&(s=[s]);let u=t.indexOf(i)!==-1,d=s===null||!s.includes(i);if(u&&d){let a=BigInt64Array.from(t.data.map(h=>h!=i));return new Tensor("int64",a,t.dims)}else return ones_like(t)}function preparePositionIds(m,t,i){if(!m.inputNames.includes("position_ids"))return;const s=new BigInt64Array(t.attention_mask.data.length);for(let u=0;u0&&d.push(new NoRepeatNGramLogitsProcessor(i.no_repeat_ngram_size)),i.bad_words_ids!==null&&d.push(new NoBadWordsLogitsProcessor(i.bad_words_ids,i.eos_token_id)),i.min_length!==null&&i.eos_token_id!==null&&i.min_length>0&&d.push(new MinLengthLogitsProcessor(i.min_length,i.eos_token_id)),i.min_new_tokens!==null&&i.eos_token_id!==null&&i.min_new_tokens>0&&d.push(new MinNewTokensLengthLogitsProcessor(s,i.min_new_tokens,i.eos_token_id)),i.forced_bos_token_id!==null&&d.push(new ForcedBOSTokenLogitsProcessor(i.forced_bos_token_id)),i.forced_eos_token_id!==null&&d.push(new ForcedEOSTokenLogitsProcessor(i.max_length,i.forced_eos_token_id)),i.begin_suppress_tokens!==null){let a=s>1||i.forced_bos_token_id===null?s:s+1;i.forced_decoder_ids!==null&&(a+=i.forced_decoder_ids[i.forced_decoder_ids.length-1][0]),d.push(new SuppressTokensAtBeginLogitsProcessor(i.begin_suppress_tokens,a))}return i.forced_decoder_ids!==null&&d.push(new ForceTokensLogitsProcessor(i.forced_decoder_ids)),u!==null&&d.extend(u),d}_get_generation_config(i){let s=new GenerationConfig(this.config);return"generation_config"in this&&Object.assign(s,this.generation_config),i!==null&&Object.assign(s,i),s}async generate(i,s=null,u=null,{inputs_attention_mask:d=null}={}){if(!this.can_generate){let _=`The current model class (${MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const b=this.config.model_type,y=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(b)??MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES.get(b)??MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES.get(b)??MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES.get(b);throw y&&(_+=` Please use the following class instead: '${y[0]}'`),Error(_)}if(!(i instanceof Tensor)&&!isTypedArray(i)&&!Array.isArray(i))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${i.constructor.name}".`);let a;if(this.config.is_encoder_decoder)a=0;else if(a=i instanceof Tensor?i.dims.at(-1):i.length,a===0)throw Error("Must supply a non-empty array of input token ids.");s=this._get_generation_config(s),u=u??new LogitsProcessorList,u=this._get_logits_processor(s,a,u);let h=s.eos_token_id;h!==null&&!Array.isArray(h)&&(h=[h]);let f=1;const c=f+(s.max_new_tokens??1/0),l=Number.isInteger(s.max_length)&&(s.max_new_tokens??null)===null;let n=Sampler.getSampler(s),e=this.getStartBeams(i,s,f,d);for(;e.some(g=>!g.done)&&f=s.max_length){_.done=!0,g.push(_);continue}let b=await this.runBeam(_);s.output_attentions&&this.addAttentionsToBeam(_,b),s.output_scores;let y=b.logits.slice(null,-1,null);u(_.output_token_ids,y);let w=n(y);for(let[T,S]of w){let A={..._};this.updateBeam(A,T),A.score+=S,h&&h.includes(T)&&(A.done=!0),g.push(A)}}++f,g=this.groupBeams(g).map(_=>_.sort((b,y)=>y.score-b.score).slice(0,s.num_beams)),e=g.flat(),s.callback_function&&s.callback_function(e)}const r=this.groupBeams(e),o=g=>r.map(_=>s.num_return_sequences>1?_.slice(0,s.num_return_sequences).map(b=>b[g]):[_[0][g]]).flat(),p=o("output_token_ids");if(s.return_dict_in_generate){const g=o("decoder_attentions"),_=o("cross_attentions");return{sequences:p,decoder_attentions:g,cross_attentions:_}}else return p}addAttentionsToBeam(i,s){if(this.config.is_encoder_decoder){if(!s.cross_attentions||s.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`.");i.cross_attentions||(i.cross_attentions=[]),i.cross_attentions.push(s.cross_attentions)}if(!s.decoder_attentions||s.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`.");i.decoder_attentions||(i.decoder_attentions=[]),i.decoder_attentions.push(s.decoder_attentions)}groupBeams(i){const s=Object.create(null);for(const u of i)s[u.id]===void 0?s[u.id]=[u]:s[u.id].push(u);return Object.values(s)}getPastKeyValues(i,s){const u=Object.create(null);for(const d in i)if(d.startsWith("present")){let a=d.replace("present","past_key_values");s&&d.includes("encoder")?u[a]=s[a]:u[a]=i[d]}return u}getAttentions(i){const s=Object.create(null);for(const u of["cross_attentions","decoder_attentions"]){const d=[];for(const a in i)if(a.startsWith(u)){const h=a.split(".").pop();d[h]=i[a]}s[u]=d}return s}addPastKeyValues(i,s){if(s)Object.assign(i,s);else if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??!0)){let d=[1,this.num_encoder_heads,0,this.encoder_dim_kv],a=[1,this.num_decoder_heads,0,this.decoder_dim_kv];for(let h=0;h{let n=Array.from({length:this.config.decoder_layers},(_,b)=>cat(l.map(y=>y[b]),2)),e=stack(s.map(([_,b])=>u?n[_].slice(null,b,null,[0,u]):n[_].slice(null,b)));e=e.transpose(1,0,2,3);let[r,o]=std_mean(e,-2,0,!0),p=e.clone();for(let _=0;_e[b+1]-e[b]),p=mergeArrays([1],o).map(_=>!!_),g=[];for(let _=0;_=e&&(Array.from(A.data).filter(x=>x>=s).length>0||_>=n))break}const b=cat(o),{waveform:y}=await sessionRun(a.session,{spectrogram:b});return{spectrogram:b,waveform:y}}}class SpeechT5HifiGan extends PreTrainedModel{constructor(){super(...arguments);he(this,"main_input_name","spectrogram")}}class TrOCRPreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_encoder_layers=this.num_decoder_layers=this.config.decoder_layers,this.num_encoder_heads=this.num_decoder_heads=this.config.decoder_attention_heads,this.encoder_dim_kv=this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads}}class TrOCRForCausalLM extends TrOCRPreTrainedModel{}class MistralPreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class MistralModel extends MistralPreTrainedModel{}class MistralForCausalLM extends MistralPreTrainedModel{}class FalconPreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class FalconModel extends FalconPreTrainedModel{}class FalconForCausalLM extends FalconPreTrainedModel{}class ClapPreTrainedModel extends PreTrainedModel{}class ClapModel extends ClapPreTrainedModel{}class ClapTextModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(t,i={}){return i.model_file_name??(i.model_file_name="text_model"),super.from_pretrained(t,i)}}class ClapAudioModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(t,i={}){return i.model_file_name??(i.model_file_name="audio_model"),super.from_pretrained(t,i)}}class PretrainedMixin{static async from_pretrained(t,{quantized:i=!0,progress_callback:s=null,config:u=null,cache_dir:d=null,local_files_only:a=!1,revision:h="main",model_file_name:f=null}={}){let c={quantized:i,progress_callback:s,config:u,cache_dir:d,local_files_only:a,revision:h,model_file_name:f};if(u=await AutoConfig.from_pretrained(t,c),c.config||(c.config=u),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let l of this.MODEL_CLASS_MAPPINGS){const n=l.get(u.model_type);if(n)return await n[1].from_pretrained(t,c)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${u.model_type}", attempting to construct from base class.`),await PreTrainedModel.from_pretrained(t,c);throw Error(`Unsupported model type: ${u.model_type}`)}}he(PretrainedMixin,"MODEL_CLASS_MAPPINGS",null),he(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]],["clap",["ClapModel",ClapModel]],["clip",["CLIPModel",CLIPModel]],["mobilebert",["MobileBertModel",MobileBertModel]],["squeezebert",["SqueezeBertModel",SqueezeBertModel]],["wav2vec2",["Wav2Vec2Model",Wav2Vec2Model]],["wavlm",["WavLMModel",WavLMModel]],["audio-spectrogram-transformer",["ASTModel",ASTModel]],["detr",["DetrModel",DetrModel]],["vit",["ViTModel",ViTModel]],["mobilevit",["MobileViTModel",MobileViTModel]],["owlvit",["OwlViTModel",OwlViTModel]],["beit",["BeitModel",BeitModel]],["deit",["DeiTModel",DeiTModel]],["convnext",["ConvNextModel",ConvNextModel]],["convnextv2",["ConvNextV2Model",ConvNextV2Model]],["resnet",["ResNetModel",ResNetModel]],["swin",["SwinModel",SwinModel]],["swin2sr",["Swin2SRModel",Swin2SRModel]],["donut-swin",["DonutSwinModel",DonutSwinModel]],["yolos",["YolosModel",YolosModel]],["dpt",["DPTModel",DPTModel]],["glpn",["GLPNModel",GLPNModel]],["hifigan",["SpeechT5HifiGan",SpeechT5HifiGan]],["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]],["mistral",["MistralModel",MistralModel]],["falcon",["FalconModel",FalconModel]]]),MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForSpeechToText",SpeechT5ForSpeechToText]],["whisper",["WhisperForConditionalGeneration",WhisperForConditionalGeneration]]]),MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForTextToSpeech",SpeechT5ForTextToSpeech]]]),MODEL_FOR_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]],["mistral",["MistralForCausalLM",MistralForCausalLM]],["falcon",["FalconForCausalLM",FalconForCausalLM]],["trocr",["TrOCRForCausalLM",TrOCRForCausalLM]]]),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]],["convnext",["ConvNextForImageClassification",ConvNextForImageClassification]],["convnextv2",["ConvNextV2ForImageClassification",ConvNextV2ForImageClassification]],["resnet",["ResNetForImageClassification",ResNetForImageClassification]],["swin",["SwinForImageClassification",SwinForImageClassification]]]),MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES=new Map([["detr",["DetrForObjectDetection",DetrForObjectDetection]],["yolos",["YolosForObjectDetection",YolosForObjectDetection]]]),MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES=new Map([["owlvit",["OwlViTForObjectDetection",OwlViTForObjectDetection]]]),MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES=new Map([["detr",["DetrForSegmentation",DetrForSegmentation]]]),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]],["audio-spectrogram-transformer",["ASTForAudioClassification",ASTForAudioClassification]]]),MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES=new Map([["swin2sr",["Swin2SRForImageSuperResolution",Swin2SRForImageSuperResolution]]]),MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES=new Map([["dpt",["DPTForDepthEstimation",DPTForDepthEstimation]],["glpn",["GLPNForDepthEstimation",GLPNForDepthEstimation]]]),MODEL_CLASS_TYPE_MAPPING=[[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_TYPES.EncoderOnly],[MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_TYPES.EncoderDecoder],[MODEL_MAPPING_NAMES_DECODER_ONLY,MODEL_TYPES.DecoderOnly],[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_WITH_LM_HEAD_MAPPING_NAMES,MODEL_TYPES.DecoderOnly],[MODEL_FOR_MASKED_LM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Vision2Seq],[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_MASK_GENERATION_MAPPING_NAMES,MODEL_TYPES.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[m,t]of MODEL_CLASS_TYPE_MAPPING)for(const[i,s]of m.values())MODEL_TYPE_MAPPING.set(i,t),MODEL_CLASS_TO_NAME_MAPPING.set(s,i),MODEL_NAME_TO_CLASS_MAPPING.set(i,s);const CUSTOM_MAPPING=[["CLIPTextModelWithProjection",CLIPTextModelWithProjection,MODEL_TYPES.EncoderOnly],["CLIPVisionModelWithProjection",CLIPVisionModelWithProjection,MODEL_TYPES.EncoderOnly],["ClapTextModelWithProjection",ClapTextModelWithProjection,MODEL_TYPES.EncoderOnly],["ClapAudioModelWithProjection",ClapAudioModelWithProjection,MODEL_TYPES.EncoderOnly]];for(const[m,t,i]of CUSTOM_MAPPING)MODEL_TYPE_MAPPING.set(m,i),MODEL_CLASS_TO_NAME_MAPPING.set(t,m),MODEL_NAME_TO_CLASS_MAPPING.set(m,t);class AutoModel extends PretrainedMixin{}he(AutoModel,"MODEL_CLASS_MAPPINGS",[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_MAPPING_NAMES_DECODER_ONLY]),he(AutoModel,"BASE_IF_FAIL",!0);class AutoModelForSequenceClassification extends PretrainedMixin{}he(AutoModelForSequenceClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForTokenClassification extends PretrainedMixin{}he(AutoModelForTokenClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForSeq2SeqLM extends PretrainedMixin{}he(AutoModelForSeq2SeqLM,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES]);class AutoModelForSpeechSeq2Seq extends PretrainedMixin{}he(AutoModelForSpeechSeq2Seq,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES]);class AutoModelForTextToSpectrogram extends PretrainedMixin{}he(AutoModelForTextToSpectrogram,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES]);class AutoModelForCausalLM extends PretrainedMixin{}he(AutoModelForCausalLM,"MODEL_CLASS_MAPPINGS",[MODEL_WITH_LM_HEAD_MAPPING_NAMES]);class AutoModelForMaskedLM extends PretrainedMixin{}he(AutoModelForMaskedLM,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_MASKED_LM_MAPPING_NAMES]);class AutoModelForQuestionAnswering extends PretrainedMixin{}he(AutoModelForQuestionAnswering,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES]);class AutoModelForVision2Seq extends PretrainedMixin{}he(AutoModelForVision2Seq,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES]);class AutoModelForImageClassification extends PretrainedMixin{}he(AutoModelForImageClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForImageSegmentation extends PretrainedMixin{}he(AutoModelForImageSegmentation,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES]);class AutoModelForObjectDetection extends PretrainedMixin{}he(AutoModelForObjectDetection,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES]);class AutoModelForZeroShotObjectDetection extends PretrainedMixin{}he(AutoModelForZeroShotObjectDetection,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES]);class AutoModelForCTC extends PretrainedMixin{}he(AutoModelForCTC,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_CTC_MAPPING_NAMES]);class AutoModelForAudioClassification extends PretrainedMixin{}he(AutoModelForAudioClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForDocumentQuestionAnswering extends PretrainedMixin{}he(AutoModelForDocumentQuestionAnswering,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES]);class AutoModelForImageToImage extends PretrainedMixin{}he(AutoModelForImageToImage,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES]);class AutoModelForDepthEstimation extends PretrainedMixin{}he(AutoModelForDepthEstimation,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES]);class Seq2SeqLMOutput extends ModelOutput{constructor({logits:t,past_key_values:i,encoder_outputs:s,decoder_attentions:u=null,cross_attentions:d=null}){super(),this.logits=t,this.past_key_values=i,this.encoder_outputs=s,this.decoder_attentions=u,this.cross_attentions=d}}class SequenceClassifierOutput extends ModelOutput{constructor({logits:t}){super(),this.logits=t}}class TokenClassifierOutput extends ModelOutput{constructor({logits:t}){super(),this.logits=t}}class MaskedLMOutput extends ModelOutput{constructor({logits:t}){super(),this.logits=t}}class QuestionAnsweringModelOutput extends ModelOutput{constructor({start_logits:t,end_logits:i}){super(),this.start_logits=t,this.end_logits=i}}class CausalLMOutput extends ModelOutput{constructor({logits:t}){super(),this.logits=t}}const BROWSER_ENV=typeof self<"u",WEBWORKER_ENV=BROWSER_ENV&&self.constructor.name==="DedicatedWorkerGlobalScope";let createCanvasFunction,ImageDataClass,loadImageFunction;if(BROWSER_ENV)createCanvasFunction=(m,t)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this browser.");return new self.OffscreenCanvas(m,t)},loadImageFunction=self.createImageBitmap,ImageDataClass=self.ImageData;else if(sharp)loadImageFunction=async m=>{const i=(await m.metadata()).channels;let{data:s,info:u}=await m.raw().toBuffer({resolveWithObject:!0});const d=new RawImage(new Uint8ClampedArray(s),u.width,u.height,u.channels);return i!==void 0&&i!==u.channels&&d.convert(i),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"},CONTENT_TYPE_MAP=new Map([["png","image/png"],["jpg","image/jpeg"],["jpeg","image/jpeg"],["gif","image/gif"]]);class RawImage{constructor(t,i,s,u){this.data=t,this.width=i,this.height=s,this.channels=u}get size(){return[this.width,this.height]}static async read(t){if(t instanceof RawImage)return t;if(isString(t)||t instanceof URL)return await this.fromURL(t);throw new Error(`Unsupported input type: ${typeof t}`)}static async fromURL(t){let i=await getFile(t);if(i.status!==200)throw new Error(`Unable to read image from "${t}" (${i.status} ${i.statusText})`);let s=await i.blob();return this.fromBlob(s)}static async fromBlob(t){if(BROWSER_ENV){let i=await loadImageFunction(t);const s=createCanvasFunction(i.width,i.height).getContext("2d");return s.drawImage(i,0,0),new this(s.getImageData(0,0,i.width,i.height).data,i.width,i.height,4)}else{let i=sharp(await t.arrayBuffer());return await loadImageFunction(i)}}static fromTensor(t,i="CHW"){if(i==="CHW")t=t.transpose(1,2,0);else if(i!=="HWC")throw new Error(`Unsupported channel format: ${i}`);return new RawImage(t.data,t.dims[1],t.dims[0],t.dims[2])}grayscale(){if(this.channels===1)return this;let t=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let i=0,s=0;i=0?f=s:l=-s,u>=0?c=u:n=-u,h.drawImage(a,f,c,t,i,l,n,t,i),new RawImage(h.getImageData(0,0,t,i).data,t,i,4).convert(d)}else{let d=this.toSharp();if(s>=0&&u>=0)d=d.extract({left:Math.floor(s),top:Math.floor(u),width:t,height:i});else if(s<=0&&u<=0){let a=Math.floor(-u),h=Math.floor(-s);d=d.extend({top:a,left:h,right:t-this.width-h,bottom:i-this.height-a})}else{let a=[0,0],h=0;u<0?(a[0]=Math.floor(-u),a[1]=i-this.height-a[0]):h=Math.floor(u);let f=[0,0],c=0;s<0?(f[0]=Math.floor(-s),f[1]=t-this.width-f[0]):c=Math.floor(s),d=d.extend({top:a[0],bottom:a[1],left:f[0],right:f[1]}).extract({left:c,top:h,width:t,height:i})}return await loadImageFunction(d)}}async toBlob(t="image/png",i=1){if(!BROWSER_ENV)throw new Error("toBlob() is only supported in browser environments.");return await this.toCanvas().convertToBlob({type:t,quality:i})}toCanvas(){if(!BROWSER_ENV)throw new Error("toCanvas() is only supported in browser environments.");let t=this.clone().rgba(),i=createCanvasFunction(t.width,t.height),s=new ImageDataClass(t.data,t.width,t.height);return i.getContext("2d").putImageData(s,0,0),i}_update(t,i,s,u=null){return this.data=t,this.width=i,this.height=s,u!==null&&(this.channels=u),this}clone(){return new RawImage(this.data.slice(),this.width,this.height,this.channels)}convert(t){if(this.channels===t)return this;switch(t){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(t){if(BROWSER_ENV){if(WEBWORKER_ENV)throw new Error("Unable to save an image from a Web Worker.");const i=t.split(".").pop().toLowerCase(),s=CONTENT_TYPE_MAP.get(i)??"image/png",u=await this.toBlob(s),d=URL.createObjectURL(u),a=document.createElement("a");a.href=d,a.download=t,a.click(),a.remove()}else{if(env$1.useFS)return await this.toSharp().toFile(t);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(m,t){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 i=await(await getFile(m)).arrayBuffer(),s=new AudioContext({sampleRate:t});typeof t>"u"&&console.warn(`No sampling rate provided, using default of ${s.sampleRate}Hz.`);const u=await s.decodeAudioData(i);let d;if(u.numberOfChannels===2){const a=Math.sqrt(2),h=u.getChannelData(0),f=u.getChannelData(1);d=new Float32Array(h.length);for(let c=0;c2595*Math.log10(1+m/700),kaldi:m=>1127*Math.log(1+m/700),slaney:(m,t=1e3,i=15,s=27/Math.log(6.4))=>m>=t?i+Math.log(m/t)*s:3*m/200};function hertz_to_mel(m,t="htk"){const i=HERTZ_TO_MEL_MAPPING[t];if(!i)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return typeof m=="number"?i(m):m.map(s=>i(s))}const MEL_TO_HERTZ_MAPPING={htk:m=>700*(10**(m/2595)-1),kaldi:m=>700*(Math.exp(m/1127)-1),slaney:(m,t=1e3,i=15,s=Math.log(6.4)/27)=>m>=i?t*Math.exp(s*(m-i)):200*m/3};function mel_to_hertz(m,t="htk"){const i=MEL_TO_HERTZ_MAPPING[t];if(!i)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return typeof m=="number"?i(m):m.map(s=>i(s))}function _create_triangular_filter_bank(m,t){const i=Float64Array.from({length:t.length-1},(a,h)=>t[h+1]-t[h]),s=Array.from({length:m.length},()=>new Array(t.length));for(let a=0;anew Array(m.length));for(let a=0;am+s*d)}function mel_filter_bank(m,t,i,s,u,d=null,a="htk",h=!1){if(d!==null&&d!=="slaney")throw new Error('norm must be one of null or "slaney"');const f=hertz_to_mel(i,a),c=hertz_to_mel(s,a),l=linspace(f,c,t+2);let n=mel_to_hertz(l,a),e;if(h){const o=u/(m*2);e=hertz_to_mel(Float64Array.from({length:m},(p,g)=>g*o),a),n=l}else e=linspace(0,Math.floor(u/2),m);const r=_create_triangular_filter_bank(e,n);if(d!==null&&d==="slaney")for(let o=0;ou)throw Error(`frame_length (${i}) may not be larger than fft_length (${u})`);if(w!==i)throw new Error(`Length of the window (${w}) must equal frame_length (${i})`);if(s<=0)throw new Error("hop_length must be greater than zero");if(a){if(h!=="reflect")throw new Error(`pad_mode="${h}" not implemented yet.`);const D=Math.floor((u-1)/2)+1;m=padReflect(m,D,D)}const T=Math.floor(1+Math.floor((m.length-i)/s)),S=f?Math.floor(u/2)+1:u;let A=T,P=T;_!==null&&(_>T?b&&(P=_):P=A=_);const x=new FFT(u),M=new Float64Array(u),N=new Float64Array(x.outputBufferSize),z=new Array(A);for(let D=0;D=1;--V)M[V]-=c*M[V-1];M[0]*=1-c}for(let V=0;Vs)throw new Error(`Length of the window (${m}) may not be larger than frame_length (${s})`);return a}function center_to_corners_format([m,t,i,s]){return[m-i/2,t-s/2,m+i/2,t+s/2]}function post_process_object_detection(m,t=.5,i=null,s=!1){const u=m.logits,d=m.pred_boxes,[a,h,f]=u.dims;if(i!==null&&i.length!==a)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let c=[];for(let l=0;lt&&_.push(y)}else{let y=max(g.data)[1];if(y===f-1)continue;_.push(y),b=softmax(g.data)}for(const y of _){let w=o[p].data;w=center_to_corners_format(w),n!==null&&(w=w.map((T,S)=>T*n[(S+1)%2])),e.boxes.push(w),e.classes.push(y),e.scores.push(b[y])}}c.push(e)}return c}function validate_audio_inputs(m,t){var i;if(!(m instanceof Float32Array||m instanceof Float64Array))throw new Error(`${t} expects input to be a Float32Array or a Float64Array, but got ${((i=m==null?void 0:m.constructor)==null?void 0:i.name)??typeof m} 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.`)}class FeatureExtractor extends Callable{constructor(t){super(),this.config=t}}class ImageFeatureExtractor extends FeatureExtractor{constructor(t){super(t),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.size_divisor=this.config.size_divisor,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.do_crop_margin=this.config.do_crop_margin,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(t,i,s=2){const u=t.height,d=t.width,a=i.height,h=i.width;let f=Math.min(u,a),c=Math.min(d,h);return f===u&&c===d?t:(u>d?c=Math.floor(d*f/u):d>u&&(f=Math.floor(u*c/d)),await t.resize(c,f,{resample:s}))}async crop_margin(t,i=200){const s=t.clone().grayscale(),u=min(s.data)[0],a=max(s.data)[0]-u;if(a===0)return t;const h=i/255;let f=s.width,c=s.height,l=0,n=0;for(let e=0;ethis.preprocess(d)));return s.forEach(d=>d.pixel_values.dims=[1,...d.pixel_values.dims]),{pixel_values:cat(s.map(d=>d.pixel_values)),original_sizes:s.map(d=>d.original_size),reshaped_input_sizes:s.map(d=>d.reshaped_input_size)}}}class DPTFeatureExtractor extends ImageFeatureExtractor{}class GLPNFeatureExtractor extends ImageFeatureExtractor{}class CLIPFeatureExtractor extends ImageFeatureExtractor{}class ConvNextFeatureExtractor extends ImageFeatureExtractor{}class ConvNextImageProcessor extends ConvNextFeatureExtractor{}class ViTFeatureExtractor extends ImageFeatureExtractor{}class MobileViTFeatureExtractor extends ImageFeatureExtractor{}class OwlViTFeatureExtractor extends ImageFeatureExtractor{post_process_object_detection(...t){return post_process_object_detection(...t)}}class DeiTFeatureExtractor extends ImageFeatureExtractor{}class BeitFeatureExtractor extends ImageFeatureExtractor{}class DonutFeatureExtractor extends ImageFeatureExtractor{pad_image(t,i,s,u={}){const[d,a,h]=i;let f=this.image_mean;Array.isArray(this.image_mean)||(f=new Array(h).fill(f)),this.image_std,Array.isArray(this.image_std)||new Array(h).fill(f);const c=f.map((l,n)=>-l/this.image_std[n]);return super.pad_image(t,i,s,{center:!0,constant_values:c,...u})}}class NougatImageProcessor extends DonutFeatureExtractor{}class DetrFeatureExtractor extends ImageFeatureExtractor{async _call(t){const i=await super._call(t),s=[i.pixel_values.dims[0],64,64],u=new Tensor("int64",new BigInt64Array(s.reduce((d,a)=>d*a)).fill(1n),s);return{...i,pixel_mask:u}}post_process_object_detection(...t){return post_process_object_detection(...t)}remove_low_and_no_objects(t,i,s,u){let d=[],a=[],h=[];for(let f=0;fs&&(d.push(l),a.push(r),h.push(n))}return[d,a,h]}check_segment_validity(t,i,s,u=.5,d=.8){let a=[],h=0,f=0;for(let l=0;l=u&&++f;let c=h>0&&f>0;return c&&(c=h/f>d),[c,a]}compute_segments(t,i,s,u,d,a=null,h=null){let[f,c]=h??t[0].dims,l=new Tensor("int32",new Int32Array(f*c),[f,c]),n=[];if(h!==null)for(let p=0;pr[_]&&(e[_]=p,r[_]=t[p].data[_])}let o=0;for(let p=0;pBigInt(Math.round(f)))),a);return{pixel_values:s,original_sizes:u,reshaped_input_sizes:d,input_points:h}}post_process_masks(t,i,s,{mask_threshold:u=0,binarize:d=!0,pad_size:a=null}={}){let h=[];a=a??this.pad_size;let f=[a.height,a.width];for(let c=0;cb>u),_.dims)),_.dims=[1,..._.dims],r.push(_)}let o=cat(r);h.push(o)}return h}}class Swin2SRImageProcessor extends ImageFeatureExtractor{pad_image(t,i,s,u={}){const[d,a,h]=i;return super.pad_image(t,i,{width:d+(s-d%s)%s,height:a+(s-a%s)%s},{mode:"symmetric",center:!1,constant_values:-1,...u})}}class WhisperFeatureExtractor extends FeatureExtractor{constructor(t){var i;super(t),(i=this.config).mel_filters??(i.mel_filters=mel_filter_bank(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney")),this.window=window_function(this.config.n_fft,"hann")}_extract_fbank_features(t){const{data:i,dims:s}=spectrogram(t,this.window,this.config.n_fft,this.config.hop_length,{power:2,mel_filters:this.config.mel_filters,log_mel:"log10",max_num_frames:this.config.nb_max_frames}),u=max(i)[0];for(let d=0;dthis.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`."),i=t.slice(0,this.config.n_samples)):(i=new Float32Array(this.config.n_samples),i.set(t));const{data:s,dims:u}=this._extract_fbank_features(i);return{input_features:new Tensor("float32",s,[1,...u])}}}class Wav2Vec2FeatureExtractor extends FeatureExtractor{_zero_mean_unit_var_norm(t){const s=t.reduce((d,a)=>d+a,0)/t.length,u=t.reduce((d,a)=>d+(a-s)**2,0)/t.length;return t.map(d=>(d-s)/Math.sqrt(u+1e-7))}async _call(t){validate_audio_inputs(t,"Wav2Vec2FeatureExtractor"),t instanceof Float64Array&&(t=new Float32Array(t));let i=t;this.config.do_normalize&&(i=this._zero_mean_unit_var_norm(i));const s=[1,i.length];return{input_values:new Tensor("float32",i,s),attention_mask:new Tensor("int64",new BigInt64Array(i.length).fill(1n),s)}}}class ASTFeatureExtractor extends FeatureExtractor{constructor(t){super(t);const i=this.config.sampling_rate,s=mel_filter_bank(256,this.config.num_mel_bins,20,Math.floor(i/2),i,null,"kaldi",!0);for(let u=0;u0)if(s==="rand_trunc"){a=!0;const f=Math.floor(Math.random()*(h+1));t=t.subarray(f,f+i),d=this._extract_fbank_features(t,this.mel_filters_slaney,this.config.nb_max_samples),d.dims=[1,...d.dims]}else throw new Error(`Truncation strategy "${s}" not implemented`);else{if(h<0){let f=new Float64Array(i);if(f.set(t),u==="repeat")for(let c=t.length;cRawImage.read(t))),m}class Pipeline extends Callable{constructor({task:t,model:i,tokenizer:s=null,processor:u=null}){super(),this.task=t,this.model=i,this.tokenizer=s,this.processor=u}async dispose(){await this.model.dispose()}async _call(t,...i){let s=this.tokenizer(t,{padding:!0,truncation:!0}),u=await this.model(s);return[s,u]}}class TextClassificationPipeline extends Pipeline{async _call(t,{topk:i=1}={}){let s=this.model.config.problem_type==="multi_label_classification"?f=>f.sigmoid().data:f=>softmax(f.data),[u,d]=await super._call(t),a=this.model.config.id2label,h=[];for(let f of d.logits){let c=s(f),n=getTopItems(c,i).map(function(e){return{label:a[e[0]],score:e[1]}});i===1?h.push(...n):h.push(n)}return Array.isArray(t)||i===1?h:h[0]}}class TokenClassificationPipeline extends Pipeline{async _call(t,{ignore_labels:i=["O"]}={}){let s=Array.isArray(t);s||(t=[t]);let u=this.tokenizer,[d,a]=await super._call(t),h=a.logits,f=this.model.config.id2label,c=[];for(let l=0;l[r,o]).filter(r=>r[1]>c),n=Array.from(softmax(d.end_logits[h].data)).map((r,o)=>[r,o]).filter(r=>r[1]>c),e=product(l,n).filter(r=>r[0][1]<=r[1][1]).map(r=>[r[0][1],r[1][1],r[0][0]*r[1][0]]).sort((r,o)=>o[2]-r[2]);for(let r=0;r{let o=[...f];return o[c]=r[0],{score:r[1],token:r[0],token_str:d.model.vocab[r[0]],sequence:d.decode(o,{skip_special_tokens:!0})}}))}return Array.isArray(t)?a:a[0]}}class Text2TextGenerationPipeline extends Pipeline{constructor(){super(...arguments);he(this,"_key","generated_text")}async _call(i,s={}){Array.isArray(i)||(i=[i]),this.model.config.prefix&&(i=i.map(c=>this.model.config.prefix+c));let u=this.model.config.task_specific_params;u&&u[this.task]&&u[this.task].prefix&&(i=i.map(c=>u[this.task].prefix+c));let d={padding:!0,truncation:!0},a;this instanceof TranslationPipeline&&"_build_translation_inputs"in this.tokenizer?a=this.tokenizer._build_translation_inputs(i,d,s).input_ids:a=this.tokenizer(i,d).input_ids;let h=await this.model.generate(a,s),f=this.tokenizer.batch_decode(h,{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);he(this,"_key","summary_text")}}class TranslationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);he(this,"_key","translation_text")}}class TextGenerationPipeline extends Pipeline{async _call(t,i={}){let s=typeof t=="string"||t instanceof String;s&&(t=[t]);const u=i.add_special_tokens??!1;this.tokenizer.padding_side="left";let d=this.tokenizer(t,{add_special_tokens:u,padding:!0,truncation:!0}),a=d.input_ids,h=d.attention_mask,f=await this.model.generate(a,i,null,{inputs_attention_mask:h});const c=this.tokenizer.batch_decode(f,{skip_special_tokens:!0}),l=Array.from({length:t.length},n=>[]);for(let n=0;n[i.toLowerCase(),s])),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(t,i,{hypothesis_template:s="This example is {}.",multi_label:u=!1}={}){let d=Array.isArray(t);d||(t=[t]),Array.isArray(i)||(i=[i]);let a=i.map(c=>s.replace("{}",c)),h=u||i.length===1,f=[];for(let c of t){let l=[];for(let r of a){let o=this.tokenizer(c,{text_pair:r,padding:!0,truncation:!0}),p=await this.model(o);h?l.push([p.logits.data[this.contradiction_id],p.logits.data[this.entailment_id]]):l.push(p.logits.data[this.entailment_id])}let n;h?n=l.map(r=>softmax(r)[1]):n=softmax(l);let e=n.map((r,o)=>[r,o]).sort((r,o)=>o[0]-r[0]);f.push({sequence:c,labels:e.map(r=>i[r[1]]),scores:e.map(r=>r[0])})}return d?f:f[0]}}class FeatureExtractionPipeline extends Pipeline{async _call(t,{pooling:i="none",normalize:s=!1}={}){let[u,d]=await super._call(t),a=d.last_hidden_state??d.logits;if(i!=="none")if(i==="mean")a=mean_pooling(a,u.attention_mask);else throw Error(`Pooling method '${i}' not supported.`);return s&&(a=a.normalize(2,-1)),a}}class AudioClassificationPipeline extends Pipeline{constructor(t){super(t)}async _preprocess(t,i){return isString(t)&&(t=await read_audio(t,i)),t}async _call(t,{topk:i=5}={}){let s=!Array.isArray(t);s&&(t=[t]);const u=this.model.config.id2label,d=this.processor.feature_extractor.config.sampling_rate;let a=[];for(let h of t){h=await this._preprocess(h,d);const f=await this.processor(h),l=(await this.model(f)).logits[0];let e=getTopItems(softmax(l.data),i).map(function(r){return{label:u[r[0]],score:r[1]}});i===1?a.push(...e):a.push(e)}return!s||i===1?a:a[0]}}class ZeroShotAudioClassificationPipeline extends Pipeline{constructor(t){super(t)}async _preprocess(t,i){return isString(t)&&(t=await read_audio(t,i)),t}async _call(t,i,{hypothesis_template:s="This is a sound of {}."}={}){const u=!Array.isArray(t);u&&(t=[t]);const d=i.map(c=>s.replace("{}",c)),a=this.tokenizer(d,{padding:!0,truncation:!0}),h=this.processor.feature_extractor.config.sampling_rate,f=[];for(let c of t){c=await this._preprocess(c,h);const l=await this.processor(c),n=await this.model({...a,...l}),e=softmax(n.logits_per_audio.data);f.push([...e].map((r,o)=>({score:r,label:i[o]})))}return u?f[0]:f}}class AutomaticSpeechRecognitionPipeline extends Pipeline{constructor(t){super(t)}async _preprocess(t,i){return isString(t)&&(t=await read_audio(t,i)),t}async _call(t,i={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(t,i);case"wav2vec2":return this._call_wav2vec2(t,i);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(t,i={}){i.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),i.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');let s=!Array.isArray(t);s&&(t=[t]);const u=this.processor.feature_extractor.config.sampling_rate;let d=[];for(let a of t){a=await this._preprocess(a,u);const h=await this.processor(a),c=(await this.model(h)).logits[0],l=[];for(let e of c)l.push(max(e.data)[1]);const n=this.tokenizer.decode(l);d.push({text:n})}return s?d[0]:d}async _call_whisper(t,i={}){let s=i.return_timestamps??!1,u=i.chunk_length_s??0,d=i.stride_length_s??null,a=i.chunk_callback??null,h=i.force_full_sequences??!1;s==="word"&&(i.return_token_timestamps=!0);let f=pop(i,"language",null),c=pop(i,"task",null);if(f||c||s){if(i.forced_decoder_ids)throw new Error("Cannot specify `language`/`task`/`return_timestamps` and `forced_decoder_ids` at the same time.");let p=this.tokenizer.get_decoder_prompt_ids({language:f,task:c,no_timestamps:!s});p.length>0&&(i.forced_decoder_ids=p)}let l=!Array.isArray(t);l&&(t=[t]);const n=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 o=[];for(let p of t){p=await this._preprocess(p,n);let g=[];if(u>0){if(d===null)d=u/6;else if(u<=d)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const y=n*u,w=n*d,T=y-2*w;let S=0;for(;S=p.length;g.push({stride:[A.length,x?0:w,M?0:w],input_features:P.input_features,is_last:M}),S+=T}}else g=[{stride:[p.length,0,0],input_features:(await this.processor(p)).input_features,is_last:!0}];for(let y of g){i.num_frames=Math.floor(y.stride[0]/r);let w=await this.model.generate(y.input_features,i);s==="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/n),a!==null&&a(y)}let[_,b]=this.tokenizer._decode_asr(g,{time_precision:e,return_timestamps:s,force_full_sequences:h});o.push({text:_,...b})}return l?o[0]:o}}class ImageToTextPipeline extends Pipeline{constructor(t){super(t)}async _call(t,i={}){let s=Array.isArray(t);t=await prepareImages(t);let{pixel_values:u}=await this.processor(t),d=[];for(let a of u){a.dims=[1,...a.dims];let h=await this.model.generate(a,i),f=this.tokenizer.batch_decode(h,{skip_special_tokens:!0}).map(c=>({generated_text:c.trim()}));d.push(f)}return s?d:d[0]}}class ImageClassificationPipeline extends Pipeline{constructor(t){super(t)}async _call(t,{topk:i=1}={}){let s=Array.isArray(t);t=await prepareImages(t);let{pixel_values:u}=await this.processor(t),d=await this.model({pixel_values:u}),a=this.model.config.id2label,h=[];for(let f of d.logits){let l=getTopItems(softmax(f.data),i).map(function(n){return{label:a[n[0]],score:n[1]}});i===1?h.push(...l):h.push(l)}return s||i===1?h:h[0]}}class ImageSegmentationPipeline extends Pipeline{constructor(t){super(t),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(t,{threshold:i=.5,mask_threshold:s=.5,overlap_mask_area_threshold:u=.8,label_ids_to_fuse:d=null,target_sizes:a=null,subtask:h=null}={}){if(Array.isArray(t)&&t.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");t=await prepareImages(t);let c=t.map(p=>[p.height,p.width]),{pixel_values:l,pixel_mask:n}=await this.processor(t),e=await this.model({pixel_values:l,pixel_mask:n}),r=null;if(h!==null)r=this.subtasks_mapping[h];else for(let[p,g]of Object.entries(this.subtasks_mapping))if(g in this.processor.feature_extractor){r=this.processor.feature_extractor[g].bind(this.processor.feature_extractor),h=p;break}let o=[];if(h==="panoptic"||h==="instance"){let p=r(e,i,s,u,d,a??c)[0],g=p.segmentation,_=this.model.config.id2label;for(let b of p.segments_info){let y=new Uint8ClampedArray(g.data.length);for(let T=0;Ts.replace("{}",l)),a=this.tokenizer(d,{padding:!0,truncation:!0}),{pixel_values:h}=await this.processor(t),f=await this.model({...a,pixel_values:h}),c=[];for(let l of f.logits_per_image){let n=softmax(l.data);c.push([...n].map((e,r)=>({score:e,label:i[r]})))}return u?c:c[0]}}class ObjectDetectionPipeline extends Pipeline{constructor(t){super(t)}async _call(t,{threshold:i=.9,percentage:s=!1}={}){let u=Array.isArray(t);if(u&&t.length!==1)throw Error("Object detection pipeline currently only supports a batch size of 1.");t=await prepareImages(t);let d=s?null:t.map(e=>[e.height,e.width]),{pixel_values:a,pixel_mask:h}=await this.processor(t),f=await this.model({pixel_values:a,pixel_mask:h}),c=this.processor.feature_extractor.post_process_object_detection(f,i,d),l=this.model.config.id2label;const n=c.map(e=>e.boxes.map((r,o)=>({score:e.scores[o],label:l[e.classes[o]],box:get_bounding_box(r,!s)})));return u?n:n[0]}}class ZeroShotObjectDetectionPipeline extends Pipeline{constructor(t){super(t)}async _call(t,i,{threshold:s=.1,topk:u=null,percentage:d=!1}={}){const a=Array.isArray(t);t=await prepareImages(t);const h=this.tokenizer(i,{padding:!0,truncation:!0}),f=await this.processor(t),c=[];for(let l=0;l({score:p.scores[b],label:i[p.classes[b]],box:get_bounding_box(_,!d)})).sort((_,b)=>b.score-_.score);u!==null&&(g=g.slice(0,u)),c.push(g)}return a?c:c[0]}}class DocumentQuestionAnsweringPipeline extends Pipeline{constructor(t){super(t)}async _call(t,i,s={}){t=(await prepareImages(t))[0];const{pixel_values:u}=await this.processor(t),d=`${i}`,a=this.tokenizer(d,{add_special_tokens:!1,padding:!0,truncation:!0}).input_ids,h=await this.model.generate(u,{...s,decoder_input_ids:a,max_length:this.model.config.decoder.max_position_embeddings}),c=this.tokenizer.batch_decode(h)[0].match(/(.*?)<\/s_answer>/);let l=null;return c&&c.length>=2&&(l=c[1].trim()),[{answer:l}]}}class TextToAudioPipeline extends Pipeline{constructor(i){super(i);he(this,"DEFAULT_VOCODER_ID","Xenova/speecht5_hifigan");this.vocoder=i.vocoder??null}async _call(i,{speaker_embeddings:s=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 s=="string"||s instanceof URL)&&(s=new Float32Array(await(await fetch(s)).arrayBuffer())),s instanceof Float32Array)s=new Tensor("float32",s,[1,s.length]);else if(!(s instanceof Tensor))throw new Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");const{input_ids:u}=this.tokenizer(i,{padding:!0,truncation:!0}),{waveform:d}=await this.model.generate_speech(u,s,{vocoder:this.vocoder}),a=this.processor.feature_extractor.config.sampling_rate;return{audio:d.data,sampling_rate:a}}}class ImageToImagePipeline extends Pipeline{async _call(t){t=await prepareImages(t);let i=await this.processor(t),s=await this.model(i),u=[];for(let d of s.reconstruction){const a=d.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");u.push(RawImage.fromTensor(a))}return u.length>1?u:u[0]}}class DepthEstimationPipeline extends Pipeline{async _call(t){t=await prepareImages(t);const i=await this.processor(t),{predicted_depth:s}=await this.model(i),u=[];for(let d=0;d1?u:u[0]}}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"},"zero-shot-audio-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotAudioClassificationPipeline,model:AutoModel,processor:AutoProcessor,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"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"},"zero-shot-object-detection":{tokenizer:AutoTokenizer,pipeline:ZeroShotObjectDetectionPipeline,model:AutoModelForZeroShotObjectDetection,processor:AutoProcessor,default:{model:"Xenova/owlvit-base-patch32"},type:"multimodal"},"document-question-answering":{tokenizer:AutoTokenizer,pipeline:DocumentQuestionAnsweringPipeline,model:AutoModelForDocumentQuestionAnswering,processor:AutoProcessor,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"image-to-image":{pipeline:ImageToImagePipeline,model:AutoModelForImageToImage,processor:AutoProcessor,default:{model:"Xenova/swin2SR-classical-sr-x2-64"},type:"image"},"depth-estimation":{pipeline:DepthEstimationPipeline,model:AutoModelForDepthEstimation,processor:AutoProcessor,default:{model:"Xenova/dpt-large"},type:"image"},"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(m,t=null,{quantized:i=!0,progress_callback:s=null,config:u=null,cache_dir:d=null,local_files_only:a=!1,revision:h="main"}={}){m=TASK_ALIASES[m]??m;let f=SUPPORTED_TASKS[m.split("_",1)[0]];if(!f)throw Error(`Unsupported pipeline: ${m}. Must be one of [${Object.keys(SUPPORTED_TASKS)}]`);t||(t=f.default.model,console.log(`No model specified. Using default model: "${t}".`));let c={quantized:i,progress_callback:s,config:u,cache_dir:d,local_files_only:a,revision:h};const l=new Map([["tokenizer",f.tokenizer],["model",f.model],["processor",f.processor]]);let n=await loadItems(l,t,c);n.task=m,dispatchCallback(s,{status:"ready",task:m,model:t});let e=f.pipeline;return new e(n)}async function loadItems(m,t,i){const s=Object.create(null),u=[];for(let[d,a]of m.entries()){if(!a)continue;let h;Array.isArray(a)?h=new Promise(async(f,c)=>{let l;for(let n of a)try{f(await n.from_pretrained(t,i));return}catch(e){l=e}c(l)}):h=a.from_pretrained(t,i),s[d]=h,u.push(h)}await Promise.all(u);for(let[d,a]of Object.entries(s))s[d]=await a;return s}self.addEventListener("message",async m=>{let t=await MyTranslationPipeline.getInstance(s=>{self.postMessage(s)}),i=await t(m.data.text,{tgt_lang:m.data.tgt_lang,src_lang:m.data.src_lang,callback_function:s=>{self.postMessage({status:"update",output:t.tokenizer.decode(s[0].output_token_ids,{skip_special_tokens:!0})})}});self.postMessage({status:"complete",output:i})});class MyTranslationPipeline{static async getInstance(t=null){return this.instance===null&&(this.instance=pipeline(this.task,this.model,{progress_callback:t})),this.instance}}he(MyTranslationPipeline,"task","translation"),he(MyTranslationPipeline,"model","Xenova/nllb-200-distilled-600M"),he(MyTranslationPipeline,"instance",null)})();