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ERR: ${o.map(l=>`[${l.name}] ${l.err}`).join(", ")}`)};class EnvImpl{constructor(){this.wasm={},this.webgl={},this.logLevelInternal="warning"}set logLevel(n){if(n!==void 0){if(typeof n!="string"||["verbose","info","warning","error","fatal"].indexOf(n)===-1)throw new Error(`Unsupported logging level: ${n}`);this.logLevelInternal=n}}get logLevel(){return this.logLevelInternal}}const env$1=new EnvImpl,isBigInt64ArrayAvailable=typeof BigInt64Array<"u"&&typeof BigInt64Array.from=="function",isBigUint64ArrayAvailable=typeof BigUint64Array<"u"&&typeof BigUint64Array.from=="function",NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP=new Map([["float32",Float32Array],["uint8",Uint8Array],["int8",Int8Array],["uint16",Uint16Array],["int16",Int16Array],["int32",Int32Array],["bool",Uint8Array],["float64",Float64Array],["uint32",Uint32Array]]),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP=new Map([[Float32Array,"float32"],[Uint8Array,"uint8"],[Int8Array,"int8"],[Uint16Array,"uint16"],[Int16Array,"int16"],[Int32Array,"int32"],[Float64Array,"float64"],[Uint32Array,"uint32"]]);isBigInt64ArrayAvailable&&(NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set("int64",BigInt64Array),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigInt64Array,"int64")),isBigUint64ArrayAvailable&&(NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set("uint64",BigUint64Array),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigUint64Array,"uint64"));const calculateSize=y=>{let n=1;for(let o=0;o<y.length;o++){const l=y[o];if(typeof l!="number"||!Number.isSafeInteger(l))throw new TypeError(`dims[${o}] must be an integer, got: ${l}`);if(l<0)throw new RangeError(`dims[${o}] must be a non-negative integer, got: ${l}`);n*=l}return n};let Tensor$2=class ut{constructor(n,o,l){let c,f,a;if(typeof n=="string")if(c=n,a=l,n==="string"){if(!Array.isArray(o))throw new TypeError("A string tensor's data must be a string array.");f=o}else{const 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bufferToTensor(n,o){if(n===void 0)throw new Error("Image buffer must be defined");if(o.height===void 0||o.width===void 0)throw new Error("Image height and width must be defined");const{height:l,width:c}=o,f=o.norm;let a,h;f===void 0||f.mean===void 0?a=255:a=f.mean,f===void 0||f.bias===void 0?h=0:h=f.bias;const p=o.bitmapFormat!==void 0?o.bitmapFormat:"RGBA",u=o.tensorFormat!==void 0&&o.tensorFormat!==void 0?o.tensorFormat:"RGB",s=l*c,t=u==="RGBA"?new Float32Array(s*4):new Float32Array(s*3);let e=4,r=0,i=1,d=2,g=3,m=0,b=s,_=s*2,v=-1;p==="RGB"&&(e=3,r=0,i=1,d=2,g=-1),u==="RGBA"?v=s*3:u==="RBG"?(m=0,_=s,b=s*2):u==="BGR"&&(_=0,b=s,m=s*2);for(let S=0;S<s;S++,r+=e,d+=e,i+=e,g+=e)t[m++]=(n[r]+h)/a,t[b++]=(n[i]+h)/a,t[_++]=(n[d]+h)/a,v!==-1&&g!==-1&&(t[v++]=(n[g]+h)/a);return u==="RGBA"?new ut("float32",t,[1,4,l,c]):new ut("float32",t,[1,3,l,c])}static async fromImage(n,o){const l=typeof HTMLImageElement<"u"&&n instanceof HTMLImageElement,c=typeof ImageData<"u"&&n instanceof ImageData,f=typeof 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d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.name!=null&&e.hasOwnProperty("name")&&!u.isString(e.name))return"name: string expected";if(e.refAttrName!=null&&e.hasOwnProperty("refAttrName")&&!u.isString(e.refAttrName))return"refAttrName: string expected";if(e.docString!=null&&e.hasOwnProperty("docString")&&!u.isString(e.docString))return"docString: string expected";if(e.type!=null&&e.hasOwnProperty("type"))switch(e.type){default:return"type: enum value expected";case 0:case 1:case 2:case 3:case 4:case 5:case 6:case 7:case 8:case 9:case 10:}if(e.f!=null&&e.hasOwnProperty("f")&&typeof e.f!="number")return"f: number expected";if(e.i!=null&&e.hasOwnProperty("i")&&!(u.isInteger(e.i)||e.i&&u.isInteger(e.i.low)&&u.isInteger(e.i.high)))return"i: integer|Long expected";if(e.s!=null&&e.hasOwnProperty("s")&&!(e.s&&typeof e.s.length=="number"||u.isString(e.s)))return"s: buffer expected";if(e.t!=null&&e.hasOwnProperty("t")&&(i=s.onnx.TensorProto.verify(e.t)))return"t."+i;if(e.g!=null&&e.hasOwnProperty("g")&&(i=s.onnx.GraphProto.verify(e.g)))return"g."+i;if(e.floats!=null&&e.hasOwnProperty("floats")){if(!Array.isArray(e.floats))return"floats: array expected";for(var r=0;r<e.floats.length;++r)if(typeof e.floats[r]!="number")return"floats: number[] expected"}if(e.ints!=null&&e.hasOwnProperty("ints")){if(!Array.isArray(e.ints))return"ints: array expected";for(r=0;r<e.ints.length;++r)if(!(u.isInteger(e.ints[r])||e.ints[r]&&u.isInteger(e.ints[r].low)&&u.isInteger(e.ints[r].high)))return"ints: integer|Long[] expected"}if(e.strings!=null&&e.hasOwnProperty("strings")){if(!Array.isArray(e.strings))return"strings: array expected";for(r=0;r<e.strings.length;++r)if(!(e.strings[r]&&typeof e.strings[r].length=="number"||u.isString(e.strings[r])))return"strings: buffer[] expected"}if(e.tensors!=null&&e.hasOwnProperty("tensors")){if(!Array.isArray(e.tensors))return"tensors: array expected";for(r=0;r<e.tensors.length;++r)if(i=s.onnx.TensorProto.verify(e.tensors[r]))return"tensors."+i}if(e.graphs!=null&&e.hasOwnProperty("graphs")){if(!Array.isArray(e.graphs))return"graphs: array expected";for(r=0;r<e.graphs.length;++r){var i;if(i=s.onnx.GraphProto.verify(e.graphs[r]))return"graphs."+i}}return null},t.fromObject=function(e){if(e instanceof s.onnx.AttributeProto)return e;var r=new s.onnx.AttributeProto;switch(e.name!=null&&(r.name=String(e.name)),e.refAttrName!=null&&(r.refAttrName=String(e.refAttrName)),e.docString!=null&&(r.docString=String(e.docString)),e.type){case"UNDEFINED":case 0:r.type=0;break;case"FLOAT":case 1:r.type=1;break;case"INT":case 2:r.type=2;break;case"STRING":case 3:r.type=3;break;case"TENSOR":case 4:r.type=4;break;case"GRAPH":case 5:r.type=5;break;case"FLOATS":case 6:r.type=6;break;case"INTS":case 7:r.type=7;break;case"STRINGS":case 8:r.type=8;break;case"TENSORS":case 9:r.type=9;break;case"GRAPHS":case 10:r.type=10}if(e.f!=null&&(r.f=Number(e.f)),e.i!=null&&(u.Long?(r.i=u.Long.fromValue(e.i)).unsigned=!1:typeof e.i=="string"?r.i=parseInt(e.i,10):typeof e.i=="number"?r.i=e.i:typeof e.i=="object"&&(r.i=new u.LongBits(e.i.low>>>0,e.i.high>>>0).toNumber())),e.s!=null&&(typeof e.s=="string"?u.base64.decode(e.s,r.s=u.newBuffer(u.base64.length(e.s)),0):e.s.length&&(r.s=e.s)),e.t!=null){if(typeof e.t!="object")throw TypeError(".onnx.AttributeProto.t: object expected");r.t=s.onnx.TensorProto.fromObject(e.t)}if(e.g!=null){if(typeof e.g!="object")throw TypeError(".onnx.AttributeProto.g: object expected");r.g=s.onnx.GraphProto.fromObject(e.g)}if(e.floats){if(!Array.isArray(e.floats))throw TypeError(".onnx.AttributeProto.floats: array expected");r.floats=[];for(var i=0;i<e.floats.length;++i)r.floats[i]=Number(e.floats[i])}if(e.ints){if(!Array.isArray(e.ints))throw TypeError(".onnx.AttributeProto.ints: array expected");for(r.ints=[],i=0;i<e.ints.length;++i)u.Long?(r.ints[i]=u.Long.fromValue(e.ints[i])).unsigned=!1:typeof e.ints[i]=="string"?r.ints[i]=parseInt(e.ints[i],10):typeof e.ints[i]=="number"?r.ints[i]=e.ints[i]:typeof e.ints[i]=="object"&&(r.ints[i]=new u.LongBits(e.ints[i].low>>>0,e.ints[i].high>>>0).toNumber())}if(e.strings){if(!Array.isArray(e.strings))throw TypeError(".onnx.AttributeProto.strings: array expected");for(r.strings=[],i=0;i<e.strings.length;++i)typeof e.strings[i]=="string"?u.base64.decode(e.strings[i],r.strings[i]=u.newBuffer(u.base64.length(e.strings[i])),0):e.strings[i].length&&(r.strings[i]=e.strings[i])}if(e.tensors){if(!Array.isArray(e.tensors))throw TypeError(".onnx.AttributeProto.tensors: array expected");for(r.tensors=[],i=0;i<e.tensors.length;++i){if(typeof e.tensors[i]!="object")throw TypeError(".onnx.AttributeProto.tensors: object expected");r.tensors[i]=s.onnx.TensorProto.fromObject(e.tensors[i])}}if(e.graphs){if(!Array.isArray(e.graphs))throw TypeError(".onnx.AttributeProto.graphs: array expected");for(r.graphs=[],i=0;i<e.graphs.length;++i){if(typeof e.graphs[i]!="object")throw TypeError(".onnx.AttributeProto.graphs: object expected");r.graphs[i]=s.onnx.GraphProto.fromObject(e.graphs[i])}}return r},t.toObject=function(e,r){r||(r={});var i={};if((r.arrays||r.defaults)&&(i.floats=[],i.ints=[],i.strings=[],i.tensors=[],i.graphs=[]),r.defaults){if(i.name="",i.f=0,u.Long){var d=new u.Long(0,0,!1);i.i=r.longs===String?d.toString():r.longs===Number?d.toNumber():d}else i.i=r.longs===String?"0":0;r.bytes===String?i.s="":(i.s=[],r.bytes!==Array&&(i.s=u.newBuffer(i.s))),i.t=null,i.g=null,i.docString="",i.type=r.enums===String?"UNDEFINED":0,i.refAttrName=""}if(e.name!=null&&e.hasOwnProperty("name")&&(i.name=e.name),e.f!=null&&e.hasOwnProperty("f")&&(i.f=r.json&&!isFinite(e.f)?String(e.f):e.f),e.i!=null&&e.hasOwnProperty("i")&&(typeof e.i=="number"?i.i=r.longs===String?String(e.i):e.i:i.i=r.longs===String?u.Long.prototype.toString.call(e.i):r.longs===Number?new u.LongBits(e.i.low>>>0,e.i.high>>>0).toNumber():e.i),e.s!=null&&e.hasOwnProperty("s")&&(i.s=r.bytes===String?u.base64.encode(e.s,0,e.s.length):r.bytes===Array?Array.prototype.slice.call(e.s):e.s),e.t!=null&&e.hasOwnProperty("t")&&(i.t=s.onnx.TensorProto.toObject(e.t,r)),e.g!=null&&e.hasOwnProperty("g")&&(i.g=s.onnx.GraphProto.toObject(e.g,r)),e.floats&&e.floats.length){i.floats=[];for(var g=0;g<e.floats.length;++g)i.floats[g]=r.json&&!isFinite(e.floats[g])?String(e.floats[g]):e.floats[g]}if(e.ints&&e.ints.length)for(i.ints=[],g=0;g<e.ints.length;++g)typeof e.ints[g]=="number"?i.ints[g]=r.longs===String?String(e.ints[g]):e.ints[g]:i.ints[g]=r.longs===String?u.Long.prototype.toString.call(e.ints[g]):r.longs===Number?new u.LongBits(e.ints[g].low>>>0,e.ints[g].high>>>0).toNumber():e.ints[g];if(e.strings&&e.strings.length)for(i.strings=[],g=0;g<e.strings.length;++g)i.strings[g]=r.bytes===String?u.base64.encode(e.strings[g],0,e.strings[g].length):r.bytes===Array?Array.prototype.slice.call(e.strings[g]):e.strings[g];if(e.tensors&&e.tensors.length)for(i.tensors=[],g=0;g<e.tensors.length;++g)i.tensors[g]=s.onnx.TensorProto.toObject(e.tensors[g],r);if(e.graphs&&e.graphs.length)for(i.graphs=[],g=0;g<e.graphs.length;++g)i.graphs[g]=s.onnx.GraphProto.toObject(e.graphs[g],r);return e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),e.type!=null&&e.hasOwnProperty("type")&&(i.type=r.enums===String?s.onnx.AttributeProto.AttributeType[e.type]:e.type),e.refAttrName!=null&&e.hasOwnProperty("refAttrName")&&(i.refAttrName=e.refAttrName),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},t.AttributeType=function(){var e={},r=Object.create(e);return r[e[0]="UNDEFINED"]=0,r[e[1]="FLOAT"]=1,r[e[2]="INT"]=2,r[e[3]="STRING"]=3,r[e[4]="TENSOR"]=4,r[e[5]="GRAPH"]=5,r[e[6]="FLOATS"]=6,r[e[7]="INTS"]=7,r[e[8]="STRINGS"]=8,r[e[9]="TENSORS"]=9,r[e[10]="GRAPHS"]=10,r}(),t}(),f.ValueInfoProto=function(){function t(e){if(e)for(var r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.name="",t.prototype.type=null,t.prototype.docString="",t.create=function(e){return new t(e)},t.encode=function(e,r){return r||(r=p.create()),e.name!=null&&e.hasOwnProperty("name")&&r.uint32(10).string(e.name),e.type!=null&&e.hasOwnProperty("type")&&s.onnx.TypeProto.encode(e.type,r.uint32(18).fork()).ldelim(),e.docString!=null&&e.hasOwnProperty("docString")&&r.uint32(26).string(e.docString),r},t.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},t.decode=function(e,r){e instanceof h||(e=h.create(e));for(var i=r===void 0?e.len:e.pos+r,d=new s.onnx.ValueInfoProto;e.pos<i;){var g=e.uint32();switch(g>>>3){case 1:d.name=e.string();break;case 2:d.type=s.onnx.TypeProto.decode(e,e.uint32());break;case 3:d.docString=e.string();break;default:e.skipType(7&g)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.name!=null&&e.hasOwnProperty("name")&&!u.isString(e.name))return"name: string expected";if(e.type!=null&&e.hasOwnProperty("type")){var r=s.onnx.TypeProto.verify(e.type);if(r)return"type."+r}return e.docString!=null&&e.hasOwnProperty("docString")&&!u.isString(e.docString)?"docString: string expected":null},t.fromObject=function(e){if(e instanceof s.onnx.ValueInfoProto)return e;var r=new s.onnx.ValueInfoProto;if(e.name!=null&&(r.name=String(e.name)),e.type!=null){if(typeof e.type!="object")throw TypeError(".onnx.ValueInfoProto.type: object expected");r.type=s.onnx.TypeProto.fromObject(e.type)}return e.docString!=null&&(r.docString=String(e.docString)),r},t.toObject=function(e,r){r||(r={});var i={};return r.defaults&&(i.name="",i.type=null,i.docString=""),e.name!=null&&e.hasOwnProperty("name")&&(i.name=e.name),e.type!=null&&e.hasOwnProperty("type")&&(i.type=s.onnx.TypeProto.toObject(e.type,r)),e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},t}(),f.NodeProto=function(){function t(e){if(this.input=[],this.output=[],this.attribute=[],e)for(var r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.input=u.emptyArray,t.prototype.output=u.emptyArray,t.prototype.name="",t.prototype.opType="",t.prototype.domain="",t.prototype.attribute=u.emptyArray,t.prototype.docString="",t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=p.create()),e.input!=null&&e.input.length)for(var i=0;i<e.input.length;++i)r.uint32(10).string(e.input[i]);if(e.output!=null&&e.output.length)for(i=0;i<e.output.length;++i)r.uint32(18).string(e.output[i]);if(e.name!=null&&e.hasOwnProperty("name")&&r.uint32(26).string(e.name),e.opType!=null&&e.hasOwnProperty("opType")&&r.uint32(34).string(e.opType),e.attribute!=null&&e.attribute.length)for(i=0;i<e.attribute.length;++i)s.onnx.AttributeProto.encode(e.attribute[i],r.uint32(42).fork()).ldelim();return e.docString!=null&&e.hasOwnProperty("docString")&&r.uint32(50).string(e.docString),e.domain!=null&&e.hasOwnProperty("domain")&&r.uint32(58).string(e.domain),r},t.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},t.decode=function(e,r){e instanceof h||(e=h.create(e));for(var i=r===void 0?e.len:e.pos+r,d=new s.onnx.NodeProto;e.pos<i;){var g=e.uint32();switch(g>>>3){case 1:d.input&&d.input.length||(d.input=[]),d.input.push(e.string());break;case 2:d.output&&d.output.length||(d.output=[]),d.output.push(e.string());break;case 3:d.name=e.string();break;case 4:d.opType=e.string();break;case 7:d.domain=e.string();break;case 5:d.attribute&&d.attribute.length||(d.attribute=[]),d.attribute.push(s.onnx.AttributeProto.decode(e,e.uint32()));break;case 6:d.docString=e.string();break;default:e.skipType(7&g)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.input!=null&&e.hasOwnProperty("input")){if(!Array.isArray(e.input))return"input: array expected";for(var r=0;r<e.input.length;++r)if(!u.isString(e.input[r]))return"input: string[] expected"}if(e.output!=null&&e.hasOwnProperty("output")){if(!Array.isArray(e.output))return"output: array expected";for(r=0;r<e.output.length;++r)if(!u.isString(e.output[r]))return"output: string[] expected"}if(e.name!=null&&e.hasOwnProperty("name")&&!u.isString(e.name))return"name: string expected";if(e.opType!=null&&e.hasOwnProperty("opType")&&!u.isString(e.opType))return"opType: string expected";if(e.domain!=null&&e.hasOwnProperty("domain")&&!u.isString(e.domain))return"domain: string expected";if(e.attribute!=null&&e.hasOwnProperty("attribute")){if(!Array.isArray(e.attribute))return"attribute: array expected";for(r=0;r<e.attribute.length;++r){var i=s.onnx.AttributeProto.verify(e.attribute[r]);if(i)return"attribute."+i}}return e.docString!=null&&e.hasOwnProperty("docString")&&!u.isString(e.docString)?"docString: string expected":null},t.fromObject=function(e){if(e instanceof s.onnx.NodeProto)return e;var r=new s.onnx.NodeProto;if(e.input){if(!Array.isArray(e.input))throw TypeError(".onnx.NodeProto.input: array expected");r.input=[];for(var i=0;i<e.input.length;++i)r.input[i]=String(e.input[i])}if(e.output){if(!Array.isArray(e.output))throw TypeError(".onnx.NodeProto.output: array expected");for(r.output=[],i=0;i<e.output.length;++i)r.output[i]=String(e.output[i])}if(e.name!=null&&(r.name=String(e.name)),e.opType!=null&&(r.opType=String(e.opType)),e.domain!=null&&(r.domain=String(e.domain)),e.attribute){if(!Array.isArray(e.attribute))throw TypeError(".onnx.NodeProto.attribute: array expected");for(r.attribute=[],i=0;i<e.attribute.length;++i){if(typeof e.attribute[i]!="object")throw TypeError(".onnx.NodeProto.attribute: object expected");r.attribute[i]=s.onnx.AttributeProto.fromObject(e.attribute[i])}}return e.docString!=null&&(r.docString=String(e.docString)),r},t.toObject=function(e,r){r||(r={});var i={};if((r.arrays||r.defaults)&&(i.input=[],i.output=[],i.attribute=[]),r.defaults&&(i.name="",i.opType="",i.docString="",i.domain=""),e.input&&e.input.length){i.input=[];for(var d=0;d<e.input.length;++d)i.input[d]=e.input[d]}if(e.output&&e.output.length)for(i.output=[],d=0;d<e.output.length;++d)i.output[d]=e.output[d];if(e.name!=null&&e.hasOwnProperty("name")&&(i.name=e.name),e.opType!=null&&e.hasOwnProperty("opType")&&(i.opType=e.opType),e.attribute&&e.attribute.length)for(i.attribute=[],d=0;d<e.attribute.length;++d)i.attribute[d]=s.onnx.AttributeProto.toObject(e.attribute[d],r);return e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),e.domain!=null&&e.hasOwnProperty("domain")&&(i.domain=e.domain),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},t}(),f.ModelProto=function(){function t(e){if(this.opsetImport=[],this.metadataProps=[],e)for(var r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.irVersion=u.Long?u.Long.fromBits(0,0,!1):0,t.prototype.opsetImport=u.emptyArray,t.prototype.producerName="",t.prototype.producerVersion="",t.prototype.domain="",t.prototype.modelVersion=u.Long?u.Long.fromBits(0,0,!1):0,t.prototype.docString="",t.prototype.graph=null,t.prototype.metadataProps=u.emptyArray,t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=p.create()),e.irVersion!=null&&e.hasOwnProperty("irVersion")&&r.uint32(8).int64(e.irVersion),e.producerName!=null&&e.hasOwnProperty("producerName")&&r.uint32(18).string(e.producerName),e.producerVersion!=null&&e.hasOwnProperty("producerVersion")&&r.uint32(26).string(e.producerVersion),e.domain!=null&&e.hasOwnProperty("domain")&&r.uint32(34).string(e.domain),e.modelVersion!=null&&e.hasOwnProperty("modelVersion")&&r.uint32(40).int64(e.modelVersion),e.docString!=null&&e.hasOwnProperty("docString")&&r.uint32(50).string(e.docString),e.graph!=null&&e.hasOwnProperty("graph")&&s.onnx.GraphProto.encode(e.graph,r.uint32(58).fork()).ldelim(),e.opsetImport!=null&&e.opsetImport.length)for(var i=0;i<e.opsetImport.length;++i)s.onnx.OperatorSetIdProto.encode(e.opsetImport[i],r.uint32(66).fork()).ldelim();if(e.metadataProps!=null&&e.metadataProps.length)for(i=0;i<e.metadataProps.length;++i)s.onnx.StringStringEntryProto.encode(e.metadataProps[i],r.uint32(114).fork()).ldelim();return r},t.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},t.decode=function(e,r){e instanceof h||(e=h.create(e));for(var i=r===void 0?e.len:e.pos+r,d=new s.onnx.ModelProto;e.pos<i;){var g=e.uint32();switch(g>>>3){case 1:d.irVersion=e.int64();break;case 8:d.opsetImport&&d.opsetImport.length||(d.opsetImport=[]),d.opsetImport.push(s.onnx.OperatorSetIdProto.decode(e,e.uint32()));break;case 2:d.producerName=e.string();break;case 3:d.producerVersion=e.string();break;case 4:d.domain=e.string();break;case 5:d.modelVersion=e.int64();break;case 6:d.docString=e.string();break;case 7:d.graph=s.onnx.GraphProto.decode(e,e.uint32());break;case 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s.onnx.ModelProto)return e;var r=new s.onnx.ModelProto;if(e.irVersion!=null&&(u.Long?(r.irVersion=u.Long.fromValue(e.irVersion)).unsigned=!1:typeof e.irVersion=="string"?r.irVersion=parseInt(e.irVersion,10):typeof e.irVersion=="number"?r.irVersion=e.irVersion:typeof e.irVersion=="object"&&(r.irVersion=new u.LongBits(e.irVersion.low>>>0,e.irVersion.high>>>0).toNumber())),e.opsetImport){if(!Array.isArray(e.opsetImport))throw TypeError(".onnx.ModelProto.opsetImport: array expected");r.opsetImport=[];for(var i=0;i<e.opsetImport.length;++i){if(typeof e.opsetImport[i]!="object")throw TypeError(".onnx.ModelProto.opsetImport: object expected");r.opsetImport[i]=s.onnx.OperatorSetIdProto.fromObject(e.opsetImport[i])}}if(e.producerName!=null&&(r.producerName=String(e.producerName)),e.producerVersion!=null&&(r.producerVersion=String(e.producerVersion)),e.domain!=null&&(r.domain=String(e.domain)),e.modelVersion!=null&&(u.Long?(r.modelVersion=u.Long.fromValue(e.modelVersion)).unsigned=!1:typeof 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r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.key="",t.prototype.value="",t.create=function(e){return new t(e)},t.encode=function(e,r){return r||(r=p.create()),e.key!=null&&e.hasOwnProperty("key")&&r.uint32(10).string(e.key),e.value!=null&&e.hasOwnProperty("value")&&r.uint32(18).string(e.value),r},t.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},t.decode=function(e,r){e instanceof h||(e=h.create(e));for(var i=r===void 0?e.len:e.pos+r,d=new s.onnx.StringStringEntryProto;e.pos<i;){var g=e.uint32();switch(g>>>3){case 1:d.key=e.string();break;case 2:d.value=e.string();break;default:e.skipType(7&g)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){return typeof e!="object"||e===null?"object expected":e.key!=null&&e.hasOwnProperty("key")&&!u.isString(e.key)?"key: string expected":e.value!=null&&e.hasOwnProperty("value")&&!u.isString(e.value)?"value: string expected":null},t.fromObject=function(e){if(e instanceof s.onnx.StringStringEntryProto)return e;var r=new s.onnx.StringStringEntryProto;return e.key!=null&&(r.key=String(e.key)),e.value!=null&&(r.value=String(e.value)),r},t.toObject=function(e,r){r||(r={});var i={};return r.defaults&&(i.key="",i.value=""),e.key!=null&&e.hasOwnProperty("key")&&(i.key=e.key),e.value!=null&&e.hasOwnProperty("value")&&(i.value=e.value),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},t}(),f.TensorAnnotation=function(){function t(e){if(this.quantParameterTensorNames=[],e)for(var r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.tensorName="",t.prototype.quantParameterTensorNames=u.emptyArray,t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=p.create()),e.tensorName!=null&&e.hasOwnProperty("tensorName")&&r.uint32(10).string(e.tensorName),e.quantParameterTensorNames!=null&&e.quantParameterTensorNames.length)for(var i=0;i<e.quantParameterTensorNames.length;++i)s.onnx.StringStringEntryProto.encode(e.quantParameterTensorNames[i],r.uint32(18).fork()).ldelim();return r},t.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},t.decode=function(e,r){e instanceof h||(e=h.create(e));for(var i=r===void 0?e.len:e.pos+r,d=new s.onnx.TensorAnnotation;e.pos<i;){var g=e.uint32();switch(g>>>3){case 1:d.tensorName=e.string();break;case 2:d.quantParameterTensorNames&&d.quantParameterTensorNames.length||(d.quantParameterTensorNames=[]),d.quantParameterTensorNames.push(s.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.tensorName!=null&&e.hasOwnProperty("tensorName")&&!u.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<e.quantParameterTensorNames.length;++r){var i=s.onnx.StringStringEntryProto.verify(e.quantParameterTensorNames[r]);if(i)return"quantParameterTensorNames."+i}}return null},t.fromObject=function(e){if(e instanceof s.onnx.TensorAnnotation)return e;var r=new s.onnx.TensorAnnotation;if(e.tensorName!=null&&(r.tensorName=String(e.tensorName)),e.quantParameterTensorNames){if(!Array.isArray(e.quantParameterTensorNames))throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: array expected");r.quantParameterTensorNames=[];for(var i=0;i<e.quantParameterTensorNames.length;++i){if(typeof e.quantParameterTensorNames[i]!="object")throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: object expected");r.quantParameterTensorNames[i]=s.onnx.StringStringEntryProto.fromObject(e.quantParameterTensorNames[i])}}return r},t.toObject=function(e,r){r||(r={});var i={};if((r.arrays||r.defaults)&&(i.quantParameterTensorNames=[]),r.defaults&&(i.tensorName=""),e.tensorName!=null&&e.hasOwnProperty("tensorName")&&(i.tensorName=e.tensorName),e.quantParameterTensorNames&&e.quantParameterTensorNames.length){i.quantParameterTensorNames=[];for(var d=0;d<e.quantParameterTensorNames.length;++d)i.quantParameterTensorNames[d]=s.onnx.StringStringEntryProto.toObject(e.quantParameterTensorNames[d],r)}return i},t.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},t}(),f.GraphProto=function(){function t(e){if(this.node=[],this.initializer=[],this.input=[],this.output=[],this.valueInfo=[],this.quantizationAnnotation=[],e)for(var r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.node=u.emptyArray,t.prototype.name="",t.prototype.initializer=u.emptyArray,t.prototype.docString="",t.prototype.input=u.emptyArray,t.prototype.output=u.emptyArray,t.prototype.valueInfo=u.emptyArray,t.prototype.quantizationAnnotation=u.emptyArray,t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=p.create()),e.node!=null&&e.node.length)for(var i=0;i<e.node.length;++i)s.onnx.NodeProto.encode(e.node[i],r.uint32(10).fork()).ldelim();if(e.name!=null&&e.hasOwnProperty("name")&&r.uint32(18).string(e.name),e.initializer!=null&&e.initializer.length)for(i=0;i<e.initializer.length;++i)s.onnx.TensorProto.encode(e.initializer[i],r.uint32(42).fork()).ldelim();if(e.docString!=null&&e.hasOwnProperty("docString")&&r.uint32(82).string(e.docString),e.input!=null&&e.input.length)for(i=0;i<e.input.length;++i)s.onnx.ValueInfoProto.encode(e.input[i],r.uint32(90).fork()).ldelim();if(e.output!=null&&e.output.length)for(i=0;i<e.output.length;++i)s.onnx.ValueInfoProto.encode(e.output[i],r.uint32(98).fork()).ldelim();if(e.valueInfo!=null&&e.valueInfo.length)for(i=0;i<e.valueInfo.length;++i)s.onnx.ValueInfoProto.encode(e.valueInfo[i],r.uint32(106).fork()).ldelim();if(e.quantizationAnnotation!=null&&e.quantizationAnnotation.length)for(i=0;i<e.quantizationAnnotation.length;++i)s.onnx.TensorAnnotation.encode(e.quantizationAnnotation[i],r.uint32(114).fork()).ldelim();return r},t.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},t.decode=function(e,r){e instanceof h||(e=h.create(e));for(var i=r===void 0?e.len:e.pos+r,d=new s.onnx.GraphProto;e.pos<i;){var g=e.uint32();switch(g>>>3){case 1:d.node&&d.node.length||(d.node=[]),d.node.push(s.onnx.NodeProto.decode(e,e.uint32()));break;case 2:d.name=e.string();break;case 5:d.initializer&&d.initializer.length||(d.initializer=[]),d.initializer.push(s.onnx.TensorProto.decode(e,e.uint32()));break;case 10:d.docString=e.string();break;case 11:d.input&&d.input.length||(d.input=[]),d.input.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 12:d.output&&d.output.length||(d.output=[]),d.output.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 13:d.valueInfo&&d.valueInfo.length||(d.valueInfo=[]),d.valueInfo.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 14:d.quantizationAnnotation&&d.quantizationAnnotation.length||(d.quantizationAnnotation=[]),d.quantizationAnnotation.push(s.onnx.TensorAnnotation.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.node!=null&&e.hasOwnProperty("node")){if(!Array.isArray(e.node))return"node: array expected";for(var r=0;r<e.node.length;++r)if(i=s.onnx.NodeProto.verify(e.node[r]))return"node."+i}if(e.name!=null&&e.hasOwnProperty("name")&&!u.isString(e.name))return"name: string expected";if(e.initializer!=null&&e.hasOwnProperty("initializer")){if(!Array.isArray(e.initializer))return"initializer: array expected";for(r=0;r<e.initializer.length;++r)if(i=s.onnx.TensorProto.verify(e.initializer[r]))return"initializer."+i}if(e.docString!=null&&e.hasOwnProperty("docString")&&!u.isString(e.docString))return"docString: string expected";if(e.input!=null&&e.hasOwnProperty("input")){if(!Array.isArray(e.input))return"input: array expected";for(r=0;r<e.input.length;++r)if(i=s.onnx.ValueInfoProto.verify(e.input[r]))return"input."+i}if(e.output!=null&&e.hasOwnProperty("output")){if(!Array.isArray(e.output))return"output: array expected";for(r=0;r<e.output.length;++r)if(i=s.onnx.ValueInfoProto.verify(e.output[r]))return"output."+i}if(e.valueInfo!=null&&e.hasOwnProperty("valueInfo")){if(!Array.isArray(e.valueInfo))return"valueInfo: array expected";for(r=0;r<e.valueInfo.length;++r)if(i=s.onnx.ValueInfoProto.verify(e.valueInfo[r]))return"valueInfo."+i}if(e.quantizationAnnotation!=null&&e.hasOwnProperty("quantizationAnnotation")){if(!Array.isArray(e.quantizationAnnotation))return"quantizationAnnotation: array expected";for(r=0;r<e.quantizationAnnotation.length;++r){var i;if(i=s.onnx.TensorAnnotation.verify(e.quantizationAnnotation[r]))return"quantizationAnnotation."+i}}return null},t.fromObject=function(e){if(e instanceof s.onnx.GraphProto)return e;var r=new s.onnx.GraphProto;if(e.node){if(!Array.isArray(e.node))throw TypeError(".onnx.GraphProto.node: array expected");r.node=[];for(var i=0;i<e.node.length;++i){if(typeof e.node[i]!="object")throw TypeError(".onnx.GraphProto.node: object expected");r.node[i]=s.onnx.NodeProto.fromObject(e.node[i])}}if(e.name!=null&&(r.name=String(e.name)),e.initializer){if(!Array.isArray(e.initializer))throw TypeError(".onnx.GraphProto.initializer: array expected");for(r.initializer=[],i=0;i<e.initializer.length;++i){if(typeof e.initializer[i]!="object")throw TypeError(".onnx.GraphProto.initializer: object expected");r.initializer[i]=s.onnx.TensorProto.fromObject(e.initializer[i])}}if(e.docString!=null&&(r.docString=String(e.docString)),e.input){if(!Array.isArray(e.input))throw TypeError(".onnx.GraphProto.input: array expected");for(r.input=[],i=0;i<e.input.length;++i){if(typeof e.input[i]!="object")throw TypeError(".onnx.GraphProto.input: object expected");r.input[i]=s.onnx.ValueInfoProto.fromObject(e.input[i])}}if(e.output){if(!Array.isArray(e.output))throw TypeError(".onnx.GraphProto.output: array expected");for(r.output=[],i=0;i<e.output.length;++i){if(typeof e.output[i]!="object")throw TypeError(".onnx.GraphProto.output: object expected");r.output[i]=s.onnx.ValueInfoProto.fromObject(e.output[i])}}if(e.valueInfo){if(!Array.isArray(e.valueInfo))throw TypeError(".onnx.GraphProto.valueInfo: array expected");for(r.valueInfo=[],i=0;i<e.valueInfo.length;++i){if(typeof e.valueInfo[i]!="object")throw TypeError(".onnx.GraphProto.valueInfo: object expected");r.valueInfo[i]=s.onnx.ValueInfoProto.fromObject(e.valueInfo[i])}}if(e.quantizationAnnotation){if(!Array.isArray(e.quantizationAnnotation))throw TypeError(".onnx.GraphProto.quantizationAnnotation: array expected");for(r.quantizationAnnotation=[],i=0;i<e.quantizationAnnotation.length;++i){if(typeof e.quantizationAnnotation[i]!="object")throw TypeError(".onnx.GraphProto.quantizationAnnotation: object expected");r.quantizationAnnotation[i]=s.onnx.TensorAnnotation.fromObject(e.quantizationAnnotation[i])}}return r},t.toObject=function(e,r){r||(r={});var i={};if((r.arrays||r.defaults)&&(i.node=[],i.initializer=[],i.input=[],i.output=[],i.valueInfo=[],i.quantizationAnnotation=[]),r.defaults&&(i.name="",i.docString=""),e.node&&e.node.length){i.node=[];for(var d=0;d<e.node.length;++d)i.node[d]=s.onnx.NodeProto.toObject(e.node[d],r)}if(e.name!=null&&e.hasOwnProperty("name")&&(i.name=e.name),e.initializer&&e.initializer.length)for(i.initializer=[],d=0;d<e.initializer.length;++d)i.initializer[d]=s.onnx.TensorProto.toObject(e.initializer[d],r);if(e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),e.input&&e.input.length)for(i.input=[],d=0;d<e.input.length;++d)i.input[d]=s.onnx.ValueInfoProto.toObject(e.input[d],r);if(e.output&&e.output.length)for(i.output=[],d=0;d<e.output.length;++d)i.output[d]=s.onnx.ValueInfoProto.toObject(e.output[d],r);if(e.valueInfo&&e.valueInfo.length)for(i.valueInfo=[],d=0;d<e.valueInfo.length;++d)i.valueInfo[d]=s.onnx.ValueInfoProto.toObject(e.valueInfo[d],r);if(e.quantizationAnnotation&&e.quantizationAnnotation.length)for(i.quantizationAnnotation=[],d=0;d<e.quantizationAnnotation.length;++d)i.quantizationAnnotation[d]=s.onnx.TensorAnnotation.toObject(e.quantizationAnnotation[d],r);return i},t.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},t}(),f.TensorProto=function(){function t(e){if(this.dims=[],this.floatData=[],this.int32Data=[],this.stringData=[],this.int64Data=[],this.externalData=[],this.doubleData=[],this.uint64Data=[],e)for(var r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.dims=u.emptyArray,t.prototype.dataType=0,t.prototype.segment=null,t.prototype.floatData=u.emptyArray,t.prototype.int32Data=u.emptyArray,t.prototype.stringData=u.emptyArray,t.prototype.int64Data=u.emptyArray,t.prototype.name="",t.prototype.docString="",t.prototype.rawData=u.newBuffer([]),t.prototype.externalData=u.emptyArray,t.prototype.dataLocation=0,t.prototype.doubleData=u.emptyArray,t.prototype.uint64Data=u.emptyArray,t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=p.create()),e.dims!=null&&e.dims.length){r.uint32(10).fork();for(var i=0;i<e.dims.length;++i)r.int64(e.dims[i]);r.ldelim()}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&r.uint32(16).int32(e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&s.onnx.TensorProto.Segment.encode(e.segment,r.uint32(26).fork()).ldelim(),e.floatData!=null&&e.floatData.length){for(r.uint32(34).fork(),i=0;i<e.floatData.length;++i)r.float(e.floatData[i]);r.ldelim()}if(e.int32Data!=null&&e.int32Data.length){for(r.uint32(42).fork(),i=0;i<e.int32Data.length;++i)r.int32(e.int32Data[i]);r.ldelim()}if(e.stringData!=null&&e.stringData.length)for(i=0;i<e.stringData.length;++i)r.uint32(50).bytes(e.stringData[i]);if(e.int64Data!=null&&e.int64Data.length){for(r.uint32(58).fork(),i=0;i<e.int64Data.length;++i)r.int64(e.int64Data[i]);r.ldelim()}if(e.name!=null&&e.hasOwnProperty("name")&&r.uint32(66).string(e.name),e.rawData!=null&&e.hasOwnProperty("rawData")&&r.uint32(74).bytes(e.rawData),e.doubleData!=null&&e.doubleData.length){for(r.uint32(82).fork(),i=0;i<e.doubleData.length;++i)r.double(e.doubleData[i]);r.ldelim()}if(e.uint64Data!=null&&e.uint64Data.length){for(r.uint32(90).fork(),i=0;i<e.uint64Data.length;++i)r.uint64(e.uint64Data[i]);r.ldelim()}if(e.docString!=null&&e.hasOwnProperty("docString")&&r.uint32(98).string(e.docString),e.externalData!=null&&e.externalData.length)for(i=0;i<e.externalData.length;++i)s.onnx.StringStringEntryProto.encode(e.externalData[i],r.uint32(106).fork()).ldelim();return e.dataLocation!=null&&e.hasOwnProperty("dataLocation")&&r.uint32(112).int32(e.dataLocation),r},t.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},t.decode=function(e,r){e instanceof h||(e=h.create(e));for(var i=r===void 0?e.len:e.pos+r,d=new s.onnx.TensorProto;e.pos<i;){var g=e.uint32();switch(g>>>3){case 1:if(d.dims&&d.dims.length||(d.dims=[]),(7&g)==2)for(var m=e.uint32()+e.pos;e.pos<m;)d.dims.push(e.int64());else d.dims.push(e.int64());break;case 2:d.dataType=e.int32();break;case 3:d.segment=s.onnx.TensorProto.Segment.decode(e,e.uint32());break;case 4:if(d.floatData&&d.floatData.length||(d.floatData=[]),(7&g)==2)for(m=e.uint32()+e.pos;e.pos<m;)d.floatData.push(e.float());else d.floatData.push(e.float());break;case 5:if(d.int32Data&&d.int32Data.length||(d.int32Data=[]),(7&g)==2)for(m=e.uint32()+e.pos;e.pos<m;)d.int32Data.push(e.int32());else d.int32Data.push(e.int32());break;case 6:d.stringData&&d.stringData.length||(d.stringData=[]),d.stringData.push(e.bytes());break;case 7:if(d.int64Data&&d.int64Data.length||(d.int64Data=[]),(7&g)==2)for(m=e.uint32()+e.pos;e.pos<m;)d.int64Data.push(e.int64());else d.int64Data.push(e.int64());break;case 8:d.name=e.string();break;case 12:d.docString=e.string();break;case 9:d.rawData=e.bytes();break;case 13:d.externalData&&d.externalData.length||(d.externalData=[]),d.externalData.push(s.onnx.StringStringEntryProto.decode(e,e.uint32()));break;case 14:d.dataLocation=e.int32();break;case 10:if(d.doubleData&&d.doubleData.length||(d.doubleData=[]),(7&g)==2)for(m=e.uint32()+e.pos;e.pos<m;)d.doubleData.push(e.double());else d.doubleData.push(e.double());break;case 11:if(d.uint64Data&&d.uint64Data.length||(d.uint64Data=[]),(7&g)==2)for(m=e.uint32()+e.pos;e.pos<m;)d.uint64Data.push(e.uint64());else d.uint64Data.push(e.uint64());break;default:e.skipType(7&g)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.dims!=null&&e.hasOwnProperty("dims")){if(!Array.isArray(e.dims))return"dims: array expected";for(var r=0;r<e.dims.length;++r)if(!(u.isInteger(e.dims[r])||e.dims[r]&&u.isInteger(e.dims[r].low)&&u.isInteger(e.dims[r].high)))return"dims: integer|Long[] expected"}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&!u.isInteger(e.dataType))return"dataType: integer expected";if(e.segment!=null&&e.hasOwnProperty("segment")&&(i=s.onnx.TensorProto.Segment.verify(e.segment)))return"segment."+i;if(e.floatData!=null&&e.hasOwnProperty("floatData")){if(!Array.isArray(e.floatData))return"floatData: array expected";for(r=0;r<e.floatData.length;++r)if(typeof e.floatData[r]!="number")return"floatData: number[] expected"}if(e.int32Data!=null&&e.hasOwnProperty("int32Data")){if(!Array.isArray(e.int32Data))return"int32Data: array expected";for(r=0;r<e.int32Data.length;++r)if(!u.isInteger(e.int32Data[r]))return"int32Data: integer[] expected"}if(e.stringData!=null&&e.hasOwnProperty("stringData")){if(!Array.isArray(e.stringData))return"stringData: array expected";for(r=0;r<e.stringData.length;++r)if(!(e.stringData[r]&&typeof e.stringData[r].length=="number"||u.isString(e.stringData[r])))return"stringData: buffer[] expected"}if(e.int64Data!=null&&e.hasOwnProperty("int64Data")){if(!Array.isArray(e.int64Data))return"int64Data: array expected";for(r=0;r<e.int64Data.length;++r)if(!(u.isInteger(e.int64Data[r])||e.int64Data[r]&&u.isInteger(e.int64Data[r].low)&&u.isInteger(e.int64Data[r].high)))return"int64Data: integer|Long[] expected"}if(e.name!=null&&e.hasOwnProperty("name")&&!u.isString(e.name))return"name: string expected";if(e.docString!=null&&e.hasOwnProperty("docString")&&!u.isString(e.docString))return"docString: string expected";if(e.rawData!=null&&e.hasOwnProperty("rawData")&&!(e.rawData&&typeof e.rawData.length=="number"||u.isString(e.rawData)))return"rawData: buffer expected";if(e.externalData!=null&&e.hasOwnProperty("externalData")){if(!Array.isArray(e.externalData))return"externalData: array expected";for(r=0;r<e.externalData.length;++r){var i;if(i=s.onnx.StringStringEntryProto.verify(e.externalData[r]))return"externalData."+i}}if(e.dataLocation!=null&&e.hasOwnProperty("dataLocation"))switch(e.dataLocation){default:return"dataLocation: enum value expected";case 0:case 1:}if(e.doubleData!=null&&e.hasOwnProperty("doubleData")){if(!Array.isArray(e.doubleData))return"doubleData: array expected";for(r=0;r<e.doubleData.length;++r)if(typeof e.doubleData[r]!="number")return"doubleData: number[] expected"}if(e.uint64Data!=null&&e.hasOwnProperty("uint64Data")){if(!Array.isArray(e.uint64Data))return"uint64Data: array expected";for(r=0;r<e.uint64Data.length;++r)if(!(u.isInteger(e.uint64Data[r])||e.uint64Data[r]&&u.isInteger(e.uint64Data[r].low)&&u.isInteger(e.uint64Data[r].high)))return"uint64Data: integer|Long[] expected"}return null},t.fromObject=function(e){if(e instanceof s.onnx.TensorProto)return e;var r=new s.onnx.TensorProto;if(e.dims){if(!Array.isArray(e.dims))throw TypeError(".onnx.TensorProto.dims: array expected");r.dims=[];for(var i=0;i<e.dims.length;++i)u.Long?(r.dims[i]=u.Long.fromValue(e.dims[i])).unsigned=!1:typeof e.dims[i]=="string"?r.dims[i]=parseInt(e.dims[i],10):typeof e.dims[i]=="number"?r.dims[i]=e.dims[i]:typeof e.dims[i]=="object"&&(r.dims[i]=new u.LongBits(e.dims[i].low>>>0,e.dims[i].high>>>0).toNumber())}if(e.dataType!=null&&(r.dataType=0|e.dataType),e.segment!=null){if(typeof e.segment!="object")throw TypeError(".onnx.TensorProto.segment: object expected");r.segment=s.onnx.TensorProto.Segment.fromObject(e.segment)}if(e.floatData){if(!Array.isArray(e.floatData))throw TypeError(".onnx.TensorProto.floatData: array expected");for(r.floatData=[],i=0;i<e.floatData.length;++i)r.floatData[i]=Number(e.floatData[i])}if(e.int32Data){if(!Array.isArray(e.int32Data))throw TypeError(".onnx.TensorProto.int32Data: array expected");for(r.int32Data=[],i=0;i<e.int32Data.length;++i)r.int32Data[i]=0|e.int32Data[i]}if(e.stringData){if(!Array.isArray(e.stringData))throw TypeError(".onnx.TensorProto.stringData: array expected");for(r.stringData=[],i=0;i<e.stringData.length;++i)typeof e.stringData[i]=="string"?u.base64.decode(e.stringData[i],r.stringData[i]=u.newBuffer(u.base64.length(e.stringData[i])),0):e.stringData[i].length&&(r.stringData[i]=e.stringData[i])}if(e.int64Data){if(!Array.isArray(e.int64Data))throw TypeError(".onnx.TensorProto.int64Data: array expected");for(r.int64Data=[],i=0;i<e.int64Data.length;++i)u.Long?(r.int64Data[i]=u.Long.fromValue(e.int64Data[i])).unsigned=!1:typeof e.int64Data[i]=="string"?r.int64Data[i]=parseInt(e.int64Data[i],10):typeof e.int64Data[i]=="number"?r.int64Data[i]=e.int64Data[i]:typeof e.int64Data[i]=="object"&&(r.int64Data[i]=new u.LongBits(e.int64Data[i].low>>>0,e.int64Data[i].high>>>0).toNumber())}if(e.name!=null&&(r.name=String(e.name)),e.docString!=null&&(r.docString=String(e.docString)),e.rawData!=null&&(typeof e.rawData=="string"?u.base64.decode(e.rawData,r.rawData=u.newBuffer(u.base64.length(e.rawData)),0):e.rawData.length&&(r.rawData=e.rawData)),e.externalData){if(!Array.isArray(e.externalData))throw TypeError(".onnx.TensorProto.externalData: array expected");for(r.externalData=[],i=0;i<e.externalData.length;++i){if(typeof e.externalData[i]!="object")throw TypeError(".onnx.TensorProto.externalData: object expected");r.externalData[i]=s.onnx.StringStringEntryProto.fromObject(e.externalData[i])}}switch(e.dataLocation){case"DEFAULT":case 0:r.dataLocation=0;break;case"EXTERNAL":case 1:r.dataLocation=1}if(e.doubleData){if(!Array.isArray(e.doubleData))throw TypeError(".onnx.TensorProto.doubleData: array 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i={};if((r.arrays||r.defaults)&&(i.dims=[],i.floatData=[],i.int32Data=[],i.stringData=[],i.int64Data=[],i.doubleData=[],i.uint64Data=[],i.externalData=[]),r.defaults&&(i.dataType=0,i.segment=null,i.name="",r.bytes===String?i.rawData="":(i.rawData=[],r.bytes!==Array&&(i.rawData=u.newBuffer(i.rawData))),i.docString="",i.dataLocation=r.enums===String?"DEFAULT":0),e.dims&&e.dims.length){i.dims=[];for(var d=0;d<e.dims.length;++d)typeof e.dims[d]=="number"?i.dims[d]=r.longs===String?String(e.dims[d]):e.dims[d]:i.dims[d]=r.longs===String?u.Long.prototype.toString.call(e.dims[d]):r.longs===Number?new u.LongBits(e.dims[d].low>>>0,e.dims[d].high>>>0).toNumber():e.dims[d]}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&(i.dataType=e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&(i.segment=s.onnx.TensorProto.Segment.toObject(e.segment,r)),e.floatData&&e.floatData.length)for(i.floatData=[],d=0;d<e.floatData.length;++d)i.floatData[d]=r.json&&!isFinite(e.floatData[d])?String(e.floatData[d]):e.floatData[d];if(e.int32Data&&e.int32Data.length)for(i.int32Data=[],d=0;d<e.int32Data.length;++d)i.int32Data[d]=e.int32Data[d];if(e.stringData&&e.stringData.length)for(i.stringData=[],d=0;d<e.stringData.length;++d)i.stringData[d]=r.bytes===String?u.base64.encode(e.stringData[d],0,e.stringData[d].length):r.bytes===Array?Array.prototype.slice.call(e.stringData[d]):e.stringData[d];if(e.int64Data&&e.int64Data.length)for(i.int64Data=[],d=0;d<e.int64Data.length;++d)typeof e.int64Data[d]=="number"?i.int64Data[d]=r.longs===String?String(e.int64Data[d]):e.int64Data[d]:i.int64Data[d]=r.longs===String?u.Long.prototype.toString.call(e.int64Data[d]):r.longs===Number?new u.LongBits(e.int64Data[d].low>>>0,e.int64Data[d].high>>>0).toNumber():e.int64Data[d];if(e.name!=null&&e.hasOwnProperty("name")&&(i.name=e.name),e.rawData!=null&&e.hasOwnProperty("rawData")&&(i.rawData=r.bytes===String?u.base64.encode(e.rawData,0,e.rawData.length):r.bytes===Array?Array.prototype.slice.call(e.rawData):e.rawData),e.doubleData&&e.doubleData.length)for(i.doubleData=[],d=0;d<e.doubleData.length;++d)i.doubleData[d]=r.json&&!isFinite(e.doubleData[d])?String(e.doubleData[d]):e.doubleData[d];if(e.uint64Data&&e.uint64Data.length)for(i.uint64Data=[],d=0;d<e.uint64Data.length;++d)typeof e.uint64Data[d]=="number"?i.uint64Data[d]=r.longs===String?String(e.uint64Data[d]):e.uint64Data[d]:i.uint64Data[d]=r.longs===String?u.Long.prototype.toString.call(e.uint64Data[d]):r.longs===Number?new u.LongBits(e.uint64Data[d].low>>>0,e.uint64Data[d].high>>>0).toNumber(!0):e.uint64Data[d];if(e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),e.externalData&&e.externalData.length)for(i.externalData=[],d=0;d<e.externalData.length;++d)i.externalData[d]=s.onnx.StringStringEntryProto.toObject(e.externalData[d],r);return e.dataLocation!=null&&e.hasOwnProperty("dataLocation")&&(i.dataLocation=r.enums===String?s.onnx.TensorProto.DataLocation[e.dataLocation]:e.dataLocation),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},t.DataType=function(){var e={},r=Object.create(e);return r[e[0]="UNDEFINED"]=0,r[e[1]="FLOAT"]=1,r[e[2]="UINT8"]=2,r[e[3]="INT8"]=3,r[e[4]="UINT16"]=4,r[e[5]="INT16"]=5,r[e[6]="INT32"]=6,r[e[7]="INT64"]=7,r[e[8]="STRING"]=8,r[e[9]="BOOL"]=9,r[e[10]="FLOAT16"]=10,r[e[11]="DOUBLE"]=11,r[e[12]="UINT32"]=12,r[e[13]="UINT64"]=13,r[e[14]="COMPLEX64"]=14,r[e[15]="COMPLEX128"]=15,r[e[16]="BFLOAT16"]=16,r}(),t.Segment=function(){function e(r){if(r)for(var i=Object.keys(r),d=0;d<i.length;++d)r[i[d]]!=null&&(this[i[d]]=r[i[d]])}return e.prototype.begin=u.Long?u.Long.fromBits(0,0,!1):0,e.prototype.end=u.Long?u.Long.fromBits(0,0,!1):0,e.create=function(r){return new e(r)},e.encode=function(r,i){return i||(i=p.create()),r.begin!=null&&r.hasOwnProperty("begin")&&i.uint32(8).int64(r.begin),r.end!=null&&r.hasOwnProperty("end")&&i.uint32(16).int64(r.end),i},e.encodeDelimited=function(r,i){return this.encode(r,i).ldelim()},e.decode=function(r,i){r instanceof h||(r=h.create(r));for(var d=i===void 0?r.len:r.pos+i,g=new s.onnx.TensorProto.Segment;r.pos<d;){var m=r.uint32();switch(m>>>3){case 1:g.begin=r.int64();break;case 2:g.end=r.int64();break;default:r.skipType(7&m)}}return g},e.decodeDelimited=function(r){return r instanceof h||(r=new h(r)),this.decode(r,r.uint32())},e.verify=function(r){return typeof r!="object"||r===null?"object expected":r.begin!=null&&r.hasOwnProperty("begin")&&!(u.isInteger(r.begin)||r.begin&&u.isInteger(r.begin.low)&&u.isInteger(r.begin.high))?"begin: integer|Long expected":r.end!=null&&r.hasOwnProperty("end")&&!(u.isInteger(r.end)||r.end&&u.isInteger(r.end.low)&&u.isInteger(r.end.high))?"end: integer|Long expected":null},e.fromObject=function(r){if(r instanceof s.onnx.TensorProto.Segment)return r;var i=new s.onnx.TensorProto.Segment;return r.begin!=null&&(u.Long?(i.begin=u.Long.fromValue(r.begin)).unsigned=!1:typeof r.begin=="string"?i.begin=parseInt(r.begin,10):typeof r.begin=="number"?i.begin=r.begin:typeof r.begin=="object"&&(i.begin=new 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        return offset;
      }
      `)}}getOutputSamplingSnippet(){const s=this.context.outputTextureLayout;return s.isPacked?this.getPackedOutputSamplingSnippet(s):this.getUnpackedOutputSamplingSnippet(s)}getPackedOutputSamplingSnippet(s){const t=s.unpackedShape,e=[s.width,s.height],r={},i="getOutputCoords";switch(t.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputPacked1DCoords(t,e);break;case 2:r[i]=this.getOutputPacked2DCoords(t,e);break;case 3:r[i]=this.getOutputPacked3DCoords(t,e);break;default:r[i]=this.getOutputPackedNDCoords(t,e)}const d=`
      void setOutput(vec4 val) {
        ${(0,f.getGlsl)(this.context.glContext.version).output} = val;
      }
    `;return r.floatTextureSetRGBA=new c.GlslLibRoutine(d),r}getUnpackedOutputSamplingSnippet(s){const t=s.unpackedShape,e=[s.width,s.height],r={},i="getOutputCoords";switch(t.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputUnpacked1DCoords(t,e);break;case 2:r[i]=this.getOutputUnpacked2DCoords(t,e);break;case 3:r[i]=this.getOutputUnpacked3DCoords(t,e);break;case 4:r[i]=this.getOutputUnpacked4DCoords(t,e);break;case 5:r[i]=this.getOutputUnpacked5DCoords(t,e);break;case 6:r[i]=this.getOutputUnpacked6DCoords(t,e);break;default:throw new Error(`Unsupported output dimensionality: ${t.length}`)}const d=`
        void setOutput(float val) {
          ${(0,f.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0);
        }
    `;return r.floatTextureSetR=new c.GlslLibRoutine(d),r}getOutputScalarCoords(){return new c.GlslLibRoutine(`
      int getOutputCoords() {
        return 0;
      }
    `)}getOutputPacked1DCoords(s,t){const e=t;let r="";return e[0]===1?(r=`
          int getOutputCoords() {
            return 2 * int(TexCoords.y * ${e[1]}.0);
          }
        `,new c.GlslLibRoutine(r)):e[1]===1?(r=`
          int getOutputCoords() {
            return 2 * int(TexCoords.x * ${e[0]}.0);
          }
        `,new c.GlslLibRoutine(r)):(r=`
        int getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                 vec2(${e[0]}, ${e[1]}));
          return 2 * (resTexRC.y * ${e[0]} + resTexRC.x);
        }
      `,new c.GlslLibRoutine(r))}getOutputPacked2DCoords(s,t){let e="";if(l.ArrayUtil.arraysEqual(s,t))return e=`
        ivec2 getOutputCoords() {
          return 2 * ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]}));
        }
      `,new c.GlslLibRoutine(e);const r=t,i=Math.ceil(s[1]/2);return e=`
        ivec2 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${r[0]}, ${r[1]}));

          int index = resTexRC.y * ${r[0]} + resTexRC.x;

          // reverse r and c order for packed texture
          int r = imod(index, ${i}) * 2;
          int c = 2 * (index / ${i});

          return ivec2(r, c);
        }
      `,new c.GlslLibRoutine(e)}getOutputPacked3DCoords(s,t){const e=[t[0],t[1]],r=Math.ceil(s[2]/2),i=r*Math.ceil(s[1]/2),d=`
        ivec3 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${e[0]}, ${e[1]}));
          int index = resTexRC.y * ${e[0]} + resTexRC.x;

          int b = index / ${i};
          index -= b * ${i};

          // reverse r and c order for packed texture
          int r = imod(index, ${r}) * 2;
          int c = 2 * (index / ${r});

          return ivec3(b, r, c);
        }
      `;return new c.GlslLibRoutine(d)}getOutputPackedNDCoords(s,t){const e=[t[0],t[1]],r=Math.ceil(s[s.length-1]/2),i=r*Math.ceil(s[s.length-2]/2);let d=i,g="",m="b, r, c";for(let _=2;_<s.length-1;_++)d*=s[s.length-_-1],g=`
      int b${_} = index / ${d};
      index -= b${_} * ${d};
    `+g,m=`b${_}, `+m;const b=`
      ivec${s.length} getOutputCoords() {
        ivec2 resTexRC = ivec2(TexCoords.xy *
                              vec2(${e[0]}, ${e[1]}));
        int index = resTexRC.y * ${e[0]} + resTexRC.x;

        ${g}

        int b = index / ${i};
        index -= b * ${i};

        // reverse r and c order for packed texture
        int r = imod(index, ${r}) * 2;
        int c = 2 * (index / ${r});

        return ivec${s.length}(${m});
      }
    `;return new c.GlslLibRoutine(b)}getOutputUnpacked1DCoords(s,t){const e=`
        int getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          return resTexRC.y * ${t[0]} + resTexRC.x;
        }
      `;return new c.GlslLibRoutine(e)}getOutputUnpacked2DCoords(s,t){const e=`
        ivec2 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          int index = resTexRC.y * ${t[0]} + resTexRC.x;
          int r = index / ${s[1]};
          int c = index - r * ${s[1]};
          return ivec2(r, c);
        }
      `;return new c.GlslLibRoutine(e)}getOutputUnpacked3DCoords(s,t){let e="";const r=s.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=s[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*s[m+1];const d=["r","c","d"],g=i.map((m,b)=>`int ${d[b]} = index / ${m}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${m}`:`index -= ${d[b]} * ${m}`};`).join("");return e=`
        ivec3 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          int index = resTexRC.y * ${t[0]} + resTexRC.x;
          ${g}
          return ivec3(r, c, d);
        }
      `,new c.GlslLibRoutine(e)}getOutputUnpacked4DCoords(s,t){let e="";const r=s.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=s[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*s[m+1];const d=["r","c","d","d2"],g=i.map((m,b)=>`int ${d[b]} = index / ${m}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${m}`:`index -= ${d[b]} * ${m}`};`).join("");return e=`
      ivec4 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          int index = resTexRC.y * ${t[0]} + resTexRC.x;
          ${g}
          return ivec4(r, c, d, d2);
        }
      `,new c.GlslLibRoutine(e)}getOutputUnpacked5DCoords(s,t){let e="";const r=s.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=s[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*s[m+1];const d=["r","c","d","d2","d3"],g=i.map((m,b)=>`int ${d[b]} = index / ${m}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${m}`:`index -= ${d[b]} * ${m}`};`).join("");return e=`
      ivec5 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          int index = resTexRC.y * ${t[0]} + resTexRC.x;
          ${g}
          return ivec5(r, c, d, d2, d3);
        }
      `,new c.GlslLibRoutine(e)}getOutputUnpacked6DCoords(s,t){let e="";const r=s.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=s[r-1];for(let m=r-3;m>=0;--m)i[m]=i[m+1]*s[m+1];const d=["r","c","d","d2","d3","d4"],g=i.map((m,b)=>`int ${d[b]} = index / ${m}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${m}`:`index -= ${d[b]} * ${m}`};`).join("");return e=`
     ivec6 getOutputCoords() {
         ivec2 resTexRC = ivec2(TexCoords.xy *
                               vec2(${t[0]}, ${t[1]}));
         int index = resTexRC.y * ${t[0]} + resTexRC.x;
         ${g}
         return ivec6(r, c, d, d2, d3, d4);
       }
     `,new c.GlslLibRoutine(e)}getCommonUtilFuncs(){const s={};let t="uvFromFlat";s[t]=new c.GlslLibRoutine(`
    vec2 uvFromFlat(int texNumR, int texNumC, int index) {
      int texC = index / texNumR;
      int texR = index - texC * texNumR;
      // TODO: swap texR, texC order in following function so row is corresponding to u and column is corresponding to
      //       v.
      return (vec2(texR, texC) + halfCR) / vec2(texNumR, texNumC);
    }
    `),t="packedUVfrom1D",s[t]=new c.GlslLibRoutine(`
      vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
        int texelIndex = index / 2;
        int texR = texelIndex / texNumC;
        int texC = texelIndex - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),t="packedUVfrom2D",s[t]=new c.GlslLibRoutine(`
      vec2 packedUVfrom2D(int texNumR, int texNumC, int texelsInLogicalRow, int row, int col) {
        int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
        int texR = texelIndex / texNumC;
        int texC = texelIndex - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),t="packedUVfrom3D",s[t]=new c.GlslLibRoutine(`
      vec2 packedUVfrom3D(int texNumR, int texNumC,
          int texelsInBatch, int texelsInLogicalRow, int b,
          int row, int col) {
        int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
        int texR = index / texNumC;
        int texC = index - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),t="sampleTexture";const e=(0,f.getGlsl)(this.context.glContext.version);return s[t]=new c.GlslLibRoutine(`
        float sampleTexture(sampler2D textureSampler, vec2 uv) {
            return ${e.texture2D}(textureSampler, uv).r;
        }`),s}getInputsSamplingSnippets(){const s={},t=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,r)=>{const i=this.context.inputTextureLayouts[r],d=(0,h.generateShaderFuncNameFromInputSamplerName)(e);i.isPacked?s[d]=this.getPackedSamplerFromInput(d,e,i):s[d]=this.getUnpackedSamplerFromInput(d,e,i);const g=(0,h.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(e);i.unpackedShape.length<=t.unpackedShape.length&&(i.isPacked?s[g]=this.getPackedSamplerAtOutputCoords(g,i,t,e):s[g]=this.getUnpackedSamplerAtOutputCoords(g,i,t,e))}),s}getPackedSamplerAtOutputCoords(s,t,e,r){const i=t.unpackedShape,d=e.unpackedShape,g=r,m=(0,h.generateShaderFuncNameFromInputSamplerName)(g),b=i.length,_=d.length,v=l.BroadcastUtil.getBroadcastDims(i,d),w=(0,h.getCoordsDataType)(_),S=_-b;let A;const O=(0,h.getGlChannels)();A=b===0?"":_<2&&v.length>=1?"coords = 0;":v.map(N=>`coords.${O[N+S]} = 0;`).join(`
`);let x="";x=_<2&&b>0?"coords":i.map((N,H)=>`coords.${O[H+S]}`).join(", ");let I="return outputValue;";const $=l.ShapeUtil.size(i)===1,B=l.ShapeUtil.size(d)===1;if(b!==1||$||B){if($&&!B)I=_===1?`
          return vec4(outputValue.x, outputValue.x, 0., 0.);
        `:`
          return vec4(outputValue.x);
        `;else if(v.length){const N=b-2,H=b-1;v.indexOf(N)>-1&&v.indexOf(H)>-1?I="return vec4(outputValue.x);":v.indexOf(N)>-1?I="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":v.indexOf(H)>-1&&(I="return vec4(outputValue.xx, outputValue.zz);")}}else I=`
        return vec4(outputValue.xy, outputValue.xy);
      `;const L=`
      vec4 ${s}() {
        ${w} coords = getOutputCoords();
        
        int lastDim = coords.${O[_-1]};
        coords.${O[_-1]} = coords.${O[_-2]};
        coords.${O[_-2]} = lastDim;
      
        ${A}
        vec4 outputValue = ${m}(${x});
        ${I}
      }
    `;return new c.GlslLibRoutine(L,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(s,t,e,r){const i=[e.width,e.height],d=[t.width,t.height],g=t.unpackedShape.length,m=e.unpackedShape.length,b=t.unpackedShape,_=e.unpackedShape,v=(0,h.generateShaderFuncNameFromInputSamplerName)(r);if(g===m&&l.ArrayUtil.arraysEqual(d,i)){const B=`
          float ${s}() {
            return sampleTexture(${r}, TexCoords);
          }
        `;return new c.GlslLibRoutine(B,["coordinates.sampleTexture"])}const w=(0,h.getCoordsDataType)(m),S=l.BroadcastUtil.getBroadcastDims(b,_),A=m-g;let O;const x=(0,h.getGlChannels)();O=g===0?"":m<2&&S.length>=1?"coords = 0;":S.map(B=>`coords.${x[B+A]} = 0;`).join(`
`);let I="";I=m<2&&g>0?"coords":t.unpackedShape.map((B,L)=>`coords.${x[L+A]}`).join(", ");const $=`
        float ${s}() {
          ${w} coords = getOutputCoords();
          ${O}
          return ${v}(${I});
        }
      `;return new c.GlslLibRoutine($,["coordinates.getOutputCoords"])}getPackedSamplerFromInput(s,t,e){switch(e.unpackedShape.length){case 0:return this.getPackedSamplerScalar(s,t);case 1:return this.getPackedSampler1D(s,t,e);case 2:return this.getPackedSampler2D(s,t,e);case 3:return this.getPackedSampler3D(s,t,e);default:return this.getPackedSamplerND(s,t,e)}}getUnpackedSamplerFromInput(s,t,e){const r=e.unpackedShape;switch(r.length){case 0:return this.getUnpackedSamplerScalar(s,t,e);case 1:return this.getUnpackedSampler1D(s,t,e);case 2:return this.getUnpackedSampler2D(s,t,e);case 3:return this.getUnpackedSampler3D(s,t,e);case 4:return this.getUnpackedSampler4D(s,t,e);case 5:return this.getUnpackedSampler5D(s,t,e);case 6:return this.getUnpackedSampler6D(s,t,e);default:throw new Error(`Unsupported dimension ${r.length}-D`)}}getPackedSamplerScalar(s,t){const e=`
          vec4 ${s}() {
            return ${(0,f.getGlsl)(this.context.glContext.version).texture2D}(${t}, halfCR);
          }
        `;return new c.GlslLibRoutine(e)}getPackedSampler1D(s,t,e){const r=[e.width,e.height],i=[r[1],r[0]],d=(0,f.getGlsl)(this.context.glContext.version),g=`vec4 ${s}(int index) {
      vec2 uv = packedUVfrom1D(
      ${i[0]}, ${i[1]}, index);
      return ${d.texture2D}(${t}, uv);
    }`;return new c.GlslLibRoutine(g,["coordinates.packedUVfrom1D"])}getPackedSampler2D(s,t,e){const r=e.unpackedShape,i=[e.width,e.height],d=(0,f.getGlsl)(this.context.glContext.version),g=i[0],m=i[1];if(i!=null&&l.ArrayUtil.arraysEqual(r,i)){const w=`vec4 ${s}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${m}.0, ${g}.0);
        return ${d.texture2D}(${t}, uv);
      }`;return new c.GlslLibRoutine(w)}const b=i,_=Math.ceil(r[1]/2),v=`vec4 ${s}(int row, int col) {
      vec2 uv = packedUVfrom2D(${b[1]}, ${b[0]}, ${_}, row, col);
      return ${d.texture2D}(${t}, uv);
    }`;return new c.GlslLibRoutine(v,["coordinates.packedUVfrom2D"])}getPackedSampler3D(s,t,e){const r=e.unpackedShape,i=[e.width,e.height],d=[i[0],i[1]],g=(0,f.getGlsl)(this.context.glContext.version);if(r[0]===1){const w=r.slice(1),S=[1,2],A=(0,h.squeezeInputShape)(r,w),O=["b","row","col"],x=JSON.parse(JSON.stringify(e));x.unpackedShape=A;const I=this.getPackedSamplerFromInput(s,t,x),$=`${I.routineBody}
      vec4 ${s}(int b, int row, int col) {
        return ${s}(${(0,h.getSqueezedParams)(O,S)});
      } `;return new c.GlslLibRoutine($,I.dependencies)}const m=d[0],b=d[1],_=Math.ceil(r[2]/2),v=`vec4 ${s}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${b}, ${m}, ${_*Math.ceil(r[1]/2)}, ${_}, b, row, col);
      return ${g.texture2D}(${t}, uv);}`;return new c.GlslLibRoutine(v,["coordinates.packedUVfrom3D"])}getPackedSamplerND(s,t,e){const r=e.unpackedShape,i=r.length,d=[e.width,e.height],g=(0,f.getGlsl)(this.context.glContext.version),m=[d[0],d[1]],b=m[1],_=m[0],v=Math.ceil(r[i-1]/2);let w=v*Math.ceil(r[i-2]/2),S="int b, int row, int col",A=`b * ${w} + (row / 2) * ${v} + (col / 2)`;for(let x=2;x<i-1;x++)S=`int b${x}, `+S,w*=r[i-x-1],A=`b${x} * ${w} + `+A;const O=`vec4 ${s}(${S}) {
      int index = ${A};
      int texR = index / ${_};
      int texC = index - texR * ${_};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${_}, ${b});
      return ${g.texture2D}(${t}, uv);
    }`;return new c.GlslLibRoutine(O)}getUnpackedSamplerScalar(s,t,e){const[r,i]=[e.width,e.height];if(r===1&&i===1){const g=`
          float ${s}() {
            return sampleTexture(${t}, halfCR);
          }
        `;return new c.GlslLibRoutine(g,["coordinates.sampleTexture"])}const d=`
        float ${s}() {
          int offset_${t} = coordsToOffset(TexCoords, ${r}, ${i});
          vec2 uv = uvFromFlat(${r}, ${i}, offset_${t});
          return sampleTexture(${t}, uv);
        }
      `;return new c.GlslLibRoutine(d,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler1D(s,t,e){const r=e.width,i=e.height;if(i===1&&r===1){const g=`
        float ${s}(int index) {
          return sampleTexture(${t}, halfCR);
        }
      `;return new c.GlslLibRoutine(g,["coordinates.sampleTexture"])}if(i===1){const g=`
          float ${s}(int index) {
            vec2 uv = vec2((float(index) + 0.5) / ${r}.0, 0.5);
            return sampleTexture(${t}, uv);
          }
        `;return new c.GlslLibRoutine(g,["coordinates.sampleTexture"])}if(r===1){const g=`
          float ${s}(int index) {
            vec2 uv = vec2(0.5, (float(index) + 0.5) / ${i}.0);
            return sampleTexture(${t}, uv);
          }
        `;return new c.GlslLibRoutine(g,["coordinates.sampleTexture"])}const d=`
        float ${s}(int index) {
          vec2 uv = uvFromFlat(${r}, ${i}, index);
          return sampleTexture(${t}, uv);
        }
      `;return new c.GlslLibRoutine(d,["coordinates.uvFromFlat","coordinates.sampleTexture"])}getUnpackedSampler2D(s,t,e){const r=e.unpackedShape,i=[e.height,e.width];if(i!=null&&l.ArrayUtil.arraysEqual(r,i)){const w=`
          float ${s}(int row, int col) {
            vec2 uv = (vec2(row, col) + halfCR) / vec2(${i[1]}.0, ${i[0]}.0);
            return sampleTexture(${t}, uv);
          }
        `;return new c.GlslLibRoutine(w,["coordinates.sampleTexture"])}const{newShape:d,keptDims:g}=(0,a.squeezeShape)(r),m=d;if(m.length<r.length){const w=(0,h.squeezeInputShape)(r,m),S=JSON.parse(JSON.stringify(e));S.unpackedShape=w;const A=["col","row"],O=`
          ${this.getUnpackedSamplerFromInput(s,t,S).routineBody}
          float ${s}(int row, int col) {
            return ${s}(${(0,h.getSqueezedParams)(A,g)});
          }
        `;return new c.GlslLibRoutine(O,["coordinates.sampleTexture"])}const b=i[1],_=i[0];if(_===1){const w=`
          float ${s}(int row, int col) {
            int offset_${t} = coordsToOffset(TexCoords, ${b}, ${_});
            float index = dot(vec3(row, col, offset_${t}), vec3(${r[1]}, 1, 1));
            vec2 uv = vec2(0.5, (index + 0.5) / ${b}.0);
            return sampleTexture(${t}, uv);
          }
        `;return new c.GlslLibRoutine(w,["coordinates.sampleTexture","coordinates.coordsToOffset"])}if(b===1){const w=`
          float ${s}(int row, int col) {
            int offset_${t} = coordsToOffset(TexCoords, ${b}, ${_});
            float index = dot(vec3(row, col, offset_${t}), vec3(${r[1]}, 1, 1));
            vec2 uv = vec2((index + 0.5) / ${_}.0, 0.5);
            return sampleTexture(${t}, uv);
          }
        `;return new c.GlslLibRoutine(w,["coordinates.sampleTexture","coordinates.coordsToOffset"])}const v=`
        float ${s}(int row, int col) {
          int index = col * ${r[1]} + row;
          vec2 uv = uvFromFlat(${b}, ${_}, index);
          return sampleTexture(${t}, uv);
        }
      `;return new c.GlslLibRoutine(v,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler3D(s,t,e){const r=e.unpackedShape,i=r[1]*r[2],d=r[2],{newShape:g,keptDims:m}=(0,a.squeezeShape)(r),b=g;if(b.length<r.length){const v=(0,h.squeezeInputShape)(r,b),w=["batch","col","row"],S=JSON.parse(JSON.stringify(e));S.unpackedShape=v;const A=this.getUnpackedSamplerFromInput(s,t,S),O=m.reverse(),x=`
          ${A.routineBody}
          float ${s}(int batch, int row, int col) {
            return ${s}(${(0,h.getSqueezedParams)(w,O)});
          }
        `;return new c.GlslLibRoutine(x,A.dependencies)}const _=`
          float ${s}(int depth, int row, int col) {
            // Explicitly use integer operations as dot() only works on floats.
            int index = depth * ${i} + col * ${d} + row;
            vec2 uv = uvFromFlat(${e.width}, ${e.height}, index);
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        c[${t-1}] = offset;`);const g=`
      void toVec(vec2 texCoords, out int c[${t}]) {
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      void toVec(int offset, out int c[${t}]) {
        ${d.join("")}
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          int offset = indicesToOffset${d}(m);
          vec2 coords = offsetToCoords(offset, ${e}, ${r});
          float value = getColorAsFloat(${(0,f.getGlsl)(this.context.glContext.version).texture2D}(${s}, coords));
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        }
        `}getPackedValueFrom(s,t,e,r,i){let d=`_${s}_Pack`;return i&&(d+="_T"),`
        vec4 ${d}(int m[${t}]) {
          int offset = indicesToOffset_${s}(m);
          vec2 coords = offsetToCoords(offset, ${e}, ${r});
          return ${(0,f.getGlsl)(this.context.glContext.version).texture2D}(${s}, coords);
        }
        `}}n.CoordsGlslLib=p},8520:(y,n)=>{var o;Object.defineProperty(n,"__esModule",{value:!0}),n.TopologicalSortGlslRoutines=n.GlslLibRoutineNode=n.GlslLibRoutine=n.GlslLib=n.GlslContext=n.FunctionType=void 0,(o=n.FunctionType||(n.FunctionType={}))[o.ValueBased=0]="ValueBased",o[o.Positional=1]="Positional",n.GlslContext=class{constructor(l,c,f,a){this.glContext=l,this.programInfo=c,this.inputTextureLayouts=f,this.outputTextureLayout=a}},n.GlslLib=class{constructor(l){this.context=l}},n.GlslLibRoutine=class{constructor(l,c){this.routineBody=l,this.dependencies=c}},n.GlslLibRoutineNode=class{constructor(l,c,f){this.name=l,this.dependencies=f||[],c&&(this.routineBody=c)}addDependency(l){l&&this.dependencies.push(l)}},n.TopologicalSortGlslRoutines=class{static returnOrderedNodes(l){if(!l||l.length===0)return[];if(l.length===1)return l;const c=new Set,f=new Set,a=new Array;return this.createOrderedNodes(l,c,f,a),a}static createOrderedNodes(l,c,f,a){for(let h=0;h<l.length;++h)this.dfsTraverse(l[h],c,f,a)}static dfsTraverse(l,c,f,a){if(!l||f.has(l.name))return;if(c.has(l.name))throw new Error("Cyclic dependency detected. Can't topologically sort routines needed for shader.");c.add(l.name);const h=l.dependencies;if(h&&h.length>0)for(let p=0;p<h.length;++p)this.dfsTraverse(h[p],c,f,a);a.push(l),f.add(l.name),c.delete(l.name)}}},7341:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.EncodingGlslLib=void 0;const l=o(8520);class c extends l.GlslLib{constructor(a){super(a)}getFunctions(){return Object.assign(Object.assign({},this.encodeFloat32()),this.decodeFloat32())}getCustomTypes(){return{}}encodeFloat32(){return{encode:new l.GlslLibRoutine(`highp vec4 encode(highp float f) {
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        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}
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        return rgba;
    }
        `)}}decodeUint8(){const a=c.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{decode:new l.GlslLibRoutine(`
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          ${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),p=new Uint8Array(a);if(h[0]=3735928559,p[0]===239)return!0;if(p[0]===222)return!1;throw new Error("unknown endianness")}}n.EncodingGlslLib=c},9894:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.FragColorGlslLib=void 0;const l=o(8520),c=o(5060);class f extends l.GlslLib{constructor(h){super(h)}getFunctions(){return Object.assign(Object.assign({},this.setFragColor()),this.getColorAsFloat())}getCustomTypes(){return{}}setFragColor(){const h=(0,c.getGlsl)(this.context.glContext.version);return{setFragColor:new l.GlslLibRoutine(`
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      ${e}
      {
        ${r}
      }
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    ${this.getUniforms(h.inputNames,h.variables)}
    ${this.getImports(p)}
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`}return u}selectGlslLibRoutinesToBeIncluded(h){const p=[];return Object.keys(this.glslLibRoutineDependencyGraph).forEach(u=>{const s=u.split(".")[1];h.indexOf(s)!==-1&&p.push(this.glslLibRoutineDependencyGraph[u])}),l.TopologicalSortGlslRoutines.returnOrderedNodes(p)}getUniforms(h,p){const u=[];if(h)for(const s of h)u.push(`uniform sampler2D ${s};`);if(p)for(const s of p)u.push(`uniform ${s.type} ${s.name}${s.arrayLength?`[${s.arrayLength}]`:""};`);return u.join(`
`)}}},5483:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.glslRegistry=void 0;const l=o(5107),c=o(7341),f=o(9894),a=o(2655),h=o(3891);n.glslRegistry={encoding:c.EncodingGlslLib,fragcolor:f.FragColorGlslLib,vec:h.VecGlslLib,shapeUtils:a.ShapeUtilsGlslLib,coordinates:l.CoordsGlslLib}},2655:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.ShapeUtilsGlslLib=void 0;const l=o(8520);class c extends l.GlslLib{constructor(a){super(a)}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.bcastIndex()),this.bcastMatmulIndex()),this.offsetToIndices()),this.indicesToOffset()),this.incrementIndices())}getCustomTypes(){return{}}bcastIndex(){const a=this.context.outputTextureLayout.shape.length,h={};return this.context.programInfo.inputNames.forEach((p,u)=>{const s=this.context.inputTextureLayouts[u].unpackedShape;if(s.length<=a){const t=s.length,e=a-t,r=`bcastIndices_${p}`;let i="";for(let g=0;g<t;++g)i+=`
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        void ${r} (int bcastedIndices[${a}], out int realIndices[${t}]) {
          ${i}
        }
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          `;const d=`
        void ${r}(int bcastedIndices[${a}], out int realIndices[${t}]) {
          ${i}
          realIndices[${t-1}] = bcastedIndices[${a-1}];
          realIndices[${t-2}] = bcastedIndices[${a-2}];
        }
        `;h[r]=new l.GlslLibRoutine(d)}}),h}indicesToOffset(){const a={};return this.context.programInfo.inputNames.forEach((h,p)=>{const u=this.context.inputTextureLayouts[p].shape,s=this.context.inputTextureLayouts[p].strides,t=u.length;let e=`indicesToOffset_${h}`;a[e]=new l.GlslLibRoutine(c.indexToOffsetSingle(e,t,s)),e=`indicesToOffset_${h}_T`,a[e]=new l.GlslLibRoutine(c.indexToOffsetSingle(e,t,s.slice().reverse()))}),a}static indexToOffsetSingle(a,h,p){let u="";for(let s=h-1;s>=0;--s)u+=`
        offset += indices[${s}] * ${p[s]};
        `;return`
      int ${a}(int indices[${h}]) {
        int offset = 0;
        ${u}
        return offset;
      }
      `}offsetToIndices(){const a={};return this.context.programInfo.inputNames.forEach((h,p)=>{const u=this.context.inputTextureLayouts[p].shape,s=this.context.inputTextureLayouts[p].strides,t=u.length;let e=`offsetToIndices_${h}`;a[e]=new l.GlslLibRoutine(c.offsetToIndicesSingle(e,t,s)),e=`offsetToIndices_${h}_T`,a[e]=new l.GlslLibRoutine(c.offsetToIndicesSingle(e,t,s.slice().reverse()))}),a}static offsetToIndicesSingle(a,h,p){const u=[];for(let s=0;s<h-1;++s)u.push(`
      indices[${s}] = offset / ${p[s]};`),u.push(`
        offset -= indices[${s}] * ${p[s]};`);return u.push(`
      indices[${h-1}] = offset;`),`
      void ${a}(int offset, out int indices[${h}]) {
        ${u.join("")}
      }
      `}incrementIndices(){const a={};return this.context.programInfo.inputNames.forEach((h,p)=>{const u=this.context.inputTextureLayouts[p].shape,s=u.length,t=`incrementIndices_${h}`;let e="";for(let i=0;i<s;++i)e+=`
        shape[${i}] = ${u[i]};`;const r=`
        void ${t}(int axis, out int indices[${s}]) {
          int shape[${s}];
          ${e};
          for(int i = ${s} -1 ; i >= 0; --i) {
            if(i > axis) continue;
            indices[i] += 1;
            if(indices[i] < shape[i]) {
              break;
            }
            indices[i] = 0;
          }
        }
        `;a[t]=new l.GlslLibRoutine(r)}),a}}n.ShapeUtilsGlslLib=c},5060:(y,n)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.getDefaultFragShaderMain=n.getFragShaderPreamble=n.getVertexShaderSource=n.getGlsl=void 0;const o={version:"",attribute:"attribute",varyingVertex:"varying",varyingFrag:"varying",texture2D:"texture2D",output:"gl_FragColor",outputDeclaration:""},l={version:"#version 300 es",attribute:"in",varyingVertex:"out",varyingFrag:"in",texture2D:"texture",output:"outputColor",outputDeclaration:"out vec4 outputColor;"};function c(f){return f===1?o:l}n.getGlsl=c,n.getVertexShaderSource=function(f){const a=c(f);return`${a.version}
      precision highp float;
      ${a.attribute} vec3 position;
      ${a.attribute} vec2 textureCoord;

      ${a.varyingVertex} vec2 TexCoords;

      void main()
      {
          gl_Position = vec4(position, 1.0);
          TexCoords = textureCoord;
      }`},n.getFragShaderPreamble=function(f){const a=c(f);return`${a.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${a.varyingFrag} vec2 TexCoords;
    ${a.outputDeclaration}
    const vec2 halfCR = vec2(0.5, 0.5);

    // Custom vector types to handle higher dimenalities.
    struct ivec5
    {
      int x;
      int y;
      int z;
      int w;
      int u;
    };

    struct ivec6
    {
      int x;
      int y;
      int z;
      int w;
      int u;
      int v;
    };

    int imod(int x, int y) {
      return x - y * (x / y);
    }

    `},n.getDefaultFragShaderMain=function(f,a){return`
  void main() {
    int indices[${a}];
    toVec(TexCoords, indices);
    vec4 result = vec4(process(indices));
    ${c(f).output} = result;
  }
  `}},3891:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.VecGlslLib=void 0;const l=o(8520);class c extends l.GlslLib{constructor(a){super(a)}getCustomTypes(){return{}}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign({},this.binaryVecFunctions()),this.copyVec()),this.setVecItem()),this.getVecItem())}binaryVecFunctions(){const a=this.context.outputTextureLayout.shape.length,h={add:"+=",sub:"-=",mul:"*=",div:"/="},p={};for(const u in h){const s=`${u}Vec`;let t="";for(let r=0;r<a;++r)t+=`
          dest[${r}] ${h[u]} src[${r}];
          `;const e=`
        void ${s}(int src[${a}], out int dest[${a}]) {
          ${t}
        }
        `;p[s]=new l.GlslLibRoutine(e)}return p}copyVec(){const a=this.context.outputTextureLayout.shape.length;let h="";for(let u=0;u<a;++u)h+=`
        dest[${u}] = src[${u}];
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      void copyVec(int src[${a}], out int dest[${a}]) {
        ${h}
      }
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        if(index < 0)
            index =${a} + index;
        if (index == 0)
            m[0] = value;
        `;for(let u=1;u<a-1;++u)h+=`
        else if (index == ${u})
            m[${u}] = value;
            `;h+=`
        else
            m[${a-1}] = value;
        `;const p=`
      void setVecItem(out int m[${a}], int index, int value) {
        ${h}
      }
        `;return{setVecItem:new l.GlslLibRoutine(p)}}getVecItem(){const a=this.context.outputTextureLayout.shape.length;let h=`
        if(index < 0)
            index = ${a} + index;
        if (index == 0)
            return m[0];
      `;for(let u=1;u<a-1;++u)h+=`
        else if (index == ${u})
            return m[${u}];
      `;h+=`
        else
            return m[${a-1}];
        `;const p=`
      int getVecItem(int m[${a}], int index) {
        ${h}
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        ${X}
        ${Q}
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      ${L.output} = result;
    }
    `;return{name:A.name,inputNames:["A","B"],inputTypes:[x,x],output:{dims:S[0].dims,type:O,textureType:x},shaderSource:N,hasMain:!0}};n.add=(w,S)=>[w.run(_(w,S,h()),S)],n.and=(w,S)=>[w.run(_(w,S,i(),"bool"),S)],n.div=(w,S)=>[w.run(_(w,S,p()),S)],n.equal=(w,S)=>[w.run(_(w,S,t(),"bool"),S)],n.greater=(w,S)=>[w.run(_(w,S,e(),"bool"),S)],n.less=(w,S)=>[w.run(_(w,S,r(),"bool"),S)],n.mul=(w,S)=>[w.run(_(w,S,u()),S)],n.or=(w,S)=>[w.run(_(w,S,d(),"bool"),S)],n.pow=(w,S)=>[w.run(_(w,S,m()),S)],n.pRelu=(w,S)=>[w.run(_(w,S,b()),S)],n.sub=(w,S)=>[w.run(_(w,S,s()),S)],n.xor=(w,S)=>[w.run(_(w,S,g(),"bool"),S)]},4196:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseCastAttributes=n.cast=void 0;const l=o(2517);n.cast=(f,a,h)=>(c(a),[f.cast(a[0],h)]),n.parseCastAttributes=f=>l.ProtoUtil.tensorDataTypeFromProto(f.attributes.getInt("to"));const c=f=>{if(!f||f.length!==1)throw new Error("Cast requires 1 input.");if(f[0].type==="string")throw new Error("Invalid input type.")}},1163:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedConcatProgramInfoLoader=void 0;const l=o(5060),c=o(2039),f=o(9390),a=o(2827);n.createPackedConcatProgramInfoLoader=(p,u,s)=>{const t=(e=u.length,r=s.cacheKey,{name:"Concat (packed)",inputNames:Array.from({length:e},(i,d)=>`X${d}`),inputTypes:Array(e).fill(c.TextureType.packed),cacheHint:r});var e,r;return Object.assign(Object.assign({},t),{get:()=>((i,d,g,m)=>{const b=g[0].dims.slice();if(m>=b.length||m<-1*b.length)throw new Error("axis specified for concat doesn't match input dimensionality");m<0&&(m=b.length+m);const _=b.slice(0);for(let X=1;X<g.length;X++){const Q=g[X].dims.slice();for(let ee=0;ee<b.length;ee++)if(ee===m)_[m]+=Q[ee];else if(b[ee]!==Q[ee])throw new Error("non concat dimensions must match")}const v=_.length,w=(0,a.getChannels)("coords",v),S=(0,f.getCoordsDataType)(v),A=(0,a.unpackFromChannel)(),O=g.map(X=>X.dims),x=(0,f.getGlChannels)(v),I=new Array(O.length-1);I[0]=O[0][m];for(let X=1;X<I.length;X++)I[X]=I[X-1]+O[X][m];const $=x[m],B=x.slice(-2),L=x.join();let N=`if (${$} < ${I[0]}) {
        return getChannel(
            getX0(${L}), vec2(${B.join()}));
        }`;for(let X=1;X<I.length;X++){const Q=I[X-1];N+=`
            if (${$} < ${I[X]}  && ${$} >= ${I[X-1]}) {
              return getChannel(
                getX${X}(${h(x,$,Q)}),
                vec2(${h(B,$,Q)}));
            }`}const H=I.length,M=I[I.length-1];N+=`
            return getChannel(
              getX${H}(${h(x,$,M)}),
              vec2(${h(B,$,M)}));`;const j=(0,l.getGlsl)(i.session.backend.glContext.version),Z=`
          ${A}
          float getValue(${x.map(X=>"int "+X)}) {
            ${N}
          }

          void main() {
            ${S} coords = getOutputCoords();
            int lastDim = coords.${x[v-1]};
            coords.${x[v-1]} = coords.${x[v-2]};
            coords.${x[v-2]} = lastDim;

            vec4 result = vec4(getValue(${w}), 0., 0., 0.);

            ${w[v-1]} = ${w[v-1]} + 1;
            if (${w[v-1]} < ${_[v-1]}) {
              result.g = getValue(${w});
            }

            ${w[v-2]} = ${w[v-2]} + 1;
            if (${w[v-2]} < ${_[v-2]}) {
              result.a = getValue(${w});
            }

            ${w[v-1]} = ${w[v-1]} - 1;
            if (${w[v-2]} < ${_[v-2]} &&
                ${w[v-1]} < ${_[v-1]}) {
              result.b = getValue(${w});
            }
            ${j.output} = result;
          }
        `;return Object.assign(Object.assign({},d),{output:{dims:_,type:g[0].type,textureType:c.TextureType.packed},shaderSource:Z,hasMain:!0})})(p,t,u,s.axis)})};const h=(p,u,s)=>{const t=p.indexOf(u);return p.map((e,r)=>r===t?`${e} - ${s}`:e).join()}},2069:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConcatAttributes=n.concat=void 0;const l=o(246),c=o(2039),f=o(1163);n.concat=(e,r,i)=>(t(r),e.session.pack&&r[0].dims.length>1?[e.run((0,f.createPackedConcatProgramInfoLoader)(e,r,i),r)]:[e.run(a(e,r,i),r)]);const a=(e,r,i)=>{const d=(g=r.length,m=i.cacheKey,{name:"Concat",inputNames:Array.from({length:g},(b,_)=>`X${_}`),inputTypes:Array(g).fill(c.TextureType.unpacked),cacheHint:m});var g,m;return Object.assign(Object.assign({},d),{get:()=>((b,_,v,w)=>{const S=v[0].dims.slice();if(w>=S.length||w<-1*S.length)throw new Error("axis specified for concat doesn't match input dimensionality");w<0&&(w=S.length+w);const A=S.slice(0);for(let L=1;L<v.length;L++){const N=v[L].dims.slice();for(let H=0;H<S.length;H++)if(H===w)A[w]+=N[H];else if(S[H]!==N[H])throw new Error("non concat dimensions must match")}const O=A.length,x=new Array(v.length);let I=0;for(let L=0;L<x.length;++L)I+=v[L].dims[w],x[L]=I;let $="";$=v.length<5?h(x):p(x);const B=`
        ${u(v.length,O)}
        ${s(x)}
        ${$}
        float process(int indices[${O}]) {
          int textureIndex = getTextureWhereDataResides (indices[${w}]);

          if(textureIndex != 0) {
            indices[${w}] = indices[${w}] - int(getSizeInConcatAxisValueFromIndex(textureIndex-int(1)));
          }

          return fetchDataFromCorrectTexture(textureIndex, indices);
        }`;return Object.assign(Object.assign({},_),{output:{dims:A,type:v[0].type,textureType:c.TextureType.unpacked},shaderSource:B})})(0,d,r,i.axis)})},h=e=>`int getTextureWhereDataResides(int index) {
      ${e.map((r,i)=>`if(index<${r}) {return ${i};}
`).join("")}
    }`,p=e=>h(e),u=(e,r)=>{const i=[`float fetchDataFromCorrectTexture(int textureIndex, int indices[${r}]) {`];for(let d=0;d<e;++d)d===0?i.push(`	if (textureIndex == ${d}) { return _X${d}(indices); }`):d===e-1?i.push(`	else { return _X${d}(indices); }`):i.push(`	else if (textureIndex == ${d}) { return _X${d}(indices); }`);return i.push("	}"),i.join(`
`)},s=e=>{const r=["int getSizeInConcatAxisValueFromIndex(int index) {"];for(let i=0;i<e.length;++i)i===0?r.push(`	if (index == ${i}) { return ${e[i]}; }`):i===e.length-1?r.push(`	else { return ${e[i]}; }`):r.push(`	else if (index == ${i}) { return ${e[i]}; }`);return r.push("	}"),r.join(`
`)};n.parseConcatAttributes=e=>(0,l.createAttributeWithCacheKey)({axis:e.attributes.getInt("axis")});const t=e=>{if(!e||e.length<1)throw new Error("too few inputs");const r=e[0].type,i=e[0].dims.length;if(r==="string")throw new Error("string tensor is not supported yet");for(const d of e){if(d.type!==r)throw new Error("input tensors should be one type");if(d.dims.length!==i)throw new Error("input tensors should have the same shape")}}},4770:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createUnpackedGroupedConvProgramInfoLoader=void 0;const l=o(6231),c=o(5060),f=o(2039),a=o(8138),h=o(2823);n.createUnpackedGroupedConvProgramInfoLoader=(p,u,s)=>{const t=(e=u.length>2,r=s.cacheKey,{name:"GroupedConv",inputNames:e?["X","W","Bias"]:["X","W"],inputTypes:e?[f.TextureType.unpacked,f.TextureType.unpacked,f.TextureType.unpacked]:[f.TextureType.unpacked,f.TextureType.unpacked],cacheHint:r});var e,r;return Object.assign(Object.assign({},t),{get:()=>((i,d,g,m)=>{const b=d.length>2?"value += getBias(output_channel);":"",_=d[0].dims.slice(),v=d[1].dims.slice(),w=v[0]/m.group;l.Logger.verbose("GroupedConv",`autpPad:${m.autoPad}, dilations:${m.dilations}, group:${m.group}, kernelShape:${m.kernelShape}, pads:${m.pads}, strides:${m.strides}`);const S=(0,a.calculateOutputShape)(_,v,m.dilations,m.pads,m.strides),A=(0,c.getGlsl)(i.session.backend.glContext.version),{activationFunction:O,applyActivation:x}=(0,h.getActivationSnippet)(m),I=`
  const ivec2 strides = ivec2(${m.strides[0]}, ${m.strides[1]});
  const ivec2 pads = ivec2(${m.pads[0]}, ${m.pads[1]});
  ${O}
  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 / ${w};

    float value = 0.0;
    for (int wInChannel = 0; wInChannel < ${v[1]}; wInChannel++) {
      int input_channel = group_id * ${v[1]} + wInChannel;
      for (int wHeight = 0; wHeight < ${v[2]}; wHeight++) {
        int xHeight = xRCCorner.x + wHeight * ${m.dilations[0]};

        if (xHeight < 0 || xHeight >= ${_[2]}) {
          continue;
        }

        for (int wWidth = 0; wWidth < ${v[3]}; wWidth++) {
          int xWidth = xRCCorner.y + wWidth * ${m.dilations[1]};
          if (xWidth < 0 || xWidth >= ${_[3]}) {
            continue;
          }

          float xVal = getX(batch, input_channel, xWidth, xHeight);
          float wVal = getW(output_channel, wInChannel, wWidth, wHeight);
          value += xVal*wVal;
        }
      }
    }
    ${b}
    ${x}
    ${A.output} = vec4(value, .0, .0, .0);
  }
`;return Object.assign(Object.assign({},g),{output:{dims:S,type:d[0].type,textureType:f.TextureType.unpacked},shaderSource:I,hasMain:!0})})(p,u,t,s)})}},1386:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.conv2DPacked=n.conv2DPackedPointwise=void 0;const l=o(8138),c=o(8555),f=o(708);n.conv2DPackedPointwise=(a,h,p)=>{const u=h[0].dims,s=h[1].dims,t=(0,l.calculateOutputShape)(u,s,p.dilations,p.pads,p.strides),e=a.reshapePacked(h[0],[u[1],u[2]*u[3]]),r=a.reshapePacked(h[1],[s[0],s[1]]),i=h.length>2?[r,e,h[2]]:[r,e],d=a.run((0,f.createPackedMatmulProgramInfoLoader)(a,i,p),i);return a.reshapePacked(d,t)},n.conv2DPacked=(a,h,p)=>{const u=h[0].dims,s=h[1].dims,t=(0,l.calculateOutputShape)(u,s,p.dilations,p.pads,p.strides),e=a.run((0,c.createPackedIm2ColProgramInfoLoader)(a,h[0],h[1],t,p),[h[0]]),r=a.reshapePacked(h[1],[s[0],s[1]*s[2]*s[3]]),i=h.length===3?[r,e,h[2]]:[r,e],d=a.run((0,f.createPackedMatmulProgramInfoLoader)(a,i,p),i);return a.reshapePacked(d,t)}},9663:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConvTransposeAttributes=n.convTranspose=void 0;const l=o(246),c=o(5060),f=o(2039),a=o(2823),h=(r,i,d,g,m,b)=>(r-1)*i+d+(g-1)*m+1-b,p=(r,i,d,g,m)=>{const b=Math.floor(r/2);i==="SAME_UPPER"?(d[g]=b,d[m]=r-b):i==="SAME_LOWER"&&(d[g]=r-b,d[m]=b)};n.convTranspose=(r,i,d)=>(e(i,d),u(r,i,d));const u=(r,i,d)=>{const g=t(d,i);return[s(r,i,g)]},s=(r,i,d)=>r.run(((g,m,b)=>{const _=(v=m.length>2,w=b.cacheKey,{name:"ConvTranspose",inputNames:v?["X","W","B"]:["X","W"],inputTypes:v?[f.TextureType.unpacked,f.TextureType.unpacked,f.TextureType.unpacked]:[f.TextureType.unpacked,f.TextureType.unpacked],cacheHint:w});var v,w;return Object.assign(Object.assign({},_),{get:()=>((S,A,O,x)=>{const I=A.length>2?"getB(output_channel)":"0.0",$=A[0].dims,B=A[1].dims,L=B[1],N=B[0]/x.group,H=[A[0].dims[0],A[1].dims[1]*x.group,...x.outputShape],M=(0,c.getGlsl)(S.session.backend.glContext.version),{activationFunction:j,applyActivation:Z}=(0,a.getActivationSnippet)(x),X=`
  const ivec2 strides = ivec2(${x.strides[0]}, ${x.strides[1]});
  const ivec2 pads = ivec2(${x.pads[0]}, ${x.pads[1]});
  ${j}
  void main() {
    ivec4 coords = getOutputCoords();
    int batch = coords.x;
    int output_channel = coords.y;

    ivec2 loc = coords.zw + pads;

    int group_id = output_channel / ${L};
    int wOutChannel = output_channel - group_id * ${L};

    float value = ${I};
    for (int inChannelOffset = 0; inChannelOffset < ${N}; inChannelOffset++) {
      int input_channel = group_id * ${N} + inChannelOffset;
      for (int wWOff = 0; wWOff < ${B[2]}; wWOff++) {
        for (int wHOff = 0; wHOff < ${B[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 < ${$[2]} &&
            wLocIn.y >= 0 && wLocIn.y < ${$[3]}
          ) {
            float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x);
            float wVal = getW(input_channel, wOutChannel, wHOff, wWOff);
            value += xVal * wVal;
          }
        }
      }
    }
    ${Z}
    ${M.output} = vec4(value, .0, .0, .0);
  }
`;return Object.assign(Object.assign({},O),{output:{dims:H,type:A[0].type,textureType:f.TextureType.unpacked},shaderSource:X,hasMain:!0})})(g,m,_,b)})})(r,i,d),i),t=(r,i)=>{const d=r.kernelShape.slice();if(r.kernelShape.length===0)for(let _=2;_<i[1].dims.length;++_)d.push(i[1].dims[_]);const g=r.pads.slice(),m=r.outputShape.slice();((_,v,w,S,A,O,x,I)=>{const $=_.length-2,B=I.length===0;for(let L=0;L<$;++L){const N=B?_[L+2]*O[L]:I[L],H=h(_[L+2],O[L],A[L],v[L],w[L],N);p(H,S,A,L,L+$),B&&I.push(O[L]*(_[L+2]-1)+x[L]+(v[L]-1)*w[L]+1-A[L]-A[L+$])}})(i[0].dims,d,r.dilations,r.autoPad,g,r.strides,r.outputPadding,m);const b=Object.assign({},r);return Object.assign(b,{kernelShape:d,pads:g,outputShape:m,cacheKey:r.cacheKey}),b};n.parseConvTransposeAttributes=r=>{const i=r.attributes,d=(0,a.parseInternalActivationAttributes)(i),g=i.getString("auto_pad","NOTSET"),m=i.getInts("dilations",[1,1]),b=i.getInt("group",1),_=i.getInts("kernel_shape",[]),v=i.getInts("output_padding",[0,0]),w=i.getInts("output_shape",[]),S=i.getInts("pads",[0,0,0,0]),A=i.getInts("strides",[1,1]);return(0,l.createAttributeWithCacheKey)(Object.assign({autoPad:g,dilations:m,group:b,kernelShape:_,outputPadding:v,outputShape:w,pads:S,strides:A},d))};const e=(r,i)=>{if(!r||r.length!==2&&r.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(r[0].dims.length!==4||r[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(r[0].dims[1]!==r[1].dims[0])throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");const d=r[1].dims[1]*i.group;if(r.length===3&&(r[2].dims.length!==1||r[2].dims[0]!==d))throw new Error("invalid bias");const g=r[0].dims.length-2;if(i.dilations.length!==g)throw new Error(`dilations should be ${g}D`);if(i.strides.length!==g)throw new Error(`strides should be ${g}D`);if(i.pads.length!==2*g)throw new Error(`pads should be ${2*g}D`);if(i.outputPadding.length!==g)throw new Error(`output_padding should be ${g}D`);if(i.kernelShape.length!==0&&i.kernelShape.length!==r[1].dims.length-2)throw new Error("invalid kernel shape");if(i.outputShape.length!==0&&i.outputShape.length!==r[0].dims.length-2)throw new Error("invalid output shape");if(r[0].type!=="float32"||r[1].type!=="float32")throw new Error("ConvTranspose input(X,W) should be float tensor");if(r.length===3&&r[2].type!=="float32")throw new Error("ConvTranspose input(bias) should be float tensor")}},8138:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConvAttributes=n.conv=n.calculateOutputShape=void 0;const l=o(246),c=o(2517),f=o(4770),a=o(1386),h=o(9828),p=o(2823),u=o(3248),s=o(5623);n.calculateOutputShape=(g,m,b,_,v)=>{const w=g[0],S=g.slice(2),A=S.length,O=m[0],x=m.slice(2).map(($,B)=>$+($-1)*(b[B]-1)),I=S.map(($,B)=>$+_[B]+_[B+A]).map(($,B)=>Math.floor(($-x[B]+v[B])/v[B]));return[w,O].concat(...I)},n.conv=(g,m,b)=>(d(m,b),t(g,m,b));const t=(g,m,b)=>{const _=i(b,m),v=g.session.pack,w=_.kernelShape[0]===1&&_.kernelShape[1]===1;return _.group>1?[g.run((0,f.createUnpackedGroupedConvProgramInfoLoader)(g,m,_),m)]:w&&v?[e(g,m,_)]:v&&m[0].dims.length===4&&m[0].dims[0]===1&&!w?[(0,a.conv2DPacked)(g,m,_)]:[r(g,m,_)]},e=(g,m,b)=>{const _=m[0].dims,v=m[1].dims,w=(0,n.calculateOutputShape)(_,v,b.dilations,b.pads,b.strides),S=g.reshapeUnpacked(m[0],[_[1],_[2]*_[3]]),A=g.reshapeUnpacked(m[1],[v[0],v[1]]),O=m.length>2?[A,S,m[2]]:[A,S],x=g.run((0,s.createMatmulProgramInfoLoader)(O,b),O);return g.reshapeUnpacked(x,w)},r=(g,m,b)=>{const _=m[0].dims,v=m[1].dims,w=(0,n.calculateOutputShape)(_,v,b.dilations,b.pads,b.strides),S=g.run((0,u.createIm2ColProgramInfoLoader)(g,m[0],m[1],w,b),[m[0]]),A=m.length===3?[S,m[1],m[2]]:[S,m[1]];return g.run((0,h.createDotProductProgramInfoLoader)(g,m,w,b),A)},i=(g,m)=>{const b=g.kernelShape.slice();if(g.kernelShape.length===0)for(let w=2;w<m[1].dims.length;++w)b.push(m[1].dims[w]);const _=g.pads.slice();c.PoolConvUtil.adjustPadsBasedOnAutoPad(m[0].dims,g.strides,g.dilations,b,_,g.autoPad);const v=Object.assign({},g);return Object.assign(v,{kernelShape:b,pads:_,cacheKey:g.cacheKey}),v};n.parseConvAttributes=g=>{const m=g.attributes,b=(0,p.parseInternalActivationAttributes)(m),_=m.getString("auto_pad","NOTSET"),v=m.getInts("dilations",[1,1]),w=m.getInt("group",1),S=m.getInts("kernel_shape",[]),A=m.getInts("pads",[0,0,0,0]),O=m.getInts("strides",[1,1]);return(0,l.createAttributeWithCacheKey)(Object.assign({autoPad:_,dilations:v,group:w,kernelShape:S,pads:A,strides:O},b))};const d=(g,m)=>{if(!g||g.length!==2&&g.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(g[0].dims.length!==4||g[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(g[0].dims[1]!==g[1].dims[1]*m.group)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(g.length===3&&(g[2].dims.length!==1||g[1].dims[0]!==g[2].dims[0]))throw new Error("invalid bias");const b=g[0].dims.length-2;if(m.dilations.length!==b)throw new Error(`dilations should be ${b}D`);if(m.strides.length!==b)throw new Error(`strides should be ${b}D`);if(m.pads.length!==2*b)throw new Error(`pads should be ${2*b}D`);if(m.kernelShape.length!==0&&m.kernelShape.length!==g[1].dims.length-2)throw new Error("invalid kernel shape");if(g[0].type!=="float32"||g[1].type!=="float32")throw new Error("Conv input(X,W) should be float tensor");if(g.length===3&&g[2].type!=="float32")throw new Error("Conv input(bias) should be float tensor")}},5193:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseDepthToSpaceAttributes=n.depthToSpace=void 0;const l=o(3738);n.depthToSpace=(f,a,h)=>{c(a);const p=h.blocksize,u=p*p,s=h.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],t=h.mode==="DCR"?[a[0].dims[0],p,p,a[0].dims[1]/u,a[0].dims[2],a[0].dims[3]]:[a[0].dims[0],a[0].dims[1]/u,p,p,a[0].dims[2],a[0].dims[3]],e=f.reshapeUnpacked(a[0],t),r={perm:s,cacheKey:`${s}`},[i]=(0,l.transpose)(f,[e],r),d=[a[0].dims[0],a[0].dims[1]/u,a[0].dims[2]*p,a[0].dims[3]*p];return[f.reshapeUnpacked(i,d)]},n.parseDepthToSpaceAttributes=f=>{const a=f.attributes.getInt("blocksize");if(a<1)throw new Error(`blocksize must be >= 1, but got : ${a} for DepthToSpace`);const h=f.attributes.getString("mode","DCR");if(h!=="DCR"&&h!=="CRD")throw new Error(`unrecognized mode: ${h} for DepthToSpace`);return{mode:h,blocksize:a}};const c=f=>{if(f.length!==1)throw new Error(`DepthToSpace expect 1 inputs, but got ${f.length}`);if(f[0].type==="string"||f[0].dims.length!==4)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}},9828:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createDotProductProgramInfoLoader=void 0;const l=o(2517),c=o(5060),f=o(2039),a=o(2823),h=o(3248);n.createDotProductProgramInfoLoader=(p,u,s,t)=>{const e=((r,i)=>({name:"ConvDotProduct",inputNames:r?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:r?[f.TextureType.unpacked,f.TextureType.packedLastDimension,f.TextureType.unpacked]:[f.TextureType.unpacked,f.TextureType.packedLastDimension],cacheKey:i.activationCacheKey}))(u.length>2,t);return Object.assign(Object.assign({},e),{get:()=>((r,i,d,g,m)=>{const b=d[0].dims,_=d[1].dims,v=[_[0],Math.ceil(b[1]*_[2]*_[3]/4)],w=(0,h.calculateIm2ColDims)(b,_,g),[S,A]=r.calculateTextureWidthAndHeight(v,f.TextureType.packedLastDimension),O=l.ShapeUtil.computeStrides(w),[x,I]=r.calculateTextureWidthAndHeight(w,f.TextureType.packedLastDimension),$=g.length,B=d.length<3?"0.0":"_B(b)",L=Math.ceil(b[1]*_[2]*_[3]/4),{activationFunction:N,applyActivation:H}=(0,a.getActivationSnippet)(m),M=(0,c.getGlsl)(r.session.backend.glContext.version),j=`
${N}
float process(int indices[${$}]) {
  int b[1];
  b[0] = indices[1];
  int im2col[4];
  im2col[0] = indices[0];
  im2col[1] = indices[2];
  im2col[2] = indices[3];
  int im2colOffset = im2col[0] * ${O[0]} + im2col[1] * ${O[1]} + im2col[2] * ${O[2]};
  int kernelOffset = indices[1] * ${v[1]};
  float value = ${B};
  for (int i = 0; i < ${L}; ++i) {
    vec2 im2colCoords = offsetToCoords(im2colOffset, ${x}, ${I});
    vec2 kernelCoords = offsetToCoords(kernelOffset, ${S}, ${A});
    value += dot(${M.texture2D}(Im2Col, im2colCoords), ${M.texture2D}(K, kernelCoords));
    ++im2colOffset;
    ++kernelOffset;
  }
  ${H}
  return value;
}`;return Object.assign(Object.assign({},i),{output:{dims:g,type:d[0].type,textureType:f.TextureType.unpacked},shaderSource:j})})(p,e,u,s,t)})}},7992:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseFlattenAttributes=n.flatten=void 0;const l=o(2517);n.flatten=(f,a,h)=>{c(a,h);const p=l.ShapeUtil.flattenShape(a[0].dims,h);return[f.reshapeUnpacked(a[0],p)]},n.parseFlattenAttributes=f=>f.attributes.getInt("axis",1);const c=(f,a)=>{if(!f||f.length!==1)throw new Error("Flatten requires 1 input.");const h=f[0].dims.length;if(h===0)throw new Error("scalar tensor is not supported.");if(a<-h||a>h)throw new Error("Invalid axis");if(f[0].type==="string")throw new Error("string tensor is not supported.")}},2823:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInternalActivationAttributes=n.getActivationSnippet=void 0;const l=o(2517),c=o(4909);n.getActivationSnippet=function(f){let a;switch(f.activation){case"Relu":a=(0,c.glslRelu)();break;case"Sigmoid":a=(0,c.glslSigmoid)();break;case"Clip":a=(0,c.glslClip)(f.clipMin,f.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const h=a.name;return{activationFunction:a.body,applyActivation:`value = ${h}_(value);`}},n.parseInternalActivationAttributes=f=>{const a=f.getString("activation","");if(a==="Clip"){const[h,p]=f.getFloats("activation_params",[l.MIN_CLIP,l.MAX_CLIP]);return{activation:a,clipMax:p,clipMin:h,activationCacheKey:`${a}:${h},${p}`}}return{activation:a,activationCacheKey:a}}},1253:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGatherAttributes=n.gather=void 0;const l=o(246),c=o(782),f=o(2517),a=o(2039);n.gather=(s,t,e)=>(u(t,e.axis),[s.run(p(s,t,e),t)]),n.parseGatherAttributes=s=>(0,l.createAttributeWithCacheKey)({axis:s.attributes.getInt("axis",0)});const h={name:"Gather",inputNames:["A","B"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked]},p=(s,t,e)=>{const r=Object.assign(Object.assign({},h),{cacheHint:e.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((i,d,g,m)=>{const b=g[0].dims.slice(),_=g[1].dims.slice(),v=new Array(b.length+_.length-1);m=f.ShapeUtil.normalizeAxis(m,b.length);const w=[];for(let A=0;A<v.length;A++)A<m?(v[A]=b[A],w.push(`inputIdx[${A}] = outputIdx[${A}];`)):A<m+_.length?(v[A]=_[A-m],w.push(`indexDataIdx[${A-m}] = outputIdx[${A}];`)):(v[A]=b[A-_.length+1],w.push(`inputIdx[${A-_.length+1}] = outputIdx[${A}];`));const S=`
      float process(int outputIdx[${v.length||1}]) {
        int inputIdx[${b.length}];
        int indexDataIdx[${_.length||1}];
        indexDataIdx[0] = 0;
        ${w.join(`
        `)}
        int idx = int(_B(indexDataIdx));
        inputIdx[${m}] = idx < 0 ? idx + ${b[m]} : idx;
        return _A(inputIdx);
      }`;return Object.assign(Object.assign({},d),{output:{dims:v,type:g[0].type,textureType:a.TextureType.unpacked},shaderSource:S})})(0,r,t,e.axis)})},u=(s,t)=>{if(!s||s.length!==2)throw new Error("Gather requires 2 inputs.");const e=s[0].dims.length;if(e<1)throw new Error("Invalid input shape.");if(t<-e||t>e-1)throw new Error("Invalid axis.");if(c.NUMBER_TYPES.indexOf(s[0].type)===-1)throw new Error("Invaid input type.");if(s[1].type!=="int32"&&s[1].type!=="int16")throw new Error("Invaid input type.")}},4776:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGemmAttributesV11=n.parseGemmAttributesV7=n.gemm=void 0;const l=o(246),c=o(2517),f=o(2039);n.gemm=(s,t,e)=>(u(t,e),[s.run(h(t,e),t)]);const a=(s,t)=>{const e=s.attributes.getInt("transA",0)!==0,r=s.attributes.getInt("transB",0)!==0,i=s.attributes.getFloat("alpha",1),d=s.attributes.getFloat("beta",1);return(0,l.createAttributeWithCacheKey)({transA:e,transB:r,alpha:i,beta:d,isOptionalC:t})};n.parseGemmAttributesV7=s=>a(s,!1),n.parseGemmAttributesV11=s=>a(s,!0);const h=(s,t)=>{const e={name:"Gemm",inputNames:s.length===3?["A","B","C"]:["A","B"],inputTypes:s.length===3?[f.TextureType.unpacked,f.TextureType.unpacked,f.TextureType.unpacked]:[f.TextureType.unpacked,f.TextureType.unpacked],key:t.cacheKey};return Object.assign(Object.assign({},e),{get:()=>p(e,s,t)})},p=(s,t,e)=>{const r=t[0].dims.slice(),i=t[1].dims.slice(),[d,g]=c.GemmUtil.getShapeOfGemmResult(r,e.transA,i,e.transB,t.length===3?t[2].dims:void 0),m=[d,g];if(!m)throw new Error("Can't use gemm on the given tensors");let b=r[r.length-1],_="";e.transA&&(b=r[0]),e.transA&&e.transB?_="value += _A_T(a) * _B_T(b);":e.transA&&!e.transB?_="value += _A_T(a) * _B(b);":!e.transA&&e.transB?_="value += _A(a) * _B_T(b);":e.transA||e.transB||(_="value += _A(a) * _B(b);");const v=m.length,w=`
      float process(int indices[${v}]) {
          int a[${v}];
          int b[${v}];
          ${t.length===3?`int c[${t[2].dims.length}];`:""}

          copyVec(indices, a);
          copyVec(indices, b);
          ${t.length===3?"bcastIndices_C(indices, c);":""}

          float value = 0.0;
          for (int k=0; k<${b}; ++k) {
              a[${v-1}] = k;
              b[${v-2}] = k;
              ${_}
          }

          value = value * alpha;
          ${t.length===3?"value += beta * _C(c);":""}
          return value;
      }`;return Object.assign(Object.assign({},s),{output:{dims:m,type:t[0].type,textureType:f.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:e.alpha},{name:"beta",type:"float",data:e.beta}],shaderSource:w})},u=(s,t)=>{if(!s)throw new Error("Input is missing");if(t.isOptionalC&&(s.length<2||s.length>3))throw new Error("Invaid input shape.");if(!t.isOptionalC&&s.length!==3)throw new Error("Gemm requires 3 inputs");if(s.length===3&&s[2].dims.length!==1&&s[2].dims.length!==2)throw new Error("Invalid input shape of C");if(s[0].type!=="float32"&&s[0].type!=="float64"||s[1].type!=="float32"&&s[1].type!=="float64"||s.length===3&&s[2].type!=="float32"&&s[2].type!=="float64")throw new Error("Invalid input type.");if(s[0].type!==s[1].type||s.length===3&&s[0].type!==s[2].type)throw new Error("Input types are mismatched")}},8555:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedIm2ColProgramInfoLoader=void 0;const l=o(5060),c=o(2039),f=o(2827);n.createPackedIm2ColProgramInfoLoader=(a,h,p,u,s)=>{const t=(e=s.cacheKey,{name:"Im2Col (packed)",inputNames:["A"],inputTypes:[c.TextureType.packed],cacheHint:e});var e;return Object.assign(Object.assign({},t),{get:()=>((r,i,d,g,m,b)=>{const _=d.dims,v=g.dims,w=m.length,S=[v[1]*v[2]*v[3],m[2]*m[3]],A=v[2]*v[3],O=(0,f.unpackFromChannel)(),x=(0,l.getGlsl)(r.session.backend.glContext.version);let I="";for(let B=0;B<=1;B++)for(let L=0;L<=1;L++)I+=`
            blockIndex = rc.x + ${L};
            pos = rc.y + ${B};

            if(blockIndex < ${S[1]} && pos < ${S[0]}) {
              offsetY = int(blockIndex / (${m[w-1]})) * ${b.strides[0]} -
                ${b.pads[0]};
              d0 = offsetY + ${b.dilations[0]} * (imod(pos, ${A}) / ${v[2]});

              if(d0 < ${_[2]} && d0 >= 0) {
                offsetX = imod(blockIndex, ${m[w-1]}) * ${b.strides[1]} -
                  ${b.pads[1]};
                d1 = offsetX + ${b.dilations[1]} * imod(imod(pos, ${A}), ${v[2]});

                if(d1 < ${_[3]} && d1 >= 0) {

                  ch = int(float(pos)/ ${A}.);
                    innerDims = vec2(d0, d1);
                    result[${2*B+L}] = getChannel(
                      getA(0, ch, int(innerDims.x),
                      int(innerDims.y)), innerDims);
                }
              }
            }

          `;const $=`
      ${O}

      void main() {
        ivec2 rc = getOutputCoords();
          vec4 result = vec4(0.0);
          int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
          vec2 innerDims;
          ${I}
          ${x.output} = result;
      }
            `;return Object.assign(Object.assign({},i),{output:{dims:S,type:d.type,textureType:c.TextureType.packed},shaderSource:$,hasMain:!0})})(a,t,h,p,u,s)})}},3248:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.calculateIm2ColDims=n.createIm2ColProgramInfoLoader=void 0;const l=o(2039);n.createIm2ColProgramInfoLoader=(c,f,a,h,p)=>{const u=(s=p.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[l.TextureType.unpacked],cacheHint:s});var s;return Object.assign(Object.assign({},u),{get:()=>((t,e,r,i,d,g)=>{const m=r.dims,b=i.dims,_=d.length,v=(0,n.calculateIm2ColDims)(m,b,d,4),w=`
        const int XC = ${m[1]};
        const int XH = ${m[2]};
        const int XW = ${m[3]};
        const int KH = ${g.kernelShape[0]};
        const int KW = ${g.kernelShape[1]};
        const int dilationH = ${g.dilations[0]};
        const int dilationW = ${g.dilations[1]};
        const int strideH = ${g.strides[0]};
        const int strideW = ${g.strides[1]};
        const int padH = ${g.pads[0]};
        const int padW = ${g.pads[1]};
        const int KHKW = KH*KW;
        const int XCKHKW = XC * KHKW;
        const int outputChannels = 4;
        vec4 process(int indices[${_}]) {
          int b  = indices[0]; // batch size
          int oh = indices[1] * strideH - padH; //output height
          int ow = indices[2] * strideW - padW; //output width
          int p = indices[3] * outputChannels; //patch
          vec4 value = vec4(0.0);
          for(int i=0; i < outputChannels; ++i) {
            if(p < XCKHKW) {
              int patchC = p / KHKW;
              int patchH = (p - patchC*KHKW) / KW;
              int patchW = (p - patchC*KHKW) - patchH * KW;
              int xh2 = oh + patchH * dilationH;
              int xw2 = ow + patchW * dilationW;
              int x[${m.length}];
              x[0] = b;
              x[1] = patchC;
              x[2] = xh2;
              x[3] = xw2;
              if(xh2 >= 0 &&
                  xh2 < XH &&
                  xw2 >= 0 &&
                  xw2 < XW) {
                value[i] = _X(x);
              }
            }
            ++p;
          }
          return value;
        }
        `;return Object.assign(Object.assign({},e),{output:{dims:v,type:r.type,textureType:l.TextureType.packedLastDimension},shaderSource:w})})(0,u,f,a,h,p)})},n.calculateIm2ColDims=(c,f,a,h=4)=>[a[0],a[2],a[3],Math.ceil(c[1]*f[2]*f[3]/h)]},6572:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseImageScalerAttributes=n.imageScaler=void 0;const l=o(246),c=o(2039);n.imageScaler=(u,s,t)=>(p(s),[u.run(a(u,s,t),s)]),n.parseImageScalerAttributes=u=>{const s=u.attributes.getFloat("scale"),t=u.attributes.getFloats("bias");return(0,l.createAttributeWithCacheKey)({scale:s,bias:t})};const f={name:"ImageScaler",inputNames:["X"],inputTypes:[c.TextureType.unpacked]},a=(u,s,t)=>{const e=Object.assign(Object.assign({},f),{cacheHint:t.cacheKey});return Object.assign(Object.assign({},e),{get:()=>((r,i,d,g)=>{const m=d[0].dims.slice(),b=m.length,_=`
      ${h(g.bias.length)}
      float process(int indices[${b}]) {
        return _X(indices) * scale + getBias(bias, indices[1]);
      }`;return Object.assign(Object.assign({},i),{output:{dims:m,type:d[0].type,textureType:c.TextureType.unpacked},variables:[{name:"bias",type:"float",arrayLength:g.bias.length,data:g.bias},{name:"scale",type:"float",data:g.scale}],shaderSource:_})})(0,e,s,t)})},h=u=>{const s=[`float getBias(float bias[${u}], int channel) {`];for(let t=0;t<u;++t)t===0?s.push(`	if (channel == ${t}) { return bias[${t}]; }`):t===u-1?s.push(`	else { return bias[${t}]; }`):s.push(`	else if (channel == ${t}) { return bias[${t}]; }`);return s.push("	}"),s.join(`
`)},p=u=>{if(!u||u.length!==1)throw new Error("ImageScaler requires 1 input.");if(u[0].dims.length!==4)throw new Error("Invalid input shape.");if(u[0].type!=="float32"&&u[0].type!=="float64")throw new Error("Invalid input type.")}},3346:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInstanceNormalizationAttributes=n.instanceNormalization=void 0;const l=o(5060),c=o(2039);n.instanceNormalization=(s,t,e)=>{u(t);const r=s.run(a(t[0]),t);return[s.run(p(s,t[0],e,r.dims),[t[0],r,t[1],t[2]])]},n.parseInstanceNormalizationAttributes=s=>s.attributes.getFloat("epsilon",1e-5);const f={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[c.TextureType.unpacked]},a=s=>Object.assign(Object.assign({},f),{get:()=>((t,e)=>{const r=e.dims.slice(),i=r[1],d=r[2]*r[3],g=[r[0],i],m=`
      vec4 process(int[2] indices) {
        vec4 v = vec4(0.0);
        int a[4];
        a[0] = indices[0];
        a[1] = indices[1];
        float temp = 0.0;
        for(int a2=0; a2<${r[2]}; a2++) {
          a[2] = a2;
          for(int a3=0; a3<${r[3]}; a3++) {
            a[3] = a3;
            float x = _X(a);
            temp += x;
          }
        }
        float mean = temp / float(${d});
        temp = 0.0;
        for(int a2=0; a2<${r[2]}; a2++) {
          a[2] = a2;
          for(int a3=0; a3<${r[3]}; a3++) {
            a[3] = a3;
            float x = _X(a);
            temp += (x - mean) * (x - mean);
          }
        }
        v.r = mean;
        v.g = temp / float(${d});

        return v;
      }`;return Object.assign(Object.assign({},t),{output:{dims:g,type:e.type,textureType:c.TextureType.packedLastDimension},shaderSource:m})})(f,s)}),h={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[c.TextureType.unpacked,c.TextureType.packedLastDimension,c.TextureType.unpacked,c.TextureType.unpacked]},p=(s,t,e,r)=>{const i=Object.assign(Object.assign({},h),{cacheHint:`${e}`});return Object.assign(Object.assign({},i),{get:()=>((d,g,m,b,_)=>{const v=(0,l.getGlsl)(d.session.backend.glContext.version),[w,S]=d.calculateTextureWidthAndHeight(_,c.TextureType.packedLastDimension),[A,O]=[w/4,S],x=`
      vec4 get_MeanAndVariance(int[2] mv) {
        int offset = indicesToOffset_MeanAndVariance(mv);
        vec2 coords = offsetToCoords(offset, ${A}, ${O});
        return ${v.texture2D}(MeanAndVariance, coords);
      }

      float process(int[4] indices) {
        int mv[2];
        mv[0] = indices[0];
        mv[1] = indices[1];
        vec4 mean_and_variance = get_MeanAndVariance(mv);
        float mean = mean_and_variance.r;
        float variance = mean_and_variance.g;

        int sb[1];
        sb[0] = indices[1];
        float scale = _Scale(sb);
        float b = _B(sb);

        return scale * (_X(indices) - mean) / sqrt(variance + epsilon) + b;
      }`;return Object.assign(Object.assign({},g),{output:{dims:m.dims,type:m.type,textureType:c.TextureType.unpacked},variables:[{name:"epsilon",type:"float",data:b}],shaderSource:x})})(s,i,t,e,r)})},u=s=>{if(!s||s.length!==3)throw new Error("InstanceNormalization requires 3 inputs.");const t=s[0],e=s[1],r=s[2];if(t.dims.length<3||e.dims.length!==1||r.dims.length!==1)throw new Error("Invalid input shape.");if(e.dims[0]!==t.dims[1]||r.dims[0]!==t.dims[1])throw new Error("Input shapes are mismatched.");if(t.type!=="float32"&&t.type!=="float64"||e.type!=="float32"&&e.type!=="float64"||r.type!=="float32"&&r.type!=="float64")throw new Error("Invalid input type.");if(s[0].dims.length!==4)throw new Error("Only support 4-D input shape.")}},708:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedMatmulProgramInfoLoader=void 0;const l=o(2517),c=o(5060),f=o(2039),a=o(9390),h=o(2823),p=o(5623);n.createPackedMatmulProgramInfoLoader=(u,s,t)=>{const e=(r=s.length>2,i=t.activationCacheKey,{name:"MatMul (packed)",inputNames:r?["A","B","Bias"]:["A","B"],inputTypes:r?[f.TextureType.packed,f.TextureType.packed,f.TextureType.packed]:[f.TextureType.packed,f.TextureType.packed],cacheHint:i});var r,i;return Object.assign(Object.assign({},e),{get:()=>((d,g,m,b)=>{const _=m.length>2,v=_?"value += getBiasForMatmul();":"",w=m[0].dims,S=m[1].dims,A=l.BroadcastUtil.calcShape(w,S,!0),O=!l.ShapeUtil.areEqual(m[0].dims,m[1].dims);if(!A)throw new Error("Can't use matmul on the given tensors");const x=w[w.length-1],I=Math.ceil(x/2),$=w.length,B=S.length,L=(0,c.getGlsl)(d.session.backend.glContext.version),N=(0,a.getCoordsDataType)(A.length),H=A.length,M=(0,a.getGlChannels)(),{activationFunction:j,applyActivation:Z}=(0,h.getActivationSnippet)(b),X=_?`${(0,p.getBiasForMatmul)(N,M,m[2].dims,A,!0)}`:"",Q=O?`${function(xe,oe,we,ye){let ke=[],Ne=[];const Te=we[0].dims,$e=we[1].dims,Ce=Te.length,Ee=$e.length,Oe=ye.length,Be=Oe-Ce,Ve=Oe-Ee;ke=Te.map((Ie,je)=>`coords.${oe[je+Be]}`),ke[Ce-1]="i*2",ke.join(", "),Ne=$e.map((Ie,je)=>`coords.${oe[je+Ve]}`),Ne[Ee-2]="i*2",Ne.join(", ");const Ge=l.BroadcastUtil.getBroadcastDims(Te,ye),Xe=l.BroadcastUtil.getBroadcastDims($e,ye),Ze=Ge.map(Ie=>`coords.${oe[Ie+Be]} = 0;`).join(`
`),qe=Xe.map(Ie=>`coords.${oe[Ie+Ve]} = 0;`).join(`
`),Ue=`int lastDim = coords.${oe[Oe-1]};
  coords.${oe[Oe-1]} = coords.${oe[Oe-2]};
  coords.${oe[Oe-2]} = lastDim;`;return`
vec4 getAAtOutCoordsMatmul(int i) {
  ${xe} coords = getOutputCoords();
  ${Ue}
  ${Ze}
  vec4 outputValue = getA(${ke});
  return outputValue;
}

vec4 getBAtOutCoordsMatmul(int i) {
  ${xe} coords = getOutputCoords();
  ${Ue}
  ${qe}
  vec4 outputValue = getB(${Ne});
  return outputValue;
}`}(N,M,m,A)}`:"",ee=O?"getAAtOutCoordsMatmul(i)":`getA(${function(xe,oe){let we="";for(let ye=0;ye<oe-2;ye++)we+=`rc.${xe[ye]}, `;return we+=`rc.${xe[oe-2]}, i*2`,we}(M,$)})`,ue=O?"getBAtOutCoordsMatmul(i)":`getB(${function(xe,oe){let we="";for(let ye=0;ye<oe-2;ye++)we+=`rc.${xe[ye]}, `;return we+=`i*2, rc.${xe[oe-1]}`,we}(M,B)})`,Ae=`
            ${Q}
            ${X}
            ${j}
            void main() {
              ${O?"":`${N} rc =
          getOutputCoords(); int lastDim = rc.${M[H-1]}; rc.${M[H-1]} =
          rc.${M[H-2]}; rc.${M[H-2]} = lastDim;
      `}

              vec4 value = vec4(0);
              for (int i = 0; i < ${I}; i++) {
                vec4 a = ${ee};
                vec4 b = ${ue};

                value += (a.rrbb * b.rgrg);
                value += (a.ggaa * b.baba);
              }
              ${v}
              ${Z}
              ${L.output} = value;
            }`;return Object.assign(Object.assign({},g),{output:{dims:A,type:m[0].type,textureType:f.TextureType.packed},shaderSource:Ae,hasMain:!0})})(u,e,s,t)})}},5623:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.getBiasForMatmul=n.createMatmulProgramInfoLoader=n.parseMatMulAttributes=n.matMul=void 0;const l=o(2517),c=o(2039),f=o(9390),a=o(2823),h=o(708);function p(t,e){const r=(i=t.length>2,d=e.activationCacheKey,{name:"MatMul",inputNames:i?["A","B","Bias"]:["A","B"],inputTypes:i?[c.TextureType.unpacked,c.TextureType.unpacked,c.TextureType.unpacked]:[c.TextureType.unpacked,c.TextureType.unpacked],cacheHint:d});var i,d;return Object.assign(Object.assign({},r),{get:()=>function(g,m,b){const _=m[0].dims,v=m[1].dims,w=l.BroadcastUtil.calcShape(_,v,!0);if(!w)throw new Error("Can't use matmul on the given tensors");const S=(0,f.getCoordsDataType)(w.length),A=(0,f.getGlChannels)(),{activationFunction:O,applyActivation:x}=(0,a.getActivationSnippet)(b),I=m.length>2,$=I?"value += getBiasForMatmul();":"",B=I?`${s(S,A,m[2].dims,w,!1)}`:"",L=w.length,N=_.length,H=v.length,M=`
    ${O}
    ${B}
    float process(int indices[${L}]) {
        int a[${N}];
        int b[${H}];
        bcastMatmulIndices_A(indices, a);
        bcastMatmulIndices_B(indices, b);

        float value;
        for (int k=0; k<${_[_.length-1]}; ++k) {
            a[${N-1}] = k;
            b[${H-2}] = k;
            value += _A(a) * _B(b);
        }
        ${$}
        ${x}
        return value;
    }`;return Object.assign(Object.assign({},g),{output:{dims:w,type:m[0].type,textureType:c.TextureType.unpacked},shaderSource:M})}(r,t,e)})}n.matMul=(t,e,r)=>(u(e),t.session.pack?[t.run((0,h.createPackedMatmulProgramInfoLoader)(t,e,r),e)]:[t.run(p(e,r),e)]),n.parseMatMulAttributes=t=>(0,a.parseInternalActivationAttributes)(t.attributes),n.createMatmulProgramInfoLoader=p;const u=t=>{if(!t||t.length!==2)throw new Error("MatMul requires 2 inputs.");if(t[0].dims[t[0].dims.length-1]!==t[1].dims[t[1].dims.length-2])throw new Error("shared dimension does not match.");if(t[0].type!=="float32"&&t[0].type!=="float64"||t[1].type!=="float32"&&t[1].type!=="float64")throw new Error("inputs should be float type");if(t[0].type!==t[1].type)throw new Error("inputs types should match")};function s(t,e,r,i,d){let g="";const m=r.length,b=i.length,_=b-m;g=b<2&&m>0?"coords":r.map((S,A)=>`coords.${e[A+_]}`).join(", ");const v=l.BroadcastUtil.getBroadcastDims(r,i).map(S=>`coords.${e[S+_]} = 0;`).join(`
`);let w="vec4(outputValue.xx, outputValue.yy)";return l.ShapeUtil.size(r)===1&&(w="vec4(outputValue.x)"),d?`
vec4 getBiasForMatmul() {
  ${t} coords = getOutputCoords();
  ${v}
  vec4 outputValue = getBias(${g});
  return ${w};
}`:`
float getBiasForMatmul() {
  ${t} coords = getOutputCoords();
  ${v}
  return getBias(coords.x);
}`}n.getBiasForMatmul=s},2403:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackProgramInfoLoader=void 0;const l=o(5060),c=o(2039),f=o(9390),a=o(2827),h={name:"pack",inputNames:["A"],inputTypes:[c.TextureType.unpackedReversed]};n.createPackProgramInfoLoader=(p,u)=>Object.assign(Object.assign({},h),{get:()=>((s,t)=>{const e=(0,l.getGlsl)(s.session.backend.glContext.version),r=t.dims,i=r.length,d=t.dims.length,g=(0,f.getCoordsDataType)(d),m=(0,a.getChannels)("rc",d),b=(_=d,v=m,w=r[r.length-2],S=r[r.length-1],_===0||_===1?"":`
    int r = ${v[_-2]};
    int c = ${v[_-1]};
    int rp1 = ${v[_-2]} + 1;
    int cp1 = ${v[_-1]} + 1;
    bool rEdge = rp1 >= ${S};
    bool cEdge = cp1 >= ${w};
    `);var _,v,w,S;let A;A=i===0?[1,1]:i===1?[r[0],1]:[r[d-1],r[d-2]];const O=function($,B,L){if($===0)return"false";if($===1)return`rc > ${B[0]}`;let N="";for(let H=$-2;H<$;H++)N+=`${L[H]} >= ${B[H-$+2]}`,H<$-1&&(N+="||");return N}(d,A,m),x=function($,B){const L=$.length;if(L===0)return"getA(), 0, 0, 0";if(L===1)return`getA(rc),
            rc + 1 >= ${$[0]} ? 0. : getA(rc + 1),
            0, 0`;let N="";if(L>2)for(let H=0;H<L-2;++H)N+=`${B[H]},`;return`getA(${N}r, c),
          rEdge ? 0. : getA(${N}rp1, c),
          cEdge ? 0. : getA(${N}r, cp1),
          rEdge || cEdge ? 0. : getA(${N}rp1, cp1)`}(r,m),I=`
        void main() {
          ${g} rc = getOutputCoords();

          if(${O}) {
            ${e.output} = vec4(0);
          } else {
            ${b}

            ${e.output} = vec4(${x});
          }
        }
      `;return Object.assign(Object.assign({},h),{hasMain:!0,output:{dims:t.dims,type:t.type,textureType:c.TextureType.packed},shaderSource:I})})(p,u)})},2827:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.unpackFromChannel=n.getChannels=n.getVecChannels=void 0;const l=o(9390);function c(f,a){return(0,l.getGlChannels)(a).map(h=>`${f}.${h}`)}n.getVecChannels=c,n.getChannels=function(f,a){return a===1?[f]:c(f,a)},n.unpackFromChannel=function(){return`
    float getChannel(vec4 frag, int dim) {
      int modCoord = imod(dim, 2);
      return modCoord == 0 ? frag.r : frag.g;
    }

    float getChannel(vec4 frag, vec2 innerDims) {
      vec2 modCoord = mod(innerDims, 2.);
      return modCoord.x == 0. ?
        (modCoord.y == 0. ? frag.r : frag.g) :
        (modCoord.y == 0. ? frag.b : frag.a);
    }
  `}},2870:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parsePadAttributesV11=n.padV11=n.parsePadAttributesV2=n.padV2=void 0;const l=o(246),c=o(2517),f=o(5060),a=o(2039),h={name:"Pad",inputNames:["A"],inputTypes:[a.TextureType.unpacked]};n.padV2=(g,m,b)=>(s(m),[g.run(Object.assign(Object.assign({},h),{cacheHint:b.cacheKey,get:()=>u(g,m[0],b)}),m)]),n.parsePadAttributesV2=g=>{const m=g.attributes.getString("mode","constant"),b=g.attributes.getFloat("value",0),_=g.attributes.getInts("pads");return(0,l.createAttributeWithCacheKey)({mode:m,value:b,pads:_})},n.padV11=(g,m,b)=>{t(m);const _=p(g,m,b);return(0,n.padV2)(g,[m[0]],_)},n.parsePadAttributesV11=g=>g.attributes.getString("mode","constant");const p=(g,m,b)=>{if(!g.session.isInitializer(m[1].dataId)||m.length>=3&&!g.session.isInitializer(m[2].dataId))throw new Error("dynamic pad attributes are not allowed");const _=Array.from(m[1].integerData),v=m.length>=3?m[2].floatData[0]:0;return(0,l.createAttributeWithCacheKey)({mode:b,pads:_,value:v})},u=(g,m,b)=>{const _=c.ShapeUtil.padShape(m.dims.slice(),b.pads),v=_.length,w=`
      ${e(g,m,b)}
      float process(int[${v}] indices) {
          return padA(indices);
      }`;return{name:"Pad",inputNames:["A"],inputTypes:[a.TextureType.unpacked],output:{dims:_,type:m.type,textureType:a.TextureType.unpacked},shaderSource:w}},s=g=>{if(!g||g.length!==1)throw new Error("Pad requires 1 input");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type.")},t=g=>{if(!g||g.length!==2&&g.length!==3)throw new Error("Pad requires 2 or 3 inputs");if(g[1].type!=="int32")throw new Error("Invalid input type.");if(g.length>=3&&g[2].type==="string")throw new Error("Invalid input type.")},e=(g,m,b)=>{const _=(0,f.getGlsl)(g.session.backend.glContext.version),[v,w]=g.calculateTextureWidthAndHeight(m.dims,a.TextureType.unpacked),S=c.ShapeUtil.computeStrides(m.dims);switch(b.mode){case"constant":return r(_,m.dims,S,v,w,b.pads,b.value);case"reflect":return i(_,m.dims,S,v,w,b.pads);case"edge":return d(_,m.dims,S,v,w,b.pads);default:throw new Error("Invalid mode")}},r=(g,m,b,_,v,w,S)=>{const A=m.length;let O="";for(let x=A-1;x>=0;--x)O+=`
        k = m[${x}] - ${w[x]};
        if (k < 0)  return constant;
        if (k >= ${m[x]}) return constant;
        offset += k * ${b[x]};
        `;return`
      float padA(int m[${A}]) {
        const float constant = float(${S});
        int offset = 0;
        int k = 0;
        ${O}
        vec2 coords = offsetToCoords(offset, ${_}, ${v});
        float value = getColorAsFloat(${g.texture2D}(A, coords));
        return value;
      }
      `},i=(g,m,b,_,v,w)=>{const S=m.length;let A="";for(let O=S-1;O>=0;--O)A+=`
        k = m[${O}] - ${w[O]};
        if (k < 0) { k = -k; }
        {
          const int _2n_1 = ${2*(m[O]-1)};
          k = int( mod( float(k), float(_2n_1) ) ) ;
          if(k >= ${m[O]}) { k = _2n_1 - k; }
        }
        offset += k * ${b[O]};
        `;return`
      float padA(int m[${S}]) {
        int offset = 0;
        int k = 0;
        ${A}
        vec2 coords = offsetToCoords(offset, ${_}, ${v});
        float value = getColorAsFloat(${g.texture2D}(A, coords));
        return value;
      }
      `},d=(g,m,b,_,v,w)=>{const S=m.length;let A="";for(let O=S-1;O>=0;--O)A+=`
        k = m[${O}] - ${w[O]};
        if (k < 0)  k = 0;
        if (k >= ${m[O]}) k = ${m[O]-1};
        offset += k * ${b[O]};
      `;return`
      float padA(int m[${S}]) {
        int offset = 0;
        int k = 0;
        ${A}
        vec2 coords = offsetToCoords(offset, ${_}, ${v});
        float value = getColorAsFloat(${g.texture2D}(A, coords));
        return value;
      }
      `}},2143:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.globalMaxPool=n.parseMaxPoolAttributes=n.maxPool=n.parseGlobalAveragePoolAttributes=n.globalAveragePool=n.parseAveragePoolAttributes=n.averagePool=void 0;const l=o(246),c=o(2517),f=o(2039);n.averagePool=(d,g,m)=>{t(g);const b={name:"AveragePool",inputNames:["X"],inputTypes:[f.TextureType.unpacked],cacheHint:m.cacheKey};return[d.run(Object.assign(Object.assign({},b),{get:()=>a(g,b,!1,m)}),g)]},n.parseAveragePoolAttributes=d=>{const g=d.attributes.getString("auto_pad","NOTSET"),m=d.attributes.getInt("ceil_mode",0),b=d.attributes.getInt("count_include_pad",0)!==0,_=d.attributes.getInts("kernel_shape"),v=d.attributes.getInts("strides",[]),w=d.attributes.getInts("pads",[]);if(m!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,l.createAttributeWithCacheKey)({autoPad:g,ceilMode:m,countIncludePad:b,kernelShape:_,strides:v,pads:w})};const a=(d,g,m,b)=>{const[_,v]=p(d,b,m),w=c.ShapeUtil.size(_.kernelShape);let S="";_.countIncludePad?S+=`value /= float(${w});`:S+=`value /= float(${w} - pad);`;const A=`
        ${e(d[0].dims,_,"value += _X(x);",S,"0.0")}
      `;return Object.assign(Object.assign({},g),{output:{dims:v,type:d[0].type,textureType:f.TextureType.unpacked},shaderSource:A})};n.globalAveragePool=(d,g,m)=>{t(g);const b={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[f.TextureType.unpacked],cacheHint:`${m.countIncludePad}`};return[d.run(Object.assign(Object.assign({},b),{get:()=>a(g,b,!0,m)}),g)]},n.parseGlobalAveragePoolAttributes=d=>{const g=d.attributes.getInt("count_include_pad",0)!==0;return(0,l.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:g,kernelShape:[],strides:[],pads:[]})},n.maxPool=(d,g,m)=>{t(g);const b={name:"MaxPool",inputNames:["X"],inputTypes:[f.TextureType.unpacked],cacheHint:m.cacheKey};return[d.run(Object.assign(Object.assign({},b),{get:()=>h(g,b,!1,m)}),g)]},n.parseMaxPoolAttributes=d=>{const g=d.attributes.getString("auto_pad","NOTSET"),m=d.attributes.getInt("ceil_mode",0),b=d.attributes.getInts("kernel_shape"),_=d.attributes.getInts("strides",[]),v=d.attributes.getInts("pads",[]),w=d.attributes.getInt("storage_order",0),S=d.attributes.getInts("dilations",[]);if(w!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(m!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return(0,l.createAttributeWithCacheKey)({autoPad:g,ceilMode:m,countIncludePad:!1,kernelShape:b,strides:_,pads:v,storageOrder:w,dilations:S})};const h=(d,g,m,b)=>{const[_,v]=p(d,b,m),w=`
      ${e(d[0].dims,_,`
      value = max(_X(x), value);
    `,"","-1e5")}
    `;return Object.assign(Object.assign({},g),{output:{dims:v,type:d[0].type,textureType:f.TextureType.unpacked},shaderSource:w})},p=(d,g,m)=>{const b=d[0].dims.slice(),_=Object.hasOwnProperty.call(g,"dilations"),v=g.kernelShape.slice(),w=g.strides.slice(),S=_?g.dilations.slice():[],A=g.pads.slice();c.PoolConvUtil.adjustPoolAttributes(m,b,v,w,S,A);const O=c.PoolConvUtil.computePoolOutputShape(m,b,w,S,v,A,g.autoPad),x=Object.assign({},g);return _?Object.assign(x,{kernelShape:v,strides:w,pads:A,dilations:S,cacheKey:g.cacheKey}):Object.assign(x,{kernelShape:v,strides:w,pads:A,cacheKey:g.cacheKey}),[x,O]},u={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},s={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[f.TextureType.unpacked]};n.globalMaxPool=(d,g)=>(t(g),[d.run(Object.assign(Object.assign({},s),{get:()=>h(g,s,!0,u)}),g)]);const t=d=>{if(!d||d.length!==1)throw new Error("Pool ops requires 1 input.");if(d[0].type!=="float32"&&d[0].type!=="float64")throw new Error("Invalid input type.")},e=(d,g,m,b,_)=>{const v=d.length;if(g.kernelShape.length<=2){const w=g.kernelShape[g.kernelShape.length-1],S=g.strides[g.strides.length-1],A=g.pads[g.pads.length/2-1],O=g.pads[g.pads.length-1],x=d[v-1];let I="",$="",B="";if(I=A+O!==0?`
          for (int i = 0; i < ${w}; i++) {
            x[${v} - 1] = indices[${v} - 1] * ${S} - ${A} + i;
            if (x[${v} - 1] < 0 || x[${v} - 1] >= ${x}) {
              pad++;
              continue;
            }
            ${m}
          }`:`
          for (int i = 0; i < ${w}; i++) {
            x[${v} - 1] = indices[${v} - 1] * ${S} - ${A} + i;
            ${m}
          }`,g.kernelShape.length===2){const L=g.kernelShape[g.kernelShape.length-2],N=g.strides[g.strides.length-2],H=g.pads[g.pads.length/2-2],M=g.pads[g.pads.length-2],j=d[v-2];$=H+M!==0?`
            for (int j = 0; j < ${L}; j++) {
              x[${v} - 2] = indices[${v} - 2] * ${N} - ${H} + j;
              if (x[${v} - 2] < 0 || x[${v} - 2] >= ${j}) {
                pad+= ${w};
                continue;
              }
          `:`
            for (int j = 0; j < ${L}; j++) {
              x[${v} - 2] = indices[${v} - 2] * ${N} - ${H} + j;
            `,B=`
          }
        `}return`
        float process(int indices[${v}]) {
          int x[${v}];
          copyVec(indices, x);

          float value = ${_};
          int pad = 0;
          ${$}
          ${I}
          ${B}
          ${b}
          return value;
        }
      `}{const w=c.ShapeUtil.size(g.kernelShape),S=c.ShapeUtil.computeStrides(g.kernelShape),A=S.length,O=g.pads.length,x=i(A),I=r(d,"inputDims"),$=r(g.pads,"pads"),B=r(S,"kernelStrides"),L=r(g.strides,"strides");let N="";return N=g.pads.reduce((H,M)=>H+M)?`
            if (x[j] >= inputDims[j] || x[j] < 0) {
              pad++;
              isPad = true;
              break;
            }
          }
          if (!isPad) {
            ${m}
          }`:`
          }
          ${m}
        `,`
        ${x}
        float process(int indices[${v}]) {
          int x[${v}];
          copyVec(indices, x);
          int offset[${A}];
          int pads[${O}];
          int inputDims[${v}];
          int kernelStrides[${A}];
          int strides[${A}];
          ${$}
          ${I}
          ${L}
          ${B}

          float value = ${_};
          int pad = 0;
          bool isPad = false;
          for (int i = 0; i < ${w}; i++) {
            offsetToIndices(i, kernelStrides, offset);
            isPad = false;
            for (int j = ${v} - ${A}; j < ${v}; j++) {
              x[j] = indices[j] * strides[j - ${v} + ${A}]
                + offset[j - ${v} + ${A}] - pads[j - 2];
              ${N}
          }
          ${b}

          return value;
        }
      `}},r=(d,g)=>{let m="";for(let b=0;b<d.length;b++)m+=`
      ${g}[${b}] = ${d[b]};
    `;return m},i=d=>`
  void offsetToIndices(int offset, int[${d}] strides, out int[${d}] indices) {
    if (${d} == 0) {
      return;
    }
    for (int i = 0; i < ${d} - 1; ++i) {
      indices[i] = offset / strides[i];
      offset -= indices[i] * strides[i];
    }
    indices[${d} - 1] = offset;
  }`},4939:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.reduceLogSumSquare=n.reduceLogSum=n.reduceProd=n.reduceMin=n.reduceMax=n.reduceMean=n.reduceSum=n.parseReduceAttributes=void 0;const l=o(246),c=o(782),f=o(2517),a=o(2039),h=(s,t,e,r,i)=>{u(t);const d={name:r,inputNames:["A"],inputTypes:[a.TextureType.unpacked]};return[s.run(Object.assign(Object.assign({},d),{cacheHint:e.cacheKey,get:()=>p(s,t,e,r,i,d)}),t)]};n.parseReduceAttributes=s=>{const t=s.attributes.getInts("axes",[]),e=s.attributes.getInt("keepdims",1)===1;return(0,l.createAttributeWithCacheKey)({axes:t,keepDims:e})};const p=(s,t,e,r,i,d)=>{const g=[],m=t[0].dims.length||1,b=[],_=f.ShapeUtil.normalizeAxes(e.axes,t[0].dims.length),v=i(t,_);let w=v[1];for(let A=0;A<t[0].dims.length;A++)_.indexOf(A)>=0||_.length===0?(e.keepDims&&g.push(1),w=`
          for(int j${A} = 0; j${A} < ${t[0].dims[A]}; j${A}++) {
            inputIdx[${A}] = j${A};
            ${w}
          }`):(b.push(`inputIdx[${A}] = outputIdx[${g.length}];`),g.push(t[0].dims[A]));const S=`
      float process(int outputIdx[${g.length||1}]) {
        float value;                 // final result
        int inputIdx[${m}];      // addressing input data
        ${b.join(`
`)}
        ${v[0]}       // init ops for reduce max/min
        ${w}
        ${v[2]}       // final computation for reduce mean
        return value;
      }`;return Object.assign(Object.assign({},d),{output:{dims:g,type:t[0].type,textureType:a.TextureType.unpacked},shaderSource:S})},u=s=>{if(!s||s.length!==1)throw new Error("Reduce op requires 1 input.");if(c.NUMBER_TYPES.indexOf(s[0].type)===-1)throw new Error("Invalid input type.")};n.reduceSum=(s,t,e)=>h(s,t,e,"ReduceSum",()=>["value = 0.0;","value += _A(inputIdx);",""]),n.reduceMean=(s,t,e)=>h(s,t,e,"ReduceMean",(r,i)=>{let d=1;for(let g=0;g<r[0].dims.length;g++)(i.indexOf(g)>=0||i.length===0)&&(d*=r[0].dims[g]);return["value = 0.0;","value += _A(inputIdx);",`value /= ${d}.;`]}),n.reduceMax=(s,t,e)=>h(s,t,e,"ReduceMax",(r,i)=>{const d=[];for(let g=0;g<r[0].dims.length;g++)(i.indexOf(g)>=0||i.length===0)&&d.push(`inputIdx[${g}] = 0;`);return[`${d.join(`
`)}
value = _A(inputIdx);`,"value = max(value, _A(inputIdx));",""]}),n.reduceMin=(s,t,e)=>h(s,t,e,"ReduceMin",(r,i)=>{const d=[];for(let g=0;g<r[0].dims.length;g++)(i.indexOf(g)>=0||i.length===0)&&d.push(`inputIdx[${g}] = 0;`);return[`${d.join(`
`)}
value = _A(inputIdx);`,"value = min(value, _A(inputIdx));",""]}),n.reduceProd=(s,t,e)=>h(s,t,e,"ReduceProd",()=>["value = 1.0;","value *= _A(inputIdx);",""]),n.reduceLogSum=(s,t,e)=>h(s,t,e,"ReduceLogSum",()=>["value = 0.0;","value += _A(inputIdx);","value = log(value);"]),n.reduceLogSumSquare=(s,t,e)=>h(s,t,e,"ReduceLogSumSquare",()=>["float t; value = 0.0;","t = _A(inputIdx); value += t * t;",""])},7019:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.isReshapeCheap=n.processDims3D=n.createPackedReshape3DProgramInfoLoader=void 0;const l=o(2517),c=o(5060),f=o(2039),a=o(2827);n.createPackedReshape3DProgramInfoLoader=(h,p,u)=>{const s=(t=>({name:"Reshape (packed)",inputTypes:[f.TextureType.packed],inputNames:["A"],cacheHint:`${t}`}))(u);return Object.assign(Object.assign({},s),{get:()=>((t,e,r,i)=>{const d=e.dims,g=i;let m="";for(let v=0;v<4;v++){let w="";switch(v){case 0:w="outputCoords = rc;";break;case 1:w="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:w="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:w="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}m+=`
        ${w}
        ${v>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[${v}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims);

        ${v>0?"}":""}
      `}const b=(0,c.getGlsl)(t.session.backend.glContext.version),_=`
      ${function(v){const w=l.ShapeUtil.computeStrides(v),S=["b","r","c"],A="index";return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${w.map((O,x)=>`int ${S[x]} = ${A} / ${O}; ${x===w.length-1?`int ${S[x+1]} = ${A} - ${S[x]} * ${O}`:`index -= ${S[x]} * ${O}`};`).join("")}
      return ivec3(b, r, c);
    }
  `}(d)}
      ${function(v){const w=l.ShapeUtil.computeStrides(v);return`
  int getFlattenedIndex(ivec3 coords) {
    // reverse y, z order
    return coords.x * ${w[0]} + coords.z * ${w[1]} + coords.y;
  }
`}(g)}
      ${(0,a.unpackFromChannel)()}

      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0.0);

        ivec3 outputCoords;
        int rows = ${g[2]};
        int cols = ${g[1]};

        ${m}
        ${b.output} = result;
      }
    `;return Object.assign(Object.assign({},r),{output:{dims:g,type:e.type,textureType:f.TextureType.packed},shaderSource:_,hasMain:!0})})(h,p,s,u)})},n.processDims3D=function(h){if(h.length===0)return[1,1,1];let p=1;for(let u=0;u<h.length-2;++u)p*=h[u];return[p,h.length>1?h[h.length-2]:1,h[h.length-1]]},n.isReshapeCheap=function(h,p){let u=!1;return u=h.length===0||p.length===0||(h.length<2||p.length<2?h[h.length-1]===p[p.length-1]:h[h.length-1]===p[p.length-1]&&h[h.length-2]===p[p.length-2]),u}},718:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.reshape=void 0;const l=o(2517);n.reshape=(c,f)=>{const a=l.ShapeUtil.calculateReshapedDims(f[0].dims,f[1].integerData);return c.session.pack?[c.reshapePacked(f[0],a)]:[c.reshapeUnpacked(f[0],a)]}},2268:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseResizeAttributesV11=n.parseResizeAttributesV10=n.resize=void 0;const l=o(5060),c=o(2039),f=o(9390),a=o(2827),h=o(9793),p={name:"Resize",inputNames:["A"],inputTypes:[c.TextureType.packed]};n.resize=(r,i,d)=>((0,h.validateInputs)(i,d),[r.run(Object.assign(Object.assign({},p),{cacheHint:d.cacheKey,get:()=>u(r,i,d)}),i)]),n.parseResizeAttributesV10=r=>(0,h.parseUpsampleAttributes)(r,10),n.parseResizeAttributesV11=r=>(0,h.parseUpsampleAttributes)(r,11);const u=(r,i,d)=>{const g=(0,l.getGlsl)(r.session.backend.glContext.version),[m,b]=s(i,d);if(m.every(N=>N===1)&&d.coordinateTransformMode!=="tf_crop_and_resize")return Object.assign(Object.assign({},p),{output:{dims:b,type:i[0].type,textureType:c.TextureType.packed},hasMain:!0,shaderSource:`void main() {
                    vec4 v = ${g.texture2D}(X, TexCoords);
                    ${g.output} = v;
                }`});const _=b.length;if(_<2)throw new Error(`output dimension should be at least 2, but got ${_}`);const v=b[_-2],w=b[_-1],S=i[0].dims;if(_!==S.length)throw new Error(`output dimension should match input ${S.length}, but got ${_}`);const A=S[_-2],O=S[_-1],x=m[_-2],I=m[_-1];let $="";if(d.mode!=="linear")throw new Error(`resize (packed) does not support mode: '${d.mode}'`);switch(d.coordinateTransformMode){case"asymmetric":$=`
                    vec4 getSourceFracIndex(ivec4 coords) {
                        return vec4(coords) / scaleWHWH;
                    }
                `;break;case"half_pixel":$=`
                    vec4 getSourceFracIndex(ivec4 coords) {
                        return (vec4(coords) + 0.5) / scaleWHWH - 0.5;
                    }
                `;break;case"pytorch_half_pixel":$=`
                    vec4 getSourceFracIndex(ivec4 coords) {
                        vec4 fcoords = vec4(coords);
                        return vec4(
                            ${w}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0,
                            ${v}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0,
                            ${w}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0,
                            ${v}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0
                          );
                    }
                `;break;case"align_corners":$=`
                    vec4 getSourceFracIndex(ivec4 coords) {
                        vec4 resized = vec4(${w}.0 - 1.0, ${v}.0 - 1.0, ${w}.0 - 1.0,
                            ${v}.0 - 1.0);
                        vec4 original = vec4(${O}.0 - 1.0, ${A}.0 - 1.0, ${O}.0 - 1.0,
                            ${A}.0 - 1.0);
                        vec4 new_scale = original / resized;
                        return vec4(coords) * new_scale;
                    }
                `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode:                                 '${d.coordinateTransformMode}'`)}const B=(0,f.getCoordsDataType)(_),L=`
            const vec2 inputWH = vec2(${A}.0, ${O}.0);
            const vec4 scaleWHWH = vec4(float(${x}), float(${I}), float(${x}), float(${I}));
            ${(0,a.unpackFromChannel)()}
            ${$}
            float getAValue(int x10, int r, int c, int d) {
                return getChannel(getA(x10, r, c, d), vec2(c, d));
            }
            void main() {
                ${B} 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 < ${v-1};
                bool hasNextCol = rc.z < ${w-1};

                // pack x00, x01, x10, x11's top-left corner into one vec4 structure
                vec4 topLeft = vec4(
                    getAValue(batch, depth, x00.x, x00.y),
                    hasNextCol ? getAValue(batch, depth, x01.x, x01.y) : 0.0,
                    hasNextRow ? getAValue(batch, depth, x10.x, x10.y) : 0.0,
                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.y) : 0.0);

                // pack x00, x01, x10, x11's top-right corner into one vec4 structure
                vec4 topRight = vec4(
                    getAValue(batch, depth, x00.x, x00.w),
                    hasNextCol ? getAValue(batch, depth, x01.x, x01.w) : 0.0,
                    hasNextRow ? getAValue(batch, depth, x10.x, x10.w) : 0.0,
                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.w) : 0.0);

                // pack x00, x01, x10, x11's bottom-left corner into one vec4 structure
                vec4 bottomLeft = vec4(
                    getAValue(batch, depth, x00.z, x00.y),
                    hasNextCol ? getAValue(batch, depth, x01.z, x01.y) : 0.0,
                    hasNextRow ? getAValue(batch, depth, x10.z, x10.y) : 0.0,
                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.y) : 0.0);

                // pack x00, x01, x10, x11's bottom-right corner into one vec4 structure
                vec4 bottomRight = vec4(
                    getAValue(batch, depth, x00.z, x00.w),
                    hasNextCol ? getAValue(batch, depth, x01.z, x01.w) : 0.0,
                    hasNextRow ? getAValue(batch, depth, x10.z, x10.w) : 0.0,
                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.w) : 0.0);

                // calculate the interpolation fraction on u and v direction
                vec4 frac = vec4(sourceFrac) - floor(sourceFrac);
                vec4 clampFrac = clamp(frac, vec4(0.0), vec4(1.0));

                vec4 top = mix(topLeft, topRight, clampFrac.ywyw);
                vec4 bottom = mix(bottomLeft, bottomRight, clampFrac.ywyw);
                vec4 newValue = mix(top, bottom, clampFrac.xxzz);

                ${g.output} = vec4(newValue);
            }
        `;return Object.assign(Object.assign({},p),{output:{dims:b,type:i[0].type,textureType:c.TextureType.packed},hasMain:!0,shaderSource:L})},s=(r,i)=>{const d=r[0].dims;let g,m=i.scales;if(m.length===0){const _=r[i.scalesInputIdx];if(_&&_.size!==0){if(r[i.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");m=t(_,i.mode,i.isResize)}else{const v=r[i.sizesInputIdx];if(!v||v.size===0)throw new Error("Either scales or sizes MUST be provided as input.");g=Array.from(v.integerData),m=e(g,d,i.mode,i.isResize)}}else if(r[i.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");const b=g||d.map((_,v)=>Math.floor(_*m[v]));return[m,b]},t=(r,i,d)=>{const g=Array.from(r.floatData);return(0,h.scalesValidation)(g,i,d),g},e=(r,i,d,g)=>{const m=i.length,b=new Array(m);for(let _=0,v=m;_<v;_++)if(i[_]===0){if(r[_]!==0)throw new Error("Input dim is zero but required output dim is non-zero.");b[_]=1}else b[_]=r[_]/i[_];return(0,h.scalesValidation)(b,d,g),b}},8117:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.shape=void 0;const l=o(9162);n.shape=(f,a)=>(c(a),[new l.Tensor([a[0].dims.length],"int32",void 0,void 0,new Int32Array(a[0].dims))]);const c=f=>{if(!f||f.length!==1)throw new Error("Shape requires 1 input.")}},2278:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.sliceV10=n.parseSliceAttributes=n.slice=void 0;const l=o(246),c=o(782),f=o(2517),a=o(2039),h={name:"Slice",inputNames:["A"],inputTypes:[a.TextureType.unpacked]};n.slice=(e,r,i)=>(u(r),[e.run(Object.assign(Object.assign({},h),{cacheHint:i.cacheKey,get:()=>p(e,r[0],i)}),r)]),n.parseSliceAttributes=e=>{const r=e.attributes.getInts("starts"),i=e.attributes.getInts("ends"),d=e.attributes.getInts("axes",[]);return(0,l.createAttributeWithCacheKey)({starts:r,ends:i,axes:d})};const p=(e,r,i)=>{const d=i.axes.length===0?r.dims.slice(0).map((S,A)=>A):i.axes,g=f.ShapeUtil.normalizeAxes(d,r.dims.length),m=i.starts.map((S,A)=>S>r.dims[g[A]]-1?r.dims[g[A]]:f.ShapeUtil.normalizeAxis(S,r.dims[g[A]])),b=i.ends.map((S,A)=>S>r.dims[g[A]]-1?r.dims[g[A]]:f.ShapeUtil.normalizeAxis(S,r.dims[g[A]])),_=r.dims.slice(),v=[];for(let S=0;S<g.length;S++)_[g[S]]=b[S]-m[S],m[S]>0&&v.push(`outputIdx[${g[S]}] += ${m[S]};`);const w=`
      float process(int outputIdx[${_.length}]) {
        ${v.join(`
      `)}
        return _A(outputIdx);
      }`;return Object.assign(Object.assign({},h),{output:{dims:_,type:r.type,textureType:a.TextureType.unpacked},shaderSource:w})},u=e=>{if(!e||e.length!==1)throw new Error("Slice requires 1 input.");if(c.NUMBER_TYPES.indexOf(e[0].type)===-1)throw new Error("Invalid input type.")};n.sliceV10=(e,r)=>{t(r);const i=s(e,r);return[e.run(Object.assign(Object.assign({},h),{cacheHint:i.cacheKey,get:()=>p(e,r[0],i)}),[r[0]])]};const s=(e,r)=>{if(!e.session.isInitializer(r[1].dataId)||!e.session.isInitializer(r[2].dataId)||r.length>=4&&!e.session.isInitializer(r[3].dataId)||r.length>=5&&!e.session.isInitializer(r[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(r.length>=5&&r[4].integerData.some(m=>m!==1))throw new Error("currently non-1 steps is not supported for Slice");const i=Array.from(r[1].integerData),d=Array.from(r[2].integerData),g=r.length>=4?Array.from(r[3].integerData):[];return{starts:i,ends:d,axes:g,cacheKey:`${g};${i};${d}`}},t=e=>{if(!e||e.length<3||e.length>5)throw new Error("Invalid input number.");if(e[1].type!=="int32"||e[1].dims.length!==1)throw new Error("Invalid input type.");if(e[2].type!=="int32"||e[2].dims.length!==1)throw new Error("Invalid input type.");if(e.length>=4&&(e[3].type!=="int32"||e[3].dims.length!==1))throw new Error("Invalid input type.");if(e.length>=5&&(e[4].type!=="int32"||e[4].dims.length!==1))throw new Error("Invalid input type.")}},5524:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.softmaxV13=n.parseSoftmaxAttributesV13=n.parseSoftmaxAttributes=n.softmax=void 0;const l=o(246),c=o(2517),f=o(5060),a=o(2039),h=o(3738),p={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[a.TextureType.unpacked]},u={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked]},s={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[a.TextureType.unpacked,a.TextureType.unpacked,a.TextureType.unpacked]};n.softmax=(g,m,b)=>{d(m);const _=m[0].dims.slice(),v=c.ShapeUtil.normalizeAxis(b.axis,_.length),w=c.ShapeUtil.sizeToDimension(_,v),S=c.ShapeUtil.sizeFromDimension(_,v);return t(g,m,b,w,S)},n.parseSoftmaxAttributes=g=>(0,l.createAttributeWithCacheKey)({axis:g.attributes.getInt("axis",1)}),n.parseSoftmaxAttributesV13=g=>(0,l.createAttributeWithCacheKey)({axis:g.attributes.getInt("axis",-1)}),n.softmaxV13=(g,m,b)=>{d(m);const _=m[0].dims.slice(),v=c.ShapeUtil.normalizeAxis(b.axis,_.length),w=_.length,S=v!==w-1,A=[];let O,x=[],I=[];S&&(x=Array.from({length:w}).map((N,H)=>H),x[v]=w-1,x[w-1]=v,x.map(N=>A.push(_[N])),O=(0,l.createAttributeWithCacheKey)({perm:x}),I=(0,h.transpose)(g,m,O));const $=S?c.ShapeUtil.sizeToDimension(A,w-1):c.ShapeUtil.sizeToDimension(_,w-1),B=S?c.ShapeUtil.sizeFromDimension(A,w-1):c.ShapeUtil.sizeFromDimension(_,w-1),L=t(g,S?I:m,b,$,B);return S?(0,h.transpose)(g,L,O):L};const t=(g,m,b,_,v)=>{const w=e(g,m[0],_,v,[_]),S=g.run(Object.assign(Object.assign({},p),{cacheHint:b.cacheKey,get:()=>w}),m),A=r(g,m[0],_,v,w.output.dims,[_]),O=g.run(Object.assign(Object.assign({},u),{cacheHint:b.cacheKey,get:()=>A}),[m[0],S]),x=i(g,m[0],_,v,w.output.dims,A.output.dims);return[g.run(Object.assign(Object.assign({},s),{cacheHint:b.cacheKey,get:()=>x}),[m[0],S,O])]},e=(g,m,b,_,v)=>{const[w,S]=g.calculateTextureWidthAndHeight(m.dims,a.TextureType.unpacked),A=v.length;if(b<1||_<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(v.length!==1)throw new Error("Dimensionality of the output should be 1");if(v[0]!==b)throw new Error("Shape of the output should be equal to logical row count");const O=(0,f.getGlsl)(g.session.backend.glContext.version),x=`
      float process(int[${A}] indices) {
        int logical_row_start_offset = indices[0] * ${_};

        float max = getColorAsFloat(${O.texture2D}(A, offsetToCoords(logical_row_start_offset, ${w},
        ${S} )));
        for(int i=1; i<${_}; ++i)
        {
          float current = getColorAsFloat(${O.texture2D}(A, offsetToCoords(logical_row_start_offset + i,
            ${w}, ${S})));
          if(current > max)
          max = current;
        }

        return max;
      }`;return Object.assign(Object.assign({},p),{output:{dims:v,type:m.type,textureType:a.TextureType.unpacked},shaderSource:x})},r=(g,m,b,_,v,w)=>{const[S,A]=g.calculateTextureWidthAndHeight(m.dims,a.TextureType.unpacked),O=w.length;if(b<1||_<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");if(v.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(v[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const x=`
      float process(int[${O}] indices) {
        int logical_row_start_offset = indices[0] * ${_};

        float norm_factor = 0.0;
        float max = _Max(indices);
        for(int i=0; i<${_}; ++i)
        {
          norm_factor += exp(getColorAsFloat(${(0,f.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({},u),{output:{dims:w,type:m.type,textureType:a.TextureType.unpacked},shaderSource:x})},i=(g,m,b,_,v,w)=>{const[S,A]=g.calculateTextureWidthAndHeight(m.dims,a.TextureType.unpacked),O=m.dims.length;if(b<1||_<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(v.length!==1||w.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(v[0]!==b||w[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const x=`
      float process(int[${O}] indices) {

      // get offset of current logical tensor index from the 2-D texture coordinates (TexCoords)
      int offset = coordsToOffset(TexCoords, ${S}, ${A});

      //determine the logical row for this index
      int logical_row_index[1];
      logical_row_index[0] = offset / ${_};

      float norm_factor = _Norm(logical_row_index);

      // avoid possible division by 0
      // if norm_facor is 0, all elements are zero
      // if so, return 0
      if(norm_factor == 0.0)
        return 0.0;

      return exp(_A(indices) - _Max(logical_row_index)) / norm_factor;
    }`;return Object.assign(Object.assign({},s),{output:{dims:m.dims,type:m.type,textureType:a.TextureType.unpacked},shaderSource:x})},d=g=>{if(!g||g.length!==1)throw new Error("Softmax requires 1 input.");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type")}},5975:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSplitAttributes=n.split=void 0;const l=o(246),c=o(2517),f=o(2039),a={name:"Split",inputNames:["A"],inputTypes:[f.TextureType.unpacked]};n.split=(s,t,e)=>{u(t);const r=c.ShapeUtil.normalizeAxis(e.axis,t[0].dims.length),i=h(s,t,r,e),d=[];for(let g=0;g<i;++g)d.push(s.run(Object.assign(Object.assign({},a),{cacheHint:`${e.cacheKey};${g}`,get:()=>p(s,t[0],e,r,g)}),t));return d},n.parseSplitAttributes=s=>{const t=s.attributes.getInt("axis",0),e=s.attributes.getInts("split",[]),r=s.outputs.length;return(0,l.createAttributeWithCacheKey)({axis:t,split:e,numOutputs:r})};const h=(s,t,e,r)=>{const[,i]=c.SplitUtil.splitShape(t[0].dims,e,r.split,r.numOutputs);return i.length},p=(s,t,e,r,i)=>{const[d,g]=c.SplitUtil.splitShape(t.dims,r,e.split,e.numOutputs),m=g[i],b=d[i],_=`
      float process(int indices[${b.length}]) {
        indices[${r}] += ${m};
        return _A(indices);
      }
    `;return Object.assign(Object.assign({},a),{cacheHint:`${e.cacheKey}:${i}`,output:{dims:b,type:t.type,textureType:f.TextureType.unpacked},shaderSource:_})},u=s=>{if(!s||s.length!==1)throw new Error("Split requires one input.");if(s[0].type!=="int8"&&s[0].type!=="uint8"&&s[0].type!=="int16"&&s[0].type!=="uint16"&&s[0].type!=="int32"&&s[0].type!=="uint32"&&s[0].type!=="float32"&&s[0].type!=="float64"&&s[0].type!=="bool")throw new Error("Invalid input type.")}},3933:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSqueezeAttributes=n.squeezeV13=n.squeeze=void 0;const l=o(2517);n.squeeze=(a,h,p)=>{c(h);const u=l.ShapeUtil.squeezeShape(h[0].dims,p);return[a.reshapeUnpacked(h[0],u)]},n.squeezeV13=(a,h)=>(f(h),(0,n.squeeze)(a,[h[0]],Array.from(h[1].integerData))),n.parseSqueezeAttributes=a=>a.attributes.getInts("axes");const c=a=>{if(!a||a.length!==1)throw new Error("Squeeze requires 1 input.");if(a[0].type==="string")throw new Error("invalid input tensor types.")},f=a=>{if(!a||a.length!==2)throw new Error("Squeeze requires 2 inputs.");if(a[1].type!=="int32")throw new Error("Invalid input type.")}},6558:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.sum=void 0;const l=o(5060),c=o(2039);n.sum=(h,p)=>{a(p);const u={name:"Sum",inputNames:p.map((s,t)=>`X${t}`),inputTypes:new Array(p.length).fill(c.TextureType.unpacked)};return[h.run(Object.assign(Object.assign({},u),{get:()=>f(h,p,u)}),p)]};const f=(h,p,u)=>{const s=(0,l.getGlsl)(h.session.backend.glContext.version),t=p[0].dims.slice(),e=`
      void main() {
        vec4 result = ${p.map((r,i)=>`${s.texture2D}(X${i},TexCoords)`).join(" + ")};
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      }
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      float process(int outputIdx[${r}]) {
        int inputIdx[${r}];
        ${e.join(`
`)}
        return _A(inputIdx);
      }
    `;return Object.assign(Object.assign({},u),{output:{dims:t,type:p[0].type,textureType:c.TextureType.unpacked},shaderSource:i})},a=h=>{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(l.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:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseTransposeAttributes=n.transpose=void 0;const l=o(246),c=o(2517),f=o(2039),a={name:"Transpose",inputNames:["A"],inputTypes:[f.TextureType.unpacked]};n.transpose=(e,r,i)=>(t(r),[e.run(Object.assign(Object.assign({},a),{cacheHint:i.cacheKey,get:()=>h(e,r[0],i.perm)}),r)]),n.parseTransposeAttributes=e=>(0,l.createAttributeWithCacheKey)({perm:e.attributes.getInts("perm",[])});const h=(e,r,i)=>{const d=r.dims;i=p(d,i);const g=u(d,i),m=d.length,b=`
      ${s("perm",i,m)}
      float process(int indices[${m}]) {
        int a[${m}];
        perm(a, indices);
        return _A(a);
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`)},t=e=>{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:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.encodeAsUint8=void 0;const l=o(5060),c=o(2039);n.encodeAsUint8=(f,a)=>{const h=a.shape,p=(0,l.getGlsl)(f.session.backend.glContext.version),u=`
    const float FLOAT_MAX = 1.70141184e38;
    const float FLOAT_MIN = 1.17549435e-38;

    bool isNaN(float val) {
      return (val < 1.0 || 0.0 < val || val == 0.0) ? false : true;
    }

    highp vec4 encodeAsUint8(highp float v) {
      if (isNaN(v)) {
        return vec4(255, 255, 255, 255);
      }

      highp float av = abs(v);

      if(av < FLOAT_MIN) {
        return vec4(0.0, 0.0, 0.0, 0.0);
      } else if(v > FLOAT_MAX) {
        return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
      } else if(v < -FLOAT_MAX) {
        return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
      }

      highp vec4 c = vec4(0,0,0,0);

      highp float e = floor(log2(av));
      highp float m = exp2(fract(log2(av))) - 1.0;

      c[2] = floor(128.0 * m);
      m -= c[2] / 128.0;
      c[1] = floor(32768.0 * m);
      m -= c[1] / 32768.0;
      c[0] = floor(8388608.0 * m);

      highp float ebias = e + 127.0;
      c[3] = floor(ebias / 2.0);
      ebias -= c[3] * 2.0;
      c[2] += floor(ebias) * 128.0;

      c[3] += 128.0 * step(0.0, -v);

      return c / 255.0;
    }

    void main() {
      float value = ${p.texture2D}(X,TexCoords).r;
      ${p.output} = encodeAsUint8(value);
    }`,s={name:"Uint8Encode",inputTypes:[c.TextureType.unpacked],inputNames:["X"],output:{dims:h,type:a.tensor.type,textureType:c.TextureType.downloadUint8AsFloat},shaderSource:u,hasMain:!0};return f.executeProgram(s,[a.tensor])}},4909:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.tanh=n.tan=n.sqrt=n.sin=n.sigmoid=n.relu=n.not=n.neg=n.log=n.parseLeakyReluAttributes=n.leakyRelu=n.identity=n.floor=n.exp=n.parseEluAttributes=n.elu=n.cos=n.ceil=n.clipV11=n.parseClipAttributes=n.clip=n.atan=n.asin=n.acos=n.abs=n.glslTanh=n.glslTan=n.glslSqrt=n.glslSigmoid=n.glslRelu=n.glslSin=n.glslNot=n.glslNeg=n.glslLog=n.glslLeakyRelu=n.glslIdentity=n.glslClip=n.glslFloor=n.glslExp=n.glslElu=n.glslCos=n.glslCeil=n.glslAtan=n.glslAsin=n.glslAcos=n.glslAbs=void 0;const l=o(246),c=o(2517),f=o(8520),a=o(5060),h=o(2039);function p(){return L("abs")}function u(){return L("acos")}function s(){return L("asin")}function t(){return L("atan")}function e(){return L("ceil")}function r(){return L("cos")}function i(M){const j="elu";return{body:`
  const float alpha = float(${M});

  float ${j}_(float a) {
    return a >= 0.0 ? a: (exp(a) - 1.0) * alpha;
  }
  vec4 ${j}_(vec4 v) {
    return vec4(${j}_(v.x), ${j}_(v.y), ${j}_(v.z), ${j}_(v.w));
  }
  `,name:j,type:f.FunctionType.ValueBased}}function d(){return L("exp")}function g(){return L("floor")}function m(M,j){const Z="clip";return{body:`
  const float min = float(${M});
  const float max = float(${j});

  float ${Z}_(float a) {
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  }
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  float ${M}_(float a) {
    return a;
  }
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    return v;
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  const float alpha = float(${M});

  float ${j}_(float a) {
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  }
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  }
  `,name:j,type:f.FunctionType.ValueBased}}function v(){return L("log")}function w(){const M="neg";return{body:`
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    return -v;
  }
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    return float( ! bool(a) );
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    return vec4(!bool(v.x), !bool(v.y), !bool(v.z), !bool(v.w));
  }
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  }
  `,name:M,type:f.FunctionType.ValueBased}}function I(){return L("sqrt")}function $(){return L("tan")}function B(){const M="tanh";return{body:`
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  vec4 ${M}_(vec4 v) {
    v = clamp(v, -10., 10.);
    v = exp(2.*v);
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  }
  `,name:M,type:f.FunctionType.ValueBased}}function L(M){return{body:`
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  }
  `,name:M,type:f.FunctionType.ValueBased}}n.glslAbs=p,n.glslAcos=u,n.glslAsin=s,n.glslAtan=t,n.glslCeil=e,n.glslCos=r,n.glslElu=i,n.glslExp=d,n.glslFloor=g,n.glslClip=m,n.glslIdentity=b,n.glslLeakyRelu=_,n.glslLog=v,n.glslNeg=w,n.glslNot=S,n.glslSin=A,n.glslRelu=O,n.glslSigmoid=x,n.glslSqrt=I,n.glslTan=$,n.glslTanh=B;const N=(M,j,Z,X)=>{const Q=M.session.pack?h.TextureType.packed:h.TextureType.unpacked,ee={name:Z.name,inputTypes:[Q],inputNames:["A"],cacheHint:X};return Object.assign(Object.assign({},ee),{get:()=>((ue,Ae,xe,oe)=>{const we=ue.session.pack?h.TextureType.packed:h.TextureType.unpacked,ye=(0,a.getGlsl)(ue.session.backend.glContext.version);return Object.assign(Object.assign({},Ae),{output:{dims:xe.dims,type:xe.type,textureType:we},shaderSource:`
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     void main() {
       vec4 v = ${ye.texture2D}(A, TexCoords);
       v = ${oe.name}_(v);
       ${ye.output} = v;
     }
     `,hasMain:!0})})(M,ee,j,Z)})};n.abs=(M,j)=>[M.run(N(M,j[0],p()),j)],n.acos=(M,j)=>[M.run(N(M,j[0],u()),j)],n.asin=(M,j)=>[M.run(N(M,j[0],s()),j)],n.atan=(M,j)=>[M.run(N(M,j[0],t()),j)],n.clip=(M,j,Z)=>[M.run(N(M,j[0],m(Z.min,Z.max),Z.cacheKey),j)],n.parseClipAttributes=M=>(0,l.createAttributeWithCacheKey)({min:M.attributes.getFloat("min",c.MIN_CLIP),max:M.attributes.getFloat("max",c.MAX_CLIP)}),n.clipV11=(M,j)=>{const Z=H(M,j);return(0,n.clip)(M,[j[0]],Z)};const H=(M,j)=>{if(j.length>=3&&(!M.session.isInitializer(j[1].dataId)||!M.session.isInitializer(j[2].dataId)))throw new Error("dynamic clip attributes are not allowed");const Z=j.length>=3?j[1].numberData[0]:c.MIN_CLIP,X=j.length>=3?j[2].numberData[0]:c.MAX_CLIP;return(0,l.createAttributeWithCacheKey)({min:Z,max:X})};n.ceil=(M,j)=>[M.run(N(M,j[0],e()),j)],n.cos=(M,j)=>[M.run(N(M,j[0],r()),j)],n.elu=(M,j,Z)=>[M.run(N(M,j[0],i(Z.alpha),Z.cacheKey),j)],n.parseEluAttributes=M=>(0,l.createAttributeWithCacheKey)({alpha:M.attributes.getFloat("alpha",1)}),n.exp=(M,j)=>[M.run(N(M,j[0],d()),j)],n.floor=(M,j)=>[M.run(N(M,j[0],g()),j)],n.identity=(M,j)=>[M.run(N(M,j[0],b()),j)],n.leakyRelu=(M,j,Z)=>[M.run(N(M,j[0],_(Z.alpha),Z.cacheKey),j)],n.parseLeakyReluAttributes=M=>(0,l.createAttributeWithCacheKey)({alpha:M.attributes.getFloat("alpha",.01)}),n.log=(M,j)=>[M.run(N(M,j[0],v()),j)],n.neg=(M,j)=>[M.run(N(M,j[0],w()),j)],n.not=(M,j)=>[M.run(N(M,j[0],S()),j)],n.relu=(M,j)=>[M.run(N(M,j[0],O()),j)],n.sigmoid=(M,j)=>[M.run(N(M,j[0],x()),j)],n.sin=(M,j)=>[M.run(N(M,j[0],A()),j)],n.sqrt=(M,j)=>[M.run(N(M,j[0],I()),j)],n.tan=(M,j)=>[M.run(N(M,j[0],$()),j)],n.tanh=(M,j)=>[M.run(N(M,j[0],B()),j)]},5611:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createUnpackProgramInfoLoader=n.createUnpackProgramInfo=void 0;const l=o(5060),c=o(2039),f=o(9390),a=o(2827),h={name:"unpack",inputNames:["A"],inputTypes:[c.TextureType.packed]};n.createUnpackProgramInfo=(p,u)=>{const s=u.dims.length,t=(0,a.getChannels)("rc",s),e=t.slice(-2),r=(0,f.getCoordsDataType)(s),i=(0,a.unpackFromChannel)(),d=u.dims.length===0?"":function(b,_){if(b===1)return"rc";let v="";for(let w=0;w<b;w++)v+=_[w],w<b-1&&(v+=",");return v}(s,t),g=s<=1?"rc":`vec2(${e.join(",")})`,m=`
    ${i}
    void main() {
      ${r} rc = getOutputCoords();

       // Sample the texture with the coords to get the rgba channel value.
       vec4 packedInput = getA(${d});

       ${(0,l.getGlsl)(p.session.backend.glContext.version).output} = vec4(getChannel(packedInput, ${g}), 0, 0, 0);
     }
   `;return Object.assign(Object.assign({},h),{hasMain:!0,output:{dims:u.dims,type:u.type,textureType:c.TextureType.unpacked},shaderSource:m})},n.createUnpackProgramInfoLoader=(p,u)=>Object.assign(Object.assign({},h),{get:()=>(0,n.createUnpackProgramInfo)(p,u)})},8428:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseUnsqueezeAttributes=n.unsqueezeV13=n.unsqueeze=void 0;const l=o(2517);n.unsqueeze=(a,h,p)=>{c(h);const u=l.ShapeUtil.unsqueezeShape(h[0].dims,p);return[a.reshapeUnpacked(h[0],u)]},n.unsqueezeV13=(a,h)=>(f(h),(0,n.unsqueeze)(a,[h[0]],Array.from(h[1].integerData))),n.parseUnsqueezeAttributes=a=>a.attributes.getInts("axes");const c=a=>{if(!a||a.length!==1)throw new Error("Unsqueeze requires 1 input.");if(a[0].type==="string")throw new Error("invalid input tensor types.")},f=a=>{if(!a||a.length!==2)throw new Error("Unsqueeze requires 2 inputs.");if(a[1].type!=="int32")throw new Error("Invalid input type.")}},9793:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.scalesValidation=n.validateInputs=n.parseUpsampleAttributes=n.parseUpsampleAttributesV9=n.parseUpsampleAttributesV7=n.upsample=void 0;const l=o(246),c=o(5060),f=o(2039),a={name:"Upsample",inputNames:["X"],inputTypes:[f.TextureType.unpacked]};n.upsample=(p,u,s)=>((0,n.validateInputs)(u,s),[p.run(Object.assign(Object.assign({},a),{cacheHint:s.cacheKey,get:()=>h(p,u,s)}),u)]),n.parseUpsampleAttributesV7=p=>(0,n.parseUpsampleAttributes)(p,7),n.parseUpsampleAttributesV9=p=>(0,n.parseUpsampleAttributes)(p,9),n.parseUpsampleAttributes=(p,u)=>{const s=u>=10,t=p.attributes.getString("mode","nearest");if(t!=="nearest"&&t!=="linear"&&(u<11||t!=="cubic"))throw new Error(`unrecognized mode: ${t}`);let e=[];u<9&&(e=p.attributes.getFloats("scales"),(0,n.scalesValidation)(e,t,s));const r=p.attributes.getFloat("extrapolation_value",0),i=u>10?p.attributes.getString("coordinate_transformation_mode","half_pixel"):"asymmetric";if(["asymmetric","pytorch_half_pixel","tf_half_pixel_for_nn","align_corners","tf_crop_and_resize","half_pixel"].indexOf(i)===-1)throw new Error(`coordinate_transform_mode '${i}' is not supported`);const d=i==="tf_crop_and_resize",g=d,m=t==="nearest"&&u>=11?p.attributes.getString("nearest_mode","round_prefer_floor"):"";if(["round_prefer_floor","round_prefer_ceil","floor","ceil",""].indexOf(m)===-1)throw new Error(`nearest_mode '${m}' is not supported`);const b=p.attributes.getFloat("cubic_coeff_a",-.75),_=p.attributes.getInt("exclude_outside",0)!==0;if(_&&t!=="cubic")throw new Error("exclude_outside can be set to 1 only when mode is CUBIC.");const v=u<11||t==="nearest"&&i==="asymmetric"&&m==="floor";let w=0,S=0,A=0;return u>10?p.inputs.length>2?(w=1,S=2,A=3):(S=1,A=2):u===9&&(S=1),(0,l.createAttributeWithCacheKey)({opset:u,isResize:s,mode:t,scales:e,extrapolationValue:r,coordinateTransformMode:i,useExtrapolation:g,needRoiInput:d,nearestMode:m,cubicCoefficientA:b,excludeOutside:_,useNearest2xOptimization:v,roiInputIdx:w,scalesInputIdx:S,sizesInputIdx:A})};const h=(p,u,s)=>{const t=(0,c.getGlsl)(p.session.backend.glContext.version),[e,r]=p.calculateTextureWidthAndHeight(u[0].dims,f.TextureType.unpacked),i=u[0].dims.map((A,O)=>Math.floor(A*s.scales[O])),[d,g]=p.calculateTextureWidthAndHeight(i,f.TextureType.unpacked),m=i.length,b=new Array(m),_=new Array(m);let v=`
      int output_pitches[${m}];
      int input_pitches[${m}];
      `;for(let A=m-1;A>=0;A--)b[A]=A===m-1?1:b[A+1]*i[A+1],_[A]=A===m-1?1:_[A+1]*u[0].dims[A+1],v+=`
        output_pitches[${A}] = ${b[A]};
        input_pitches[${A}] = ${_[A]};
        `;const w=`
      float getInputFloat(int index) {
        vec2 coords = offsetToCoords(index, ${e}, ${r});
        float value = getColorAsFloat(${t.texture2D}(X, coords));
        return value;
      }
      `,S=s.mode==="nearest"?`
    ${w}
    float process(int indices[${m}]) {
      int input_index = 0;
      int output_index = coordsToOffset(TexCoords, ${d}, ${g});

      ${v}

      int d, m;
      for (int dim = 0; dim < ${m}; ++dim) {
        d = output_index / output_pitches[dim];
        m = output_index - d * output_pitches[dim];
        output_index = m;

        if (scales[dim] != 1 && d > 0) {
          int d2 = d / scales[dim];
          m = d - d2 * scales[dim];
          d = d2;
        }
        input_index += input_pitches[dim] * d;
      }

      return getInputFloat(input_index);
    }`:m===4?`
    ${w}
    float process(int indices[4]) {
      int input_index = 0;
      int output_index = coordsToOffset(TexCoords, ${d}, ${g});

      ${v}

      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 == (${u[0].dims[2]} - 1)) {
        // It's the end in dimension 2
        x01 = x00;
        end_of_dim2 = true;
      } else {
        x01 = getInputFloat(input_index + input_pitches[2]);
      }

      if (index_of_input_dim3 == (input_pitches[2] - 1)) {
        // It's the end in dimension 3
        x10 = x00;
        x11 = x01;
      }
      else {
        x10 = getInputFloat(input_index + 1);
        x11 = end_of_dim2 ? x10 : getInputFloat(input_index + input_pitches[2] + 1);
      }

      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[2]);
      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[2]);
      return y0 + float(x_offset) * (y1 - y0) / float(scales[3]);
    }`:`
    ${w}
    float process(int indices[2]) {
      int input_index = 0;
      int output_index = coordsToOffset(TexCoords, ${d}, ${g});

      ${v}

      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 == (${u[0].dims[0]} - 1)) {
        // It's the end in dimension 0
        x01 = x00;
        end_of_dim0 = true;
      } else {
        x01 = getInputFloat(input_index + input_pitches[0]);
      }

      if (index_of_input_dim1 == (input_pitches[0] - 1)) {
        // It's the end in dimension 1
        x10 = x00;
        x11 = x01;
      }
      else {
        x10 = getInputFloat(input_index + 1);
        x11 = end_of_dim0 ? x10 : getInputFloat(input_index + input_pitches[0] + 1);
      }

      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[0]);
      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[0]);
      return y0 + float(x_offset) * (y1 - y0) / float(scales[1]);
    }`;return Object.assign(Object.assign({},a),{output:{dims:i,type:u[0].type,textureType:f.TextureType.unpacked},shaderSource:S,variables:[{name:"scales",type:"int",arrayLength:s.scales.length,data:s.scales.map(A=>Math.ceil(A))}]})};n.validateInputs=(p,u)=>{if(!p||u.opset<9&&p.length!==1||u.opset>=9&&u.opset<11&&p.length!==2||u.opset>=11&&p.length<2)throw new Error("invalid inputs.");if(u.scales.length>0&&p[0].dims.length!==u.scales.length)throw new Error("Invalid input shape.");if(p[0].type==="string")throw new Error("Invalid input tensor types.")},n.scalesValidation=(p,u,s)=>{if(s){for(const t of p)if(t<=0)throw new Error("Scale value should be greater than 0.")}else for(const t of p)if(t<1)throw new Error("Scale value should be greater than or equal to 1.");if(!(u!=="linear"&&u!=="cubic"||p.length===2||p.length===4&&p[0]===1&&p[1]===1))throw new Error(`'Linear' mode and 'Cubic' mode only support 2-D inputs ('Bilinear', 'Bicubic')         or 4-D inputs with the corresponding outermost 2 scale values being 1         in the ${s?"Resize":"Upsample"} opeartor.`)}},1958:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.ProgramManager=void 0;const l=o(1670),c=o(6231),f=o(8879),a=o(5060);n.ProgramManager=class{constructor(h,p,u){this.profiler=h,this.glContext=p,this.textureLayoutStrategy=u,this.repo=new Map,this.attributesBound=!1}getArtifact(h){return this.repo.get(h)}setArtifact(h,p){this.repo.set(h,p)}run(h,p,u){var s;this.profiler.event("op",`ProgramManager.run ${(s=h.programInfo.name)!==null&&s!==void 0?s:"unknown kernel"}`,()=>{var t;const e=this.glContext.gl,r=h.program;e.useProgram(r);try{this.bindOutput(u),this.attributesBound||this.bindAttributes(h.attribLocations),this.bindUniforms(h.uniformLocations,(t=h.programInfo.variables)!==null&&t!==void 0?t:[],p)}catch(i){throw c.Logger.error("ProgramManager",h.programInfo.shaderSource),i}this.profiler.event("backend","GlContext.draw()",()=>{this.glContext.draw()})},this.glContext)}dispose(){this.vertexShader&&this.glContext.deleteShader(this.vertexShader),this.repo.forEach(h=>this.glContext.deleteProgram(h.program))}build(h,p,u){return this.profiler.event("backend","ProgramManager.build",()=>{const s=new f.GlslPreprocessor(this.glContext,h,p,u),t=s.preprocess(),e=this.compile(t);return{programInfo:h,program:e,uniformLocations:this.getUniformLocations(e,s.context.programInfo.inputNames,s.context.programInfo.variables),attribLocations:this.getAttribLocations(e)}})}compile(h){if(!this.vertexShader){c.Logger.verbose("ProrgramManager","Compiling and caching Vertex shader for the first time");const s=(0,a.getVertexShaderSource)(this.glContext.version);this.vertexShader=this.glContext.compileShader(s,this.glContext.gl.VERTEX_SHADER)}l.env.debug&&c.Logger.verbose("ProrgramManager",`FragShader:
${h}
`);const p=this.glContext.compileShader(h,this.glContext.gl.FRAGMENT_SHADER),u=this.glContext.createProgram(this.vertexShader,p);return this.glContext.deleteShader(p),u}bindOutput(h){const p=h.width,u=h.height;c.Logger.verbose("ProrgramManager",`Binding output texture to Framebuffer: w/h=${p}/${u}, shape=${h.shape}, type=${h.tensor.type}`),this.glContext.attachFramebuffer(h.texture,p,u)}bindAttributes(h){const p=h.position,u=h.textureCoord;this.glContext.setVertexAttributes(p,u),this.attributesBound=!0}bindUniforms(h,p,u){var s;const t=this.glContext.gl;let e=0;for(const{name:r,type:i,location:d,arrayLength:g}of h){const m=(s=p.find(b=>b.name===r))===null||s===void 0?void 0:s.data;if(i!=="sampler2D"&&!m)throw new Error(`variable '${r}' does not have data defined in program info`);switch(i){case"sampler2D":this.bindTexture(u[e],d,e),e++;break;case"float":g?t.uniform1fv(d,m):t.uniform1f(d,m);break;case"int":g?t.uniform1iv(d,m):t.uniform1i(d,m);break;default:throw new Error(`Uniform not implemented: ${i}`)}}}bindTexture(h,p,u){this.glContext.bindTextureToUniform(h.texture,u,p)}getAttribLocations(h){return{position:this.getAttribLocation(h,"position"),textureCoord:this.getAttribLocation(h,"textureCoord")}}getUniformLocations(h,p,u){const s=[];if(p)for(const t of p)s.push({name:t,type:"sampler2D",location:this.getUniformLocation(h,t)});if(u)for(const t of u)s.push(Object.assign(Object.assign({},t),{location:this.getUniformLocation(h,t.name)}));return s}getUniformLocation(h,p){const u=this.glContext.gl.getUniformLocation(h,p);if(u===null)throw new Error(`Uniform ${p} not found.`);return u}getAttribLocation(h,p){return this.glContext.gl.getAttribLocation(h,p)}}},6416:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.WebGLSessionHandler=void 0;const l=o(6231),c=o(1047),f=o(8316),a=o(1640),h=o(1958),p=o(7859),u=o(5702);n.WebGLSessionHandler=class{constructor(s,t){this.backend=s,this.context=t,this.layoutStrategy=new p.PreferLogicalStrategy(s.glContext.maxTextureSize),this.programManager=new h.ProgramManager(this.context.profiler,s.glContext,this.layoutStrategy),this.textureManager=new u.TextureManager(s.glContext,this.layoutStrategy,this.context.profiler,{reuseTextures:s.textureCacheMode==="full"}),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new Map,this.pack=s.pack,this.pack2unpackMap=new Map,this.unpack2packMap=new Map}createInferenceHandler(){return new f.WebGLInferenceHandler(this)}onGraphInitialized(s){const t=s.getValues().filter(e=>e.from===-1&&e.tensor).map(e=>e.tensor.dataId);this.initializers=new Set(t)}isInitializer(s){return!!this.initializers&&this.initializers.has(s)}addInitializer(s){this.initializers.add(s)}getTextureData(s,t){return t?this.packedTextureDataCache.get(s):this.unpackedTextureDataCache.get(s)}setTextureData(s,t,e=!1){l.Logger.verbose("WebGLSessionHandler","Storing Texture data in cache"),e?this.packedTextureDataCache.set(s,t):this.unpackedTextureDataCache.set(s,t)}dispose(){this.programManager.dispose(),this.textureManager.clearActiveTextures(),this.packedTextureDataCache.forEach(s=>this.textureManager.releaseTexture(s,!0)),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache.forEach(s=>this.textureManager.releaseTexture(s,!0)),this.unpackedTextureDataCache=new Map}resolve(s,t,e){const r=(0,c.resolveOperator)(s,t,a.WEBGL_OP_RESOLVE_RULES);return{impl:r.opImpl,context:r.opInit?r.opInit(s,e):s}}}},7769:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Uint8DataEncoder=n.RGBAFloatDataEncoder=n.RedFloat32DataEncoder=void 0;const l=o(6231);n.RedFloat32DataEncoder=class{constructor(c,f=1){if(f===1)this.internalFormat=c.R32F,this.format=c.RED,this.textureType=c.FLOAT,this.channelSize=f;else{if(f!==4)throw new Error(`Invalid number of channels: ${f}`);this.internalFormat=c.RGBA32F,this.format=c.RGBA,this.textureType=c.FLOAT,this.channelSize=f}}encode(c,f){let a,h;return c.constructor!==Float32Array&&(l.Logger.warning("Encoder","data was not of type Float32; creating new Float32Array"),h=new Float32Array(c)),f*this.channelSize>c.length?(l.Logger.warning("Encoder","Source data too small. Allocating larger array"),h=c,a=this.allocate(f*this.channelSize),h.forEach((p,u)=>a[u]=p)):(h=c,a=h),a}allocate(c){return new Float32Array(4*c)}decode(c,f){return this.channelSize===1?c.filter((a,h)=>h%4==0).subarray(0,f):c.subarray(0,f)}},n.RGBAFloatDataEncoder=class{constructor(c,f=1,a){if(f!==1&&f!==4)throw new Error(`Invalid number of channels: ${f}`);this.internalFormat=c.RGBA,this.format=c.RGBA,this.channelSize=f,this.textureType=a||c.FLOAT}encode(c,f){let a=c;return this.channelSize===1&&(l.Logger.verbose("Encoder","Exploding into a larger array"),a=this.allocate(f),c.forEach((h,p)=>a[4*p]=h)),a}allocate(c){return new Float32Array(4*c)}decode(c,f){return this.channelSize===1?c.filter((a,h)=>h%4==0).subarray(0,f):c.subarray(0,f)}},n.Uint8DataEncoder=class{constructor(c,f=1){if(this.channelSize=4,f===1)this.internalFormat=c.ALPHA,this.format=c.ALPHA,this.textureType=c.UNSIGNED_BYTE,this.channelSize=f;else{if(f!==4)throw new Error(`Invalid number of channels: ${f}`);this.internalFormat=c.RGBA,this.format=c.RGBA,this.textureType=c.UNSIGNED_BYTE,this.channelSize=f}}encode(c,f){return new Uint8Array(c.buffer,c.byteOffset,c.byteLength)}allocate(c){return new Uint8Array(c*this.channelSize)}decode(c,f){if(c instanceof Uint8Array)return c.subarray(0,f);throw new Error(`Invalid array type: ${c.constructor}`)}}},7859:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.getBatchDim=n.sizeToSquarishShape=n.getRowsCols=n.sizeFromShape=n.isInt=n.parseAxisParam=n.squeezeShape=n.PreferLogicalStrategy=n.AlwaysKeepOriginalSizeStrategy=void 0;const l=o(6231),c=o(2517);function f(s,t){const e=[],r=[],i=t!=null&&Array.isArray(t)&&t.length===0,d=t==null||i?null:a(t,s).sort();let g=0;for(let m=0;m<s.length;++m){if(d!=null){if(d[g]===m&&s[m]!==1)throw new Error(`Can't squeeze axis ${m} since its dim '${s[m]}' is not 1`);(d[g]==null||d[g]>m)&&s[m]===1&&(e.push(s[m]),r.push(m)),d[g]<=m&&g++}s[m]!==1&&(e.push(s[m]),r.push(m))}return{newShape:e,keptDims:r}}function a(s,t){const e=t.length;return s=s==null?t.map((r,i)=>i):[].concat(s),(0,c.assert)(s.every(r=>r>=-e&&r<e),()=>`All values in axis param must be in range [-${e}, ${e}) but got axis ${s}`),(0,c.assert)(s.every(h),()=>`All values in axis param must be integers but got axis ${s}`),s.map(r=>r<0?e+r:r)}function h(s){return s%1==0}function p(s){if(s.length===0)return 1;let t=s[0];for(let e=1;e<s.length;e++)t*=s[e];return t}function u(s){const t=Math.ceil(Math.sqrt(s));return[t,Math.ceil(s/t)]}n.AlwaysKeepOriginalSizeStrategy=class{constructor(s){this.maxTextureSize=s}computeTextureWH(s,t){if(s.length===0)return[1,1];const e=this.maxTextureSize;if(t&&t.breakAxis!==void 0){const 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u=this._starter.slice(0),s=this.graph.getValues(),t=this.graph.getNodes();let e=0;for(;e<u.length;){const i=u[e++],d=this._ops[i],g=d.node.inputs.map(v=>this._values[v]);if(g.indexOf(void 0)!==-1)throw new Error(`unresolved input detected: op: ${d.node}`);const m=g;l.Logger.verbose("ExecPlan",`Runing op:${d.node.name} (${m.map((v,w)=>`'${d.node.inputs[w]}': ${v.type}[${v.dims.join(",")}]`).join(", ")})`);const b=await this.profiler.event("node",d.node.name,async()=>d.op.impl(h,m,d.op.context));if(b.length!==d.node.outputs.length)throw new Error("the size of output does not match model definition.");b.forEach((v,w)=>{const S=d.node.outputs[w];if(this._values[S])throw new Error(`output [${S}] already has value: op:${d.node.name}`);this._values[S]=v});const _=new Set;b.forEach((v,w)=>{const S=d.node.outputs[w];for(const A of s[S].to){const O=t[A];let x=!0;for(const I of O.inputs)if(!this._values[I]){x=!1;break}x&&_.add(A)}}),u.push(..._)}const r=[];for(let 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w=r.outputs(v);if(m.has(w))throw new Error(`duplicated output name: ${w}`);const S=this._allData.push(new u)-1;m.set(w,S),this._allOutputIndices.push(S),this._allOutputNames.push(w)}if(!r.nodes)throw new Error("missing information in graph: node");for(let v=0;v<r.nodesLength();v++){const w=r.nodes(v);let S=w.name();if(!S)for(let O=0;S=`unnamed_${w.opType()}_${O}`,b.has(S);O++);if(b.has(S))throw new Error(`duplicated node name: ${S}`);const A=this._nodes.push(new s(w,S))-1;b.set(S,A)}for(let v=0;v<this._nodes.length;v++){const w=this._nodes[v],S=r.nodes(v);if(S==null)throw new Error(`No node exists at index ${v}`);if((S==null?void 0:S.outputsLength())===0)throw new Error(`missing output for node: ${S.name}`);for(let A=0;A<(S==null?void 0:S.outputsLength());A++){const O=S==null?void 0:S.outputs(A);let x=m.get(O);if(x===void 0&&(x=this._allData.push(new u)-1,m.set(O,x)),w.outputs.push(x),this._allData[x]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${x}`);if(this._allData[x]._from=v,S.opType()==="Constant"){if(S.attributesLength()!==1||!S.attributes(0).t())throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(S.outputsLength()!==1)throw new Error("missing output or incorrect number of outputs for this Constant operator");w.outputs.pop(),w.executeNode=!1,this._allData[x]._from=-1,this._allData[x].tensor=a.Tensor.fromOrtTensor(S.attributes(0).t())}}}for(let v=0;v<this._nodes.length;v++){const w=this._nodes[v],S=r.nodes(v);if(S.inputsLength()===0)throw new Error(`missing input for node: ${S.name}`);for(let A=0;A<S.inputsLength();A++){const O=S.inputs(A),x=m.get(O);if(x===void 0)throw new Error(`unrecognized input '${O}' for node: ${S.name()}`);w.inputs.push(x),this._allData[x]._to.push(v)}}}checkIsAcyclic(){const r=new Set;this._allInputIndices.forEach(g=>{this._allData[g]._to.forEach(m=>{r.add(m)})});const i=Array.from(r),d=new Array(this._nodes.length).fill("white");for(;i.length>0;){const g=i.pop();d[g]==="gray"?d[g]="black":(i.push(g),d[g]="gray",this._nodes[g].outputs.forEach(m=>{const b=this._allData[m];if(b.tensor!==void 0)throw new Error("node outputs should not be initialized");if(b._from!==g)throw new Error("from property of the Value object doesn't match index of Node being processed");b._to.forEach(_=>{if(d[_]==="gray")throw new Error("model graph is cyclic");d[_]==="white"&&i.push(_)})}))}}transformGraph(r){this.removeAllIdentityNodes(),this.removeAllDropoutNodes(),this.fuseConvActivationNodes(),r&&r.transformGraph(this),this.finalizeGraph()}finalizeGraph(){let r=0;for(let i=0;i<this._nodes.length;i++)this._nodes[i].executeNode?r>0&&(this._nodes[i].inputs.forEach(d=>{const 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startInputsVector(t,e){t.startVector(4,e,4)}static addOutputs(t,e){t.addFieldOffset(6,e,0)}static createOutputsVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startOutputsVector(t,e){t.startVector(4,e,4)}static addSparseInitializers(t,e){t.addFieldOffset(7,e,0)}static createSparseInitializersVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startSparseInitializersVector(t,e){t.startVector(4,e,4)}static endGraph(t){return t.endObject()}static createGraph(t,e,r,i,d,g,m,b,_){return u.startGraph(t),u.addInitializers(t,e),u.addNodeArgs(t,r),u.addNodes(t,i),u.addMaxNodeIndex(t,d),u.addNodeEdges(t,g),u.addInputs(t,m),u.addOutputs(t,b),u.addSparseInitializers(t,_),u.endGraph(t)}}p.Graph=u})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(p){class u{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsModel(t,e){return(e||new u).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsModel(t,e){return t.setPosition(t.position()+l.flatbuffers.SIZE_PREFIX_LENGTH),(e||new u).__init(t.readInt32(t.position())+t.position(),t)}irVersion(){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}opsetImport(t,e){let r=this.bb.__offset(this.bb_pos,6);return r?(e||new a.experimental.fbs.OperatorSetId).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}opsetImportLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}producerName(t){let e=this.bb.__offset(this.bb_pos,8);return e?this.bb.__string(this.bb_pos+e,t):null}producerVersion(t){let e=this.bb.__offset(this.bb_pos,10);return e?this.bb.__string(this.bb_pos+e,t):null}domain(t){let e=this.bb.__offset(this.bb_pos,12);return e?this.bb.__string(this.bb_pos+e,t):null}modelVersion(){let t=this.bb.__offset(this.bb_pos,14);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}docString(t){let e=this.bb.__offset(this.bb_pos,16);return e?this.bb.__string(this.bb_pos+e,t):null}graph(t){let e=this.bb.__offset(this.bb_pos,18);return e?(t||new a.experimental.fbs.Graph).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}graphDocString(t){let e=this.bb.__offset(this.bb_pos,20);return e?this.bb.__string(this.bb_pos+e,t):null}static startModel(t){t.startObject(9)}static addIrVersion(t,e){t.addFieldInt64(0,e,t.createLong(0,0))}static addOpsetImport(t,e){t.addFieldOffset(1,e,0)}static createOpsetImportVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startOpsetImportVector(t,e){t.startVector(4,e,4)}static addProducerName(t,e){t.addFieldOffset(2,e,0)}static addProducerVersion(t,e){t.addFieldOffset(3,e,0)}static addDomain(t,e){t.addFieldOffset(4,e,0)}static addModelVersion(t,e){t.addFieldInt64(5,e,t.createLong(0,0))}static addDocString(t,e){t.addFieldOffset(6,e,0)}static addGraph(t,e){t.addFieldOffset(7,e,0)}static addGraphDocString(t,e){t.addFieldOffset(8,e,0)}static endModel(t){return t.endObject()}static createModel(t,e,r,i,d,g,m,b,_,v){return u.startModel(t),u.addIrVersion(t,e),u.addOpsetImport(t,r),u.addProducerName(t,i),u.addProducerVersion(t,d),u.addDomain(t,g),u.addModelVersion(t,m),u.addDocString(t,b),u.addGraph(t,_),u.addGraphDocString(t,v),u.endModel(t)}}p.Model=u})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(p){class u{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsKernelCreateInfos(t,e){return(e||new u).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsKernelCreateInfos(t,e){return t.setPosition(t.position()+l.flatbuffers.SIZE_PREFIX_LENGTH),(e||new u).__init(t.readInt32(t.position())+t.position(),t)}nodeIndices(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.readUint32(this.bb.__vector(this.bb_pos+e)+4*t):0}nodeIndicesLength(){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.__vector_len(this.bb_pos+t):0}nodeIndicesArray(){let t=this.bb.__offset(this.bb_pos,4);return t?new Uint32Array(this.bb.bytes().buffer,this.bb.bytes().byteOffset+this.bb.__vector(this.bb_pos+t),this.bb.__vector_len(this.bb_pos+t)):null}kernelDefHashes(t){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.readUint64(this.bb.__vector(this.bb_pos+e)+8*t):this.bb.createLong(0,0)}kernelDefHashesLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}static startKernelCreateInfos(t){t.startObject(2)}static addNodeIndices(t,e){t.addFieldOffset(0,e,0)}static createNodeIndicesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addInt32(e[r]);return t.endVector()}static startNodeIndicesVector(t,e){t.startVector(4,e,4)}static addKernelDefHashes(t,e){t.addFieldOffset(1,e,0)}static createKernelDefHashesVector(t,e){t.startVector(8,e.length,8);for(let r=e.length-1;r>=0;r--)t.addInt64(e[r]);return t.endVector()}static startKernelDefHashesVector(t,e){t.startVector(8,e,8)}static endKernelCreateInfos(t){return t.endObject()}static createKernelCreateInfos(t,e,r){return u.startKernelCreateInfos(t),u.addNodeIndices(t,e),u.addKernelDefHashes(t,r),u.endKernelCreateInfos(t)}}p.KernelCreateInfos=u})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(p){class u{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsSubGraphSessionState(t,e){return(e||new u).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSubGraphSessionState(t,e){return t.setPosition(t.position()+l.flatbuffers.SIZE_PREFIX_LENGTH),(e||new u).__init(t.readInt32(t.position())+t.position(),t)}graphId(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,t):null}sessionState(t){let e=this.bb.__offset(this.bb_pos,6);return e?(t||new a.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startSubGraphSessionState(t){t.startObject(2)}static addGraphId(t,e){t.addFieldOffset(0,e,0)}static addSessionState(t,e){t.addFieldOffset(1,e,0)}static endSubGraphSessionState(t){let e=t.endObject();return t.requiredField(e,4),e}static createSubGraphSessionState(t,e,r){return u.startSubGraphSessionState(t),u.addGraphId(t,e),u.addSessionState(t,r),u.endSubGraphSessionState(t)}}p.SubGraphSessionState=u})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(p){class u{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsSessionState(t,e){return(e||new u).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSessionState(t,e){return t.setPosition(t.position()+l.flatbuffers.SIZE_PREFIX_LENGTH),(e||new u).__init(t.readInt32(t.position())+t.position(),t)}kernels(t){let e=this.bb.__offset(this.bb_pos,4);return e?(t||new a.experimental.fbs.KernelCreateInfos).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}subGraphSessionStates(t,e){let r=this.bb.__offset(this.bb_pos,6);return r?(e||new a.experimental.fbs.SubGraphSessionState).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}subGraphSessionStatesLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}static startSessionState(t){t.startObject(2)}static addKernels(t,e){t.addFieldOffset(0,e,0)}static addSubGraphSessionStates(t,e){t.addFieldOffset(1,e,0)}static createSubGraphSessionStatesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startSubGraphSessionStatesVector(t,e){t.startVector(4,e,4)}static endSessionState(t){return t.endObject()}static createSessionState(t,e,r){return u.startSessionState(t),u.addKernels(t,e),u.addSubGraphSessionStates(t,r),u.endSessionState(t)}}p.SessionState=u})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(a){(function(h){(function(p){class u{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsInferenceSession(t,e){return(e||new u).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsInferenceSession(t,e){return t.setPosition(t.position()+l.flatbuffers.SIZE_PREFIX_LENGTH),(e||new u).__init(t.readInt32(t.position())+t.position(),t)}static bufferHasIdentifier(t){return t.__has_identifier("ORTM")}ortVersion(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,t):null}model(t){let e=this.bb.__offset(this.bb_pos,6);return e?(t||new a.experimental.fbs.Model).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}sessionState(t){let e=this.bb.__offset(this.bb_pos,8);return e?(t||new a.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startInferenceSession(t){t.startObject(3)}static addOrtVersion(t,e){t.addFieldOffset(0,e,0)}static addModel(t,e){t.addFieldOffset(1,e,0)}static addSessionState(t,e){t.addFieldOffset(2,e,0)}static endInferenceSession(t){return t.endObject()}static finishInferenceSessionBuffer(t,e){t.finish(e,"ORTM")}static finishSizePrefixedInferenceSessionBuffer(t,e){t.finish(e,"ORTM",!0)}static createInferenceSession(t,e,r,i){return u.startInferenceSession(t),u.addOrtVersion(t,e),u.addModel(t,r),u.addSessionState(t,i),u.endInferenceSession(t)}}p.InferenceSession=u})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(n.onnxruntime||(n.onnxruntime={}))},7448:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.OnnxjsSessionHandler=void 0;const l=o(1670),c=o(9162);n.OnnxjsSessionHandler=class{constructor(f){this.session=f,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(f,a,h){const p=new Map;for(const t in f)if(Object.hasOwnProperty.call(f,t)){const e=f[t];p.set(t,new c.Tensor(e.dims,e.type,void 0,void 0,e.data))}const u=await this.session.run(p),s={};return u.forEach((t,e)=>{s[e]=new l.Tensor(t.type,t.data,t.dims)}),s}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(y,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Session=void 0;const l=o(7067),c=o(1296),f=o(7091),a=o(1036),h=o(6231),p=o(2644);n.Session=class{constructor(u={}){this._initialized=!1,this.backendHint=u.backendHint,this.profiler=h.Profiler.create(u.profiler),this.context={profiler:this.profiler,graphInputTypes:[],graphInputDims:[]}}get inputNames(){return this._model.graph.getInputNames()}get outputNames(){return this._model.graph.getOutputNames()}startProfiling(){this.profiler.start()}endProfiling(){this.profiler.stop()}async loadModel(u,s,t){await this.profiler.event("session","Session.loadModel",async()=>{const e=await(0,f.resolveBackend)(this.backendHint);if(this.sessionHandler=e.createSessionHandler(this.context),this._model=new p.Model,typeof u=="string"){const r=u.endsWith(".ort");if(typeof fetch>"u"){const i=await(0,c.promisify)(l.readFile)(u);this.initialize(i,r)}else{const i=await fetch(u),d=await i.arrayBuffer();this.initialize(new Uint8Array(d),r)}}else if(ArrayBuffer.isView(u))this.initialize(u);else{const r=new Uint8Array(u,s||0,t||u.byteLength);this.initialize(r)}})}initialize(u,s){if(this._initialized)throw new Error("already initialized");this.profiler.event("session","Session.initialize",()=>{const t=this.sessionHandler.transformGraph?this.sessionHandler:void 0;this._model.load(u,t,s),this.sessionHandler.onGraphInitialized&&this.sessionHandler.onGraphInitialized(this._model.graph),this.initializeOps(this._model.graph),this._executionPlan=new a.ExecutionPlan(this._model.graph,this._ops,this.profiler)}),this._initialized=!0}async run(u){if(!this._initialized)throw new Error("session not initialized yet");return this.profiler.event("session","Session.run",async()=>{const s=this.normalizeAndValidateInputs(u),t=await this._executionPlan.execute(this.sessionHandler,s);return this.createOutput(t)})}normalizeAndValidateInputs(u){const s=this._model.graph.getInputNames();if(Array.isArray(u)){if(u.length!==s.length)throw new Error(`incorrect input array length: expected ${s.length} but got ${u.length}`)}else{if(u.size!==s.length)throw new Error(`incorrect input map size: expected ${s.length} but got ${u.size}`);const t=new Array(u.size);let e=0;for(let r=0;r<s.length;++r){const i=u.get(s[r]);if(!i)throw new Error(`missing input tensor for: '${name}'`);t[e++]=i}u=t}if(this.context.graphInputTypes&&this.context.graphInputTypes.length!==0&&this.context.graphInputDims&&this.context.graphInputDims.length!==0)this.validateInputTensorDims(this.context.graphInputDims,u,!1);else{const t=this._model.graph.getInputIndices(),e=this._model.graph.getValues(),r=new Array(t.length);for(let i=0;i<t.length;++i){const d=e[t[i]];r[i]=d.type.shape.dims,this.context.graphInputTypes.push(d.type.tensorType),this.context.graphInputDims.push(u[i].dims)}this.validateInputTensorDims(r,u,!0)}return this.validateInputTensorTypes(this.context.graphInputTypes,u),u}validateInputTensorTypes(u,s){for(let t=0;t<s.length;t++){const e=u[t],r=s[t].type;if(e!==r)throw new Error(`input tensor[${t}] check failed: expected type '${e}' but got ${r}`)}}validateInputTensorDims(u,s,t){for(let e=0;e<s.length;e++){const r=u[e],i=s[e].dims;if(!this.compareTensorDims(r,i,t))throw new Error(`input tensor[${e}] check failed: expected shape '[${r.join(",")}]' but got [${i.join(",")}]`)}}compareTensorDims(u,s,t){if(u.length!==s.length)return!1;for(let e=0;e<u.length;++e)if(u[e]!==s[e]&&(!t||u[e]!==0))return!1;return!0}createOutput(u){const s=this._model.graph.getOutputNames();if(u.length!==s.length)throw new Error("expected number of outputs do not match number of generated outputs");const t=new Map;for(let e=0;e<s.length;++e)t.set(s[e],u[e]);return t}initializeOps(u){const s=u.getNodes();this._ops=new Array(s.length);for(let t=0;t<s.length;t++)this._ops[t]=this.sessionHandler.resolve(s[t],this._model.opsets,u)}}},9162:function(y,n,o){var l=this&&this.__importDefault||function(d){return d&&d.__esModule?d:{default:d}};Object.defineProperty(n,"__esModule",{value:!0}),n.Tensor=void 0;const c=o(3442),f=l(o(3720)),a=o(1446),h=o(9395),p=o(2517);var u=h.onnxruntime.experimental.fbs;class s{get data(){if(this.cache===void 0){const g=this.dataProvider(this.dataId);if(g.length!==this.size)throw new Error("Length of data provided by the Data Provider is inconsistent with the dims of this Tensor.");this.cache=g}return this.cache}get stringData(){if(this.type!=="string")throw new TypeError("data type is not string");return this.data}get integerData(){switch(this.type){case"uint8":case"int8":case"uint16":case"int16":case"int32":case"uint32":case"bool":return this.data;default:throw new TypeError("data type is not integer (uint8, int8, uint16, int16, int32, uint32, bool)")}}get floatData(){switch(this.type){case"float32":case"float64":return this.data;default:throw new TypeError("data type is not float (float32, float64)")}}get numberData(){if(this.type!=="string")return this.data;throw new TypeError("type cannot be non-number (string)")}get(g){return this.data[p.ShapeUtil.indicesToOffset(g,this.strides)]}set(g,m){this.data[p.ShapeUtil.indicesToOffset(g,this.strides)]=m}async getData(){return this.cache===void 0&&(this.cache=await this.asyncDataProvider(this.dataId)),this.cache}get strides(){return this._strides||(this._strides=p.ShapeUtil.computeStrides(this.dims)),this._strides}constructor(g,m,b,_,v,w=c.Guid.create()){this.dims=g,this.type=m,this.dataProvider=b,this.asyncDataProvider=_,this.cache=v,this.dataId=w,this.size=p.ShapeUtil.validateDimsAndCalcSize(g);const S=this.size,A=b===void 0&&_===void 0&&v===void 0;if(v!==void 0&&v.length!==S)throw new RangeError("Input dims doesn't match data length.");if(m==="string"){if(!(v===void 0||Array.isArray(v)&&v.every(O=>typeof O=="string")))throw new TypeError("cache should be a string array");A&&(this.cache=new Array(S))}else{if(v!==void 0){const O=e(m);if(!(v instanceof O))throw new TypeError(`cache should be type ${O.name}`)}if(A){const O=new ArrayBuffer(S*function(x){switch(x){case"bool":case"int8":case"uint8":return 1;case"int16":case"uint16":return 2;case"int32":case"uint32":case"float32":return 4;case"float64":return 8;default:throw new Error(`cannot calculate sizeof() on type ${x}`)}}(m));this.cache=function(x,I){return new(e(I))(x)}(O,m)}}}static fromProto(g){if(!g)throw new Error("cannot construct Value from an empty tensor");const m=p.ProtoUtil.tensorDataTypeFromProto(g.dataType),b=p.ProtoUtil.tensorDimsFromProto(g.dims),_=new s(b,m);if(m==="string")g.stringData.forEach((v,w)=>{_.data[w]=(0,p.decodeUtf8String)(v)});else if(g.rawData&&typeof g.rawData.byteLength=="number"&&g.rawData.byteLength>0){const v=_.data,w=new DataView(g.rawData.buffer,g.rawData.byteOffset,g.rawData.byteLength),S=t(g.dataType),A=g.rawData.byteLength/S;if(g.rawData.byteLength%S!=0)throw new Error("invalid buffer length");if(v.length!==A)throw new Error("buffer length mismatch");for(let O=0;O<A;O++){const x=i(w,g.dataType,O*S);v[O]=x}}else{let v;switch(g.dataType){case a.onnx.TensorProto.DataType.FLOAT:v=g.floatData;break;case a.onnx.TensorProto.DataType.INT32:case a.onnx.TensorProto.DataType.INT16:case a.onnx.TensorProto.DataType.UINT16:case a.onnx.TensorProto.DataType.INT8:case a.onnx.TensorProto.DataType.UINT8:case a.onnx.TensorProto.DataType.BOOL:v=g.int32Data;break;case a.onnx.TensorProto.DataType.INT64:v=g.int64Data;break;case a.onnx.TensorProto.DataType.DOUBLE:v=g.doubleData;break;case a.onnx.TensorProto.DataType.UINT32:case a.onnx.TensorProto.DataType.UINT64:v=g.uint64Data;break;default:throw new Error("unspecific error")}if(v==null)throw new Error("failed to populate data from a tensorproto value");const w=_.data;if(w.length!==v.length)throw new Error("array length mismatch");for(let S=0;S<v.length;S++){const A=v[S];f.default.isLong(A)?w[S]=r(A,g.dataType):w[S]=A}}return _}static fromData(g,m,b){return new s(m,b,void 0,void 0,g)}static fromOrtTensor(g){if(!g)throw new Error("cannot construct Value from an empty tensor");const m=p.ProtoUtil.tensorDimsFromORTFormat(g),b=p.ProtoUtil.tensorDataTypeFromProto(g.dataType()),_=new s(m,b);if(b==="string")for(let v=0;v<g.stringDataLength();v++)_.data[v]=g.stringData(v);else if(g.rawDataArray()&&typeof g.rawDataLength()=="number"&&g.rawDataLength()>0){const v=_.data,w=new DataView(g.rawDataArray().buffer,g.rawDataArray().byteOffset,g.rawDataLength()),S=t(g.dataType()),A=g.rawDataLength()/S;if(g.rawDataLength()%S!=0)throw new Error("invalid buffer length");if(v.length!==A)throw new Error("buffer length mismatch");for(let O=0;O<A;O++){const x=i(w,g.dataType(),O*S);v[O]=x}}return _}}function t(d){switch(d){case a.onnx.TensorProto.DataType.UINT8:case a.onnx.TensorProto.DataType.INT8:case a.onnx.TensorProto.DataType.BOOL:return 1;case a.onnx.TensorProto.DataType.UINT16:case a.onnx.TensorProto.DataType.INT16:return 2;case a.onnx.TensorProto.DataType.FLOAT:case a.onnx.TensorProto.DataType.INT32:case a.onnx.TensorProto.DataType.UINT32:return 4;case a.onnx.TensorProto.DataType.INT64:case a.onnx.TensorProto.DataType.DOUBLE:case a.onnx.TensorProto.DataType.UINT64:return 8;default:throw new Error(`cannot calculate sizeof() on type ${a.onnx.TensorProto.DataType[d]}`)}}function e(d){switch(d){case"bool":case"uint8":return Uint8Array;case"int8":return Int8Array;case"int16":return Int16Array;case"uint16":return Uint16Array;case"int32":return Int32Array;case"uint32":return Uint32Array;case"float32":return Float32Array;case"float64":return Float64Array;default:throw new Error("unspecified error")}}function r(d,g){if(g===a.onnx.TensorProto.DataType.INT64||g===u.TensorDataType.INT64){if(d.greaterThanOrEqual(2147483648)||d.lessThan(-2147483648))throw new TypeError("int64 is not supported")}else{if(g!==a.onnx.TensorProto.DataType.UINT32&&g!==u.TensorDataType.UINT32&&g!==a.onnx.TensorProto.DataType.UINT64&&g!==u.TensorDataType.UINT64)throw new TypeError(`not a LONG type: ${a.onnx.TensorProto.DataType[g]}`);if(d.greaterThanOrEqual(4294967296)||d.lessThan(0))throw new TypeError("uint64 is not supported")}return d.toNumber()}function i(d,g,m){switch(g){case a.onnx.TensorProto.DataType.BOOL:case a.onnx.TensorProto.DataType.UINT8:return d.getUint8(m);case a.onnx.TensorProto.DataType.INT8:return d.getInt8(m);case a.onnx.TensorProto.DataType.UINT16:return d.getUint16(m,!0);case a.onnx.TensorProto.DataType.INT16:return d.getInt16(m,!0);case a.onnx.TensorProto.DataType.FLOAT:return d.getFloat32(m,!0);case a.onnx.TensorProto.DataType.INT32:return d.getInt32(m,!0);case a.onnx.TensorProto.DataType.UINT32:return d.getUint32(m,!0);case a.onnx.TensorProto.DataType.INT64:return r(f.default.fromBits(d.getUint32(m,!0),d.getUint32(m+4,!0),!1),g);case a.onnx.TensorProto.DataType.DOUBLE:return d.getFloat64(m,!0);case a.onnx.TensorProto.DataType.UINT64:return r(f.default.fromBits(d.getUint32(m,!0),d.getUint32(m+4,!0),!0),g);default:throw new Error(`cannot read from DataView for type ${a.onnx.TensorProto.DataType[g]}`)}}n.Tensor=s},2517:function(y,n,o){var l=this&&this.__importDefault||function(g){return g&&g.__esModule?g:{default:g}};Object.defineProperty(n,"__esModule",{value:!0}),n.decodeUtf8String=n.MAX_CLIP=n.MIN_CLIP=n.PoolConvUtil=n.ReduceUtil=n.SplitUtil=n.MathUtil=n.ShapeUtil=n.LongUtil=n.ProtoUtil=n.GemmUtil=n.arrayCopyHelper=n.BroadcastUtil=n.MatMulUtil=n.ArrayUtil=n.assert=n.checkInputsShape=void 0;const c=o(5686),f=l(o(3720)),a=o(1446),h=o(9162);n.checkInputsShape=function(g,...m){if(!g||g.length!==m.length)return!1;for(let b=0;b<g.length;b++)if(!g[b].dims||g[b].dims.length!==m[b])return!1;return!0},n.assert=function(g,m){if(!g)throw new Error(typeof m=="string"?m:m())},n.ArrayUtil=class{static arraysEqual(g,m){if(g.length!==m.length)return!1;for(let b=0;b<g.length;b++)if(g[b]!==m[b])return!1;return!0}};class p{static preprocessInputShapes(m,b){return[m.length===1?[1,m[0]]:m,b.length===1?[b[0],1]:b]}static postprocessOutputShape(m,b,_){b===1&&m.splice(m.length-2,1),_===1&&m.pop()}static calcMatMulShape(m,b){return m[1]!==b[0]?void 0:[m[0],b[1]]}}n.MatMulUtil=p;class u{static calcShape(m,b,_=!1){const v=m.length,w=b.length;if(v===0)return b;if(w===0)return m;const S=Math.max(m.length,b.length),A=new Array(S);if(_){if(v<2||w<2)return;const O=p.calcMatMulShape([m[v-2],m[v-1]],[b[w-2],b[w-1]]);if(O===void 0)return;[A[S-2],A[S-1]]=O}for(let O=_?3:1;O<=S;O++){const x=v-O<0?1:m[v-O],I=w-O<0?1:b[w-O];if(x!==I&&x>1&&I>1)return;A[S-O]=Math.max(x,I)}return A}static index(m,b){const _=new Array(b.length);return u.fillIndex(m,b,_),_}static fillIndex(m,b,_){const v=m.length-b.length;for(let w=0;w<b.length;w++)_[w]=m[v+w]%b[w]}static calc(m,b,_,v,w){const S=u.calcShape(m.dims,b.dims);if(S){if(v&&!e.areEqual(S,m.dims))return;const A=e.size(S),O=v?m:new h.Tensor(S,w||m.type);if(S.length===0)O.set([],_(m.get([]),b.get([])));else{const x=new Array(S.length),I=new Array(m.dims.length),$=new Array(b.dims.length);let B,L=0,N=0,H=!1,M=!1;m.dims.length===0&&(L=m.get([]),H=!0),b.dims.length===0&&(N=b.get([]),M=!0);for(let j=0;j<A;j++){B=j;for(let Z=S.length-1;Z>=0;Z--)x[Z]=B%S[Z],B=Math.floor(B/S[Z]);H||(u.fillIndex(x,m.dims,I),L=m.get(I)),M||(u.fillIndex(x,b.dims,$),N=b.get($)),O.set(x,_(L,N))}}return O}}static isValidBroadcast(m,b){const _=m.length,v=b.length;if(_>v)return!1;for(let w=1;w<=_;w++)if(m[_-w]!==1&&m[_-w]!==b[v-w])return!1;return!0}static getBroadcastDims(m,b){const _=m.length,v=[];for(let w=0;w<_;w++){const S=_-1-w,A=m[S]||1;(b[b.length-1-w]||1)>1&&A===1&&v.unshift(S)}return v}}n.BroadcastUtil=u,n.arrayCopyHelper=function(g,m,b,_,v){if(_<0||_>=m.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(_+v>m.length)throw new Error("source indices to be copied are outside bounds");if(b+v>g.length)throw new Error("target array is too small to hold result");for(let w=0;w<v;w++)g[b+w]=m[_+w]},n.GemmUtil=class{static getShapeOfGemmResult(g,m,b,_,v){if(g.length!==2||b.length!==2)throw new Error("shape need to be of size 2");let w,S,A;m?(w=g[1],S=g[0]):(w=g[0],S=g[1]);let O=-1;if(_?(A=b[0],O=1):(A=b[1],O=0),b[O]!==S)throw new Error("dimension mismatch");if(w<=0||A<=0||S<=0)throw new Error("invalid shape specified");if(v&&!u.isValidBroadcast(v,[w,A]))throw new Error("gemm: invalid bias shape for broadcast");return[w,A,S]}};class s{static tensorDataTypeFromProto(m){switch(m){case a.onnx.TensorProto.DataType.INT8:return"int8";case a.onnx.TensorProto.DataType.UINT8:return"uint8";case a.onnx.TensorProto.DataType.BOOL:return"bool";case a.onnx.TensorProto.DataType.INT16:return"int16";case a.onnx.TensorProto.DataType.UINT16:return"uint16";case a.onnx.TensorProto.DataType.INT32:return"int32";case a.onnx.TensorProto.DataType.UINT32:return"uint32";case a.onnx.TensorProto.DataType.FLOAT:return"float32";case a.onnx.TensorProto.DataType.DOUBLE:return"float64";case a.onnx.TensorProto.DataType.STRING:return"string";case a.onnx.TensorProto.DataType.INT64:return"int32";case a.onnx.TensorProto.DataType.UINT64:return"uint32";default:throw new Error(`unsupported data type: ${a.onnx.TensorProto.DataType[m]}`)}}static tensorDataTypeStringToEnum(m){switch(m){case"int8":return a.onnx.TensorProto.DataType.INT8;case"uint8":return a.onnx.TensorProto.DataType.UINT8;case"bool":return a.onnx.TensorProto.DataType.BOOL;case"int16":return a.onnx.TensorProto.DataType.INT16;case"uint16":return a.onnx.TensorProto.DataType.UINT16;case"int32":return a.onnx.TensorProto.DataType.INT32;case"uint32":return a.onnx.TensorProto.DataType.UINT32;case"float32":return a.onnx.TensorProto.DataType.FLOAT;case"float64":return a.onnx.TensorProto.DataType.DOUBLE;case"string":return a.onnx.TensorProto.DataType.STRING;case"int64":return a.onnx.TensorProto.DataType.INT64;case"uint64":return a.onnx.TensorProto.DataType.UINT64;default:throw new Error(`unsupported data type: ${m}`)}}static tensorDimsFromProto(m){return m.map(b=>f.default.isLong(b)?b.toNumber():b)}static tensorValueTypeFromProto(m){return{tensorType:s.tensorDataTypeFromProto(m.elemType),shape:{dims:s.tensorDimsFromProto(m.shape.dim.map(b=>b.dimValue))}}}static tensorDimsFromORTFormat(m){const b=[];for(let _=0;_<m.dimsLength();_++)b.push(t.longToNumber(m.dims(_)));return b}static tensorAttributesFromORTFormat(m){const b=[];for(let _=0;_<m.attributesLength();_++)b.push(m.attributes(_));return b}}n.ProtoUtil=s;class t{static longToNumber(m,b){return f.default.isLong(m)?m.toNumber():m instanceof c.flatbuffers.Long?f.default.fromValue({low:m.low,high:m.high,unsigned:b!=null&&b}).toNumber():m}static isLong(m){return f.default.isLong(m)||m instanceof c.flatbuffers.Long}}n.LongUtil=t;class e{static size(m){return e.getSizeFromDimensionRange(m,0,m.length)}static sizeFromDimension(m,b){if(b<0||b>m.length)throw new Error(`invalid dimension of ${b} for sizeFromDimension as Tensor has ${m.length} dimensions.`);return e.getSizeFromDimensionRange(m,b,m.length)}static sizeToDimension(m,b){if(b<0||b>m.length)throw new Error(`invalid dimension of ${b} for sizeToDimension as Tensor has ${m.length} dimensions.`);return e.getSizeFromDimensionRange(m,0,b)}static getSizeFromDimensionRange(m,b,_){let v=1;for(let w=b;w<_;w++){if(m[w]<=0)throw new Error("cannot get valid size from specified dimension range. Most likely the range contains 0 or negative values in them.");v*=m[w]}return v}static computeStrides(m){const b=m.length;if(b===0)return[];if(b===1)return[1];const _=new Array(b);_[b-1]=1,_[b-2]=m[b-1];for(let v=b-3;v>=0;--v)_[v]=_[v+1]*m[v+1];return _}static transpose(m){return m.slice().reverse()}static indicesToOffset(m,b,_){_===void 0&&(_=m.length);let v=0;for(let w=0;w<_;++w)v+=b[w]*m[w];return v}static offsetToIndices(m,b){const _=b.length;if(_===0)return[];if(_===1)return[m*b[0]];const v=new Array(b.length);for(let w=0;w<v.length-1;++w)v[w]=Math.floor(m/b[w]),m-=v[w]*b[w];return v[v.length-1]=m,v}static normalizeAxis(m,b){if(m<-b&&m>=b)throw new Error("unsupported axis for this operation.");return m<0?m+b:m}static normalizeAxes(m,b){return m.map(_=>this.normalizeAxis(_,b))}static incrementIndex(m,b,_){if(b.length===0||m.length===0)throw new Error("Index incrementing unsupported for scalar Tensor");if(_===void 0)_=b.length;else if(_<=0||_>b.length)throw new Error("Incorrect axis to increment on");for(let v=_-1;v>=0&&(m[v]++,!(m[v]<b[v]));--v)m[v]=0}static calculateReshapedDims(m,b){if(b.length===0){if(m.length===0||e.size(m)===1)return[];throw new Error("cannot reshape to a scalar Tensor")}const _=b.length,v=new Array(_);let w=-1,S=1;for(let O=0;O<_;O++){if(b[O]<-1)throw new Error("a dimension in shape hints cannot be less than -1");if(b[O]===-1){if(w!==-1)throw new Error("at most one dimension in shape hints can be -1");w=O}else{if(b[O]===0){if(O>=m.length)throw new Error("the dimension with value zero exceeds the dimension size of the input tensor");v[O]=m[O]}else v[O]=b[O];S*=v[O]}}const A=e.size(m);if(w!==-1){if(A%S!=0)throw new Error(`the input tensor cannot be reshaped to the requested shape. Input shape: [${m}] Output shape: [${b}]`);v[w]=A/S}else if(S!==A)throw new Error("reshapedDims and originalDims don't have matching sizes");return v}static sortBasedOnPerm(m,b){return b?b.map(_=>m[_]):m.slice().reverse()}static padShape(m,b){const _=m.length;return m.map((v,w)=>v+b[w]+b[w+_])}static areEqual(m,b){return m.length===b.length&&m.every((_,v)=>_===b[v])}static validateDimsAndCalcSize(m){if(m.length>6)throw new TypeError("Only rank 0 to 6 is supported for tensor shape.");let b=1;for(const _ of m){if(!Number.isInteger(_))throw new TypeError(`Invalid shape: ${_} is not an integer`);if(_<0||_>2147483647)throw new TypeError(`Invalid shape: length ${_} is not allowed`);b*=_}return b}static flattenShape(m,b){b<0&&(b+=m.length);const _=m.reduce((w,S)=>w*S,1),v=m.slice(b).reduce((w,S)=>w*S,1);return[_/v,v]}static squeezeShape(m,b){const _=new Array;b=e.normalizeAxes(b,m.length);for(let v=0;v<m.length;v++){const w=b.indexOf(v)>=0;if(w&&m[v]!==1)throw new Error("squeeze an axis of size different than 1");(b.length===0&&m[v]>1||b.length>0&&!w)&&_.push(m[v])}return _}static unsqueezeShape(m,b){const _=new Array(m.length+b.length);_.fill(0);for(let w=0;w<b.length;w++){const S=e.normalizeAxis(b[w],_.length);if(S>=_.length)throw new Error("'axes' has an out of range axis");if(_[S]!==0)throw new Error("'axes' has a duplicate axis");_[S]=1}let v=0;for(let w=0;w<_.length;w++)_[w]===0&&(_[w]=m[v++]);if(v!==m.length)throw new Error("the unsqueezed dimension could not be established");return _}}n.ShapeUtil=e,n.MathUtil=class{static sqr(g,m,b,_,v){if(_<0||_>=m.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(_+v>m.length)throw new Error("source indices to be copied are outside bounds");if(b+v>g.length)throw new Error("target array is too small to hold result");for(let w=0;w<v;w++)g[b+w]+=Math.pow(m[_+w],2)}static axpy(g,m,b,_,v,w){if(_<0||_>=m.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(_+v>m.length)throw new Error("source indices to be copied are outside bounds");if(b+v>g.length)throw new Error("target array is too small to hold result");for(let S=0;S<v;S++)g[b+S]+=w*m[_+S]}static powx(g,m,b,_,v,w){if(_<0||_>=m.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(_+v>m.length)throw new Error("source indices to be copied are outside bounds");if(b+v>g.length)throw new Error("target array is too small to hold result");for(let S=0;S<v;S++)g[b+S]=Math.pow(m[_+S],w)}static mul(g,m,b,_,v){if(_<0||_>=m.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(_+v>m.length)throw new Error("source indices to be copied are outside bounds");if(b+v>g.length)throw new Error("target array is too small to hold result");for(let w=0;w<v;w++)g[b+w]=m[_+w]*g[b+w]}};class r{static splitShape(m,b,_,v){if(_.length===0){if(!v)throw new Error("need to know number of outputs when the 'split' attribute is not specified");r.determineSplit(m[b],v,_)}const w=[],S=[0];for(let A=0;A<_.length;++A){A!==0&&S.push(S[A-1]+_[A-1]);const O=m.slice();O[b]=_[A],w.push(O)}return[w,S]}static determineSplit(m,b,_){if(m%b!=0)throw new Error("cannot split tensor to equal sized parts");for(let v=0;v<b;++v)_.push(m/b)}}n.SplitUtil=r;class i{static calcReduce(m,b,_,v,w){const S=m.dims.slice(0);b.length===0&&S.forEach((L,N)=>b.push(N));const A=i.calcReduceShape(S,b,!0),O=e.size(A),x=new h.Tensor(A,m.type),I=e.computeStrides(A),$=e.computeStrides(S),B=new Array(S.length);for(let L=0;L<O;L++){const N=e.offsetToIndices(L,I);u.fillIndex(N,S,B),x.set(N,i.calcReduceByAxis(m.numberData,b,S,0,e.indicesToOffset(B,$),v,w))}return _?x:new h.Tensor(i.calcReduceShape(S,b,_),x.type,void 0,void 0,x.data,x.dataId)}static calcReduceByAxis(m,b,_,v,w,S,A){let O=0;if(v>=b.length)return S(m[w]);const x=b[v],I=x>=_.length?1:e.size(_.slice(x+1));for(let $=0;$<_[x];$++)O=$===0?i.calcReduceByAxis(m,b,_,v+1,w,S,A):A(O,i.calcReduceByAxis(m,b,_,v+1,w,S,A)),w+=I;return O}static calcReduceShape(m,b,_){const v=m.slice();for(let w=0;w<b.length;w++)v[b[w]]=_?1:0;return v.filter(w=>w!==0)}}n.ReduceUtil=i;class d{static adjustPoolAttributes(m,b,_,v,w,S){if(!m&&_.length!==b.length-2)throw new Error("length of specified kernel shapes should be 2 less than length of input dimensions");if(m)for(let A=0;A<b.length-2;A++)A>=_.length?_.push(b[A+2]):_[A]=b[A+2];for(let A=0;A<_.length;A++)if(A<v.length){if(v[A]<0)throw new Error("strides should be greater than or equal to 1")}else v.push(1);for(let A=0;A<_.length;A++)if(A<w.length){if(w[A]<0)throw new Error("dilations should be greater than or equal to 1")}else w.push(1);for(let A=0;A<2*_.length;A++)if(A<S.length){if(S[A]<0)throw new Error("pad should be greater than or equal to 1")}else S.push(0);for(let A=0;A<_.length;A++){if(_[A]<=0)throw new Error("kernel shapes need to be greater than 0");if(S[A]>=_[A]||S[A+_.length]>=_[A])throw new Error("pads should be smaller than kernel")}}static adjustPadsBasedOnAutoPad(m,b,_,v,w,S){if(S){if(w.length!==2*(m.length-2))throw new Error("length of pads should be twice the length of data dimensions");if(b.length!==m.length-2)throw new Error("length of strides should be the length of data dimensions");if(v.length!==m.length-2)throw new Error("length of kernel shapes should be the length of data dimensions");for(let A=0;A<m.length-2;A++)d.adjustPadAndReturnShape(m[A+2],b[A],_[A],v[A],w,A,A+m.length-2,S)}}static computePoolOutputShape(m,b,_,v,w,S,A){if(b.length<=0)throw new Error("input shape must be of size greater than 0");const O=[b[0],b[1]];return d.computeShapeHelper(m,b,O,_,v,w,S,A),O}static computeConvOutputShape(m,b,_,v,w,S,A){if(m.length<=0||b.length<=0)throw new Error("invalid input tensor dims or invalid filter tensor dims");const O=[m[0],b[0]];return d.computeShapeHelper(!1,m,O,_,v,w,S,A),O}static computeShapeHelper(m,b,_,v,w,S,A,O){if(m)for(let x=0;x<b.length-2;x++)_.push(1);else for(let x=0;x<b.length-2;x++)_.push(d.adjustPadAndReturnShape(b[x+2],v[x],w[x],S[x],A,x,x+b.length-2,O))}static adjustPadAndReturnShape(m,b,_,v,w,S,A,O){const x=_*(v-1)+1;if(!O||O==="NOTSET")return Math.floor((m+w[S]+w[A]-x)/b+1);switch(O){case"VALID":return w[S]=0,w[A]=0,Math.floor((m-x)/b+1);case"SAME_LOWER":case"SAME_UPPER":if(_!==1)throw new Error("Dilation not supported for SAME_UPPER or SAME_LOWER");{const I=((m+b-1)/b-1)*b+v-m;return w[S]=Math.floor(O==="SAME_LOWER"?(I+1)/2:I/2),w[A]=I-w[S],Math.floor((m+I-v)/b+1)}default:throw new Error("Unsupported AutoPad type")}}}n.PoolConvUtil=d,n.MIN_CLIP=-34028234663852886e22,n.MAX_CLIP=34028234663852886e22,n.decodeUtf8String=function(g){return new TextDecoder().decode(g)}},7967:(y,n)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.iterateExtraOptions=void 0,n.iterateExtraOptions=(o,l,c,f)=>{if(typeof 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transpose_data(y,n,o){const l=new Array(o.length),c=new Array(o.length);for(let h=o.length-1,p=1;h>=0;--h)c[h]=p,l[h]=n[o[h]],p*=l[h];const f=o.map((h,p)=>c[o.indexOf(p)]),a=new y.constructor(y.length);for(let h=0;h<y.length;++h){let p=0;for(let u=n.length-1,s=h;u>=0;--u)p+=s%n[u]*f[u],s=Math.floor(s/n[u]);a[p]=y[h]}return[a,l]}function softmax(y){const n=max(y)[0],o=y.map(f=>Math.exp(f-n)),l=o.reduce((f,a)=>f+a,0);return o.map(f=>f/l)}function log_softmax(y){return softmax(y).map(l=>Math.log(l))}function getTopItems(y,n=0){return y=Array.from(y).map((o,l)=>[l,o]).sort((o,l)=>l[1]-o[1]),n>0&&(y=y.slice(0,n)),y}function min(y){if(y.length===0)throw Error("Array must not be empty");let n=y[0],o=0;for(let l=1;l<y.length;++l)y[l]<n&&(n=y[l],o=l);return[n,o]}function max(y){if(y.length===0)throw Error("Array must not be empty");let n=y[0],o=0;for(let l=1;l<y.length;++l)y[l]>n&&(n=y[l],o=l);return[n,o]}function rfftfreq(y,n=1){if(!Number.isInteger(y))throw new TypeError(`n should be an integer, but ${y} given.`);const o=1/(y*n),l=Math.floor(y/2)+1,c=new Array(l);for(let f=0;f<l;++f)c[f]=f*o;return c}class FFT{constructor(n){if(this.size=n|0,this.size<=1||this.size&this.size-1)throw new Error("FFT size must be a power of two and bigger than 1");this._csize=n<<1,this.table=new Float32Array(this.size*2);for(let l=0;l<this.table.length;l+=2){const c=Math.PI*l/this.size;this.table[l]=Math.cos(c),this.table[l+1]=-Math.sin(c)}let o=0;for(let l=1;this.size>l;l<<=1)++o;this._width=o%2===0?o-1:o,this._bitrev=new Int32Array(1<<this._width);for(let l=0;l<this._bitrev.length;++l){this._bitrev[l]=0;for(let c=0;c<this._width;c+=2){const f=this._width-c-2;this._bitrev[l]|=(l>>>c&3)<<f}}}createComplexArray(){return new Float32Array(this._csize)}fromComplexArray(n,o){const l=o||new Array(n.length>>>1);for(let c=0;c<n.length;c+=2)l[c>>>1]=n[c];return l}toComplexArray(n,o){const l=o||this.createComplexArray();for(let c=0;c<l.length;c+=2)l[c]=n[c>>>1],l[c+1]=0;return l}completeSpectrum(n){const o=this._csize,l=o>>>1;for(let c=2;c<l;c+=2)n[o-c]=n[c],n[o-c+1]=-n[c+1]}transform(n,o){if(n===o)throw new Error("Input and output buffers must be different");this._transform4(n,o,1)}realTransform(n,o){if(n===o)throw new Error("Input and output buffers must be different");this._realTransform4(n,o,1)}inverseTransform(n,o){if(n===o)throw new Error("Input and output buffers must be different");this._transform4(n,o,-1);for(let l=0;l<n.length;++l)n[l]/=this.size}_transform4(n,o,l){const c=this._csize;let a=1<<this._width,h=c/a<<1,p,u,s=this._bitrev;if(h===4)for(p=0,u=0;p<c;p+=h,++u){const t=s[u];this._singleTransform2(o,n,p,t,a)}else for(p=0,u=0;p<c;p+=h,++u){const t=s[u];this._singleTransform4(o,n,p,t,a,l)}for(a>>=2;a>=2;a>>=2){h=c/a<<1;let t=h>>>2;for(p=0;p<c;p+=h){let e=p+t;for(let r=p,i=0;r<e;r+=2,i+=a){const d=r,g=d+t,m=g+t,b=m+t,_=n[d],v=n[d+1],w=n[g],S=n[g+1],A=n[m],O=n[m+1],x=n[b],I=n[b+1],$=this.table[i],B=l*this.table[i+1],L=w*$-S*B,N=w*B+S*$,H=this.table[2*i],M=l*this.table[2*i+1],j=A*H-O*M,Z=A*M+O*H,X=this.table[3*i],Q=l*this.table[3*i+1],ee=x*X-I*Q,ue=x*Q+I*X,Ae=_+j,xe=v+Z,oe=_-j,we=v-Z,ye=L+ee,ke=N+ue,Ne=l*(L-ee),Te=l*(N-ue);n[d]=Ae+ye,n[d+1]=xe+ke,n[g]=oe+Te,n[g+1]=we-Ne,n[m]=Ae-ye,n[m+1]=xe-ke,n[b]=oe-Te,n[b+1]=we+Ne}}}}_singleTransform2(n,o,l,c,f){const a=n[c],h=n[c+1],p=n[c+f],u=n[c+f+1];o[l]=a+p,o[l+1]=h+u,o[l+2]=a-p,o[l+3]=h-u}_singleTransform4(n,o,l,c,f,a){const h=f*2,p=f*3,u=n[c],s=n[c+1],t=n[c+f],e=n[c+f+1],r=n[c+h],i=n[c+h+1],d=n[c+p],g=n[c+p+1],m=u+r,b=s+i,_=u-r,v=s-i,w=t+d,S=e+g,A=a*(t-d),O=a*(e-g);o[l]=m+w,o[l+1]=b+S,o[l+2]=_+O,o[l+3]=v-A,o[l+4]=m-w,o[l+5]=b-S,o[l+6]=_-O,o[l+7]=v+A}_realTransform4(n,o,l){const c=this._csize;let a=1<<this._width,h=c/a<<1;var p,u,s=this._bitrev;if(h===4)for(p=0,u=0;p<c;p+=h,++u){const t=s[u];this._singleRealTransform2(o,n,p,t>>>1,a>>>1)}else for(p=0,u=0;p<c;p+=h,++u){const t=s[u];this._singleRealTransform4(o,n,p,t>>>1,a>>>1,l)}for(a>>=2;a>=2;a>>=2){h=c/a<<1;const t=h>>>1,e=t>>>1,r=e>>>1;for(p=0;p<c;p+=h)for(let i=0,d=0;i<=r;i+=2,d+=a){const g=p+i,m=g+e,b=m+e,_=b+e,v=n[g],w=n[g+1],S=n[m],A=n[m+1],O=n[b],x=n[b+1],I=n[_],$=n[_+1],B=this.table[d],L=l*this.table[d+1],N=S*B-A*L,H=S*L+A*B,M=this.table[2*d],j=l*this.table[2*d+1],Z=O*M-x*j,X=O*j+x*M,Q=this.table[3*d],ee=l*this.table[3*d+1],ue=I*Q-$*ee,Ae=I*ee+$*Q,xe=v+Z,oe=w+X,we=v-Z,ye=w-X,ke=N+ue,Ne=H+Ae,Te=l*(N-ue),$e=l*(H-Ae);if(n[g]=xe+ke,n[g+1]=oe+Ne,n[m]=we+$e,n[m+1]=ye-Te,i===0){n[b]=xe-ke,n[b+1]=oe-Ne;continue}if(i===r)continue;const Ce=p+e-i,Ee=p+t-i;n[Ce]=we+-l*$e,n[Ce+1]=-ye-l*Te,n[Ee]=xe+-l*ke,n[Ee+1]=-oe+l*Ne}}}_singleRealTransform2(n,o,l,c,f){const a=n[c],h=n[c+f];o[l]=a+h,o[l+1]=0,o[l+2]=a-h,o[l+3]=0}_singleRealTransform4(n,o,l,c,f,a){const h=f*2,p=f*3,u=n[c],s=n[c+f],t=n[c+h],e=n[c+p],r=u+t,i=u-t,d=s+e,g=a*(s-e);o[l]=r+d,o[l+1]=0,o[l+2]=i,o[l+3]=-g,o[l+4]=r-d,o[l+5]=0,o[l+6]=i,o[l+7]=g}}const ONNXTensor$1=ONNX.Tensor;class Tensor extends ONNXTensor$1{constructor(...n){return n[0]instanceof ONNX.Tensor?super(n[0].type,n[0].data,n[0].dims):super(...n),new Proxy(this,{get:(o,l)=>{if(typeof l=="string"){let c=Number(l);if(Number.isInteger(c))return o._getitem(c)}return o[l]},set:(o,l,c)=>o[l]=c})}*[Symbol.iterator](){const[n,...o]=this.dims;if(o.length>0){const l=o.reduce((c,f)=>c*f);for(let c=0;c<n;++c)yield this._subarray(c,l,o)}else yield*this.data}_getitem(n){const[o,...l]=this.dims;if(n>=o||n<-o)throw new Error(`Index ${n} is out of bounds for dimension 0 with size ${o}`);if(n<0&&(n+=o),l.length>0){const c=l.reduce((f,a)=>f*a);return this._subarray(n,c,l)}else return new Tensor(this.type,[this.data[n]],l)}indexOf(n){for(let o=0;o<this.data.length;++o)if(this.data[o]==n)return o;return-1}_subarray(n,o,l){let c=this.data.subarray(n*o,(n+1)*o);return new Tensor(this.type,c,l)}item(){if(this.data.length!==1)throw new Error(`a Tensor with ${this.data.length} elements cannot be converted to Scalar`);return this.data[0]}tolist(){return reshape(this.data,this.dims)}sigmoid(){return this.clone().sigmoid_()}sigmoid_(){for(let n=0;n<this.data.length;++n)this.data[n]=1/(1+Math.exp(-this.data[n]));return this}clone(){return new Tensor(this.type,this.data.slice(),this.dims.slice())}slice(...n){let o=[],l=[];for(let p=0;p<this.dims.length;++p){let u=n[p];if(u==null)l.push([0,this.dims[p]]),o.push(this.dims[p]);else if(typeof u=="number"){if(u<-this.dims[p]||u>=this.dims[p])throw new Error(`IndexError: index ${u} is out of bounds for dimension ${p} with size ${this.dims[p]}`);u<0&&(u+=this.dims[p]),l.push([u,u+1])}else if(Array.isArray(u)&&u.length===2){if(u[0]>u[1])throw new Error(`Invalid slice: ${u}`);let s=[Math.max(u[0],0),Math.min(u[1],this.dims[p])];l.push(s),o.push(s[1]-s[0])}else throw new Error(`Invalid slice: ${u}`)}let c=l.map(([p,u])=>u-p),f=c.reduce((p,u)=>p*u),a=new this.data.constructor(f);const h=new Array(this.dims.length);for(let p=c.length-1,u=1;p>=0;--p)h[p]=u,u*=this.dims[p];for(let p=0;p<f;++p){let u=0;for(let s=c.length-1,t=p;s>=0;--s){const e=c[s];u+=(t%e+l[s][0])*h[s],t=Math.floor(t/e)}a[p]=this.data[u]}return new Tensor(this.type,a,o)}transpose(...n){return transpose(this,n)}sum(n=null,o=!1){return this.norm(1,n,o)}norm(n="fro",o=null,l=!1){if(n==="fro")n=2;else if(typeof n=="string")throw Error(`Unsupported norm: ${n}`);if(o===null){let a=this.data.reduce((h,p)=>h+p**n,0)**(1/n);return new Tensor(this.type,[a],[1])}o<0&&(o+=this.dims.length);const c=this.dims.slice();c[o]=1;const f=new this.data.constructor(this.data.length/this.dims[o]);for(let a=0;a<this.data.length;++a){let h=0;for(let p=this.dims.length-1,u=a,s=1;p>=0;--p){const t=this.dims[p];if(p!==o){const e=u%t;h+=e*s,s*=c[p]}u=Math.floor(u/t)}f[h]+=this.data[a]**n}if(n!==1)for(let a=0;a<f.length;++a)f[a]=f[a]**(1/n);return l||c.splice(o,1),new Tensor(this.type,f,c)}normalize_(n=2,o=1){o<0&&(o+=this.dims.length);const l=this.norm(n,o,!0);for(let c=0;c<this.data.length;++c){let f=0;for(let a=this.dims.length-1,h=c,p=1;a>=0;--a){const u=this.dims[a];if(a!==o){const s=h%u;f+=s*p,p*=this.dims[a]}h=Math.floor(h/u)}this.data[c]/=l.data[f]}return this}normalize(n=2,o=1){return this.clone().normalize_(n,o)}stride(){const n=new Array(this.dims.length);for(let o=this.dims.length-1,l=1;o>=0;--o)n[o]=l,l*=this.dims[o];return n}squeeze(n=null){return new Tensor(this.type,this.data,calc_squeeze_dims(this.dims,n))}squeeze_(n=null){return this.dims=calc_squeeze_dims(this.dims,n),this}unsqueeze(n=null){return new Tensor(this.type,this.data,calc_unsqueeze_dims(this.dims,n))}unsqueeze_(n=null){return this.dims=calc_unsqueeze_dims(this.dims,n),this}}function reshape(y,n){const o=y.length,l=n.reduce((f,a)=>f*a);if(o!==l)throw Error(`cannot reshape array of size ${o} into shape (${n})`);let c=y;for(let f=n.length-1;f>=0;f--)c=c.reduce((a,h)=>{let p=a[a.length-1];return p.length<n[f]?p.push(h):a.push([h]),a},[[]]);return c[0]}function transpose(y,n){const[o,l]=transpose_data(y.data,y.dims,n);return new Tensor(y.type,o,l)}function cat(y){if(y.length===0)return y[0];let n=y[0].type,o=[...y[0].dims];o[0]=y.length;let l=0;for(let a of y)l+=a.data.length;let c=new y[0].data.constructor(l),f=0;for(let a of y)c.set(a.data,f),f+=a.data.length;return new Tensor(n,c,o)}function interpolate(y,[n,o],l="bilinear",c=!1){const f=y.dims.at(-3)??1,a=y.dims.at(-2),h=y.dims.at(-1);let p=interpolate_data(y.data,[f,a,h],[n,o],l,c);return new Tensor(y.type,p,[f,n,o])}function mean_pooling(y,n){let o=[y.dims[0],y.dims[2]],l=new y.data.constructor(o[0]*o[1]),[c,f,a]=y.dims,h=0;for(let p=0;p<c;++p){let u=p*a*f;for(let s=0;s<a;++s){let t=0,e=0,r=p*f,i=u+s;for(let g=0;g<f;++g){let m=Number(n.data[r+g]);e+=m,t+=y.data[i+g*a]*m}let d=t/e;l[h++]=d}}return new Tensor(y.type,l,o)}function calc_squeeze_dims(y,n){return y=y.slice(),n===null?y=y.filter(o=>o!==1):typeof n=="number"?y[n]===1&&y.splice(n,1):Array.isArray(n)&&(y=y.filter((o,l)=>o!==1||!n.includes(l))),y}function calc_unsqueeze_dims(y,n){return y=y.slice(),n<0&&(n=(n%y.length+y.length)%y.length),y.splice(n,0,1),y}async function loadTokenizer(y,n){return await Promise.all([getModelJSON(y,"tokenizer.json",!0,n),getModelJSON(y,"tokenizer_config.json",!0,n)])}function createPattern(y){return y.Regex?new RegExp(y.Regex,"gu"):y.String?y.String:(console.warn("Unknown pattern type:",y),null)}function clean_up_tokenization(y){return y.replace(/ \./g,".").replace(/ \?/g,"?").replace(/ \!/g,"!").replace(/ ,/g,",").replace(/ \' /g,"'").replace(/ n\'t/g,"n't").replace(/ \'m/g,"'m").replace(/ \'s/g,"'s").replace(/ \'ve/g,"'ve").replace(/ \'re/g,"'re")}function fuse(y,n){let o=[],l=0;for(;l<y.length;){if(o.push(y[l]),y[l]!==n){++l;continue}for(;l<y.length&&y[l]===n;)++l}return o}function whitespace_split(y){return y.match(/\S+/g)||[]}class TokenizerModel extends Callable{constructor(n){super(),this.config=n,this.vocab=[],this.tokens_to_ids=new Map,this.unk_token_id=void 0,this.unk_token=void 0,this.end_of_word_suffix=void 0,this.fuse_unk=!1}static fromConfig(n,...o){switch(n.type){case"WordPiece":return new WordPieceTokenizer(n);case"Unigram":return new Unigram(n,...o);case"BPE":return new BPE(n,...o);default:throw new Error(`Unknown TokenizerModel type: ${n.type}`)}}_call(n){return this.encode(n)}encode(n){throw Error("encode should be implemented in subclass.")}convert_tokens_to_ids(n){let o=n.map(l=>this.tokens_to_ids.get(l)??this.unk_token_id);return this.fuse_unk&&(o=fuse(o,this.unk_token_id)),o}convert_ids_to_tokens(n){return n.map(o=>this.vocab[o]??this.unk_token)}}class WordPieceTokenizer extends TokenizerModel{constructor(n){super(n),this.tokens_to_ids=n.vocab,this.unk_token_id=this.tokens_to_ids.get(n.unk_token),this.unk_token=n.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[o,l]of this.tokens_to_ids)this.vocab[l]=o}encode(n){let o=[];for(let l of n){let c=[...l],f=!1,a=0,h=[];for(;a<c.length;){let p=c.length,u=null;for(;a<p;){let s=c.slice(a,p).join("");if(a>0&&(s=this.config.continuing_subword_prefix+s),this.tokens_to_ids.has(s)){u=s;break}--p}if(u===null){f=!0;break}h.push(u),a=p}f?o.push(this.unk_token):o.push(...h)}return o}}class Unigram extends TokenizerModel{constructor(n,o){super(n),this.vocab=new Array(n.vocab.size),this.scores=new Array(n.vocab.size);let l=0;n.vocab.forEach((c,f)=>{this.vocab[l]=f,this.scores[l]=c,++l}),this.unk_token_id=n.unk_id,this.unk_token=this.vocab[n.unk_id],this.tokens_to_ids=new Map(this.vocab.map((c,f)=>[c,f])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=o.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=min(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new CharTrie,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(n){const o=n.sentence,l=o.length;let c=0;for(;c<l;){let a=!1;for(let h of this.trie.commonPrefixSearch(o.slice(c))){const p=this.tokens_to_ids.get(h),u=this.scores[p],s=h.length;n.insert(c,s,u,p),!a&&s===1&&(a=!0)}a||n.insert(c,1,this.unkScore,this.unk_token_id),c+=1}}tokenize(n){const o=new TokenLattice(n,this.bosTokenId,this.eosTokenId);return this.populateNodes(o),o.tokens()}encode(n){let o=[];for(let l of n){const c=this.tokenize(l);o.push(...c)}return o}}const BYTES_TO_UNICODE=(()=>{const y=[...Array.from({length:"~".charCodeAt(0)-"!".charCodeAt(0)+1},(c,f)=>f+"!".charCodeAt(0)),...Array.from({length:"¬".charCodeAt(0)-"¡".charCodeAt(0)+1},(c,f)=>f+"¡".charCodeAt(0)),...Array.from({length:"ÿ".charCodeAt(0)-"®".charCodeAt(0)+1},(c,f)=>f+"®".charCodeAt(0))];let n=y.slice(),o=0;for(let c=0;c<256;++c)y.includes(c)||(y.push(c),n.push(256+o),o+=1);let l=n.map(c=>String.fromCharCode(c));return Object.fromEntries(y.map((c,f)=>[c,l[f]]))})(),UNICODE_TO_BYTES=reverseDictionary(BYTES_TO_UNICODE);class BPE extends TokenizerModel{constructor(n){super(n),this.tokens_to_ids=n.vocab,this.unk_token_id=this.tokens_to_ids.get(n.unk_token),this.unk_token=n.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[o,l]of this.tokens_to_ids)this.vocab[l]=o;this.bpe_ranks=Object.fromEntries(n.merges.map((o,l)=>[o,l])),this.merges=n.merges.map(o=>o.split(/\s+/)),this.end_of_word_suffix=n.end_of_word_suffix,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.cache=Object.create(null),this.fuse_unk??(this.fuse_unk=this.config.fuse_unk)}get_pairs(n){let o=new Set,l=n[0];for(let c=1;c<n.length;++c){let f=n[c];o.add(`${l} ${f}`),l=f}return Array.from(o)}bpe(n){if(n in this.cache)return this.cache[n];let o=Array.from(n);this.end_of_word_suffix&&(o[o.length-1]+=this.end_of_word_suffix);let l=this.get_pairs(o);if(!l.length)return this.end_of_word_suffix&&(n+=this.end_of_word_suffix),n;for(;;){let f=l.reduce((t,e)=>{let r=this.bpe_ranks[t]??1/0,i=this.bpe_ranks[e]??1/0;return r<=i?t:e});if(!(f in this.bpe_ranks))break;let[a,h]=f.split(/\s+/g),p=[],u=0,s=-1;for(;u<o.length;){try{if(s=o.indexOf(a,u),s===-1)throw"Error"}catch{p.push(...o.slice(u));break}p.push(...o.slice(u,s)),u=s,o[u]===a&&u<o.length-1&&o[u+1]===h?(p.push(a+h),u+=2):(p.push(o[u]),u+=1)}if(o=p,o.length===1)break;l=this.get_pairs(o)}let c=o.join(" ");return this.cache[n]=c,c}encode(n){let o=[];for(let l of n){let c=this.bpe(l).split(" ");for(let f of c)this.tokens_to_ids.has(f)?o.push(f):this.byte_fallback?o.push(...Array.from(this.text_encoder.encode(f)).map(a=>`<0x${a.toString(16).toUpperCase().padStart(2,"0")}>`)):o.push(this.unk_token)}return o}}class Normalizer extends Callable{constructor(n){super(),this.config=n}static fromConfig(n){if(n===null)return null;switch(n.type){case"BertNormalizer":return new BertNormalizer(n);case"Precompiled":return new Precompiled(n);case"Sequence":return new NormalizerSequence(n);case"Replace":return new Replace(n);case"NFC":return new NFC(n);case"NFKD":return new NFKD(n);case"StripAccents":return new StripAccents(n);case"Lowercase":return new Lowercase(n);case"Prepend":return new Prepend(n);default:throw new Error(`Unknown Normalizer type: ${n.type}`)}}normalize(n){throw Error("normalize should be implemented in subclass.")}_call(n){return this.normalize(n)}}class Replace extends Normalizer{normalize(n){let o=createPattern(this.config.pattern);return o===null||(n=n.replaceAll(o,this.config.content)),n}}class NFC extends Normalizer{normalize(n){return n=n.normalize("NFC"),n}}class NFKD extends Normalizer{normalize(n){return n=n.normalize("NFKD"),n}}class StripAccents extends Normalizer{normalize(n){return n=n.replace(/[\u0300-\u036f]/g,""),n}}class Lowercase extends Normalizer{normalize(n){return n=n.toLowerCase(),n}}class Prepend extends Normalizer{normalize(n){return n=this.config.prepend+n,n}}class NormalizerSequence extends Normalizer{constructor(n){super(n),this.normalizers=n.normalizers.map(o=>Normalizer.fromConfig(o))}normalize(n){return this.normalizers.reduce((o,l)=>l.normalize(o),n)}}class BertNormalizer extends Normalizer{_tokenize_chinese_chars(n){let o=[];for(let l=0;l<n.length;++l){let c=n[l],f=c.charCodeAt(0);this._is_chinese_char(f)?(o.push(" "),o.push(c),o.push(" ")):o.push(c)}return o.join("")}_is_chinese_char(n){return n>=19968&&n<=40959||n>=13312&&n<=19903||n>=131072&&n<=173791||n>=173824&&n<=177983||n>=177984&&n<=178207||n>=178208&&n<=183983||n>=63744&&n<=64255||n>=194560&&n<=195103}stripAccents(n){return n.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}normalize(n){return this.config.handle_chinese_chars&&(n=this._tokenize_chinese_chars(n)),this.config.lowercase?(n=n.toLowerCase(),this.config.strip_accents!==!1&&(n=this.stripAccents(n))):this.config.strip_accents&&(n=this.stripAccents(n)),n}}class PreTokenizer extends Callable{static fromConfig(n){if(n===null)return null;switch(n.type){case"BertPreTokenizer":return new BertPreTokenizer(n);case"Sequence":return new PreTokenizerSequence(n);case"WhitespaceSplit":return new WhitespaceSplit(n);case"Metaspace":return new MetaspacePreTokenizer(n);case"ByteLevel":return new ByteLevelPreTokenizer(n);case"Split":return new SplitPreTokenizer(n);default:throw new Error(`Unknown PreTokenizer type: ${n.type}`)}}pre_tokenize_text(n){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(n){let o=[];return Array.isArray(n)?o=n.map(l=>this.pre_tokenize_text(l)):o=this.pre_tokenize_text(n),o.flat()}_call(n){return this.pre_tokenize(n)}}class BertPreTokenizer extends PreTokenizer{constructor(n){super();const o="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E";this.pattern=new RegExp(`[^\\s${o}]+|[${o}]`,"gu")}pre_tokenize_text(n){return n.trim().match(this.pattern)||[]}}class ByteLevelPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=/'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+/gu,this.byte_encoder=BYTES_TO_UNICODE,this.text_encoder=new TextEncoder}pre_tokenize_text(n){return(this.use_regex?n.match(this.pattern)||[]:[n]).map(l=>(this.add_prefix_space&&!l.startsWith(" ")&&(l=" "+l),l=Array.from(this.text_encoder.encode(l),c=>this.byte_encoder[c]).join(""),l))}}class SplitPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n}pre_tokenize_text(n){let o=createPattern(this.config.pattern);if(o===null)return[];switch(this.config.behavior.toLowerCase()){case"isolated":case"removed":return n.match(o)||[];default:return console.warn(`Unknown split behavior: "${this.config.behavior}"`),[]}}}class PostProcessor extends Callable{constructor(n){super(),this.config=n}static fromConfig(n){switch(n.type){case"TemplateProcessing":return new TemplateProcessing(n);case"ByteLevel":return new ByteLevelPostProcessor(n);case"RobertaProcessing":return new RobertaProcessing(n);default:throw new Error(`Unknown PostProcessor type: ${n.type}`)}}post_process(n,...o){throw Error("post_process should be implemented in subclass.")}_call(n,...o){return this.post_process(n,...o)}}class RobertaProcessing extends PostProcessor{constructor(n){super(n),this.cls=n.cls[0],this.sep=n.sep[0]}post_process(n,o=null){return n=[this.cls,...n,this.sep],o!==null&&(n=[...n,this.sep,...o,this.sep]),n}}class TemplateProcessing extends PostProcessor{constructor(n){super(n),this.single=n.single,this.pair=n.pair}post_process(n,o=null){let l=o===null?this.single:this.pair,c=[];for(let f of l)"SpecialToken"in f?c.push(f.SpecialToken.id):"Sequence"in f&&(f.Sequence.id==="A"?c.push(...n):f.Sequence.id==="B"&&c.push(...o));return c}}class ByteLevelPostProcessor extends PostProcessor{post_process(n){return n}}class Decoder extends Callable{constructor(n){super(),this.config=n,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=n.trim_offsets}static fromConfig(n){switch(n.type){case"WordPiece":return new WordPieceDecoder(n);case"Metaspace":return new MetaspaceDecoder(n);case"ByteLevel":return new ByteLevelDecoder(n);case"Replace":return new ReplaceDecoder(n);case"ByteFallback":return new ByteFallback(n);case"Fuse":return new FuseDecoder(n);case"Strip":return new StripDecoder(n);case"Sequence":return new DecoderSequence(n);default:throw new Error(`Unknown Decoder type: ${n.type}`)}}_call(n){return this.decode(n)}decode(n){return this.decode_chain(n).join("")}decode_chain(n){throw Error("`decode_chain` should be implemented in subclass.")}}class ReplaceDecoder extends Decoder{constructor(n){super(n)}decode_chain(n){let o=createPattern(this.config.pattern);return o===null?n:n.map(l=>l.replaceAll(o,this.config.content))}}class ByteFallback extends Decoder{constructor(n){super(n),this.text_decoder=new TextDecoder}decode_chain(n){let o=[],l=[];for(let c of n){let f=null;if(c.length===6&&c.startsWith("<0x")&&c.endsWith(">")){let a=parseInt(c.slice(3,5),16);isNaN(a)||(f=a)}if(f!==null)l.push(f);else{if(l.length>0){let a=this.text_decoder.decode(Uint8Array.from(l));o.push(a),l=[]}o.push(c)}}if(l.length>0){let c=this.text_decoder.decode(Uint8Array.from(l));o.push(c),l=[]}return o}}class FuseDecoder extends Decoder{constructor(n){super(n)}decode_chain(n){return[n.join("")]}}class StripDecoder extends Decoder{constructor(n){super(n),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(n){return n.map(o=>{let l=0;for(let f=0;f<this.start&&o[f]===this.content;++f){l=f+1;continue}let c=o.length;for(let f=0;f<this.stop;++f){const a=o.length-f-1;if(o[a]===this.content){c=a;continue}else break}return o.slice(l,c)})}}class WordPieceDecoder extends Decoder{constructor(n){super(n),this.cleanup=n.cleanup}decode_chain(n){return n.map((o,l)=>(l!==0&&(o.startsWith(this.config.prefix)?o=o.replace(this.config.prefix,""):o=" "+o),this.cleanup&&(o=clean_up_tokenization(o)),o))}}class ByteLevelDecoder extends Decoder{constructor(n){super(n),this.byte_decoder=UNICODE_TO_BYTES,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(n){let o=n.join(""),l=new Uint8Array([...o].map(f=>this.byte_decoder[f]));return this.text_decoder.decode(l)}decode_chain(n){let o=[],l=[];for(let c of n)this.added_tokens.includes(c)?(l.length>0&&(o.push(this.convert_tokens_to_string(l)),l=[]),o.push(c)):l.push(c);return l.length>0&&o.push(this.convert_tokens_to_string(l)),o}}class DecoderSequence extends Decoder{constructor(n){super(n),this.decoders=n.decoders.map(o=>Decoder.fromConfig(o))}decode_chain(n){return this.decoders.reduce((o,l)=>l.decode_chain(o),n)}}class MetaspacePreTokenizer extends PreTokenizer{constructor(n){super(),this.addPrefixSpace=n.add_prefix_space,this.replacement=n.replacement,this.strRep=n.str_rep||this.replacement}pre_tokenize(n){typeof n=="string"&&(n=n.trimStart().split(/\s+/));const o=[];for(let l of n){let c=l.replaceAll(" ",this.strRep);this.addPrefixSpace&&!c.startsWith(this.replacement)&&(c=this.strRep+c),o.push(c)}return o}}class MetaspaceDecoder extends Decoder{constructor(n){super(n),this.addPrefixSpace=n.add_prefix_space,this.replacement=n.replacement}decode_chain(n){let o=[];for(let l=0;l<n.length;++l){let c=n[l].replaceAll(this.replacement," ");this.addPrefixSpace&&l==0&&c.startsWith(" ")&&(c=c.substring(1)),o.push(c)}return o}}class Precompiled extends Normalizer{constructor(n){super(n),this.charsmap=n.precompiled_charsmap}normalize(n){return n}}class PreTokenizerSequence extends PreTokenizer{constructor(n){super(),this.tokenizers=n.pretokenizers.map(o=>PreTokenizer.fromConfig(o))}pre_tokenize_text(n){return typeof n=="string"&&(n=[n]),this.tokenizers.reduce((o,l)=>l.pre_tokenize(o),n)}}class WhitespaceSplit extends PreTokenizer{constructor(n){super()}pre_tokenize_text(n){return whitespace_split(n)}}class PreTrainedTokenizer extends Callable{constructor(n,o){super(),this.normalizer=Normalizer.fromConfig(n.normalizer),this.pre_tokenizer=PreTokenizer.fromConfig(n.pre_tokenizer),n.model.vocab&&(Array.isArray(n.model.vocab)||(n.model.vocab=Object.entries(n.model.vocab)),n.model.vocab=new Map(n.model.vocab)),this.model=TokenizerModel.fromConfig(n.model,o),this.post_processor=PostProcessor.fromConfig(n.post_processor),this.decoder=Decoder.fromConfig(n.decoder),this.decoder.end_of_word_suffix=this.model.end_of_word_suffix,this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(let l of n.added_tokens){let c=l.id,f=l.content;this.added_tokens.push(f),this.model.tokens_to_ids.set(f,c),this.model.vocab[c]=f,l.special&&(this.special_tokens.push(f),this.all_special_ids.push(c))}this.decoder.added_tokens=this.added_tokens,this.added_tokens_regex=new RegExp("("+this.added_tokens.map(escapeRegExp).join("|")+")"),this.mask_token=this.getToken(o,"mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken(o,"pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken(o,"sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.model_max_length=o.model_max_length,this.remove_space=o.remove_space,this.clean_up_tokenization_spaces=o.clean_up_tokenization_spaces??!0,this.padding_side="right"}getToken(n,...o){for(let l of o){let c=n[l];if(c)if(typeof c=="object"){if(c.__type==="AddedToken")return c.content;throw Error(`Unknown token: ${c}`)}else return c}return null}static async from_pretrained(n,{progress_callback:o=null,config:l=null,cache_dir:c=null,local_files_only:f=!1,revision:a="main"}={}){let h=await loadTokenizer(n,{progress_callback:o,config:l,cache_dir:c,local_files_only:f,revision:a});return new this(...h)}prepare_model_inputs(n){return n}_call(n,{text_pair:o=null,padding:l=!1,truncation:c=null,max_length:f=null,return_tensor:a=!0}={}){let h;if(Array.isArray(n)){if(n.length===0)throw Error("text array must be non-empty");if(o!==null){if(Array.isArray(o)){if(n.length!==o.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");h=n.map((t,e)=>this.encode(t,o[e]))}else h=n.map(t=>this.encode(t))}else{if(n===null)throw Error("text may not be null");if(Array.isArray(o))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");h=[this.encode(n,o)]}let p=Math.max(...h.map(t=>t.length));f===null&&(f=p),f=Math.min(f,this.model_max_length);let u=[];if(l||c)for(let t=0;t<h.length;++t)if(h[t].length===f){u.push(new Array(h[t].length).fill(1));continue}else if(h[t].length>f)c&&(h[t]=h[t].slice(0,f)),u.push(new Array(h[t].length).fill(1));else if(l){let e=f-h[t].length;this.padding_side==="right"?(u.push(new Array(h[t].length).fill(1).concat(new Array(e).fill(0))),h[t].push(...new Array(e).fill(this.pad_token_id))):(u.push(new Array(e).fill(0).concat(new Array(h[t].length).fill(1))),h[t].unshift(...new Array(e).fill(this.pad_token_id)))}else u.push(new Array(h[t].length).fill(1));else u=h.map(t=>new Array(t.length).fill(1));if(a){if(!(l&&c)&&h.some(e=>e.length!==h[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");let t=[h.length,h[0].length];h=new Tensor("int64",BigInt64Array.from(h.flat().map(BigInt)),t),u=new Tensor("int64",BigInt64Array.from(u.flat().map(BigInt)),t)}else Array.isArray(n)||(h=h[0],u=u[0]);let s={input_ids:h,attention_mask:u};return s=this.prepare_model_inputs(s),s}_encode_text(n){return n===null?null:n.split(this.added_tokens_regex).filter(c=>c).map(c=>{if(this.added_tokens.includes(c))return c;{this.remove_space===!0&&(c=c.trim().split(/\s+/).join(" ")),this.normalizer!==null&&(c=this.normalizer(c));let f=this.pre_tokenizer!==null?this.pre_tokenizer(c):[c];return this.model(f)}}).flat()}encode(n,o=null){let l=this._encode_text(n),c=this._encode_text(o),f=this.post_processor(l,c);return this.model.convert_tokens_to_ids(f)}batch_decode(n,o={}){return n.map(l=>this.decode(l,o))}decode(n,o={}){if(!Array.isArray(n)||n.length===0||!isIntegralNumber(n[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(n,o)}decode_single(n,{skip_special_tokens:o=!1,clean_up_tokenization_spaces:l=null}){let c=this.model.convert_ids_to_tokens(n);o&&(c=c.filter(a=>!this.special_tokens.includes(a)));let f=this.decoder(c);return this.decoder.end_of_word_suffix&&(f=f.replaceAll(this.decoder.end_of_word_suffix," "),o&&(f=f.trim())),(l??this.clean_up_tokenization_spaces)&&(f=clean_up_tokenization(f)),f}}function add_token_types(y){if(y.input_ids instanceof Tensor)y.token_type_ids=new Tensor("int64",new BigInt64Array(y.input_ids.data.length),y.input_ids.dims);else if(Array.isArray(y.input_ids))Array.isArray(y.input_ids[0])?y.token_type_ids=y.input_ids.map(n=>new Array(n.length).fill(0)):y.token_type_ids=new Array(y.input_ids.length).fill(0);else throw new Error("Input ids must be a Tensor or an Array");return y}class BertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class AlbertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class MobileBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class SqueezeBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class DistilBertTokenizer extends PreTrainedTokenizer{}class T5Tokenizer extends PreTrainedTokenizer{}class GPT2Tokenizer extends PreTrainedTokenizer{}class BartTokenizer extends PreTrainedTokenizer{}class RobertaTokenizer extends PreTrainedTokenizer{}class BloomTokenizer extends PreTrainedTokenizer{}class LlamaTokenizer extends PreTrainedTokenizer{prepare_model_inputs(n){return add_token_types(n)}}class NllbTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(l=>this.languageRegex.test(l))}_build_translation_inputs(n,o,l){if(!this.language_codes.includes(l.tgt_lang))throw new Error(`Target language code "${l.tgt_lang}" is not valid. Must be one of: {${this.language_codes.join(", ")}}`);if(l.src_lang!==void 0){if(!this.language_codes.includes(l.src_lang))throw new Error(`Source language code "${l.src_lang}" is not valid. Must be one of: {${this.language_codes.join(", ")}}`);for(let c of this.post_processor.config.single)if("SpecialToken"in c&&this.languageRegex.test(c.SpecialToken.id)){c.SpecialToken.id=l.src_lang;break}}return l.forced_bos_token_id=this.model.convert_tokens_to_ids([l.tgt_lang])[0],this._call(n,o)}}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(([y,n])=>[n,y]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);class WhisperTokenizer extends PreTrainedTokenizer{_decode_asr(n,{return_timestamps:o=!1,return_language:l=!1,time_precision:c=null,force_full_sequences:f=!0}={}){if(c===null)throw Error("Must specify time_precision");let a=null;function h(){return{language:a,timestamp:[null,null],text:""}}const p=[];let u=h(),s=0;const t=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let e=[],r=!1,i=null;const d=new Set(this.all_special_ids);for(let b of n){const _=b.tokens;let v=null,w=t;if("stride"in b){const[A,O,x]=b.stride;if(s-=O,i=A-x,O&&(w=O/c+t),x)for(let I=_.length-1;I>=0;--I){const $=_[I];if($>=t){if(v!==null&&($-t)*c<i)break;v=$}}}let S=[];for(const A of _)if(d.has(A)){const O=this.decode([A]);if(O[0]==="["&&O[O.length-1]==="]"){const x=WHISPER_LANGUAGE_MAPPING.get(O.slice(1,-1));if(x!==void 0){if(a!==null&&x!==a&&!o){e.push(S);const I=this.findLongestCommonSequence(e),$=this.decode(I);u.text=$,p.push(u),e=[],S=[],u=h()}a=u.language=x}}}else if(A>=t){const O=(A-t)*c+s,x=Math.round(O*100)/100;if(v!==null&&A>=v)r=!0;else if(r||e.length>0&&A<w)r=!1;else if(u.timestamp[0]===null)u.timestamp[0]=x;else if(x!==u.timestamp[0]){u.timestamp[1]=O,e.push(S);const I=this.findLongestCommonSequence(e),$=this.decode(I);u.text=$,p.push(u),e=[],S=[],u=h()}}else S.push(A);if("stride"in b){const[A,O,x]=b.stride;s+=A-x}S.length>0?e.push(S):e.every(A=>A.length===0)&&(u=h(),e=[],S=[])}if(e.length>0){if(f&&o)throw new Error("There was an error while processing timestamps, we haven't found a timestamp as last token.");const b=this.findLongestCommonSequence(e),_=this.decode(b);u.text=_,p.push(u)}let g=Object.create(null);const m=p.map(b=>b.text).join("");if(o||l){for(let b=0;b<p.length;++b){const _=p[b];o||delete _.timestamp,l||delete _.language}g={chunks:p}}return[m,g]}findLongestCommonSequence(n){let o=n[0],l=o.length,c=[];for(let f=1;f<n.length;++f){const a=n[f];let h=0,p=[l,l,0,0];const u=a.length;for(let g=1;g<l+u;++g){const m=g/1e4,b=Math.max(0,l-g),_=Math.min(l,l+u-g),v=o.slice(b,_),w=Math.max(0,g-l),S=Math.min(u,g),A=a.slice(w,S);if(v.length!==A.length)throw new Error("There is a bug within whisper `decode_asr` function, please report it. Dropping to prevent bad inference.");const O=v.filter((I,$)=>I===A[$]).length,x=O/g+m;O>1&&x>h&&(h=x,p=[b,_,w,S])}const[s,t,e,r]=p,i=Math.floor((t+s)/2),d=Math.floor((r+e)/2);c.push(...o.slice(0,i)),o=a.slice(d),l=o.length}return c.push(...o),c}get_decoder_prompt_ids({language:n=null,task:o=null,no_timestamps:l=!0}={}){let c=[];if(n){n=n.toLowerCase();let f=WHISPER_TO_LANGUAGE_CODE_MAPPING.get(n);if(f===void 0)if(WHISPER_LANGUAGE_MAPPING.has(n))f=n;else{const p=n.length===2?WHISPER_LANGUAGE_MAPPING.keys():WHISPER_LANGUAGE_MAPPING.values();throw new Error(`Language "${n}" is not supported. Must be one of: ${JSON.stringify(p)}`)}let a=this.model.tokens_to_ids.get(`<|${f}|>`);if(a===void 0)throw new Error(`Unable to find language "${f}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);c.push(a)}else c.push(null);if(o){if(o=o.toLowerCase(),o!=="transcribe"&&o!=="translate")throw new Error(`Task "${o}" is not supported. Must be one of: ["transcribe", "translate"]`);let f=this.model.tokens_to_ids.get(`<|${o}|>`);if(f===void 0)throw new Error(`Unable to find task "${o}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);c.push(f)}else c.push(null);if(l){let f=this.model.tokens_to_ids.get("<|notimestamps|>");if(f===void 0)throw new Error('Unable to find "<|notimestamps|>" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.');c.push(f)}return c.map((f,a)=>[a+1,f]).filter(f=>f[1]!==null)}}class CodeGenTokenizer extends PreTrainedTokenizer{}class CLIPTokenizer extends PreTrainedTokenizer{}class MarianTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter(l=>this.languageRegex.test(l)),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(n){if(n===null)return null;let[o,...l]=n.trim().split(this.languageRegex);if(l.length===0)return super._encode_text(o);if(l.length===2){let[c,f]=l;return this.supported_language_codes.includes(c)||console.warn(`Unsupported language code "${c}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),[c,...super._encode_text(f)]}}}class CharTrie{constructor(){this.root=CharTrieNode.default()}extend(n){for(let o of n)this.push(o)}push(n){let o=this.root;for(let l of n){let c=o.children.get(l);c===void 0&&(c=CharTrieNode.default(),o.children.set(l,c)),o=c}o.isLeaf=!0}*commonPrefixSearch(n){let o=this.root,l="";for(let c=0;c<n.length&&o!==void 0;++c){const f=n[c];l+=f,o=o.children.get(f),o!==void 0&&o.isLeaf&&(yield l)}}}class CharTrieNode{constructor(n,o){this.isLeaf=n,this.children=o}static default(){return new CharTrieNode(!1,new Map)}}class TokenLattice{constructor(n,o,l){this.sentence=n,this.len=n.length,this.bosTokenId=o,this.eosTokenId=l,this.nodes=[],this.beginNodes=new Array(this.len+1),this.endNodes=new Array(this.len+1);for(let a=0;a<this.len+1;++a)this.beginNodes[a]=[],this.endNodes[a]=[];const c=new TokenLatticeNode(this.bosTokenId,0,0,0,0),f=new TokenLatticeNode(this.eosTokenId,1,this.len,0,0);this.nodes.push(c.clone()),this.nodes.push(f.clone()),this.beginNodes[this.len].push(f),this.endNodes[0].push(c)}insert(n,o,l,c){const f=this.nodes.length,a=new TokenLatticeNode(c,f,n,o,l);this.beginNodes[n].push(a),this.endNodes[n+o].push(a),this.nodes.push(a)}viterbi(){const n=this.len;let o=0;for(;o<=n;){if(this.beginNodes[o].length==0)return[];for(let h of this.beginNodes[o]){h.prev=null;let p=0,u=null;for(let s of this.endNodes[o]){const t=s.backtraceScore+h.score;(u===null||t>p)&&(u=s.clone(),p=t)}if(u!==null)h.prev=u,h.backtraceScore=p;else return[]}++o}const l=[],f=this.beginNodes[n][0].prev;if(f===null)return[];let a=f.clone();for(;a.prev!==null;)l.push(a.clone()),a=a.clone().prev.clone();return l.reverse(),l}piece(n){return this.sentence.slice(n.pos,n.pos+n.length)}tokens(){return this.viterbi().map(o=>this.piece(o))}tokenIds(){return this.viterbi().map(o=>o.tokenId)}}class TokenLatticeNode{constructor(n,o,l,c,f){this.tokenId=n,this.nodeId=o,this.pos=l,this.length=c,this.score=f,this.prev=null,this.backtraceScore=0}clone(){const n=new TokenLatticeNode(this.tokenId,this.nodeId,this.pos,this.length,this.score);return n.prev=this.prev,n.backtraceScore=this.backtraceScore,n}}class AutoTokenizer{static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let[p,u]=await loadTokenizer(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h}),s=u.tokenizer_class.replace(/Fast$/,""),t=this.TOKENIZER_CLASS_MAPPING[s];return t||(console.warn(`Unknown tokenizer class "${s}", attempting to construct from base class.`),t=PreTrainedTokenizer),new t(p,u)}}le(AutoTokenizer,"TOKENIZER_CLASS_MAPPING",{T5Tokenizer,DistilBertTokenizer,BertTokenizer,MobileBertTokenizer,SqueezeBertTokenizer,AlbertTokenizer,GPT2Tokenizer,BartTokenizer,RobertaTokenizer,WhisperTokenizer,CodeGenTokenizer,CLIPTokenizer,MarianTokenizer,BloomTokenizer,NllbTokenizer,LlamaTokenizer});async function loadConfig(y,n){return await getModelJSON(y,"config.json",!0,n)}class PretrainedConfig{constructor(n){this.is_encoder_decoder=!1,Object.assign(this,n)}static async from_pretrained(n,{progress_callback:o=null,config:l=null,cache_dir:c=null,local_files_only:f=!1,revision:a="main"}={}){let h=l??await loadConfig(n,{progress_callback:o,config:l,cache_dir:c,local_files_only:f,revision:a});return new this(h)}}class AutoConfig{static async from_pretrained(...n){return PretrainedConfig.from_pretrained(...n)}}class LogitsProcessorList extends Callable{constructor(){super(),this.processors=[]}push(n){this.processors.push(n)}extend(n){this.processors.push(...n)}_call(n,o){for(let l of o)this.processors.forEach(c=>c(n,l))}[Symbol.iterator](){return this.processors.values()}}class LogitsProcessor extends Callable{_call(n,o){throw Error("`_call` should be implemented in a subclass")}}class ForceTokensLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.force_token_map=Object.fromEntries(n??[])}_call(n,o){let l=this.force_token_map[n.length];return exists(l)&&(o.data.fill(-1/0),o.data[l]=0),o}}class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.bos_token_id=n}_call(n,o){return n.length===1&&(o.data.fill(-1/0),o.data[this.bos_token_id]=0),o}}class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.max_length=n,this.forced_eos_token_id=o}_call(n,o){}}class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.begin_suppress_tokens=n,this.begin_index=o}_call(n,o){if(n.length===this.begin_index)for(let l of this.begin_suppress_tokens)o.data[l]=-1/0;return o}}class WhisperTimeStampLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.eos_token_id=n.eos_token_id,this.no_timestamps_token_id=n.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(n.forced_decoder_ids||[]).length+2,n.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=n.max_initial_timestamp_index}_call(n,o){if(o.data[this.no_timestamps_token_id]=-1/0,n.length===this.begin_index-1)return o.data.fill(-1/0),o.data[this.timestamp_begin]=0,o;const l=n.slice(this.begin_index),c=l.length>=1&&l[l.length-1]>=this.timestamp_begin,f=l.length<2||l[l.length-2]>=this.timestamp_begin;if(c&&(f?o.data.subarray(this.timestamp_begin).fill(-1/0):o.data.subarray(0,this.eos_token_id).fill(-1/0)),n.length===this.begin_index&&this.max_initial_timestamp_index!==null){const u=this.timestamp_begin+this.max_initial_timestamp_index;o.data.subarray(u+1).fill(-1/0)}const a=log_softmax(o.data),h=Math.log(a.subarray(this.timestamp_begin).map(Math.exp).reduce((u,s)=>u+s)),p=max(a.subarray(0,this.timestamp_begin))[0];return h>p&&o.data.subarray(0,this.timestamp_begin).fill(-1/0),o}}class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.no_repeat_ngram_size=n}getNgrams(n){const o=n.length,l=[];for(let f=0;f<o+1-this.no_repeat_ngram_size;++f){const a=[];for(let h=0;h<this.no_repeat_ngram_size;++h)a.push(n[f+h]);l.push(a)}const c=new Map;for(const f of l){const a=f.slice(0,f.length-1),h=JSON.stringify(a),p=c.get(h)??[];p.push(f[f.length-1]),c.set(h,p)}return c}getGeneratedNgrams(n,o){const l=o.slice(o.length+1-this.no_repeat_ngram_size,o.length);return n.get(JSON.stringify(l))??[]}calcBannedNgramTokens(n){const o=[];if(n.length+1<this.no_repeat_ngram_size)return o;{const l=this.getNgrams(n);return this.getGeneratedNgrams(l,n)}}_call(n,o){const l=this.calcBannedNgramTokens(n);for(const c of l)o.data[c]=-1/0;return o}}class RepetitionPenaltyLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.penalty=n}_call(n,o){for(const l of n)o.data[l]<0?o.data[l]*=this.penalty:o.data[l]/=this.penalty;return o}}class GenerationConfig{constructor(n={}){this.max_length=n.max_length??20,this.max_new_tokens=n.max_new_tokens??null,this.min_length=n.min_length??0,this.min_new_tokens=n.min_new_tokens??null,this.early_stopping=n.early_stopping??!1,this.max_time=n.max_time??null,this.do_sample=n.do_sample??!1,this.num_beams=n.num_beams??1,this.num_beam_groups=n.num_beam_groups??1,this.penalty_alpha=n.penalty_alpha??null,this.use_cache=n.use_cache??!0,this.temperature=n.temperature??1,this.top_k=n.top_k??50,this.top_p=n.top_p??1,this.typical_p=n.typical_p??1,this.epsilon_cutoff=n.epsilon_cutoff??0,this.eta_cutoff=n.eta_cutoff??0,this.diversity_penalty=n.diversity_penalty??0,this.repetition_penalty=n.repetition_penalty??1,this.encoder_repetition_penalty=n.encoder_repetition_penalty??1,this.length_penalty=n.length_penalty??1,this.no_repeat_ngram_size=n.no_repeat_ngram_size??0,this.bad_words_ids=n.bad_words_ids??null,this.force_words_ids=n.force_words_ids??null,this.renormalize_logits=n.renormalize_logits??!1,this.constraints=n.constraints??null,this.forced_bos_token_id=n.forced_bos_token_id??null,this.forced_eos_token_id=n.forced_eos_token_id??null,this.remove_invalid_values=n.remove_invalid_values??!1,this.exponential_decay_length_penalty=n.exponential_decay_length_penalty??null,this.suppress_tokens=n.suppress_tokens??null,this.begin_suppress_tokens=n.begin_suppress_tokens??null,this.forced_decoder_ids=n.forced_decoder_ids??null,this.num_return_sequences=n.num_return_sequences??1,this.output_attentions=n.output_attentions??!1,this.output_hidden_states=n.output_hidden_states??!1,this.output_scores=n.output_scores??!1,this.return_dict_in_generate=n.return_dict_in_generate??!1,this.pad_token_id=n.pad_token_id??null,this.bos_token_id=n.bos_token_id??null,this.eos_token_id=n.eos_token_id??null,this.encoder_no_repeat_ngram_size=n.encoder_no_repeat_ngram_size??0,this.decoder_start_token_id=n.decoder_start_token_id??null,this.generation_kwargs=n.generation_kwargs??{}}}class Sampler extends Callable{constructor(n){super(),this.temperature=n}_call(n,o=-1){return this.sample(n,o)}sample(n,o){throw Error("sample should be implemented in subclasses.")}getLogits(n,o){let l=n.dims[2],c=n.data;if(o===-1)c=c.slice(-l);else{let f=o*l;c=c.slice(f,f+l)}return this.temperature>0&&(c=c.map(f=>f/this.temperature)),c}randomSelect(n){let o=n.reduce((c,f)=>c+f,0),l=Math.random()*o;for(let c=0;c<n.length;++c)if(l-=n[c],l<=0)return c;return 0}static getSampler(n){if(n.num_beams>1)return new BeamSearchSampler(n.temperature,n.num_beams,n.do_sample,n.top_k);if(n.do_sample)return new TopKSampler(n.temperature,n.top_k);if(n.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${n.num_return_sequences}.`);return new GreedySampler(n.temperature)}}class GreedySampler extends Sampler{sample(n,o=-1){let l=this.getLogits(n,o);return[[max(l)[1],0]]}}class TopKSampler extends Sampler{constructor(n,o){super(n),this.k=o}sample(n,o=-1){let[l,c,f]=n.dims,a=f;this.k>0&&(a=Math.min(this.k,a));let h=this.getLogits(n,o),p=getTopItems(h,a),u=softmax(p.map(r=>r[1])),s=this.randomSelect(u),t=p[s][0],e=Math.log(u[s]);return[[t,e]]}}class BeamSearchSampler extends Sampler{constructor(n,o,l,c){super(n),this.num_beams=o,this.do_sample=l,this.top_k=c}sample(n,o=-1){let l=this.getLogits(n,o);if(this.do_sample||this.top_k>0){const[c,f,a]=n.dims;let h=a;this.top_k>0&&(h=Math.min(this.top_k,h));const p=getTopItems(l,h),u=softmax(p.map(s=>s[1]));return Array.from({length:this.num_beams},()=>{const s=this.randomSelect(u);return[p[s][0],Math.log(u[s])]})}else{const c=log_softmax(l);return getTopItems(c,this.num_beams)}}}const{InferenceSession,Tensor:ONNXTensor}=ONNX;async function constructSession(y,n,o){let l=`onnx/${n}${o.quantized?"_quantized":""}.onnx`,c=await getModelFile(y,l,!0,o);try{return await InferenceSession.create(c,{executionProviders})}catch(f){if(executionProviders.length===1&&executionProviders[0]==="wasm")throw f;return console.warn(f),console.warn("Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback. "),await InferenceSession.create(c,{executionProviders:["wasm"]})}}async function sessionRun(y,n){const o={},l=[];for(let a of y.inputNames)n[a]===void 0?l.push(a):o[a]=n[a];if(l.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${l.join(", ")}.`);const c=Object.keys(n).length,f=y.inputNames.length;if(c>f){let a=Object.keys(n).filter(h=>!y.inputNames.includes(h));console.warn(`WARNING: Too many inputs were provided (${c} > ${f}). The following inputs will be ignored: "${a.join(", ")}".`)}try{let a=await y.run(o);return a=replaceTensors(a),a}catch(a){throw console.error(`An error occurred during model execution: "${a}".`),console.error("Inputs given to model:",o),a}}function replaceTensors(y){for(let n in y)y[n]instanceof ONNXTensor&&(y[n]=new Tensor(y[n]));return y}function toI64Tensor(y){if(y instanceof Tensor)return y;if(y.length===0)throw Error("items must be non-empty");if(Array.isArray(y[0])){if(y.some(n=>n.length!==y[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(y.flat().map(n=>BigInt(n))),[y.length,y[0].length])}else return new Tensor("int64",BigInt64Array.from(y.map(n=>BigInt(n))),[1,y.length])}function _prepare_attention_mask(y,n){let o=y.config.pad_token_id??null,l=y.config.eos_token_id??null;isIntegralNumber(l)&&(l=[l]);let c=n.indexOf(o)!==-1,f=l===null||!l.includes(o);if(c&&f){let a=BigInt64Array.from(n.data.map(h=>h!=o));return new Tensor("int64",a,n.dims)}else return new Tensor("int64",new BigInt64Array(n.data.length).fill(1n),n.dims)}function boolTensor(y){return new Tensor("bool",[y],[1])}async function loadAutoModel(y,n){let o=await AutoConfig.from_pretrained(y,n),l=o.is_encoder_decoder?"encoder_model":"model",c=await constructSession(y,l,n);return[o,c]}async function loadModel(y,n){return await Promise.all([AutoConfig.from_pretrained(y,n),constructSession(y,"model",n)])}async function seq2seqLoadModel(y,n){return await Promise.all([AutoConfig.from_pretrained(y,n),constructSession(y,"encoder_model",n),constructSession(y,"decoder_model_merged",n),getModelJSON(y,"generation_config.json",!1,n)])}async function encoderDecoderLoadModel(y,n){return await Promise.all([AutoConfig.from_pretrained(y,n),constructSession(y,"encoder_model",n),constructSession(y,"decoder_model_merged",n)])}async function decoderLoadModel(y,n){return await Promise.all([AutoConfig.from_pretrained(y,n),constructSession(y,"decoder_model_merged",n)])}async function seq2seq_forward(y,n,{encoder_input_name:o="input_ids",add_decoder_pkv:l=!0}={}){let c=n.encoder_outputs,f=n.past_key_values;if(c===null){const u={[o]:n[o]};y.session.inputNames.includes("attention_mask")&&(u.attention_mask=n.attention_mask),c=(await sessionRun(y.session,u)).last_hidden_state}let a={input_ids:n.decoder_input_ids,encoder_hidden_states:c,use_cache_branch:boolTensor(f!==null)};y.decoder_merged_session.inputNames.includes("encoder_attention_mask")&&(a.encoder_attention_mask=n.attention_mask),y.addPastKeyValues(a,f,l);const h=await sessionRun(y.decoder_merged_session,a);let p=h.logits;return f=y.getPastKeyValues(h,f),new Seq2SeqLMOutput(p,f,c)}function seq2seqStartBeams(y,n,o,l=!0){let c=[],f=0,a=y.config.decoder_start_token_id;Array.isArray(a)||(a=[a]);for(let h of n){h.dims=[1,...h.dims];let p={inputs:h,encoder_outputs:null,past_key_values:null,output_token_ids:a,done:!1,score:0,id:f++};l&&(p.attention_mask=_prepare_attention_mask(y,h)),c.push(p)}return c}async function seq2seqRunBeam(y,n,{input_name:o="input_ids"}={}){let l={[o]:n.inputs,decoder_input_ids:toI64Tensor(n.output_token_ids.slice(-1)),encoder_outputs:n.encoder_outputs,past_key_values:n.past_key_values};n.attention_mask&&(l.attention_mask=n.attention_mask);let c=await y.forward(l);return n.past_key_values=c.past_key_values,n.encoder_outputs=c.encoder_outputs,c}async function textgen_forward(y,n){let o=n.past_key_values,l={input_ids:n.input_ids,attention_mask:n.attention_mask,use_cache_branch:boolTensor(o!==null)};y.addPastKeyValues(l,o);let c=await sessionRun(y.session,l),f=c.logits;return o=y.getPastKeyValues(c,o),{logits:f,past_key_values:o}}function textgenStartBeams(y,n,o,l){let c=[],f=0;for(let a of n){a.dims=[1,...a.dims];let h;l?(h=l[f],h.dims=[1,...h.dims]):h=_prepare_attention_mask(y,a);let p={input:a,model_input_ids:a,attention_mask:h,past_key_values:null,output_token_ids:[],num_output_tokens:o,done:!1,score:0,id:f++};c.push(p)}return c}async function textgenRunBeam(y,n){let o=new BigInt64Array(n.input.data.length+n.output_token_ids.length).fill(1n),l={input_ids:n.model_input_ids,attention_mask:new Tensor("int64",o,[1,o.length]),past_key_values:n.past_key_values},c=await y.forward(l);return n.past_key_values=c.past_key_values,c}function textgenUpdatebeam(y,n){y.output_token_ids=[...y.output_token_ids,n],y.model_input_ids=new Tensor("int64",[BigInt(n)],[1,1])}class PreTrainedModel extends Callable{constructor(n,o){super(),this.config=n,this.session=o}async dispose(){let n=[];for(let o of Object.keys(this)){let l=this[o];l instanceof InferenceSession&&n.push(l.handler.dispose())}return await Promise.all(n)}static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let p=await loadAutoModel(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h});return new this(...p)}async _call(n){return await sessionRun(this.session,n)}async forward(n){throw Error("forward should be implemented in subclasses.")}_get_logits_processor(n,o,l=null){const c=new LogitsProcessorList;if(n.repetition_penalty!==null&&n.repetition_penalty!==1&&c.push(new RepetitionPenaltyLogitsProcessor(n.repetition_penalty)),n.no_repeat_ngram_size!==null&&n.no_repeat_ngram_size>0&&c.push(new NoRepeatNGramLogitsProcessor(n.no_repeat_ngram_size)),n.forced_bos_token_id!==null&&c.push(new ForcedBOSTokenLogitsProcessor(n.forced_bos_token_id)),n.forced_eos_token_id!==null&&c.push(new ForcedEOSTokenLogitsProcessor(n.max_length,n.forced_eos_token_id)),n.begin_suppress_tokens!==null){let f=o>1||n.forced_bos_token_id===null?o:o+1;n.forced_decoder_ids!==null&&(f+=n.forced_decoder_ids[n.forced_decoder_ids.length-1][0]),c.push(new SuppressTokensAtBeginLogitsProcessor(n.begin_suppress_tokens,f))}return n.forced_decoder_ids!==null&&c.push(new ForceTokensLogitsProcessor(n.forced_decoder_ids)),l!==null&&c.extend(l),c}_get_generation_config(n){let o=new GenerationConfig;return"generation_config"in this&&Object.assign(o,this.generation_config),n!==null&&Object.assign(o,n),o}async generate(n,o=null,l=null,{inputs_attention_mask:c=null}={}){if(!(n instanceof Tensor)&&!isTypedArray(n)&&!Array.isArray(n))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${n.constructor.name}".`);let f;if(this.config.is_encoder_decoder)f=0;else if(f=n instanceof Tensor?n.dims[0]:n.length,f===0)throw Error("Must supply a non-empty array of input token ids.");o=this._get_generation_config(o),l=l??new LogitsProcessorList,l=this._get_logits_processor(o,f,l);let a=1;const h=a+(o.max_new_tokens??1/0),p=Number.isInteger(o.max_length)&&(o.max_new_tokens??null)===null;let u=Sampler.getSampler(o),s=this.getStartBeams(n,a,c);for(;s.some(t=>!t.done)&&a<h;){let t=[];for(let e of s){if(e.done){t.push(e);continue}if(p&&e.output_token_ids.length>=o.max_length){e.done=!0,t.push(e);continue}let i=(await this.runBeam(e)).logits.slice(null,-1,null);l(e.output_token_ids,i);let d=u(i);for(let[g,m]of d){let b={...e};this.updateBeam(b,g),b.score+=m,g===this.config.eos_token_id&&(b.done=!0),t.push(b)}}++a,t=this.groupBeams(t).map(e=>e.sort((r,i)=>i.score-r.score).slice(0,o.num_beams)),s=t.flat(),o.callback_function&&o.callback_function(s)}return this.groupBeams(s).map(t=>o.num_return_sequences>1?t.slice(0,o.num_return_sequences).map(e=>e.output_token_ids):[t[0].output_token_ids]).flat()}groupBeams(n){const o=Object.create(null);for(const l of n)o[l.id]===void 0?o[l.id]=[l]:o[l.id].push(l);return Object.values(o)}getPastKeyValues(n,o){const l=Object.create(null);for(const c in n)if(c.startsWith("present")){let f=c.replace("present","past_key_values");o!==null&&c.includes("encoder")?l[f]=o[f]:l[f]=n[c]}return l}addPastKeyValues(n,o,l=!1){if(o===null)if(l){let c=[1,this.num_encoder_heads,0,this.encoder_dim_kv];for(let a=0;a<this.num_encoder_layers;++a)n[`past_key_values.${a}.encoder.key`]=new Tensor("float32",[],c),n[`past_key_values.${a}.encoder.value`]=new Tensor("float32",[],c);let f=[1,this.num_decoder_heads,0,this.decoder_dim_kv];for(let a=0;a<this.num_decoder_layers;++a)n[`past_key_values.${a}.decoder.key`]=new Tensor("float32",[],f),n[`past_key_values.${a}.decoder.value`]=new Tensor("float32",[],f)}else{let c=[1,this.num_heads,0,this.dim_kv];for(let f=0;f<this.num_layers;++f)n[`past_key_values.${f}.key`]=new Tensor("float32",[],c),n[`past_key_values.${f}.value`]=new Tensor("float32",[],c)}else Object.assign(n,o)}}class ModelOutput{}class BertPreTrainedModel extends PreTrainedModel{}class BertModel extends BertPreTrainedModel{}class BertForMaskedLM extends BertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new MaskedLMOutput(o)}}class BertForSequenceClassification extends BertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new SequenceClassifierOutput(o)}}class BertForTokenClassification extends BertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new TokenClassifierOutput(o)}}class BertForQuestionAnswering extends BertPreTrainedModel{async _call(n){let o=await super._call(n);return new QuestionAnsweringModelOutput(o.start_logits,o.end_logits)}}class DistilBertPreTrainedModel extends PreTrainedModel{}class DistilBertModel extends DistilBertPreTrainedModel{}class DistilBertForSequenceClassification extends DistilBertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new SequenceClassifierOutput(o)}}class DistilBertForTokenClassification extends DistilBertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new TokenClassifierOutput(o)}}class DistilBertForQuestionAnswering extends DistilBertPreTrainedModel{async _call(n){let o=await super._call(n);return new QuestionAnsweringModelOutput(o.start_logits,o.end_logits)}}class DistilBertForMaskedLM extends DistilBertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new MaskedLMOutput(o)}}class MobileBertPreTrainedModel extends PreTrainedModel{}class MobileBertModel extends MobileBertPreTrainedModel{}class MobileBertForMaskedLM extends MobileBertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new MaskedLMOutput(o)}}class MobileBertForSequenceClassification extends MobileBertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new SequenceClassifierOutput(o)}}class MobileBertForQuestionAnswering extends MobileBertPreTrainedModel{async _call(n){let o=await super._call(n);return new QuestionAnsweringModelOutput(o.start_logits,o.end_logits)}}class SqueezeBertPreTrainedModel extends PreTrainedModel{}class SqueezeBertModel extends SqueezeBertPreTrainedModel{}class SqueezeBertForMaskedLM extends SqueezeBertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new MaskedLMOutput(o)}}class SqueezeBertForSequenceClassification extends SqueezeBertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new SequenceClassifierOutput(o)}}class SqueezeBertForQuestionAnswering extends SqueezeBertPreTrainedModel{async _call(n){let o=await super._call(n);return new QuestionAnsweringModelOutput(o.start_logits,o.end_logits)}}class AlbertPreTrainedModel extends PreTrainedModel{}class AlbertModel extends AlbertPreTrainedModel{}class AlbertForSequenceClassification extends AlbertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new SequenceClassifierOutput(o)}}class AlbertForQuestionAnswering extends AlbertPreTrainedModel{async _call(n){let o=await super._call(n);return new QuestionAnsweringModelOutput(o.start_logits,o.end_logits)}}class AlbertForMaskedLM extends AlbertPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new MaskedLMOutput(o)}}class T5PreTrainedModel extends PreTrainedModel{}class T5Model extends T5PreTrainedModel{async generate(...n){throw Error("The current model class (T5Model) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'T5ForConditionalGeneration'}")}}class T5ForConditionalGeneration extends T5PreTrainedModel{constructor(n,o,l,c){super(n,o),this.decoder_merged_session=l,this.generation_config=c,this.num_decoder_layers=this.config.num_decoder_layers,this.num_decoder_heads=this.config.num_heads,this.decoder_dim_kv=this.config.d_kv,this.num_encoder_layers=this.config.num_layers,this.num_encoder_heads=this.config.num_heads,this.encoder_dim_kv=this.config.d_kv}static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let p=await seq2seqLoadModel(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h});return new this(...p)}getStartBeams(n,o,...l){return seq2seqStartBeams(this,n)}async runBeam(n){return await seq2seqRunBeam(this,n)}updateBeam(n,o){n.output_token_ids=[...n.output_token_ids,o]}async forward(n){return await seq2seq_forward(this,n)}}class MT5PreTrainedModel extends PreTrainedModel{}class MT5Model extends MT5PreTrainedModel{async generate(...n){throw Error("The current model class (MT5Model) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'MT5ForConditionalGeneration'}")}}class MT5ForConditionalGeneration extends MT5PreTrainedModel{constructor(n,o,l,c){super(n,o),this.decoder_merged_session=l,this.generation_config=c,this.num_decoder_layers=this.config.num_decoder_layers,this.num_decoder_heads=this.config.num_heads,this.decoder_dim_kv=this.config.d_kv,this.num_encoder_layers=this.config.num_layers,this.num_encoder_heads=this.config.num_heads,this.encoder_dim_kv=this.config.d_kv}static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let p=await seq2seqLoadModel(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h});return new this(...p)}getStartBeams(n,o,...l){return seq2seqStartBeams(this,n)}async runBeam(n){return await seq2seqRunBeam(this,n)}updateBeam(n,o){n.output_token_ids=[...n.output_token_ids,o]}async forward(n){return await seq2seq_forward(this,n)}}class BartPretrainedModel extends PreTrainedModel{}class BartModel extends BartPretrainedModel{async generate(...n){throw Error("The current model class (BartModel) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'BartForConditionalGeneration'}")}}class BartForConditionalGeneration extends BartPretrainedModel{constructor(n,o,l,c){super(n,o),this.decoder_merged_session=l,this.generation_config=c,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let p=await seq2seqLoadModel(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h});return new this(...p)}getStartBeams(n,o,...l){return seq2seqStartBeams(this,n)}async runBeam(n){return await seq2seqRunBeam(this,n)}updateBeam(n,o){n.output_token_ids=[...n.output_token_ids,o]}async forward(n){return await seq2seq_forward(this,n)}}class BartForSequenceClassification extends BartPretrainedModel{async _call(n){let o=(await super._call(n)).logits;return new SequenceClassifierOutput(o)}}class RobertaPreTrainedModel extends PreTrainedModel{}class RobertaModel extends RobertaPreTrainedModel{}class RobertaForMaskedLM extends RobertaPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new MaskedLMOutput(o)}}class RobertaForSequenceClassification extends RobertaPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new SequenceClassifierOutput(o)}}class RobertaForQuestionAnswering extends RobertaPreTrainedModel{async _call(n){let o=await super._call(n);return new QuestionAnsweringModelOutput(o.start_logits,o.end_logits)}}class WhisperPreTrainedModel extends PreTrainedModel{}class WhisperModel extends WhisperPreTrainedModel{async generate(...n){throw Error("The current model class (WhisperModel) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'WhisperForConditionalGeneration'}")}}class WhisperForConditionalGeneration extends WhisperPreTrainedModel{constructor(n,o,l,c){super(n,o),this.decoder_merged_session=l,this.generation_config=c,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}async generate(n,o=null,l=null){return o=this._get_generation_config(o),o.return_timestamps??(o.return_timestamps=!1),o.return_timestamps&&(l=[new WhisperTimeStampLogitsProcessor(o)]),super.generate(n,o,l)}static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let p=await seq2seqLoadModel(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h});return new this(...p)}getStartBeams(n,o,...l){return seq2seqStartBeams(this,n,o,!1)}async runBeam(n){return await seq2seqRunBeam(this,n,{input_name:"input_features"})}updateBeam(n,o){n.output_token_ids=[...n.output_token_ids,o]}async forward(n){return await seq2seq_forward(this,n,{encoder_input_name:"input_features"})}}class VisionEncoderDecoderModel extends PreTrainedModel{constructor(n,o,l){super(n,o),this.decoder_merged_session=l,this.num_layers=this.config.decoder.n_layer,this.num_heads=this.config.decoder.n_head,this.dim_kv=this.config.decoder.n_embd/this.num_heads}static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let p=await encoderDecoderLoadModel(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h});return new this(...p)}getStartBeams(n,o,...l){return seq2seqStartBeams(this,n)}async runBeam(n){return seq2seqRunBeam(this,n,{input_name:"pixel_values"})}updateBeam(n,o){n.output_token_ids=[...n.output_token_ids,o]}async forward(n){return await seq2seq_forward(this,n,{encoder_input_name:"pixel_values",add_decoder_pkv:!1})}}class CLIPPreTrainedModel extends PreTrainedModel{}class CLIPModel extends CLIPPreTrainedModel{}class GPT2PreTrainedModel extends PreTrainedModel{}class GPT2Model extends GPT2PreTrainedModel{async generate(...n){throw Error("The current model class (GPT2Model) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'GPT2LMHeadModel'}")}}class GPT2LMHeadModel extends GPT2PreTrainedModel{constructor(n,o){super(n,o),this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}getStartBeams(n,o,l){return textgenStartBeams(this,n,o,l)}async runBeam(n){return await textgenRunBeam(this,n)}updateBeam(n,o){return textgenUpdatebeam(n,o)}async forward(n){return await textgen_forward(this,n)}}class GPTNeoPreTrainedModel extends PreTrainedModel{}class GPTNeoModel extends GPTNeoPreTrainedModel{async generate(...n){throw Error("The current model class (GPTNeoModel) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'GPTNeoForCausalLM'}")}}class GPTNeoForCausalLM extends GPTNeoPreTrainedModel{constructor(n,o){super(n,o),this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_heads,this.num_layers=this.config.num_layers,this.dim_kv=this.config.hidden_size/this.num_heads}getStartBeams(n,o,l){return textgenStartBeams(this,n,o,l)}async runBeam(n){return await textgenRunBeam(this,n)}updateBeam(n,o){return textgenUpdatebeam(n,o)}async forward(n){return await textgen_forward(this,n)}}class CodeGenPreTrainedModel extends PreTrainedModel{}class CodeGenModel extends CodeGenPreTrainedModel{async generate(...n){throw Error("The current model class (CodeGenModel) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'CodeGenForCausalLM'}")}}class CodeGenForCausalLM extends CodeGenPreTrainedModel{constructor(n,o){super(n,o),this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}getStartBeams(n,o,l){return textgenStartBeams(this,n,o,l)}async runBeam(n){return await textgenRunBeam(this,n)}updateBeam(n,o){return textgenUpdatebeam(n,o)}async forward(n){return await textgen_forward(this,n)}}class ViTPreTrainedModel extends PreTrainedModel{}class ViTForImageClassification extends ViTPreTrainedModel{async _call(n){let o=(await super._call(n)).logits;return new SequenceClassifierOutput(o)}}class DetrPreTrainedModel extends PreTrainedModel{}class DetrForObjectDetection extends DetrPreTrainedModel{async _call(n){let o=await super._call(n);return new DetrObjectDetectionOutput(o.logits,o.pred_boxes)}}class DetrForSegmentation extends DetrPreTrainedModel{async _call(n){let o=await super._call(n);return new DetrSegmentationOutput(o.logits,o.pred_boxes,o.pred_masks)}}class DetrObjectDetectionOutput extends ModelOutput{constructor(n,o){super(),this.logits=n,this.pred_boxes=o}}class DetrSegmentationOutput extends ModelOutput{constructor(n,o,l){super(),this.logits=n,this.pred_boxes=o,this.pred_masks=l}}class SamPreTrainedModel extends PreTrainedModel{}class SamModel extends SamPreTrainedModel{async _call(n){let o=await super._call(n);return new SamImageSegmentationOutput(o.iou_scores,o.pred_masks)}}class SamImageSegmentationOutput extends ModelOutput{constructor(n,o){super(),this.iou_scores=n,this.pred_masks=o}}class MarianPreTrainedModel extends PreTrainedModel{}class MarianModel extends MarianPreTrainedModel{async generate(...n){throw Error("The current model class (MarianModel) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'MarianMTModel'}")}}class MarianMTModel extends MarianPreTrainedModel{constructor(n,o,l,c){super(n,o),this.decoder_merged_session=l,this.generation_config=c,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let p=await seq2seqLoadModel(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h});return new this(...p)}getStartBeams(n,o,...l){return seq2seqStartBeams(this,n)}async runBeam(n){return await seq2seqRunBeam(this,n)}updateBeam(n,o){n.output_token_ids=[...n.output_token_ids,o]}async forward(n){return await seq2seq_forward(this,n)}}class M2M100PreTrainedModel extends PreTrainedModel{}class M2M100Model extends M2M100PreTrainedModel{async generate(...n){throw Error("The current model class (M2M100Model) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'M2M100ForConditionalGeneration'}")}}class M2M100ForConditionalGeneration extends M2M100PreTrainedModel{constructor(n,o,l,c){super(n,o),this.decoder_merged_session=l,this.generation_config=c,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){let p=await seq2seqLoadModel(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h});return new this(...p)}getStartBeams(n,o,...l){return seq2seqStartBeams(this,n)}async runBeam(n){return await seq2seqRunBeam(this,n)}updateBeam(n,o){n.output_token_ids=[...n.output_token_ids,o]}async forward(n){return await seq2seq_forward(this,n)}}class PretrainedMixin{static async from_pretrained(n,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){if(this.LOAD_FUNCTION===null)throw new Error("`LOAD_FUNCTION` not implemented for this model");let p=await this.LOAD_FUNCTION(n,{quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h}),u=this.MODEL_CLASS_MAPPING[p[0].model_type];if(!u)if(this.BASE_IF_FAIL)console.warn(`Unknown model class "${p[0].model_type}", attempting to construct from base class.`),u=PreTrainedModel;else throw Error(`Unsupported model type: ${p[0].model_type}`);return new u(...p)}}le(PretrainedMixin,"MODEL_CLASS_MAPPING",Object.create(null)),le(PretrainedMixin,"BASE_IF_FAIL",!1),le(PretrainedMixin,"LOAD_FUNCTION",null);class AutoModel extends PretrainedMixin{}le(AutoModel,"LOAD_FUNCTION",loadAutoModel),le(AutoModel,"BASE_IF_FAIL",!0),le(AutoModel,"MODEL_CLASS_MAPPING",{bert:BertModel,albert:AlbertModel,distilbert:DistilBertModel,t5:T5Model,mt5:MT5Model,gpt2:GPT2Model,gpt_neo:GPTNeoModel,codegen:CodeGenModel,bart:BartModel,roberta:RobertaModel,whisper:WhisperModel,clip:CLIPModel,mobilebert:MobileBertModel,squeezebert:SqueezeBertModel,marian:MarianModel,m2m_100:M2M100Model,sam:SamModel});class AutoModelForSequenceClassification extends PretrainedMixin{}le(AutoModelForSequenceClassification,"LOAD_FUNCTION",loadModel),le(AutoModelForSequenceClassification,"MODEL_CLASS_MAPPING",{bert:BertForSequenceClassification,albert:AlbertForSequenceClassification,distilbert:DistilBertForSequenceClassification,roberta:RobertaForSequenceClassification,bart:BartForSequenceClassification,mobilebert:MobileBertForSequenceClassification,squeezebert:SqueezeBertForSequenceClassification});class AutoModelForTokenClassification extends PretrainedMixin{}le(AutoModelForTokenClassification,"LOAD_FUNCTION",loadModel),le(AutoModelForTokenClassification,"MODEL_CLASS_MAPPING",{bert:BertForTokenClassification,distilbert:DistilBertForTokenClassification});class AutoModelForSeq2SeqLM extends PretrainedMixin{}le(AutoModelForSeq2SeqLM,"LOAD_FUNCTION",seq2seqLoadModel),le(AutoModelForSeq2SeqLM,"MODEL_CLASS_MAPPING",{t5:T5ForConditionalGeneration,mt5:MT5ForConditionalGeneration,bart:BartForConditionalGeneration,whisper:WhisperForConditionalGeneration,marian:MarianMTModel,m2m_100:M2M100ForConditionalGeneration});class AutoModelForCausalLM extends PretrainedMixin{}le(AutoModelForCausalLM,"LOAD_FUNCTION",decoderLoadModel),le(AutoModelForCausalLM,"MODEL_CLASS_MAPPING",{gpt2:GPT2LMHeadModel,gpt_neo:GPTNeoForCausalLM,codegen:CodeGenForCausalLM});class AutoModelForMaskedLM extends PretrainedMixin{}le(AutoModelForMaskedLM,"LOAD_FUNCTION",loadAutoModel),le(AutoModelForMaskedLM,"MODEL_CLASS_MAPPING",{bert:BertForMaskedLM,albert:AlbertForMaskedLM,distilbert:DistilBertForMaskedLM,roberta:RobertaForMaskedLM,mobilebert:MobileBertForMaskedLM,squeezebert:SqueezeBertForMaskedLM});class AutoModelForQuestionAnswering extends PretrainedMixin{}le(AutoModelForQuestionAnswering,"LOAD_FUNCTION",loadModel),le(AutoModelForQuestionAnswering,"MODEL_CLASS_MAPPING",{bert:BertForQuestionAnswering,albert:AlbertForQuestionAnswering,distilbert:DistilBertForQuestionAnswering,roberta:RobertaForQuestionAnswering,mobilebert:MobileBertForQuestionAnswering,squeezebert:SqueezeBertForQuestionAnswering});class AutoModelForVision2Seq extends PretrainedMixin{}le(AutoModelForVision2Seq,"LOAD_FUNCTION",encoderDecoderLoadModel),le(AutoModelForVision2Seq,"MODEL_CLASS_MAPPING",{"vision-encoder-decoder":VisionEncoderDecoderModel});class AutoModelForImageClassification extends PretrainedMixin{}le(AutoModelForImageClassification,"LOAD_FUNCTION",loadModel),le(AutoModelForImageClassification,"MODEL_CLASS_MAPPING",{vit:ViTForImageClassification});class AutoModelForImageSegmentation extends PretrainedMixin{}le(AutoModelForImageSegmentation,"LOAD_FUNCTION",loadModel),le(AutoModelForImageSegmentation,"MODEL_CLASS_MAPPING",{detr:DetrForSegmentation});class AutoModelForObjectDetection extends PretrainedMixin{}le(AutoModelForObjectDetection,"LOAD_FUNCTION",loadModel),le(AutoModelForObjectDetection,"MODEL_CLASS_MAPPING",{detr:DetrForObjectDetection});class Seq2SeqLMOutput extends ModelOutput{constructor(n,o,l){super(),this.logits=n,this.past_key_values=o,this.encoder_outputs=l}}class SequenceClassifierOutput extends ModelOutput{constructor(n){super(),this.logits=n}}class TokenClassifierOutput extends ModelOutput{constructor(n){super(),this.logits=n}}class MaskedLMOutput extends ModelOutput{constructor(n){super(),this.logits=n}}class QuestionAnsweringModelOutput extends ModelOutput{constructor(n,o){super(),this.start_logits=n,this.end_logits=o}}const BROWSER_ENV=typeof self<"u";let createCanvasFunction,ImageDataClass,loadImageFunction;if(BROWSER_ENV)createCanvasFunction=(y,n)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this browser.");return new self.OffscreenCanvas(y,n)},loadImageFunction=self.createImageBitmap,ImageDataClass=self.ImageData;else if(fs)loadImageFunction=async y=>{let{data:n,info:o}=await y.raw().toBuffer({resolveWithObject:!0});return new RawImage(new Uint8ClampedArray(n),o.width,o.height,o.channels)};else throw new Error("Unable to load image processing library.");const RESAMPLING_MAPPING={0:"nearest",1:"lanczos",2:"bilinear",3:"bicubic",4:"box",5:"hamming"};class RawImage{constructor(n,o,l,c){this._update(n,o,l,c)}static async read(n){if(n instanceof RawImage)return n;if(isString(n)||n instanceof URL)return await this.fromURL(n);throw new Error(`Unsupported input type: ${typeof n}`)}static async fromURL(n){let l=await(await getFile(n)).blob();return this.fromBlob(l)}static async fromBlob(n){if(BROWSER_ENV){let o=await loadImageFunction(n);const l=createCanvasFunction(o.width,o.height).getContext("2d");return l.drawImage(o,0,0),new this(l.getImageData(0,0,o.width,o.height).data,o.width,o.height,4)}else{let o=fs(await n.arrayBuffer());return await loadImageFunction(o)}}grayscale(){if(this.channels===1)return this;let n=new Uint8ClampedArray(this.width*this.height*3);switch(this.channels){case 3:case 4:for(let o=0,l=0;o<this.data.length;o+=this.channels){const c=this.data[o],f=this.data[o+1],a=this.data[o+2];n[l++]=Math.round(.2989*c+.587*f+.114*a)}break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(n,this.width,this.height,1)}rgb(){if(this.channels===3)return this;let n=new Uint8ClampedArray(this.width*this.height*3);switch(this.channels){case 1:for(let o=0,l=0;o<this.data.length;++o)n[l++]=this.data[o],n[l++]=this.data[o],n[l++]=this.data[o];break;case 4:for(let o=0,l=0;o<this.data.length;o+=4)n[l++]=this.data[o],n[l++]=this.data[o+1],n[l++]=this.data[o+2];break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(n,this.width,this.height,3)}rgba(){if(this.channels===4)return this;let n=new Uint8ClampedArray(this.width*this.height*4);switch(this.channels){case 1:for(let o=0,l=0;o<this.data.length;++o)n[l++]=this.data[o],n[l++]=this.data[o],n[l++]=this.data[o],n[l++]=255;break;case 3:for(let o=0,l=0;o<this.data.length;o+=3)n[l++]=this.data[o],n[l++]=this.data[o+1],n[l++]=this.data[o+2],n[l++]=255;break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(n,this.width,this.height,4)}async resize(n,o,{resample:l=2}={}){let c=RESAMPLING_MAPPING[l]??l;if(BROWSER_ENV){let f=this.channels,a=this.toCanvas();const h=createCanvasFunction(n,o).getContext("2d");return h.drawImage(a,0,0,n,o),new RawImage(h.getImageData(0,0,n,o).data,n,o,4).convert(f)}else{let f=fs(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}});switch(c){case"box":case"hamming":(c==="box"||c==="hamming")&&(console.warn(`Resampling method ${c} is not yet supported. Using bilinear instead.`),c="bilinear");case"nearest":case"bilinear":case"bicubic":f=f.affine([n/this.width,0,0,o/this.height],{interpolator:c});break;case"lanczos":f=f.resize({width:n,height:o,fit:"fill",kernel:"lanczos3"});break;default:throw new Error(`Resampling method ${c} is not supported.`)}return await loadImageFunction(f)}}async pad([n,o,l,c]){if(n=Math.max(n,0),o=Math.max(o,0),l=Math.max(l,0),c=Math.max(c,0),n===0&&o===0&&l===0&&c===0)return this;if(BROWSER_ENV){let f=this.channels,a=this.toCanvas(),h=this.width+n+o,p=this.height+l+c;const u=createCanvasFunction(h,p).getContext("2d");return u.drawImage(a,0,0,this.width,this.height,n,l,h,p),new RawImage(u.getImageData(0,0,h,p).data,h,p,4).convert(f)}else{let f=fs(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}}).extend({left:n,right:o,top:l,bottom:c});return await loadImageFunction(f)}}async center_crop(n,o){if(this.width===n&&this.height===o)return this;let l=(this.width-n)/2,c=(this.height-o)/2;if(BROWSER_ENV){let f=this.channels,a=this.toCanvas();const h=createCanvasFunction(n,o).getContext("2d");let p=0,u=0,s=0,t=0;return l>=0?p=l:s=-l,c>=0?u=c:t=-c,h.drawImage(a,p,u,n,o,s,t,n,o),new RawImage(h.getImageData(0,0,n,o).data,n,o,4).convert(f)}else{let f=fs(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}});if(l>=0&&c>=0)f=f.extract({left:Math.floor(l),top:Math.floor(c),width:n,height:o});else if(l<=0&&c<=0){let a=Math.floor(-c),h=Math.floor(-l);f=f.extend({top:a,left:h,right:n-this.width-h,bottom:o-this.height-a})}else{let a=[0,0],h=0;c<0?(a[0]=Math.floor(-c),a[1]=o-this.height-a[0]):h=Math.floor(c);let p=[0,0],u=0;l<0?(p[0]=Math.floor(-l),p[1]=n-this.width-p[0]):u=Math.floor(l),f=f.extend({top:a[0],bottom:a[1],left:p[0],right:p[1]}).extract({left:u,top:h,width:n,height:o})}return await loadImageFunction(f)}}toCanvas(){let n=this.clone().rgba(),o=createCanvasFunction(n.width,n.height),l=new ImageDataClass(n.data,n.width,n.height);return o.getContext("2d").putImageData(l,0,0),o}_update(n,o,l,c=null){return this.data=n,this.width=o,this.height=l,c!==null&&(this.channels=c),this}clone(){return new RawImage(this.data.slice(),this.width,this.height,this.channels)}convert(n){if(this.channels===n)return this;switch(n){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}save(n,o="image/png"){if(!env.useFS)throw new Error("Unable to save the image because filesystem is disabled in this environment.");const c=this.toCanvas().toBuffer(o);fs.writeFileSync(n,c)}}async function read_audio(y,n){if(typeof AudioContext>"u")throw Error("Unable to load audio from path/URL since `AudioContext` is not available in your environment. As a result, audio data must be passed directly to the processor. If you are running in node.js, you can use an external library (e.g., https://github.com/audiojs/web-audio-api) to do this.");const o=await(await getFile(y)).arrayBuffer(),l=new AudioContext({sampleRate:n});typeof n>"u"&&console.warn(`No sampling rate provided, using default of ${l.sampleRate}Hz.`);const c=await l.decodeAudioData(o);let f;if(c.numberOfChannels===2){const a=Math.sqrt(2);let h=c.getChannelData(0),p=c.getChannelData(1);f=new Float32Array(h.length);for(let u=0;u<c.length;++u)f[u]=a*(h[u]+p[u])/2}else f=c.getChannelData(0);return f}function getMelFilters(y,n,o=128){o=Math.floor(o);const l=Math.floor(1+n/2),c=new Array(o),f=rfftfreq(n,1/y),a=0,u=(45.245640471924965-a)/(o+1),s=0,t=200/3,e=new Array(o+2),r=1e3,i=(r-s)/t,d=Math.log(6.4)/27,g=new Array(e.length);for(let b=0;b<e.length;++b){const _=b*u+a;_>=i?e[b]=r*Math.exp(d*(_-i)):e[b]=s+t*_,g[b]=f.map(v=>e[b]-v)}const m=e.slice(1).map((b,_)=>1/(b-e[_]));for(let b=0;b<c.length;++b){c[b]=new Array(l);const _=m[b],v=m[b+1],w=g[b],S=g[b+2],A=2/(e[b+2]-e[b]);for(let O=0;O<c[b].length;++O){const x=-w[O]*_,I=S[O]*v;c[b][O]=Math.max(0,Math.min(x,I))*A}}return c}class FeatureExtractor extends Callable{constructor(n){super(),this.config=n}}class ImageFeatureExtractor extends FeatureExtractor{constructor(n){super(n),this.image_mean=this.config.image_mean,this.image_std=this.config.image_std,this.resample=this.config.resample??2,this.do_rescale=this.config.do_rescale??!0,this.rescale_factor=this.config.rescale_factor??1/255,this.do_normalize=this.config.do_normalize,this.do_resize=this.config.do_resize,this.size=this.config.size,this.do_center_crop=this.config.do_center_crop,this.crop_size=this.config.crop_size,this.do_convert_rgb=this.config.do_convert_rgb??!0,this.pad_size=this.config.pad_size,this.do_pad=(this.config.do_pad??!1)&&this.pad_size}async preprocess(n){this.do_convert_rgb&&(n=n.rgb());const o=n.width,l=n.height;if(this.do_resize){let u,s;if(Number.isInteger(this.size)?(u=this.size,s=this.config.max_size??u):(u=this.size.shortest_edge,s=this.size.longest_edge),u!==void 0||s!==void 0){const t=u===void 0?1:Math.max(u/o,u/l),e=o*t,r=l*t,i=s===void 0?1:Math.min(s/e,s/r);n=await n.resize(Math.floor(e*i),Math.floor(r*i),{resample:this.resample})}else if(this.size.width!==void 0&&this.size.height!==void 0)n=await n.resize(this.size.width,this.size.height,{resample:this.resample});else throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(this.size)}`)}if(this.do_center_crop){let u,s;Number.isInteger(this.crop_size)?(u=this.crop_size,s=this.crop_size):(u=this.crop_size.width,s=this.crop_size.height),n=await n.center_crop(u,s)}let c=[n.height,n.width];if(this.do_pad){let u=0,s=this.pad_size.width-n.width,t=0,e=this.pad_size.height-n.height;n=await n.pad([u,s,t,e])}const f=Float32Array.from(n.data);if(this.do_rescale)for(let u=0;u<f.length;++u)f[u]=this.rescale_factor*f[u];if(this.do_normalize){let u=this.image_mean;Array.isArray(this.image_mean)||(u=new Array(n.channels).fill(u));let s=this.image_std;if(Array.isArray(this.image_std)||(s=new Array(n.channels).fill(u)),u.length!==n.channels||s.length!==n.channels)throw new Error(`When set to arrays, the length of \`image_mean\` (${u.length}) and \`image_std\` (${s.length}) must match the number of channels in the image (${n.channels}).`);for(let t=0;t<f.length;t+=n.channels)for(let e=0;e<n.channels;++e)f[t+e]=(f[t+e]-this.image_mean[e])/this.image_std[e]}let a=[n.height,n.width,n.channels],h=new Tensor("float32",f,a),p=transpose(h,[2,0,1]);return{original_size:[l,o],reshaped_input_size:c,pixel_values:p}}async _call(n){Array.isArray(n)||(n=[n]);let o=await Promise.all(n.map(c=>this.preprocess(c)));return o.forEach(c=>c.pixel_values.dims=[1,...c.pixel_values.dims]),{pixel_values:cat(o.map(c=>c.pixel_values)),original_sizes:o.map(c=>c.original_size),reshaped_input_sizes:o.map(c=>c.reshaped_input_size)}}}class ViTFeatureExtractor extends ImageFeatureExtractor{}class DetrFeatureExtractor extends ImageFeatureExtractor{async _call(n){let o=await super._call(n),l=[o.pixel_values.dims[0],64,64];return o.pixel_mask=new Tensor("int64",new BigInt64Array(l.reduce((c,f)=>c*f)).fill(1n),l),o}center_to_corners_format([n,o,l,c]){return[n-l/2,o-c/2,n+l/2,o+c/2]}post_process_object_detection(n,o=.5,l=null){const c=n.logits,f=n.pred_boxes,[a,h,p]=c.dims;if(l!==null&&l.length!==a)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let u=[];for(let s=0;s<a;++s){let t=l!==null?l[s]:null,e={boxes:[],classes:[],scores:[]},r=c[s],i=f[s];for(let d=0;d<h;++d){let g=r[d],m=max(g.data)[1];if(m===p-1)continue;let _=softmax(g.data)[m];if(_>o){let v=i[d].data;v=this.center_to_corners_format(v),t!==null&&(v=v.map((w,S)=>w*t[(S+1)%2])),e.boxes.push(v),e.classes.push(m),e.scores.push(_)}}u.push(e)}return u}remove_low_and_no_objects(n,o,l,c){let f=[],a=[],h=[];for(let p=0;p<n.dims[0];++p){let u=n[p],s=o[p],t=max(u.data)[1];if(t===c)continue;let r=softmax(u.data)[t];r>l&&(f.push(s),a.push(r),h.push(t))}return[f,a,h]}check_segment_validity(n,o,l,c=.5,f=.8){let a=[],h=0,p=0;for(let s=0;s<n.length;++s)n[s]===l&&(a.push(s),++h),o[l].data[s]>=c&&++p;let u=h>0&&p>0;return u&&(u=h/p>f),[u,a]}compute_segments(n,o,l,c,f,a=null,h=null){let[p,u]=h??n[0].dims,s=new Tensor("int32",new Int32Array(p*u),[p,u]),t=[];if(h!==null)for(let d=0;d<n.length;++d)n[d]=interpolate(n[d],h,"bilinear",!1);let e=new Int32Array(n[0].data.length),r=new Float32Array(n[0].data.length);for(let d=0;d<n.length;++d){let g=o[d];for(let m=0;m<n[d].data.length;++m)n[d].data[m]*=g,n[d].data[m]>r[m]&&(e[m]=d,r[m]=n[d].data[m])}let i=0;for(let d=0;d<l.length;++d){let g=l[d],[m,b]=this.check_segment_validity(e,n,d,c,f);if(m){++i;for(let _ of b)s.data[_]=i;t.push({id:i,label_id:g,score:o[d]})}}return[s,t]}post_process_panoptic_segmentation(n,o=.5,l=.5,c=.8,f=null,a=null){f===null&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),f=new Set);const h=n.logits,u=n.pred_masks.sigmoid();let[s,t,e]=h.dims;if(e-=1,a!==null&&a.length!==s)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let r=[];for(let i=0;i<s;++i){let d=a!==null?a[i]:null,g=h[i],m=u[i],[b,_,v]=this.remove_low_and_no_objects(g,m,o,e);if(v.length===0){let[A,O]=d??m.dims.slice(-2),x=new Tensor("int32",new Int32Array(A*O).fill(-1),[A,O]);r.push({segmentation:x,segments_info:[]});continue}let[w,S]=this.compute_segments(b,_,v,l,c,f,d);r.push({segmentation:w,segments_info:S})}return r}post_process_instance_segmentation(){throw Error("Not implemented yet")}}class SamImageProcessor extends ImageFeatureExtractor{async _call(n,o){let{pixel_values:l,original_sizes:c,reshaped_input_sizes:f}=await super._call(n),a=calculateDimensions(o);if(a.length===3)a=[1,...a],o=[o];else if(a.length!==4)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");for(let p=0;p<o.length;++p){let u=c[p],s=f[p],t=[s[0]/u[0],s[1]/u[1]];for(let e=0;e<o[p].length;++e)for(let r=0;r<o[p][e].length;++r)for(let i=0;i<o[p][e][r].length;++i)o[p][e][r][i]*=t[i]}let h=new Tensor("int64",BigInt64Array.from(o.flat(1/0).map(p=>BigInt(Math.round(p)))),a);return{pixel_values:l,original_sizes:c,reshaped_input_sizes:f,input_points:h}}post_process_masks(n,o,l,{mask_threshold:c=0,binarize:f=!0,pad_size:a=null}={}){let h=[];a=a??this.pad_size;let p=[a.height,a.width];for(let u=0;u<o.length;++u){let s=o[u],t=l[u],e=n[u],r=[];for(let d=0;d<e.dims[0];++d){let g=e[d],m=interpolate(g,p,"bilinear",!1);m=m.slice(null,[0,t[0]],[0,t[1]]),m=interpolate(e,s,"bilinear",!1),f&&(m=new Tensor("bool",Array.from(m.data).map(b=>b>c),m.dims)),m.dims=[1,...m.dims],r.push(m)}let i=cat(r);h.push(i)}return h}}class WhisperFeatureExtractor extends FeatureExtractor{constructor(n){var o;super(n),(o=this.config).mel_filters??(o.mel_filters=getMelFilters(this.config.sampling_rate,this.config.n_fft,this.config.feature_size))}calcOffset(n,o){return Math.abs((n+o)%(2*o)-o)}padReflect(n,o,l){const c=new Float32Array(n.length+o+l),f=n.length-1;for(let a=0;a<n.length;++a)c[o+a]=n[a];for(let a=1;a<=o;++a)c[o-a]=n[this.calcOffset(a,f)];for(let a=1;a<=l;++a)c[f+o+a]=n[this.calcOffset(f-a,f)];return c}stft(n,o){const l=this.config.n_fft,c=2*(l-1),f=2*(2*l-1),a=2**Math.ceil(Math.log2(f)),h=l+2,p=new Float32Array(h*n.length),u=new Float32Array(f),s=new Float32Array(a),t=new Float32Array(a),e=new Float32Array(a),r=new Float32Array(a),i=new Float32Array(a),d=new Float32Array(a),g=-2*Math.PI/l,m=Math.cos(g),b=Math.sin(g);for(let w=0;w<f>>1;++w){const S=(w+1-l)**2/2,A=Math.sqrt(m**2+b**2)**S,O=S*Math.atan2(b,m);let x=2*w;u[x]=A*Math.cos(O),u[x+1]=A*Math.sin(O),s[x]=u[x],s[x+1]=-u[x+1]}const _=u.subarray(c,f),v=new FFT(a>>1);v.transform(r,s);for(let w=0;w<n.length;++w){const S=n[w];for(let O=0;O<_.length;O+=2){const x=O+1,I=O>>1,$=S[I]*o[I];t[O]=$*_[O],t[x]=$*_[x]}v.transform(i,t);for(let O=0;O<r.length;O+=2){const x=O+1;e[O]=i[O]*r[O]-i[x]*r[x],e[x]=i[O]*r[x]+i[x]*r[O]}v.inverseTransform(d,e);const A=w*h;for(let O=0;O<h;O+=2){const x=d[O+c],I=d[O+c+1],$=_[O],B=_[O+1],L=A+O;p[L]=x*$-I*B,p[L+1]=x*B+I*$}}return{data:p,dims:[n.length,h]}}fram_wave(n,o=!0){const l=[],c=Math.floor((this.config.n_fft-1)/2)+1,f=n.length;for(let a=0;a<f+1;a+=this.config.hop_length){let h;if(o){let p=a>c?a-c:0,u=a<f-c?a+c:f;h=n.subarray(p,u),p===0?h=this.padReflect(h,-a+c,0):u===f&&(h=this.padReflect(h,0,a-f+c))}else{h=new Float32Array(this.config.n_fft);const p=n.subarray(a,a+this.config.n_fft);p.length<this.config.n_fft?(h.set(p),h.fill(0,p.length,this.config.n_fft)):h=p}l.push(h)}return l}hanning(n){if(n<1)return[];if(n===1)return[1];const o=n-1,l=new Float32Array(o);for(let c=0;c<o;++c){const f=2*c-n+1;l[c]=.5+.5*Math.cos(Math.PI*f/o)}return l}_extract_fbank_features(n){const o=new Float32Array(this.config.n_samples);o.set(n);const l=this.hanning(this.config.n_fft+1),c=this.fram_wave(o),f=this.stft(c,l),a=f.data,h=f.dims[0]-1,p=f.dims[1]>>1,u=new Float32Array(h*p);for(let m=0;m<h;++m)for(let b=0;b<p;++b){let _=m*p+b,v=_<<1,w=a[v]**2+a[v+1]**2;u[_]=w}const s=this.config.mel_filters,t=s.length,e=new Float32Array(t*h);let r=0;for(let m=0;m<t;++m){const b=s[m];for(let _=0;_<h;++_){let v=0;for(let w=0;w<p;++w)v+=b[w]*u[_*p+w];e[r++]=v}}const i=1e-10,d=new Float32Array(e.length);let g=0;for(let m=0;m<e.length;++m){const b=Math.max(i,e[m]),_=Math.log10(b);d[m]=_,g=Math.max(_,g)}for(let m=0;m<d.length;++m)d[m]=Math.max(d[m],g-8),d[m]=(d[m]+4)/4;return{data:d,dims:[t,h]}}async _call(n){n.length>this.config.n_samples&&console.warn("Attempting to extract features for audio longer than 30 seconds. If using a pipeline to extract transcript from a long audio clip, remember to specify `chunk_length_s` and/or `stride_length_s`.");let o=n.slice(0,this.config.n_samples),l=this._extract_fbank_features(o);return{input_features:new Tensor("float32",l.data,[1,...l.dims])}}}class Processor extends Callable{constructor(n){super(),this.feature_extractor=n}async _call(n){return await this.feature_extractor(n)}}class SamProcessor extends Processor{async _call(n,o){return await this.feature_extractor(n,o)}post_process_masks(...n){return this.feature_extractor.post_process_masks(...n)}}class WhisperProcessor extends Processor{async _call(n){return await this.feature_extractor(n)}}class AutoProcessor{static async from_pretrained(n,{progress_callback:o=null,config:l=null,cache_dir:c=null,local_files_only:f=!1,revision:a="main"}={}){let h=l??await getModelJSON(n,"preprocessor_config.json",!0,{progress_callback:o,config:l,cache_dir:c,local_files_only:f,revision:a}),p=h.feature_extractor_type??h.image_processor_type,u=this.FEATURE_EXTRACTOR_CLASS_MAPPING[p];if(!u)if(h.size!==void 0)console.warn("Feature extractor type not specified, assuming ImageFeatureExtractor due to size parameter in config."),u=ImageFeatureExtractor;else throw new Error(`Unknown Feature Extractor type: ${h.feature_extractor_type}`);let s=this.PROCESSOR_CLASS_MAPPING[h.processor_class]??Processor,t=new u(h);return new s(t)}}le(AutoProcessor,"FEATURE_EXTRACTOR_CLASS_MAPPING",{WhisperFeatureExtractor,ViTFeatureExtractor,DetrFeatureExtractor,SamImageProcessor}),le(AutoProcessor,"PROCESSOR_CLASS_MAPPING",{WhisperProcessor,SamProcessor});async function prepareImages(y){return Array.isArray(y)||(y=[y]),y=await Promise.all(y.map(n=>RawImage.read(n))),y}class Pipeline extends Callable{constructor(n,o,l){super(),this.task=n,this.tokenizer=o,this.model=l}async dispose(){await this.model.dispose()}async _call(n){let o=this.tokenizer(n,{padding:!0,truncation:!0}),l=await this.model(o);return[o,l]}}class TextClassificationPipeline extends Pipeline{async _call(n,{topk:o=1}={}){let[l,c]=await super._call(n),f=this.model.config.id2label,a=[];for(let h of c.logits){let u=getTopItems(softmax(h.data),o).map(function(s){return{label:f[s[0]],score:s[1]}});o===1?a.push(...u):a.push(u)}return Array.isArray(n)||o===1?a:a[0]}}class TokenClassificationPipeline extends Pipeline{async _call(n,{ignore_labels:o=["O"]}={}){let l=Array.isArray(n);l||(n=[n]);let c=this.tokenizer,[f,a]=await super._call(n),h=a.logits,p=this.model.config.id2label,u=[];for(let s=0;s<h.dims[0];++s){let t=f.input_ids[s],e=h[s],r=[];for(let i=0;i<e.dims[0];++i){let d=e[i],g=max(d.data)[1],m=p[g];if(o.includes(m))continue;let b=c.decode([t[i].item()],{skip_special_tokens:!0});if(b==="")continue;let _=softmax(d.data);r.push({entity:m,score:_[g],index:i,word:b,start:null,end:null})}u.push(r)}return l?u:u[0]}}class QuestionAnsweringPipeline extends Pipeline{async _call(n,o,{topk:l=1}={}){let c=this.tokenizer(n,{text_pair:o}),f=await this.model(c),a=[];for(let h=0;h<f.start_logits.dims[0];++h){let p=c.input_ids[h],u=p.indexOf(this.tokenizer.sep_token_id),s=Array.from(softmax(f.start_logits[h].data)).map((r,i)=>[r,i]).filter(r=>r[1]>u),t=Array.from(softmax(f.end_logits[h].data)).map((r,i)=>[r,i]).filter(r=>r[1]>u),e=product(s,t).filter(r=>r[0][1]<=r[1][1]).map(r=>[r[0][1],r[1][1],r[0][0]*r[1][0]]).sort((r,i)=>i[2]-r[2]);for(let r=0;r<Math.min(e.length,l);++r){let[i,d,g]=e[r],m=[...p].slice(i,d+1),b=this.tokenizer.decode(m,{skip_special_tokens:!0});a.push({answer:b,score:g})}}return l===1?a[0]:a}}class FillMaskPipeline extends Pipeline{async _call(n,{topk:o=5}={}){let[l,c]=await super._call(n),f=this.tokenizer,a=[];for(let h=0;h<l.input_ids.dims[0];++h){let p=l.input_ids[h],u=p.indexOf(this.tokenizer.mask_token_id);if(u===-1)throw Error(`Mask token (${f.mask_token}) not found in text.`);let t=c.logits[h][u],e=getTopItems(softmax(t.data),o);a.push(e.map(r=>{let i=[...p];return i[u]=r[0],{score:r[1],token:r[0],token_str:f.model.vocab[r[0]],sequence:f.decode(i,{skip_special_tokens:!0})}}))}return Array.isArray(n)?a:a[0]}}class Text2TextGenerationPipeline extends Pipeline{constructor(){super(...arguments);le(this,"_key",null)}async _call(o,l={}){Array.isArray(o)||(o=[o]),this.model.config.prefix&&(o=o.map(u=>this.model.config.prefix+u));let c=this.model.config.task_specific_params;c&&c[this.task]&&c[this.task].prefix&&(o=o.map(u=>c[this.task].prefix+u));let f={padding:!0,truncation:!0},a;this instanceof TranslationPipeline&&"_build_translation_inputs"in this.tokenizer?a=this.tokenizer._build_translation_inputs(o,f,l).input_ids:a=this.tokenizer(o,f).input_ids;let h=await this.model.generate(a,l),p=this.tokenizer.batch_decode(h,{skip_special_tokens:!0});return this._key!==null&&(p=p.map(u=>this._key===null?u:{[this._key]:u})),p}}class SummarizationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);le(this,"_key","summary_text")}}class TranslationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);le(this,"_key","translation_text")}}class TextGenerationPipeline extends Pipeline{async _call(n,o={}){let l=typeof n=="string"||n instanceof String;l&&(n=[n]),this.tokenizer.padding_side="left";let c=this.tokenizer(n,{padding:!0,truncation:!0}),f=c.input_ids,a=c.attention_mask,h=await this.model.generate(f,o,null,{inputs_attention_mask:a});const p=n.map(t=>t.trim()),u=this.tokenizer.batch_decode(h,{skip_special_tokens:!0}),s=Array.from({length:n.length},t=>[]);for(let t=0;t<u.length;++t){const e=Math.floor(t/h.length*p.length);let r=p[e];s[e].push({generated_text:r+u[t]})}return l&&s.length===1?s[0]:s}}class ZeroShotClassificationPipeline extends Pipeline{constructor(n,o,l){super(n,o,l),this.label2id=Object.fromEntries(Object.entries(this.model.config.label2id).map(([c,f])=>[c.toLowerCase(),f])),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.contradiction_id===void 0&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(n,o,{hypothesis_template:l="This example is {}.",multi_label:c=!1}={}){let f=Array.isArray(n);f||(n=[n]),Array.isArray(o)||(o=[o]);let a=o.map(u=>l.replace("{}",u)),h=c||o.length===1,p=[];for(let u of n){let s=[];for(let r of a){let i=this.tokenizer(u,{text_pair:r}),d=await this.model(i);h?s.push([d.logits.data[this.contradiction_id],d.logits.data[this.entailment_id]]):s.push(d.logits.data[this.entailment_id])}let t;h?t=s.map(r=>softmax(r)[1]):t=softmax(s);let e=t.map((r,i)=>[r,i]).sort((r,i)=>i[0]-r[0]);p.push({sequence:u,labels:e.map(r=>o[r[1]]),scores:e.map(r=>r[0])})}return f?p:p[0]}}class FeatureExtractionPipeline extends Pipeline{async _call(n,{pooling:o="none",normalize:l=!1}={}){let[c,f]=await super._call(n),a=f.last_hidden_state??f.logits;if(o!=="none")if(o==="mean")a=mean_pooling(a,c.attention_mask);else throw Error(`Pooling method '${o}' not supported.`);return l&&(a=a.normalize(2,-1)),a}}class AutomaticSpeechRecognitionPipeline extends Pipeline{constructor(n,o,l,c){super(n,o,l),this.processor=c}async _preprocess(n,o){return isString(n)&&(n=await read_audio(n,o)),n}async _call(n,o={}){let l=o.return_timestamps??!1,c=o.chunk_length_s??0,f=o.stride_length_s??null,a=o.chunk_callback??null,h=o.force_full_sequences??!1,p=pop(o,"language",null),u=pop(o,"task",null);if(p||u||l){if(o.forced_decoder_ids)throw new Error("Cannot specify `language`/`task`/`return_timestamps` and `forced_decoder_ids` at the same time.");let i=this.tokenizer.get_decoder_prompt_ids({language:p,task:u,no_timestamps:!l});i.length>0&&(o.forced_decoder_ids=i)}let s=!Array.isArray(n);s&&(n=[n]);const t=this.processor.feature_extractor.config.sampling_rate,e=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions;let r=[];for(let i of n){i=await this._preprocess(i,t);let d=[];if(c>0){if(f===null)f=c/6;else if(c<=f)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const b=t*c,_=t*f,v=b-2*_;let w=0;for(;w<i.length;){let S=i.subarray(w,w+b),A=await this.processor(S),O=w===0,x=w+v>=i.length;d.push({stride:[S.length,O?0:_,x?0:_],input_features:A.input_features,is_last:x}),w+=v}}else d=[{stride:[i.length,0,0],input_features:(await this.processor(i)).input_features,is_last:!0}];for(let b of d){let _=await this.model.generate(b.input_features,o);b.tokens=_[0],b.stride=b.stride.map(v=>v/t),a!==null&&a(b)}let[g,m]=this.tokenizer._decode_asr(d,{time_precision:e,return_timestamps:l,force_full_sequences:h});r.push({text:g,...m})}return s?r[0]:r}}class ImageToTextPipeline extends Pipeline{constructor(n,o,l,c){super(n,o,l),this.processor=c}async _call(n,o={}){let l=Array.isArray(n);n=await prepareImages(n);let{pixel_values:c}=await this.processor(n),f=[];for(let a of c){a.dims=[1,...a.dims];let h=await this.model.generate(a,o),p=this.tokenizer.batch_decode(h,{skip_special_tokens:!0}).map(u=>({generated_text:u.trim()}));f.push(p)}return l?f:f[0]}}class ImageClassificationPipeline extends Pipeline{constructor(n,o,l){super(n,null,o),this.processor=l}async _call(n,{topk:o=1}={}){let l=Array.isArray(n);n=await prepareImages(n);let{pixel_values:c}=await this.processor(n),f=await this.model({pixel_values:c}),a=this.model.config.id2label,h=[];for(let p of f.logits){let s=getTopItems(softmax(p.data),o).map(function(t){return{label:a[t[0]],score:t[1]}});o===1?h.push(...s):h.push(s)}return l||o===1?h:h[0]}}class ImageSegmentationPipeline extends Pipeline{constructor(n,o,l){super(n,null,o),this.processor=l,this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(n,{threshold:o=.5,mask_threshold:l=.5,overlap_mask_area_threshold:c=.8,label_ids_to_fuse:f=null,target_sizes:a=null,subtask:h=null}={}){if(Array.isArray(n)&&n.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");n=await prepareImages(n);let u=n.map(d=>[d.height,d.width]),{pixel_values:s,pixel_mask:t}=await this.processor(n),e=await this.model({pixel_values:s,pixel_mask:t}),r=null;if(h!==null)r=this.subtasks_mapping[h];else for(let[d,g]of Object.entries(this.subtasks_mapping))if(g in this.processor.feature_extractor){r=this.processor.feature_extractor[g].bind(this.processor.feature_extractor),h=d;break}let i=[];if(h==="panoptic"||h==="instance"){let d=r(e,o,l,c,f,a??u)[0],g=d.segmentation,m=this.model.config.id2label;for(let b of d.segments_info){let _=new Uint8ClampedArray(g.data.length);for(let w=0;w<g.data.length;++w)g.data[w]===b.id&&(_[w]=255);let v=new RawImage(_,g.dims[1],g.dims[0],1);i.push({score:b.score,label:m[b.label_id],mask:v})}}else throw Error(h==="semantic"?"semantic segmentation not yet supported.":`Subtask ${h} not supported.`);return i}}class ZeroShotImageClassificationPipeline extends Pipeline{constructor(n,o,l,c){super(n,o,l),this.processor=c}async _call(n,o,{hypothesis_template:l="This is a photo of {}"}={}){let c=Array.isArray(n);n=await prepareImages(n);let f=o.map(s=>l.replace("{}",s)),a=this.tokenizer(f,{padding:!0,truncation:!0}),{pixel_values:h}=await this.processor(n),p=await this.model({...a,pixel_values:h}),u=[];for(let s of p.logits_per_image){let t=softmax(s.data);u.push([...t].map((e,r)=>({score:e,label:o[r]})))}return c?u:u[0]}}class ObjectDetectionPipeline extends Pipeline{constructor(n,o,l){super(n,null,o),this.processor=l}async _call(n,{threshold:o=.9,percentage:l=!1}={}){let c=Array.isArray(n);if(c&&n.length!==1)throw Error("Object detection pipeline currently only supports a batch size of 1.");n=await prepareImages(n);let f=l?null:n.map(t=>[t.height,t.width]),{pixel_values:a,pixel_mask:h}=await this.processor(n),p=await this.model({pixel_values:a,pixel_mask:h}),u=this.processor.feature_extractor.post_process_object_detection(p,o,f),s=this.model.config.id2label;return u.forEach(t=>t.labels=t.classes.map(e=>s[e])),c?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"},"automatic-speech-recognition":{tokenizer:AutoTokenizer,pipeline:AutomaticSpeechRecognitionPipeline,model:AutoModelForSeq2SeqLM,processor:AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"image-to-text":{tokenizer:AutoTokenizer,pipeline:ImageToTextPipeline,model:AutoModelForVision2Seq,processor:AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:ImageClassificationPipeline,model:AutoModelForImageClassification,processor:AutoProcessor,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:ImageSegmentationPipeline,model:AutoModelForImageSegmentation,processor:AutoProcessor,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotImageClassificationPipeline,model:AutoModel,processor:AutoProcessor,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:ObjectDetectionPipeline,model:AutoModelForObjectDetection,processor:AutoProcessor,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"feature-extraction":{tokenizer:AutoTokenizer,pipeline:FeatureExtractionPipeline,model:AutoModel,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"}},TASK_ALIASES={"sentiment-analysis":"text-classification",ner:"token-classification",vqa:"visual-question-answering",asr:"automatic-speech-recognition",embeddings:"feature-extraction"};async function pipeline(y,n=null,{quantized:o=!0,progress_callback:l=null,config:c=null,cache_dir:f=null,local_files_only:a=!1,revision:h="main"}={}){y=TASK_ALIASES[y]??y;let p=SUPPORTED_TASKS[y.split("_",1)[0]];if(!p)throw Error(`Unsupported pipeline: ${y}. Must be one of [${Object.keys(SUPPORTED_TASKS)}]`);n||(n=p.default.model,console.log(`No model specified. Using default model: "${n}".`));let u=p.tokenizer,s=p.model,t=p.pipeline,e=p.processor,r=[],i={quantized:o,progress_callback:l,config:c,cache_dir:f,local_files_only:a,revision:h};u&&r.push(u.from_pretrained(n,i)),s&&r.push(s.from_pretrained(n,i)),e&&r.push(e.from_pretrained(n,i));let d=await Promise.all(r);return dispatchCallback(l,{status:"ready",task:y,model:n}),new t(y,...d)}function product(...y){return y.reduce((n,o)=>n.flatMap(l=>o.map(c=>[l,c])))}env.allowLocalModels=!1;class PipelineFactory{constructor(n,o,l){this.tokenizer=n,this.model=o,this.quantized=l}static async getInstance(n=null){return this.instance===null&&(this.instance=pipeline(this.task,this.model,{quantized:this.quantized,progress_callback:n})),this.instance}}le(PipelineFactory,"task",null),le(PipelineFactory,"model",null),le(PipelineFactory,"quantized",null),le(PipelineFactory,"instance",null),self.addEventListener("message",async y=>{const n=y.data;let o=await transcribe(n.audio,n.model,n.model,n.quantized,n.subtask,n.language);o!==null&&self.postMessage({status:"complete",task:"automatic-speech-recognition",data:o})});class AutomaticSpeechRecognitionPipelineFactory extends PipelineFactory{}le(AutomaticSpeechRecognitionPipelineFactory,"task","automatic-speech-recognition"),le(AutomaticSpeechRecognitionPipelineFactory,"model",null),le(AutomaticSpeechRecognitionPipelineFactory,"quantized",null);const transcribe=async(y,n,o,l,c,f)=>{const a=`Xenova/whisper-${n}${o?"":".en"}`,h=AutomaticSpeechRecognitionPipelineFactory;(h.model!==a||h.quantized!==l)&&(h.model=a,h.quantized=l,h.instance!==null&&((await h.getInstance()).dispose(),h.instance=null));let p=await h.getInstance(i=>{self.postMessage(i)});const u=p.processor.feature_extractor.config.chunk_length/p.model.config.max_source_positions;let s=[{tokens:[],finalised:!1}];function t(i){let d=s[s.length-1];Object.assign(d,i),d.finalised=!0,i.is_last||s.push({tokens:[],finalised:!1})}function e(i){let d=s[s.length-1];d.tokens=[...i[0].output_token_ids];let g=p.tokenizer._decode_asr(s,{time_precision:u,return_timestamps:!0,force_full_sequences:!1});self.postMessage({status:"update",task:"automatic-speech-recognition",data:g})}return await p(y,{top_k:0,do_sample:!1,chunk_length_s:30,stride_length_s:5,language:f,task:c,return_timestamps:!0,force_full_sequences:!1,callback_function:e,chunk_callback:t}).catch(i=>(self.postMessage({status:"error",task:"automatic-speech-recognition",data:i}),null))}})();