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ERR: ${o.map(a=>`[${a.name}] ${a.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$2=new EnvImpl,isBigInt64ArrayAvailable=typeof BigInt64Array<"u"&&typeof BigInt64Array.from=="function",isBigUint64ArrayAvailable=typeof BigUint64Array<"u"&&typeof BigUint64Array.from=="function",NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP=new Map([["float32",Float32Array],["uint8",Uint8Array],["int8",Int8Array],["uint16",Uint16Array],["int16",Int16Array],["int32",Int32Array],["bool",Uint8Array],["float64",Float64Array],["uint32",Uint32Array]]),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP=new Map([[Float32Array,"float32"],[Uint8Array,"uint8"],[Int8Array,"int8"],[Uint16Array,"uint16"],[Int16Array,"int16"],[Int32Array,"int32"],[Float64Array,"float64"],[Uint32Array,"uint32"]]);isBigInt64ArrayAvailable&&(NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set("int64",BigInt64Array),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigInt64Array,"int64")),isBigUint64ArrayAvailable&&(NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set("uint64",BigUint64Array),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigUint64Array,"uint64"));const calculateSize=f=>{let n=1;for(let o=0;o<f.length;o++){const a=f[o];if(typeof a!="number"||!Number.isSafeInteger(a))throw new TypeError(`dims[${o}] must be an integer, got: ${a}`);if(a<0)throw new RangeError(`dims[${o}] must be a non-negative integer, got: ${a}`);n*=a}return n};let Tensor$2=class ut{constructor(n,o,a){let l,p,u;if(typeof n=="string")if(l=n,u=a,n==="string"){if(!Array.isArray(o))throw new TypeError("A string tensor's data must be a string array.");p=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:a,width:l}=o,p=o.norm;let u,h;p===void 0||p.mean===void 0?u=255:u=p.mean,p===void 0||p.bias===void 0?h=0:h=p.bias;const g=o.bitmapFormat!==void 0?o.bitmapFormat:"RGBA",c=o.tensorFormat!==void 0&&o.tensorFormat!==void 0?o.tensorFormat:"RGB",s=a*l,t=c==="RGBA"?new Float32Array(s*4):new Float32Array(s*3);let e=4,r=0,i=1,d=2,m=3,_=0,b=s,y=s*2,T=-1;g==="RGB"&&(e=3,r=0,i=1,d=2,m=-1),c==="RGBA"?T=s*3:c==="RBG"?(_=0,y=s,b=s*2):c==="BGR"&&(y=0,b=s,_=s*2);for(let S=0;S<s;S++,r+=e,d+=e,i+=e,m+=e)t[_++]=(n[r]+h)/u,t[b++]=(n[i]+h)/u,t[y++]=(n[d]+h)/u,T!==-1&&m!==-1&&(t[T++]=(n[m]+h)/u);return c==="RGBA"?new ut("float32",t,[1,4,a,l]):new ut("float32",t,[1,3,a,l])}static async fromImage(n,o){const a=typeof HTMLImageElement<"u"&&n instanceof HTMLImageElement,l=typeof ImageData<"u"&&n instanceof ImageData,p=typeof 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i=0;i<e.floats.length;++i)r.float(e.floats[i]);r.ldelim()}if(e.ints!=null&&e.ints.length){for(r.uint32(66).fork(),i=0;i<e.ints.length;++i)r.int64(e.ints[i]);r.ldelim()}if(e.strings!=null&&e.strings.length)for(i=0;i<e.strings.length;++i)r.uint32(74).bytes(e.strings[i]);if(e.tensors!=null&&e.tensors.length)for(i=0;i<e.tensors.length;++i)s.onnx.TensorProto.encode(e.tensors[i],r.uint32(82).fork()).ldelim();if(e.graphs!=null&&e.graphs.length)for(i=0;i<e.graphs.length;++i)s.onnx.GraphProto.encode(e.graphs[i],r.uint32(90).fork()).ldelim();return e.docString!=null&&e.hasOwnProperty("docString")&&r.uint32(106).string(e.docString),e.type!=null&&e.hasOwnProperty("type")&&r.uint32(160).int32(e.type),e.refAttrName!=null&&e.hasOwnProperty("refAttrName")&&r.uint32(170).string(e.refAttrName),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.AttributeProto;e.pos<i;){var m=e.uint32();switch(m>>>3){case 1:d.name=e.string();break;case 21:d.refAttrName=e.string();break;case 13:d.docString=e.string();break;case 20:d.type=e.int32();break;case 2:d.f=e.float();break;case 3:d.i=e.int64();break;case 4:d.s=e.bytes();break;case 5:d.t=s.onnx.TensorProto.decode(e,e.uint32());break;case 6:d.g=s.onnx.GraphProto.decode(e,e.uint32());break;case 7:if(d.floats&&d.floats.length||(d.floats=[]),(7&m)==2)for(var _=e.uint32()+e.pos;e.pos<_;)d.floats.push(e.float());else d.floats.push(e.float());break;case 8:if(d.ints&&d.ints.length||(d.ints=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.ints.push(e.int64());else d.ints.push(e.int64());break;case 9:d.strings&&d.strings.length||(d.strings=[]),d.strings.push(e.bytes());break;case 10:d.tensors&&d.tensors.length||(d.tensors=[]),d.tensors.push(s.onnx.TensorProto.decode(e,e.uint32()));break;case 11:d.graphs&&d.graphs.length||(d.graphs=[]),d.graphs.push(s.onnx.GraphProto.decode(e,e.uint32()));break;default:e.skipType(7&m)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.name!=null&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(e.refAttrName!=null&&e.hasOwnProperty("refAttrName")&&!c.isString(e.refAttrName))return"refAttrName: string expected";if(e.docString!=null&&e.hasOwnProperty("docString")&&!c.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")&&!(c.isInteger(e.i)||e.i&&c.isInteger(e.i.low)&&c.isInteger(e.i.high)))return"i: integer|Long expected";if(e.s!=null&&e.hasOwnProperty("s")&&!(e.s&&typeof e.s.length=="number"||c.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(!(c.isInteger(e.ints[r])||e.ints[r]&&c.isInteger(e.ints[r].low)&&c.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"||c.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&&(c.Long?(r.i=c.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 c.LongBits(e.i.low>>>0,e.i.high>>>0).toNumber())),e.s!=null&&(typeof e.s=="string"?c.base64.decode(e.s,r.s=c.newBuffer(c.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)c.Long?(r.ints[i]=c.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 c.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"?c.base64.decode(e.strings[i],r.strings[i]=c.newBuffer(c.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,c.Long){var d=new c.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=c.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?c.Long.prototype.toString.call(e.i):r.longs===Number?new c.LongBits(e.i.low>>>0,e.i.high>>>0).toNumber():e.i),e.s!=null&&e.hasOwnProperty("s")&&(i.s=r.bytes===String?c.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 m=0;m<e.floats.length;++m)i.floats[m]=r.json&&!isFinite(e.floats[m])?String(e.floats[m]):e.floats[m]}if(e.ints&&e.ints.length)for(i.ints=[],m=0;m<e.ints.length;++m)typeof e.ints[m]=="number"?i.ints[m]=r.longs===String?String(e.ints[m]):e.ints[m]:i.ints[m]=r.longs===String?c.Long.prototype.toString.call(e.ints[m]):r.longs===Number?new c.LongBits(e.ints[m].low>>>0,e.ints[m].high>>>0).toNumber():e.ints[m];if(e.strings&&e.strings.length)for(i.strings=[],m=0;m<e.strings.length;++m)i.strings[m]=r.bytes===String?c.base64.encode(e.strings[m],0,e.strings[m].length):r.bytes===Array?Array.prototype.slice.call(e.strings[m]):e.strings[m];if(e.tensors&&e.tensors.length)for(i.tensors=[],m=0;m<e.tensors.length;++m)i.tensors[m]=s.onnx.TensorProto.toObject(e.tensors[m],r);if(e.graphs&&e.graphs.length)for(i.graphs=[],m=0;m<e.graphs.length;++m)i.graphs[m]=s.onnx.GraphProto.toObject(e.graphs[m],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,u.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}(),p.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=g.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 m=e.uint32();switch(m>>>3){case 1:d.name=e.string();break;case 2:d.type=s.onnx.TypeProto.decode(e,e.uint32());break;case 3:d.docString=e.string();break;default:e.skipType(7&m)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.name!=null&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(e.type!=null&&e.hasOwnProperty("type")){var r=s.onnx.TypeProto.verify(e.type);if(r)return"type."+r}return e.docString!=null&&e.hasOwnProperty("docString")&&!c.isString(e.docString)?"docString: string expected":null},t.fromObject=function(e){if(e instanceof s.onnx.ValueInfoProto)return e;var r=new s.onnx.ValueInfoProto;if(e.name!=null&&(r.name=String(e.name)),e.type!=null){if(typeof e.type!="object")throw TypeError(".onnx.ValueInfoProto.type: object expected");r.type=s.onnx.TypeProto.fromObject(e.type)}return e.docString!=null&&(r.docString=String(e.docString)),r},t.toObject=function(e,r){r||(r={});var i={};return r.defaults&&(i.name="",i.type=null,i.docString=""),e.name!=null&&e.hasOwnProperty("name")&&(i.name=e.name),e.type!=null&&e.hasOwnProperty("type")&&(i.type=s.onnx.TypeProto.toObject(e.type,r)),e.docString!=null&&e.hasOwnProperty("docString")&&(i.docString=e.docString),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,u.util.toJSONOptions)},t}(),p.NodeProto=function(){function t(e){if(this.input=[],this.output=[],this.attribute=[],e)for(var r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.input=c.emptyArray,t.prototype.output=c.emptyArray,t.prototype.name="",t.prototype.opType="",t.prototype.domain="",t.prototype.attribute=c.emptyArray,t.prototype.docString="",t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=g.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 m=e.uint32();switch(m>>>3){case 1:d.input&&d.input.length||(d.input=[]),d.input.push(e.string());break;case 2:d.output&&d.output.length||(d.output=[]),d.output.push(e.string());break;case 3:d.name=e.string();break;case 4:d.opType=e.string();break;case 7:d.domain=e.string();break;case 5:d.attribute&&d.attribute.length||(d.attribute=[]),d.attribute.push(s.onnx.AttributeProto.decode(e,e.uint32()));break;case 6:d.docString=e.string();break;default:e.skipType(7&m)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.input!=null&&e.hasOwnProperty("input")){if(!Array.isArray(e.input))return"input: array expected";for(var r=0;r<e.input.length;++r)if(!c.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(!c.isString(e.output[r]))return"output: string[] expected"}if(e.name!=null&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(e.opType!=null&&e.hasOwnProperty("opType")&&!c.isString(e.opType))return"opType: string expected";if(e.domain!=null&&e.hasOwnProperty("domain")&&!c.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")&&!c.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,u.util.toJSONOptions)},t}(),p.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=c.Long?c.Long.fromBits(0,0,!1):0,t.prototype.opsetImport=c.emptyArray,t.prototype.producerName="",t.prototype.producerVersion="",t.prototype.domain="",t.prototype.modelVersion=c.Long?c.Long.fromBits(0,0,!1):0,t.prototype.docString="",t.prototype.graph=null,t.prototype.metadataProps=c.emptyArray,t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=g.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 m=e.uint32();switch(m>>>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&&(c.Long?(r.irVersion=c.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 c.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&&(c.Long?(r.modelVersion=c.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=g.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 m=e.uint32();switch(m>>>3){case 1:d.key=e.string();break;case 2:d.value=e.string();break;default:e.skipType(7&m)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){return typeof e!="object"||e===null?"object expected":e.key!=null&&e.hasOwnProperty("key")&&!c.isString(e.key)?"key: string expected":e.value!=null&&e.hasOwnProperty("value")&&!c.isString(e.value)?"value: string expected":null},t.fromObject=function(e){if(e instanceof s.onnx.StringStringEntryProto)return e;var r=new s.onnx.StringStringEntryProto;return e.key!=null&&(r.key=String(e.key)),e.value!=null&&(r.value=String(e.value)),r},t.toObject=function(e,r){r||(r={});var i={};return r.defaults&&(i.key="",i.value=""),e.key!=null&&e.hasOwnProperty("key")&&(i.key=e.key),e.value!=null&&e.hasOwnProperty("value")&&(i.value=e.value),i},t.prototype.toJSON=function(){return this.constructor.toObject(this,u.util.toJSONOptions)},t}(),p.TensorAnnotation=function(){function t(e){if(this.quantParameterTensorNames=[],e)for(var r=Object.keys(e),i=0;i<r.length;++i)e[r[i]]!=null&&(this[r[i]]=e[r[i]])}return t.prototype.tensorName="",t.prototype.quantParameterTensorNames=c.emptyArray,t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=g.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 m=e.uint32();switch(m>>>3){case 1:d.tensorName=e.string();break;case 2:d.quantParameterTensorNames&&d.quantParameterTensorNames.length||(d.quantParameterTensorNames=[]),d.quantParameterTensorNames.push(s.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&m)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.tensorName!=null&&e.hasOwnProperty("tensorName")&&!c.isString(e.tensorName))return"tensorName: string expected";if(e.quantParameterTensorNames!=null&&e.hasOwnProperty("quantParameterTensorNames")){if(!Array.isArray(e.quantParameterTensorNames))return"quantParameterTensorNames: array expected";for(var r=0;r<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,u.util.toJSONOptions)},t}(),p.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=c.emptyArray,t.prototype.name="",t.prototype.initializer=c.emptyArray,t.prototype.docString="",t.prototype.input=c.emptyArray,t.prototype.output=c.emptyArray,t.prototype.valueInfo=c.emptyArray,t.prototype.quantizationAnnotation=c.emptyArray,t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=g.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 m=e.uint32();switch(m>>>3){case 1:d.node&&d.node.length||(d.node=[]),d.node.push(s.onnx.NodeProto.decode(e,e.uint32()));break;case 2:d.name=e.string();break;case 5:d.initializer&&d.initializer.length||(d.initializer=[]),d.initializer.push(s.onnx.TensorProto.decode(e,e.uint32()));break;case 10:d.docString=e.string();break;case 11:d.input&&d.input.length||(d.input=[]),d.input.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 12:d.output&&d.output.length||(d.output=[]),d.output.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 13:d.valueInfo&&d.valueInfo.length||(d.valueInfo=[]),d.valueInfo.push(s.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 14:d.quantizationAnnotation&&d.quantizationAnnotation.length||(d.quantizationAnnotation=[]),d.quantizationAnnotation.push(s.onnx.TensorAnnotation.decode(e,e.uint32()));break;default:e.skipType(7&m)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.node!=null&&e.hasOwnProperty("node")){if(!Array.isArray(e.node))return"node: array expected";for(var r=0;r<e.node.length;++r)if(i=s.onnx.NodeProto.verify(e.node[r]))return"node."+i}if(e.name!=null&&e.hasOwnProperty("name")&&!c.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")&&!c.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,u.util.toJSONOptions)},t}(),p.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=c.emptyArray,t.prototype.dataType=0,t.prototype.segment=null,t.prototype.floatData=c.emptyArray,t.prototype.int32Data=c.emptyArray,t.prototype.stringData=c.emptyArray,t.prototype.int64Data=c.emptyArray,t.prototype.name="",t.prototype.docString="",t.prototype.rawData=c.newBuffer([]),t.prototype.externalData=c.emptyArray,t.prototype.dataLocation=0,t.prototype.doubleData=c.emptyArray,t.prototype.uint64Data=c.emptyArray,t.create=function(e){return new t(e)},t.encode=function(e,r){if(r||(r=g.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 m=e.uint32();switch(m>>>3){case 1:if(d.dims&&d.dims.length||(d.dims=[]),(7&m)==2)for(var _=e.uint32()+e.pos;e.pos<_;)d.dims.push(e.int64());else d.dims.push(e.int64());break;case 2:d.dataType=e.int32();break;case 3:d.segment=s.onnx.TensorProto.Segment.decode(e,e.uint32());break;case 4:if(d.floatData&&d.floatData.length||(d.floatData=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.floatData.push(e.float());else d.floatData.push(e.float());break;case 5:if(d.int32Data&&d.int32Data.length||(d.int32Data=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.int32Data.push(e.int32());else d.int32Data.push(e.int32());break;case 6:d.stringData&&d.stringData.length||(d.stringData=[]),d.stringData.push(e.bytes());break;case 7:if(d.int64Data&&d.int64Data.length||(d.int64Data=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.int64Data.push(e.int64());else d.int64Data.push(e.int64());break;case 8:d.name=e.string();break;case 12:d.docString=e.string();break;case 9:d.rawData=e.bytes();break;case 13:d.externalData&&d.externalData.length||(d.externalData=[]),d.externalData.push(s.onnx.StringStringEntryProto.decode(e,e.uint32()));break;case 14:d.dataLocation=e.int32();break;case 10:if(d.doubleData&&d.doubleData.length||(d.doubleData=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.doubleData.push(e.double());else d.doubleData.push(e.double());break;case 11:if(d.uint64Data&&d.uint64Data.length||(d.uint64Data=[]),(7&m)==2)for(_=e.uint32()+e.pos;e.pos<_;)d.uint64Data.push(e.uint64());else d.uint64Data.push(e.uint64());break;default:e.skipType(7&m)}}return d},t.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},t.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.dims!=null&&e.hasOwnProperty("dims")){if(!Array.isArray(e.dims))return"dims: array expected";for(var r=0;r<e.dims.length;++r)if(!(c.isInteger(e.dims[r])||e.dims[r]&&c.isInteger(e.dims[r].low)&&c.isInteger(e.dims[r].high)))return"dims: integer|Long[] expected"}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&!c.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(!c.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"||c.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(!(c.isInteger(e.int64Data[r])||e.int64Data[r]&&c.isInteger(e.int64Data[r].low)&&c.isInteger(e.int64Data[r].high)))return"int64Data: integer|Long[] expected"}if(e.name!=null&&e.hasOwnProperty("name")&&!c.isString(e.name))return"name: string expected";if(e.docString!=null&&e.hasOwnProperty("docString")&&!c.isString(e.docString))return"docString: string expected";if(e.rawData!=null&&e.hasOwnProperty("rawData")&&!(e.rawData&&typeof e.rawData.length=="number"||c.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(!(c.isInteger(e.uint64Data[r])||e.uint64Data[r]&&c.isInteger(e.uint64Data[r].low)&&c.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)c.Long?(r.dims[i]=c.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 c.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"?c.base64.decode(e.stringData[i],r.stringData[i]=c.newBuffer(c.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)c.Long?(r.int64Data[i]=c.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 c.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"?c.base64.decode(e.rawData,r.rawData=c.newBuffer(c.base64.length(e.rawData)),0):e.rawData.length&&(r.rawData=e.rawData)),e.externalData){if(!Array.isArray(e.externalData))throw TypeError(".onnx.TensorProto.externalData: array expected");for(r.externalData=[],i=0;i<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 expected");for(r.doubleData=[],i=0;i<e.doubleData.length;++i)r.doubleData[i]=Number(e.doubleData[i])}if(e.uint64Data){if(!Array.isArray(e.uint64Data))throw TypeError(".onnx.TensorProto.uint64Data: array expected");for(r.uint64Data=[],i=0;i<e.uint64Data.length;++i)c.Long?(r.uint64Data[i]=c.Long.fromValue(e.uint64Data[i])).unsigned=!0:typeof e.uint64Data[i]=="string"?r.uint64Data[i]=parseInt(e.uint64Data[i],10):typeof e.uint64Data[i]=="number"?r.uint64Data[i]=e.uint64Data[i]:typeof e.uint64Data[i]=="object"&&(r.uint64Data[i]=new c.LongBits(e.uint64Data[i].low>>>0,e.uint64Data[i].high>>>0).toNumber(!0))}return r},t.toObject=function(e,r){r||(r={});var i={};if((r.arrays||r.defaults)&&(i.dims=[],i.floatData=[],i.int32Data=[],i.stringData=[],i.int64Data=[],i.doubleData=[],i.uint64Data=[],i.externalData=[]),r.defaults&&(i.dataType=0,i.segment=null,i.name="",r.bytes===String?i.rawData="":(i.rawData=[],r.bytes!==Array&&(i.rawData=c.newBuffer(i.rawData))),i.docString="",i.dataLocation=r.enums===String?"DEFAULT":0),e.dims&&e.dims.length){i.dims=[];for(var d=0;d<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?c.Long.prototype.toString.call(e.dims[d]):r.longs===Number?new c.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?c.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?c.Long.prototype.toString.call(e.int64Data[d]):r.longs===Number?new c.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?c.base64.encode(e.rawData,0,e.rawData.length):r.bytes===Array?Array.prototype.slice.call(e.rawData):e.rawData),e.doubleData&&e.doubleData.length)for(i.doubleData=[],d=0;d<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?c.Long.prototype.toString.call(e.uint64Data[d]):r.longs===Number?new c.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,u.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=c.Long?c.Long.fromBits(0,0,!1):0,e.prototype.end=c.Long?c.Long.fromBits(0,0,!1):0,e.create=function(r){return new e(r)},e.encode=function(r,i){return i||(i=g.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,m=new s.onnx.TensorProto.Segment;r.pos<d;){var _=r.uint32();switch(_>>>3){case 1:m.begin=r.int64();break;case 2:m.end=r.int64();break;default:r.skipType(7&_)}}return m},e.decodeDelimited=function(r){return r instanceof h||(r=new h(r)),this.decode(r,r.uint32())},e.verify=function(r){return typeof r!="object"||r===null?"object expected":r.begin!=null&&r.hasOwnProperty("begin")&&!(c.isInteger(r.begin)||r.begin&&c.isInteger(r.begin.low)&&c.isInteger(r.begin.high))?"begin: integer|Long expected":r.end!=null&&r.hasOwnProperty("end")&&!(c.isInteger(r.end)||r.end&&c.isInteger(r.end.low)&&c.isInteger(r.end.high))?"end: integer|Long expected":null},e.fromObject=function(r){if(r instanceof s.onnx.TensorProto.Segment)return r;var i=new s.onnx.TensorProto.Segment;return r.begin!=null&&(c.Long?(i.begin=c.Long.fromValue(r.begin)).unsigned=!1:typeof r.begin=="string"?i.begin=parseInt(r.begin,10):typeof r.begin=="number"?i.begin=r.begin:typeof r.begin=="object"&&(i.begin=new 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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,p.getGlsl)(this.context.glContext.version).output} = val;
      }
    `;return r.floatTextureSetRGBA=new l.GlslLibRoutine(d),r}getUnpackedOutputSamplingSnippet(s){const t=s.unpackedShape,e=[s.width,s.height],r={},i="getOutputCoords";switch(t.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputUnpacked1DCoords(t,e);break;case 2:r[i]=this.getOutputUnpacked2DCoords(t,e);break;case 3:r[i]=this.getOutputUnpacked3DCoords(t,e);break;case 4:r[i]=this.getOutputUnpacked4DCoords(t,e);break;case 5:r[i]=this.getOutputUnpacked5DCoords(t,e);break;case 6:r[i]=this.getOutputUnpacked6DCoords(t,e);break;default:throw new Error(`Unsupported output dimensionality: ${t.length}`)}const d=`
        void setOutput(float val) {
          ${(0,p.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0);
        }
    `;return r.floatTextureSetR=new l.GlslLibRoutine(d),r}getOutputScalarCoords(){return new l.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 l.GlslLibRoutine(r)):e[1]===1?(r=`
          int getOutputCoords() {
            return 2 * int(TexCoords.x * ${e[0]}.0);
          }
        `,new l.GlslLibRoutine(r)):(r=`
        int getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                 vec2(${e[0]}, ${e[1]}));
          return 2 * (resTexRC.y * ${e[0]} + resTexRC.x);
        }
      `,new l.GlslLibRoutine(r))}getOutputPacked2DCoords(s,t){let e="";if(a.ArrayUtil.arraysEqual(s,t))return e=`
        ivec2 getOutputCoords() {
          return 2 * ivec2(TexCoords.xy * vec2(${t[0]}, ${t[1]}));
        }
      `,new l.GlslLibRoutine(e);const r=t,i=Math.ceil(s[1]/2);return e=`
        ivec2 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${r[0]}, ${r[1]}));

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

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

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

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

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

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

        ${m}

        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${s.length}(${_});
      }
    `;return new l.GlslLibRoutine(b)}getOutputUnpacked1DCoords(s,t){const e=`
        int getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          return resTexRC.y * ${t[0]} + resTexRC.x;
        }
      `;return new l.GlslLibRoutine(e)}getOutputUnpacked2DCoords(s,t){const e=`
        ivec2 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${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 l.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 _=r-3;_>=0;--_)i[_]=i[_+1]*s[_+1];const d=["r","c","d"],m=i.map((_,b)=>`int ${d[b]} = index / ${_}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${_}`:`index -= ${d[b]} * ${_}`};`).join("");return e=`
        ivec3 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          int index = resTexRC.y * ${t[0]} + resTexRC.x;
          ${m}
          return ivec3(r, c, d);
        }
      `,new l.GlslLibRoutine(e)}getOutputUnpacked4DCoords(s,t){let e="";const r=s.length;let i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=s[r-1];for(let _=r-3;_>=0;--_)i[_]=i[_+1]*s[_+1];const d=["r","c","d","d2"],m=i.map((_,b)=>`int ${d[b]} = index / ${_}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${_}`:`index -= ${d[b]} * ${_}`};`).join("");return e=`
      ivec4 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          int index = resTexRC.y * ${t[0]} + resTexRC.x;
          ${m}
          return ivec4(r, c, d, d2);
        }
      `,new l.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 _=r-3;_>=0;--_)i[_]=i[_+1]*s[_+1];const d=["r","c","d","d2","d3"],m=i.map((_,b)=>`int ${d[b]} = index / ${_}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${_}`:`index -= ${d[b]} * ${_}`};`).join("");return e=`
      ivec5 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${t[0]}, ${t[1]}));
          int index = resTexRC.y * ${t[0]} + resTexRC.x;
          ${m}
          return ivec5(r, c, d, d2, d3);
        }
      `,new l.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 _=r-3;_>=0;--_)i[_]=i[_+1]*s[_+1];const d=["r","c","d","d2","d3","d4"],m=i.map((_,b)=>`int ${d[b]} = index / ${_}; ${b===i.length-1?`int ${d[b+1]} = index - ${d[b]} * ${_}`:`index -= ${d[b]} * ${_}`};`).join("");return e=`
     ivec6 getOutputCoords() {
         ivec2 resTexRC = ivec2(TexCoords.xy *
                               vec2(${t[0]}, ${t[1]}));
         int index = resTexRC.y * ${t[0]} + resTexRC.x;
         ${m}
         return ivec6(r, c, d, d2, d3, d4);
       }
     `,new l.GlslLibRoutine(e)}getCommonUtilFuncs(){const s={};let t="uvFromFlat";s[t]=new l.GlslLibRoutine(`
    vec2 uvFromFlat(int texNumR, int texNumC, int index) {
      int texC = index / texNumR;
      int texR = index - texC * texNumR;
      // TODO: swap texR, texC order in following function so row is corresponding to u and column is corresponding to
      //       v.
      return (vec2(texR, texC) + halfCR) / vec2(texNumR, texNumC);
    }
    `),t="packedUVfrom1D",s[t]=new l.GlslLibRoutine(`
      vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
        int texelIndex = index / 2;
        int texR = texelIndex / texNumC;
        int texC = texelIndex - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),t="packedUVfrom2D",s[t]=new l.GlslLibRoutine(`
      vec2 packedUVfrom2D(int texNumR, int texNumC, int texelsInLogicalRow, int row, int col) {
        int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
        int texR = texelIndex / texNumC;
        int texC = texelIndex - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),t="packedUVfrom3D",s[t]=new l.GlslLibRoutine(`
      vec2 packedUVfrom3D(int texNumR, int texNumC,
          int texelsInBatch, int texelsInLogicalRow, int b,
          int row, int col) {
        int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
        int texR = index / texNumC;
        int texC = index - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),t="sampleTexture";const e=(0,p.getGlsl)(this.context.glContext.version);return s[t]=new l.GlslLibRoutine(`
        float sampleTexture(sampler2D textureSampler, vec2 uv) {
            return ${e.texture2D}(textureSampler, uv).r;
        }`),s}getInputsSamplingSnippets(){const s={},t=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,r)=>{const i=this.context.inputTextureLayouts[r],d=(0,h.generateShaderFuncNameFromInputSamplerName)(e);i.isPacked?s[d]=this.getPackedSamplerFromInput(d,e,i):s[d]=this.getUnpackedSamplerFromInput(d,e,i);const m=(0,h.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(e);i.unpackedShape.length<=t.unpackedShape.length&&(i.isPacked?s[m]=this.getPackedSamplerAtOutputCoords(m,i,t,e):s[m]=this.getUnpackedSamplerAtOutputCoords(m,i,t,e))}),s}getPackedSamplerAtOutputCoords(s,t,e,r){const i=t.unpackedShape,d=e.unpackedShape,m=r,_=(0,h.generateShaderFuncNameFromInputSamplerName)(m),b=i.length,y=d.length,T=a.BroadcastUtil.getBroadcastDims(i,d),w=(0,h.getCoordsDataType)(y),S=y-b;let E;const O=(0,h.getGlChannels)();E=b===0?"":y<2&&T.length>=1?"coords = 0;":T.map(C=>`coords.${O[C+S]} = 0;`).join(`
`);let v="";v=y<2&&b>0?"coords":i.map((C,U)=>`coords.${O[U+S]}`).join(", ");let M="return outputValue;";const $=a.ShapeUtil.size(i)===1,D=a.ShapeUtil.size(d)===1;if(b!==1||$||D){if($&&!D)M=y===1?`
          return vec4(outputValue.x, outputValue.x, 0., 0.);
        `:`
          return vec4(outputValue.x);
        `;else if(T.length){const C=b-2,U=b-1;T.indexOf(C)>-1&&T.indexOf(U)>-1?M="return vec4(outputValue.x);":T.indexOf(C)>-1?M="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":T.indexOf(U)>-1&&(M="return vec4(outputValue.xx, outputValue.zz);")}}else M=`
        return vec4(outputValue.xy, outputValue.xy);
      `;const L=`
      vec4 ${s}() {
        ${w} coords = getOutputCoords();
        
        int lastDim = coords.${O[y-1]};
        coords.${O[y-1]} = coords.${O[y-2]};
        coords.${O[y-2]} = lastDim;
      
        ${E}
        vec4 outputValue = ${_}(${v});
        ${M}
      }
    `;return new l.GlslLibRoutine(L,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(s,t,e,r){const i=[e.width,e.height],d=[t.width,t.height],m=t.unpackedShape.length,_=e.unpackedShape.length,b=t.unpackedShape,y=e.unpackedShape,T=(0,h.generateShaderFuncNameFromInputSamplerName)(r);if(m===_&&a.ArrayUtil.arraysEqual(d,i)){const D=`
          float ${s}() {
            return sampleTexture(${r}, TexCoords);
          }
        `;return new l.GlslLibRoutine(D,["coordinates.sampleTexture"])}const w=(0,h.getCoordsDataType)(_),S=a.BroadcastUtil.getBroadcastDims(b,y),E=_-m;let O;const v=(0,h.getGlChannels)();O=m===0?"":_<2&&S.length>=1?"coords = 0;":S.map(D=>`coords.${v[D+E]} = 0;`).join(`
`);let M="";M=_<2&&m>0?"coords":t.unpackedShape.map((D,L)=>`coords.${v[L+E]}`).join(", ");const $=`
        float ${s}() {
          ${w} coords = getOutputCoords();
          ${O}
          return ${T}(${M});
        }
      `;return new l.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 ${(0,p.getGlsl)(this.context.glContext.version).texture2D}(${t}, halfCR);
          }
        `;return new l.GlslLibRoutine(e)}getPackedSampler1D(s,t,e){const r=[e.width,e.height],i=[r[1],r[0]],d=(0,p.getGlsl)(this.context.glContext.version),m=`vec4 ${s}(int index) {
      vec2 uv = packedUVfrom1D(
      ${i[0]}, ${i[1]}, index);
      return ${d.texture2D}(${t}, uv);
    }`;return new l.GlslLibRoutine(m,["coordinates.packedUVfrom1D"])}getPackedSampler2D(s,t,e){const r=e.unpackedShape,i=[e.width,e.height],d=(0,p.getGlsl)(this.context.glContext.version),m=i[0],_=i[1];if(i!=null&&a.ArrayUtil.arraysEqual(r,i)){const w=`vec4 ${s}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${_}.0, ${m}.0);
        return ${d.texture2D}(${t}, uv);
      }`;return new l.GlslLibRoutine(w)}const b=i,y=Math.ceil(r[1]/2),T=`vec4 ${s}(int row, int col) {
      vec2 uv = packedUVfrom2D(${b[1]}, ${b[0]}, ${y}, row, col);
      return ${d.texture2D}(${t}, uv);
    }`;return new l.GlslLibRoutine(T,["coordinates.packedUVfrom2D"])}getPackedSampler3D(s,t,e){const r=e.unpackedShape,i=[e.width,e.height],d=[i[0],i[1]],m=(0,p.getGlsl)(this.context.glContext.version);if(r[0]===1){const w=r.slice(1),S=[1,2],E=(0,h.squeezeInputShape)(r,w),O=["b","row","col"],v=JSON.parse(JSON.stringify(e));v.unpackedShape=E;const M=this.getPackedSamplerFromInput(s,t,v),$=`${M.routineBody}
      vec4 ${s}(int b, int row, int col) {
        return ${s}(${(0,h.getSqueezedParams)(O,S)});
      } `;return new l.GlslLibRoutine($,M.dependencies)}const _=d[0],b=d[1],y=Math.ceil(r[2]/2),T=`vec4 ${s}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${b}, ${_}, ${y*Math.ceil(r[1]/2)}, ${y}, b, row, col);
      return ${m.texture2D}(${t}, uv);}`;return new l.GlslLibRoutine(T,["coordinates.packedUVfrom3D"])}getPackedSamplerND(s,t,e){const r=e.unpackedShape,i=r.length,d=[e.width,e.height],m=(0,p.getGlsl)(this.context.glContext.version),_=[d[0],d[1]],b=_[1],y=_[0],T=Math.ceil(r[i-1]/2);let w=T*Math.ceil(r[i-2]/2),S="int b, int row, int col",E=`b * ${w} + (row / 2) * ${T} + (col / 2)`;for(let v=2;v<i-1;v++)S=`int b${v}, `+S,w*=r[i-v-1],E=`b${v} * ${w} + `+E;const O=`vec4 ${s}(${S}) {
      int index = ${E};
      int texR = index / ${y};
      int texC = index - texR * ${y};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${y}, ${b});
      return ${m.texture2D}(${t}, uv);
    }`;return new l.GlslLibRoutine(O)}getUnpackedSamplerScalar(s,t,e){const[r,i]=[e.width,e.height];if(r===1&&i===1){const m=`
          float ${s}() {
            return sampleTexture(${t}, halfCR);
          }
        `;return new l.GlslLibRoutine(m,["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 l.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 m=`
        float ${s}(int index) {
          return sampleTexture(${t}, halfCR);
        }
      `;return new l.GlslLibRoutine(m,["coordinates.sampleTexture"])}if(i===1){const m=`
          float ${s}(int index) {
            vec2 uv = vec2((float(index) + 0.5) / ${r}.0, 0.5);
            return sampleTexture(${t}, uv);
          }
        `;return new l.GlslLibRoutine(m,["coordinates.sampleTexture"])}if(r===1){const m=`
          float ${s}(int index) {
            vec2 uv = vec2(0.5, (float(index) + 0.5) / ${i}.0);
            return sampleTexture(${t}, uv);
          }
        `;return new l.GlslLibRoutine(m,["coordinates.sampleTexture"])}const d=`
        float ${s}(int index) {
          vec2 uv = uvFromFlat(${r}, ${i}, index);
          return sampleTexture(${t}, uv);
        }
      `;return new l.GlslLibRoutine(d,["coordinates.uvFromFlat","coordinates.sampleTexture"])}getUnpackedSampler2D(s,t,e){const r=e.unpackedShape,i=[e.height,e.width];if(i!=null&&a.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 l.GlslLibRoutine(w,["coordinates.sampleTexture"])}const{newShape:d,keptDims:m}=(0,u.squeezeShape)(r),_=d;if(_.length<r.length){const w=(0,h.squeezeInputShape)(r,_),S=JSON.parse(JSON.stringify(e));S.unpackedShape=w;const E=["col","row"],O=`
          ${this.getUnpackedSamplerFromInput(s,t,S).routineBody}
          float ${s}(int row, int col) {
            return ${s}(${(0,h.getSqueezedParams)(E,m)});
          }
        `;return new l.GlslLibRoutine(O,["coordinates.sampleTexture"])}const b=i[1],y=i[0];if(y===1){const w=`
          float ${s}(int row, int col) {
            int offset_${t} = coordsToOffset(TexCoords, ${b}, ${y});
            float index = dot(vec3(row, col, offset_${t}), vec3(${r[1]}, 1, 1));
            vec2 uv = vec2(0.5, (index + 0.5) / ${b}.0);
            return sampleTexture(${t}, uv);
          }
        `;return new l.GlslLibRoutine(w,["coordinates.sampleTexture","coordinates.coordsToOffset"])}if(b===1){const w=`
          float ${s}(int row, int col) {
            int offset_${t} = coordsToOffset(TexCoords, ${b}, ${y});
            float index = dot(vec3(row, col, offset_${t}), vec3(${r[1]}, 1, 1));
            vec2 uv = vec2((index + 0.5) / ${y}.0, 0.5);
            return sampleTexture(${t}, uv);
          }
        `;return new l.GlslLibRoutine(w,["coordinates.sampleTexture","coordinates.coordsToOffset"])}const T=`
        float ${s}(int row, int col) {
          int index = col * ${r[1]} + row;
          vec2 uv = uvFromFlat(${b}, ${y}, index);
          return sampleTexture(${t}, uv);
        }
      `;return new l.GlslLibRoutine(T,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler3D(s,t,e){const r=e.unpackedShape,i=r[1]*r[2],d=r[2],{newShape:m,keptDims:_}=(0,u.squeezeShape)(r),b=m;if(b.length<r.length){const T=(0,h.squeezeInputShape)(r,b),w=["batch","col","row"],S=JSON.parse(JSON.stringify(e));S.unpackedShape=T;const E=this.getUnpackedSamplerFromInput(s,t,S),O=_.reverse(),v=`
          ${E.routineBody}
          float ${s}(int batch, int row, int col) {
            return ${s}(${(0,h.getSqueezedParams)(w,O)});
          }
        `;return new l.GlslLibRoutine(v,E.dependencies)}const y=`
          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}, ${e.height}, index);
            return sampleTexture(${t}, uv);
          }
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          }
        `;return new l.GlslLibRoutine(O,["coordinates.sampleTexture","coordinates.uvFromFlat"])}const T=`
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          return sampleTexture(${t}, uv);
        }
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            vec2 uv = uvFromFlat(${e.width}, ${e.height}, index);
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        int offset = coordsToOffset(texCoords, ${r}, ${i});
        ${d.join("")}
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        ${d.join("")}
      }
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          vec2 coords = offsetToCoords(offset, ${e}, ${r});
          float value = getColorAsFloat(${(0,p.getGlsl)(this.context.glContext.version).texture2D}(${s}, coords));
          return value;
        }
        `}getPackedValueFrom(s,t,e,r,i){let d=`_${s}_Pack`;return i&&(d+="_T"),`
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          int offset = indicesToOffset_${s}(m);
          vec2 coords = offsetToCoords(offset, ${e}, ${r});
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        highp float Sign = step(0.0,-f);
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        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)));
        ${u}
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        return rgba;
    }
        `)}}decodeUint8(){const u=l.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{decode:new a.GlslLibRoutine(`
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          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 u=new ArrayBuffer(4),h=new Uint32Array(u),g=new Uint8Array(u);if(h[0]=3735928559,g[0]===239)return!0;if(g[0]===222)return!1;throw new Error("unknown endianness")}}n.EncodingGlslLib=l},9894:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.FragColorGlslLib=void 0;const a=o(8520),l=o(5060);class p extends a.GlslLib{constructor(h){super(h)}getFunctions(){return Object.assign(Object.assign({},this.setFragColor()),this.getColorAsFloat())}getCustomTypes(){return{}}setFragColor(){const h=(0,l.getGlsl)(this.context.glContext.version);return{setFragColor:new a.GlslLibRoutine(`
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    ${this.getUniforms(h.inputNames,h.variables)}
    ${this.getImports(g)}
    ${g}`}getImports(h){const g=this.selectGlslLibRoutinesToBeIncluded(h);if(g.length===0)return"";let c="";for(let s=0;s<g.length;++s){if(!g[s].routineBody)throw new Error(`Missing body for the Glsl Library routine: ${g[s].name}`);c+=g[s].routineBody+`
`}return c}selectGlslLibRoutinesToBeIncluded(h){const g=[];return Object.keys(this.glslLibRoutineDependencyGraph).forEach(c=>{const s=c.split(".")[1];h.indexOf(s)!==-1&&g.push(this.glslLibRoutineDependencyGraph[c])}),a.TopologicalSortGlslRoutines.returnOrderedNodes(g)}getUniforms(h,g){const c=[];if(h)for(const s of h)c.push(`uniform sampler2D ${s};`);if(g)for(const s of g)c.push(`uniform ${s.type} ${s.name}${s.arrayLength?`[${s.arrayLength}]`:""};`);return c.join(`
`)}}},5483:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.glslRegistry=void 0;const a=o(5107),l=o(7341),p=o(9894),u=o(2655),h=o(3891);n.glslRegistry={encoding:l.EncodingGlslLib,fragcolor:p.FragColorGlslLib,vec:h.VecGlslLib,shapeUtils:u.ShapeUtilsGlslLib,coordinates:a.CoordsGlslLib}},2655:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.ShapeUtilsGlslLib=void 0;const a=o(8520);class l extends a.GlslLib{constructor(u){super(u)}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.bcastIndex()),this.bcastMatmulIndex()),this.offsetToIndices()),this.indicesToOffset()),this.incrementIndices())}getCustomTypes(){return{}}bcastIndex(){const u=this.context.outputTextureLayout.shape.length,h={};return this.context.programInfo.inputNames.forEach((g,c)=>{const s=this.context.inputTextureLayouts[c].unpackedShape;if(s.length<=u){const t=s.length,e=u-t,r=`bcastIndices_${g}`;let i="";for(let m=0;m<t;++m)i+=`
          realIndices[${m}] = int( mod(float(bcastedIndices[${e+m}]), ${s[m]}.0) );
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        void ${r} (int bcastedIndices[${u}], out int realIndices[${t}]) {
          ${i}
        }
        `;h[r]=new a.GlslLibRoutine(d)}}),h}bcastMatmulIndex(){const u=this.context.outputTextureLayout.shape.length,h={};return this.context.programInfo.inputNames.forEach((g,c)=>{const s=this.context.inputTextureLayouts[c].shape;if(!(s.length<2||s.length>u)){const t=s.length,e=u-t,r=`bcastMatmulIndices_${g}`;let i="";for(let m=0;m<t-2;++m)i+=`
          realIndices[${m}] = int( mod(float(bcastedIndices[${e+m}]), ${s[m]}.0) );
          `;const d=`
        void ${r}(int bcastedIndices[${u}], out int realIndices[${t}]) {
          ${i}
          realIndices[${t-1}] = bcastedIndices[${u-1}];
          realIndices[${t-2}] = bcastedIndices[${u-2}];
        }
        `;h[r]=new a.GlslLibRoutine(d)}}),h}indicesToOffset(){const u={};return this.context.programInfo.inputNames.forEach((h,g)=>{const c=this.context.inputTextureLayouts[g].shape,s=this.context.inputTextureLayouts[g].strides,t=c.length;let e=`indicesToOffset_${h}`;u[e]=new a.GlslLibRoutine(l.indexToOffsetSingle(e,t,s)),e=`indicesToOffset_${h}_T`,u[e]=new a.GlslLibRoutine(l.indexToOffsetSingle(e,t,s.slice().reverse()))}),u}static indexToOffsetSingle(u,h,g){let c="";for(let s=h-1;s>=0;--s)c+=`
        offset += indices[${s}] * ${g[s]};
        `;return`
      int ${u}(int indices[${h}]) {
        int offset = 0;
        ${c}
        return offset;
      }
      `}offsetToIndices(){const u={};return this.context.programInfo.inputNames.forEach((h,g)=>{const c=this.context.inputTextureLayouts[g].shape,s=this.context.inputTextureLayouts[g].strides,t=c.length;let e=`offsetToIndices_${h}`;u[e]=new a.GlslLibRoutine(l.offsetToIndicesSingle(e,t,s)),e=`offsetToIndices_${h}_T`,u[e]=new a.GlslLibRoutine(l.offsetToIndicesSingle(e,t,s.slice().reverse()))}),u}static offsetToIndicesSingle(u,h,g){const c=[];for(let s=0;s<h-1;++s)c.push(`
      indices[${s}] = offset / ${g[s]};`),c.push(`
        offset -= indices[${s}] * ${g[s]};`);return c.push(`
      indices[${h-1}] = offset;`),`
      void ${u}(int offset, out int indices[${h}]) {
        ${c.join("")}
      }
      `}incrementIndices(){const u={};return this.context.programInfo.inputNames.forEach((h,g)=>{const c=this.context.inputTextureLayouts[g].shape,s=c.length,t=`incrementIndices_${h}`;let e="";for(let i=0;i<s;++i)e+=`
        shape[${i}] = ${c[i]};`;const r=`
        void ${t}(int axis, out int indices[${s}]) {
          int shape[${s}];
          ${e};
          for(int i = ${s} -1 ; i >= 0; --i) {
            if(i > axis) continue;
            indices[i] += 1;
            if(indices[i] < shape[i]) {
              break;
            }
            indices[i] = 0;
          }
        }
        `;u[t]=new a.GlslLibRoutine(r)}),u}}n.ShapeUtilsGlslLib=l},5060:(f,n)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.getDefaultFragShaderMain=n.getFragShaderPreamble=n.getVertexShaderSource=n.getGlsl=void 0;const o={version:"",attribute:"attribute",varyingVertex:"varying",varyingFrag:"varying",texture2D:"texture2D",output:"gl_FragColor",outputDeclaration:""},a={version:"#version 300 es",attribute:"in",varyingVertex:"out",varyingFrag:"in",texture2D:"texture",output:"outputColor",outputDeclaration:"out vec4 outputColor;"};function l(p){return p===1?o:a}n.getGlsl=l,n.getVertexShaderSource=function(p){const u=l(p);return`${u.version}
      precision highp float;
      ${u.attribute} vec3 position;
      ${u.attribute} vec2 textureCoord;

      ${u.varyingVertex} vec2 TexCoords;

      void main()
      {
          gl_Position = vec4(position, 1.0);
          TexCoords = textureCoord;
      }`},n.getFragShaderPreamble=function(p){const u=l(p);return`${u.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${u.varyingFrag} vec2 TexCoords;
    ${u.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(p,u){return`
  void main() {
    int indices[${u}];
    toVec(TexCoords, indices);
    vec4 result = vec4(process(indices));
    ${l(p).output} = result;
  }
  `}},3891:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.VecGlslLib=void 0;const a=o(8520);class l extends a.GlslLib{constructor(u){super(u)}getCustomTypes(){return{}}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign({},this.binaryVecFunctions()),this.copyVec()),this.setVecItem()),this.getVecItem())}binaryVecFunctions(){const u=this.context.outputTextureLayout.shape.length,h={add:"+=",sub:"-=",mul:"*=",div:"/="},g={};for(const c in h){const s=`${c}Vec`;let t="";for(let r=0;r<u;++r)t+=`
          dest[${r}] ${h[c]} src[${r}];
          `;const e=`
        void ${s}(int src[${u}], out int dest[${u}]) {
          ${t}
        }
        `;g[s]=new a.GlslLibRoutine(e)}return g}copyVec(){const u=this.context.outputTextureLayout.shape.length;let h="";for(let c=0;c<u;++c)h+=`
        dest[${c}] = src[${c}];
        `;const g=`
      void copyVec(int src[${u}], out int dest[${u}]) {
        ${h}
      }
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        if(index < 0)
            index =${u} + index;
        if (index == 0)
            m[0] = value;
        `;for(let c=1;c<u-1;++c)h+=`
        else if (index == ${c})
            m[${c}] = value;
            `;h+=`
        else
            m[${u-1}] = value;
        `;const g=`
      void setVecItem(out int m[${u}], int index, int value) {
        ${h}
      }
        `;return{setVecItem:new a.GlslLibRoutine(g)}}getVecItem(){const u=this.context.outputTextureLayout.shape.length;let h=`
        if(index < 0)
            index = ${u} + index;
        if (index == 0)
            return m[0];
      `;for(let c=1;c<u-1;++c)h+=`
        else if (index == ${c})
            return m[${c}];
      `;h+=`
        else
            return m[${u-1}];
        `;const g=`
      int getVecItem(int m[${u}], int index) {
        ${h}
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      ${L.output} = result;
    }
    `;return{name:E.name,inputNames:["A","B"],inputTypes:[v,v],output:{dims:S[0].dims,type:O,textureType:v},shaderSource:C,hasMain:!0}};n.add=(w,S)=>[w.run(y(w,S,h()),S)],n.and=(w,S)=>[w.run(y(w,S,i(),"bool"),S)],n.div=(w,S)=>[w.run(y(w,S,g()),S)],n.equal=(w,S)=>[w.run(y(w,S,t(),"bool"),S)],n.greater=(w,S)=>[w.run(y(w,S,e(),"bool"),S)],n.less=(w,S)=>[w.run(y(w,S,r(),"bool"),S)],n.mul=(w,S)=>[w.run(y(w,S,c()),S)],n.or=(w,S)=>[w.run(y(w,S,d(),"bool"),S)],n.pow=(w,S)=>[w.run(y(w,S,_()),S)],n.pRelu=(w,S)=>[w.run(y(w,S,b()),S)],n.sub=(w,S)=>[w.run(y(w,S,s()),S)],n.xor=(w,S)=>[w.run(y(w,S,m(),"bool"),S)]},4196:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseCastAttributes=n.cast=void 0;const a=o(2517);n.cast=(p,u,h)=>(l(u),[p.cast(u[0],h)]),n.parseCastAttributes=p=>a.ProtoUtil.tensorDataTypeFromProto(p.attributes.getInt("to"));const l=p=>{if(!p||p.length!==1)throw new Error("Cast requires 1 input.");if(p[0].type==="string")throw new Error("Invalid input type.")}},1163:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createPackedConcatProgramInfoLoader=void 0;const a=o(5060),l=o(2039),p=o(9390),u=o(2827);n.createPackedConcatProgramInfoLoader=(g,c,s)=>{const t=(e=c.length,r=s.cacheKey,{name:"Concat (packed)",inputNames:Array.from({length:e},(i,d)=>`X${d}`),inputTypes:Array(e).fill(l.TextureType.packed),cacheHint:r});var e,r;return Object.assign(Object.assign({},t),{get:()=>((i,d,m,_)=>{const b=m[0].dims.slice();if(_>=b.length||_<-1*b.length)throw new Error("axis specified for concat doesn't match input dimensionality");_<0&&(_=b.length+_);const y=b.slice(0);for(let Y=1;Y<m.length;Y++){const ee=m[Y].dims.slice();for(let te=0;te<b.length;te++)if(te===_)y[_]+=ee[te];else if(b[te]!==ee[te])throw new Error("non concat dimensions must match")}const T=y.length,w=(0,u.getChannels)("coords",T),S=(0,p.getCoordsDataType)(T),E=(0,u.unpackFromChannel)(),O=m.map(Y=>Y.dims),v=(0,p.getGlChannels)(T),M=new Array(O.length-1);M[0]=O[0][_];for(let Y=1;Y<M.length;Y++)M[Y]=M[Y-1]+O[Y][_];const $=v[_],D=v.slice(-2),L=v.join();let C=`if (${$} < ${M[0]}) {
        return getChannel(
            getX0(${L}), vec2(${D.join()}));
        }`;for(let Y=1;Y<M.length;Y++){const ee=M[Y-1];C+=`
            if (${$} < ${M[Y]}  && ${$} >= ${M[Y-1]}) {
              return getChannel(
                getX${Y}(${h(v,$,ee)}),
                vec2(${h(D,$,ee)}));
            }`}const U=M.length,N=M[M.length-1];C+=`
            return getChannel(
              getX${U}(${h(v,$,N)}),
              vec2(${h(D,$,N)}));`;const j=(0,a.getGlsl)(i.session.backend.glContext.version),J=`
          ${E}
          float getValue(${v.map(Y=>"int "+Y)}) {
            ${C}
          }

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

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

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

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

            ${w[T-1]} = ${w[T-1]} - 1;
            if (${w[T-2]} < ${y[T-2]} &&
                ${w[T-1]} < ${y[T-1]}) {
              result.b = getValue(${w});
            }
            ${j.output} = result;
          }
        `;return Object.assign(Object.assign({},d),{output:{dims:y,type:m[0].type,textureType:l.TextureType.packed},shaderSource:J,hasMain:!0})})(g,t,c,s.axis)})};const h=(g,c,s)=>{const t=g.indexOf(c);return g.map((e,r)=>r===t?`${e} - ${s}`:e).join()}},2069:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConcatAttributes=n.concat=void 0;const a=o(246),l=o(2039),p=o(1163);n.concat=(e,r,i)=>(t(r),e.session.pack&&r[0].dims.length>1?[e.run((0,p.createPackedConcatProgramInfoLoader)(e,r,i),r)]:[e.run(u(e,r,i),r)]);const u=(e,r,i)=>{const d=(m=r.length,_=i.cacheKey,{name:"Concat",inputNames:Array.from({length:m},(b,y)=>`X${y}`),inputTypes:Array(m).fill(l.TextureType.unpacked),cacheHint:_});var m,_;return Object.assign(Object.assign({},d),{get:()=>((b,y,T,w)=>{const S=T[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 E=S.slice(0);for(let L=1;L<T.length;L++){const C=T[L].dims.slice();for(let U=0;U<S.length;U++)if(U===w)E[w]+=C[U];else if(S[U]!==C[U])throw new Error("non concat dimensions must match")}const O=E.length,v=new Array(T.length);let M=0;for(let L=0;L<v.length;++L)M+=T[L].dims[w],v[L]=M;let $="";$=T.length<5?h(v):g(v);const D=`
        ${c(T.length,O)}
        ${s(v)}
        ${$}
        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({},y),{output:{dims:E,type:T[0].type,textureType:l.TextureType.unpacked},shaderSource:D})})(0,d,r,i.axis)})},h=e=>`int getTextureWhereDataResides(int index) {
      ${e.map((r,i)=>`if(index<${r}) {return ${i};}
`).join("")}
    }`,g=e=>h(e),c=(e,r)=>{const i=[`float fetchDataFromCorrectTexture(int textureIndex, int indices[${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 ${e[i]}; }`);return r.push("	}"),r.join(`
`)};n.parseConcatAttributes=e=>(0,a.createAttributeWithCacheKey)({axis:e.attributes.getInt("axis")});const t=e=>{if(!e||e.length<1)throw new Error("too few inputs");const r=e[0].type,i=e[0].dims.length;if(r==="string")throw new Error("string tensor is not supported yet");for(const d of e){if(d.type!==r)throw new Error("input tensors should be one type");if(d.dims.length!==i)throw new Error("input tensors should have the same shape")}}},4770:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createUnpackedGroupedConvProgramInfoLoader=void 0;const a=o(6231),l=o(5060),p=o(2039),u=o(8138),h=o(2823);n.createUnpackedGroupedConvProgramInfoLoader=(g,c,s)=>{const t=(e=c.length>2,r=s.cacheKey,{name:"GroupedConv",inputNames:e?["X","W","Bias"]:["X","W"],inputTypes:e?[p.TextureType.unpacked,p.TextureType.unpacked,p.TextureType.unpacked]:[p.TextureType.unpacked,p.TextureType.unpacked],cacheHint:r});var e,r;return Object.assign(Object.assign({},t),{get:()=>((i,d,m,_)=>{const b=d.length>2?"value += getBias(output_channel);":"",y=d[0].dims.slice(),T=d[1].dims.slice(),w=T[0]/_.group;a.Logger.verbose("GroupedConv",`autpPad:${_.autoPad}, dilations:${_.dilations}, group:${_.group}, kernelShape:${_.kernelShape}, pads:${_.pads}, strides:${_.strides}`);const S=(0,u.calculateOutputShape)(y,T,_.dilations,_.pads,_.strides),E=(0,l.getGlsl)(i.session.backend.glContext.version),{activationFunction:O,applyActivation:v}=(0,h.getActivationSnippet)(_),M=`
  const ivec2 strides = ivec2(${_.strides[0]}, ${_.strides[1]});
  const ivec2 pads = ivec2(${_.pads[0]}, ${_.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 < ${T[1]}; wInChannel++) {
      int input_channel = group_id * ${T[1]} + wInChannel;
      for (int wHeight = 0; wHeight < ${T[2]}; wHeight++) {
        int xHeight = xRCCorner.x + wHeight * ${_.dilations[0]};

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

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

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

    ivec2 loc = coords.zw + pads;

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

    float value = ${M};
    for (int inChannelOffset = 0; inChannelOffset < ${C}; inChannelOffset++) {
      int input_channel = group_id * ${C} + inChannelOffset;
      for (int wWOff = 0; wWOff < ${D[2]}; wWOff++) {
        for (int wHOff = 0; wHOff < ${D[3]}; wHOff++) {
          ivec2 wOff = ivec2(wWOff * ${v.dilations[0]}, wHOff * ${v.dilations[1]});
          ivec2 wLoc = loc - wOff;
          ivec2 wLocIn = wLoc / strides;
          if (
            wLocIn * strides == wLoc &&
            wLocIn.x >= 0 && wLocIn.x < ${$[2]} &&
            wLocIn.y >= 0 && wLocIn.y < ${$[3]}
          ) {
            float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x);
            float wVal = getW(input_channel, wOutChannel, wHOff, wWOff);
            value += xVal * wVal;
          }
        }
      }
    }
    ${J}
    ${N.output} = vec4(value, .0, .0, .0);
  }
`;return Object.assign(Object.assign({},O),{output:{dims:U,type:E[0].type,textureType:p.TextureType.unpacked},shaderSource:Y,hasMain:!0})})(m,_,y,b)})})(r,i,d),i),t=(r,i)=>{const d=r.kernelShape.slice();if(r.kernelShape.length===0)for(let y=2;y<i[1].dims.length;++y)d.push(i[1].dims[y]);const m=r.pads.slice(),_=r.outputShape.slice();((y,T,w,S,E,O,v,M)=>{const $=y.length-2,D=M.length===0;for(let L=0;L<$;++L){const C=D?y[L+2]*O[L]:M[L],U=h(y[L+2],O[L],E[L],T[L],w[L],C);g(U,S,E,L,L+$),D&&M.push(O[L]*(y[L+2]-1)+v[L]+(T[L]-1)*w[L]+1-E[L]-E[L+$])}})(i[0].dims,d,r.dilations,r.autoPad,m,r.strides,r.outputPadding,_);const b=Object.assign({},r);return Object.assign(b,{kernelShape:d,pads:m,outputShape:_,cacheKey:r.cacheKey}),b};n.parseConvTransposeAttributes=r=>{const i=r.attributes,d=(0,u.parseInternalActivationAttributes)(i),m=i.getString("auto_pad","NOTSET"),_=i.getInts("dilations",[1,1]),b=i.getInt("group",1),y=i.getInts("kernel_shape",[]),T=i.getInts("output_padding",[0,0]),w=i.getInts("output_shape",[]),S=i.getInts("pads",[0,0,0,0]),E=i.getInts("strides",[1,1]);return(0,a.createAttributeWithCacheKey)(Object.assign({autoPad:m,dilations:_,group:b,kernelShape:y,outputPadding:T,outputShape:w,pads:S,strides:E},d))};const e=(r,i)=>{if(!r||r.length!==2&&r.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(r[0].dims.length!==4||r[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(r[0].dims[1]!==r[1].dims[0])throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");const d=r[1].dims[1]*i.group;if(r.length===3&&(r[2].dims.length!==1||r[2].dims[0]!==d))throw new Error("invalid bias");const m=r[0].dims.length-2;if(i.dilations.length!==m)throw new Error(`dilations should be ${m}D`);if(i.strides.length!==m)throw new Error(`strides should be ${m}D`);if(i.pads.length!==2*m)throw new Error(`pads should be ${2*m}D`);if(i.outputPadding.length!==m)throw new Error(`output_padding should be ${m}D`);if(i.kernelShape.length!==0&&i.kernelShape.length!==r[1].dims.length-2)throw new Error("invalid kernel shape");if(i.outputShape.length!==0&&i.outputShape.length!==r[0].dims.length-2)throw new Error("invalid output shape");if(r[0].type!=="float32"||r[1].type!=="float32")throw new Error("ConvTranspose input(X,W) should be float tensor");if(r.length===3&&r[2].type!=="float32")throw new Error("ConvTranspose input(bias) should be float tensor")}},8138:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseConvAttributes=n.conv=n.calculateOutputShape=void 0;const a=o(246),l=o(2517),p=o(4770),u=o(1386),h=o(9828),g=o(2823),c=o(3248),s=o(5623);n.calculateOutputShape=(m,_,b,y,T)=>{const w=m[0],S=m.slice(2),E=S.length,O=_[0],v=_.slice(2).map(($,D)=>$+($-1)*(b[D]-1)),M=S.map(($,D)=>$+y[D]+y[D+E]).map(($,D)=>Math.floor(($-v[D]+T[D])/T[D]));return[w,O].concat(...M)},n.conv=(m,_,b)=>(d(_,b),t(m,_,b));const t=(m,_,b)=>{const y=i(b,_),T=m.session.pack,w=y.kernelShape[0]===1&&y.kernelShape[1]===1;return y.group>1?[m.run((0,p.createUnpackedGroupedConvProgramInfoLoader)(m,_,y),_)]:w&&T?[e(m,_,y)]:T&&_[0].dims.length===4&&_[0].dims[0]===1&&!w?[(0,u.conv2DPacked)(m,_,y)]:[r(m,_,y)]},e=(m,_,b)=>{const y=_[0].dims,T=_[1].dims,w=(0,n.calculateOutputShape)(y,T,b.dilations,b.pads,b.strides),S=m.reshapeUnpacked(_[0],[y[1],y[2]*y[3]]),E=m.reshapeUnpacked(_[1],[T[0],T[1]]),O=_.length>2?[E,S,_[2]]:[E,S],v=m.run((0,s.createMatmulProgramInfoLoader)(O,b),O);return m.reshapeUnpacked(v,w)},r=(m,_,b)=>{const y=_[0].dims,T=_[1].dims,w=(0,n.calculateOutputShape)(y,T,b.dilations,b.pads,b.strides),S=m.run((0,c.createIm2ColProgramInfoLoader)(m,_[0],_[1],w,b),[_[0]]),E=_.length===3?[S,_[1],_[2]]:[S,_[1]];return m.run((0,h.createDotProductProgramInfoLoader)(m,_,w,b),E)},i=(m,_)=>{const b=m.kernelShape.slice();if(m.kernelShape.length===0)for(let w=2;w<_[1].dims.length;++w)b.push(_[1].dims[w]);const y=m.pads.slice();l.PoolConvUtil.adjustPadsBasedOnAutoPad(_[0].dims,m.strides,m.dilations,b,y,m.autoPad);const T=Object.assign({},m);return Object.assign(T,{kernelShape:b,pads:y,cacheKey:m.cacheKey}),T};n.parseConvAttributes=m=>{const _=m.attributes,b=(0,g.parseInternalActivationAttributes)(_),y=_.getString("auto_pad","NOTSET"),T=_.getInts("dilations",[1,1]),w=_.getInt("group",1),S=_.getInts("kernel_shape",[]),E=_.getInts("pads",[0,0,0,0]),O=_.getInts("strides",[1,1]);return(0,a.createAttributeWithCacheKey)(Object.assign({autoPad:y,dilations:T,group:w,kernelShape:S,pads:E,strides:O},b))};const d=(m,_)=>{if(!m||m.length!==2&&m.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(m[0].dims.length!==4||m[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(m[0].dims[1]!==m[1].dims[1]*_.group)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(m.length===3&&(m[2].dims.length!==1||m[1].dims[0]!==m[2].dims[0]))throw new Error("invalid bias");const b=m[0].dims.length-2;if(_.dilations.length!==b)throw new Error(`dilations should be ${b}D`);if(_.strides.length!==b)throw new Error(`strides should be ${b}D`);if(_.pads.length!==2*b)throw new Error(`pads should be ${2*b}D`);if(_.kernelShape.length!==0&&_.kernelShape.length!==m[1].dims.length-2)throw new Error("invalid kernel shape");if(m[0].type!=="float32"||m[1].type!=="float32")throw new Error("Conv input(X,W) should be float tensor");if(m.length===3&&m[2].type!=="float32")throw new Error("Conv input(bias) should be float tensor")}},5193:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseDepthToSpaceAttributes=n.depthToSpace=void 0;const a=o(3738);n.depthToSpace=(p,u,h)=>{l(u);const g=h.blocksize,c=g*g,s=h.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],t=h.mode==="DCR"?[u[0].dims[0],g,g,u[0].dims[1]/c,u[0].dims[2],u[0].dims[3]]:[u[0].dims[0],u[0].dims[1]/c,g,g,u[0].dims[2],u[0].dims[3]],e=p.reshapeUnpacked(u[0],t),r={perm:s,cacheKey:`${s}`},[i]=(0,a.transpose)(p,[e],r),d=[u[0].dims[0],u[0].dims[1]/c,u[0].dims[2]*g,u[0].dims[3]*g];return[p.reshapeUnpacked(i,d)]},n.parseDepthToSpaceAttributes=p=>{const u=p.attributes.getInt("blocksize");if(u<1)throw new Error(`blocksize must be >= 1, but got : ${u} for DepthToSpace`);const h=p.attributes.getString("mode","DCR");if(h!=="DCR"&&h!=="CRD")throw new Error(`unrecognized mode: ${h} for DepthToSpace`);return{mode:h,blocksize:u}};const l=p=>{if(p.length!==1)throw new Error(`DepthToSpace expect 1 inputs, but got ${p.length}`);if(p[0].type==="string"||p[0].dims.length!==4)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}},9828:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createDotProductProgramInfoLoader=void 0;const a=o(2517),l=o(5060),p=o(2039),u=o(2823),h=o(3248);n.createDotProductProgramInfoLoader=(g,c,s,t)=>{const e=((r,i)=>({name:"ConvDotProduct",inputNames:r?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:r?[p.TextureType.unpacked,p.TextureType.packedLastDimension,p.TextureType.unpacked]:[p.TextureType.unpacked,p.TextureType.packedLastDimension],cacheKey:i.activationCacheKey}))(c.length>2,t);return Object.assign(Object.assign({},e),{get:()=>((r,i,d,m,_)=>{const b=d[0].dims,y=d[1].dims,T=[y[0],Math.ceil(b[1]*y[2]*y[3]/4)],w=(0,h.calculateIm2ColDims)(b,y,m),[S,E]=r.calculateTextureWidthAndHeight(T,p.TextureType.packedLastDimension),O=a.ShapeUtil.computeStrides(w),[v,M]=r.calculateTextureWidthAndHeight(w,p.TextureType.packedLastDimension),$=m.length,D=d.length<3?"0.0":"_B(b)",L=Math.ceil(b[1]*y[2]*y[3]/4),{activationFunction:C,applyActivation:U}=(0,u.getActivationSnippet)(_),N=(0,l.getGlsl)(r.session.backend.glContext.version),j=`
${C}
float process(int indices[${$}]) {
  int b[1];
  b[0] = indices[1];
  int im2col[4];
  im2col[0] = indices[0];
  im2col[1] = indices[2];
  im2col[2] = indices[3];
  int im2colOffset = im2col[0] * ${O[0]} + im2col[1] * ${O[1]} + im2col[2] * ${O[2]};
  int kernelOffset = indices[1] * ${T[1]};
  float value = ${D};
  for (int i = 0; i < ${L}; ++i) {
    vec2 im2colCoords = offsetToCoords(im2colOffset, ${v}, ${M});
    vec2 kernelCoords = offsetToCoords(kernelOffset, ${S}, ${E});
    value += dot(${N.texture2D}(Im2Col, im2colCoords), ${N.texture2D}(K, kernelCoords));
    ++im2colOffset;
    ++kernelOffset;
  }
  ${U}
  return value;
}`;return Object.assign(Object.assign({},i),{output:{dims:m,type:d[0].type,textureType:p.TextureType.unpacked},shaderSource:j})})(g,e,c,s,t)})}},7992:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseFlattenAttributes=n.flatten=void 0;const a=o(2517);n.flatten=(p,u,h)=>{l(u,h);const g=a.ShapeUtil.flattenShape(u[0].dims,h);return[p.reshapeUnpacked(u[0],g)]},n.parseFlattenAttributes=p=>p.attributes.getInt("axis",1);const l=(p,u)=>{if(!p||p.length!==1)throw new Error("Flatten requires 1 input.");const h=p[0].dims.length;if(h===0)throw new Error("scalar tensor is not supported.");if(u<-h||u>h)throw new Error("Invalid axis");if(p[0].type==="string")throw new Error("string tensor is not supported.")}},2823:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseInternalActivationAttributes=n.getActivationSnippet=void 0;const a=o(2517),l=o(4909);n.getActivationSnippet=function(p){let u;switch(p.activation){case"Relu":u=(0,l.glslRelu)();break;case"Sigmoid":u=(0,l.glslSigmoid)();break;case"Clip":u=(0,l.glslClip)(p.clipMin,p.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const h=u.name;return{activationFunction:u.body,applyActivation:`value = ${h}_(value);`}},n.parseInternalActivationAttributes=p=>{const u=p.getString("activation","");if(u==="Clip"){const[h,g]=p.getFloats("activation_params",[a.MIN_CLIP,a.MAX_CLIP]);return{activation:u,clipMax:g,clipMin:h,activationCacheKey:`${u}:${h},${g}`}}return{activation:u,activationCacheKey:u}}},1253:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGatherAttributes=n.gather=void 0;const a=o(246),l=o(782),p=o(2517),u=o(2039);n.gather=(s,t,e)=>(c(t,e.axis),[s.run(g(s,t,e),t)]),n.parseGatherAttributes=s=>(0,a.createAttributeWithCacheKey)({axis:s.attributes.getInt("axis",0)});const h={name:"Gather",inputNames:["A","B"],inputTypes:[u.TextureType.unpacked,u.TextureType.unpacked]},g=(s,t,e)=>{const r=Object.assign(Object.assign({},h),{cacheHint:e.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((i,d,m,_)=>{const b=m[0].dims.slice(),y=m[1].dims.slice(),T=new Array(b.length+y.length-1);_=p.ShapeUtil.normalizeAxis(_,b.length);const w=[];for(let E=0;E<T.length;E++)E<_?(T[E]=b[E],w.push(`inputIdx[${E}] = outputIdx[${E}];`)):E<_+y.length?(T[E]=y[E-_],w.push(`indexDataIdx[${E-_}] = outputIdx[${E}];`)):(T[E]=b[E-y.length+1],w.push(`inputIdx[${E-y.length+1}] = outputIdx[${E}];`));const S=`
      float process(int outputIdx[${T.length||1}]) {
        int inputIdx[${b.length}];
        int indexDataIdx[${y.length||1}];
        indexDataIdx[0] = 0;
        ${w.join(`
        `)}
        int idx = int(_B(indexDataIdx));
        inputIdx[${_}] = idx < 0 ? idx + ${b[_]} : idx;
        return _A(inputIdx);
      }`;return Object.assign(Object.assign({},d),{output:{dims:T,type:m[0].type,textureType:u.TextureType.unpacked},shaderSource:S})})(0,r,t,e.axis)})},c=(s,t)=>{if(!s||s.length!==2)throw new Error("Gather requires 2 inputs.");const e=s[0].dims.length;if(e<1)throw new Error("Invalid input shape.");if(t<-e||t>e-1)throw new Error("Invalid axis.");if(l.NUMBER_TYPES.indexOf(s[0].type)===-1)throw new Error("Invaid input type.");if(s[1].type!=="int32"&&s[1].type!=="int16")throw new Error("Invaid input type.")}},4776:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseGemmAttributesV11=n.parseGemmAttributesV7=n.gemm=void 0;const a=o(246),l=o(2517),p=o(2039);n.gemm=(s,t,e)=>(c(t,e),[s.run(h(t,e),t)]);const u=(s,t)=>{const e=s.attributes.getInt("transA",0)!==0,r=s.attributes.getInt("transB",0)!==0,i=s.attributes.getFloat("alpha",1),d=s.attributes.getFloat("beta",1);return(0,a.createAttributeWithCacheKey)({transA:e,transB:r,alpha:i,beta:d,isOptionalC:t})};n.parseGemmAttributesV7=s=>u(s,!1),n.parseGemmAttributesV11=s=>u(s,!0);const h=(s,t)=>{const e={name:"Gemm",inputNames:s.length===3?["A","B","C"]:["A","B"],inputTypes:s.length===3?[p.TextureType.unpacked,p.TextureType.unpacked,p.TextureType.unpacked]:[p.TextureType.unpacked,p.TextureType.unpacked],key:t.cacheKey};return Object.assign(Object.assign({},e),{get:()=>g(e,s,t)})},g=(s,t,e)=>{const r=t[0].dims.slice(),i=t[1].dims.slice(),[d,m]=l.GemmUtil.getShapeOfGemmResult(r,e.transA,i,e.transB,t.length===3?t[2].dims:void 0),_=[d,m];if(!_)throw new Error("Can't use gemm on the given tensors");let b=r[r.length-1],y="";e.transA&&(b=r[0]),e.transA&&e.transB?y="value += _A_T(a) * _B_T(b);":e.transA&&!e.transB?y="value += _A_T(a) * _B(b);":!e.transA&&e.transB?y="value += _A(a) * _B_T(b);":e.transA||e.transB||(y="value += _A(a) * _B(b);");const T=_.length,w=`
      float process(int indices[${T}]) {
          int a[${T}];
          int b[${T}];
          ${t.length===3?`int c[${t[2].dims.length}];`:""}

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

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

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

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

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

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

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

          `;const $=`
      ${O}

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

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

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

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

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

vec4 getBAtOutCoordsMatmul(int i) {
  ${Oe} coords = getOutputCoords();
  ${ze}
  ${Ge}
  vec4 outputValue = getB(${He});
  return outputValue;
}`}(C,N,_,E)}`:"",te=O?"getAAtOutCoordsMatmul(i)":`getA(${function(Oe,he){let xe="";for(let we=0;we<he-2;we++)xe+=`rc.${Oe[we]}, `;return xe+=`rc.${Oe[he-2]}, i*2`,xe}(N,$)})`,de=O?"getBAtOutCoordsMatmul(i)":`getB(${function(Oe,he){let xe="";for(let we=0;we<he-2;we++)xe+=`rc.${Oe[we]}, `;return xe+=`i*2, rc.${Oe[he-1]}`,xe}(N,D)})`,ke=`
            ${ee}
            ${Y}
            ${j}
            void main() {
              ${O?"":`${C} rc =
          getOutputCoords(); int lastDim = rc.${N[U-1]}; rc.${N[U-1]} =
          rc.${N[U-2]}; rc.${N[U-2]} = lastDim;
      `}

              vec4 value = vec4(0);
              for (int i = 0; i < ${M}; i++) {
                vec4 a = ${te};
                vec4 b = ${de};

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

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

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

            ${e.output} = vec4(${v});
          }
        }
      `;return Object.assign(Object.assign({},h),{hasMain:!0,output:{dims:t.dims,type:t.type,textureType:l.TextureType.packed},shaderSource:M})})(g,c)})},2827:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.unpackFromChannel=n.getChannels=n.getVecChannels=void 0;const a=o(9390);function l(p,u){return(0,a.getGlChannels)(u).map(h=>`${p}.${h}`)}n.getVecChannels=l,n.getChannels=function(p,u){return u===1?[p]:l(p,u)},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:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parsePadAttributesV11=n.padV11=n.parsePadAttributesV2=n.padV2=void 0;const a=o(246),l=o(2517),p=o(5060),u=o(2039),h={name:"Pad",inputNames:["A"],inputTypes:[u.TextureType.unpacked]};n.padV2=(m,_,b)=>(s(_),[m.run(Object.assign(Object.assign({},h),{cacheHint:b.cacheKey,get:()=>c(m,_[0],b)}),_)]),n.parsePadAttributesV2=m=>{const _=m.attributes.getString("mode","constant"),b=m.attributes.getFloat("value",0),y=m.attributes.getInts("pads");return(0,a.createAttributeWithCacheKey)({mode:_,value:b,pads:y})},n.padV11=(m,_,b)=>{t(_);const y=g(m,_,b);return(0,n.padV2)(m,[_[0]],y)},n.parsePadAttributesV11=m=>m.attributes.getString("mode","constant");const g=(m,_,b)=>{if(!m.session.isInitializer(_[1].dataId)||_.length>=3&&!m.session.isInitializer(_[2].dataId))throw new Error("dynamic pad attributes are not allowed");const y=Array.from(_[1].integerData),T=_.length>=3?_[2].floatData[0]:0;return(0,a.createAttributeWithCacheKey)({mode:b,pads:y,value:T})},c=(m,_,b)=>{const y=l.ShapeUtil.padShape(_.dims.slice(),b.pads),T=y.length,w=`
      ${e(m,_,b)}
      float process(int[${T}] indices) {
          return padA(indices);
      }`;return{name:"Pad",inputNames:["A"],inputTypes:[u.TextureType.unpacked],output:{dims:y,type:_.type,textureType:u.TextureType.unpacked},shaderSource:w}},s=m=>{if(!m||m.length!==1)throw new Error("Pad requires 1 input");if(m[0].type!=="float32"&&m[0].type!=="float64")throw new Error("Invalid input type.")},t=m=>{if(!m||m.length!==2&&m.length!==3)throw new Error("Pad requires 2 or 3 inputs");if(m[1].type!=="int32")throw new Error("Invalid input type.");if(m.length>=3&&m[2].type==="string")throw new Error("Invalid input type.")},e=(m,_,b)=>{const y=(0,p.getGlsl)(m.session.backend.glContext.version),[T,w]=m.calculateTextureWidthAndHeight(_.dims,u.TextureType.unpacked),S=l.ShapeUtil.computeStrides(_.dims);switch(b.mode){case"constant":return r(y,_.dims,S,T,w,b.pads,b.value);case"reflect":return i(y,_.dims,S,T,w,b.pads);case"edge":return d(y,_.dims,S,T,w,b.pads);default:throw new Error("Invalid mode")}},r=(m,_,b,y,T,w,S)=>{const E=_.length;let O="";for(let v=E-1;v>=0;--v)O+=`
        k = m[${v}] - ${w[v]};
        if (k < 0)  return constant;
        if (k >= ${_[v]}) return constant;
        offset += k * ${b[v]};
        `;return`
      float padA(int m[${E}]) {
        const float constant = float(${S});
        int offset = 0;
        int k = 0;
        ${O}
        vec2 coords = offsetToCoords(offset, ${y}, ${T});
        float value = getColorAsFloat(${m.texture2D}(A, coords));
        return value;
      }
      `},i=(m,_,b,y,T,w)=>{const S=_.length;let E="";for(let O=S-1;O>=0;--O)E+=`
        k = m[${O}] - ${w[O]};
        if (k < 0) { k = -k; }
        {
          const int _2n_1 = ${2*(_[O]-1)};
          k = int( mod( float(k), float(_2n_1) ) ) ;
          if(k >= ${_[O]}) { k = _2n_1 - k; }
        }
        offset += k * ${b[O]};
        `;return`
      float padA(int m[${S}]) {
        int offset = 0;
        int k = 0;
        ${E}
        vec2 coords = offsetToCoords(offset, ${y}, ${T});
        float value = getColorAsFloat(${m.texture2D}(A, coords));
        return value;
      }
      `},d=(m,_,b,y,T,w)=>{const S=_.length;let E="";for(let O=S-1;O>=0;--O)E+=`
        k = m[${O}] - ${w[O]};
        if (k < 0)  k = 0;
        if (k >= ${_[O]}) k = ${_[O]-1};
        offset += k * ${b[O]};
      `;return`
      float padA(int m[${S}]) {
        int offset = 0;
        int k = 0;
        ${E}
        vec2 coords = offsetToCoords(offset, ${y}, ${T});
        float value = getColorAsFloat(${m.texture2D}(A, coords));
        return value;
      }
      `}},2143:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.globalMaxPool=n.parseMaxPoolAttributes=n.maxPool=n.parseGlobalAveragePoolAttributes=n.globalAveragePool=n.parseAveragePoolAttributes=n.averagePool=void 0;const a=o(246),l=o(2517),p=o(2039);n.averagePool=(d,m,_)=>{t(m);const b={name:"AveragePool",inputNames:["X"],inputTypes:[p.TextureType.unpacked],cacheHint:_.cacheKey};return[d.run(Object.assign(Object.assign({},b),{get:()=>u(m,b,!1,_)}),m)]},n.parseAveragePoolAttributes=d=>{const m=d.attributes.getString("auto_pad","NOTSET"),_=d.attributes.getInt("ceil_mode",0),b=d.attributes.getInt("count_include_pad",0)!==0,y=d.attributes.getInts("kernel_shape"),T=d.attributes.getInts("strides",[]),w=d.attributes.getInts("pads",[]);if(_!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,a.createAttributeWithCacheKey)({autoPad:m,ceilMode:_,countIncludePad:b,kernelShape:y,strides:T,pads:w})};const u=(d,m,_,b)=>{const[y,T]=g(d,b,_),w=l.ShapeUtil.size(y.kernelShape);let S="";y.countIncludePad?S+=`value /= float(${w});`:S+=`value /= float(${w} - pad);`;const E=`
        ${e(d[0].dims,y,"value += _X(x);",S,"0.0")}
      `;return Object.assign(Object.assign({},m),{output:{dims:T,type:d[0].type,textureType:p.TextureType.unpacked},shaderSource:E})};n.globalAveragePool=(d,m,_)=>{t(m);const b={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[p.TextureType.unpacked],cacheHint:`${_.countIncludePad}`};return[d.run(Object.assign(Object.assign({},b),{get:()=>u(m,b,!0,_)}),m)]},n.parseGlobalAveragePoolAttributes=d=>{const m=d.attributes.getInt("count_include_pad",0)!==0;return(0,a.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:m,kernelShape:[],strides:[],pads:[]})},n.maxPool=(d,m,_)=>{t(m);const b={name:"MaxPool",inputNames:["X"],inputTypes:[p.TextureType.unpacked],cacheHint:_.cacheKey};return[d.run(Object.assign(Object.assign({},b),{get:()=>h(m,b,!1,_)}),m)]},n.parseMaxPoolAttributes=d=>{const m=d.attributes.getString("auto_pad","NOTSET"),_=d.attributes.getInt("ceil_mode",0),b=d.attributes.getInts("kernel_shape"),y=d.attributes.getInts("strides",[]),T=d.attributes.getInts("pads",[]),w=d.attributes.getInt("storage_order",0),S=d.attributes.getInts("dilations",[]);if(w!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(_!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return(0,a.createAttributeWithCacheKey)({autoPad:m,ceilMode:_,countIncludePad:!1,kernelShape:b,strides:y,pads:T,storageOrder:w,dilations:S})};const h=(d,m,_,b)=>{const[y,T]=g(d,b,_),w=`
      ${e(d[0].dims,y,`
      value = max(_X(x), value);
    `,"","-1e5")}
    `;return Object.assign(Object.assign({},m),{output:{dims:T,type:d[0].type,textureType:p.TextureType.unpacked},shaderSource:w})},g=(d,m,_)=>{const b=d[0].dims.slice(),y=Object.hasOwnProperty.call(m,"dilations"),T=m.kernelShape.slice(),w=m.strides.slice(),S=y?m.dilations.slice():[],E=m.pads.slice();l.PoolConvUtil.adjustPoolAttributes(_,b,T,w,S,E);const O=l.PoolConvUtil.computePoolOutputShape(_,b,w,S,T,E,m.autoPad),v=Object.assign({},m);return y?Object.assign(v,{kernelShape:T,strides:w,pads:E,dilations:S,cacheKey:m.cacheKey}):Object.assign(v,{kernelShape:T,strides:w,pads:E,cacheKey:m.cacheKey}),[v,O]},c={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},s={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[p.TextureType.unpacked]};n.globalMaxPool=(d,m)=>(t(m),[d.run(Object.assign(Object.assign({},s),{get:()=>h(m,s,!0,c)}),m)]);const t=d=>{if(!d||d.length!==1)throw new Error("Pool ops requires 1 input.");if(d[0].type!=="float32"&&d[0].type!=="float64")throw new Error("Invalid input type.")},e=(d,m,_,b,y)=>{const T=d.length;if(m.kernelShape.length<=2){const w=m.kernelShape[m.kernelShape.length-1],S=m.strides[m.strides.length-1],E=m.pads[m.pads.length/2-1],O=m.pads[m.pads.length-1],v=d[T-1];let M="",$="",D="";if(M=E+O!==0?`
          for (int i = 0; i < ${w}; i++) {
            x[${T} - 1] = indices[${T} - 1] * ${S} - ${E} + i;
            if (x[${T} - 1] < 0 || x[${T} - 1] >= ${v}) {
              pad++;
              continue;
            }
            ${_}
          }`:`
          for (int i = 0; i < ${w}; i++) {
            x[${T} - 1] = indices[${T} - 1] * ${S} - ${E} + i;
            ${_}
          }`,m.kernelShape.length===2){const L=m.kernelShape[m.kernelShape.length-2],C=m.strides[m.strides.length-2],U=m.pads[m.pads.length/2-2],N=m.pads[m.pads.length-2],j=d[T-2];$=U+N!==0?`
            for (int j = 0; j < ${L}; j++) {
              x[${T} - 2] = indices[${T} - 2] * ${C} - ${U} + j;
              if (x[${T} - 2] < 0 || x[${T} - 2] >= ${j}) {
                pad+= ${w};
                continue;
              }
          `:`
            for (int j = 0; j < ${L}; j++) {
              x[${T} - 2] = indices[${T} - 2] * ${C} - ${U} + j;
            `,D=`
          }
        `}return`
        float process(int indices[${T}]) {
          int x[${T}];
          copyVec(indices, x);

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

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

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

          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex);
          vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z));

          result[${T}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims);

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

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

        vec4 result = vec4(0.0);

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

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

                int batch = rc[0];
                int depth = rc[1];

                // retrieve the 4 coordinates that is used in the 4 packed output values.
                ivec4 coords = ivec4(rc.wz, rc.w + 1, rc.z + 1);

                // calculate the source index in fraction
                vec4 sourceFrac = getSourceFracIndex(coords);

                // get the lower and upper bound of the 4 values that will be packed into one texel.
                ivec4 x00 = ivec4(max(sourceFrac.xy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xy)));
                ivec4 x01 = ivec4(max(sourceFrac.xw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xw)));
                ivec4 x10 = ivec4(max(sourceFrac.zy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zy)));
                ivec4 x11 = ivec4(max(sourceFrac.zw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zw)));

                bool hasNextRow = rc.w < ${T-1};
                bool hasNextCol = rc.z < ${w-1};

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

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

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

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

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

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

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

        float max = getColorAsFloat(${O.texture2D}(A, offsetToCoords(logical_row_start_offset, ${w},
        ${S} )));
        for(int i=1; i<${y}; ++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({},g),{output:{dims:T,type:_.type,textureType:u.TextureType.unpacked},shaderSource:v})},r=(m,_,b,y,T,w)=>{const[S,E]=m.calculateTextureWidthAndHeight(_.dims,u.TextureType.unpacked),O=w.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(w.length!==1)throw new Error("Dimensionality of the output should be 1");if(w[0]!==b)throw new Error("Shape of the output should be equal to logical row count");if(T.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(T[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const v=`
      float process(int[${O}] indices) {
        int logical_row_start_offset = indices[0] * ${y};

        float norm_factor = 0.0;
        float max = _Max(indices);
        for(int i=0; i<${y}; ++i)
        {
          norm_factor += exp(getColorAsFloat(${(0,p.getGlsl)(m.session.backend.glContext.version).texture2D}(A, offsetToCoords(logical_row_start_offset + i,
            ${S}, ${E}))) - max);
        }

        return norm_factor;
      }`;return Object.assign(Object.assign({},c),{output:{dims:w,type:_.type,textureType:u.TextureType.unpacked},shaderSource:v})},i=(m,_,b,y,T,w)=>{const[S,E]=m.calculateTextureWidthAndHeight(_.dims,u.TextureType.unpacked),O=_.dims.length;if(b<1||y<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(T.length!==1||w.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(T[0]!==b||w[0]!==b)throw new Error("Shape of the intermediate results should be equal to logical row count");const v=`
      float process(int[${O}] indices) {

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

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

      float norm_factor = _Norm(logical_row_index);

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

      return exp(_A(indices) - _Max(logical_row_index)) / norm_factor;
    }`;return Object.assign(Object.assign({},s),{output:{dims:_.dims,type:_.type,textureType:u.TextureType.unpacked},shaderSource:v})},d=m=>{if(!m||m.length!==1)throw new Error("Softmax requires 1 input.");if(m[0].type!=="float32"&&m[0].type!=="float64")throw new Error("Invalid input type")}},5975:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSplitAttributes=n.split=void 0;const a=o(246),l=o(2517),p=o(2039),u={name:"Split",inputNames:["A"],inputTypes:[p.TextureType.unpacked]};n.split=(s,t,e)=>{c(t);const r=l.ShapeUtil.normalizeAxis(e.axis,t[0].dims.length),i=h(s,t,r,e),d=[];for(let m=0;m<i;++m)d.push(s.run(Object.assign(Object.assign({},u),{cacheHint:`${e.cacheKey};${m}`,get:()=>g(s,t[0],e,r,m)}),t));return d},n.parseSplitAttributes=s=>{const t=s.attributes.getInt("axis",0),e=s.attributes.getInts("split",[]),r=s.outputs.length;return(0,a.createAttributeWithCacheKey)({axis:t,split:e,numOutputs:r})};const h=(s,t,e,r)=>{const[,i]=l.SplitUtil.splitShape(t[0].dims,e,r.split,r.numOutputs);return i.length},g=(s,t,e,r,i)=>{const[d,m]=l.SplitUtil.splitShape(t.dims,r,e.split,e.numOutputs),_=m[i],b=d[i],y=`
      float process(int indices[${b.length}]) {
        indices[${r}] += ${_};
        return _A(indices);
      }
    `;return Object.assign(Object.assign({},u),{cacheHint:`${e.cacheKey}:${i}`,output:{dims:b,type:t.type,textureType:p.TextureType.unpacked},shaderSource:y})},c=s=>{if(!s||s.length!==1)throw new Error("Split requires one input.");if(s[0].type!=="int8"&&s[0].type!=="uint8"&&s[0].type!=="int16"&&s[0].type!=="uint16"&&s[0].type!=="int32"&&s[0].type!=="uint32"&&s[0].type!=="float32"&&s[0].type!=="float64"&&s[0].type!=="bool")throw new Error("Invalid input type.")}},3933:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseSqueezeAttributes=n.squeezeV13=n.squeeze=void 0;const a=o(2517);n.squeeze=(u,h,g)=>{l(h);const c=a.ShapeUtil.squeezeShape(h[0].dims,g);return[u.reshapeUnpacked(h[0],c)]},n.squeezeV13=(u,h)=>(p(h),(0,n.squeeze)(u,[h[0]],Array.from(h[1].integerData))),n.parseSqueezeAttributes=u=>u.attributes.getInts("axes");const l=u=>{if(!u||u.length!==1)throw new Error("Squeeze requires 1 input.");if(u[0].type==="string")throw new Error("invalid input tensor types.")},p=u=>{if(!u||u.length!==2)throw new Error("Squeeze requires 2 inputs.");if(u[1].type!=="int32")throw new Error("Invalid input type.")}},6558:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.sum=void 0;const a=o(5060),l=o(2039);n.sum=(h,g)=>{u(g);const c={name:"Sum",inputNames:g.map((s,t)=>`X${t}`),inputTypes:new Array(g.length).fill(l.TextureType.unpacked)};return[h.run(Object.assign(Object.assign({},c),{get:()=>p(h,g,c)}),g)]};const p=(h,g,c)=>{const s=(0,a.getGlsl)(h.session.backend.glContext.version),t=g[0].dims.slice(),e=`
      void main() {
        vec4 result = ${g.map((r,i)=>`${s.texture2D}(X${i},TexCoords)`).join(" + ")};
        ${s.output} = result;
      }
    `;return Object.assign(Object.assign({},c),{output:{dims:t,type:g[0].type,textureType:l.TextureType.unpacked},hasMain:!0,shaderSource:e})},u=h=>{if(!h||h.length===0)throw new Error("Sum requires inputs.");const g=h[0].dims.length;for(let c=1;c<h.length;c++){if(g!==h[c].dims.length)throw new Error("Input shapes are mismatched.");for(let s=0;s<g;s++)if(h[0].dims[s]!==h[c].dims[s])throw new Error("Input shapes are not matched.")}if(h[0].type!=="float32"&&h[0].type!=="float64")throw new Error("Invalid input type.");for(let c=1;c<h.length;c++)if(h[0].type!==h[c].type)throw new Error("Input types are not matched.")}},5723:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.tile=void 0;const a=o(782),l=o(2039);n.tile=(h,g)=>{u(g);const c={name:"Tile",inputNames:["A"],inputTypes:[l.TextureType.unpacked]};return[h.run(Object.assign(Object.assign({},c),{get:()=>p(h,g,c)}),g)]};const p=(h,g,c)=>{const s=g[0].dims.slice(),t=new Array(s.length),e=[];for(let d=0;d<s.length;d++)t[d]=s[d]*g[1].numberData[d],e.push(`inputIdx[${d}] = int(mod(float(outputIdx[${d}]), ${s[d]}.));`);const r=t.length,i=`
      float process(int outputIdx[${r}]) {
        int inputIdx[${r}];
        ${e.join(`
`)}
        return _A(inputIdx);
      }
    `;return Object.assign(Object.assign({},c),{output:{dims:t,type:g[0].type,textureType:l.TextureType.unpacked},shaderSource:i})},u=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(a.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:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.parseTransposeAttributes=n.transpose=void 0;const a=o(246),l=o(2517),p=o(2039),u={name:"Transpose",inputNames:["A"],inputTypes:[p.TextureType.unpacked]};n.transpose=(e,r,i)=>(t(r),[e.run(Object.assign(Object.assign({},u),{cacheHint:i.cacheKey,get:()=>h(e,r[0],i.perm)}),r)]),n.parseTransposeAttributes=e=>(0,a.createAttributeWithCacheKey)({perm:e.attributes.getInts("perm",[])});const h=(e,r,i)=>{const d=r.dims;i=g(d,i);const m=c(d,i),_=d.length,b=`
      ${s("perm",i,_)}
      float process(int indices[${_}]) {
        int a[${_}];
        perm(a, indices);
        return _A(a);
      }`;return Object.assign(Object.assign({},u),{output:{dims:m,type:r.type,textureType:p.TextureType.unpacked},shaderSource:b})},g=(e,r)=>(r&&r.length!==e.length&&(r=[...e.keys()].reverse()),r),c=(e,r)=>(r=g(e,r),l.ShapeUtil.sortBasedOnPerm(e,r)),s=(e,r,i)=>{const d=[];d.push(`void ${e}(out int a[${i}], int src[${i}]) {`);for(let m=0;m<i;++m)d.push(`	a[${r[m]}]=src[${m}];`);return d.push("	}"),d.join(`
`)},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:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.encodeAsUint8=void 0;const a=o(5060),l=o(2039);n.encodeAsUint8=(p,u)=>{const h=u.shape,g=(0,a.getGlsl)(p.session.backend.glContext.version),c=`
    const float FLOAT_MAX = 1.70141184e38;
    const float FLOAT_MIN = 1.17549435e-38;

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

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

      highp float av = abs(v);

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

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

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

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

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

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

      return c / 255.0;
    }

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

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

  float ${J}_(float a) {
    return clamp(a, min, max);
  }
  vec4 ${J}_(vec4 v) {
    return clamp(v, min, max);
  }
  `,name:J,type:p.FunctionType.ValueBased}}function b(){const N="indentity";return{body:`
  float ${N}_(float a) {
    return a;
  }
  vec4 ${N}_(vec4 v) {
    return v;
  }
  `,name:N,type:p.FunctionType.ValueBased}}function y(N){const j="leakyRelu";return{body:`
  const float alpha = float(${N});

  float ${j}_(float a) {
    return a < 0.0 ? a * alpha : a;
  }
  vec4 ${j}_(vec4 v) {
    return vec4(${j}_(v.x), ${j}_(v.y), ${j}_(v.z), ${j}_(v.w));
  }
  `,name:j,type:p.FunctionType.ValueBased}}function T(){return L("log")}function w(){const N="neg";return{body:`
  float ${N}_(float a) {
    return -a;
  }
  vec4 ${N}_(vec4 v) {
    return -v;
  }
  `,name:N,type:p.FunctionType.ValueBased}}function S(){const N="not";return{body:`
  float ${N}_(float a) {
    return float( ! bool(a) );
  }
  bool ${N}_(bool a) {
    return !a;
  }
  vec4 ${N}_(vec4 v) {
    return vec4(!bool(v.x), !bool(v.y), !bool(v.z), !bool(v.w));
  }
  bvec4 ${N}_(bvec4 v) {
    return bvec4(!v.x, !v.y, !v.z, !v.w);
  }
  `,name:N,type:p.FunctionType.ValueBased}}function E(){return L("sin")}function O(){const N="relu";return{body:`
  float ${N}_(float a) {
    return max( a, 0.0 );
  }
  vec4 ${N}_(vec4 v) {
    return max( v, 0.0 );
  }
  `,name:N,type:p.FunctionType.ValueBased}}function v(){const N="sigmoid";return{body:`
  float ${N}_(float a) {
    return 1.0 / (1.0 + exp(-a));
  }
  vec4 ${N}_(vec4 v) {
    return 1.0 / (1.0 + exp(-v));
  }
  `,name:N,type:p.FunctionType.ValueBased}}function M(){return L("sqrt")}function $(){return L("tan")}function D(){const N="tanh";return{body:`
  float ${N}_(float a) {
    a = clamp(a, -10., 10.);
    a = exp(2.*a);
    return (a - 1.) / (a + 1.);
  }
  vec4 ${N}_(vec4 v) {
    v = clamp(v, -10., 10.);
    v = exp(2.*v);
    return (v - 1.) / (v + 1.);
  }
  `,name:N,type:p.FunctionType.ValueBased}}function L(N){return{body:`
  float ${N}_(float a) {
    return ${N}(a);
  }
  vec4 ${N}_(vec4 v) {
    return ${N}(v);
  }
  `,name:N,type:p.FunctionType.ValueBased}}n.glslAbs=g,n.glslAcos=c,n.glslAsin=s,n.glslAtan=t,n.glslCeil=e,n.glslCos=r,n.glslElu=i,n.glslExp=d,n.glslFloor=m,n.glslClip=_,n.glslIdentity=b,n.glslLeakyRelu=y,n.glslLog=T,n.glslNeg=w,n.glslNot=S,n.glslSin=E,n.glslRelu=O,n.glslSigmoid=v,n.glslSqrt=M,n.glslTan=$,n.glslTanh=D;const C=(N,j,J,Y)=>{const ee=N.session.pack?h.TextureType.packed:h.TextureType.unpacked,te={name:J.name,inputTypes:[ee],inputNames:["A"],cacheHint:Y};return Object.assign(Object.assign({},te),{get:()=>((de,ke,Oe,he)=>{const xe=de.session.pack?h.TextureType.packed:h.TextureType.unpacked,we=(0,u.getGlsl)(de.session.backend.glContext.version);return Object.assign(Object.assign({},ke),{output:{dims:Oe.dims,type:Oe.type,textureType:xe},shaderSource:`
     ${he.body}
     void main() {
       vec4 v = ${we.texture2D}(A, TexCoords);
       v = ${he.name}_(v);
       ${we.output} = v;
     }
     `,hasMain:!0})})(N,te,j,J)})};n.abs=(N,j)=>[N.run(C(N,j[0],g()),j)],n.acos=(N,j)=>[N.run(C(N,j[0],c()),j)],n.asin=(N,j)=>[N.run(C(N,j[0],s()),j)],n.atan=(N,j)=>[N.run(C(N,j[0],t()),j)],n.clip=(N,j,J)=>[N.run(C(N,j[0],_(J.min,J.max),J.cacheKey),j)],n.parseClipAttributes=N=>(0,a.createAttributeWithCacheKey)({min:N.attributes.getFloat("min",l.MIN_CLIP),max:N.attributes.getFloat("max",l.MAX_CLIP)}),n.clipV11=(N,j)=>{const J=U(N,j);return(0,n.clip)(N,[j[0]],J)};const U=(N,j)=>{if(j.length>=3&&(!N.session.isInitializer(j[1].dataId)||!N.session.isInitializer(j[2].dataId)))throw new Error("dynamic clip attributes are not allowed");const J=j.length>=3?j[1].numberData[0]:l.MIN_CLIP,Y=j.length>=3?j[2].numberData[0]:l.MAX_CLIP;return(0,a.createAttributeWithCacheKey)({min:J,max:Y})};n.ceil=(N,j)=>[N.run(C(N,j[0],e()),j)],n.cos=(N,j)=>[N.run(C(N,j[0],r()),j)],n.elu=(N,j,J)=>[N.run(C(N,j[0],i(J.alpha),J.cacheKey),j)],n.parseEluAttributes=N=>(0,a.createAttributeWithCacheKey)({alpha:N.attributes.getFloat("alpha",1)}),n.exp=(N,j)=>[N.run(C(N,j[0],d()),j)],n.floor=(N,j)=>[N.run(C(N,j[0],m()),j)],n.identity=(N,j)=>[N.run(C(N,j[0],b()),j)],n.leakyRelu=(N,j,J)=>[N.run(C(N,j[0],y(J.alpha),J.cacheKey),j)],n.parseLeakyReluAttributes=N=>(0,a.createAttributeWithCacheKey)({alpha:N.attributes.getFloat("alpha",.01)}),n.log=(N,j)=>[N.run(C(N,j[0],T()),j)],n.neg=(N,j)=>[N.run(C(N,j[0],w()),j)],n.not=(N,j)=>[N.run(C(N,j[0],S()),j)],n.relu=(N,j)=>[N.run(C(N,j[0],O()),j)],n.sigmoid=(N,j)=>[N.run(C(N,j[0],v()),j)],n.sin=(N,j)=>[N.run(C(N,j[0],E()),j)],n.sqrt=(N,j)=>[N.run(C(N,j[0],M()),j)],n.tan=(N,j)=>[N.run(C(N,j[0],$()),j)],n.tanh=(N,j)=>[N.run(C(N,j[0],D()),j)]},5611:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.createUnpackProgramInfoLoader=n.createUnpackProgramInfo=void 0;const a=o(5060),l=o(2039),p=o(9390),u=o(2827),h={name:"unpack",inputNames:["A"],inputTypes:[l.TextureType.packed]};n.createUnpackProgramInfo=(g,c)=>{const s=c.dims.length,t=(0,u.getChannels)("rc",s),e=t.slice(-2),r=(0,p.getCoordsDataType)(s),i=(0,u.unpackFromChannel)(),d=c.dims.length===0?"":function(b,y){if(b===1)return"rc";let T="";for(let w=0;w<b;w++)T+=y[w],w<b-1&&(T+=",");return T}(s,t),m=s<=1?"rc":`vec2(${e.join(",")})`,_=`
    ${i}
    void main() {
      ${r} rc = getOutputCoords();

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

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

      ${T}

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

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

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

      ${T}

      int m;
      int index_of_dim0, index_of_dim1, index_of_dim2, index_of_dim3;
      index_of_dim0 = output_index / output_pitches[0];
      m = output_index - index_of_dim0 * output_pitches[0];
      index_of_dim1 = m / output_pitches[1];
      m = m - index_of_dim1 * output_pitches[1];
      index_of_dim2 = m / output_pitches[2];
      m = m - index_of_dim2 * output_pitches[2];
      index_of_dim3 = m;

      int index_of_input_dim2, index_of_input_dim3, x_offset, y_offset;
      index_of_input_dim2 = index_of_dim2 / scales[2];
      y_offset = index_of_dim2 - index_of_input_dim2 * scales[2];
      index_of_input_dim3 = index_of_dim3 / scales[3];
      x_offset = index_of_dim3 - index_of_input_dim3 * scales[3];

      input_index = index_of_dim0 * input_pitches[0] +
            index_of_dim1 * input_pitches[1] +
            index_of_input_dim2 * input_pitches[2] +
            index_of_input_dim3;

      float x00 = getInputFloat(input_index);
      float x10, x01, x11;

      bool end_of_dim2 = false;
      if (index_of_input_dim2 == (${c[0].dims[2]} - 1)) {
        // It's the end in dimension 2
        x01 = x00;
        end_of_dim2 = true;
      } else {
        x01 = getInputFloat(input_index + input_pitches[2]);
      }

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

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

      ${T}

      int m;
      int index_of_dim0, index_of_dim1;
      index_of_dim0 = output_index / output_pitches[0];
      m = output_index - index_of_dim0 * output_pitches[0];
      index_of_dim1 = m;

      int index_of_input_dim0, index_of_input_dim1, x_offset, y_offset;
      index_of_input_dim0 = index_of_dim0 / scales[0];
      y_offset = index_of_dim0 - index_of_input_dim0 * scales[0];
      index_of_input_dim1 = index_of_dim1 / scales[1];
      x_offset = index_of_dim1 - index_of_input_dim1 * scales[1];

      input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1;

      float x00 = getInputFloat(input_index);
      float x10, x01, x11;

      bool end_of_dim0 = false;
      if (index_of_input_dim0 == (${c[0].dims[0]} - 1)) {
        // It's the end in dimension 0
        x01 = x00;
        end_of_dim0 = true;
      } else {
        x01 = getInputFloat(input_index + input_pitches[0]);
      }

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

      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[0]);
      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[0]);
      return y0 + float(x_offset) * (y1 - y0) / float(scales[1]);
    }`;return Object.assign(Object.assign({},u),{output:{dims:i,type:c[0].type,textureType:p.TextureType.unpacked},shaderSource:S,variables:[{name:"scales",type:"int",arrayLength:s.scales.length,data:s.scales.map(E=>Math.ceil(E))}]})};n.validateInputs=(g,c)=>{if(!g||c.opset<9&&g.length!==1||c.opset>=9&&c.opset<11&&g.length!==2||c.opset>=11&&g.length<2)throw new Error("invalid inputs.");if(c.scales.length>0&&g[0].dims.length!==c.scales.length)throw new Error("Invalid input shape.");if(g[0].type==="string")throw new Error("Invalid input tensor types.")},n.scalesValidation=(g,c,s)=>{if(s){for(const t of g)if(t<=0)throw new Error("Scale value should be greater than 0.")}else for(const t of g)if(t<1)throw new Error("Scale value should be greater than or equal to 1.");if(!(c!=="linear"&&c!=="cubic"||g.length===2||g.length===4&&g[0]===1&&g[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:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.ProgramManager=void 0;const a=o(1670),l=o(6231),p=o(8879),u=o(5060);n.ProgramManager=class{constructor(h,g,c){this.profiler=h,this.glContext=g,this.textureLayoutStrategy=c,this.repo=new Map,this.attributesBound=!1}getArtifact(h){return this.repo.get(h)}setArtifact(h,g){this.repo.set(h,g)}run(h,g,c){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(c),this.attributesBound||this.bindAttributes(h.attribLocations),this.bindUniforms(h.uniformLocations,(t=h.programInfo.variables)!==null&&t!==void 0?t:[],g)}catch(i){throw l.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,g,c){return this.profiler.event("backend","ProgramManager.build",()=>{const s=new p.GlslPreprocessor(this.glContext,h,g,c),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){l.Logger.verbose("ProrgramManager","Compiling and caching Vertex shader for the first time");const s=(0,u.getVertexShaderSource)(this.glContext.version);this.vertexShader=this.glContext.compileShader(s,this.glContext.gl.VERTEX_SHADER)}a.env.debug&&l.Logger.verbose("ProrgramManager",`FragShader:
${h}
`);const g=this.glContext.compileShader(h,this.glContext.gl.FRAGMENT_SHADER),c=this.glContext.createProgram(this.vertexShader,g);return this.glContext.deleteShader(g),c}bindOutput(h){const g=h.width,c=h.height;l.Logger.verbose("ProrgramManager",`Binding output texture to Framebuffer: w/h=${g}/${c}, shape=${h.shape}, type=${h.tensor.type}`),this.glContext.attachFramebuffer(h.texture,g,c)}bindAttributes(h){const g=h.position,c=h.textureCoord;this.glContext.setVertexAttributes(g,c),this.attributesBound=!0}bindUniforms(h,g,c){var s;const t=this.glContext.gl;let e=0;for(const{name:r,type:i,location:d,arrayLength:m}of h){const _=(s=g.find(b=>b.name===r))===null||s===void 0?void 0:s.data;if(i!=="sampler2D"&&!_)throw new Error(`variable '${r}' does not have data defined in program info`);switch(i){case"sampler2D":this.bindTexture(c[e],d,e),e++;break;case"float":m?t.uniform1fv(d,_):t.uniform1f(d,_);break;case"int":m?t.uniform1iv(d,_):t.uniform1i(d,_);break;default:throw new Error(`Uniform not implemented: ${i}`)}}}bindTexture(h,g,c){this.glContext.bindTextureToUniform(h.texture,c,g)}getAttribLocations(h){return{position:this.getAttribLocation(h,"position"),textureCoord:this.getAttribLocation(h,"textureCoord")}}getUniformLocations(h,g,c){const s=[];if(g)for(const t of g)s.push({name:t,type:"sampler2D",location:this.getUniformLocation(h,t)});if(c)for(const t of c)s.push(Object.assign(Object.assign({},t),{location:this.getUniformLocation(h,t.name)}));return s}getUniformLocation(h,g){const c=this.glContext.gl.getUniformLocation(h,g);if(c===null)throw new Error(`Uniform ${g} not found.`);return c}getAttribLocation(h,g){return this.glContext.gl.getAttribLocation(h,g)}}},6416:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.WebGLSessionHandler=void 0;const a=o(6231),l=o(1047),p=o(8316),u=o(1640),h=o(1958),g=o(7859),c=o(5702);n.WebGLSessionHandler=class{constructor(s,t){this.backend=s,this.context=t,this.layoutStrategy=new g.PreferLogicalStrategy(s.glContext.maxTextureSize),this.programManager=new h.ProgramManager(this.context.profiler,s.glContext,this.layoutStrategy),this.textureManager=new c.TextureManager(s.glContext,this.layoutStrategy,this.context.profiler,{reuseTextures:s.textureCacheMode==="full"}),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new Map,this.pack=s.pack,this.pack2unpackMap=new Map,this.unpack2packMap=new Map}createInferenceHandler(){return new p.WebGLInferenceHandler(this)}onGraphInitialized(s){const t=s.getValues().filter(e=>e.from===-1&&e.tensor).map(e=>e.tensor.dataId);this.initializers=new Set(t)}isInitializer(s){return!!this.initializers&&this.initializers.has(s)}addInitializer(s){this.initializers.add(s)}getTextureData(s,t){return t?this.packedTextureDataCache.get(s):this.unpackedTextureDataCache.get(s)}setTextureData(s,t,e=!1){a.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,l.resolveOperator)(s,t,u.WEBGL_OP_RESOLVE_RULES);return{impl:r.opImpl,context:r.opInit?r.opInit(s,e):s}}}},7769:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Uint8DataEncoder=n.RGBAFloatDataEncoder=n.RedFloat32DataEncoder=void 0;const a=o(6231);n.RedFloat32DataEncoder=class{constructor(l,p=1){if(p===1)this.internalFormat=l.R32F,this.format=l.RED,this.textureType=l.FLOAT,this.channelSize=p;else{if(p!==4)throw new Error(`Invalid number of channels: ${p}`);this.internalFormat=l.RGBA32F,this.format=l.RGBA,this.textureType=l.FLOAT,this.channelSize=p}}encode(l,p){let u,h;return l.constructor!==Float32Array&&(a.Logger.warning("Encoder","data was not of type Float32; creating new Float32Array"),h=new Float32Array(l)),p*this.channelSize>l.length?(a.Logger.warning("Encoder","Source data too small. Allocating larger array"),h=l,u=this.allocate(p*this.channelSize),h.forEach((g,c)=>u[c]=g)):(h=l,u=h),u}allocate(l){return new Float32Array(4*l)}decode(l,p){return this.channelSize===1?l.filter((u,h)=>h%4==0).subarray(0,p):l.subarray(0,p)}},n.RGBAFloatDataEncoder=class{constructor(l,p=1,u){if(p!==1&&p!==4)throw new Error(`Invalid number of channels: ${p}`);this.internalFormat=l.RGBA,this.format=l.RGBA,this.channelSize=p,this.textureType=u||l.FLOAT}encode(l,p){let u=l;return this.channelSize===1&&(a.Logger.verbose("Encoder","Exploding into a larger array"),u=this.allocate(p),l.forEach((h,g)=>u[4*g]=h)),u}allocate(l){return new Float32Array(4*l)}decode(l,p){return this.channelSize===1?l.filter((u,h)=>h%4==0).subarray(0,p):l.subarray(0,p)}},n.Uint8DataEncoder=class{constructor(l,p=1){if(this.channelSize=4,p===1)this.internalFormat=l.ALPHA,this.format=l.ALPHA,this.textureType=l.UNSIGNED_BYTE,this.channelSize=p;else{if(p!==4)throw new Error(`Invalid number of channels: ${p}`);this.internalFormat=l.RGBA,this.format=l.RGBA,this.textureType=l.UNSIGNED_BYTE,this.channelSize=p}}encode(l,p){return new Uint8Array(l.buffer,l.byteOffset,l.byteLength)}allocate(l){return new Uint8Array(l*this.channelSize)}decode(l,p){if(l instanceof Uint8Array)return l.subarray(0,p);throw new Error(`Invalid array type: ${l.constructor}`)}}},7859:(f,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 a=o(6231),l=o(2517);function p(s,t){const e=[],r=[],i=t!=null&&Array.isArray(t)&&t.length===0,d=t==null||i?null:u(t,s).sort();let m=0;for(let _=0;_<s.length;++_){if(d!=null){if(d[m]===_&&s[_]!==1)throw new Error(`Can't squeeze axis ${_} since its dim '${s[_]}' is not 1`);(d[m]==null||d[m]>_)&&s[_]===1&&(e.push(s[_]),r.push(_)),d[m]<=_&&m++}s[_]!==1&&(e.push(s[_]),r.push(_))}return{newShape:e,keptDims:r}}function u(s,t){const e=t.length;return s=s==null?t.map((r,i)=>i):[].concat(s),(0,l.assert)(s.every(r=>r>=-e&&r<e),()=>`All values in axis param must be in range [-${e}, ${e}) but got axis ${s}`),(0,l.assert)(s.every(h),()=>`All values in axis param must be integers but got axis ${s}`),s.map(r=>r<0?e+r:r)}function h(s){return s%1==0}function g(s){if(s.length===0)return 1;let t=s[0];for(let e=1;e<s.length;e++)t*=s[e];return t}function c(s){const t=Math.ceil(Math.sqrt(s));return[t,Math.ceil(s/t)]}n.AlwaysKeepOriginalSizeStrategy=class{constructor(s){this.maxTextureSize=s}computeTextureWH(s,t){if(s.length===0)return[1,1];const e=this.maxTextureSize;if(t&&t.breakAxis!==void 0){const d=t.breakAxis>=s.length?1:s.slice(t.breakAxis).reduce((_,b)=>_*b),m=t.breakAxis<=0?1:s.slice(0,t.breakAxis).reduce((_,b)=>_*b);if(!(d>e||m>e))return[d,m];a.Logger.verbose("TextureLayout",`Given width/height preferences were unattainable: shape:${s}, breakAxis:${t.breakAxis}`)}const r=s.reduce((d,m)=>d*m);let i=Math.floor(Math.sqrt(r));for(;i<e&&i<r&&r%i!=0;i++);if(i>=e||r%i!=0)throw new Error(`The given dimensions are outside this GPU's boundaries: ${s}`);return[i,r/i]}},n.PreferLogicalStrategy=class{constructor(s){this.maxTextureSize=s}computeTextureWH(s,t){const e=this.computeTexture(s,t);return t&&t.isPacked&&(e[0]/=2,e[1]/=2),t&&t.reverseWH?[e[1],e[0]]:e}computeTexture(s,t){const e=t&&t.isPacked;if(s.length===0)return e?[2,2]:[1,1];let r=this.maxTextureSize;if(t&&t.breakAxis!==void 0){const m=t.breakAxis>=s.length?1:s.slice(t.breakAxis).reduce((b,y)=>b*y),_=t.breakAxis<=0?1:s.slice(0,t.breakAxis).reduce((b,y)=>b*y);if(!(m>r||_>r))return[m,_];a.Logger.verbose("TextureLayout",`Given 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Shader source:
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s.bindBuffer(s.ARRAY_BUFFER,t),s.bufferData(s.ARRAY_BUFFER,e,s.STATIC_DRAW),this.checkError(),t}createFramebuffer(){const s=this.gl.createFramebuffer();if(!s)throw new Error("createFramebuffer returned null");return s}queryVitalParameters(){const s=this.gl;if(this.isFloatTextureAttachableToFrameBuffer=this.checkFloatTextureAttachableToFrameBuffer(),this.isRenderFloat32Supported=this.checkRenderFloat32(),this.isFloat32DownloadSupported=this.checkFloat32Download(),this.version===1&&!this.textureHalfFloatExtension&&!this.isRenderFloat32Supported)throw new Error("both float32 and float16 TextureType are not 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i=s.checkFramebufferStatus(s.FRAMEBUFFER)===s.FRAMEBUFFER_COMPLETE;return s.bindTexture(s.TEXTURE_2D,null),s.bindFramebuffer(s.FRAMEBUFFER,null),s.deleteTexture(t),s.deleteFramebuffer(r),i}checkRenderFloat32(){if(this.version===2){if(!this.colorBufferFloatExtension)return!1}else if(!this.textureFloatExtension)return!1;return this.isFloatTextureAttachableToFrameBuffer}checkFloat32Download(){if(this.version===2){if(!this.colorBufferFloatExtension)return!1}else if(!this.textureFloatExtension||!this.gl.getExtension("WEBGL_color_buffer_float"))return!1;return this.isFloatTextureAttachableToFrameBuffer}checkFloat32Blend(){const s=this.gl;let t,e,r,i,d;try{t=s.createTexture(),e=s.createFramebuffer(),s.bindTexture(s.TEXTURE_2D,t);const m=this.version===2?s.RGBA32F:s.RGBA;return s.texImage2D(s.TEXTURE_2D,0,m,1,1,0,s.RGBA,s.FLOAT,null),s.bindFramebuffer(s.FRAMEBUFFER,e),s.framebufferTexture2D(s.FRAMEBUFFER,s.COLOR_ATTACHMENT0,s.TEXTURE_2D,t,0),s.enable(s.BLEND),r=s.createShader(s.VERTEX_SHADER),!!r&&(s.shaderSource(r,"void main(){}"),s.compileShader(r),i=s.createShader(s.FRAGMENT_SHADER),!!i&&(s.shaderSource(i,"precision highp float;void main(){gl_FragColor=vec4(0.5);}"),s.compileShader(i),d=s.createProgram(),!!d&&(s.attachShader(d,r),s.attachShader(d,i),s.linkProgram(d),s.useProgram(d),s.drawArrays(s.POINTS,0,1),s.getError()===s.NO_ERROR)))}finally{s.disable(s.BLEND),d&&s.deleteProgram(d),r&&s.deleteShader(r),i&&s.deleteShader(i),e&&(s.bindFramebuffer(s.FRAMEBUFFER,null),s.deleteFramebuffer(e)),t&&(s.bindTexture(s.TEXTURE_2D,null),s.deleteTexture(t))}}beginTimer(){if(this.version===2&&this.disjointTimerQueryWebgl2Extension){const s=this.gl,t=this.disjointTimerQueryWebgl2Extension,e=s.createQuery();return s.beginQuery(t.TIME_ELAPSED_EXT,e),e}throw new Error("WebGL1 profiling currently not supported.")}endTimer(){if(this.version!==2||!this.disjointTimerQueryWebgl2Extension)throw new Error("WebGL1 profiling currently not supported");{const s=this.gl,t=this.disjointTimerQueryWebgl2Extension;s.endQuery(t.TIME_ELAPSED_EXT)}}isTimerResultAvailable(s){let t=!1,e=!1;if(this.version!==2||!this.disjointTimerQueryWebgl2Extension)throw new Error("WebGL1 profiling currently not supported");{const r=this.gl,i=this.disjointTimerQueryWebgl2Extension;t=r.getQueryParameter(s,r.QUERY_RESULT_AVAILABLE),e=r.getParameter(i.GPU_DISJOINT_EXT)}return t&&!e}getTimerResult(s){let t=0;if(this.version!==2)throw new Error("WebGL1 profiling currently not supported");{const e=this.gl;t=e.getQueryParameter(s,e.QUERY_RESULT),e.deleteQuery(s)}return t/1e6}async waitForQueryAndGetTime(s){return await(0,g.repeatedTry)(()=>this.isTimerResultAvailable(s)),this.getTimerResult(s)}async createAndWaitForFence(){const s=this.createFence(this.gl);return this.pollFence(s)}createFence(s){let t;const e=s,r=e.fenceSync(e.SYNC_GPU_COMMANDS_COMPLETE,0);return s.flush(),t=r===null?()=>!0:()=>{const i=e.clientWaitSync(r,0,0);return i===e.ALREADY_SIGNALED||i===e.CONDITION_SATISFIED},{query:r,isFencePassed:t}}async pollFence(s){return new Promise(t=>{this.addItemToPoll(()=>s.isFencePassed(),()=>t())})}pollItems(){const s=c(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=s;++t){const{resolveFn:e}=this.itemsToPoll[t];e()}this.itemsToPoll=this.itemsToPoll.slice(s+1)}async addItemToPoll(s,t){this.itemsToPoll.push({isDoneFn:s,resolveFn:t}),this.itemsToPoll.length>1||await(0,g.repeatedTry)(()=>(this.pollItems(),this.itemsToPoll.length===0))}}},1036:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.ExecutionPlan=void 0;const a=o(6231);class l{constructor(u,h){this.op=u,this.node=h}}n.ExecutionPlan=class{constructor(p,u,h){this.graph=p,this.profiler=h,this.initialize(u)}initialize(p){this.profiler.event("session","ExecutionPlan.initialize",()=>{const u=this.graph.getNodes();if(u.length!==p.length)throw new Error("The size of nodes and OPs do not match.");this._ops=p.map((h,g)=>new l(h,u[g])),this.reset(),this._starter=[],this._ops.forEach((h,g)=>{let c=!0;for(const s of h.node.inputs)if(!this._values[s]&&this.graph.getInputIndices().indexOf(s)===-1){c=!1;break}c&&this._starter.push(g)})})}reset(){this._values=this.graph.getValues().map(p=>p.tensor)}async execute(p,u){return this.profiler.event("session","ExecutionPlan.execute",async()=>{this.reset();const h=p.createInferenceHandler(),g=this.graph.getInputIndices();if(u.length!==g.length)throw new Error(`number of input tensors don't match the number of inputs to the model: actual: ${u.length} expected: ${g.length}`);u.forEach((i,d)=>{const m=g[d];this._values[m]=i});const c=this._starter.slice(0),s=this.graph.getValues(),t=this.graph.getNodes();let e=0;for(;e<c.length;){const i=c[e++],d=this._ops[i],m=d.node.inputs.map(T=>this._values[T]);if(m.indexOf(void 0)!==-1)throw new Error(`unresolved input detected: op: ${d.node}`);const _=m;a.Logger.verbose("ExecPlan",`Runing op:${d.node.name} (${_.map((T,w)=>`'${d.node.inputs[w]}': ${T.type}[${T.dims.join(",")}]`).join(", ")})`);const b=await this.profiler.event("node",d.node.name,async()=>d.op.impl(h,_,d.op.context));if(b.length!==d.node.outputs.length)throw new Error("the size of output does not match model definition.");b.forEach((T,w)=>{const S=d.node.outputs[w];if(this._values[S])throw new Error(`output [${S}] already has value: op:${d.node.name}`);this._values[S]=T});const y=new Set;b.forEach((T,w)=>{const S=d.node.outputs[w];for(const E of s[S].to){const O=t[E];let v=!0;for(const M of O.inputs)if(!this._values[M]){v=!1;break}v&&y.add(E)}}),c.push(...y)}const r=[];for(let i=0;i<this.graph.getOutputIndices().length;i++){const d=this.graph.getOutputIndices()[i],m=this._values[d];if(m===void 0)throw new Error(`required output [${d}] does not have value`);d===0?await m.getData():m.data,r.push(m)}return a.Logger.verbose("ExecPlan","disposing of inferenceHandler"),h.dispose(),r})}}},7070:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Graph=void 0;const a=o(1446),l=o(7778),p=o(9395),u=o(9162),h=o(2517);var g=p.onnxruntime.experimental.fbs;n.Graph={from:(e,r)=>new t(e,r)};class c{constructor(r){this._from=void 0,this._to=[],this.tensor=void 0,this.type=void 0,r&&(this.type=h.ProtoUtil.tensorValueTypeFromProto(r.type.tensorType))}get from(){return this._from}get to(){return this._to}}class s{constructor(r,i){r instanceof a.onnx.NodeProto?(this.name=r.name,this.opType=r.opType,this.attributes=new l.Attribute(r.attribute)):r instanceof g.Node&&(this.name=i??r.name(),this.opType=r.opType(),this.attributes=new l.Attribute(h.ProtoUtil.tensorAttributesFromORTFormat(r))),this.inputs=[],this.outputs=[],this.executeNode=!0}}class t{constructor(r,i){if(!r)throw new TypeError("graph is empty");this.buildGraph(r),this.transformGraph(i),this.checkIsAcyclic()}getInputIndices(){return this._allInputIndices}getInputNames(){return this._allInputNames}getOutputIndices(){return this._allOutputIndices}getOutputNames(){return this._allOutputNames}getValues(){return this._allData}getNodes(){return this._nodes}buildGraph(r){if(r instanceof a.onnx.GraphProto)this.buildGraphFromOnnxFormat(r);else{if(!(r instanceof g.Graph))throw new TypeError("Graph type is not supported.");this.buildGraphFromOrtFormat(r)}}buildGraphFromOnnxFormat(r){const i=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const d=new Map;if(!r.input)throw new Error("missing information in graph: input");const m=[];for(const _ of r.input){if(i.has(_.name))throw new Error(`duplicated input name: ${_.name}`);const b=this._allData.push(new c(_))-1;i.set(_.name,b),m.push(_.name)}if(!r.initializer)throw new Error("missing information in graph: initializer");for(const _ of r.initializer){let b=i.get(_.name);if(b===void 0){const y=new c;y.type={shape:{dims:h.ProtoUtil.tensorDimsFromProto(_.dims)},tensorType:h.ProtoUtil.tensorDataTypeFromProto(_.dataType)},b=this._allData.push(y)-1,i.set(_.name,b)}this._allData[b]._from=-1,this._allData[b].tensor=u.Tensor.fromProto(_)}for(let _=0;_<this._allData.length;_++)this._allData[_].tensor||(this._allInputIndices.push(_),this._allInputNames.push(m[_]));if(!r.output)throw new Error("missing information in graph: output");for(const _ of r.output){if(i.has(_.name))throw new Error(`duplicated output name: ${_.name}`);const b=this._allData.push(new c(_))-1;i.set(_.name,b),this._allOutputIndices.push(b),this._allOutputNames.push(_.name)}if(!r.node)throw new Error("missing information in graph: node");for(const _ of r.node){if(!_.name)for(let y=0;;y++){const T=`unnamed_${_.opType}_${y}`;if(!d.has(T)){_.name=T;break}}if(d.has(_.name))throw new Error(`duplicated node name: ${_.name}`);const b=this._nodes.push(new s(_))-1;d.set(_.name,b)}for(let _=0;_<this._nodes.length;_++){const b=this._nodes[_],y=r.node[_];if(!y.output)throw new Error(`missing output for node: ${y.name}`);for(const T of y.output){let w=i.get(T);if(w===void 0&&(w=this._allData.push(new c)-1,i.set(T,w)),b.outputs.push(w),this._allData[w]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${w}`);if(this._allData[w]._from=_,y.opType==="Constant"){if(!y.attribute||y.attribute.length!==1||!y.attribute[0].t)throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(!y.output||y.output.length!==1)throw new Error("missing output or incorrect number of outputs for this Constant operator");b.outputs.pop(),b.executeNode=!1,this._allData[w]._from=-1,this._allData[w].tensor=u.Tensor.fromProto(y.attribute[0].t)}}}for(let _=0;_<this._nodes.length;_++){const b=this._nodes[_],y=r.node[_];if(!y.input)throw new Error(`missing input for node: ${y.name}`);for(const T of y.input){const w=i.get(T);if(w===void 0){if(T===""&&y.input.length===3&&y.opType==="Resize")continue;throw new Error(`unrecognized input '${T}' for node: ${y.name}`)}b.inputs.push(w),this._allData[w]._to.push(_)}}return!0}buildGraphFromOrtFormat(r){var i,d,m;const _=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const b=new Map,y=[];for(let T=0;T<r.inputsLength();T++){const w=r.inputs(T);if(_.has(w))throw new Error(`duplicated input name: ${w}`);for(let S=0;S<r.nodeArgsLength();S++)if(((i=r.nodeArgs(S))===null||i===void 0?void 0:i.name())===w){const E=new c;if(((m=(d=r.nodeArgs(S))===null||d===void 0?void 0:d.type())===null||m===void 0?void 0:m.valueType())!==g.TypeInfoValue.tensor_type)throw new Error("Unexpected value type for the nodeArg.");const O=r.nodeArgs(S).type().value(new g.TensorTypeAndShape),v=h.ProtoUtil.tensorDataTypeFromProto(O.elemType()),M=O.shape(),$=[];for(let L=0;L<M.dimLength();L++)$.push(h.LongUtil.longToNumber(M.dim(L).value().dimValue()));E.type={shape:{dims:$},tensorType:v};const D=this._allData.push(E)-1;_.set(w,D),y.push(w)}}for(let T=0;T<r.initializersLength();T++){const w=r.initializers(T);let S=_.get(w.name());if(S===void 0){const E=new c,O=h.ProtoUtil.tensorDimsFromORTFormat(w),v=h.ProtoUtil.tensorDataTypeFromProto(w.dataType());E.type={shape:{dims:O},tensorType:v},S=this._allData.push(E)-1,_.set(w.name(),S)}this._allData[S]._from=-1,this._allData[S].tensor=u.Tensor.fromOrtTensor(w)}for(let T=0;T<this._allData.length;T++)this._allData[T].tensor||(this._allInputIndices.push(T),this._allInputNames.push(y[T]));for(let T=0;T<r.outputsLength();T++){const w=r.outputs(T);if(_.has(w))throw new Error(`duplicated output name: ${w}`);const S=this._allData.push(new c)-1;_.set(w,S),this._allOutputIndices.push(S),this._allOutputNames.push(w)}if(!r.nodes)throw new Error("missing information in graph: node");for(let T=0;T<r.nodesLength();T++){const w=r.nodes(T);let S=w.name();if(!S)for(let O=0;S=`unnamed_${w.opType()}_${O}`,b.has(S);O++);if(b.has(S))throw new Error(`duplicated node name: ${S}`);const E=this._nodes.push(new s(w,S))-1;b.set(S,E)}for(let T=0;T<this._nodes.length;T++){const w=this._nodes[T],S=r.nodes(T);if(S==null)throw new Error(`No node exists at index ${T}`);if((S==null?void 0:S.outputsLength())===0)throw new Error(`missing output for node: ${S.name}`);for(let E=0;E<(S==null?void 0:S.outputsLength());E++){const O=S==null?void 0:S.outputs(E);let v=_.get(O);if(v===void 0&&(v=this._allData.push(new c)-1,_.set(O,v)),w.outputs.push(v),this._allData[v]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${v}`);if(this._allData[v]._from=T,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[v]._from=-1,this._allData[v].tensor=u.Tensor.fromOrtTensor(S.attributes(0).t())}}}for(let T=0;T<this._nodes.length;T++){const w=this._nodes[T],S=r.nodes(T);if(S.inputsLength()===0)throw new Error(`missing input for node: ${S.name}`);for(let E=0;E<S.inputsLength();E++){const O=S.inputs(E),v=_.get(O);if(v===void 0)throw new Error(`unrecognized input '${O}' for node: ${S.name()}`);w.inputs.push(v),this._allData[v]._to.push(T)}}}checkIsAcyclic(){const r=new Set;this._allInputIndices.forEach(m=>{this._allData[m]._to.forEach(_=>{r.add(_)})});const i=Array.from(r),d=new Array(this._nodes.length).fill("white");for(;i.length>0;){const m=i.pop();d[m]==="gray"?d[m]="black":(i.push(m),d[m]="gray",this._nodes[m].outputs.forEach(_=>{const b=this._allData[_];if(b.tensor!==void 0)throw new Error("node outputs should not be initialized");if(b._from!==m)throw new Error("from property of the Value object doesn't match index of Node being processed");b._to.forEach(y=>{if(d[y]==="gray")throw new Error("model graph is cyclic");d[y]==="white"&&i.push(y)})}))}}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 m=this._allData[d]._to.indexOf(i+r);m!==-1&&(this._allData[d]._to[m]=i)}),this._nodes[i].outputs.forEach(d=>{this._allData[d]._from&&this._allData[d]._from===i+r&&(this._allData[d]._from=i)})):(r++,this._nodes[i].outputs.forEach(d=>{this._allData[d]._from=-2}),this._nodes.splice(i,1),i--);r=0;for(let i=0;i<this._allData.length;i++)if(this._allData[i].from!==-2||this._allOutputIndices.indexOf(i+r)!==-1){if(r>0){let d=-1;this._allData[i].from!==void 0&&this._allData[i].from!==-1?(d=this._nodes[this._allData[i].from].outputs.indexOf(i+r),d!==-1&&(this._nodes[this._allData[i].from].outputs[d]=i)):(d=this._allInputIndices.indexOf(i+r),d!==-1&&(this._allInputIndices[d]=i)),this._allData[i].to.forEach(m=>{d=this._nodes[m].inputs.indexOf(i+r),d!==-1&&(this._nodes[m].inputs[d]=i)}),this._allData[i].to.length===0&&(d=this._allOutputIndices.indexOf(i+r),d!==-1&&(this._allOutputIndices[d]=i))}}else r++,this._allData.splice(i,1),i--}deleteNode(r){const i=this._nodes[r];if(i.outputs.length>1){for(let T=1;T<i.outputs.length;T++)if(this._allData[i.outputs[T]].to.length>0)throw new Error("Node deletion with more than one output connected to other nodes is not supported. ")}i.executeNode=!1;const d=i.inputs[0],m=i.outputs[0],_=this._allData[m].to,b=this._allData[d].to.indexOf(r);if(b===-1)throw new Error("The Value object doesn't have the current Node in it's 'to' property ");this._allData[d].to.splice(b,1),this._allData[m]._to=[];const y=this._allOutputIndices.indexOf(m);if(y!==-1&&(this._allOutputIndices[y]=d),_&&_.length>0)for(const T of _){const w=this._nodes[T].inputs.indexOf(m);if(w===-1)throw new Error("The Node object doesn't have the output Value in it's 'inputs' property ");this._nodes[T].inputs[w]=d,this._allData[d].to.push(T)}}removeAllDropoutNodes(){let r=0;for(const i of this._nodes){if(i.opType==="Dropout"){if(i.inputs.length!==1)throw new Error("Dropout nodes should only contain one input. 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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,m,_,b,y){return c.startGraph(t),c.addInitializers(t,e),c.addNodeArgs(t,r),c.addNodes(t,i),c.addMaxNodeIndex(t,d),c.addNodeEdges(t,m),c.addInputs(t,_),c.addOutputs(t,b),c.addSparseInitializers(t,y),c.endGraph(t)}}g.Graph=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsModel(t,e){return(e||new c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsModel(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(t.readInt32(t.position())+t.position(),t)}irVersion(){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}opsetImport(t,e){let r=this.bb.__offset(this.bb_pos,6);return r?(e||new u.experimental.fbs.OperatorSetId).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*t),this.bb):null}opsetImportLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}producerName(t){let e=this.bb.__offset(this.bb_pos,8);return e?this.bb.__string(this.bb_pos+e,t):null}producerVersion(t){let e=this.bb.__offset(this.bb_pos,10);return e?this.bb.__string(this.bb_pos+e,t):null}domain(t){let e=this.bb.__offset(this.bb_pos,12);return e?this.bb.__string(this.bb_pos+e,t):null}modelVersion(){let t=this.bb.__offset(this.bb_pos,14);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}docString(t){let e=this.bb.__offset(this.bb_pos,16);return e?this.bb.__string(this.bb_pos+e,t):null}graph(t){let e=this.bb.__offset(this.bb_pos,18);return e?(t||new u.experimental.fbs.Graph).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}graphDocString(t){let e=this.bb.__offset(this.bb_pos,20);return e?this.bb.__string(this.bb_pos+e,t):null}static startModel(t){t.startObject(9)}static addIrVersion(t,e){t.addFieldInt64(0,e,t.createLong(0,0))}static addOpsetImport(t,e){t.addFieldOffset(1,e,0)}static createOpsetImportVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addOffset(e[r]);return t.endVector()}static startOpsetImportVector(t,e){t.startVector(4,e,4)}static addProducerName(t,e){t.addFieldOffset(2,e,0)}static addProducerVersion(t,e){t.addFieldOffset(3,e,0)}static addDomain(t,e){t.addFieldOffset(4,e,0)}static addModelVersion(t,e){t.addFieldInt64(5,e,t.createLong(0,0))}static addDocString(t,e){t.addFieldOffset(6,e,0)}static addGraph(t,e){t.addFieldOffset(7,e,0)}static addGraphDocString(t,e){t.addFieldOffset(8,e,0)}static endModel(t){return t.endObject()}static createModel(t,e,r,i,d,m,_,b,y,T){return c.startModel(t),c.addIrVersion(t,e),c.addOpsetImport(t,r),c.addProducerName(t,i),c.addProducerVersion(t,d),c.addDomain(t,m),c.addModelVersion(t,_),c.addDocString(t,b),c.addGraph(t,y),c.addGraphDocString(t,T),c.endModel(t)}}g.Model=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsKernelCreateInfos(t,e){return(e||new c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsKernelCreateInfos(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(t.readInt32(t.position())+t.position(),t)}nodeIndices(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.readUint32(this.bb.__vector(this.bb_pos+e)+4*t):0}nodeIndicesLength(){let t=this.bb.__offset(this.bb_pos,4);return t?this.bb.__vector_len(this.bb_pos+t):0}nodeIndicesArray(){let t=this.bb.__offset(this.bb_pos,4);return t?new Uint32Array(this.bb.bytes().buffer,this.bb.bytes().byteOffset+this.bb.__vector(this.bb_pos+t),this.bb.__vector_len(this.bb_pos+t)):null}kernelDefHashes(t){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.readUint64(this.bb.__vector(this.bb_pos+e)+8*t):this.bb.createLong(0,0)}kernelDefHashesLength(){let t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}static startKernelCreateInfos(t){t.startObject(2)}static addNodeIndices(t,e){t.addFieldOffset(0,e,0)}static createNodeIndicesVector(t,e){t.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)t.addInt32(e[r]);return t.endVector()}static startNodeIndicesVector(t,e){t.startVector(4,e,4)}static addKernelDefHashes(t,e){t.addFieldOffset(1,e,0)}static createKernelDefHashesVector(t,e){t.startVector(8,e.length,8);for(let r=e.length-1;r>=0;r--)t.addInt64(e[r]);return t.endVector()}static startKernelDefHashesVector(t,e){t.startVector(8,e,8)}static endKernelCreateInfos(t){return t.endObject()}static createKernelCreateInfos(t,e,r){return c.startKernelCreateInfos(t),c.addNodeIndices(t,e),c.addKernelDefHashes(t,r),c.endKernelCreateInfos(t)}}g.KernelCreateInfos=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsSubGraphSessionState(t,e){return(e||new c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSubGraphSessionState(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(t.readInt32(t.position())+t.position(),t)}graphId(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,t):null}sessionState(t){let e=this.bb.__offset(this.bb_pos,6);return e?(t||new u.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startSubGraphSessionState(t){t.startObject(2)}static addGraphId(t,e){t.addFieldOffset(0,e,0)}static addSessionState(t,e){t.addFieldOffset(1,e,0)}static endSubGraphSessionState(t){let e=t.endObject();return t.requiredField(e,4),e}static createSubGraphSessionState(t,e,r){return c.startSubGraphSessionState(t),c.addGraphId(t,e),c.addSessionState(t,r),c.endSubGraphSessionState(t)}}g.SubGraphSessionState=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{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 c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSessionState(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(t.readInt32(t.position())+t.position(),t)}kernels(t){let e=this.bb.__offset(this.bb_pos,4);return e?(t||new u.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 u.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 c.startSessionState(t),c.addKernels(t,e),c.addSubGraphSessionStates(t,r),c.endSessionState(t)}}g.SessionState=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={})),function(u){(function(h){(function(g){class c{constructor(){this.bb=null,this.bb_pos=0}__init(t,e){return this.bb_pos=t,this.bb=e,this}static getRootAsInferenceSession(t,e){return(e||new c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsInferenceSession(t,e){return t.setPosition(t.position()+a.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(t.readInt32(t.position())+t.position(),t)}static bufferHasIdentifier(t){return t.__has_identifier("ORTM")}ortVersion(t){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,t):null}model(t){let e=this.bb.__offset(this.bb_pos,6);return e?(t||new u.experimental.fbs.Model).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}sessionState(t){let e=this.bb.__offset(this.bb_pos,8);return e?(t||new u.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startInferenceSession(t){t.startObject(3)}static addOrtVersion(t,e){t.addFieldOffset(0,e,0)}static addModel(t,e){t.addFieldOffset(1,e,0)}static addSessionState(t,e){t.addFieldOffset(2,e,0)}static endInferenceSession(t){return t.endObject()}static finishInferenceSessionBuffer(t,e){t.finish(e,"ORTM")}static finishSizePrefixedInferenceSessionBuffer(t,e){t.finish(e,"ORTM",!0)}static createInferenceSession(t,e,r,i){return c.startInferenceSession(t),c.addOrtVersion(t,e),c.addModel(t,r),c.addSessionState(t,i),c.endInferenceSession(t)}}g.InferenceSession=c})(h.fbs||(h.fbs={}))})(u.experimental||(u.experimental={}))}(n.onnxruntime||(n.onnxruntime={}))},7448:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.OnnxjsSessionHandler=void 0;const a=o(1670),l=o(9162);n.OnnxjsSessionHandler=class{constructor(p){this.session=p,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(p,u,h){const g=new Map;for(const t in p)if(Object.hasOwnProperty.call(p,t)){const e=p[t];g.set(t,new l.Tensor(e.dims,e.type,void 0,void 0,e.data))}const c=await this.session.run(g),s={};return c.forEach((t,e)=>{s[e]=new a.Tensor(t.type,t.data,t.dims)}),s}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(f,n,o)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.Session=void 0;const a=o(7067),l=o(1296),p=o(7091),u=o(1036),h=o(6231),g=o(2644);n.Session=class{constructor(c={}){this._initialized=!1,this.backendHint=c.backendHint,this.profiler=h.Profiler.create(c.profiler),this.context={profiler:this.profiler,graphInputTypes:[],graphInputDims:[]}}get inputNames(){return this._model.graph.getInputNames()}get outputNames(){return this._model.graph.getOutputNames()}startProfiling(){this.profiler.start()}endProfiling(){this.profiler.stop()}async loadModel(c,s,t){await this.profiler.event("session","Session.loadModel",async()=>{const e=await(0,p.resolveBackend)(this.backendHint);if(this.sessionHandler=e.createSessionHandler(this.context),this._model=new g.Model,typeof c=="string"){const r=c.endsWith(".ort");if(typeof fetch>"u"){const i=await(0,l.promisify)(a.readFile)(c);this.initialize(i,r)}else{const i=await fetch(c),d=await i.arrayBuffer();this.initialize(new Uint8Array(d),r)}}else if(ArrayBuffer.isView(c))this.initialize(c);else{const r=new Uint8Array(c,s||0,t||c.byteLength);this.initialize(r)}})}initialize(c,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(c,t,s),this.sessionHandler.onGraphInitialized&&this.sessionHandler.onGraphInitialized(this._model.graph),this.initializeOps(this._model.graph),this._executionPlan=new u.ExecutionPlan(this._model.graph,this._ops,this.profiler)}),this._initialized=!0}async run(c){if(!this._initialized)throw new Error("session not initialized yet");return this.profiler.event("session","Session.run",async()=>{const s=this.normalizeAndValidateInputs(c),t=await this._executionPlan.execute(this.sessionHandler,s);return this.createOutput(t)})}normalizeAndValidateInputs(c){const s=this._model.graph.getInputNames();if(Array.isArray(c)){if(c.length!==s.length)throw new Error(`incorrect input array length: expected ${s.length} but got ${c.length}`)}else{if(c.size!==s.length)throw new Error(`incorrect input map size: expected ${s.length} but got ${c.size}`);const t=new Array(c.size);let e=0;for(let r=0;r<s.length;++r){const i=c.get(s[r]);if(!i)throw new Error(`missing input tensor for: '${name}'`);t[e++]=i}c=t}if(this.context.graphInputTypes&&this.context.graphInputTypes.length!==0&&this.context.graphInputDims&&this.context.graphInputDims.length!==0)this.validateInputTensorDims(this.context.graphInputDims,c,!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(c[i].dims)}this.validateInputTensorDims(r,c,!0)}return this.validateInputTensorTypes(this.context.graphInputTypes,c),c}validateInputTensorTypes(c,s){for(let t=0;t<s.length;t++){const e=c[t],r=s[t].type;if(e!==r)throw new Error(`input tensor[${t}] check failed: expected type '${e}' but got ${r}`)}}validateInputTensorDims(c,s,t){for(let e=0;e<s.length;e++){const r=c[e],i=s[e].dims;if(!this.compareTensorDims(r,i,t))throw new Error(`input tensor[${e}] check failed: expected shape '[${r.join(",")}]' but got [${i.join(",")}]`)}}compareTensorDims(c,s,t){if(c.length!==s.length)return!1;for(let e=0;e<c.length;++e)if(c[e]!==s[e]&&(!t||c[e]!==0))return!1;return!0}createOutput(c){const s=this._model.graph.getOutputNames();if(c.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],c[e]);return t}initializeOps(c){const s=c.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,c)}}},9162:function(f,n,o){var a=this&&this.__importDefault||function(d){return d&&d.__esModule?d:{default:d}};Object.defineProperty(n,"__esModule",{value:!0}),n.Tensor=void 0;const l=o(3442),p=a(o(3720)),u=o(1446),h=o(9395),g=o(2517);var c=h.onnxruntime.experimental.fbs;class s{get data(){if(this.cache===void 0){const m=this.dataProvider(this.dataId);if(m.length!==this.size)throw new Error("Length of data provided by the Data Provider is inconsistent with the dims of this Tensor.");this.cache=m}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(m){return this.data[g.ShapeUtil.indicesToOffset(m,this.strides)]}set(m,_){this.data[g.ShapeUtil.indicesToOffset(m,this.strides)]=_}async getData(){return this.cache===void 0&&(this.cache=await this.asyncDataProvider(this.dataId)),this.cache}get strides(){return this._strides||(this._strides=g.ShapeUtil.computeStrides(this.dims)),this._strides}constructor(m,_,b,y,T,w=l.Guid.create()){this.dims=m,this.type=_,this.dataProvider=b,this.asyncDataProvider=y,this.cache=T,this.dataId=w,this.size=g.ShapeUtil.validateDimsAndCalcSize(m);const S=this.size,E=b===void 0&&y===void 0&&T===void 0;if(T!==void 0&&T.length!==S)throw new RangeError("Input dims doesn't match data length.");if(_==="string"){if(!(T===void 0||Array.isArray(T)&&T.every(O=>typeof O=="string")))throw new TypeError("cache should be a string array");E&&(this.cache=new Array(S))}else{if(T!==void 0){const O=e(_);if(!(T instanceof O))throw new TypeError(`cache should be type ${O.name}`)}if(E){const O=new ArrayBuffer(S*function(v){switch(v){case"bool":case"int8":case"uint8":return 1;case"int16":case"uint16":return 2;case"int32":case"uint32":case"float32":return 4;case"float64":return 8;default:throw new Error(`cannot calculate sizeof() on type ${v}`)}}(_));this.cache=function(v,M){return new(e(M))(v)}(O,_)}}}static fromProto(m){if(!m)throw new Error("cannot construct Value from an empty tensor");const _=g.ProtoUtil.tensorDataTypeFromProto(m.dataType),b=g.ProtoUtil.tensorDimsFromProto(m.dims),y=new s(b,_);if(_==="string")m.stringData.forEach((T,w)=>{y.data[w]=(0,g.decodeUtf8String)(T)});else if(m.rawData&&typeof m.rawData.byteLength=="number"&&m.rawData.byteLength>0){const T=y.data,w=new DataView(m.rawData.buffer,m.rawData.byteOffset,m.rawData.byteLength),S=t(m.dataType),E=m.rawData.byteLength/S;if(m.rawData.byteLength%S!=0)throw new Error("invalid buffer length");if(T.length!==E)throw new Error("buffer length mismatch");for(let O=0;O<E;O++){const v=i(w,m.dataType,O*S);T[O]=v}}else{let T;switch(m.dataType){case u.onnx.TensorProto.DataType.FLOAT:T=m.floatData;break;case u.onnx.TensorProto.DataType.INT32:case u.onnx.TensorProto.DataType.INT16:case u.onnx.TensorProto.DataType.UINT16:case u.onnx.TensorProto.DataType.INT8:case u.onnx.TensorProto.DataType.UINT8:case u.onnx.TensorProto.DataType.BOOL:T=m.int32Data;break;case u.onnx.TensorProto.DataType.INT64:T=m.int64Data;break;case u.onnx.TensorProto.DataType.DOUBLE:T=m.doubleData;break;case u.onnx.TensorProto.DataType.UINT32:case u.onnx.TensorProto.DataType.UINT64:T=m.uint64Data;break;default:throw new Error("unspecific error")}if(T==null)throw new Error("failed to populate data from a tensorproto value");const w=y.data;if(w.length!==T.length)throw new Error("array length mismatch");for(let S=0;S<T.length;S++){const E=T[S];p.default.isLong(E)?w[S]=r(E,m.dataType):w[S]=E}}return y}static fromData(m,_,b){return new s(_,b,void 0,void 0,m)}static fromOrtTensor(m){if(!m)throw new Error("cannot construct Value from an empty tensor");const _=g.ProtoUtil.tensorDimsFromORTFormat(m),b=g.ProtoUtil.tensorDataTypeFromProto(m.dataType()),y=new s(_,b);if(b==="string")for(let T=0;T<m.stringDataLength();T++)y.data[T]=m.stringData(T);else if(m.rawDataArray()&&typeof m.rawDataLength()=="number"&&m.rawDataLength()>0){const T=y.data,w=new DataView(m.rawDataArray().buffer,m.rawDataArray().byteOffset,m.rawDataLength()),S=t(m.dataType()),E=m.rawDataLength()/S;if(m.rawDataLength()%S!=0)throw new Error("invalid buffer length");if(T.length!==E)throw new Error("buffer length mismatch");for(let O=0;O<E;O++){const v=i(w,m.dataType(),O*S);T[O]=v}}return y}}function t(d){switch(d){case u.onnx.TensorProto.DataType.UINT8:case u.onnx.TensorProto.DataType.INT8:case u.onnx.TensorProto.DataType.BOOL:return 1;case u.onnx.TensorProto.DataType.UINT16:case u.onnx.TensorProto.DataType.INT16:return 2;case u.onnx.TensorProto.DataType.FLOAT:case u.onnx.TensorProto.DataType.INT32:case u.onnx.TensorProto.DataType.UINT32:return 4;case u.onnx.TensorProto.DataType.INT64:case u.onnx.TensorProto.DataType.DOUBLE:case u.onnx.TensorProto.DataType.UINT64:return 8;default:throw new Error(`cannot calculate sizeof() on type ${u.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,m){if(m===u.onnx.TensorProto.DataType.INT64||m===c.TensorDataType.INT64){if(d.greaterThanOrEqual(2147483648)||d.lessThan(-2147483648))throw new TypeError("int64 is not supported")}else{if(m!==u.onnx.TensorProto.DataType.UINT32&&m!==c.TensorDataType.UINT32&&m!==u.onnx.TensorProto.DataType.UINT64&&m!==c.TensorDataType.UINT64)throw new TypeError(`not a LONG type: ${u.onnx.TensorProto.DataType[m]}`);if(d.greaterThanOrEqual(4294967296)||d.lessThan(0))throw new TypeError("uint64 is not supported")}return d.toNumber()}function i(d,m,_){switch(m){case u.onnx.TensorProto.DataType.BOOL:case u.onnx.TensorProto.DataType.UINT8:return d.getUint8(_);case u.onnx.TensorProto.DataType.INT8:return d.getInt8(_);case u.onnx.TensorProto.DataType.UINT16:return d.getUint16(_,!0);case u.onnx.TensorProto.DataType.INT16:return d.getInt16(_,!0);case u.onnx.TensorProto.DataType.FLOAT:return d.getFloat32(_,!0);case u.onnx.TensorProto.DataType.INT32:return d.getInt32(_,!0);case u.onnx.TensorProto.DataType.UINT32:return d.getUint32(_,!0);case u.onnx.TensorProto.DataType.INT64:return r(p.default.fromBits(d.getUint32(_,!0),d.getUint32(_+4,!0),!1),m);case u.onnx.TensorProto.DataType.DOUBLE:return d.getFloat64(_,!0);case u.onnx.TensorProto.DataType.UINT64:return r(p.default.fromBits(d.getUint32(_,!0),d.getUint32(_+4,!0),!0),m);default:throw new Error(`cannot read from DataView for type ${u.onnx.TensorProto.DataType[m]}`)}}n.Tensor=s},2517:function(f,n,o){var a=this&&this.__importDefault||function(m){return m&&m.__esModule?m:{default:m}};Object.defineProperty(n,"__esModule",{value:!0}),n.decodeUtf8String=n.MAX_CLIP=n.MIN_CLIP=n.PoolConvUtil=n.ReduceUtil=n.SplitUtil=n.MathUtil=n.ShapeUtil=n.LongUtil=n.ProtoUtil=n.GemmUtil=n.arrayCopyHelper=n.BroadcastUtil=n.MatMulUtil=n.ArrayUtil=n.assert=n.checkInputsShape=void 0;const l=o(5686),p=a(o(3720)),u=o(1446),h=o(9162);n.checkInputsShape=function(m,..._){if(!m||m.length!==_.length)return!1;for(let b=0;b<m.length;b++)if(!m[b].dims||m[b].dims.length!==_[b])return!1;return!0},n.assert=function(m,_){if(!m)throw new Error(typeof _=="string"?_:_())},n.ArrayUtil=class{static arraysEqual(m,_){if(m.length!==_.length)return!1;for(let b=0;b<m.length;b++)if(m[b]!==_[b])return!1;return!0}};class g{static preprocessInputShapes(_,b){return[_.length===1?[1,_[0]]:_,b.length===1?[b[0],1]:b]}static postprocessOutputShape(_,b,y){b===1&&_.splice(_.length-2,1),y===1&&_.pop()}static calcMatMulShape(_,b){return _[1]!==b[0]?void 0:[_[0],b[1]]}}n.MatMulUtil=g;class c{static calcShape(_,b,y=!1){const T=_.length,w=b.length;if(T===0)return b;if(w===0)return _;const S=Math.max(_.length,b.length),E=new Array(S);if(y){if(T<2||w<2)return;const O=g.calcMatMulShape([_[T-2],_[T-1]],[b[w-2],b[w-1]]);if(O===void 0)return;[E[S-2],E[S-1]]=O}for(let O=y?3:1;O<=S;O++){const v=T-O<0?1:_[T-O],M=w-O<0?1:b[w-O];if(v!==M&&v>1&&M>1)return;E[S-O]=Math.max(v,M)}return E}static index(_,b){const y=new Array(b.length);return c.fillIndex(_,b,y),y}static fillIndex(_,b,y){const T=_.length-b.length;for(let w=0;w<b.length;w++)y[w]=_[T+w]%b[w]}static calc(_,b,y,T,w){const S=c.calcShape(_.dims,b.dims);if(S){if(T&&!e.areEqual(S,_.dims))return;const E=e.size(S),O=T?_:new h.Tensor(S,w||_.type);if(S.length===0)O.set([],y(_.get([]),b.get([])));else{const v=new Array(S.length),M=new Array(_.dims.length),$=new Array(b.dims.length);let D,L=0,C=0,U=!1,N=!1;_.dims.length===0&&(L=_.get([]),U=!0),b.dims.length===0&&(C=b.get([]),N=!0);for(let j=0;j<E;j++){D=j;for(let J=S.length-1;J>=0;J--)v[J]=D%S[J],D=Math.floor(D/S[J]);U||(c.fillIndex(v,_.dims,M),L=_.get(M)),N||(c.fillIndex(v,b.dims,$),C=b.get($)),O.set(v,y(L,C))}}return O}}static isValidBroadcast(_,b){const y=_.length,T=b.length;if(y>T)return!1;for(let w=1;w<=y;w++)if(_[y-w]!==1&&_[y-w]!==b[T-w])return!1;return!0}static getBroadcastDims(_,b){const y=_.length,T=[];for(let w=0;w<y;w++){const S=y-1-w,E=_[S]||1;(b[b.length-1-w]||1)>1&&E===1&&T.unshift(S)}return T}}n.BroadcastUtil=c,n.arrayCopyHelper=function(m,_,b,y,T){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=m.length)throw new Error("targetIndex out of bounds");if(y+T>_.length)throw new Error("source indices to be copied are outside bounds");if(b+T>m.length)throw new Error("target array is too small to hold result");for(let w=0;w<T;w++)m[b+w]=_[y+w]},n.GemmUtil=class{static getShapeOfGemmResult(m,_,b,y,T){if(m.length!==2||b.length!==2)throw new Error("shape need to be of size 2");let w,S,E;_?(w=m[1],S=m[0]):(w=m[0],S=m[1]);let O=-1;if(y?(E=b[0],O=1):(E=b[1],O=0),b[O]!==S)throw new Error("dimension mismatch");if(w<=0||E<=0||S<=0)throw new Error("invalid shape specified");if(T&&!c.isValidBroadcast(T,[w,E]))throw new Error("gemm: invalid bias shape for broadcast");return[w,E,S]}};class s{static tensorDataTypeFromProto(_){switch(_){case u.onnx.TensorProto.DataType.INT8:return"int8";case u.onnx.TensorProto.DataType.UINT8:return"uint8";case u.onnx.TensorProto.DataType.BOOL:return"bool";case u.onnx.TensorProto.DataType.INT16:return"int16";case u.onnx.TensorProto.DataType.UINT16:return"uint16";case u.onnx.TensorProto.DataType.INT32:return"int32";case u.onnx.TensorProto.DataType.UINT32:return"uint32";case u.onnx.TensorProto.DataType.FLOAT:return"float32";case u.onnx.TensorProto.DataType.DOUBLE:return"float64";case u.onnx.TensorProto.DataType.STRING:return"string";case u.onnx.TensorProto.DataType.INT64:return"int32";case u.onnx.TensorProto.DataType.UINT64:return"uint32";default:throw new Error(`unsupported data type: ${u.onnx.TensorProto.DataType[_]}`)}}static tensorDataTypeStringToEnum(_){switch(_){case"int8":return u.onnx.TensorProto.DataType.INT8;case"uint8":return u.onnx.TensorProto.DataType.UINT8;case"bool":return u.onnx.TensorProto.DataType.BOOL;case"int16":return u.onnx.TensorProto.DataType.INT16;case"uint16":return u.onnx.TensorProto.DataType.UINT16;case"int32":return u.onnx.TensorProto.DataType.INT32;case"uint32":return u.onnx.TensorProto.DataType.UINT32;case"float32":return u.onnx.TensorProto.DataType.FLOAT;case"float64":return u.onnx.TensorProto.DataType.DOUBLE;case"string":return u.onnx.TensorProto.DataType.STRING;case"int64":return u.onnx.TensorProto.DataType.INT64;case"uint64":return u.onnx.TensorProto.DataType.UINT64;default:throw new Error(`unsupported data type: ${_}`)}}static tensorDimsFromProto(_){return _.map(b=>p.default.isLong(b)?b.toNumber():b)}static tensorValueTypeFromProto(_){return{tensorType:s.tensorDataTypeFromProto(_.elemType),shape:{dims:s.tensorDimsFromProto(_.shape.dim.map(b=>b.dimValue))}}}static tensorDimsFromORTFormat(_){const b=[];for(let y=0;y<_.dimsLength();y++)b.push(t.longToNumber(_.dims(y)));return b}static tensorAttributesFromORTFormat(_){const b=[];for(let y=0;y<_.attributesLength();y++)b.push(_.attributes(y));return b}}n.ProtoUtil=s;class t{static longToNumber(_,b){return p.default.isLong(_)?_.toNumber():_ instanceof l.flatbuffers.Long?p.default.fromValue({low:_.low,high:_.high,unsigned:b!=null&&b}).toNumber():_}static isLong(_){return p.default.isLong(_)||_ instanceof l.flatbuffers.Long}}n.LongUtil=t;class e{static size(_){return e.getSizeFromDimensionRange(_,0,_.length)}static sizeFromDimension(_,b){if(b<0||b>_.length)throw new Error(`invalid dimension of ${b} for sizeFromDimension as Tensor has ${_.length} dimensions.`);return e.getSizeFromDimensionRange(_,b,_.length)}static sizeToDimension(_,b){if(b<0||b>_.length)throw new Error(`invalid dimension of ${b} for sizeToDimension as Tensor has ${_.length} dimensions.`);return e.getSizeFromDimensionRange(_,0,b)}static getSizeFromDimensionRange(_,b,y){let T=1;for(let w=b;w<y;w++){if(_[w]<=0)throw new Error("cannot get valid size from specified dimension range. Most likely the range contains 0 or negative values in them.");T*=_[w]}return T}static computeStrides(_){const b=_.length;if(b===0)return[];if(b===1)return[1];const y=new Array(b);y[b-1]=1,y[b-2]=_[b-1];for(let T=b-3;T>=0;--T)y[T]=y[T+1]*_[T+1];return y}static transpose(_){return _.slice().reverse()}static indicesToOffset(_,b,y){y===void 0&&(y=_.length);let T=0;for(let w=0;w<y;++w)T+=b[w]*_[w];return T}static offsetToIndices(_,b){const y=b.length;if(y===0)return[];if(y===1)return[_*b[0]];const T=new Array(b.length);for(let w=0;w<T.length-1;++w)T[w]=Math.floor(_/b[w]),_-=T[w]*b[w];return T[T.length-1]=_,T}static normalizeAxis(_,b){if(_<-b&&_>=b)throw new Error("unsupported axis for this operation.");return _<0?_+b:_}static normalizeAxes(_,b){return _.map(y=>this.normalizeAxis(y,b))}static incrementIndex(_,b,y){if(b.length===0||_.length===0)throw new Error("Index incrementing unsupported for scalar Tensor");if(y===void 0)y=b.length;else if(y<=0||y>b.length)throw new Error("Incorrect axis to increment on");for(let T=y-1;T>=0&&(_[T]++,!(_[T]<b[T]));--T)_[T]=0}static calculateReshapedDims(_,b){if(b.length===0){if(_.length===0||e.size(_)===1)return[];throw new Error("cannot reshape to a scalar Tensor")}const y=b.length,T=new Array(y);let w=-1,S=1;for(let O=0;O<y;O++){if(b[O]<-1)throw new Error("a dimension in shape hints cannot be less than -1");if(b[O]===-1){if(w!==-1)throw new Error("at most one dimension in shape hints can be -1");w=O}else{if(b[O]===0){if(O>=_.length)throw new Error("the dimension with value zero exceeds the dimension size of the input tensor");T[O]=_[O]}else T[O]=b[O];S*=T[O]}}const E=e.size(_);if(w!==-1){if(E%S!=0)throw new Error(`the input tensor cannot be reshaped to the requested shape. Input shape: [${_}] Output shape: [${b}]`);T[w]=E/S}else if(S!==E)throw new Error("reshapedDims and originalDims don't have matching sizes");return T}static sortBasedOnPerm(_,b){return b?b.map(y=>_[y]):_.slice().reverse()}static padShape(_,b){const y=_.length;return _.map((T,w)=>T+b[w]+b[w+y])}static areEqual(_,b){return _.length===b.length&&_.every((y,T)=>y===b[T])}static validateDimsAndCalcSize(_){if(_.length>6)throw new TypeError("Only rank 0 to 6 is supported for tensor shape.");let b=1;for(const y of _){if(!Number.isInteger(y))throw new TypeError(`Invalid shape: ${y} is not an integer`);if(y<0||y>2147483647)throw new TypeError(`Invalid shape: length ${y} is not allowed`);b*=y}return b}static flattenShape(_,b){b<0&&(b+=_.length);const y=_.reduce((w,S)=>w*S,1),T=_.slice(b).reduce((w,S)=>w*S,1);return[y/T,T]}static squeezeShape(_,b){const y=new Array;b=e.normalizeAxes(b,_.length);for(let T=0;T<_.length;T++){const w=b.indexOf(T)>=0;if(w&&_[T]!==1)throw new Error("squeeze an axis of size different than 1");(b.length===0&&_[T]>1||b.length>0&&!w)&&y.push(_[T])}return y}static unsqueezeShape(_,b){const y=new Array(_.length+b.length);y.fill(0);for(let w=0;w<b.length;w++){const S=e.normalizeAxis(b[w],y.length);if(S>=y.length)throw new Error("'axes' has an out of range axis");if(y[S]!==0)throw new Error("'axes' has a duplicate axis");y[S]=1}let T=0;for(let w=0;w<y.length;w++)y[w]===0&&(y[w]=_[T++]);if(T!==_.length)throw new Error("the unsqueezed dimension could not be established");return y}}n.ShapeUtil=e,n.MathUtil=class{static sqr(m,_,b,y,T){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=m.length)throw new Error("targetIndex out of bounds");if(y+T>_.length)throw new Error("source indices to be copied are outside bounds");if(b+T>m.length)throw new Error("target array is too small to hold result");for(let w=0;w<T;w++)m[b+w]+=Math.pow(_[y+w],2)}static axpy(m,_,b,y,T,w){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=m.length)throw new Error("targetIndex out of bounds");if(y+T>_.length)throw new Error("source indices to be copied are outside bounds");if(b+T>m.length)throw new Error("target array is too small to hold result");for(let S=0;S<T;S++)m[b+S]+=w*_[y+S]}static powx(m,_,b,y,T,w){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=m.length)throw new Error("targetIndex out of bounds");if(y+T>_.length)throw new Error("source indices to be copied are outside bounds");if(b+T>m.length)throw new Error("target array is too small to hold result");for(let S=0;S<T;S++)m[b+S]=Math.pow(_[y+S],w)}static mul(m,_,b,y,T){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=m.length)throw new Error("targetIndex out of bounds");if(y+T>_.length)throw new Error("source indices to be copied are outside bounds");if(b+T>m.length)throw new Error("target array is too small to hold result");for(let w=0;w<T;w++)m[b+w]=_[y+w]*m[b+w]}};class r{static splitShape(_,b,y,T){if(y.length===0){if(!T)throw new Error("need to know number of outputs when the 'split' attribute is not specified");r.determineSplit(_[b],T,y)}const w=[],S=[0];for(let E=0;E<y.length;++E){E!==0&&S.push(S[E-1]+y[E-1]);const O=_.slice();O[b]=y[E],w.push(O)}return[w,S]}static determineSplit(_,b,y){if(_%b!=0)throw new Error("cannot split tensor to equal sized parts");for(let T=0;T<b;++T)y.push(_/b)}}n.SplitUtil=r;class i{static calcReduce(_,b,y,T,w){const S=_.dims.slice(0);b.length===0&&S.forEach((L,C)=>b.push(C));const E=i.calcReduceShape(S,b,!0),O=e.size(E),v=new h.Tensor(E,_.type),M=e.computeStrides(E),$=e.computeStrides(S),D=new Array(S.length);for(let L=0;L<O;L++){const C=e.offsetToIndices(L,M);c.fillIndex(C,S,D),v.set(C,i.calcReduceByAxis(_.numberData,b,S,0,e.indicesToOffset(D,$),T,w))}return y?v:new h.Tensor(i.calcReduceShape(S,b,y),v.type,void 0,void 0,v.data,v.dataId)}static calcReduceByAxis(_,b,y,T,w,S,E){let O=0;if(T>=b.length)return S(_[w]);const v=b[T],M=v>=y.length?1:e.size(y.slice(v+1));for(let $=0;$<y[v];$++)O=$===0?i.calcReduceByAxis(_,b,y,T+1,w,S,E):E(O,i.calcReduceByAxis(_,b,y,T+1,w,S,E)),w+=M;return O}static calcReduceShape(_,b,y){const T=_.slice();for(let w=0;w<b.length;w++)T[b[w]]=y?1:0;return T.filter(w=>w!==0)}}n.ReduceUtil=i;class d{static adjustPoolAttributes(_,b,y,T,w,S){if(!_&&y.length!==b.length-2)throw new Error("length of specified kernel shapes should be 2 less than length of input dimensions");if(_)for(let E=0;E<b.length-2;E++)E>=y.length?y.push(b[E+2]):y[E]=b[E+2];for(let E=0;E<y.length;E++)if(E<T.length){if(T[E]<0)throw new Error("strides should be greater than or equal to 1")}else T.push(1);for(let E=0;E<y.length;E++)if(E<w.length){if(w[E]<0)throw new Error("dilations should be greater than or equal to 1")}else w.push(1);for(let E=0;E<2*y.length;E++)if(E<S.length){if(S[E]<0)throw new Error("pad should be greater than or equal to 1")}else S.push(0);for(let E=0;E<y.length;E++){if(y[E]<=0)throw new Error("kernel shapes need to be greater than 0");if(S[E]>=y[E]||S[E+y.length]>=y[E])throw new Error("pads should be smaller than kernel")}}static adjustPadsBasedOnAutoPad(_,b,y,T,w,S){if(S){if(w.length!==2*(_.length-2))throw new Error("length of pads should be twice the length of data dimensions");if(b.length!==_.length-2)throw new Error("length of strides should be the length of data dimensions");if(T.length!==_.length-2)throw new Error("length of kernel shapes should be the length of data dimensions");for(let E=0;E<_.length-2;E++)d.adjustPadAndReturnShape(_[E+2],b[E],y[E],T[E],w,E,E+_.length-2,S)}}static computePoolOutputShape(_,b,y,T,w,S,E){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(_,b,O,y,T,w,S,E),O}static computeConvOutputShape(_,b,y,T,w,S,E){if(_.length<=0||b.length<=0)throw new Error("invalid input tensor dims or invalid filter tensor dims");const O=[_[0],b[0]];return d.computeShapeHelper(!1,_,O,y,T,w,S,E),O}static computeShapeHelper(_,b,y,T,w,S,E,O){if(_)for(let v=0;v<b.length-2;v++)y.push(1);else for(let v=0;v<b.length-2;v++)y.push(d.adjustPadAndReturnShape(b[v+2],T[v],w[v],S[v],E,v,v+b.length-2,O))}static adjustPadAndReturnShape(_,b,y,T,w,S,E,O){const v=y*(T-1)+1;if(!O||O==="NOTSET")return Math.floor((_+w[S]+w[E]-v)/b+1);switch(O){case"VALID":return w[S]=0,w[E]=0,Math.floor((_-v)/b+1);case"SAME_LOWER":case"SAME_UPPER":if(y!==1)throw new Error("Dilation not supported for SAME_UPPER or SAME_LOWER");{const M=((_+b-1)/b-1)*b+T-_;return w[S]=Math.floor(O==="SAME_LOWER"?(M+1)/2:M/2),w[E]=M-w[S],Math.floor((_+M-T)/b+1)}default:throw new Error("Unsupported AutoPad type")}}}n.PoolConvUtil=d,n.MIN_CLIP=-34028234663852886e22,n.MAX_CLIP=34028234663852886e22,n.decodeUtf8String=function(m){return new TextDecoder().decode(m)}},7967:(f,n)=>{Object.defineProperty(n,"__esModule",{value:!0}),n.iterateExtraOptions=void 0,n.iterateExtraOptions=(o,a,l,p)=>{if(typeof 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env$1={backends:{onnx:onnx_env,tfjs:{}},__dirname,version:VERSION,allowRemoteModels:!0,remoteHost:"https://huggingface.co/",remotePathTemplate:"{model}/resolve/{revision}/",allowLocalModels:!0,localModelPath,useFS:FS_AVAILABLE,useBrowserCache:WEB_CACHE_AVAILABLE,useFSCache:FS_AVAILABLE,cacheDir:DEFAULT_CACHE_DIR,useCustomCache:!1,customCache:null};function isEmpty(f){return Object.keys(f).length===0}globalThis.ReadableStream||(globalThis.ReadableStream=sharp.ReadableStream);class FileResponse{constructor(n){Z(this,"_CONTENT_TYPE_MAP",{txt:"text/plain",html:"text/html",css:"text/css",js:"text/javascript",json:"application/json",png:"image/png",jpg:"image/jpeg",jpeg:"image/jpeg",gif:"image/gif"});if(this.filePath=n,this.headers=new Headers,this.exists=sharp.existsSync(n),this.exists){this.status=200,this.statusText="OK";let o=sharp.statSync(n);this.headers.set("content-length",o.size.toString()),this.updateContentType();let a=this;this.body=new ReadableStream({start(l){a.arrayBuffer().then(p=>{l.enqueue(new Uint8Array(p)),l.close()})}})}else this.status=404,this.statusText="Not Found",this.body=null}updateContentType(){const n=this.filePath.toString().split(".").pop().toLowerCase();this.headers.set("content-type",this._CONTENT_TYPE_MAP[n]??"application/octet-stream")}clone(){let n=new FileResponse(this.filePath);return n.exists=this.exists,n.status=this.status,n.statusText=this.statusText,n.headers=new Headers(this.headers),n}async arrayBuffer(){return(await sharp.promises.readFile(this.filePath)).buffer}async blob(){const n=await sharp.promises.readFile(this.filePath);return new Blob([n],{type:this.headers.get("content-type")})}async text(){return await sharp.promises.readFile(this.filePath,"utf8")}async json(){return JSON.parse(await this.text())}}function isValidHttpUrl(f,n=null){let o;try{o=new URL(f)}catch{return!1}return n&&!n.includes(o.hostname)?!1:o.protocol==="http:"||o.protocol==="https:"}async function 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Will expand buffer when needed.");let a=parseInt(o??"0"),l=new Uint8Array(a),p=0;const u=f.body.getReader();async function h(){const{done:g,value:c}=await u.read();if(g)return;let s=p+c.length;if(s>a){a=s;let e=new Uint8Array(a);e.set(l),l=e}l.set(c,p),p=s;const t=p/a*100;return n({progress:t,loaded:p,total:a}),h()}return await h(),l}function pathJoin(...f){return f=f.map((n,o)=>(o&&(n=n.replace(new RegExp("^/"),"")),o!==f.length-1&&(n=n.replace(new RegExp("/$"),"")),n)),f.join("/")}function transpose_data(f,n,o){const a=new Array(o.length),l=new Array(o.length);for(let h=o.length-1,g=1;h>=0;--h)l[h]=g,a[h]=n[o[h]],g*=a[h];const p=o.map((h,g)=>l[o.indexOf(g)]),u=new f.constructor(f.length);for(let h=0;h<f.length;++h){let g=0;for(let c=n.length-1,s=h;c>=0;--c)g+=s%n[c]*p[c],s=Math.floor(s/n[c]);u[g]=f[h]}return[u,a]}function softmax(f){const n=max(f)[0],o=f.map(p=>Math.exp(p-n)),a=o.reduce((p,u)=>p+u,0);return o.map(p=>p/a)}function log_softmax(f){return softmax(f).map(a=>Math.log(a))}function getTopItems(f,n=0){return f=Array.from(f).map((o,a)=>[a,o]).sort((o,a)=>a[1]-o[1]),n!==null&&n>0&&(f=f.slice(0,n)),f}function min(f){if(f.length===0)throw Error("Array must not be empty");let n=f[0],o=0;for(let a=1;a<f.length;++a)f[a]<n&&(n=f[a],o=a);return[n,o]}function max(f){if(f.length===0)throw Error("Array must not be empty");let n=f[0],o=0;for(let a=1;a<f.length;++a)f[a]>n&&(n=f[a],o=a);return[Number(n),o]}function medianFilter(f,n){if(n%2===0||n<=0)throw new Error("Window size must be a positive odd number");const o=new f.constructor(f.length),a=new f.constructor(n),l=Math.floor(n/2);for(let p=0;p<f.length;++p){let u=0;for(let h=-l;h<=l;++h){let g=p+h;g<0?g=Math.abs(g):g>=f.length&&(g=2*(f.length-1)-g),a[u++]=f[g]}a.sort(),o[p]=a[l]}return o}function round(f,n){const o=Math.pow(10,n);return Math.round(f*o)/o}const DataTypeMap=Object.freeze({float32:Float32Array,float64:Float64Array,string:Array,int8:Int8Array,uint8:Uint8Array,int16:Int16Array,uint16:Uint16Array,int32:Int32Array,uint32:Uint32Array,int64:BigInt64Array,uint64:BigUint64Array,bool:Uint8Array}),ONNXTensor$1=ONNX.Tensor;class Tensor{constructor(...n){Z(this,"dims");Z(this,"type");Z(this,"data");Z(this,"size");return n[0]instanceof ONNXTensor$1?Object.assign(this,n[0]):Object.assign(this,new ONNXTensor$1(n[0],n[1],n[2])),new Proxy(this,{get:(o,a)=>{if(typeof a=="string"){let l=Number(a);if(Number.isInteger(l))return o._getitem(l)}return o[a]},set:(o,a,l)=>o[a]=l})}*[Symbol.iterator](){const[n,...o]=this.dims;if(o.length>0){const a=o.reduce((l,p)=>l*p);for(let l=0;l<n;++l)yield this._subarray(l,a,o)}else yield*this.data}_getitem(n){const[o,...a]=this.dims;if(n=safeIndex(n,o),a.length>0){const l=a.reduce((p,u)=>p*u);return this._subarray(n,l,a)}else return new Tensor(this.type,[this.data[n]],a)}indexOf(n){for(let o=0;o<this.data.length;++o)if(this.data[o]==n)return o;return-1}_subarray(n,o,a){const l=n*o,p=(n+1)*o,u="subarray"in this.data?this.data.subarray(l,p):this.data.slice(l,p);return new Tensor(this.type,u,a)}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}mul(n){return this.clone().mul_(n)}mul_(n){for(let o=0;o<this.data.length;++o)this.data[o]*=n;return this}add(n){return this.clone().add_(n)}add_(n){for(let o=0;o<this.data.length;++o)this.data[o]+=n;return this}clone(){return new Tensor(this.type,this.data.slice(),this.dims.slice())}slice(...n){let o=[],a=[];for(let g=0;g<this.dims.length;++g){let c=n[g];if(c==null)a.push([0,this.dims[g]]),o.push(this.dims[g]);else if(typeof c=="number")c=safeIndex(c,this.dims[g],g),a.push([c,c+1]);else if(Array.isArray(c)&&c.length===2){if(c[0]>c[1])throw new Error(`Invalid slice: ${c}`);let s=[Math.max(c[0],0),Math.min(c[1],this.dims[g])];a.push(s),o.push(s[1]-s[0])}else throw new Error(`Invalid slice: ${c}`)}let l=a.map(([g,c])=>c-g),p=l.reduce((g,c)=>g*c),u=new this.data.constructor(p);const h=this.stride();for(let g=0;g<p;++g){let c=0;for(let s=l.length-1,t=g;s>=0;--s){const e=l[s];c+=(t%e+a[s][0])*h[s],t=Math.floor(t/e)}u[g]=this.data[c]}return new Tensor(this.type,u,o)}transpose(...n){return transpose(this,n)}sum(n=null,o=!1){return this.norm(1,n,o)}norm(n="fro",o=null,a=!1){if(n==="fro")n=2;else if(typeof n=="string")throw Error(`Unsupported norm: ${n}`);if(o===null){let u=this.data.reduce((h,g)=>h+g**n,0)**(1/n);return new Tensor(this.type,[u],[])}o=safeIndex(o,this.dims.length);const l=this.dims.slice();l[o]=1;const p=new this.data.constructor(this.data.length/this.dims[o]);for(let u=0;u<this.data.length;++u){let h=0;for(let g=this.dims.length-1,c=u,s=1;g>=0;--g){const t=this.dims[g];if(g!==o){const e=c%t;h+=e*s,s*=l[g]}c=Math.floor(c/t)}p[h]+=this.data[u]**n}if(n!==1)for(let u=0;u<p.length;++u)p[u]=p[u]**(1/n);return a||l.splice(o,1),new Tensor(this.type,p,l)}normalize_(n=2,o=1){o=safeIndex(o,this.dims.length);const a=this.norm(n,o,!0);for(let l=0;l<this.data.length;++l){let p=0;for(let u=this.dims.length-1,h=l,g=1;u>=0;--u){const c=this.dims[u];if(u!==o){const s=h%c;p+=s*g,g*=this.dims[u]}h=Math.floor(h/c)}this.data[l]/=a.data[p]}return this}normalize(n=2,o=1){return this.clone().normalize_(n,o)}stride(){return dimsToStride(this.dims)}squeeze(n=null){return new Tensor(this.type,this.data,calc_squeeze_dims(this.dims,n))}squeeze_(n=null){return this.dims=calc_squeeze_dims(this.dims,n),this}unsqueeze(n=null){return new Tensor(this.type,this.data,calc_unsqueeze_dims(this.dims,n))}unsqueeze_(n=null){return this.dims=calc_unsqueeze_dims(this.dims,n),this}flatten_(n=0,o=-1){o=(o+this.dims.length)%this.dims.length;let a=this.dims.slice(0,n),l=this.dims.slice(n,o+1),p=this.dims.slice(o+1);return this.dims=[...a,l.reduce((u,h)=>u*h,1),...p],this}flatten(n=0,o=-1){return this.clone().flatten_(n,o)}view(...n){let o=-1;for(let a=0;a<n.length;++a)if(n[a]===-1){if(o!==-1)throw new Error("Only one dimension can be inferred");o=a}if(o!==-1){const a=n.reduce((l,p,u)=>u!==o?l*p:l,1);n[o]=this.data.length/a}return new Tensor(this.type,this.data,n)}neg_(){for(let n=0;n<this.data.length;++n)this.data[n]=-this.data[n];return this}neg(){return this.clone().neg_()}clamp_(n,o){for(let a=0;a<this.data.length;++a)this.data[a]=Math.min(Math.max(this.data[a],n),o);return this}clamp(n,o){return this.clone().clamp_(n,o)}round_(){for(let n=0;n<this.data.length;++n)this.data[n]=Math.round(this.data[n]);return this}round(){return this.clone().round_()}to(n){if(this.type===n)return this;if(!DataTypeMap.hasOwnProperty(n))throw new Error(`Unsupported type: ${n}`);return new Tensor(n,DataTypeMap[n].from(this.data),this.dims)}}function reshape(f,n){const o=f.length,a=n.reduce((p,u)=>p*u);if(o!==a)throw Error(`cannot reshape array of size ${o} into shape (${n})`);let l=f;for(let p=n.length-1;p>=0;p--)l=l.reduce((u,h)=>{let g=u[u.length-1];return g.length<n[p]?g.push(h):u.push([h]),u},[[]]);return l[0]}function transpose(f,n){const[o,a]=transpose_data(f.data,f.dims,n);return new Tensor(f.type,o,a)}function calc_squeeze_dims(f,n){return f=f.slice(),n===null?f=f.filter(o=>o!==1):typeof n=="number"?f[n]===1&&f.splice(n,1):Array.isArray(n)&&(f=f.filter((o,a)=>o!==1||!n.includes(a))),f}function calc_unsqueeze_dims(f,n){return n=safeIndex(n,f.length+1),f=f.slice(),f.splice(n,0,1),f}function safeIndex(f,n,o=null){if(f<-n||f>=n)throw new Error(`IndexError: index ${f} is out of bounds for dimension${o===null?"":" "+o} with size ${n}`);return f<0&&(f=(f%n+n)%n),f}function cat(f,n=0){n=safeIndex(n,f[0].dims.length);const o=f[0].dims.slice();o[n]=f.reduce((u,h)=>u+h.dims[n],0);const a=o.reduce((u,h)=>u*h,1),l=new f[0].data.constructor(a),p=f[0].type;if(n===0){let u=0;for(let h of f)l.set(h.data,u),u+=h.data.length}else{let u=0;for(let h=0;h<f.length;++h){let g=f[h];for(let c=0;c<g.data.length;++c){let s=0;for(let t=g.dims.length-1,e=c,r=1;t>=0;--t){const i=g.dims[t];let d=e%i;t===n&&(d+=u),s+=d*r,r*=o[t],e=Math.floor(e/i)}l[s]=g.data[c]}u+=g.dims[n]}}return new Tensor(p,l,o)}function stack(f,n=0){return cat(f.map(o=>o.unsqueeze(n)),n)}function std_mean(f,n=null,o=1,a=!1){if(n===null){const c=f.data.reduce((r,i)=>r+i,0)/f.data.length,s=Math.sqrt(f.data.reduce((r,i)=>r+(i-c)**2,0)/(f.data.length-o)),t=new Tensor(f.type,[c],[]);return[new Tensor(f.type,[s],[]),t]}n=safeIndex(n,f.dims.length);const l=mean(f,n,a),p=f.dims.slice();p[n]=1;const u=new f.data.constructor(f.data.length/f.dims[n]);for(let g=0;g<f.data.length;++g){let c=0;for(let s=f.dims.length-1,t=g,e=1;s>=0;--s){const r=f.dims[s];if(s!==n){const i=t%r;c+=i*e,e*=p[s]}t=Math.floor(t/r)}u[c]+=(f.data[g]-l.data[c])**2}for(let g=0;g<u.length;++g)u[g]=Math.sqrt(u[g]/(f.dims[n]-o));return a||p.splice(n,1),[new Tensor(f.type,u,p),l]}function mean(f,n=null,o=!1){if(n===null){let p=f.data.reduce((u,h)=>u+h,0);return new Tensor(f.type,[p/f.data.length],[])}n=safeIndex(n,f.dims.length);const a=f.dims.slice();a[n]=1;const l=new f.data.constructor(f.data.length/f.dims[n]);for(let p=0;p<f.data.length;++p){let u=0;for(let h=f.dims.length-1,g=p,c=1;h>=0;--h){const s=f.dims[h];if(h!==n){const t=g%s;u+=t*c,c*=a[h]}g=Math.floor(g/s)}l[u]+=f.data[p]}if(f.dims[n]!==1)for(let p=0;p<l.length;++p)l[p]=l[p]/f.dims[n];return o||a.splice(n,1),new Tensor(f.type,l,a)}function dynamicTimeWarping(f){const[n,o]=f.dims,a=[n+1,o+1],l=new Tensor("float32",new Float32Array(a[0]*a[1]).fill(1/0),a),p=new Tensor("float32",new Float32Array(a[0]*a[1]).fill(-1),a);l[0].data[0]=0;for(let s=1;s<o+1;++s)for(let t=1;t<n+1;++t){const e=l[t-1][s-1].item(),r=l[t-1][s].item(),i=l[t][s-1].item();let d,m;e<r&&e<i?(d=e,m=0):r<e&&r<i?(d=r,m=1):(d=i,m=2),l[t].data[s]=f[t-1][s-1].item()+d,p[t].data[s]=m}let u=n,h=o;p.data.fill(2,0,a[1]);for(let s=0;s<a[0];++s)p[s].data[0]=1;let g=[],c=[];for(;u>0||h>0;)switch(g.push(u-1),c.push(h-1),p[u][h].item()){case 0:--u,--h;break;case 1:--u;break;case 2:--h;break;default:throw new Error(`Internal error in dynamic time warping. Unexpected trace[${u}, ${h}]. Please file a bug report.`)}return g.reverse(),c.reverse(),[g,c]}function dimsToStride(f){const n=new Array(f.length);for(let o=f.length-1,a=1;o>=0;--o)n[o]=a,a*=f[o];return n}function ones(f){const n=f.reduce((o,a)=>o*a,1);return new Tensor("int64",new BigInt64Array(n).fill(1n),f)}function ones_like(f){return ones(f.dims)}class PriorityQueue{constructor(n=(o,a)=>o>a){this._heap=[],this._comparator=n}get size(){return this._heap.length}isEmpty(){return this.size===0}peek(){return this._heap[0]}push(...n){return this.extend(n)}extend(n){for(const o of n)this._heap.push(o),this._siftUp();return this.size}pop(){const n=this.peek(),o=this.size-1;return o>0&&this._swap(0,o),this._heap.pop(),this._siftDown(),n}replace(n){const o=this.peek();return this._heap[0]=n,this._siftDown(),o}_parent(n){return(n+1>>>1)-1}_left(n){return(n<<1)+1}_right(n){return n+1<<1}_greater(n,o){return this._comparator(this._heap[n],this._heap[o])}_swap(n,o){const a=this._heap[n];this._heap[n]=this._heap[o],this._heap[o]=a}_siftUp(){let n=this.size-1;for(;n>0&&this._greater(n,this._parent(n));)this._swap(n,this._parent(n)),n=this._parent(n)}_siftDown(){let n=0;for(;this._left(n)<this.size&&this._greater(this._left(n),n)||this._right(n)<this.size&&this._greater(this._right(n),n);){const o=this._right(n)<this.size&&this._greater(this._right(n),this._left(n))?this._right(n):this._left(n);this._swap(n,o),n=o}}}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 a of n){let l=o.children.get(a);l===void 0&&(l=CharTrieNode.default(),o.children.set(a,l)),o=l}o.isLeaf=!0}*commonPrefixSearch(n){let o=this.root,a="";for(let l=0;l<n.length&&o!==void 0;++l){const p=n[l];a+=p,o=o.children.get(p),o!==void 0&&o.isLeaf&&(yield a)}}}class CharTrieNode{constructor(n,o){this.isLeaf=n,this.children=o}static default(){return new CharTrieNode(!1,new Map)}}class TokenLattice{constructor(n,o,a){this.sentence=n,this.len=n.length,this.bosTokenId=o,this.eosTokenId=a,this.nodes=[],this.beginNodes=Array.from({length:this.len+1},()=>[]),this.endNodes=Array.from({length:this.len+1},()=>[]);const l=new TokenLatticeNode(this.bosTokenId,0,0,0,0),p=new TokenLatticeNode(this.eosTokenId,1,this.len,0,0);this.nodes.push(l.clone()),this.nodes.push(p.clone()),this.beginNodes[this.len].push(p),this.endNodes[0].push(l)}insert(n,o,a,l){const p=this.nodes.length,u=new TokenLatticeNode(l,p,n,o,a);this.beginNodes[n].push(u),this.endNodes[n+o].push(u),this.nodes.push(u)}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 g=0,c=null;for(let s of this.endNodes[o]){const t=s.backtraceScore+h.score;(c===null||t>g)&&(c=s.clone(),g=t)}if(c!==null)h.prev=c,h.backtraceScore=g;else return[]}++o}const a=[],p=this.beginNodes[n][0].prev;if(p===null)return[];let u=p.clone();for(;u.prev!==null;)a.push(u.clone()),u=u.clone().prev.clone();return a.reverse(),a}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,a,l,p){this.tokenId=n,this.nodeId=o,this.pos=a,this.length=l,this.score=p,this.prev=null,this.backtraceScore=0}clone(){const n=new TokenLatticeNode(this.tokenId,this.nodeId,this.pos,this.length,this.score);return n.prev=this.prev,n.backtraceScore=this.backtraceScore,n}}var TOKEN_TYPES=Object.freeze({Text:"Text",NumericLiteral:"NumericLiteral",BooleanLiteral:"BooleanLiteral",StringLiteral:"StringLiteral",Identifier:"Identifier",Equals:"Equals",OpenParen:"OpenParen",CloseParen:"CloseParen",OpenStatement:"OpenStatement",CloseStatement:"CloseStatement",OpenExpression:"OpenExpression",CloseExpression:"CloseExpression",OpenSquareBracket:"OpenSquareBracket",CloseSquareBracket:"CloseSquareBracket",Comma:"Comma",Dot:"Dot",Colon:"Colon",Pipe:"Pipe",CallOperator:"CallOperator",AdditiveBinaryOperator:"AdditiveBinaryOperator",MultiplicativeBinaryOperator:"MultiplicativeBinaryOperator",ComparisonBinaryOperator:"ComparisonBinaryOperator",UnaryOperator:"UnaryOperator",Set:"Set",If:"If",For:"For",In:"In",NotIn:"NotIn",Else:"Else",EndIf:"EndIf",ElseIf:"ElseIf",EndFor:"EndFor",And:"And",Or:"Or",Not:"UnaryOperator"}),KEYWORDS=Object.freeze({set:TOKEN_TYPES.Set,for:TOKEN_TYPES.For,in:TOKEN_TYPES.In,if:TOKEN_TYPES.If,else:TOKEN_TYPES.Else,endif:TOKEN_TYPES.EndIf,elif:TOKEN_TYPES.ElseIf,endfor:TOKEN_TYPES.EndFor,and:TOKEN_TYPES.And,or:TOKEN_TYPES.Or,not:TOKEN_TYPES.Not,"not in":TOKEN_TYPES.NotIn,true:TOKEN_TYPES.BooleanLiteral,false:TOKEN_TYPES.BooleanLiteral}),Token=class{constructor(f,n){this.value=f,this.type=n}};function isWord(f){return/\w/.test(f)}function isInteger(f){return/[0-9]/.test(f)}var ORDERED_MAPPING_TABLE=[["{%",TOKEN_TYPES.OpenStatement],["%}",TOKEN_TYPES.CloseStatement],["{{",TOKEN_TYPES.OpenExpression],["}}",TOKEN_TYPES.CloseExpression],["(",TOKEN_TYPES.OpenParen],[")",TOKEN_TYPES.CloseParen],["[",TOKEN_TYPES.OpenSquareBracket],["]",TOKEN_TYPES.CloseSquareBracket],[",",TOKEN_TYPES.Comma],[".",TOKEN_TYPES.Dot],[":",TOKEN_TYPES.Colon],["|",TOKEN_TYPES.Pipe],["<=",TOKEN_TYPES.ComparisonBinaryOperator],[">=",TOKEN_TYPES.ComparisonBinaryOperator],["==",TOKEN_TYPES.ComparisonBinaryOperator],["!=",TOKEN_TYPES.ComparisonBinaryOperator],["<",TOKEN_TYPES.ComparisonBinaryOperator],[">",TOKEN_TYPES.ComparisonBinaryOperator],["+",TOKEN_TYPES.AdditiveBinaryOperator],["-",TOKEN_TYPES.AdditiveBinaryOperator],["*",TOKEN_TYPES.MultiplicativeBinaryOperator],["/",TOKEN_TYPES.MultiplicativeBinaryOperator],["%",TOKEN_TYPES.MultiplicativeBinaryOperator],["=",TOKEN_TYPES.Equals]],ESCAPE_CHARACTERS=new Map([["n",`
`],["t","	"],["r","\r"],["b","\b"],["f","\f"],["v","\v"],["'","'"],['"','"'],["\\","\\"]]);function tokenize(f){var p,u,h;const n=[],o=f;let a=0;const l=g=>{let c="";for(;g(o[a]);){if(o[a]==="\\"){if(++a,a>=o.length)throw new SyntaxError("Unexpected end of input");const s=o[a++],t=ESCAPE_CHARACTERS.get(s);if(t===void 0)throw new SyntaxError(`Unexpected escaped character: ${s}`);c+=t;continue}if(c+=o[a++],a>=o.length)throw new SyntaxError("Unexpected end of input")}return c};e:for(;a<o.length;){const g=(p=n.at(-1))==null?void 0:p.type;if(g===void 0||g===TOKEN_TYPES.CloseStatement||g===TOKEN_TYPES.CloseExpression){let s="";for(;a<o.length&&!(o[a]==="{"&&(o[a+1]==="%"||o[a+1]==="{"));)s+=o[a++];if(s.length>0){n.push(new Token(s,TOKEN_TYPES.Text));continue}}l(s=>/\s/.test(s));const c=o[a];if(c==="-"||c==="+"){const s=(u=n.at(-1))==null?void 0:u.type;if(s===TOKEN_TYPES.Text||s===void 0)throw new SyntaxError(`Unexpected character: ${c}`);switch(s){case TOKEN_TYPES.Identifier:case TOKEN_TYPES.NumericLiteral:case TOKEN_TYPES.BooleanLiteral:case TOKEN_TYPES.StringLiteral:case TOKEN_TYPES.CloseParen:case TOKEN_TYPES.CloseSquareBracket:break;default:{++a;const t=l(isInteger);n.push(new Token(`${c}${t}`,t.length>0?TOKEN_TYPES.NumericLiteral:TOKEN_TYPES.UnaryOperator));continue}}}for(const[s,t]of ORDERED_MAPPING_TABLE)if(o.slice(a,a+s.length)===s){n.push(new Token(s,t)),a+=s.length;continue e}if(c==="'"){++a;const s=l(t=>t!=="'");n.push(new Token(s,TOKEN_TYPES.StringLiteral)),++a;continue}if(isInteger(c)){const s=l(isInteger);n.push(new Token(s,TOKEN_TYPES.NumericLiteral));continue}if(isWord(c)){const s=l(isWord),t=Object.hasOwn(KEYWORDS,s)?KEYWORDS[s]:TOKEN_TYPES.Identifier;t===TOKEN_TYPES.In&&((h=n.at(-1))==null?void 0:h.type)===TOKEN_TYPES.Not?(n.pop(),n.push(new Token("not in",TOKEN_TYPES.NotIn))):n.push(new Token(s,t));continue}throw new SyntaxError(`Unexpected character: ${c}`)}return n}var Statement=class{constructor(){Z(this,"type","Statement")}},Program=class 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TOKEN_TYPES.For:++o,D=e(),a(TOKEN_TYPES.OpenStatement,"Expected {% token"),a(TOKEN_TYPES.EndFor,"Expected endfor token"),a(TOKEN_TYPES.CloseStatement,"Expected %} token");break;default:throw new SyntaxError(`Unknown statement type: ${f[o].type}`)}return D}function c(){a(TOKEN_TYPES.OpenExpression,"Expected opening expression token");const D=r();return a(TOKEN_TYPES.CloseExpression,"Expected closing expression token"),D}function s(){const D=r();if(u(TOKEN_TYPES.Equals)){++o;const L=s();return new SetStatement(D,L)}return D}function t(){var U,N,j,J,Y,ee,te,de;const D=r();a(TOKEN_TYPES.CloseStatement,"Expected closing statement token");const L=[],C=[];for(;!(((U=f[o])==null?void 0:U.type)===TOKEN_TYPES.OpenStatement&&(((N=f[o+1])==null?void 0:N.type)===TOKEN_TYPES.ElseIf||((j=f[o+1])==null?void 0:j.type)===TOKEN_TYPES.Else||((J=f[o+1])==null?void 0:J.type)===TOKEN_TYPES.EndIf));)L.push(l());if(((Y=f[o])==null?void 0:Y.type)===TOKEN_TYPES.OpenStatement&&((ee=f[o+1])==null?void 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p=[];for(let u=n;l*u<l*o;u+=a)p.push(f[u]);return p}var RuntimeValue=class{constructor(f=void 0){Z(this,"type","RuntimeValue");Z(this,"value");Z(this,"builtins",new Map);this.value=f}__bool__(){return new BooleanValue(!!this.value)}},NumericValue=class extends RuntimeValue{constructor(){super(...arguments);Z(this,"type","NumericValue")}},StringValue=class extends RuntimeValue{constructor(){super(...arguments);Z(this,"type","StringValue");Z(this,"builtins",new Map([["upper",new FunctionValue(()=>new StringValue(this.value.toUpperCase()))],["lower",new FunctionValue(()=>new StringValue(this.value.toLowerCase()))],["strip",new FunctionValue(()=>new StringValue(this.value.trim()))],["length",new NumericValue(this.value.length)]]))}},BooleanValue=class extends RuntimeValue{constructor(){super(...arguments);Z(this,"type","BooleanValue")}},ObjectValue=class extends RuntimeValue{constructor(){super(...arguments);Z(this,"type","ObjectValue")}__bool__(){return new 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StringValue(f);case"boolean":return new BooleanValue(f);case"object":return f===null?new NullValue:Array.isArray(f)?new ArrayValue(f.map(convertToRuntimeValues)):new ObjectValue(new Map(Object.entries(f).map(([n,o])=>[n,convertToRuntimeValues(o)])));case"function":return new FunctionValue((n,o)=>{const a=f(...n.map(l=>l.value))??null;return convertToRuntimeValues(a)});default:throw new Error(`Cannot convert to runtime value: ${f}`)}}var Template=class{constructor(f){Z(this,"parsed");f=f.replace(/%}\s+{%/g,"%}{%");const n=tokenize(f);this.parsed=parse(n)}render(f){const n=new Environment;n.set("false",!1),n.set("true",!0),n.set("raise_exception",l=>{throw new Error(l)});for(const[l,p]of Object.entries(f))n.set(l,p);return new Interpreter(n).run(this.parsed).value}};async function loadTokenizer(f,n){const o=await Promise.all([getModelJSON(f,"tokenizer.json",!0,n),getModelJSON(f,"tokenizer_config.json",!0,n)]);return n.legacy!==null&&(o[1].legacy=n.legacy),o}function regexSplit(f,n){const o=[];let a=0;for(const l of f.matchAll(n)){const p=l[0];a<l.index&&o.push(f.slice(a,l.index)),p.length>0&&o.push(p),a=l.index+p.length}return a<f.length&&o.push(f.slice(a)),o}function createPattern(f,n=!0){if(f.Regex!==void 0){let o=f.Regex.replace(/\\([#&~])/g,"$1");for(const[a,l]of PROBLEMATIC_REGEX_MAP)o=o.replaceAll(a,l);return new RegExp(o,"gu")}else if(f.String!==void 0){const o=escapeRegExp(f.String);return new RegExp(n?o:`(${o})`,"gu")}else return console.warn("Unknown pattern type:",f),null}function objectToMap(f){return new Map(Object.entries(f))}function prepareTensorForDecode(f){const n=f.dims;switch(n.length){case 1:return f.tolist();case 2:if(n[0]!==1)throw new Error("Unable to decode tensor with `batch size !== 1`. Use `tokenizer.batch_decode(...)` for batched inputs.");return f.tolist()[0];default:throw new Error(`Expected tensor to have 1-2 dimensions, got ${n.length}.`)}}function clean_up_tokenization(f){return f.replace(/ \./g,".").replace(/ \?/g,"?").replace(/ \!/g,"!").replace(/ ,/g,",").replace(/ \' /g,"'").replace(/ n\'t/g,"n't").replace(/ \'m/g,"'m").replace(/ \'s/g,"'s").replace(/ \'ve/g,"'ve").replace(/ \'re/g,"'re")}function remove_accents(f){return f.replace(/[\u0300-\u036f]/g,"")}function lowercase_and_remove_accent(f){return remove_accents(f.toLowerCase())}function fuse(f,n,o){const a=[];let l=0;for(;l<f.length;){if(a.push(f[l]),(o.get(f[l])??n)!==n){++l;continue}for(;l<f.length&&(o.get(f[l])??n)===n;)++l}return a}function whitespace_split(f){return f.match(/\S+/g)||[]}const PUNCTUATION_REGEX="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E",PROBLEMATIC_REGEX_MAP=new Map([["(?i:'s|'t|'re|'ve|'m|'ll|'d)","(?:'([sS]|[tT]|[rR][eE]|[vV][eE]|[mM]|[lL][lL]|[dD]))"]]);class AddedToken{constructor(n){this.content=n.content,this.id=n.id,this.single_word=n.single_word??!1,this.lstrip=n.lstrip??!1,this.rstrip=n.rstrip??!1,this.special=n.special??!1,this.normalized=n.normalized??null}}class TokenizerModel extends Callable{constructor(n){super(),this.config=n,this.vocab=[],this.tokens_to_ids=new Map,this.unk_token_id=void 0,this.unk_token=void 0,this.end_of_word_suffix=void 0,this.fuse_unk=this.config.fuse_unk??!1}static fromConfig(n,...o){switch(n.type){case"WordPiece":return new WordPieceTokenizer(n);case"Unigram":return new Unigram(n,...o);case"BPE":return new BPE(n);default:if(n.vocab)return new LegacyTokenizerModel(n,...o);throw new Error(`Unknown TokenizerModel type: ${n.type}`)}}_call(n){let o=this.encode(n);return this.fuse_unk&&(o=fuse(o,this.unk_token_id,this.tokens_to_ids)),o}encode(n){throw Error("encode should be implemented in subclass.")}convert_tokens_to_ids(n){return n.map(o=>this.tokens_to_ids.get(o)??this.unk_token_id)}convert_ids_to_tokens(n){return n.map(o=>this.vocab[o]??this.unk_token)}}class WordPieceTokenizer extends TokenizerModel{constructor(n){super(n),this.tokens_to_ids=objectToMap(n.vocab),this.unk_token_id=this.tokens_to_ids.get(n.unk_token),this.unk_token=n.unk_token,this.max_input_chars_per_word=n.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[o,a]of this.tokens_to_ids)this.vocab[a]=o}encode(n){const o=[];for(const a of n){const l=[...a];if(l.length>this.max_input_chars_per_word){o.push(this.unk_token);continue}let p=!1,u=0;const h=[];for(;u<l.length;){let g=l.length,c=null;for(;u<g;){let s=l.slice(u,g).join("");if(u>0&&(s=this.config.continuing_subword_prefix+s),this.tokens_to_ids.has(s)){c=s;break}--g}if(c===null){p=!0;break}h.push(c),u=g}p?o.push(this.unk_token):o.push(...h)}return o}}class Unigram extends TokenizerModel{constructor(n,o){super(n);const a=n.vocab.length;this.vocab=new Array(a),this.scores=new Array(a);for(let l=0;l<a;++l){const p=n.vocab[l];this.vocab[l]=p[0],this.scores[l]=p[1]}this.unk_token_id=n.unk_id,this.unk_token=this.vocab[n.unk_id],this.tokens_to_ids=new Map(this.vocab.map((l,p)=>[l,p])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=o.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=min(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new CharTrie,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(n){const o=n.sentence,a=o.length;let l=0;for(;l<a;){let u=!1;for(let h of this.trie.commonPrefixSearch(o.slice(l))){const g=this.tokens_to_ids.get(h),c=this.scores[g],s=h.length;n.insert(l,s,c,g),!u&&s===1&&(u=!0)}u||n.insert(l,1,this.unkScore,this.unk_token_id),l+=1}}tokenize(n){const o=new TokenLattice(n,this.bosTokenId,this.eosTokenId);return this.populateNodes(o),o.tokens()}encode(n){const o=[];for(const a of n){const l=this.tokenize(a);o.push(...l)}return o}}const BYTES_TO_UNICODE=(()=>{const f=[...Array.from({length:"~".charCodeAt(0)-"!".charCodeAt(0)+1},(l,p)=>p+"!".charCodeAt(0)),...Array.from({length:"¬".charCodeAt(0)-"¡".charCodeAt(0)+1},(l,p)=>p+"¡".charCodeAt(0)),...Array.from({length:"ÿ".charCodeAt(0)-"®".charCodeAt(0)+1},(l,p)=>p+"®".charCodeAt(0))],n=f.slice();let o=0;for(let l=0;l<256;++l)f.includes(l)||(f.push(l),n.push(256+o),o+=1);const a=n.map(l=>String.fromCharCode(l));return Object.fromEntries(f.map((l,p)=>[l,a[p]]))})(),UNICODE_TO_BYTES=reverseDictionary(BYTES_TO_UNICODE);class BPE extends TokenizerModel{constructor(n){super(n),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=objectToMap(n.vocab),this.unk_token_id=this.tokens_to_ids.get(n.unk_token),this.unk_token=n.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[o,a]of this.tokens_to_ids)this.vocab[a]=o;this.bpe_ranks=new Map(n.merges.map((o,a)=>[o,a])),this.merges=n.merges.map(o=>o.split(this.BPE_SPLIT_TOKEN)),this.end_of_word_suffix=n.end_of_word_suffix,this.continuing_subword_suffix=n.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.cache=new Map}bpe(n){if(n.length===0)return[];const o=this.cache.get(n);if(o!==void 0)return o;const a=Array.from(n);this.end_of_word_suffix&&(a[a.length-1]+=this.end_of_word_suffix);let l=[];if(a.length>1){const p=new PriorityQueue((g,c)=>g.score<c.score);let u={token:a[0],bias:0,prev:null,next:null},h=u;for(let g=1;g<a.length;++g){const c={bias:g/a.length,token:a[g],prev:h,next:null};h.next=c,this._add_node(p,h),h=c}for(;!p.isEmpty();){const g=p.pop();if(g.deleted||!g.next||g.next.deleted)continue;if(g.deleted=!0,g.next.deleted=!0,g.prev){const s={...g.prev};g.prev.deleted=!0,g.prev=s,s.prev?s.prev.next=s:u=s}const c={token:g.token+g.next.token,bias:g.bias,prev:g.prev,next:g.next.next};c.prev?(c.prev.next=c,this._add_node(p,c.prev)):u=c,c.next&&(c.next.prev=c,this._add_node(p,c))}for(let g=u;g!==null;g=g.next)l.push(g.token)}else l=a;if(this.continuing_subword_suffix)for(let p=0;p<l.length-1;++p)l[p]+=this.continuing_subword_suffix;return this.cache.set(n,l),l}_add_node(n,o){const a=this.bpe_ranks.get(o.token+this.BPE_SPLIT_TOKEN+o.next.token);a!==void 0&&(o.score=a+o.bias,n.push(o))}encode(n){const o=[];for(const a of n){const l=this.bpe(a);for(const p of l)this.tokens_to_ids.has(p)?o.push(p):this.byte_fallback?o.push(...Array.from(this.text_encoder.encode(p)).map(u=>`<0x${u.toString(16).toUpperCase().padStart(2,"0")}>`)):o.push(this.unk_token)}return o}}class LegacyTokenizerModel extends TokenizerModel{constructor(n,o){super(n),this.tokens_to_ids=objectToMap(o.target_lang?n.vocab[o.target_lang]:n.vocab),this.bos_token=o.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=o.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=o.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=o.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=new Array(this.tokens_to_ids.size);for(const[a,l]of this.tokens_to_ids)this.vocab[l]=a}encode(n){return n}}class Normalizer extends Callable{constructor(n){super(),this.config=n}static fromConfig(n){if(n===null)return null;switch(n.type){case"BertNormalizer":return new BertNormalizer(n);case"Precompiled":return new Precompiled(n);case"Sequence":return new NormalizerSequence(n);case"Replace":return new Replace(n);case"NFC":return new NFC(n);case"NFKC":return new NFKC(n);case"NFKD":return new NFKD(n);case"Strip":return new StripNormalizer(n);case"StripAccents":return new StripAccents(n);case"Lowercase":return new Lowercase(n);case"Prepend":return new Prepend(n);default:throw new Error(`Unknown Normalizer type: ${n.type}`)}}normalize(n){throw Error("normalize should be implemented in subclass.")}_call(n){return this.normalize(n)}}class Replace extends Normalizer{normalize(n){const o=createPattern(this.config.pattern);return o===null?n:n.replaceAll(o,this.config.content)}}class NFC extends Normalizer{normalize(n){return n=n.normalize("NFC"),n}}class NFKC extends Normalizer{normalize(n){return n=n.normalize("NFKC"),n}}class NFKD extends Normalizer{normalize(n){return n=n.normalize("NFKD"),n}}class StripNormalizer extends Normalizer{normalize(n){return this.config.strip_left&&this.config.strip_right?n=n.trim():(this.config.strip_left&&(n=n.trimStart()),this.config.strip_right&&(n=n.trimEnd())),n}}class StripAccents extends Normalizer{normalize(n){return n=remove_accents(n),n}}class Lowercase extends Normalizer{normalize(n){return n=n.toLowerCase(),n}}class Prepend extends Normalizer{normalize(n){return n=this.config.prepend+n,n}}class NormalizerSequence extends Normalizer{constructor(n){super(n),this.normalizers=n.normalizers.map(o=>Normalizer.fromConfig(o))}normalize(n){return this.normalizers.reduce((o,a)=>a.normalize(o),n)}}class BertNormalizer extends Normalizer{_tokenize_chinese_chars(n){const o=[];for(let a=0;a<n.length;++a){const l=n[a],p=l.charCodeAt(0);this._is_chinese_char(p)?(o.push(" "),o.push(l),o.push(" ")):o.push(l)}return o.join("")}_is_chinese_char(n){return n>=19968&&n<=40959||n>=13312&&n<=19903||n>=131072&&n<=173791||n>=173824&&n<=177983||n>=177984&&n<=178207||n>=178208&&n<=183983||n>=63744&&n<=64255||n>=194560&&n<=195103}stripAccents(n){return n.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}_is_control(n){switch(n){case"	":case`
`:case"\r":return!1;default:return/^\p{Cc}|\p{Cf}|\p{Co}|\p{Cs}$/u.test(n)}}_clean_text(n){const o=[];for(const a of n){const l=a.charCodeAt(0);l===0||l===65533||this._is_control(a)||(/^\s$/.test(a)?o.push(" "):o.push(a))}return o.join("")}normalize(n){return this.config.clean_text&&(n=this._clean_text(n)),this.config.handle_chinese_chars&&(n=this._tokenize_chinese_chars(n)),this.config.lowercase?(n=n.toLowerCase(),this.config.strip_accents!==!1&&(n=this.stripAccents(n))):this.config.strip_accents&&(n=this.stripAccents(n)),n}}class PreTokenizer extends Callable{static fromConfig(n){if(n===null)return null;switch(n.type){case"BertPreTokenizer":return new BertPreTokenizer(n);case"Sequence":return new PreTokenizerSequence(n);case"Whitespace":return new WhitespacePreTokenizer(n);case"WhitespaceSplit":return new WhitespaceSplit(n);case"Metaspace":return new MetaspacePreTokenizer(n);case"ByteLevel":return new ByteLevelPreTokenizer(n);case"Split":return new SplitPreTokenizer(n);case"Punctuation":return new PunctuationPreTokenizer(n);case"Digits":return new DigitsPreTokenizer(n);case"Replace":return new ReplacePreTokenizer(n);default:throw new Error(`Unknown PreTokenizer type: ${n.type}`)}}pre_tokenize_text(n,o){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(n,o){return(Array.isArray(n)?n.map(a=>this.pre_tokenize_text(a,o)):this.pre_tokenize_text(n,o)).flat()}_call(n,o){return this.pre_tokenize(n,o)}}class BertPreTokenizer extends PreTokenizer{constructor(n){super(),this.pattern=new RegExp(`[^\\s${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]`,"gu")}pre_tokenize_text(n,o){return n.trim().match(this.pattern)||[]}}class ByteLevelPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=/'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+/gu,this.byte_encoder=BYTES_TO_UNICODE,this.text_encoder=new TextEncoder}pre_tokenize_text(n,o){return this.add_prefix_space&&!n.startsWith(" ")&&(n=" "+n),(this.use_regex?n.match(this.pattern)||[]:[n]).map(l=>Array.from(this.text_encoder.encode(l),p=>this.byte_encoder[p]).join(""))}}class SplitPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=createPattern(this.config.pattern,this.config.invert)}pre_tokenize_text(n,o){return this.pattern===null?[]:this.config.invert?n.match(this.pattern)||[]:regexSplit(n,this.pattern)}}class PunctuationPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=new RegExp(`[^${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]+`,"gu")}pre_tokenize_text(n,o){return n.match(this.pattern)||[]}}class DigitsPreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n;const o=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(o,"gu")}pre_tokenize_text(n,o){return n.match(this.pattern)||[]}}class PostProcessor extends Callable{constructor(n){super(),this.config=n}static fromConfig(n){if(n===null)return null;switch(n.type){case"TemplateProcessing":return new TemplateProcessing(n);case"ByteLevel":return new ByteLevelPostProcessor(n);case"RobertaProcessing":return new RobertaProcessing(n);case"BertProcessing":return new BertProcessing(n);default:throw new Error(`Unknown PostProcessor type: ${n.type}`)}}post_process(n,...o){throw Error("post_process should be implemented in subclass.")}_call(n,...o){return this.post_process(n,...o)}}class BertProcessing extends PostProcessor{constructor(n){super(n),this.cls=n.cls[0],this.sep=n.sep[0]}post_process(n,o=null,{add_special_tokens:a=!0}={}){a&&(n=mergeArrays([this.cls],n,[this.sep]));let l=new Array(n.length).fill(0);if(o!==null){const p=a&&this instanceof RobertaProcessing?[this.sep]:[],u=a?[this.sep]:[];n=mergeArrays(n,p,o,u),l=mergeArrays(l,new Array(o.length+p.length+u.length).fill(1))}return{tokens:n,token_type_ids:l}}}class RobertaProcessing extends BertProcessing{}class TemplateProcessing extends PostProcessor{constructor(n){super(n),this.single=n.single,this.pair=n.pair}post_process(n,o=null,{add_special_tokens:a=!0}={}){const l=o===null?this.single:this.pair;let p=[],u=[];for(const h of l)"SpecialToken"in h?a&&(p.push(h.SpecialToken.id),u.push(h.SpecialToken.type_id)):"Sequence"in h&&(h.Sequence.id==="A"?(p=mergeArrays(p,n),u=mergeArrays(u,new Array(n.length).fill(h.Sequence.type_id))):h.Sequence.id==="B"&&(p=mergeArrays(p,o),u=mergeArrays(u,new Array(o.length).fill(h.Sequence.type_id))));return{tokens:p,token_type_ids:u}}}class ByteLevelPostProcessor extends PostProcessor{post_process(n,o=null){return o&&(n=mergeArrays(n,o)),{tokens:n}}}class Decoder extends Callable{constructor(n){super(),this.config=n,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=n.trim_offsets}static fromConfig(n){if(n===null)return null;switch(n.type){case"WordPiece":return new WordPieceDecoder(n);case"Metaspace":return new MetaspaceDecoder(n);case"ByteLevel":return new ByteLevelDecoder(n);case"Replace":return new ReplaceDecoder(n);case"ByteFallback":return new ByteFallback(n);case"Fuse":return new FuseDecoder(n);case"Strip":return new StripDecoder(n);case"Sequence":return new DecoderSequence(n);case"CTC":return new CTCDecoder(n);case"BPEDecoder":return new BPEDecoder(n);default:throw new Error(`Unknown Decoder type: ${n.type}`)}}_call(n){return this.decode(n)}decode(n){return this.decode_chain(n).join("")}decode_chain(n){throw Error("`decode_chain` should be implemented in subclass.")}}class ReplaceDecoder extends Decoder{decode_chain(n){const o=createPattern(this.config.pattern);return o===null?n:n.map(a=>a.replaceAll(o,this.config.content))}}class ByteFallback extends Decoder{constructor(n){super(n),this.text_decoder=new TextDecoder}decode_chain(n){const o=[];let a=[];for(const l of n){let p=null;if(l.length===6&&l.startsWith("<0x")&&l.endsWith(">")){const u=parseInt(l.slice(3,5),16);isNaN(u)||(p=u)}if(p!==null)a.push(p);else{if(a.length>0){const u=this.text_decoder.decode(Uint8Array.from(a));o.push(u),a=[]}o.push(l)}}if(a.length>0){const l=this.text_decoder.decode(Uint8Array.from(a));o.push(l),a=[]}return o}}class FuseDecoder extends Decoder{decode_chain(n){return[n.join("")]}}class StripDecoder extends Decoder{constructor(n){super(n),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(n){return n.map(o=>{let a=0;for(let p=0;p<this.start&&o[p]===this.content;++p){a=p+1;continue}let l=o.length;for(let p=0;p<this.stop;++p){const u=o.length-p-1;if(o[u]===this.content){l=u;continue}else break}return o.slice(a,l)})}}class WordPieceDecoder extends Decoder{constructor(n){super(n),this.cleanup=n.cleanup}decode_chain(n){return n.map((o,a)=>(a!==0&&(o.startsWith(this.config.prefix)?o=o.replace(this.config.prefix,""):o=" "+o),this.cleanup&&(o=clean_up_tokenization(o)),o))}}class ByteLevelDecoder extends Decoder{constructor(n){super(n),this.byte_decoder=UNICODE_TO_BYTES,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(n){const o=n.join(""),a=new Uint8Array([...o].map(p=>this.byte_decoder[p]));return this.text_decoder.decode(a)}decode_chain(n){const o=[];let a=[];for(const l of n)this.added_tokens.find(p=>p.content===l)!==void 0?(a.length>0&&(o.push(this.convert_tokens_to_string(a)),a=[]),o.push(l)):a.push(l);return a.length>0&&o.push(this.convert_tokens_to_string(a)),o}}class CTCDecoder extends Decoder{constructor(n){super(n),this.pad_token=this.config.pad_token,this.word_delimiter_token=this.config.word_delimiter_token,this.cleanup=this.config.cleanup}convert_tokens_to_string(n){if(n.length===0)return"";const o=[n[0]];for(let p=1;p<n.length;++p)n[p]!==o.at(-1)&&o.push(n[p]);let l=o.filter(p=>p!==this.pad_token).join("");return this.cleanup&&(l=clean_up_tokenization(l).replaceAll(this.word_delimiter_token," ").trim()),l}decode_chain(n){return[this.convert_tokens_to_string(n)]}}class DecoderSequence extends Decoder{constructor(n){super(n),this.decoders=n.decoders.map(o=>Decoder.fromConfig(o))}decode_chain(n){return this.decoders.reduce((o,a)=>a.decode_chain(o),n)}}class BPEDecoder extends Decoder{constructor(n){super(n),this.suffix=this.config.suffix}decode_chain(n){return n.map((o,a)=>o.replaceAll(this.suffix,a===n.length-1?"":" "))}}class VitsDecoder extends Decoder{decode_chain(n){let o="";for(let a=1;a<n.length;a+=2)o+=n[a];return[o]}}class MetaspacePreTokenizer extends PreTokenizer{constructor(n){super(),this.addPrefixSpace=n.add_prefix_space,this.replacement=n.replacement,this.strRep=n.str_rep||this.replacement,this.prepend_scheme=n.prepend_scheme??"always"}pre_tokenize_text(n,{section_index:o=void 0}={}){let a=n.replaceAll(" ",this.strRep);return this.addPrefixSpace&&!a.startsWith(this.replacement)&&(this.prepend_scheme==="always"||this.prepend_scheme==="first"&&o===0)&&(a=this.strRep+a),[a]}}class MetaspaceDecoder extends Decoder{constructor(n){super(n),this.addPrefixSpace=n.add_prefix_space,this.replacement=n.replacement}decode_chain(n){const o=[];for(let a=0;a<n.length;++a){let l=n[a].replaceAll(this.replacement," ");this.addPrefixSpace&&a==0&&l.startsWith(" ")&&(l=l.substring(1)),o.push(l)}return o}}class Precompiled extends Normalizer{constructor(n){super(n),this.charsmap=n.precompiled_charsmap}normalize(n){return n=n.replace(/[\u0001-\u0008\u000B\u000E-\u001F\u007F\u008F\u009F]/gm,""),n=n.replace(/[\u0009\u000A\u000C\u000D\u1680\u200B\u200C\u200E\u200F\u2028\u2029\u2581\uFEFF\uFFFD]/gm," "),n.includes("～")?n=n.split("～").map(a=>a.normalize("NFKC")).join("～"):n=n.normalize("NFKC"),n}}class PreTokenizerSequence extends PreTokenizer{constructor(n){super(),this.tokenizers=n.pretokenizers.map(o=>PreTokenizer.fromConfig(o))}pre_tokenize_text(n,o){return this.tokenizers.reduce((a,l)=>l.pre_tokenize(a,o),[n])}}class WhitespacePreTokenizer extends PreTokenizer{constructor(n){super()}pre_tokenize_text(n,o){return n.match(/\w+|[^\w\s]+/g)||[]}}class WhitespaceSplit extends PreTokenizer{constructor(n){super()}pre_tokenize_text(n,o){return whitespace_split(n)}}class ReplacePreTokenizer extends PreTokenizer{constructor(n){super(),this.config=n,this.pattern=createPattern(this.config.pattern),this.content=this.config.content}pre_tokenize_text(n,o){return this.pattern===null?[n]:[n.replaceAll(this.pattern,this.config.content)]}}const SPECIAL_TOKEN_ATTRIBUTES=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function padHelper(f,n,o,a){for(const l of Object.keys(f)){const p=n-f[l].length,u=o(l),h=new Array(p).fill(u);f[l]=a==="right"?mergeArrays(f[l],h):mergeArrays(h,f[l])}}function truncateHelper(f,n){for(const o of Object.keys(f))f[o].length=n}class PreTrainedTokenizer extends Callable{constructor(o,a){super();Z(this,"return_token_type_ids",!1);Z(this,"_default_chat_template",`{% for message in messages %}{{'<|im_start|>' + message['role'] + '
' + message['content'] + '<|im_end|>' + '
'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
' }}{% endif %}`);this._tokenizer_config=a,this.normalizer=Normalizer.fromConfig(o.normalizer),this.pre_tokenizer=PreTokenizer.fromConfig(o.pre_tokenizer),this.model=TokenizerModel.fromConfig(o.model,a),this.post_processor=PostProcessor.fromConfig(o.post_processor),this.decoder=Decoder.fromConfig(o.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(const l of o.added_tokens){const p=new AddedToken(l);this.added_tokens.push(p),this.model.tokens_to_ids.set(p.content,p.id),this.model.vocab[p.id]=p.content,p.special&&(this.special_tokens.push(p.content),this.all_special_ids.push(p.id))}this.additional_special_tokens=a.additional_special_tokens??[],this.special_tokens.push(...this.additional_special_tokens),this.special_tokens=[...new Set(this.special_tokens)],this.decoder&&(this.decoder.added_tokens=this.added_tokens,this.decoder.end_of_word_suffix=this.model.end_of_word_suffix),this.added_tokens_regex=this.added_tokens.length>0?new RegExp(this.added_tokens.map(l=>`${l.lstrip?"\\s*":""}(${escapeRegExp(l.content)})${l.rstrip?"\\s*":""}`).join("|")):null,this.mask_token=this.getToken("mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken("pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken("sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.unk_token=this.getToken("unk_token"),this.unk_token_id=this.model.tokens_to_ids.get(this.unk_token),this.model_max_length=a.model_max_length,this.remove_space=a.remove_space,this.clean_up_tokenization_spaces=a.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=a.do_lowercase_and_remove_accent??!1,this.padding_side="right",this.legacy=!1,this.chat_template=a.chat_template??null,this._compiled_template_cache=new Map}getToken(...o){for(const a of o){const l=this._tokenizer_config[a];if(l)if(typeof l=="object"){if(l.__type==="AddedToken")return l.content;throw Error(`Unknown token: ${l}`)}else return l}return null}static async from_pretrained(o,{progress_callback:a=null,config:l=null,cache_dir:p=null,local_files_only:u=!1,revision:h="main",legacy:g=null}={}){const c=await loadTokenizer(o,{progress_callback:a,config:l,cache_dir:p,local_files_only:u,revision:h,legacy:g});return new this(...c)}_call(o,{text_pair:a=null,add_special_tokens:l=!0,padding:p=!1,truncation:u=null,max_length:h=null,return_tensor:g=!0}={}){const c=Array.isArray(o);let s;if(c){if(o.length===0)throw Error("text array must be non-empty");if(a!==null){if(Array.isArray(a)){if(o.length!==a.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");s=o.map((e,r)=>this._encode_plus(e,a[r],{add_special_tokens:l}))}else s=o.map(e=>this._encode_plus(e,null,{add_special_tokens:l}))}else{if(o===null)throw Error("text may not be null");if(Array.isArray(a))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");s=[this._encode_plus(o,a,{add_special_tokens:l})]}if(h===null?p==="max_length"?h=this.model_max_length:h=max(s.map(e=>e.input_ids.length))[0]:u||console.warn("Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation=true` to explicitly truncate examples to max length."),h=Math.min(h,this.model_max_length),p||u)for(let e=0;e<s.length;++e)s[e].input_ids.length!==h&&(s[e].input_ids.length>h?u&&truncateHelper(s[e],h):p&&padHelper(s[e],h,r=>r==="input_ids"?this.pad_token_id:0,this.padding_side));const t={};if(g){if(!(p&&u)&&s.some(r=>{var i;for(const d of Object.keys(r))if(r[d].length!==((i=s[0][d])==null?void 0:i.length))return!0;return!1}))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");const e=[s.length,s[0].input_ids.length];for(const r of Object.keys(s[0]))t[r]=new Tensor("int64",BigInt64Array.from(s.flatMap(i=>i[r]).map(BigInt)),e)}else{for(const e of Object.keys(s[0]))t[e]=s.map(r=>r[e]);if(!c)for(const e of Object.keys(t))t[e]=t[e][0]}return t}_encode_text(o){return o===null?null:(this.added_tokens_regex?o.split(this.added_tokens_regex).filter(p=>p):[o]).map((p,u)=>{if(this.added_tokens.find(g=>g.content===p)!==void 0)return p;{if(this.remove_space===!0&&(p=p.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(p=lowercase_and_remove_accent(p)),this.normalizer!==null&&(p=this.normalizer(p)),p.length===0)return[];const g=this.pre_tokenizer!==null?this.pre_tokenizer(p,{section_index:u}):[p];return this.model(g)}}).flat()}_encode_plus(o,a=null,{add_special_tokens:l=!0}={}){const p=this._encode_text(o),u=this._encode_text(a),h=this.post_processor?this.post_processor(p,u,{add_special_tokens:l}):{tokens:mergeArrays(p??[],u??[])},g=this.model.convert_tokens_to_ids(h.tokens),c={input_ids:g,attention_mask:new Array(g.length).fill(1)};return this.return_token_type_ids&&h.token_type_ids&&(c.token_type_ids=h.token_type_ids),c}encode(o,a=null,{add_special_tokens:l=!0}={}){const{input_ids:p}=this._encode_plus(o,a,{add_special_tokens:l});return p}batch_decode(o,a={}){return o instanceof Tensor&&(o=o.tolist()),o.map(l=>this.decode(l,a))}decode(o,a={}){if(o instanceof Tensor&&(o=prepareTensorForDecode(o)),!Array.isArray(o)||o.length===0||!isIntegralNumber(o[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(o,a)}decode_single(o,{skip_special_tokens:a=!1,clean_up_tokenization_spaces:l=null}){let p=this.model.convert_ids_to_tokens(o);a&&(p=p.filter(h=>!this.special_tokens.includes(h)));let u=this.decoder?this.decoder(p):p.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(u=u.replaceAll(this.decoder.end_of_word_suffix," "),a&&(u=u.trim())),(l??this.clean_up_tokenization_spaces)&&(u=clean_up_tokenization(u)),u}get default_chat_template(){return this._warned_about_chat_template||(console.warn("No chat template is defined for this tokenizer - using a default chat template that implements the ChatML format. If the default is not appropriate for your model, please set `tokenizer.chat_template` to an appropriate template. See https://huggingface.co/docs/transformers/main/chat_templating for more information."),this._warned_about_chat_template=!0),this._default_chat_template}apply_chat_template(o,{chat_template:a=null,add_generation_prompt:l=!1,tokenize:p=!0,padding:u=!1,truncation:h=!1,max_length:g=null,return_tensor:c=!0}={}){a??(a=this.chat_template??this.default_chat_template);let s=this._compiled_template_cache.get(a);s===void 0&&(s=new Template(a),this._compiled_template_cache.set(a,s));const t=Object.create(null);for(const r of SPECIAL_TOKEN_ATTRIBUTES){const i=this.getToken(r);i&&(t[r]=i)}const e=s.render({messages:o,add_generation_prompt:l,...t});return p?this._call(e,{add_special_tokens:!1,padding:u,truncation:h,max_length:g,return_tensor:c}).input_ids:e}}class BertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class AlbertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class MobileBertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class SqueezeBertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class DebertaTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class DebertaV2Tokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class HerbertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class ConvBertTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class RoFormerTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class DistilBertTokenizer extends PreTrainedTokenizer{}class CamembertTokenizer extends PreTrainedTokenizer{}class XLMTokenizer extends PreTrainedTokenizer{constructor(o,a){super(o,a);Z(this,"return_token_type_ids",!0);console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}}class ElectraTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"return_token_type_ids",!0)}}class T5Tokenizer extends PreTrainedTokenizer{}class GPT2Tokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"_default_chat_template",'{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}')}}class BartTokenizer extends PreTrainedTokenizer{}class MBartTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter(a=>this.languageRegex.test(a)),this.lang_to_token=a=>a}_build_translation_inputs(n,o,a){return _build_translation_inputs(this,n,o,a)}}class MBart50Tokenizer extends MBartTokenizer{}class RobertaTokenizer extends PreTrainedTokenizer{}class BloomTokenizer extends GPT2Tokenizer{constructor(n,o){var p,u;const a=".,!?…。，、।۔،",l=(u=(p=n.pre_tokenizer)==null?void 0:p.pretokenizers[0])==null?void 0:u.pattern;l&&l.Regex===` ?[^(\\s|[${a}])]+`&&(l.Regex=` ?[^\\s${a}]+`),super(n,o)}}const SPIECE_UNDERLINE="▁";class LlamaTokenizer extends PreTrainedTokenizer{constructor(o,a){super(o,a);Z(this,"_default_chat_template",`{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif USE_DEFAULT_PROMPT == true and not '<<SYS>>' in messages[0]['content'] %}{% set loop_messages = messages %}{% set system_message = 'DEFAULT_SYSTEM_MESSAGE' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>
' + system_message + '
<</SYS>>

' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'system' %}{{ '<<SYS>>
' + content.strip() + '
<</SYS>>

' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}`);Z(this,"DEFAULT_SYSTEM_PROMPT",`You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.

If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.`);this.use_default_system_prompt=a.use_default_system_prompt??!1,this.legacy=a.legacy??!0,this.legacy||(this.normalizer=null,this.pre_tokenizer=new MetaspacePreTokenizer({replacement:SPIECE_UNDERLINE,add_prefix_space:!0,prepend_scheme:"first"}))}_encode_text(o){if(o===null)return null;if(this.legacy||o.length===0)return super._encode_text(o);let a=super._encode_text(SPIECE_UNDERLINE+o.replaceAll(SPIECE_UNDERLINE," "));return a.length>1&&a[0]===SPIECE_UNDERLINE&&this.special_tokens.includes(a[1])&&(a=a.slice(1)),a}get default_chat_template(){return super.default_chat_template.replaceAll("USE_DEFAULT_PROMPT",this.use_default_system_prompt?"true":"false").replaceAll("DEFAULT_SYSTEM_MESSAGE",this.DEFAULT_SYSTEM_PROMPT.replaceAll(`
`,"\\n").replaceAll("'","\\'"))}}class CodeLlamaTokenizer extends LlamaTokenizer{}class XLMRobertaTokenizer extends PreTrainedTokenizer{}class MPNetTokenizer extends PreTrainedTokenizer{}class FalconTokenizer extends PreTrainedTokenizer{}class GPTNeoXTokenizer extends PreTrainedTokenizer{}class EsmTokenizer extends PreTrainedTokenizer{}class Qwen2Tokenizer extends PreTrainedTokenizer{}class GemmaTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"_default_chat_template",`{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '
' + message['content'] | trim + '<end_of_turn>
' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model
'}}{% endif %}`)}}function _build_translation_inputs(f,n,o,a){if(!("language_codes"in f)||!Array.isArray(f.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in f)||!(f.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in f)||typeof f.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const l=a.src_lang,p=a.tgt_lang;if(!f.language_codes.includes(p))throw new Error(`Target language code "${p}" is not valid. Must be one of: {${f.language_codes.join(", ")}}`);if(l!==void 0){if(!f.language_codes.includes(l))throw new Error(`Source language code "${l}" is not valid. Must be one of: {${f.language_codes.join(", ")}}`);for(const u of f.post_processor.config.single)if("SpecialToken"in u&&f.languageRegex.test(u.SpecialToken.id)){u.SpecialToken.id=f.lang_to_token(l);break}}return a.forced_bos_token_id=f.model.convert_tokens_to_ids([f.lang_to_token(p)])[0],f._call(n,o)}class NllbTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(a=>this.languageRegex.test(a)),this.lang_to_token=a=>a}_build_translation_inputs(n,o,a){return _build_translation_inputs(this,n,o,a)}}class M2M100Tokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(a=>this.languageRegex.test(a)).map(a=>a.slice(2,-2)),this.lang_to_token=a=>`__${a}__`}_build_translation_inputs(n,o,a){return _build_translation_inputs(this,n,o,a)}}const WHISPER_LANGUAGES=[["en","english"],["zh","chinese"],["de","german"],["es","spanish"],["ru","russian"],["ko","korean"],["fr","french"],["ja","japanese"],["pt","portuguese"],["tr","turkish"],["pl","polish"],["ca","catalan"],["nl","dutch"],["ar","arabic"],["sv","swedish"],["it","italian"],["id","indonesian"],["hi","hindi"],["fi","finnish"],["vi","vietnamese"],["he","hebrew"],["uk","ukrainian"],["el","greek"],["ms","malay"],["cs","czech"],["ro","romanian"],["da","danish"],["hu","hungarian"],["ta","tamil"],["no","norwegian"],["th","thai"],["ur","urdu"],["hr","croatian"],["bg","bulgarian"],["lt","lithuanian"],["la","latin"],["mi","maori"],["ml","malayalam"],["cy","welsh"],["sk","slovak"],["te","telugu"],["fa","persian"],["lv","latvian"],["bn","bengali"],["sr","serbian"],["az","azerbaijani"],["sl","slovenian"],["kn","kannada"],["et","estonian"],["mk","macedonian"],["br","breton"],["eu","basque"],["is","icelandic"],["hy","armenian"],["ne","nepali"],["mn","mongolian"],["bs","bosnian"],["kk","kazakh"],["sq","albanian"],["sw","swahili"],["gl","galician"],["mr","marathi"],["pa","punjabi"],["si","sinhala"],["km","khmer"],["sn","shona"],["yo","yoruba"],["so","somali"],["af","afrikaans"],["oc","occitan"],["ka","georgian"],["be","belarusian"],["tg","tajik"],["sd","sindhi"],["gu","gujarati"],["am","amharic"],["yi","yiddish"],["lo","lao"],["uz","uzbek"],["fo","faroese"],["ht","haitian creole"],["ps","pashto"],["tk","turkmen"],["nn","nynorsk"],["mt","maltese"],["sa","sanskrit"],["lb","luxembourgish"],["my","myanmar"],["bo","tibetan"],["tl","tagalog"],["mg","malagasy"],["as","assamese"],["tt","tatar"],["haw","hawaiian"],["ln","lingala"],["ha","hausa"],["ba","bashkir"],["jw","javanese"],["su","sundanese"]],WHISPER_LANGUAGE_MAPPING=new Map(WHISPER_LANGUAGES),WHISPER_TO_LANGUAGE_CODE_MAPPING=new Map([...WHISPER_LANGUAGES.map(([f,n])=>[n,f]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);class WhisperTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"_default_chat_template",'{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}')}_decode_asr(o,{return_timestamps:a=!1,return_language:l=!1,time_precision:p=null,force_full_sequences:u=!0}={}){if(p===null)throw Error("Must specify time_precision");let h=null;const g=a==="word";function c(){return{language:h,timestamp:[null,null],text:""}}const s=[];let t=c(),e=0;const r=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let i=[],d=[],m=!1,_=null;const b=new Set(this.all_special_ids);for(const w of o){const S=w.tokens,E=g?w.token_timestamps:null;let O=null,v=r;if("stride"in w){const[D,L,C]=w.stride;if(e-=L,_=D-C,L&&(v=L/p+r),C)for(let U=S.length-1;U>=0;--U){const N=S[U];if(N>=r){if(O!==null&&(N-r)*p<_)break;O=N}}}let M=[],$=[];for(let D=0;D<S.length;++D){const L=S[D];if(b.has(L)){const C=this.decode([L]),U=WHISPER_LANGUAGE_MAPPING.get(C.slice(2,-2));if(U!==void 0){if(h!==null&&U!==h&&!a){i.push(M);const N=this.findLongestCommonSequence(i)[0],j=this.decode(N);t.text=j,s.push(t),i=[],M=[],t=c()}h=t.language=U}}else if(L>=r){const C=(L-r)*p+e,U=round(C,2);if(O!==null&&L>=O)m=!0;else if(m||i.length>0&&L<v)m=!1;else if(t.timestamp[0]===null)t.timestamp[0]=U;else if(U!==t.timestamp[0]){t.timestamp[1]=U,i.push(M),g&&d.push($);const[N,j]=this.findLongestCommonSequence(i,d),J=this.decode(N);t.text=J,g&&(t.words=this.collateWordTimestamps(N,j,h)),s.push(t),i=[],M=[],d=[],$=[],t=c()}}else if(M.push(L),g){let C=round(E[D]+e,2),U;D+1<E.length?U=round(E[D+1]+e,2):U=null,$.push([C,U])}}if("stride"in w){const[D,L,C]=w.stride;e+=D-C}M.length>0?(i.push(M),g&&d.push($)):i.every(D=>D.length===0)&&(t=c(),i=[],M=[],d=[],$=[])}if(i.length>0){if(u&&a)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[w,S]=this.findLongestCommonSequence(i,d),E=this.decode(w);t.text=E,g&&(t.words=this.collateWordTimestamps(w,S,h)),s.push(t)}let y=Object.create(null);const T=s.map(w=>w.text).join("");if(a||l){for(let w=0;w<s.length;++w){const S=s[w];a||delete S.timestamp,l||delete S.language}if(g){const w=[];for(const S of s)for(const E of S.words)w.push(E);y={chunks:w}}else y={chunks:s}}return[T,y]}findLongestCommonSequence(o,a=null){let l=o[0],p=l.length,u=[];const h=Array.isArray(a)&&a.length>0;let g=h?[]:null,c=h?a[0]:null;for(let s=1;s<o.length;++s){const t=o[s];let e=0,r=[p,p,0,0];const i=t.length;for(let w=1;w<p+i;++w){const S=w/1e4,E=Math.max(0,p-w),O=Math.min(p,p+i-w),v=l.slice(E,O),M=Math.max(0,w-p),$=Math.min(i,w),D=t.slice(M,$);if(v.length!==D.length)throw new Error("There is a bug within whisper `decode_asr` function, please report it. Dropping to prevent bad inference.");const L=v.filter((U,N)=>U===D[N]).length,C=L/w+S;L>1&&C>e&&(e=C,r=[E,O,M,$])}const[d,m,_,b]=r,y=Math.floor((m+d)/2),T=Math.floor((b+_)/2);u.push(...l.slice(0,y)),l=t.slice(T),p=l.length,h&&(g.push(...c.slice(0,y)),c=a[s].slice(T))}return u.push(...l),h?(g.push(...c),[u,g]):[u,[]]}collateWordTimestamps(o,a,l){const[p,u,h]=this.combineTokensIntoWords(o,l),g=[];for(let c=0;c<p.length;++c){const s=h[c];g.push({text:p[c],timestamp:[a[s.at(0)][0],a[s.at(-1)][1]]})}return g}combineTokensIntoWords(o,a,l=`"'“¡¿([{-`,p=`"'.。,，!！?？:：”)]}、`){a=a??"english";let u,h,g;return["chinese","japanese","thai","lao","myanmar"].includes(a)?[u,h,g]=this.splitTokensOnUnicode(o):[u,h,g]=this.splitTokensOnSpaces(o),this.mergePunctuations(u,h,g,l,p)}decode(o,a){let l;return a&&a.decode_with_timestamps?(o instanceof Tensor&&(o=prepareTensorForDecode(o)),l=this.decodeWithTimestamps(o,a)):l=super.decode(o,a),l}decodeWithTimestamps(o,a){const l=(a==null?void 0:a.time_precision)??.02,p=Array.from(this.all_special_ids).at(-1)+1;let u=[[]];for(const h of o)if(h>=p){const g=round((h-p)*l,2);u.push(`<|${g}|>`),u.push([])}else u[u.length-1].push(h);return u=u.map(h=>typeof h=="string"?h:super.decode(h,a)),u.join("")}splitTokensOnUnicode(o){const a=this.decode(o,{decode_with_timestamps:!0}),l="�",p=[],u=[],h=[];let g=[],c=[],s=0;for(let t=0;t<o.length;++t){const e=o[t];g.push(e),c.push(t);const r=this.decode(g,{decode_with_timestamps:!0});(!r.includes(l)||a[s+r.indexOf(l)]===l)&&(p.push(r),u.push(g),h.push(c),g=[],c=[],s+=r.length)}return[p,u,h]}splitTokensOnSpaces(o){const[a,l,p]=this.splitTokensOnUnicode(o),u=[],h=[],g=[],c=new RegExp(`^[${PUNCTUATION_REGEX}]$`,"gu");for(let s=0;s<a.length;++s){const t=a[s],e=l[s],r=p[s],i=e[0]>=this.model.tokens_to_ids.get("<|endoftext|>"),d=t.startsWith(" "),m=t.trim(),_=c.test(m);if(i||d||_||u.length===0)u.push(t),h.push(e),g.push(r);else{const b=u.length-1;u[b]+=t,h[b].push(...e),g[b].push(...r)}}return[u,h,g]}mergePunctuations(o,a,l,p,u){const h=structuredClone(o),g=structuredClone(a),c=structuredClone(l);let s=h.length-2,t=h.length-1;for(;s>=0;)h[s].startsWith(" ")&&p.includes(h[s].trim())?(h[t]=h[s]+h[t],g[t]=mergeArrays(g[s],g[t]),c[t]=mergeArrays(c[s],c[t]),h[s]="",g[s]=[],c[s]=[]):t=s,--s;for(s=0,t=1;t<h.length;)!h[s].endsWith(" ")&&u.includes(h[t])?(h[s]+=h[t],g[s]=mergeArrays(g[s],g[t]),c[s]=mergeArrays(c[s],c[t]),h[t]="",g[t]=[],c[t]=[]):s=t,++t;return[h.filter(e=>e),g.filter(e=>e.length>0),c.filter(e=>e.length>0)]}get_decoder_prompt_ids({language:o=null,task:a=null,no_timestamps:l=!0}={}){const p=[];if(o){o=o.toLowerCase();let u=WHISPER_TO_LANGUAGE_CODE_MAPPING.get(o);if(u===void 0)if(WHISPER_LANGUAGE_MAPPING.has(o))u=o;else{const c=o.length===2?WHISPER_LANGUAGE_MAPPING.keys():WHISPER_LANGUAGE_MAPPING.values();throw new Error(`Language "${o}" is not supported. Must be one of: ${JSON.stringify(c)}`)}const h=this.model.tokens_to_ids.get(`<|${u}|>`);if(h===void 0)throw new Error(`Unable to find language "${u}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);p.push(h)}else p.push(null);if(a){if(a=a.toLowerCase(),a!=="transcribe"&&a!=="translate")throw new Error(`Task "${a}" is not supported. Must be one of: ["transcribe", "translate"]`);const u=this.model.tokens_to_ids.get(`<|${a}|>`);if(u===void 0)throw new Error(`Unable to find task "${a}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);p.push(u)}else p.push(null);if(l){const u=this.model.tokens_to_ids.get("<|notimestamps|>");if(u===void 0)throw new Error('Unable to find "<|notimestamps|>" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.');p.push(u)}return p.map((u,h)=>[h+1,u]).filter(u=>u[1]!==null)}}class CodeGenTokenizer extends PreTrainedTokenizer{}class CLIPTokenizer extends PreTrainedTokenizer{}class SiglipTokenizer extends PreTrainedTokenizer{}class MarianTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter(a=>this.languageRegex.test(a)),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(n){if(n===null)return null;const[o,...a]=n.trim().split(this.languageRegex);if(a.length===0)return super._encode_text(o);if(a.length===2){const[l,p]=a;return this.supported_language_codes.includes(l)||console.warn(`Unsupported language code "${l}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),mergeArrays([l],super._encode_text(p))}}}class Wav2Vec2CTCTokenizer extends PreTrainedTokenizer{}class BlenderbotTokenizer extends PreTrainedTokenizer{constructor(){super(...arguments);Z(this,"_default_chat_template","{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ '  ' }}{% endif %}{% endfor %}{{ eos_token }}")}}class BlenderbotSmallTokenizer extends BlenderbotTokenizer{}class SpeechT5Tokenizer extends PreTrainedTokenizer{}class NougatTokenizer extends PreTrainedTokenizer{}class VitsTokenizer extends PreTrainedTokenizer{constructor(n,o){super(n,o),this.decoder=new VitsDecoder({})}}class AutoTokenizer{static async from_pretrained(n,{quantized:o=!0,progress_callback:a=null,config:l=null,cache_dir:p=null,local_files_only:u=!1,revision:h="main",legacy:g=null}={}){var r;const[c,s]=await loadTokenizer(n,{quantized:o,progress_callback:a,config:l,cache_dir:p,local_files_only:u,revision:h,legacy:g}),t=((r=s.tokenizer_class)==null?void 0:r.replace(/Fast$/,""))??"PreTrainedTokenizer";let e=this.TOKENIZER_CLASS_MAPPING[t];return e||(console.warn(`Unknown tokenizer class "${t}", attempting to construct from base class.`),e=PreTrainedTokenizer),new e(c,s)}}Z(AutoTokenizer,"TOKENIZER_CLASS_MAPPING",{T5Tokenizer,DistilBertTokenizer,CamembertTokenizer,DebertaTokenizer,DebertaV2Tokenizer,BertTokenizer,HerbertTokenizer,ConvBertTokenizer,RoFormerTokenizer,XLMTokenizer,ElectraTokenizer,MobileBertTokenizer,SqueezeBertTokenizer,AlbertTokenizer,GPT2Tokenizer,BartTokenizer,MBartTokenizer,MBart50Tokenizer,RobertaTokenizer,WhisperTokenizer,CodeGenTokenizer,CLIPTokenizer,SiglipTokenizer,MarianTokenizer,BloomTokenizer,NllbTokenizer,M2M100Tokenizer,LlamaTokenizer,CodeLlamaTokenizer,XLMRobertaTokenizer,MPNetTokenizer,FalconTokenizer,GPTNeoXTokenizer,EsmTokenizer,Wav2Vec2CTCTokenizer,BlenderbotTokenizer,BlenderbotSmallTokenizer,SpeechT5Tokenizer,NougatTokenizer,VitsTokenizer,Qwen2Tokenizer,GemmaTokenizer,PreTrainedTokenizer});async function loadConfig(f,n){return await getModelJSON(f,"config.json",!0,n)}class PretrainedConfig{constructor(n){this.model_type=null,this.is_encoder_decoder=!1,Object.assign(this,n)}static async from_pretrained(n,{progress_callback:o=null,config:a=null,cache_dir:l=null,local_files_only:p=!1,revision:u="main"}={}){let h=a??await loadConfig(n,{progress_callback:o,config:a,cache_dir:l,local_files_only:p,revision:u});return new this(h)}}class AutoConfig{static async from_pretrained(...n){return PretrainedConfig.from_pretrained(...n)}}class LogitsProcessorList extends Callable{constructor(){super(),this.processors=[]}push(n){this.processors.push(n)}extend(n){this.processors.push(...n)}_call(n,o){for(let a of o)this.processors.forEach(l=>l(n,a))}[Symbol.iterator](){return this.processors.values()}}class LogitsProcessor extends Callable{_call(n,o){throw Error("`_call` should be implemented in a subclass")}}class ForceTokensLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.force_token_map=Object.fromEntries(n??[])}_call(n,o){let a=this.force_token_map[n.length];return exists(a)&&(o.data.fill(-1/0),o.data[a]=0),o}}class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.bos_token_id=n}_call(n,o){return n.length===1&&(o.data.fill(-1/0),o.data[this.bos_token_id]=0),o}}class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.max_length=n,this.forced_eos_token_id=o}_call(n,o){}}class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.begin_suppress_tokens=n,this.begin_index=o}_call(n,o){if(n.length===this.begin_index)for(let a of this.begin_suppress_tokens)o.data[a]=-1/0;return o}}class WhisperTimeStampLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.eos_token_id=n.eos_token_id,this.no_timestamps_token_id=n.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(n.forced_decoder_ids||[]).length+2,n.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=n.max_initial_timestamp_index}_call(n,o){const a=o.data;if(a[this.no_timestamps_token_id]=-1/0,n.length===this.begin_index-1)return a.fill(-1/0),a[this.timestamp_begin]=0,o;const l=n.slice(this.begin_index),p=l.length>=1&&l[l.length-1]>=this.timestamp_begin,u=l.length<2||l[l.length-2]>=this.timestamp_begin;if(p&&(u?a.subarray(this.timestamp_begin).fill(-1/0):a.subarray(0,this.eos_token_id).fill(-1/0)),n.length===this.begin_index&&this.max_initial_timestamp_index!==null){const s=this.timestamp_begin+this.max_initial_timestamp_index;a.subarray(s+1).fill(-1/0)}const h=log_softmax(a),g=Math.log(h.subarray(this.timestamp_begin).map(Math.exp).reduce((s,t)=>s+t)),c=max(h.subarray(0,this.timestamp_begin))[0];return g>c&&a.subarray(0,this.timestamp_begin).fill(-1/0),o}}class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.no_repeat_ngram_size=n}getNgrams(n){const o=n.length,a=[];for(let p=0;p<o+1-this.no_repeat_ngram_size;++p){const u=[];for(let h=0;h<this.no_repeat_ngram_size;++h)u.push(n[p+h]);a.push(u)}const l=new Map;for(const p of a){const u=p.slice(0,p.length-1),h=JSON.stringify(u),g=l.get(h)??[];g.push(p[p.length-1]),l.set(h,g)}return l}getGeneratedNgrams(n,o){const a=o.slice(o.length+1-this.no_repeat_ngram_size,o.length);return n.get(JSON.stringify(a))??[]}calcBannedNgramTokens(n){const o=[];if(n.length+1<this.no_repeat_ngram_size)return o;{const a=this.getNgrams(n);return this.getGeneratedNgrams(a,n)}}_call(n,o){const a=this.calcBannedNgramTokens(n);for(const l of a)o.data[l]=-1/0;return o}}class RepetitionPenaltyLogitsProcessor extends LogitsProcessor{constructor(n){super(),this.penalty=n}_call(n,o){for(const a of n)o.data[a]<0?o.data[a]*=this.penalty:o.data[a]/=this.penalty;return o}}class MinLengthLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.min_length=n,this.eos_token_id=Array.isArray(o)?o:[o]}_call(n,o){if(n.length<this.min_length)for(const a of this.eos_token_id)o.data[a]=-1/0;return o}}class MinNewTokensLengthLogitsProcessor extends LogitsProcessor{constructor(n,o,a){super(),this.prompt_length_to_skip=n,this.min_new_tokens=o,this.eos_token_id=Array.isArray(a)?a:[a]}_call(n,o){if(n.length-this.prompt_length_to_skip<this.min_new_tokens)for(const l of this.eos_token_id)o.data[l]=-1/0;return o}}class NoBadWordsLogitsProcessor extends LogitsProcessor{constructor(n,o){super(),this.bad_words_ids=n,this.eos_token_id=Array.isArray(o)?o:[o]}_call(n,o){for(const a of this.bad_words_ids){let l=!0;for(let p=1;p<=a.length-1&&a.length<n.length;++p)if(a.at(-p-1)!==n.at(-p)){l=!1;break}l&&(o.data[a.at(-1)]=-1/0)}return o}}const GenerationConfig=class{constructor(f={}){this.max_length=f.max_length??20,this.max_new_tokens=f.max_new_tokens??null,this.min_length=f.min_length??0,this.min_new_tokens=f.min_new_tokens??null,this.early_stopping=f.early_stopping??!1,this.max_time=f.max_time??null,this.do_sample=f.do_sample??!1,this.num_beams=f.num_beams??1,this.num_beam_groups=f.num_beam_groups??1,this.penalty_alpha=f.penalty_alpha??null,this.use_cache=f.use_cache??!0,this.temperature=f.temperature??1,this.top_k=f.top_k??50,this.top_p=f.top_p??1,this.typical_p=f.typical_p??1,this.epsilon_cutoff=f.epsilon_cutoff??0,this.eta_cutoff=f.eta_cutoff??0,this.diversity_penalty=f.diversity_penalty??0,this.repetition_penalty=f.repetition_penalty??1,this.encoder_repetition_penalty=f.encoder_repetition_penalty??1,this.length_penalty=f.length_penalty??1,this.no_repeat_ngram_size=f.no_repeat_ngram_size??0,this.bad_words_ids=f.bad_words_ids??null,this.force_words_ids=f.force_words_ids??null,this.renormalize_logits=f.renormalize_logits??!1,this.constraints=f.constraints??null,this.forced_bos_token_id=f.forced_bos_token_id??null,this.forced_eos_token_id=f.forced_eos_token_id??null,this.remove_invalid_values=f.remove_invalid_values??!1,this.exponential_decay_length_penalty=f.exponential_decay_length_penalty??null,this.suppress_tokens=f.suppress_tokens??null,this.begin_suppress_tokens=f.begin_suppress_tokens??null,this.forced_decoder_ids=f.forced_decoder_ids??null,this.num_return_sequences=f.num_return_sequences??1,this.output_attentions=f.output_attentions??!1,this.output_hidden_states=f.output_hidden_states??!1,this.output_scores=f.output_scores??!1,this.return_dict_in_generate=f.return_dict_in_generate??!1,this.pad_token_id=f.pad_token_id??null,this.bos_token_id=f.bos_token_id??null,this.eos_token_id=f.eos_token_id??null,this.encoder_no_repeat_ngram_size=f.encoder_no_repeat_ngram_size??0,this.decoder_start_token_id=f.decoder_start_token_id??null,this.generation_kwargs=f.generation_kwargs??{}}};class Sampler extends Callable{constructor(n){super(),this.generation_config=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 a=n.dims.at(-1),l=n.data;if(o===-1)l=l.slice(-a);else{let p=o*a;l=l.slice(p,p+a)}return this.generation_config.temperature>0&&(l=l.map(p=>p/this.generation_config.temperature)),l}randomSelect(n){let o=n.reduce((l,p)=>l+p,0),a=Math.random()*o;for(let l=0;l<n.length;++l)if(a-=n[l],a<=0)return l;return 0}static getSampler(n){if(n.do_sample)return new MultinomialSampler(n);if(n.num_beams>1)return new BeamSearchSampler(n);if(n.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${n.num_return_sequences}.`);return new GreedySampler(n)}}class GreedySampler extends Sampler{sample(n,o=-1){let a=this.getLogits(n,o);return[[max(a)[1],0]]}}class MultinomialSampler extends Sampler{sample(n,o=-1){let a=n.dims.at(-1);this.generation_config.top_k>0&&(a=Math.min(this.generation_config.top_k,a));const l=this.getLogits(n,o),p=getTopItems(l,a),u=softmax(p.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},()=>{const h=this.randomSelect(u);return[p[h][0],Math.log(u[h])]})}}class BeamSearchSampler extends Sampler{sample(n,o=-1){let a=n.dims.at(-1);this.generation_config.top_k>0&&(a=Math.min(this.generation_config.top_k,a));const l=this.getLogits(n,o),p=getTopItems(l,a),u=softmax(p.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},(h,g)=>[p[g][0],Math.log(u[g])])}}const{InferenceSession,Tensor:ONNXTensor,env}=ONNX,MODEL_TYPES={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4,MaskGeneration:5},MODEL_TYPE_MAPPING=new Map,MODEL_NAME_TO_CLASS_MAPPING=new Map,MODEL_CLASS_TO_NAME_MAPPING=new Map;async function constructSession(f,n,o){let a=`onnx/${n}${o.quantized?"_quantized":""}.onnx`,l=await getModelFile(f,a,!0,o);try{return await InferenceSession.create(l,{executionProviders})}catch(p){if(executionProviders.length===1&&executionProviders[0]==="wasm")throw p;return console.warn(p),console.warn("Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback. "),await InferenceSession.create(l,{executionProviders:["wasm"]})}}function validateInputs(f,n){const o=Object.create(null),a=[];for(const u of f.inputNames){const h=n[u];if(!(h instanceof Tensor)){a.push(u);continue}o[u]=env.wasm.proxy?h.clone():h}if(a.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${a.join(", ")}.`);const l=Object.keys(n).length,p=f.inputNames.length;if(l>p){let u=Object.keys(n).filter(h=>!f.inputNames.includes(h));console.warn(`WARNING: Too many inputs were provided (${l} > ${p}). The following inputs will be ignored: "${u.join(", ")}".`)}return o}async function sessionRun(f,n){const o=validateInputs(f,n);try{let a=await f.run(o);return a=replaceTensors(a),a}catch(a){throw console.error(`An error occurred during model execution: "${a}".`),console.error("Inputs given to model:",o),a}}function replaceTensors(f){for(let n in f)f[n]instanceof ONNXTensor?f[n]=new Tensor(f[n]):typeof f[n]=="object"&&replaceTensors(f[n]);return f}function toI64Tensor(f){if(f instanceof Tensor)return f;if(f.length===0)throw Error("items must be non-empty");if(Array.isArray(f[0])){if(f.some(n=>n.length!==f[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' and/or 'truncation=True' to have batched tensors with the same length.");return new Tensor("int64",BigInt64Array.from(f.flat().map(n=>BigInt(n))),[f.length,f[0].length])}else return new Tensor("int64",BigInt64Array.from(f.map(n=>BigInt(n))),[1,f.length])}function prepareAttentionMask(f,n){let o=f.config.pad_token_id??null,a=f.config.eos_token_id??null;isIntegralNumber(a)&&(a=[a]);let l=n.indexOf(o)!==-1,p=a===null||!a.includes(o);if(l&&p){let u=BigInt64Array.from(n.data.map(h=>h!=o));return new Tensor("int64",u,n.dims)}else return ones_like(n)}function preparePositionIds(f,n,o){if(!f.inputNames.includes("position_ids"))return;const a=new BigInt64Array(n.attention_mask.data.length);for(let l=0;l<n.attention_mask.dims[0];++l){let p=l*n.attention_mask.dims[1],u=BigInt(0);for(let h=0;h<n.attention_mask.dims[1];++h){const g=p+h;n.attention_mask.data[g]===0n?a[g]=BigInt(1):(a[g]=u,u+=n.attention_mask.data[g])}}n.position_ids=new Tensor("int64",a,n.attention_mask.dims),o&&(n.position_ids=n.position_ids.slice(null,-1).unsqueeze_(-1))}function boolTensor(f){return new Tensor("bool",[f],[1])}async function seq2seqForward(f,n){let{encoder_outputs:o,past_key_values:a}=n;o||(o=(await encoderForward(f,n)).last_hidden_state);let l={input_ids:n.decoder_input_ids,encoder_hidden_states:o};const p=!!a;f.decoder_merged_session.inputNames.includes("use_cache_branch")&&(l.use_cache_branch=boolTensor(p)),f.decoder_merged_session.inputNames.includes("encoder_attention_mask")&&(l.encoder_attention_mask=n.attention_mask),preparePositionIds(f.decoder_merged_session,l,p),f.addPastKeyValues(l,a);const u=await sessionRun(f.decoder_merged_session,l);let h=u.logits;a=f.getPastKeyValues(u,a);const g=f.getAttentions(u);return new Seq2SeqLMOutput({logits:h,past_key_values:a,encoder_outputs:o,...g})}function seq2seqStartBeams(f,n,o,a){let l=[],p=0;const u=f.requires_attention_mask??!0;let h=o.decoder_input_ids??o.decoder_start_token_id??o.bos_token_id??o.eos_token_id;h instanceof Tensor?h=h.tolist().flat():Array.isArray(h)||(h=[h]);for(let g of n){g.dims=[1,...g.dims];let c={inputs:g,encoder_outputs:null,prev_model_outputs:null,output_token_ids:h,done:!1,score:0,id:p++};u&&(c.attention_mask=prepareAttentionMask(f,g)),l.push(c)}return l}async function seq2seqRunBeam(f,n){var u;const o=f.main_input_name;let a=n.output_token_ids;n.prev_model_outputs&&(a=a.slice(-1));let l={[o]:n.inputs,decoder_input_ids:toI64Tensor(a),encoder_outputs:n.encoder_outputs,past_key_values:(u=n.prev_model_outputs)==null?void 0:u.past_key_values};n.attention_mask&&(l.attention_mask=n.attention_mask);let p=await f.forward(l);return n.prev_model_outputs=p,n.encoder_outputs=p.encoder_outputs,p}function seq2seqUpdatebeam(f,n){f.output_token_ids=[...f.output_token_ids,n]}async function encoderForward(f,n){const o=Object.create(null);for(const a of f.session.inputNames)o[a]=n[a];return f.session.inputNames.includes("token_type_ids")&&!o.token_type_ids&&(o.token_type_ids=new Tensor("int64",new BigInt64Array(o.input_ids.data.length),o.input_ids.dims)),await sessionRun(f.session,o)}async function decoderForward(f,n){let{input_ids:o,past_key_values:a,attention_mask:l}=n,p={input_ids:o,attention_mask:l??prepareAttentionMask(f,o)};const u=!!a;f.session.inputNames.includes("use_cache_branch")&&(p.use_cache_branch=boolTensor(u)),preparePositionIds(f.session,p,u),f.addPastKeyValues(p,a);let h=await sessionRun(f.session,p),g=h.logits;return a=f.getPastKeyValues(h,a),{logits:g,past_key_values:a}}function decoderStartBeams(f,n,o,a,l){let p=[],u=0;for(let h of n){let g=h.tolist().map(Number);h.dims=[1,...h.dims];let c;l?(c=l[u],c.dims=[1,...c.dims]):c=prepareAttentionMask(f,h);let s={input:h,model_input_ids:h,attention_mask:c,prev_model_outputs:null,output_token_ids:g,num_output_tokens:a,done:!1,score:0,id:u++};p.push(s)}return p}async function decoderRunBeam(f,n){var p;let o=new BigInt64Array(n.output_token_ids.length).fill(1n),a={input_ids:n.model_input_ids,attention_mask:new Tensor("int64",o,[1,o.length]),past_key_values:(p=n.prev_model_outputs)==null?void 0:p.past_key_values},l=await f.forward(a);return n.prev_model_outputs=l,l}function decoderUpdatebeam(f,n){f.output_token_ids=[...f.output_token_ids,n],f.model_input_ids=new Tensor("int64",[BigInt(n)],[1,1])}class PreTrainedModel extends Callable{constructor(o,a){super();Z(this,"main_input_name","input_ids");this.config=o,this.session=a;const l=MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor),p=MODEL_TYPE_MAPPING.get(l);this.can_generate=!1,this._runBeam=null,this._getStartBeams=null,this._updateBeam=null,this._forward=null,p===MODEL_TYPES.DecoderOnly?(this.can_generate=!0,this._runBeam=decoderRunBeam,this._getStartBeams=decoderStartBeams,this._updateBeam=decoderUpdatebeam,this._forward=decoderForward):p===MODEL_TYPES.Seq2Seq||p===MODEL_TYPES.Vision2Seq?(this.can_generate=!0,this._runBeam=seq2seqRunBeam,this._getStartBeams=seq2seqStartBeams,this._updateBeam=seq2seqUpdatebeam,this._forward=seq2seqForward):p===MODEL_TYPES.EncoderDecoder?this._forward=encoderForward:this._forward=encoderForward}async dispose(){const o=[];for(let a of Object.keys(this)){const l=this[a];l instanceof InferenceSession&&o.push(l.handler.dispose())}return await Promise.all(o)}static async from_pretrained(o,{quantized:a=!0,progress_callback:l=null,config:p=null,cache_dir:u=null,local_files_only:h=!1,revision:g="main",model_file_name:c=null}={}){let s={quantized:a,progress_callback:l,config:p,cache_dir:u,local_files_only:h,revision:g,model_file_name:c};const t=MODEL_CLASS_TO_NAME_MAPPING.get(this),e=MODEL_TYPE_MAPPING.get(t);let r;return e===MODEL_TYPES.DecoderOnly?r=await Promise.all([AutoConfig.from_pretrained(o,s),constructSession(o,s.model_file_name??"decoder_model_merged",s),getModelJSON(o,"generation_config.json",!1,s)]):e===MODEL_TYPES.Seq2Seq||e===MODEL_TYPES.Vision2Seq?r=await Promise.all([AutoConfig.from_pretrained(o,s),constructSession(o,"encoder_model",s),constructSession(o,"decoder_model_merged",s),getModelJSON(o,"generation_config.json",!1,s)]):e===MODEL_TYPES.MaskGeneration?r=await Promise.all([AutoConfig.from_pretrained(o,s),constructSession(o,"vision_encoder",s),constructSession(o,"prompt_encoder_mask_decoder",s)]):e===MODEL_TYPES.EncoderDecoder?r=await Promise.all([AutoConfig.from_pretrained(o,s),constructSession(o,"encoder_model",s),constructSession(o,"decoder_model_merged",s)]):(e!==MODEL_TYPES.EncoderOnly&&console.warn(`Model type for '${t??(p==null?void 0:p.model_type)}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`),r=await Promise.all([AutoConfig.from_pretrained(o,s),constructSession(o,s.model_file_name??"model",s)])),new this(...r)}async _call(o){return await this.forward(o)}async forward(o){return await this._forward(this,o)}_get_logits_processor(o,a,l=null){const p=new LogitsProcessorList;if(o.repetition_penalty!==null&&o.repetition_penalty!==1&&p.push(new RepetitionPenaltyLogitsProcessor(o.repetition_penalty)),o.no_repeat_ngram_size!==null&&o.no_repeat_ngram_size>0&&p.push(new NoRepeatNGramLogitsProcessor(o.no_repeat_ngram_size)),o.bad_words_ids!==null&&p.push(new NoBadWordsLogitsProcessor(o.bad_words_ids,o.eos_token_id)),o.min_length!==null&&o.eos_token_id!==null&&o.min_length>0&&p.push(new MinLengthLogitsProcessor(o.min_length,o.eos_token_id)),o.min_new_tokens!==null&&o.eos_token_id!==null&&o.min_new_tokens>0&&p.push(new MinNewTokensLengthLogitsProcessor(a,o.min_new_tokens,o.eos_token_id)),o.forced_bos_token_id!==null&&p.push(new ForcedBOSTokenLogitsProcessor(o.forced_bos_token_id)),o.forced_eos_token_id!==null&&p.push(new ForcedEOSTokenLogitsProcessor(o.max_length,o.forced_eos_token_id)),o.begin_suppress_tokens!==null){let u=a>1||o.forced_bos_token_id===null?a:a+1;o.forced_decoder_ids!==null&&(u+=o.forced_decoder_ids[o.forced_decoder_ids.length-1][0]),p.push(new SuppressTokensAtBeginLogitsProcessor(o.begin_suppress_tokens,u))}return o.forced_decoder_ids!==null&&p.push(new ForceTokensLogitsProcessor(o.forced_decoder_ids)),l!==null&&p.extend(l),p}_get_generation_config(o){let a=new GenerationConfig(this.config);return"generation_config"in this&&Object.assign(a,this.generation_config),o!==null&&Object.assign(a,o),a}async generate(o,a=null,l=null,{inputs_attention_mask:p=null}={}){if(!this.can_generate){let _=`The current model class (${MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const b=this.config.model_type,y=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(b)??MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES.get(b)??MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES.get(b)??MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES.get(b);throw y&&(_+=` Please use the following class instead: '${y[0]}'`),Error(_)}if(!(o instanceof Tensor)&&!isTypedArray(o)&&!Array.isArray(o))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${o.constructor.name}".`);let u;if(this.config.is_encoder_decoder)u=0;else if(u=o instanceof Tensor?o.dims.at(-1):o.length,u===0)throw Error("Must supply a non-empty array of input token ids.");a=this._get_generation_config(a),l=l??new LogitsProcessorList,l=this._get_logits_processor(a,u,l);let h=a.eos_token_id;h!==null&&!Array.isArray(h)&&(h=[h]);let g=1;const c=g+(a.max_new_tokens??1/0),s=Number.isInteger(a.max_length)&&(a.max_new_tokens??null)===null;let t=Sampler.getSampler(a),e=this.getStartBeams(o,a,g,p);for(;e.some(m=>!m.done)&&g<c;){let m=[];for(let _ of e){if(_.done){m.push(_);continue}if(s&&_.output_token_ids.length>=a.max_length){_.done=!0,m.push(_);continue}let b=await this.runBeam(_);a.output_attentions&&this.addAttentionsToBeam(_,b),a.output_scores;let y=b.logits.slice(null,-1,null);l(_.output_token_ids,y);let T=t(y);for(let[w,S]of T){let E={..._};this.updateBeam(E,w),E.score+=S,h&&h.includes(w)&&(E.done=!0),m.push(E)}}++g,m=this.groupBeams(m).map(_=>_.sort((b,y)=>y.score-b.score).slice(0,a.num_beams)),e=m.flat(),a.callback_function&&a.callback_function(e)}const r=this.groupBeams(e),i=m=>r.map(_=>a.num_return_sequences>1?_.slice(0,a.num_return_sequences).map(b=>b[m]):[_[0][m]]).flat(),d=i("output_token_ids");if(a.return_dict_in_generate){const m=i("decoder_attentions"),_=i("cross_attentions");return{sequences:d,decoder_attentions:m,cross_attentions:_}}else return d}addAttentionsToBeam(o,a){if(this.config.is_encoder_decoder){if(!a.cross_attentions||a.cross_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce cross-attentions. This is most likely because the model was not exported with `output_attentions=True`.");o.cross_attentions||(o.cross_attentions=[]),o.cross_attentions.push(a.cross_attentions)}if(!a.decoder_attentions||a.decoder_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce decoder-attentions. This is most likely because the model was not exported with `output_attentions=True`.");o.decoder_attentions||(o.decoder_attentions=[]),o.decoder_attentions.push(a.decoder_attentions)}groupBeams(o){const a=Object.create(null);for(const l of o)a[l.id]===void 0?a[l.id]=[l]:a[l.id].push(l);return Object.values(a)}getPastKeyValues(o,a){const l=Object.create(null);for(const p in o)if(p.startsWith("present")){let u=p.replace("present","past_key_values");a&&p.includes("encoder")?l[u]=a[u]:l[u]=o[p]}return l}getAttentions(o){const a=Object.create(null);for(const l of["cross_attentions","decoder_attentions"]){const p=[];for(const u in o)if(u.startsWith(l)){const h=u.split(".").pop();p[h]=o[u]}a[l]=p}return a}addPastKeyValues(o,a){if(a)Object.assign(o,a);else if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??!0)){let p=[1,this.num_encoder_heads,0,this.encoder_dim_kv],u=[1,this.num_decoder_heads,0,this.decoder_dim_kv];for(let h=0;h<this.num_decoder_layers;++h)o[`past_key_values.${h}.encoder.key`]=new Tensor("float32",[],p),o[`past_key_values.${h}.encoder.value`]=new Tensor("float32",[],p),o[`past_key_values.${h}.decoder.key`]=new Tensor("float32",[],u),o[`past_key_values.${h}.decoder.value`]=new Tensor("float32",[],u)}else if(this.config.model_type==="falcon"){let p=[1*this.num_heads,0,this.dim_kv];for(let u=0;u<this.num_layers;++u)o[`past_key_values.${u}.key`]=new Tensor("float32",[],p),o[`past_key_values.${u}.value`]=new Tensor("float32",[],p)}else if(this.config.multi_query){let p=[1*this.num_heads,0,2*this.dim_kv];for(let u=0;u<this.num_layers;++u)o[`past_key_values.${u}.key_value`]=new Tensor("float32",[],p)}else if(this.config.model_type==="bloom"){let p=[1*this.num_heads,this.dim_kv,0],u=[1*this.num_heads,0,this.dim_kv];for(let h=0;h<this.num_layers;++h)o[`past_key_values.${h}.key`]=new Tensor("float32",[],p),o[`past_key_values.${h}.value`]=new Tensor("float32",[],u)}else{let p=[1,this.num_heads,0,this.dim_kv];for(let u=0;u<this.num_layers;++u)o[`past_key_values.${u}.key`]=new Tensor("float32",[],p),o[`past_key_values.${u}.value`]=new Tensor("float32",[],p)}}getStartBeams(o,a,l,p){return this._getStartBeams(this,o,a,l,p)}async runBeam(o){return await this._runBeam(this,o)}updateBeam(o,a){return this._updateBeam(o,a)}}class ModelOutput{}class BertPreTrainedModel extends PreTrainedModel{}class BertModel extends BertPreTrainedModel{}class BertForMaskedLM extends BertPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class BertForSequenceClassification extends BertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class BertForTokenClassification extends BertPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class BertForQuestionAnswering extends BertPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class NomicBertPreTrainedModel extends PreTrainedModel{}class NomicBertModel extends NomicBertPreTrainedModel{}class RoFormerPreTrainedModel extends PreTrainedModel{}class RoFormerModel extends RoFormerPreTrainedModel{}class RoFormerForMaskedLM extends RoFormerPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class RoFormerForSequenceClassification extends RoFormerPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class RoFormerForTokenClassification extends RoFormerPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class RoFormerForQuestionAnswering extends RoFormerPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class ConvBertPreTrainedModel extends PreTrainedModel{}class ConvBertModel extends ConvBertPreTrainedModel{}class ConvBertForMaskedLM extends ConvBertPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class ConvBertForSequenceClassification extends ConvBertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class ConvBertForTokenClassification extends ConvBertPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class ConvBertForQuestionAnswering extends ConvBertPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class ElectraPreTrainedModel extends PreTrainedModel{}class ElectraModel extends ElectraPreTrainedModel{}class ElectraForMaskedLM extends ElectraPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class ElectraForSequenceClassification extends ElectraPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class ElectraForTokenClassification extends ElectraPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class ElectraForQuestionAnswering extends ElectraPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class CamembertPreTrainedModel extends PreTrainedModel{}class CamembertModel extends CamembertPreTrainedModel{}class CamembertForMaskedLM extends CamembertPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class CamembertForSequenceClassification extends CamembertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class CamembertForTokenClassification extends CamembertPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class CamembertForQuestionAnswering extends CamembertPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class DebertaPreTrainedModel extends PreTrainedModel{}class DebertaModel extends DebertaPreTrainedModel{}class DebertaForMaskedLM extends DebertaPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class DebertaForSequenceClassification extends DebertaPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class DebertaForTokenClassification extends DebertaPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class DebertaForQuestionAnswering extends DebertaPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class DebertaV2PreTrainedModel extends PreTrainedModel{}class DebertaV2Model extends DebertaV2PreTrainedModel{}class DebertaV2ForMaskedLM extends DebertaV2PreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class DebertaV2ForSequenceClassification extends DebertaV2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class DebertaV2ForTokenClassification extends DebertaV2PreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class DebertaV2ForQuestionAnswering extends DebertaV2PreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class DistilBertPreTrainedModel extends PreTrainedModel{}class DistilBertModel extends DistilBertPreTrainedModel{}class DistilBertForSequenceClassification extends DistilBertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class DistilBertForTokenClassification extends DistilBertPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class DistilBertForQuestionAnswering extends DistilBertPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class DistilBertForMaskedLM extends DistilBertPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class EsmPreTrainedModel extends PreTrainedModel{}class EsmModel extends EsmPreTrainedModel{}class EsmForMaskedLM extends EsmPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class EsmForSequenceClassification extends EsmPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class EsmForTokenClassification extends EsmPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class MobileBertPreTrainedModel extends PreTrainedModel{}class MobileBertModel extends MobileBertPreTrainedModel{}class MobileBertForMaskedLM extends MobileBertPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class MobileBertForSequenceClassification extends MobileBertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class MobileBertForQuestionAnswering extends MobileBertPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class MPNetPreTrainedModel extends PreTrainedModel{}class MPNetModel extends MPNetPreTrainedModel{}class MPNetForMaskedLM extends MPNetPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class MPNetForSequenceClassification extends MPNetPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class MPNetForTokenClassification extends MPNetPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class MPNetForQuestionAnswering extends MPNetPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class SqueezeBertPreTrainedModel extends PreTrainedModel{}class SqueezeBertModel extends SqueezeBertPreTrainedModel{}class SqueezeBertForMaskedLM extends SqueezeBertPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class SqueezeBertForSequenceClassification extends SqueezeBertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class SqueezeBertForQuestionAnswering extends SqueezeBertPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class AlbertPreTrainedModel extends PreTrainedModel{}class AlbertModel extends AlbertPreTrainedModel{}class AlbertForSequenceClassification extends AlbertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class AlbertForQuestionAnswering extends AlbertPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class AlbertForMaskedLM extends AlbertPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class T5PreTrainedModel extends PreTrainedModel{}class T5Model extends T5PreTrainedModel{}class T5ForConditionalGeneration extends T5PreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,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}}class LongT5PreTrainedModel extends PreTrainedModel{}class LongT5Model extends LongT5PreTrainedModel{}class LongT5ForConditionalGeneration extends LongT5PreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,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}}class MT5PreTrainedModel extends PreTrainedModel{}class MT5Model extends MT5PreTrainedModel{}class MT5ForConditionalGeneration extends MT5PreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,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}}class BartPretrainedModel extends PreTrainedModel{}class BartModel extends BartPretrainedModel{}class BartForConditionalGeneration extends BartPretrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class BartForSequenceClassification extends BartPretrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class MBartPreTrainedModel extends PreTrainedModel{}class MBartModel extends MBartPreTrainedModel{}class MBartForConditionalGeneration extends MBartPreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class MBartForSequenceClassification extends MBartPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class MBartForCausalLM extends MBartPreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class BlenderbotPreTrainedModel extends PreTrainedModel{}class BlenderbotModel extends BlenderbotPreTrainedModel{}class BlenderbotForConditionalGeneration extends BlenderbotPreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class BlenderbotSmallPreTrainedModel extends PreTrainedModel{}class BlenderbotSmallModel extends BlenderbotSmallPreTrainedModel{}class BlenderbotSmallForConditionalGeneration extends BlenderbotSmallPreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class RobertaPreTrainedModel extends PreTrainedModel{}class RobertaModel extends RobertaPreTrainedModel{}class RobertaForMaskedLM extends RobertaPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class RobertaForSequenceClassification extends RobertaPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class RobertaForTokenClassification extends RobertaPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class RobertaForQuestionAnswering extends RobertaPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class XLMPreTrainedModel extends PreTrainedModel{}class XLMModel extends XLMPreTrainedModel{}class XLMWithLMHeadModel extends XLMPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class XLMForSequenceClassification extends XLMPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class XLMForTokenClassification extends XLMPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class XLMForQuestionAnswering extends XLMPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class XLMRobertaPreTrainedModel extends PreTrainedModel{}class XLMRobertaModel extends XLMRobertaPreTrainedModel{}class XLMRobertaForMaskedLM extends XLMRobertaPreTrainedModel{async _call(n){return new MaskedLMOutput(await super._call(n))}}class XLMRobertaForSequenceClassification extends XLMRobertaPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class XLMRobertaForTokenClassification extends XLMRobertaPreTrainedModel{async _call(n){return new TokenClassifierOutput(await super._call(n))}}class XLMRobertaForQuestionAnswering extends XLMRobertaPreTrainedModel{async _call(n){return new QuestionAnsweringModelOutput(await super._call(n))}}class ASTPreTrainedModel extends PreTrainedModel{}class ASTModel extends ASTPreTrainedModel{}class ASTForAudioClassification extends ASTPreTrainedModel{}class WhisperPreTrainedModel extends PreTrainedModel{}class WhisperModel extends WhisperPreTrainedModel{}class WhisperForConditionalGeneration extends WhisperPreTrainedModel{constructor(o,a,l,p){super(o,a);Z(this,"requires_attention_mask",!1);Z(this,"main_input_name","input_features");this.decoder_merged_session=l,this.generation_config=p,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(o,a=null,l=null){if(a=this._get_generation_config(a),a.return_timestamps??(a.return_timestamps=!1),a.return_timestamps&&(l=[new WhisperTimeStampLogitsProcessor(a)]),a.return_token_timestamps&&(a.output_attentions=!0,a.return_dict_in_generate=!0,a.task==="translate"&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),!a.alignment_heads))throw new Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");const p=await super.generate(o,a,l);return a.return_token_timestamps&&a.alignment_heads&&(p.token_timestamps=this._extract_token_timestamps(p,a.alignment_heads,a.num_frames)),p}_extract_token_timestamps(o,a,l=null,p=.02){if(!o.cross_attentions)throw new Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");let u=this.config.median_filter_width;u===void 0&&(console.warn("Model config has no `median_filter_width`, using default value of 7."),u=7);const h=o.cross_attentions.map(s=>{let t=Array.from({length:this.config.decoder_layers},(_,b)=>cat(s.map(y=>y[b]),2)),e=stack(a.map(([_,b])=>l?t[_].slice(null,b,null,[0,l]):t[_].slice(null,b)));e=e.transpose(1,0,2,3);let[r,i]=std_mean(e,-2,0,!0),d=e.clone();for(let _=0;_<d.dims[0];++_){let b=d[_];for(let y=0;y<b.dims[0];++y){let T=b[y];const w=r[_][y][0],S=i[_][y][0];for(let E=0;E<T.dims[0];++E){let O=T[E];for(let v=0;v<O.data.length;++v)O.data[v]=(O.data[v]-S.data[v])/w.data[v];O.data.set(medianFilter(O.data,u))}}}return mean(d,1)}),g=[o.sequences.length,o.sequences[0].length],c=new Tensor("float32",new Float32Array(g[0]*g[1]),g);for(let s=0;s<g[0];++s){const t=h[s].neg().squeeze_(0);let[e,r]=dynamicTimeWarping(t),i=Array.from({length:e.length-1},(_,b)=>e[b+1]-e[b]),d=mergeArrays([1],i).map(_=>!!_),m=[];for(let _=0;_<d.length;++_)d[_]&&m.push(r[_]*p);c[s].data.set(m,1)}return c}}class VisionEncoderDecoderModel extends PreTrainedModel{constructor(o,a,l,p){super(o,a);Z(this,"main_input_name","pixel_values");this.decoder_merged_session=l,this.generation_config=p;const u=this.config.encoder,h=this.config.decoder,g=u.model_type;(MODEL_MAPPING_NAMES_ENCODER_ONLY.get(g)??MODEL_MAPPING_NAMES_ENCODER_DECODER.get(g))||console.warn(`Model type for encoder '${g}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`);const s=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(h.model_type);if(!s)throw new Error(`Unable to construct \`VisionEncoderDecoder\` due to unsupported decoder: "${this.config.decoder.model_type}"`);const t=s[1],e=new t(h,l,p);this.add_encoder_pkv="num_decoder_layers"in e,this.add_encoder_pkv?(this.num_decoder_layers=e.num_decoder_layers,this.num_decoder_heads=e.num_decoder_heads,this.decoder_dim_kv=e.decoder_dim_kv,this.num_encoder_layers=e.num_encoder_layers,this.num_encoder_heads=e.num_encoder_heads,this.encoder_dim_kv=e.encoder_dim_kv):(this.num_layers=e.num_layers,this.num_heads=e.num_heads,this.dim_kv=e.dim_kv)}}class CLIPPreTrainedModel extends PreTrainedModel{}class CLIPModel extends CLIPPreTrainedModel{}class CLIPTextModelWithProjection extends CLIPPreTrainedModel{static async from_pretrained(n,o={}){return o.model_file_name??(o.model_file_name="text_model"),super.from_pretrained(n,o)}}class CLIPVisionModelWithProjection extends CLIPPreTrainedModel{static async from_pretrained(n,o={}){return o.model_file_name??(o.model_file_name="vision_model"),super.from_pretrained(n,o)}}class SiglipPreTrainedModel extends PreTrainedModel{}class SiglipModel extends SiglipPreTrainedModel{}class SiglipTextModel extends SiglipPreTrainedModel{static async from_pretrained(n,o={}){return o.model_file_name??(o.model_file_name="text_model"),super.from_pretrained(n,o)}}class SiglipVisionModel extends CLIPPreTrainedModel{static async from_pretrained(n,o={}){return o.model_file_name??(o.model_file_name="vision_model"),super.from_pretrained(n,o)}}class ChineseCLIPPreTrainedModel extends PreTrainedModel{}class ChineseCLIPModel extends ChineseCLIPPreTrainedModel{}class CLIPSegPreTrainedModel extends PreTrainedModel{}class CLIPSegModel extends CLIPSegPreTrainedModel{}class CLIPSegForImageSegmentation extends CLIPSegPreTrainedModel{}class GPT2PreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class GPT2Model extends GPT2PreTrainedModel{}class GPT2LMHeadModel extends GPT2PreTrainedModel{}class GPTNeoPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_heads,this.num_layers=this.config.num_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class GPTNeoModel extends GPTNeoPreTrainedModel{}class GPTNeoForCausalLM extends GPTNeoPreTrainedModel{}class GPTNeoXPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class GPTNeoXModel extends GPTNeoXPreTrainedModel{}class GPTNeoXForCausalLM extends GPTNeoXPreTrainedModel{}class GPTJPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class GPTJModel extends GPTJPreTrainedModel{}class GPTJForCausalLM extends GPTJPreTrainedModel{}class GPTBigCodePreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class GPTBigCodeModel extends GPTBigCodePreTrainedModel{}class GPTBigCodeForCausalLM extends GPTBigCodePreTrainedModel{}class CodeGenPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class CodeGenModel extends CodeGenPreTrainedModel{}class CodeGenForCausalLM extends CodeGenPreTrainedModel{}class LlamaPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class LlamaModel extends LlamaPreTrainedModel{}class LlamaForCausalLM extends LlamaPreTrainedModel{}class Qwen2PreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class Qwen2Model extends Qwen2PreTrainedModel{}class Qwen2ForCausalLM extends Qwen2PreTrainedModel{}class PhiPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class PhiModel extends PhiPreTrainedModel{}class PhiForCausalLM extends PhiPreTrainedModel{}class BloomPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.hidden_size/this.num_heads}}class BloomModel extends BloomPreTrainedModel{}class BloomForCausalLM extends BloomPreTrainedModel{}class MptPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_heads,this.num_layers=this.config.n_layers,this.dim_kv=this.config.d_model/this.num_heads}}class MptModel extends MptPreTrainedModel{}class MptForCausalLM extends MptPreTrainedModel{}class OPTPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class OPTModel extends OPTPreTrainedModel{}class OPTForCausalLM extends OPTPreTrainedModel{}class ViTPreTrainedModel extends PreTrainedModel{}class ViTModel extends ViTPreTrainedModel{}class ViTForImageClassification extends ViTPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class VitMattePreTrainedModel extends PreTrainedModel{}class VitMatteForImageMatting extends VitMattePreTrainedModel{async _call(n){return new ImageMattingOutput(await super._call(n))}}class MobileViTPreTrainedModel extends PreTrainedModel{}class MobileViTModel extends MobileViTPreTrainedModel{}class MobileViTForImageClassification extends MobileViTPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class OwlViTPreTrainedModel extends PreTrainedModel{}class OwlViTModel extends OwlViTPreTrainedModel{}class OwlViTForObjectDetection extends OwlViTPreTrainedModel{}class Owlv2PreTrainedModel extends PreTrainedModel{}class Owlv2Model extends Owlv2PreTrainedModel{}class Owlv2ForObjectDetection extends Owlv2PreTrainedModel{}class BeitPreTrainedModel extends PreTrainedModel{}class BeitModel extends BeitPreTrainedModel{}class BeitForImageClassification extends BeitPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class DetrPreTrainedModel extends PreTrainedModel{}class DetrModel extends DetrPreTrainedModel{}class DetrForObjectDetection extends DetrPreTrainedModel{async _call(n){return new DetrObjectDetectionOutput(await super._call(n))}}class DetrForSegmentation extends DetrPreTrainedModel{async _call(n){return new DetrSegmentationOutput(await super._call(n))}}class DetrObjectDetectionOutput extends ModelOutput{constructor({logits:n,pred_boxes:o}){super(),this.logits=n,this.pred_boxes=o}}class DetrSegmentationOutput extends ModelOutput{constructor({logits:n,pred_boxes:o,pred_masks:a}){super(),this.logits=n,this.pred_boxes=o,this.pred_masks=a}}class TableTransformerPreTrainedModel extends PreTrainedModel{}class TableTransformerModel extends TableTransformerPreTrainedModel{}class TableTransformerForObjectDetection extends TableTransformerPreTrainedModel{async _call(n){return new TableTransformerObjectDetectionOutput(await super._call(n))}}class TableTransformerObjectDetectionOutput extends DetrObjectDetectionOutput{}class DeiTPreTrainedModel extends PreTrainedModel{}class DeiTModel extends DeiTPreTrainedModel{}class DeiTForImageClassification extends DeiTPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class ResNetPreTrainedModel extends PreTrainedModel{}class ResNetModel extends ResNetPreTrainedModel{}class ResNetForImageClassification extends ResNetPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class SwinPreTrainedModel extends PreTrainedModel{}class SwinModel extends SwinPreTrainedModel{}class SwinForImageClassification extends SwinPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class Swin2SRPreTrainedModel extends PreTrainedModel{}class Swin2SRModel extends Swin2SRPreTrainedModel{}class Swin2SRForImageSuperResolution extends Swin2SRPreTrainedModel{}class DPTPreTrainedModel extends PreTrainedModel{}class DPTModel extends DPTPreTrainedModel{}class DPTForDepthEstimation extends DPTPreTrainedModel{}class DepthAnythingPreTrainedModel extends PreTrainedModel{}class DepthAnythingForDepthEstimation extends DepthAnythingPreTrainedModel{}class GLPNPreTrainedModel extends PreTrainedModel{}class GLPNModel extends GLPNPreTrainedModel{}class GLPNForDepthEstimation extends GLPNPreTrainedModel{}class DonutSwinPreTrainedModel extends PreTrainedModel{}class DonutSwinModel extends DonutSwinPreTrainedModel{}class ConvNextPreTrainedModel extends PreTrainedModel{}class ConvNextModel extends ConvNextPreTrainedModel{}class ConvNextForImageClassification extends ConvNextPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class ConvNextV2PreTrainedModel extends PreTrainedModel{}class ConvNextV2Model extends ConvNextV2PreTrainedModel{}class ConvNextV2ForImageClassification extends ConvNextV2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class Dinov2PreTrainedModel extends PreTrainedModel{}class Dinov2Model extends Dinov2PreTrainedModel{}class Dinov2ForImageClassification extends Dinov2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class YolosPreTrainedModel extends PreTrainedModel{}class YolosModel extends YolosPreTrainedModel{}class YolosForObjectDetection extends YolosPreTrainedModel{async _call(n){return new YolosObjectDetectionOutput(await super._call(n))}}class YolosObjectDetectionOutput extends ModelOutput{constructor({logits:n,pred_boxes:o}){super(),this.logits=n,this.pred_boxes=o}}class SamPreTrainedModel extends PreTrainedModel{}class SamModel extends SamPreTrainedModel{constructor(n,o,a){super(n,o),this.prompt_encoder_mask_decoder=a}async get_image_embeddings({pixel_values:n}){return await encoderForward(this,{pixel_values:n})}async forward(n){if((!n.image_embeddings||!n.image_positional_embeddings)&&(n={...n,...await this.get_image_embeddings(n)}),!n.input_labels){const o=n.input_points.dims.slice(0,-1),a=o.reduce((l,p)=>l*p,1);n.input_labels=new Tensor("int64",new BigInt64Array(a).fill(1n),o)}return await sessionRun(this.prompt_encoder_mask_decoder,{input_points:n.input_points,input_labels:n.input_labels,image_embeddings:n.image_embeddings,image_positional_embeddings:n.image_positional_embeddings})}async _call(n){return new SamImageSegmentationOutput(await super._call(n))}}class SamImageSegmentationOutput extends ModelOutput{constructor({iou_scores:n,pred_masks:o}){super(),this.iou_scores=n,this.pred_masks=o}}class MarianPreTrainedModel extends PreTrainedModel{}class MarianModel extends MarianPreTrainedModel{}class MarianMTModel extends MarianPreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class M2M100PreTrainedModel extends PreTrainedModel{}class M2M100Model extends M2M100PreTrainedModel{}class M2M100ForConditionalGeneration extends M2M100PreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class Wav2Vec2PreTrainedModel extends PreTrainedModel{}class Wav2Vec2Model extends Wav2Vec2PreTrainedModel{}class Wav2Vec2ForCTC extends Wav2Vec2PreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class Wav2Vec2ForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class Wav2Vec2BertPreTrainedModel extends PreTrainedModel{}class Wav2Vec2BertModel extends Wav2Vec2BertPreTrainedModel{}class Wav2Vec2BertForCTC extends Wav2Vec2BertPreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class Wav2Vec2BertForSequenceClassification extends Wav2Vec2BertPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class HubertModel extends Wav2Vec2PreTrainedModel{}class HubertForCTC extends Wav2Vec2PreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class HubertForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class WavLMPreTrainedModel extends PreTrainedModel{}class WavLMModel extends WavLMPreTrainedModel{}class WavLMForCTC extends WavLMPreTrainedModel{async _call(n){return new CausalLMOutput(await super._call(n))}}class WavLMForSequenceClassification extends WavLMPreTrainedModel{async _call(n){return new SequenceClassifierOutput(await super._call(n))}}class SpeechT5PreTrainedModel extends PreTrainedModel{}class SpeechT5ForSpeechToText extends SpeechT5PreTrainedModel{}class SpeechT5ForTextToSpeech extends SpeechT5PreTrainedModel{constructor(n,o,a,l){super(n,o),this.decoder_merged_session=a,this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.hidden_size/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.hidden_size/this.num_encoder_heads}async generate_speech(n,o,{threshold:a=.5,minlenratio:l=0,maxlenratio:p=20,vocoder:u=null}={}){const h={input_ids:n},{encoder_outputs:g,encoder_attention_mask:c}=await encoderForward(this,h),s=g.dims[1]/this.config.reduction_factor,t=Math.floor(s*p),e=Math.floor(s*l),r=this.config.num_mel_bins;let i=[],d=null,m=null,_=0;for(;;){++_;const T=boolTensor(!!m);let w;m?w=m.output_sequence_out:w=new Tensor("float32",new Float32Array(r),[1,1,r]);let S={use_cache_branch:T,output_sequence:w,encoder_attention_mask:c,speaker_embeddings:o,encoder_hidden_states:g};this.addPastKeyValues(S,d),m=await sessionRun(this.decoder_merged_session,S),d=this.getPastKeyValues(m,d);const{prob:E,spectrum:O}=m;if(i.push(O),_>=e&&(Array.from(E.data).filter(v=>v>=a).length>0||_>=t))break}const b=cat(i),{waveform:y}=await sessionRun(u.session,{spectrogram:b});return{spectrogram:b,waveform:y}}}class SpeechT5HifiGan extends PreTrainedModel{constructor(){super(...arguments);Z(this,"main_input_name","spectrogram")}}class TrOCRPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_encoder_layers=this.num_decoder_layers=this.config.decoder_layers,this.num_encoder_heads=this.num_decoder_heads=this.config.decoder_attention_heads,this.encoder_dim_kv=this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads}}class TrOCRForCausalLM extends TrOCRPreTrainedModel{}class MistralPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class MistralModel extends MistralPreTrainedModel{}class MistralForCausalLM extends MistralPreTrainedModel{}class FalconPreTrainedModel extends PreTrainedModel{constructor(n,o,a){super(n,o),this.generation_config=a,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class FalconModel extends FalconPreTrainedModel{}class FalconForCausalLM extends FalconPreTrainedModel{}class ClapPreTrainedModel extends PreTrainedModel{}class ClapModel extends ClapPreTrainedModel{}class ClapTextModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(n,o={}){return o.model_file_name??(o.model_file_name="text_model"),super.from_pretrained(n,o)}}class ClapAudioModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(n,o={}){return o.model_file_name??(o.model_file_name="audio_model"),super.from_pretrained(n,o)}}class VitsPreTrainedModel extends PreTrainedModel{}class VitsModel extends VitsPreTrainedModel{async _call(n){return new VitsModelOutput(await super._call(n))}}class SegformerPreTrainedModel extends PreTrainedModel{}class SegformerForImageClassification extends SegformerPreTrainedModel{}class SegformerForSemanticSegmentation extends SegformerPreTrainedModel{}class PretrainedMixin{static async from_pretrained(n,{quantized:o=!0,progress_callback:a=null,config:l=null,cache_dir:p=null,local_files_only:u=!1,revision:h="main",model_file_name:g=null}={}){let c={quantized:o,progress_callback:a,config:l,cache_dir:p,local_files_only:u,revision:h,model_file_name:g};if(l=await AutoConfig.from_pretrained(n,c),c.config||(c.config=l),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let s of this.MODEL_CLASS_MAPPINGS){const t=s.get(l.model_type);if(t)return await t[1].from_pretrained(n,c)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${l.model_type}", attempting to construct from base class.`),await PreTrainedModel.from_pretrained(n,c);throw Error(`Unsupported model type: ${l.model_type}`)}}Z(PretrainedMixin,"MODEL_CLASS_MAPPINGS",null),Z(PretrainedMixin,"BASE_IF_FAIL",!1);const MODEL_MAPPING_NAMES_ENCODER_ONLY=new Map([["bert",["BertModel",BertModel]],["nomic_bert",["NomicBertModel",NomicBertModel]],["roformer",["RoFormerModel",RoFormerModel]],["electra",["ElectraModel",ElectraModel]],["esm",["EsmModel",EsmModel]],["convbert",["ConvBertModel",ConvBertModel]],["camembert",["CamembertModel",CamembertModel]],["deberta",["DebertaModel",DebertaModel]],["deberta-v2",["DebertaV2Model",DebertaV2Model]],["mpnet",["MPNetModel",MPNetModel]],["albert",["AlbertModel",AlbertModel]],["distilbert",["DistilBertModel",DistilBertModel]],["roberta",["RobertaModel",RobertaModel]],["xlm",["XLMModel",XLMModel]],["xlm-roberta",["XLMRobertaModel",XLMRobertaModel]],["clap",["ClapModel",ClapModel]],["clip",["CLIPModel",CLIPModel]],["clipseg",["CLIPSegModel",CLIPSegModel]],["chinese_clip",["ChineseCLIPModel",ChineseCLIPModel]],["siglip",["SiglipModel",SiglipModel]],["mobilebert",["MobileBertModel",MobileBertModel]],["squeezebert",["SqueezeBertModel",SqueezeBertModel]],["wav2vec2",["Wav2Vec2Model",Wav2Vec2Model]],["wav2vec2-bert",["Wav2Vec2BertModel",Wav2Vec2BertModel]],["hubert",["HubertModel",HubertModel]],["wavlm",["WavLMModel",WavLMModel]],["audio-spectrogram-transformer",["ASTModel",ASTModel]],["vits",["VitsModel",VitsModel]],["detr",["DetrModel",DetrModel]],["table-transformer",["TableTransformerModel",TableTransformerModel]],["vit",["ViTModel",ViTModel]],["mobilevit",["MobileViTModel",MobileViTModel]],["owlvit",["OwlViTModel",OwlViTModel]],["owlv2",["Owlv2Model",Owlv2Model]],["beit",["BeitModel",BeitModel]],["deit",["DeiTModel",DeiTModel]],["convnext",["ConvNextModel",ConvNextModel]],["convnextv2",["ConvNextV2Model",ConvNextV2Model]],["dinov2",["Dinov2Model",Dinov2Model]],["resnet",["ResNetModel",ResNetModel]],["swin",["SwinModel",SwinModel]],["swin2sr",["Swin2SRModel",Swin2SRModel]],["donut-swin",["DonutSwinModel",DonutSwinModel]],["yolos",["YolosModel",YolosModel]],["dpt",["DPTModel",DPTModel]],["glpn",["GLPNModel",GLPNModel]],["hifigan",["SpeechT5HifiGan",SpeechT5HifiGan]]]),MODEL_MAPPING_NAMES_ENCODER_DECODER=new Map([["t5",["T5Model",T5Model]],["longt5",["LongT5Model",LongT5Model]],["mt5",["MT5Model",MT5Model]],["bart",["BartModel",BartModel]],["mbart",["MBartModel",MBartModel]],["marian",["MarianModel",MarianModel]],["whisper",["WhisperModel",WhisperModel]],["m2m_100",["M2M100Model",M2M100Model]],["blenderbot",["BlenderbotModel",BlenderbotModel]],["blenderbot-small",["BlenderbotSmallModel",BlenderbotSmallModel]]]),MODEL_MAPPING_NAMES_DECODER_ONLY=new Map([["bloom",["BloomModel",BloomModel]],["gpt2",["GPT2Model",GPT2Model]],["gptj",["GPTJModel",GPTJModel]],["gpt_bigcode",["GPTBigCodeModel",GPTBigCodeModel]],["gpt_neo",["GPTNeoModel",GPTNeoModel]],["gpt_neox",["GPTNeoXModel",GPTNeoXModel]],["codegen",["CodeGenModel",CodeGenModel]],["llama",["LlamaModel",LlamaModel]],["qwen2",["Qwen2Model",Qwen2Model]],["phi",["PhiModel",PhiModel]],["mpt",["MptModel",MptModel]],["opt",["OPTModel",OPTModel]],["mistral",["MistralModel",MistralModel]],["falcon",["FalconModel",FalconModel]]]),MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForSpeechToText",SpeechT5ForSpeechToText]],["whisper",["WhisperForConditionalGeneration",WhisperForConditionalGeneration]]]),MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForTextToSpeech",SpeechT5ForTextToSpeech]]]),MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES=new Map([["vits",["VitsModel",VitsModel]]]),MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForSequenceClassification",BertForSequenceClassification]],["roformer",["RoFormerForSequenceClassification",RoFormerForSequenceClassification]],["electra",["ElectraForSequenceClassification",ElectraForSequenceClassification]],["esm",["EsmForSequenceClassification",EsmForSequenceClassification]],["convbert",["ConvBertForSequenceClassification",ConvBertForSequenceClassification]],["camembert",["CamembertForSequenceClassification",CamembertForSequenceClassification]],["deberta",["DebertaForSequenceClassification",DebertaForSequenceClassification]],["deberta-v2",["DebertaV2ForSequenceClassification",DebertaV2ForSequenceClassification]],["mpnet",["MPNetForSequenceClassification",MPNetForSequenceClassification]],["albert",["AlbertForSequenceClassification",AlbertForSequenceClassification]],["distilbert",["DistilBertForSequenceClassification",DistilBertForSequenceClassification]],["roberta",["RobertaForSequenceClassification",RobertaForSequenceClassification]],["xlm",["XLMForSequenceClassification",XLMForSequenceClassification]],["xlm-roberta",["XLMRobertaForSequenceClassification",XLMRobertaForSequenceClassification]],["bart",["BartForSequenceClassification",BartForSequenceClassification]],["mbart",["MBartForSequenceClassification",MBartForSequenceClassification]],["mobilebert",["MobileBertForSequenceClassification",MobileBertForSequenceClassification]],["squeezebert",["SqueezeBertForSequenceClassification",SqueezeBertForSequenceClassification]]]),MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForTokenClassification",BertForTokenClassification]],["roformer",["RoFormerForTokenClassification",RoFormerForTokenClassification]],["electra",["ElectraForTokenClassification",ElectraForTokenClassification]],["esm",["EsmForTokenClassification",EsmForTokenClassification]],["convbert",["ConvBertForTokenClassification",ConvBertForTokenClassification]],["camembert",["CamembertForTokenClassification",CamembertForTokenClassification]],["deberta",["DebertaForTokenClassification",DebertaForTokenClassification]],["deberta-v2",["DebertaV2ForTokenClassification",DebertaV2ForTokenClassification]],["mpnet",["MPNetForTokenClassification",MPNetForTokenClassification]],["distilbert",["DistilBertForTokenClassification",DistilBertForTokenClassification]],["roberta",["RobertaForTokenClassification",RobertaForTokenClassification]],["xlm",["XLMForTokenClassification",XLMForTokenClassification]],["xlm-roberta",["XLMRobertaForTokenClassification",XLMRobertaForTokenClassification]]]),MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES=new Map([["t5",["T5ForConditionalGeneration",T5ForConditionalGeneration]],["longt5",["LongT5ForConditionalGeneration",LongT5ForConditionalGeneration]],["mt5",["MT5ForConditionalGeneration",MT5ForConditionalGeneration]],["bart",["BartForConditionalGeneration",BartForConditionalGeneration]],["mbart",["MBartForConditionalGeneration",MBartForConditionalGeneration]],["marian",["MarianMTModel",MarianMTModel]],["m2m_100",["M2M100ForConditionalGeneration",M2M100ForConditionalGeneration]],["blenderbot",["BlenderbotForConditionalGeneration",BlenderbotForConditionalGeneration]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",BlenderbotSmallForConditionalGeneration]]]),MODEL_WITH_LM_HEAD_MAPPING_NAMES=new Map([["bloom",["BloomForCausalLM",BloomForCausalLM]],["gpt2",["GPT2LMHeadModel",GPT2LMHeadModel]],["gptj",["GPTJForCausalLM",GPTJForCausalLM]],["gpt_bigcode",["GPTBigCodeForCausalLM",GPTBigCodeForCausalLM]],["gpt_neo",["GPTNeoForCausalLM",GPTNeoForCausalLM]],["gpt_neox",["GPTNeoXForCausalLM",GPTNeoXForCausalLM]],["codegen",["CodeGenForCausalLM",CodeGenForCausalLM]],["llama",["LlamaForCausalLM",LlamaForCausalLM]],["qwen2",["Qwen2ForCausalLM",Qwen2ForCausalLM]],["phi",["PhiForCausalLM",PhiForCausalLM]],["mpt",["MptForCausalLM",MptForCausalLM]],["opt",["OPTForCausalLM",OPTForCausalLM]],["mbart",["MBartForCausalLM",MBartForCausalLM]],["mistral",["MistralForCausalLM",MistralForCausalLM]],["falcon",["FalconForCausalLM",FalconForCausalLM]],["trocr",["TrOCRForCausalLM",TrOCRForCausalLM]]]),MODEL_FOR_MASKED_LM_MAPPING_NAMES=new Map([["bert",["BertForMaskedLM",BertForMaskedLM]],["roformer",["RoFormerForMaskedLM",RoFormerForMaskedLM]],["electra",["ElectraForMaskedLM",ElectraForMaskedLM]],["esm",["EsmForMaskedLM",EsmForMaskedLM]],["convbert",["ConvBertForMaskedLM",ConvBertForMaskedLM]],["camembert",["CamembertForMaskedLM",CamembertForMaskedLM]],["deberta",["DebertaForMaskedLM",DebertaForMaskedLM]],["deberta-v2",["DebertaV2ForMaskedLM",DebertaV2ForMaskedLM]],["mpnet",["MPNetForMaskedLM",MPNetForMaskedLM]],["albert",["AlbertForMaskedLM",AlbertForMaskedLM]],["distilbert",["DistilBertForMaskedLM",DistilBertForMaskedLM]],["roberta",["RobertaForMaskedLM",RobertaForMaskedLM]],["xlm",["XLMWithLMHeadModel",XLMWithLMHeadModel]],["xlm-roberta",["XLMRobertaForMaskedLM",XLMRobertaForMaskedLM]],["mobilebert",["MobileBertForMaskedLM",MobileBertForMaskedLM]],["squeezebert",["SqueezeBertForMaskedLM",SqueezeBertForMaskedLM]]]),MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES=new Map([["bert",["BertForQuestionAnswering",BertForQuestionAnswering]],["roformer",["RoFormerForQuestionAnswering",RoFormerForQuestionAnswering]],["electra",["ElectraForQuestionAnswering",ElectraForQuestionAnswering]],["convbert",["ConvBertForQuestionAnswering",ConvBertForQuestionAnswering]],["camembert",["CamembertForQuestionAnswering",CamembertForQuestionAnswering]],["deberta",["DebertaForQuestionAnswering",DebertaForQuestionAnswering]],["deberta-v2",["DebertaV2ForQuestionAnswering",DebertaV2ForQuestionAnswering]],["mpnet",["MPNetForQuestionAnswering",MPNetForQuestionAnswering]],["albert",["AlbertForQuestionAnswering",AlbertForQuestionAnswering]],["distilbert",["DistilBertForQuestionAnswering",DistilBertForQuestionAnswering]],["roberta",["RobertaForQuestionAnswering",RobertaForQuestionAnswering]],["xlm",["XLMForQuestionAnswering",XLMForQuestionAnswering]],["xlm-roberta",["XLMRobertaForQuestionAnswering",XLMRobertaForQuestionAnswering]],["mobilebert",["MobileBertForQuestionAnswering",MobileBertForQuestionAnswering]],["squeezebert",["SqueezeBertForQuestionAnswering",SqueezeBertForQuestionAnswering]]]),MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",VisionEncoderDecoderModel]]]),MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES=new Map([["vit",["ViTForImageClassification",ViTForImageClassification]],["mobilevit",["MobileViTForImageClassification",MobileViTForImageClassification]],["beit",["BeitForImageClassification",BeitForImageClassification]],["deit",["DeiTForImageClassification",DeiTForImageClassification]],["convnext",["ConvNextForImageClassification",ConvNextForImageClassification]],["convnextv2",["ConvNextV2ForImageClassification",ConvNextV2ForImageClassification]],["dinov2",["Dinov2ForImageClassification",Dinov2ForImageClassification]],["resnet",["ResNetForImageClassification",ResNetForImageClassification]],["swin",["SwinForImageClassification",SwinForImageClassification]],["segformer",["SegformerForImageClassification",SegformerForImageClassification]]]),MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES=new Map([["detr",["DetrForObjectDetection",DetrForObjectDetection]],["table-transformer",["TableTransformerForObjectDetection",TableTransformerForObjectDetection]],["yolos",["YolosForObjectDetection",YolosForObjectDetection]]]),MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES=new Map([["owlvit",["OwlViTForObjectDetection",OwlViTForObjectDetection]],["owlv2",["Owlv2ForObjectDetection",Owlv2ForObjectDetection]]]),MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES=new Map([["detr",["DetrForSegmentation",DetrForSegmentation]],["clipseg",["CLIPSegForImageSegmentation",CLIPSegForImageSegmentation]]]),MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES=new Map([["segformer",["SegformerForSemanticSegmentation",SegformerForSemanticSegmentation]]]),MODEL_FOR_MASK_GENERATION_MAPPING_NAMES=new Map([["sam",["SamModel",SamModel]]]),MODEL_FOR_CTC_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForCTC",Wav2Vec2ForCTC]],["wav2vec2-bert",["Wav2Vec2BertForCTC",Wav2Vec2BertForCTC]],["wavlm",["WavLMForCTC",WavLMForCTC]],["hubert",["HubertForCTC",HubertForCTC]]]),MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Wav2Vec2ForSequenceClassification]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",Wav2Vec2BertForSequenceClassification]],["wavlm",["WavLMForSequenceClassification",WavLMForSequenceClassification]],["hubert",["HubertForSequenceClassification",HubertForSequenceClassification]],["audio-spectrogram-transformer",["ASTForAudioClassification",ASTForAudioClassification]]]),MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES=new Map([["vitmatte",["VitMatteForImageMatting",VitMatteForImageMatting]]]),MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES=new Map([["swin2sr",["Swin2SRForImageSuperResolution",Swin2SRForImageSuperResolution]]]),MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES=new Map([["dpt",["DPTForDepthEstimation",DPTForDepthEstimation]],["depth_anything",["DepthAnythingForDepthEstimation",DepthAnythingForDepthEstimation]],["glpn",["GLPNForDepthEstimation",GLPNForDepthEstimation]]]),MODEL_CLASS_TYPE_MAPPING=[[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_TYPES.EncoderOnly],[MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_TYPES.EncoderDecoder],[MODEL_MAPPING_NAMES_DECODER_ONLY,MODEL_TYPES.DecoderOnly],[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_WITH_LM_HEAD_MAPPING_NAMES,MODEL_TYPES.DecoderOnly],[MODEL_FOR_MASKED_LM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Vision2Seq],[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_MASK_GENERATION_MAPPING_NAMES,MODEL_TYPES.MaskGeneration],[MODEL_FOR_CTC_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly]];for(const[f,n]of MODEL_CLASS_TYPE_MAPPING)for(const[o,a]of f.values())MODEL_TYPE_MAPPING.set(o,n),MODEL_CLASS_TO_NAME_MAPPING.set(a,o),MODEL_NAME_TO_CLASS_MAPPING.set(o,a);const CUSTOM_MAPPING=[["CLIPTextModelWithProjection",CLIPTextModelWithProjection,MODEL_TYPES.EncoderOnly],["CLIPVisionModelWithProjection",CLIPVisionModelWithProjection,MODEL_TYPES.EncoderOnly],["SiglipTextModel",SiglipTextModel,MODEL_TYPES.EncoderOnly],["SiglipVisionModel",SiglipVisionModel,MODEL_TYPES.EncoderOnly],["ClapTextModelWithProjection",ClapTextModelWithProjection,MODEL_TYPES.EncoderOnly],["ClapAudioModelWithProjection",ClapAudioModelWithProjection,MODEL_TYPES.EncoderOnly]];for(const[f,n,o]of CUSTOM_MAPPING)MODEL_TYPE_MAPPING.set(f,o),MODEL_CLASS_TO_NAME_MAPPING.set(n,f),MODEL_NAME_TO_CLASS_MAPPING.set(f,n);class AutoModel extends PretrainedMixin{}Z(AutoModel,"MODEL_CLASS_MAPPINGS",MODEL_CLASS_TYPE_MAPPING.map(n=>n[0])),Z(AutoModel,"BASE_IF_FAIL",!0);class Seq2SeqLMOutput extends ModelOutput{constructor({logits:n,past_key_values:o,encoder_outputs:a,decoder_attentions:l=null,cross_attentions:p=null}){super(),this.logits=n,this.past_key_values=o,this.encoder_outputs=a,this.decoder_attentions=l,this.cross_attentions=p}}class SequenceClassifierOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class TokenClassifierOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class MaskedLMOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class QuestionAnsweringModelOutput extends ModelOutput{constructor({start_logits:n,end_logits:o}){super(),this.start_logits=n,this.end_logits=o}}class CausalLMOutput extends ModelOutput{constructor({logits:n}){super(),this.logits=n}}class ImageMattingOutput extends ModelOutput{constructor({alphas:n}){super(),this.alphas=n}}class VitsModelOutput extends ModelOutput{constructor({waveform:n,spectrogram:o}){super(),this.waveform=n,this.spectrogram=o}}const BROWSER_ENV=typeof self<"u";if(!BROWSER_ENV){if(!sharp)throw new Error("Unable to load image processing library.")}env$1.allowLocalModels=!1;const TOKENIZER_MAPPINGS=new Map;self.addEventListener("message",async f=>{console.log(f.data);let n=f.data.model_id,o=TOKENIZER_MAPPINGS.get(f.data.model_id);o||(o=AutoTokenizer.from_pretrained(f.data.model_id),TOKENIZER_MAPPINGS.set(f.data.model_id,new Promise(s=>{o.then(t=>{switch(t.constructor.name){case"LlamaTokenizer":case"Grok1Tokenizer":t.decoder.decoders.pop();break;case"T5Tokenizer":t.decoder.addPrefixSpace=!1;break}s(t)})})));const a=await o,l=f.data.text,p=performance.now(),u=a.encode(l),h=performance.now();console.log("[INFO]",`Tokenized ${l.length} characters in ${(h-p).toFixed(2)}ms`);let g=u.map(s=>a.decode([s])),c=[];switch(a.constructor.name){case"BertTokenizer":c=g.map((s,t)=>t===0||s.startsWith("##")?0:8),g=g.map(s=>s.replace("##",""));break;case"T5Tokenizer":g.length>0&&g.length!==" "&&(g[0]=g[0].replace(/^ /,""));break}self.postMessage({model_id:n,token_ids:u,decoded:g,margins:c})})})();