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ERR: ${i.map(s=>`[${s.name}] ${s.err}`).join(", ")}`)};class EnvImpl{constructor(){this.wasm={},this.webgl={},this.logLevelInternal="warning"}set logLevel(t){if(t!==void 0){if(typeof t!="string"||["verbose","info","warning","error","fatal"].indexOf(t)===-1)throw new Error(`Unsupported logging level: ${t}`);this.logLevelInternal=t}}get logLevel(){return this.logLevelInternal}}const env$2=new EnvImpl,isBigInt64ArrayAvailable=typeof BigInt64Array<"u"&&typeof BigInt64Array.from=="function",isBigUint64ArrayAvailable=typeof BigUint64Array<"u"&&typeof BigUint64Array.from=="function",NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP=new Map([["float32",Float32Array],["uint8",Uint8Array],["int8",Int8Array],["uint16",Uint16Array],["int16",Int16Array],["int32",Int32Array],["bool",Uint8Array],["float64",Float64Array],["uint32",Uint32Array]]),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP=new Map([[Float32Array,"float32"],[Uint8Array,"uint8"],[Int8Array,"int8"],[Uint16Array,"uint16"],[Int16Array,"int16"],[Int32Array,"int32"],[Float64Array,"float64"],[Uint32Array,"uint32"]]);isBigInt64ArrayAvailable&&(NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set("int64",BigInt64Array),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigInt64Array,"int64")),isBigUint64ArrayAvailable&&(NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set("uint64",BigUint64Array),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigUint64Array,"uint64"));const calculateSize=m=>{let t=1;for(let i=0;i<m.length;i++){const s=m[i];if(typeof s!="number"||!Number.isSafeInteger(s))throw new TypeError(`dims[${i}] must be an integer, got: ${s}`);if(s<0)throw new RangeError(`dims[${i}] must be a non-negative integer, got: ${s}`);t*=s}return t};let Tensor$2=class lt{constructor(t,i,s){let u,d,a;if(typeof t=="string")if(u=t,a=s,t==="string"){if(!Array.isArray(i))throw new TypeError("A string tensor's data must be a string array.");d=i}else{const f=NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.get(t);if(f===void 0)throw new TypeError(`Unsupported tensor type: ${t}.`);if(Array.isArray(i))d=f.from(i);else if(i instanceof f)d=i;else throw new TypeError(`A ${u} tensor's data must be type of ${f}`)}else if(a=i,Array.isArray(t)){if(t.length===0)throw new TypeError("Tensor type cannot be inferred from an empty array.");const f=typeof t[0];if(f==="string")u="string",d=t;else if(f==="boolean")u="bool",d=Uint8Array.from(t);else throw new TypeError(`Invalid element type of data array: ${f}.`)}else{const f=NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.get(t.constructor);if(f===void 0)throw new TypeError(`Unsupported type for tensor data: ${t.constructor}.`);u=f,d=t}if(a===void 0)a=[d.length];else if(!Array.isArray(a))throw new TypeError("A tensor's dims must be a number array");const h=calculateSize(a);if(h!==d.length)throw new Error(`Tensor's size(${h}) does not match data length(${d.length}).`);this.dims=a,this.type=u,this.data=d,this.size=h}static bufferToTensor(t,i){if(t===void 0)throw new Error("Image buffer must be defined");if(i.height===void 0||i.width===void 0)throw new Error("Image height and width must be defined");const{height:s,width:u}=i,d=i.norm;let a,h;d===void 0||d.mean===void 0?a=255:a=d.mean,d===void 0||d.bias===void 0?h=0:h=d.bias;const f=i.bitmapFormat!==void 0?i.bitmapFormat:"RGBA",c=i.tensorFormat!==void 0&&i.tensorFormat!==void 0?i.tensorFormat:"RGB",l=s*u,n=c==="RGBA"?new Float32Array(l*4):new Float32Array(l*3);let e=4,r=0,o=1,p=2,g=3,_=0,b=l,y=l*2,w=-1;f==="RGB"&&(e=3,r=0,o=1,p=2,g=-1),c==="RGBA"?w=l*3:c==="RBG"?(_=0,y=l,b=l*2):c==="BGR"&&(y=0,b=l,_=l*2);for(let S=0;S<l;S++,r+=e,p+=e,o+=e,g+=e)n[_++]=(t[r]+h)/a,n[b++]=(t[o]+h)/a,n[y++]=(t[p]+h)/a,w!==-1&&g!==-1&&(n[w++]=(t[g]+h)/a);return c==="RGBA"?new lt("float32",n,[1,4,s,u]):new lt("float32",n,[1,3,s,u])}static async fromImage(t,i){const s=typeof HTMLImageElement<"u"&&t instanceof HTMLImageElement,u=typeof ImageData<"u"&&t instanceof ImageData,d=typeof 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0&&i.resizedHeight!==void 0?(l=i.resizedHeight,n=i.resizedWidth):(l=t.height,n=t.width),i!==void 0){if(f=i,i.bitmapFormat!==void 0&&i.bitmapFormat!==c)throw new Error("Image input config format must be RGBA for ImageData");f.bitmapFormat="RGBA"}else f.bitmapFormat="RGBA";if(f.height=l,f.width=n,i!==void 0){const e=document.createElement("canvas");e.width=n,e.height=l;const r=e.getContext("2d");if(r!=null)r.putImageData(t,0,0),h=r.getImageData(0,0,n,l).data;else throw new Error("Can not access image data")}else h=t.data}else if(d){if(i===void 0)throw new Error("Please provide image config with format for Imagebitmap");if(i.bitmapFormat!==void 0)throw new Error("Image input config format must be defined for ImageBitmap");const c=document.createElement("canvas").getContext("2d");if(c!=null){const l=t.height,n=t.width;if(c.drawImage(t,0,0,n,l),h=c.getImageData(0,0,n,l).data,i!==void 0){if(i.height!==void 0&&i.height!==l)throw new Error("Image input config height doesn't match ImageBitmap 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0)return lt.bufferToTensor(h,f);throw new Error("Input data provided is not supported - aborted tensor creation")}toImageData(t){var i,s;const u=document.createElement("canvas").getContext("2d");let d;if(u!=null){const a=this.dims[3],h=this.dims[2],f=this.dims[1],c=t!==void 0&&t.format!==void 0?t.format:"RGB",l=t!==void 0&&((i=t.norm)===null||i===void 0?void 0:i.mean)!==void 0?t.norm.mean:255,n=t!==void 0&&((s=t.norm)===null||s===void 0?void 0:s.bias)!==void 0?t.norm.bias:0,e=h*a;if(t!==void 0){if(t.height!==void 0&&t.height!==h)throw new Error("Image output config height doesn't match tensor height");if(t.width!==void 0&&t.width!==a)throw new Error("Image output config width doesn't match tensor width");if(t.format!==void 0&&f===4&&t.format!=="RGBA"||f===3&&t.format!=="RGB"&&t.format!=="BGR")throw new Error("Tensor format doesn't match input tensor dims")}const r=4;let 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x=this.high,M=this.low;return[x>>>24,x>>>16&255,x>>>8&255,255&x,M>>>24,M>>>16&255,M>>>8&255,255&M]},i.fromBytes=function(x,M,N){return N?i.fromBytesLE(x,M):i.fromBytesBE(x,M)},i.fromBytesLE=function(x,M){return new i(x[0]|x[1]<<8|x[2]<<16|x[3]<<24,x[4]|x[5]<<8|x[6]<<16|x[7]<<24,M)},i.fromBytesBE=function(x,M){return new i(x[4]<<24|x[5]<<16|x[6]<<8|x[7],x[0]<<24|x[1]<<16|x[2]<<8|x[3],M)}},1446:(m,t,i)=>{var s,u,d,a=i(2100),h=a.Reader,f=a.Writer,c=a.util,l=a.roots.default||(a.roots.default={});l.onnx=((d={}).Version=(s={},(u=Object.create(s))[s[0]="_START_VERSION"]=0,u[s[1]="IR_VERSION_2017_10_10"]=1,u[s[2]="IR_VERSION_2017_10_30"]=2,u[s[3]="IR_VERSION_2017_11_3"]=3,u[s[4]="IR_VERSION_2019_1_22"]=4,u[s[5]="IR_VERSION"]=5,u),d.AttributeProto=function(){function n(e){if(this.floats=[],this.ints=[],this.strings=[],this.tensors=[],this.graphs=[],e)for(var r=Object.keys(e),o=0;o<r.length;++o)e[r[o]]!=null&&(this[r[o]]=e[r[o]])}return n.prototype.name="",n.prototype.refAttrName="",n.prototype.docString="",n.prototype.type=0,n.prototype.f=0,n.prototype.i=c.Long?c.Long.fromBits(0,0,!1):0,n.prototype.s=c.newBuffer([]),n.prototype.t=null,n.prototype.g=null,n.prototype.floats=c.emptyArray,n.prototype.ints=c.emptyArray,n.prototype.strings=c.emptyArray,n.prototype.tensors=c.emptyArray,n.prototype.graphs=c.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,r){if(r||(r=f.create()),e.name!=null&&e.hasOwnProperty("name")&&r.uint32(10).string(e.name),e.f!=null&&e.hasOwnProperty("f")&&r.uint32(21).float(e.f),e.i!=null&&e.hasOwnProperty("i")&&r.uint32(24).int64(e.i),e.s!=null&&e.hasOwnProperty("s")&&r.uint32(34).bytes(e.s),e.t!=null&&e.hasOwnProperty("t")&&l.onnx.TensorProto.encode(e.t,r.uint32(42).fork()).ldelim(),e.g!=null&&e.hasOwnProperty("g")&&l.onnx.GraphProto.encode(e.g,r.uint32(50).fork()).ldelim(),e.floats!=null&&e.floats.length){r.uint32(58).fork();for(var 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g=e.uint32();switch(g>>>3){case 1:p.name=e.string();break;case 21:p.refAttrName=e.string();break;case 13:p.docString=e.string();break;case 20:p.type=e.int32();break;case 2:p.f=e.float();break;case 3:p.i=e.int64();break;case 4:p.s=e.bytes();break;case 5:p.t=l.onnx.TensorProto.decode(e,e.uint32());break;case 6:p.g=l.onnx.GraphProto.decode(e,e.uint32());break;case 7:if(p.floats&&p.floats.length||(p.floats=[]),(7&g)==2)for(var _=e.uint32()+e.pos;e.pos<_;)p.floats.push(e.float());else p.floats.push(e.float());break;case 8:if(p.ints&&p.ints.length||(p.ints=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.ints.push(e.int64());else p.ints.push(e.int64());break;case 9:p.strings&&p.strings.length||(p.strings=[]),p.strings.push(e.bytes());break;case 10:p.tensors&&p.tensors.length||(p.tensors=[]),p.tensors.push(l.onnx.TensorProto.decode(e,e.uint32()));break;case 11:p.graphs&&p.graphs.length||(p.graphs=[]),p.graphs.push(l.onnx.GraphProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.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")&&(o=l.onnx.TensorProto.verify(e.t)))return"t."+o;if(e.g!=null&&e.hasOwnProperty("g")&&(o=l.onnx.GraphProto.verify(e.g)))return"g."+o;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[] 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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=l.onnx.TensorProto.fromObject(e.t)}if(e.g!=null){if(typeof e.g!="object")throw TypeError(".onnx.AttributeProto.g: object expected");r.g=l.onnx.GraphProto.fromObject(e.g)}if(e.floats){if(!Array.isArray(e.floats))throw TypeError(".onnx.AttributeProto.floats: array expected");r.floats=[];for(var o=0;o<e.floats.length;++o)r.floats[o]=Number(e.floats[o])}if(e.ints){if(!Array.isArray(e.ints))throw TypeError(".onnx.AttributeProto.ints: array 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TypeError(".onnx.AttributeProto.graphs: array expected");for(r.graphs=[],o=0;o<e.graphs.length;++o){if(typeof e.graphs[o]!="object")throw TypeError(".onnx.AttributeProto.graphs: object expected");r.graphs[o]=l.onnx.GraphProto.fromObject(e.graphs[o])}}return r},n.toObject=function(e,r){r||(r={});var o={};if((r.arrays||r.defaults)&&(o.floats=[],o.ints=[],o.strings=[],o.tensors=[],o.graphs=[]),r.defaults){if(o.name="",o.f=0,c.Long){var p=new c.Long(0,0,!1);o.i=r.longs===String?p.toString():r.longs===Number?p.toNumber():p}else o.i=r.longs===String?"0":0;r.bytes===String?o.s="":(o.s=[],r.bytes!==Array&&(o.s=c.newBuffer(o.s))),o.t=null,o.g=null,o.docString="",o.type=r.enums===String?"UNDEFINED":0,o.refAttrName=""}if(e.name!=null&&e.hasOwnProperty("name")&&(o.name=e.name),e.f!=null&&e.hasOwnProperty("f")&&(o.f=r.json&&!isFinite(e.f)?String(e.f):e.f),e.i!=null&&e.hasOwnProperty("i")&&(typeof e.i=="number"?o.i=r.longs===String?String(e.i):e.i:o.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")&&(o.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")&&(o.t=l.onnx.TensorProto.toObject(e.t,r)),e.g!=null&&e.hasOwnProperty("g")&&(o.g=l.onnx.GraphProto.toObject(e.g,r)),e.floats&&e.floats.length){o.floats=[];for(var g=0;g<e.floats.length;++g)o.floats[g]=r.json&&!isFinite(e.floats[g])?String(e.floats[g]):e.floats[g]}if(e.ints&&e.ints.length)for(o.ints=[],g=0;g<e.ints.length;++g)typeof e.ints[g]=="number"?o.ints[g]=r.longs===String?String(e.ints[g]):e.ints[g]:o.ints[g]=r.longs===String?c.Long.prototype.toString.call(e.ints[g]):r.longs===Number?new c.LongBits(e.ints[g].low>>>0,e.ints[g].high>>>0).toNumber():e.ints[g];if(e.strings&&e.strings.length)for(o.strings=[],g=0;g<e.strings.length;++g)o.strings[g]=r.bytes===String?c.base64.encode(e.strings[g],0,e.strings[g].length):r.bytes===Array?Array.prototype.slice.call(e.strings[g]):e.strings[g];if(e.tensors&&e.tensors.length)for(o.tensors=[],g=0;g<e.tensors.length;++g)o.tensors[g]=l.onnx.TensorProto.toObject(e.tensors[g],r);if(e.graphs&&e.graphs.length)for(o.graphs=[],g=0;g<e.graphs.length;++g)o.graphs[g]=l.onnx.GraphProto.toObject(e.graphs[g],r);return e.docString!=null&&e.hasOwnProperty("docString")&&(o.docString=e.docString),e.type!=null&&e.hasOwnProperty("type")&&(o.type=r.enums===String?l.onnx.AttributeProto.AttributeType[e.type]:e.type),e.refAttrName!=null&&e.hasOwnProperty("refAttrName")&&(o.refAttrName=e.refAttrName),o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n.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}(),n}(),d.ValueInfoProto=function(){function n(e){if(e)for(var r=Object.keys(e),o=0;o<r.length;++o)e[r[o]]!=null&&(this[r[o]]=e[r[o]])}return n.prototype.name="",n.prototype.type=null,n.prototype.docString="",n.create=function(e){return new n(e)},n.encode=function(e,r){return r||(r=f.create()),e.name!=null&&e.hasOwnProperty("name")&&r.uint32(10).string(e.name),e.type!=null&&e.hasOwnProperty("type")&&l.onnx.TypeProto.encode(e.type,r.uint32(18).fork()).ldelim(),e.docString!=null&&e.hasOwnProperty("docString")&&r.uint32(26).string(e.docString),r},n.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},n.decode=function(e,r){e instanceof h||(e=h.create(e));for(var o=r===void 0?e.len:e.pos+r,p=new l.onnx.ValueInfoProto;e.pos<o;){var g=e.uint32();switch(g>>>3){case 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e.docString!=null&&(r.docString=String(e.docString)),r},n.toObject=function(e,r){r||(r={});var o={};return r.defaults&&(o.name="",o.type=null,o.docString=""),e.name!=null&&e.hasOwnProperty("name")&&(o.name=e.name),e.type!=null&&e.hasOwnProperty("type")&&(o.type=l.onnx.TypeProto.toObject(e.type,r)),e.docString!=null&&e.hasOwnProperty("docString")&&(o.docString=e.docString),o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n}(),d.NodeProto=function(){function n(e){if(this.input=[],this.output=[],this.attribute=[],e)for(var r=Object.keys(e),o=0;o<r.length;++o)e[r[o]]!=null&&(this[r[o]]=e[r[o]])}return n.prototype.input=c.emptyArray,n.prototype.output=c.emptyArray,n.prototype.name="",n.prototype.opType="",n.prototype.domain="",n.prototype.attribute=c.emptyArray,n.prototype.docString="",n.create=function(e){return new n(e)},n.encode=function(e,r){if(r||(r=f.create()),e.input!=null&&e.input.length)for(var o=0;o<e.input.length;++o)r.uint32(10).string(e.input[o]);if(e.output!=null&&e.output.length)for(o=0;o<e.output.length;++o)r.uint32(18).string(e.output[o]);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(o=0;o<e.attribute.length;++o)l.onnx.AttributeProto.encode(e.attribute[o],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},n.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},n.decode=function(e,r){e instanceof h||(e=h.create(e));for(var o=r===void 0?e.len:e.pos+r,p=new l.onnx.NodeProto;e.pos<o;){var g=e.uint32();switch(g>>>3){case 1:p.input&&p.input.length||(p.input=[]),p.input.push(e.string());break;case 2:p.output&&p.output.length||(p.output=[]),p.output.push(e.string());break;case 3:p.name=e.string();break;case 4:p.opType=e.string();break;case 7:p.domain=e.string();break;case 5:p.attribute&&p.attribute.length||(p.attribute=[]),p.attribute.push(l.onnx.AttributeProto.decode(e,e.uint32()));break;case 6:p.docString=e.string();break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.input!=null&&e.hasOwnProperty("input")){if(!Array.isArray(e.input))return"input: array expected";for(var r=0;r<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 o=l.onnx.AttributeProto.verify(e.attribute[r]);if(o)return"attribute."+o}}return e.docString!=null&&e.hasOwnProperty("docString")&&!c.isString(e.docString)?"docString: string expected":null},n.fromObject=function(e){if(e instanceof l.onnx.NodeProto)return e;var r=new l.onnx.NodeProto;if(e.input){if(!Array.isArray(e.input))throw TypeError(".onnx.NodeProto.input: array expected");r.input=[];for(var o=0;o<e.input.length;++o)r.input[o]=String(e.input[o])}if(e.output){if(!Array.isArray(e.output))throw TypeError(".onnx.NodeProto.output: array expected");for(r.output=[],o=0;o<e.output.length;++o)r.output[o]=String(e.output[o])}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=[],o=0;o<e.attribute.length;++o){if(typeof e.attribute[o]!="object")throw TypeError(".onnx.NodeProto.attribute: object expected");r.attribute[o]=l.onnx.AttributeProto.fromObject(e.attribute[o])}}return e.docString!=null&&(r.docString=String(e.docString)),r},n.toObject=function(e,r){r||(r={});var o={};if((r.arrays||r.defaults)&&(o.input=[],o.output=[],o.attribute=[]),r.defaults&&(o.name="",o.opType="",o.docString="",o.domain=""),e.input&&e.input.length){o.input=[];for(var p=0;p<e.input.length;++p)o.input[p]=e.input[p]}if(e.output&&e.output.length)for(o.output=[],p=0;p<e.output.length;++p)o.output[p]=e.output[p];if(e.name!=null&&e.hasOwnProperty("name")&&(o.name=e.name),e.opType!=null&&e.hasOwnProperty("opType")&&(o.opType=e.opType),e.attribute&&e.attribute.length)for(o.attribute=[],p=0;p<e.attribute.length;++p)o.attribute[p]=l.onnx.AttributeProto.toObject(e.attribute[p],r);return e.docString!=null&&e.hasOwnProperty("docString")&&(o.docString=e.docString),e.domain!=null&&e.hasOwnProperty("domain")&&(o.domain=e.domain),o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n}(),d.ModelProto=function(){function n(e){if(this.opsetImport=[],this.metadataProps=[],e)for(var r=Object.keys(e),o=0;o<r.length;++o)e[r[o]]!=null&&(this[r[o]]=e[r[o]])}return n.prototype.irVersion=c.Long?c.Long.fromBits(0,0,!1):0,n.prototype.opsetImport=c.emptyArray,n.prototype.producerName="",n.prototype.producerVersion="",n.prototype.domain="",n.prototype.modelVersion=c.Long?c.Long.fromBits(0,0,!1):0,n.prototype.docString="",n.prototype.graph=null,n.prototype.metadataProps=c.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,r){if(r||(r=f.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")&&l.onnx.GraphProto.encode(e.graph,r.uint32(58).fork()).ldelim(),e.opsetImport!=null&&e.opsetImport.length)for(var o=0;o<e.opsetImport.length;++o)l.onnx.OperatorSetIdProto.encode(e.opsetImport[o],r.uint32(66).fork()).ldelim();if(e.metadataProps!=null&&e.metadataProps.length)for(o=0;o<e.metadataProps.length;++o)l.onnx.StringStringEntryProto.encode(e.metadataProps[o],r.uint32(114).fork()).ldelim();return r},n.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},n.decode=function(e,r){e instanceof h||(e=h.create(e));for(var o=r===void 0?e.len:e.pos+r,p=new l.onnx.ModelProto;e.pos<o;){var g=e.uint32();switch(g>>>3){case 1:p.irVersion=e.int64();break;case 8:p.opsetImport&&p.opsetImport.length||(p.opsetImport=[]),p.opsetImport.push(l.onnx.OperatorSetIdProto.decode(e,e.uint32()));break;case 2:p.producerName=e.string();break;case 3:p.producerVersion=e.string();break;case 4:p.domain=e.string();break;case 5:p.modelVersion=e.int64();break;case 6:p.docString=e.string();break;case 7:p.graph=l.onnx.GraphProto.decode(e,e.uint32());break;case 14:p.metadataProps&&p.metadataProps.length||(p.metadataProps=[]),p.metadataProps.push(l.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.irVersion!=null&&e.hasOwnProperty("irVersion")&&!(c.isInteger(e.irVersion)||e.irVersion&&c.isInteger(e.irVersion.low)&&c.isInteger(e.irVersion.high)))return"irVersion: integer|Long expected";if(e.opsetImport!=null&&e.hasOwnProperty("opsetImport")){if(!Array.isArray(e.opsetImport))return"opsetImport: array expected";for(var r=0;r<e.opsetImport.length;++r)if(o=l.onnx.OperatorSetIdProto.verify(e.opsetImport[r]))return"opsetImport."+o}if(e.producerName!=null&&e.hasOwnProperty("producerName")&&!c.isString(e.producerName))return"producerName: string expected";if(e.producerVersion!=null&&e.hasOwnProperty("producerVersion")&&!c.isString(e.producerVersion))return"producerVersion: string expected";if(e.domain!=null&&e.hasOwnProperty("domain")&&!c.isString(e.domain))return"domain: string expected";if(e.modelVersion!=null&&e.hasOwnProperty("modelVersion")&&!(c.isInteger(e.modelVersion)||e.modelVersion&&c.isInteger(e.modelVersion.low)&&c.isInteger(e.modelVersion.high)))return"modelVersion: integer|Long expected";if(e.docString!=null&&e.hasOwnProperty("docString")&&!c.isString(e.docString))return"docString: string expected";if(e.graph!=null&&e.hasOwnProperty("graph")&&(o=l.onnx.GraphProto.verify(e.graph)))return"graph."+o;if(e.metadataProps!=null&&e.hasOwnProperty("metadataProps")){if(!Array.isArray(e.metadataProps))return"metadataProps: array expected";for(r=0;r<e.metadataProps.length;++r){var o;if(o=l.onnx.StringStringEntryProto.verify(e.metadataProps[r]))return"metadataProps."+o}}return null},n.fromObject=function(e){if(e instanceof l.onnx.ModelProto)return e;var r=new l.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 o=0;o<e.opsetImport.length;++o){if(typeof e.opsetImport[o]!="object")throw TypeError(".onnx.ModelProto.opsetImport: object expected");r.opsetImport[o]=l.onnx.OperatorSetIdProto.fromObject(e.opsetImport[o])}}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 e.modelVersion=="string"?r.modelVersion=parseInt(e.modelVersion,10):typeof e.modelVersion=="number"?r.modelVersion=e.modelVersion:typeof e.modelVersion=="object"&&(r.modelVersion=new c.LongBits(e.modelVersion.low>>>0,e.modelVersion.high>>>0).toNumber())),e.docString!=null&&(r.docString=String(e.docString)),e.graph!=null){if(typeof e.graph!="object")throw TypeError(".onnx.ModelProto.graph: object expected");r.graph=l.onnx.GraphProto.fromObject(e.graph)}if(e.metadataProps){if(!Array.isArray(e.metadataProps))throw TypeError(".onnx.ModelProto.metadataProps: array expected");for(r.metadataProps=[],o=0;o<e.metadataProps.length;++o){if(typeof e.metadataProps[o]!="object")throw TypeError(".onnx.ModelProto.metadataProps: object expected");r.metadataProps[o]=l.onnx.StringStringEntryProto.fromObject(e.metadataProps[o])}}return r},n.toObject=function(e,r){r||(r={});var o={};if((r.arrays||r.defaults)&&(o.opsetImport=[],o.metadataProps=[]),r.defaults){if(c.Long){var p=new c.Long(0,0,!1);o.irVersion=r.longs===String?p.toString():r.longs===Number?p.toNumber():p}else o.irVersion=r.longs===String?"0":0;o.producerName="",o.producerVersion="",o.domain="",c.Long?(p=new c.Long(0,0,!1),o.modelVersion=r.longs===String?p.toString():r.longs===Number?p.toNumber():p):o.modelVersion=r.longs===String?"0":0,o.docString="",o.graph=null}if(e.irVersion!=null&&e.hasOwnProperty("irVersion")&&(typeof e.irVersion=="number"?o.irVersion=r.longs===String?String(e.irVersion):e.irVersion:o.irVersion=r.longs===String?c.Long.prototype.toString.call(e.irVersion):r.longs===Number?new c.LongBits(e.irVersion.low>>>0,e.irVersion.high>>>0).toNumber():e.irVersion),e.producerName!=null&&e.hasOwnProperty("producerName")&&(o.producerName=e.producerName),e.producerVersion!=null&&e.hasOwnProperty("producerVersion")&&(o.producerVersion=e.producerVersion),e.domain!=null&&e.hasOwnProperty("domain")&&(o.domain=e.domain),e.modelVersion!=null&&e.hasOwnProperty("modelVersion")&&(typeof e.modelVersion=="number"?o.modelVersion=r.longs===String?String(e.modelVersion):e.modelVersion:o.modelVersion=r.longs===String?c.Long.prototype.toString.call(e.modelVersion):r.longs===Number?new c.LongBits(e.modelVersion.low>>>0,e.modelVersion.high>>>0).toNumber():e.modelVersion),e.docString!=null&&e.hasOwnProperty("docString")&&(o.docString=e.docString),e.graph!=null&&e.hasOwnProperty("graph")&&(o.graph=l.onnx.GraphProto.toObject(e.graph,r)),e.opsetImport&&e.opsetImport.length){o.opsetImport=[];for(var g=0;g<e.opsetImport.length;++g)o.opsetImport[g]=l.onnx.OperatorSetIdProto.toObject(e.opsetImport[g],r)}if(e.metadataProps&&e.metadataProps.length)for(o.metadataProps=[],g=0;g<e.metadataProps.length;++g)o.metadataProps[g]=l.onnx.StringStringEntryProto.toObject(e.metadataProps[g],r);return o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n}(),d.StringStringEntryProto=function(){function n(e){if(e)for(var r=Object.keys(e),o=0;o<r.length;++o)e[r[o]]!=null&&(this[r[o]]=e[r[o]])}return n.prototype.key="",n.prototype.value="",n.create=function(e){return new n(e)},n.encode=function(e,r){return r||(r=f.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},n.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},n.decode=function(e,r){e instanceof h||(e=h.create(e));for(var o=r===void 0?e.len:e.pos+r,p=new l.onnx.StringStringEntryProto;e.pos<o;){var g=e.uint32();switch(g>>>3){case 1:p.key=e.string();break;case 2:p.value=e.string();break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){return typeof e!="object"||e===null?"object expected":e.key!=null&&e.hasOwnProperty("key")&&!c.isString(e.key)?"key: string expected":e.value!=null&&e.hasOwnProperty("value")&&!c.isString(e.value)?"value: string expected":null},n.fromObject=function(e){if(e instanceof l.onnx.StringStringEntryProto)return e;var r=new l.onnx.StringStringEntryProto;return e.key!=null&&(r.key=String(e.key)),e.value!=null&&(r.value=String(e.value)),r},n.toObject=function(e,r){r||(r={});var o={};return r.defaults&&(o.key="",o.value=""),e.key!=null&&e.hasOwnProperty("key")&&(o.key=e.key),e.value!=null&&e.hasOwnProperty("value")&&(o.value=e.value),o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n}(),d.TensorAnnotation=function(){function n(e){if(this.quantParameterTensorNames=[],e)for(var r=Object.keys(e),o=0;o<r.length;++o)e[r[o]]!=null&&(this[r[o]]=e[r[o]])}return n.prototype.tensorName="",n.prototype.quantParameterTensorNames=c.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,r){if(r||(r=f.create()),e.tensorName!=null&&e.hasOwnProperty("tensorName")&&r.uint32(10).string(e.tensorName),e.quantParameterTensorNames!=null&&e.quantParameterTensorNames.length)for(var o=0;o<e.quantParameterTensorNames.length;++o)l.onnx.StringStringEntryProto.encode(e.quantParameterTensorNames[o],r.uint32(18).fork()).ldelim();return r},n.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},n.decode=function(e,r){e instanceof h||(e=h.create(e));for(var o=r===void 0?e.len:e.pos+r,p=new l.onnx.TensorAnnotation;e.pos<o;){var g=e.uint32();switch(g>>>3){case 1:p.tensorName=e.string();break;case 2:p.quantParameterTensorNames&&p.quantParameterTensorNames.length||(p.quantParameterTensorNames=[]),p.quantParameterTensorNames.push(l.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.tensorName!=null&&e.hasOwnProperty("tensorName")&&!c.isString(e.tensorName))return"tensorName: string expected";if(e.quantParameterTensorNames!=null&&e.hasOwnProperty("quantParameterTensorNames")){if(!Array.isArray(e.quantParameterTensorNames))return"quantParameterTensorNames: array expected";for(var r=0;r<e.quantParameterTensorNames.length;++r){var o=l.onnx.StringStringEntryProto.verify(e.quantParameterTensorNames[r]);if(o)return"quantParameterTensorNames."+o}}return null},n.fromObject=function(e){if(e instanceof l.onnx.TensorAnnotation)return e;var r=new l.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 o=0;o<e.quantParameterTensorNames.length;++o){if(typeof e.quantParameterTensorNames[o]!="object")throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: object expected");r.quantParameterTensorNames[o]=l.onnx.StringStringEntryProto.fromObject(e.quantParameterTensorNames[o])}}return r},n.toObject=function(e,r){r||(r={});var o={};if((r.arrays||r.defaults)&&(o.quantParameterTensorNames=[]),r.defaults&&(o.tensorName=""),e.tensorName!=null&&e.hasOwnProperty("tensorName")&&(o.tensorName=e.tensorName),e.quantParameterTensorNames&&e.quantParameterTensorNames.length){o.quantParameterTensorNames=[];for(var p=0;p<e.quantParameterTensorNames.length;++p)o.quantParameterTensorNames[p]=l.onnx.StringStringEntryProto.toObject(e.quantParameterTensorNames[p],r)}return o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n}(),d.GraphProto=function(){function n(e){if(this.node=[],this.initializer=[],this.input=[],this.output=[],this.valueInfo=[],this.quantizationAnnotation=[],e)for(var r=Object.keys(e),o=0;o<r.length;++o)e[r[o]]!=null&&(this[r[o]]=e[r[o]])}return n.prototype.node=c.emptyArray,n.prototype.name="",n.prototype.initializer=c.emptyArray,n.prototype.docString="",n.prototype.input=c.emptyArray,n.prototype.output=c.emptyArray,n.prototype.valueInfo=c.emptyArray,n.prototype.quantizationAnnotation=c.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,r){if(r||(r=f.create()),e.node!=null&&e.node.length)for(var o=0;o<e.node.length;++o)l.onnx.NodeProto.encode(e.node[o],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(o=0;o<e.initializer.length;++o)l.onnx.TensorProto.encode(e.initializer[o],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(o=0;o<e.input.length;++o)l.onnx.ValueInfoProto.encode(e.input[o],r.uint32(90).fork()).ldelim();if(e.output!=null&&e.output.length)for(o=0;o<e.output.length;++o)l.onnx.ValueInfoProto.encode(e.output[o],r.uint32(98).fork()).ldelim();if(e.valueInfo!=null&&e.valueInfo.length)for(o=0;o<e.valueInfo.length;++o)l.onnx.ValueInfoProto.encode(e.valueInfo[o],r.uint32(106).fork()).ldelim();if(e.quantizationAnnotation!=null&&e.quantizationAnnotation.length)for(o=0;o<e.quantizationAnnotation.length;++o)l.onnx.TensorAnnotation.encode(e.quantizationAnnotation[o],r.uint32(114).fork()).ldelim();return r},n.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},n.decode=function(e,r){e instanceof h||(e=h.create(e));for(var o=r===void 0?e.len:e.pos+r,p=new l.onnx.GraphProto;e.pos<o;){var g=e.uint32();switch(g>>>3){case 1:p.node&&p.node.length||(p.node=[]),p.node.push(l.onnx.NodeProto.decode(e,e.uint32()));break;case 2:p.name=e.string();break;case 5:p.initializer&&p.initializer.length||(p.initializer=[]),p.initializer.push(l.onnx.TensorProto.decode(e,e.uint32()));break;case 10:p.docString=e.string();break;case 11:p.input&&p.input.length||(p.input=[]),p.input.push(l.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 12:p.output&&p.output.length||(p.output=[]),p.output.push(l.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 13:p.valueInfo&&p.valueInfo.length||(p.valueInfo=[]),p.valueInfo.push(l.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 14:p.quantizationAnnotation&&p.quantizationAnnotation.length||(p.quantizationAnnotation=[]),p.quantizationAnnotation.push(l.onnx.TensorAnnotation.decode(e,e.uint32()));break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.node!=null&&e.hasOwnProperty("node")){if(!Array.isArray(e.node))return"node: array expected";for(var r=0;r<e.node.length;++r)if(o=l.onnx.NodeProto.verify(e.node[r]))return"node."+o}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(o=l.onnx.TensorProto.verify(e.initializer[r]))return"initializer."+o}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(o=l.onnx.ValueInfoProto.verify(e.input[r]))return"input."+o}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(o=l.onnx.ValueInfoProto.verify(e.output[r]))return"output."+o}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(o=l.onnx.ValueInfoProto.verify(e.valueInfo[r]))return"valueInfo."+o}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 o;if(o=l.onnx.TensorAnnotation.verify(e.quantizationAnnotation[r]))return"quantizationAnnotation."+o}}return null},n.fromObject=function(e){if(e instanceof l.onnx.GraphProto)return e;var r=new l.onnx.GraphProto;if(e.node){if(!Array.isArray(e.node))throw TypeError(".onnx.GraphProto.node: array expected");r.node=[];for(var o=0;o<e.node.length;++o){if(typeof e.node[o]!="object")throw TypeError(".onnx.GraphProto.node: object expected");r.node[o]=l.onnx.NodeProto.fromObject(e.node[o])}}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=[],o=0;o<e.initializer.length;++o){if(typeof e.initializer[o]!="object")throw TypeError(".onnx.GraphProto.initializer: object expected");r.initializer[o]=l.onnx.TensorProto.fromObject(e.initializer[o])}}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=[],o=0;o<e.input.length;++o){if(typeof e.input[o]!="object")throw TypeError(".onnx.GraphProto.input: object expected");r.input[o]=l.onnx.ValueInfoProto.fromObject(e.input[o])}}if(e.output){if(!Array.isArray(e.output))throw TypeError(".onnx.GraphProto.output: array expected");for(r.output=[],o=0;o<e.output.length;++o){if(typeof e.output[o]!="object")throw TypeError(".onnx.GraphProto.output: object expected");r.output[o]=l.onnx.ValueInfoProto.fromObject(e.output[o])}}if(e.valueInfo){if(!Array.isArray(e.valueInfo))throw TypeError(".onnx.GraphProto.valueInfo: array expected");for(r.valueInfo=[],o=0;o<e.valueInfo.length;++o){if(typeof e.valueInfo[o]!="object")throw TypeError(".onnx.GraphProto.valueInfo: object expected");r.valueInfo[o]=l.onnx.ValueInfoProto.fromObject(e.valueInfo[o])}}if(e.quantizationAnnotation){if(!Array.isArray(e.quantizationAnnotation))throw TypeError(".onnx.GraphProto.quantizationAnnotation: array expected");for(r.quantizationAnnotation=[],o=0;o<e.quantizationAnnotation.length;++o){if(typeof e.quantizationAnnotation[o]!="object")throw TypeError(".onnx.GraphProto.quantizationAnnotation: object expected");r.quantizationAnnotation[o]=l.onnx.TensorAnnotation.fromObject(e.quantizationAnnotation[o])}}return r},n.toObject=function(e,r){r||(r={});var o={};if((r.arrays||r.defaults)&&(o.node=[],o.initializer=[],o.input=[],o.output=[],o.valueInfo=[],o.quantizationAnnotation=[]),r.defaults&&(o.name="",o.docString=""),e.node&&e.node.length){o.node=[];for(var p=0;p<e.node.length;++p)o.node[p]=l.onnx.NodeProto.toObject(e.node[p],r)}if(e.name!=null&&e.hasOwnProperty("name")&&(o.name=e.name),e.initializer&&e.initializer.length)for(o.initializer=[],p=0;p<e.initializer.length;++p)o.initializer[p]=l.onnx.TensorProto.toObject(e.initializer[p],r);if(e.docString!=null&&e.hasOwnProperty("docString")&&(o.docString=e.docString),e.input&&e.input.length)for(o.input=[],p=0;p<e.input.length;++p)o.input[p]=l.onnx.ValueInfoProto.toObject(e.input[p],r);if(e.output&&e.output.length)for(o.output=[],p=0;p<e.output.length;++p)o.output[p]=l.onnx.ValueInfoProto.toObject(e.output[p],r);if(e.valueInfo&&e.valueInfo.length)for(o.valueInfo=[],p=0;p<e.valueInfo.length;++p)o.valueInfo[p]=l.onnx.ValueInfoProto.toObject(e.valueInfo[p],r);if(e.quantizationAnnotation&&e.quantizationAnnotation.length)for(o.quantizationAnnotation=[],p=0;p<e.quantizationAnnotation.length;++p)o.quantizationAnnotation[p]=l.onnx.TensorAnnotation.toObject(e.quantizationAnnotation[p],r);return o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n}(),d.TensorProto=function(){function n(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),o=0;o<r.length;++o)e[r[o]]!=null&&(this[r[o]]=e[r[o]])}return n.prototype.dims=c.emptyArray,n.prototype.dataType=0,n.prototype.segment=null,n.prototype.floatData=c.emptyArray,n.prototype.int32Data=c.emptyArray,n.prototype.stringData=c.emptyArray,n.prototype.int64Data=c.emptyArray,n.prototype.name="",n.prototype.docString="",n.prototype.rawData=c.newBuffer([]),n.prototype.externalData=c.emptyArray,n.prototype.dataLocation=0,n.prototype.doubleData=c.emptyArray,n.prototype.uint64Data=c.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,r){if(r||(r=f.create()),e.dims!=null&&e.dims.length){r.uint32(10).fork();for(var o=0;o<e.dims.length;++o)r.int64(e.dims[o]);r.ldelim()}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&r.uint32(16).int32(e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&l.onnx.TensorProto.Segment.encode(e.segment,r.uint32(26).fork()).ldelim(),e.floatData!=null&&e.floatData.length){for(r.uint32(34).fork(),o=0;o<e.floatData.length;++o)r.float(e.floatData[o]);r.ldelim()}if(e.int32Data!=null&&e.int32Data.length){for(r.uint32(42).fork(),o=0;o<e.int32Data.length;++o)r.int32(e.int32Data[o]);r.ldelim()}if(e.stringData!=null&&e.stringData.length)for(o=0;o<e.stringData.length;++o)r.uint32(50).bytes(e.stringData[o]);if(e.int64Data!=null&&e.int64Data.length){for(r.uint32(58).fork(),o=0;o<e.int64Data.length;++o)r.int64(e.int64Data[o]);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(),o=0;o<e.doubleData.length;++o)r.double(e.doubleData[o]);r.ldelim()}if(e.uint64Data!=null&&e.uint64Data.length){for(r.uint32(90).fork(),o=0;o<e.uint64Data.length;++o)r.uint64(e.uint64Data[o]);r.ldelim()}if(e.docString!=null&&e.hasOwnProperty("docString")&&r.uint32(98).string(e.docString),e.externalData!=null&&e.externalData.length)for(o=0;o<e.externalData.length;++o)l.onnx.StringStringEntryProto.encode(e.externalData[o],r.uint32(106).fork()).ldelim();return e.dataLocation!=null&&e.hasOwnProperty("dataLocation")&&r.uint32(112).int32(e.dataLocation),r},n.encodeDelimited=function(e,r){return this.encode(e,r).ldelim()},n.decode=function(e,r){e instanceof h||(e=h.create(e));for(var o=r===void 0?e.len:e.pos+r,p=new l.onnx.TensorProto;e.pos<o;){var g=e.uint32();switch(g>>>3){case 1:if(p.dims&&p.dims.length||(p.dims=[]),(7&g)==2)for(var _=e.uint32()+e.pos;e.pos<_;)p.dims.push(e.int64());else p.dims.push(e.int64());break;case 2:p.dataType=e.int32();break;case 3:p.segment=l.onnx.TensorProto.Segment.decode(e,e.uint32());break;case 4:if(p.floatData&&p.floatData.length||(p.floatData=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.floatData.push(e.float());else p.floatData.push(e.float());break;case 5:if(p.int32Data&&p.int32Data.length||(p.int32Data=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.int32Data.push(e.int32());else p.int32Data.push(e.int32());break;case 6:p.stringData&&p.stringData.length||(p.stringData=[]),p.stringData.push(e.bytes());break;case 7:if(p.int64Data&&p.int64Data.length||(p.int64Data=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.int64Data.push(e.int64());else p.int64Data.push(e.int64());break;case 8:p.name=e.string();break;case 12:p.docString=e.string();break;case 9:p.rawData=e.bytes();break;case 13:p.externalData&&p.externalData.length||(p.externalData=[]),p.externalData.push(l.onnx.StringStringEntryProto.decode(e,e.uint32()));break;case 14:p.dataLocation=e.int32();break;case 10:if(p.doubleData&&p.doubleData.length||(p.doubleData=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.doubleData.push(e.double());else p.doubleData.push(e.double());break;case 11:if(p.uint64Data&&p.uint64Data.length||(p.uint64Data=[]),(7&g)==2)for(_=e.uint32()+e.pos;e.pos<_;)p.uint64Data.push(e.uint64());else p.uint64Data.push(e.uint64());break;default:e.skipType(7&g)}}return p},n.decodeDelimited=function(e){return e instanceof h||(e=new h(e)),this.decode(e,e.uint32())},n.verify=function(e){if(typeof e!="object"||e===null)return"object expected";if(e.dims!=null&&e.hasOwnProperty("dims")){if(!Array.isArray(e.dims))return"dims: array expected";for(var r=0;r<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")&&(o=l.onnx.TensorProto.Segment.verify(e.segment)))return"segment."+o;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 o;if(o=l.onnx.StringStringEntryProto.verify(e.externalData[r]))return"externalData."+o}}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},n.fromObject=function(e){if(e instanceof l.onnx.TensorProto)return e;var r=new l.onnx.TensorProto;if(e.dims){if(!Array.isArray(e.dims))throw TypeError(".onnx.TensorProto.dims: array expected");r.dims=[];for(var o=0;o<e.dims.length;++o)c.Long?(r.dims[o]=c.Long.fromValue(e.dims[o])).unsigned=!1:typeof e.dims[o]=="string"?r.dims[o]=parseInt(e.dims[o],10):typeof e.dims[o]=="number"?r.dims[o]=e.dims[o]:typeof e.dims[o]=="object"&&(r.dims[o]=new c.LongBits(e.dims[o].low>>>0,e.dims[o].high>>>0).toNumber())}if(e.dataType!=null&&(r.dataType=0|e.dataType),e.segment!=null){if(typeof e.segment!="object")throw TypeError(".onnx.TensorProto.segment: object expected");r.segment=l.onnx.TensorProto.Segment.fromObject(e.segment)}if(e.floatData){if(!Array.isArray(e.floatData))throw TypeError(".onnx.TensorProto.floatData: array expected");for(r.floatData=[],o=0;o<e.floatData.length;++o)r.floatData[o]=Number(e.floatData[o])}if(e.int32Data){if(!Array.isArray(e.int32Data))throw TypeError(".onnx.TensorProto.int32Data: array expected");for(r.int32Data=[],o=0;o<e.int32Data.length;++o)r.int32Data[o]=0|e.int32Data[o]}if(e.stringData){if(!Array.isArray(e.stringData))throw TypeError(".onnx.TensorProto.stringData: array expected");for(r.stringData=[],o=0;o<e.stringData.length;++o)typeof e.stringData[o]=="string"?c.base64.decode(e.stringData[o],r.stringData[o]=c.newBuffer(c.base64.length(e.stringData[o])),0):e.stringData[o].length&&(r.stringData[o]=e.stringData[o])}if(e.int64Data){if(!Array.isArray(e.int64Data))throw TypeError(".onnx.TensorProto.int64Data: array expected");for(r.int64Data=[],o=0;o<e.int64Data.length;++o)c.Long?(r.int64Data[o]=c.Long.fromValue(e.int64Data[o])).unsigned=!1:typeof e.int64Data[o]=="string"?r.int64Data[o]=parseInt(e.int64Data[o],10):typeof e.int64Data[o]=="number"?r.int64Data[o]=e.int64Data[o]:typeof e.int64Data[o]=="object"&&(r.int64Data[o]=new c.LongBits(e.int64Data[o].low>>>0,e.int64Data[o].high>>>0).toNumber())}if(e.name!=null&&(r.name=String(e.name)),e.docString!=null&&(r.docString=String(e.docString)),e.rawData!=null&&(typeof e.rawData=="string"?c.base64.decode(e.rawData,r.rawData=c.newBuffer(c.base64.length(e.rawData)),0):e.rawData.length&&(r.rawData=e.rawData)),e.externalData){if(!Array.isArray(e.externalData))throw TypeError(".onnx.TensorProto.externalData: array expected");for(r.externalData=[],o=0;o<e.externalData.length;++o){if(typeof e.externalData[o]!="object")throw TypeError(".onnx.TensorProto.externalData: object expected");r.externalData[o]=l.onnx.StringStringEntryProto.fromObject(e.externalData[o])}}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=[],o=0;o<e.doubleData.length;++o)r.doubleData[o]=Number(e.doubleData[o])}if(e.uint64Data){if(!Array.isArray(e.uint64Data))throw TypeError(".onnx.TensorProto.uint64Data: array expected");for(r.uint64Data=[],o=0;o<e.uint64Data.length;++o)c.Long?(r.uint64Data[o]=c.Long.fromValue(e.uint64Data[o])).unsigned=!0:typeof e.uint64Data[o]=="string"?r.uint64Data[o]=parseInt(e.uint64Data[o],10):typeof e.uint64Data[o]=="number"?r.uint64Data[o]=e.uint64Data[o]:typeof e.uint64Data[o]=="object"&&(r.uint64Data[o]=new c.LongBits(e.uint64Data[o].low>>>0,e.uint64Data[o].high>>>0).toNumber(!0))}return r},n.toObject=function(e,r){r||(r={});var o={};if((r.arrays||r.defaults)&&(o.dims=[],o.floatData=[],o.int32Data=[],o.stringData=[],o.int64Data=[],o.doubleData=[],o.uint64Data=[],o.externalData=[]),r.defaults&&(o.dataType=0,o.segment=null,o.name="",r.bytes===String?o.rawData="":(o.rawData=[],r.bytes!==Array&&(o.rawData=c.newBuffer(o.rawData))),o.docString="",o.dataLocation=r.enums===String?"DEFAULT":0),e.dims&&e.dims.length){o.dims=[];for(var p=0;p<e.dims.length;++p)typeof e.dims[p]=="number"?o.dims[p]=r.longs===String?String(e.dims[p]):e.dims[p]:o.dims[p]=r.longs===String?c.Long.prototype.toString.call(e.dims[p]):r.longs===Number?new c.LongBits(e.dims[p].low>>>0,e.dims[p].high>>>0).toNumber():e.dims[p]}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&(o.dataType=e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&(o.segment=l.onnx.TensorProto.Segment.toObject(e.segment,r)),e.floatData&&e.floatData.length)for(o.floatData=[],p=0;p<e.floatData.length;++p)o.floatData[p]=r.json&&!isFinite(e.floatData[p])?String(e.floatData[p]):e.floatData[p];if(e.int32Data&&e.int32Data.length)for(o.int32Data=[],p=0;p<e.int32Data.length;++p)o.int32Data[p]=e.int32Data[p];if(e.stringData&&e.stringData.length)for(o.stringData=[],p=0;p<e.stringData.length;++p)o.stringData[p]=r.bytes===String?c.base64.encode(e.stringData[p],0,e.stringData[p].length):r.bytes===Array?Array.prototype.slice.call(e.stringData[p]):e.stringData[p];if(e.int64Data&&e.int64Data.length)for(o.int64Data=[],p=0;p<e.int64Data.length;++p)typeof 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c.LongBits(e.uint64Data[p].low>>>0,e.uint64Data[p].high>>>0).toNumber(!0):e.uint64Data[p];if(e.docString!=null&&e.hasOwnProperty("docString")&&(o.docString=e.docString),e.externalData&&e.externalData.length)for(o.externalData=[],p=0;p<e.externalData.length;++p)o.externalData[p]=l.onnx.StringStringEntryProto.toObject(e.externalData[p],r);return e.dataLocation!=null&&e.hasOwnProperty("dataLocation")&&(o.dataLocation=r.enums===String?l.onnx.TensorProto.DataLocation[e.dataLocation]:e.dataLocation),o},n.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},n.DataType=function(){var e={},r=Object.create(e);return 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s.onnx.AttributeProto.AttributeType.FLOATS:return"floats";case s.onnx.AttributeProto.AttributeType.INTS:return"ints";case s.onnx.AttributeProto.AttributeType.STRINGS:return"strings";case s.onnx.AttributeProto.AttributeType.TENSORS:return"tensors";default:throw new Error(`attribute type is not supported yet: ${s.onnx.AttributeProto.AttributeType[n]}`)}}static getValue(l){const n=l instanceof s.onnx.AttributeProto?l.type:l.type();if(n===s.onnx.AttributeProto.AttributeType.GRAPH||n===s.onnx.AttributeProto.AttributeType.GRAPHS)throw new Error("graph attribute is not supported yet");const e=this.getValueNoCheck(l);if(n===s.onnx.AttributeProto.AttributeType.INT&&a.LongUtil.isLong(e))return a.LongUtil.longToNumber(e);if(n===s.onnx.AttributeProto.AttributeType.INTS){const r=e,o=new Array(r.length);for(let p=0;p<r.length;p++){const g=r[p];o[p]=a.LongUtil.longToNumber(g)}return o}if(n===s.onnx.AttributeProto.AttributeType.TENSOR)return l instanceof s.onnx.AttributeProto?d.Tensor.fromProto(e):d.Tensor.fromOrtTensor(e);if(n===s.onnx.AttributeProto.AttributeType.TENSORS){if(l instanceof s.onnx.AttributeProto)return e.map(r=>d.Tensor.fromProto(r));if(l instanceof h.Attribute)return e.map(r=>d.Tensor.fromOrtTensor(r))}if(n===s.onnx.AttributeProto.AttributeType.STRING&&l instanceof s.onnx.AttributeProto){const r=e;return(0,a.decodeUtf8String)(r)}return n===s.onnx.AttributeProto.AttributeType.STRINGS&&l instanceof s.onnx.AttributeProto?e.map(a.decodeUtf8String):e}static getValueNoCheck(l){return l instanceof s.onnx.AttributeProto?this.getValueNoCheckFromOnnxFormat(l):this.getValueNoCheckFromOrtFormat(l)}static getValueNoCheckFromOnnxFormat(l){switch(l.type){case s.onnx.AttributeProto.AttributeType.FLOAT:return l.f;case s.onnx.AttributeProto.AttributeType.INT:return l.i;case s.onnx.AttributeProto.AttributeType.STRING:return l.s;case s.onnx.AttributeProto.AttributeType.TENSOR:return l.t;case s.onnx.AttributeProto.AttributeType.GRAPH:return l.g;case s.onnx.AttributeProto.AttributeType.FLOATS:return l.floats;case s.onnx.AttributeProto.AttributeType.INTS:return l.ints;case s.onnx.AttributeProto.AttributeType.STRINGS:return l.strings;case s.onnx.AttributeProto.AttributeType.TENSORS:return l.tensors;case s.onnx.AttributeProto.AttributeType.GRAPHS:return l.graphs;default:throw new Error(`unsupported attribute type: ${s.onnx.AttributeProto.AttributeType[l.type]}`)}}static getValueNoCheckFromOrtFormat(l){switch(l.type()){case h.AttributeType.FLOAT:return l.f();case h.AttributeType.INT:return l.i();case h.AttributeType.STRING:return l.s();case h.AttributeType.TENSOR:return l.t();case h.AttributeType.GRAPH:return l.g();case h.AttributeType.FLOATS:return l.floatsArray();case h.AttributeType.INTS:{const n=[];for(let e=0;e<l.intsLength();e++)n.push(l.ints(e));return n}case h.AttributeType.STRINGS:{const n=[];for(let e=0;e<l.stringsLength();e++)n.push(l.strings(e));return n}case h.AttributeType.TENSORS:{const n=[];for(let e=0;e<l.tensorsLength();e++)n.push(l.tensors(e));return n}default:throw new Error(`unsupported attribute type: ${h.AttributeType[l.type()]}`)}}}t.Attribute=f},7091:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.resolveBackend=t.backend=void 0;const s=i(5038),u=new Map;async function d(a){const h=t.backend;if(h[a]!==void 0&&function(f){const c=f;return"initialize"in c&&typeof c.initialize=="function"&&"createSessionHandler"in c&&typeof c.createSessionHandler=="function"&&"dispose"in c&&typeof c.dispose=="function"}(h[a])){const f=h[a];let c=f.initialize();if(typeof c=="object"&&"then"in c&&(c=await c),c)return u.set(a,f),f}}t.backend={webgl:new s.WebGLBackend},t.resolveBackend=async function a(h){if(!h)return a(["webgl"]);{const f=typeof h=="string"?[h]:h;for(const c of f){const l=u.get(c);if(l)return l;const n=await d(c);if(n)return n}}throw new Error("no available backend to use")}},5038:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.WebGLBackend=void 0;const s=i(1670),u=i(6231),d=i(6416),a=i(7305);t.WebGLBackend=class{get contextId(){return s.env.webgl.contextId}set contextId(h){s.env.webgl.contextId=h}get matmulMaxBatchSize(){return s.env.webgl.matmulMaxBatchSize}set matmulMaxBatchSize(h){s.env.webgl.matmulMaxBatchSize=h}get textureCacheMode(){return s.env.webgl.textureCacheMode}set textureCacheMode(h){s.env.webgl.textureCacheMode=h}get pack(){return s.env.webgl.pack}set pack(h){s.env.webgl.pack=h}get async(){return s.env.webgl.async}set async(h){s.env.webgl.async=h}initialize(){try{return this.glContext=(0,a.createWebGLContext)(this.contextId),typeof this.matmulMaxBatchSize!="number"&&(this.matmulMaxBatchSize=16),typeof this.textureCacheMode!="string"&&(this.textureCacheMode="full"),typeof this.pack!="boolean"&&(this.pack=!1),typeof this.async!="boolean"&&(this.async=!1),u.Logger.setWithEnv(s.env),u.Logger.verbose("WebGLBackend",`Created WebGLContext: ${typeof this.glContext} with matmulMaxBatchSize: ${this.matmulMaxBatchSize}; textureCacheMode: ${this.textureCacheMode}; pack: ${this.pack}; async: ${this.async}.`),!0}catch(h){return u.Logger.warning("WebGLBackend",`Unable to initialize WebGLBackend. ${h}`),!1}}createSessionHandler(h){return new d.WebGLSessionHandler(this,h)}dispose(){this.glContext.dispose()}}},5107:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.CoordsGlslLib=void 0;const s=i(2517),u=i(8520),d=i(5060),a=i(7859),h=i(9390);class f extends u.GlslLib{constructor(l){super(l)}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.offsetToCoords()),this.coordsToOffset()),this.toVec()),this.valueFrom()),this.getCommonUtilFuncs()),this.getInputsSamplingSnippets()),this.getOutputSamplingSnippet())}getCustomTypes(){return{}}offsetToCoords(){return{offsetToCoords:new u.GlslLibRoutine(`
      vec2 offsetToCoords(int offset, int width, int height) {
        int t = offset / width;
        int s = offset - t*width;
        vec2 coords = (vec2(s,t) + vec2(0.5,0.5)) / vec2(width, height);
        return coords;
      }
      `)}}coordsToOffset(){return{coordsToOffset:new u.GlslLibRoutine(`
      int coordsToOffset(vec2 coords, int width, int height) {
        float s = coords.s * float(width);
        float t = coords.t * float(height);
        int offset = int(t) * width + int(s);
        return offset;
      }
      `)}}getOutputSamplingSnippet(){const l=this.context.outputTextureLayout;return l.isPacked?this.getPackedOutputSamplingSnippet(l):this.getUnpackedOutputSamplingSnippet(l)}getPackedOutputSamplingSnippet(l){const n=l.unpackedShape,e=[l.width,l.height],r={},o="getOutputCoords";switch(n.length){case 0:r[o]=this.getOutputScalarCoords();break;case 1:r[o]=this.getOutputPacked1DCoords(n,e);break;case 2:r[o]=this.getOutputPacked2DCoords(n,e);break;case 3:r[o]=this.getOutputPacked3DCoords(n,e);break;default:r[o]=this.getOutputPackedNDCoords(n,e)}const p=`
      void setOutput(vec4 val) {
        ${(0,d.getGlsl)(this.context.glContext.version).output} = val;
      }
    `;return r.floatTextureSetRGBA=new u.GlslLibRoutine(p),r}getUnpackedOutputSamplingSnippet(l){const n=l.unpackedShape,e=[l.width,l.height],r={},o="getOutputCoords";switch(n.length){case 0:r[o]=this.getOutputScalarCoords();break;case 1:r[o]=this.getOutputUnpacked1DCoords(n,e);break;case 2:r[o]=this.getOutputUnpacked2DCoords(n,e);break;case 3:r[o]=this.getOutputUnpacked3DCoords(n,e);break;case 4:r[o]=this.getOutputUnpacked4DCoords(n,e);break;case 5:r[o]=this.getOutputUnpacked5DCoords(n,e);break;case 6:r[o]=this.getOutputUnpacked6DCoords(n,e);break;default:throw new Error(`Unsupported output dimensionality: ${n.length}`)}const p=`
        void setOutput(float val) {
          ${(0,d.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0);
        }
    `;return r.floatTextureSetR=new u.GlslLibRoutine(p),r}getOutputScalarCoords(){return new u.GlslLibRoutine(`
      int getOutputCoords() {
        return 0;
      }
    `)}getOutputPacked1DCoords(l,n){const e=n;let r="";return e[0]===1?(r=`
          int getOutputCoords() {
            return 2 * int(TexCoords.y * ${e[1]}.0);
          }
        `,new u.GlslLibRoutine(r)):e[1]===1?(r=`
          int getOutputCoords() {
            return 2 * int(TexCoords.x * ${e[0]}.0);
          }
        `,new u.GlslLibRoutine(r)):(r=`
        int getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                 vec2(${e[0]}, ${e[1]}));
          return 2 * (resTexRC.y * ${e[0]} + resTexRC.x);
        }
      `,new u.GlslLibRoutine(r))}getOutputPacked2DCoords(l,n){let e="";if(s.ArrayUtil.arraysEqual(l,n))return e=`
        ivec2 getOutputCoords() {
          return 2 * ivec2(TexCoords.xy * vec2(${n[0]}, ${n[1]}));
        }
      `,new u.GlslLibRoutine(e);const r=n,o=Math.ceil(l[1]/2);return e=`
        ivec2 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${r[0]}, ${r[1]}));

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

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

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

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

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

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

        ${g}

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

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

        return ivec${l.length}(${_});
      }
    `;return new u.GlslLibRoutine(b)}getOutputUnpacked1DCoords(l,n){const e=`
        int getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${n[0]}, ${n[1]}));
          return resTexRC.y * ${n[0]} + resTexRC.x;
        }
      `;return new u.GlslLibRoutine(e)}getOutputUnpacked2DCoords(l,n){const e=`
        ivec2 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${n[0]}, ${n[1]}));
          int index = resTexRC.y * ${n[0]} + resTexRC.x;
          int r = index / ${l[1]};
          int c = index - r * ${l[1]};
          return ivec2(r, c);
        }
      `;return new u.GlslLibRoutine(e)}getOutputUnpacked3DCoords(l,n){let e="";const r=l.length;let o=null;r<2&&(o=[]),o=new Array(r-1),o[r-2]=l[r-1];for(let _=r-3;_>=0;--_)o[_]=o[_+1]*l[_+1];const p=["r","c","d"],g=o.map((_,b)=>`int ${p[b]} = index / ${_}; ${b===o.length-1?`int ${p[b+1]} = index - ${p[b]} * ${_}`:`index -= ${p[b]} * ${_}`};`).join("");return e=`
        ivec3 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${n[0]}, ${n[1]}));
          int index = resTexRC.y * ${n[0]} + resTexRC.x;
          ${g}
          return ivec3(r, c, d);
        }
      `,new u.GlslLibRoutine(e)}getOutputUnpacked4DCoords(l,n){let e="";const r=l.length;let o=null;r<2&&(o=[]),o=new Array(r-1),o[r-2]=l[r-1];for(let _=r-3;_>=0;--_)o[_]=o[_+1]*l[_+1];const p=["r","c","d","d2"],g=o.map((_,b)=>`int ${p[b]} = index / ${_}; ${b===o.length-1?`int ${p[b+1]} = index - ${p[b]} * ${_}`:`index -= ${p[b]} * ${_}`};`).join("");return e=`
      ivec4 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${n[0]}, ${n[1]}));
          int index = resTexRC.y * ${n[0]} + resTexRC.x;
          ${g}
          return ivec4(r, c, d, d2);
        }
      `,new u.GlslLibRoutine(e)}getOutputUnpacked5DCoords(l,n){let e="";const r=l.length;let o=null;r<2&&(o=[]),o=new Array(r-1),o[r-2]=l[r-1];for(let _=r-3;_>=0;--_)o[_]=o[_+1]*l[_+1];const p=["r","c","d","d2","d3"],g=o.map((_,b)=>`int ${p[b]} = index / ${_}; ${b===o.length-1?`int ${p[b+1]} = index - ${p[b]} * ${_}`:`index -= ${p[b]} * ${_}`};`).join("");return e=`
      ivec5 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
                                vec2(${n[0]}, ${n[1]}));
          int index = resTexRC.y * ${n[0]} + resTexRC.x;
          ${g}
          return ivec5(r, c, d, d2, d3);
        }
      `,new u.GlslLibRoutine(e)}getOutputUnpacked6DCoords(l,n){let e="";const r=l.length;let o=null;r<2&&(o=[]),o=new Array(r-1),o[r-2]=l[r-1];for(let _=r-3;_>=0;--_)o[_]=o[_+1]*l[_+1];const p=["r","c","d","d2","d3","d4"],g=o.map((_,b)=>`int ${p[b]} = index / ${_}; ${b===o.length-1?`int ${p[b+1]} = index - ${p[b]} * ${_}`:`index -= ${p[b]} * ${_}`};`).join("");return e=`
     ivec6 getOutputCoords() {
         ivec2 resTexRC = ivec2(TexCoords.xy *
                               vec2(${n[0]}, ${n[1]}));
         int index = resTexRC.y * ${n[0]} + resTexRC.x;
         ${g}
         return ivec6(r, c, d, d2, d3, d4);
       }
     `,new u.GlslLibRoutine(e)}getCommonUtilFuncs(){const l={};let n="uvFromFlat";l[n]=new u.GlslLibRoutine(`
    vec2 uvFromFlat(int texNumR, int texNumC, int index) {
      int texC = index / texNumR;
      int texR = index - texC * texNumR;
      // TODO: swap texR, texC order in following function so row is corresponding to u and column is corresponding to
      //       v.
      return (vec2(texR, texC) + halfCR) / vec2(texNumR, texNumC);
    }
    `),n="packedUVfrom1D",l[n]=new u.GlslLibRoutine(`
      vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
        int texelIndex = index / 2;
        int texR = texelIndex / texNumC;
        int texC = texelIndex - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),n="packedUVfrom2D",l[n]=new u.GlslLibRoutine(`
      vec2 packedUVfrom2D(int texNumR, int texNumC, int texelsInLogicalRow, int row, int col) {
        int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
        int texR = texelIndex / texNumC;
        int texC = texelIndex - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),n="packedUVfrom3D",l[n]=new u.GlslLibRoutine(`
      vec2 packedUVfrom3D(int texNumR, int texNumC,
          int texelsInBatch, int texelsInLogicalRow, int b,
          int row, int col) {
        int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
        int texR = index / texNumC;
        int texC = index - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),n="sampleTexture";const e=(0,d.getGlsl)(this.context.glContext.version);return l[n]=new u.GlslLibRoutine(`
        float sampleTexture(sampler2D textureSampler, vec2 uv) {
            return ${e.texture2D}(textureSampler, uv).r;
        }`),l}getInputsSamplingSnippets(){const l={},n=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,r)=>{const o=this.context.inputTextureLayouts[r],p=(0,h.generateShaderFuncNameFromInputSamplerName)(e);o.isPacked?l[p]=this.getPackedSamplerFromInput(p,e,o):l[p]=this.getUnpackedSamplerFromInput(p,e,o);const g=(0,h.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(e);o.unpackedShape.length<=n.unpackedShape.length&&(o.isPacked?l[g]=this.getPackedSamplerAtOutputCoords(g,o,n,e):l[g]=this.getUnpackedSamplerAtOutputCoords(g,o,n,e))}),l}getPackedSamplerAtOutputCoords(l,n,e,r){const o=n.unpackedShape,p=e.unpackedShape,g=r,_=(0,h.generateShaderFuncNameFromInputSamplerName)(g),b=o.length,y=p.length,w=s.BroadcastUtil.getBroadcastDims(o,p),T=(0,h.getCoordsDataType)(y),S=y-b;let A;const P=(0,h.getGlChannels)();A=b===0?"":y<2&&w.length>=1?"coords = 0;":w.map(C=>`coords.${P[C+S]} = 0;`).join(`
`);let x="";x=y<2&&b>0?"coords":o.map((C,G)=>`coords.${P[G+S]}`).join(", ");let M="return outputValue;";const N=s.ShapeUtil.size(o)===1,z=s.ShapeUtil.size(p)===1;if(b!==1||N||z){if(N&&!z)M=y===1?`
          return vec4(outputValue.x, outputValue.x, 0., 0.);
        `:`
          return vec4(outputValue.x);
        `;else if(w.length){const C=b-2,G=b-1;w.indexOf(C)>-1&&w.indexOf(G)>-1?M="return vec4(outputValue.x);":w.indexOf(C)>-1?M="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":w.indexOf(G)>-1&&(M="return vec4(outputValue.xx, outputValue.zz);")}}else M=`
        return vec4(outputValue.xy, outputValue.xy);
      `;const $=`
      vec4 ${l}() {
        ${T} coords = getOutputCoords();
        
        int lastDim = coords.${P[y-1]};
        coords.${P[y-1]} = coords.${P[y-2]};
        coords.${P[y-2]} = lastDim;
      
        ${A}
        vec4 outputValue = ${_}(${x});
        ${M}
      }
    `;return new u.GlslLibRoutine($,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(l,n,e,r){const o=[e.width,e.height],p=[n.width,n.height],g=n.unpackedShape.length,_=e.unpackedShape.length,b=n.unpackedShape,y=e.unpackedShape,w=(0,h.generateShaderFuncNameFromInputSamplerName)(r);if(g===_&&s.ArrayUtil.arraysEqual(p,o)){const z=`
          float ${l}() {
            return sampleTexture(${r}, TexCoords);
          }
        `;return new u.GlslLibRoutine(z,["coordinates.sampleTexture"])}const T=(0,h.getCoordsDataType)(_),S=s.BroadcastUtil.getBroadcastDims(b,y),A=_-g;let P;const x=(0,h.getGlChannels)();P=g===0?"":_<2&&S.length>=1?"coords = 0;":S.map(z=>`coords.${x[z+A]} = 0;`).join(`
`);let M="";M=_<2&&g>0?"coords":n.unpackedShape.map((z,$)=>`coords.${x[$+A]}`).join(", ");const N=`
        float ${l}() {
          ${T} coords = getOutputCoords();
          ${P}
          return ${w}(${M});
        }
      `;return new u.GlslLibRoutine(N,["coordinates.getOutputCoords"])}getPackedSamplerFromInput(l,n,e){switch(e.unpackedShape.length){case 0:return this.getPackedSamplerScalar(l,n);case 1:return this.getPackedSampler1D(l,n,e);case 2:return this.getPackedSampler2D(l,n,e);case 3:return this.getPackedSampler3D(l,n,e);default:return this.getPackedSamplerND(l,n,e)}}getUnpackedSamplerFromInput(l,n,e){const r=e.unpackedShape;switch(r.length){case 0:return this.getUnpackedSamplerScalar(l,n,e);case 1:return this.getUnpackedSampler1D(l,n,e);case 2:return this.getUnpackedSampler2D(l,n,e);case 3:return this.getUnpackedSampler3D(l,n,e);case 4:return this.getUnpackedSampler4D(l,n,e);case 5:return this.getUnpackedSampler5D(l,n,e);case 6:return this.getUnpackedSampler6D(l,n,e);default:throw new Error(`Unsupported dimension ${r.length}-D`)}}getPackedSamplerScalar(l,n){const e=`
          vec4 ${l}() {
            return ${(0,d.getGlsl)(this.context.glContext.version).texture2D}(${n}, halfCR);
          }
        `;return new u.GlslLibRoutine(e)}getPackedSampler1D(l,n,e){const r=[e.width,e.height],o=[r[1],r[0]],p=(0,d.getGlsl)(this.context.glContext.version),g=`vec4 ${l}(int index) {
      vec2 uv = packedUVfrom1D(
      ${o[0]}, ${o[1]}, index);
      return ${p.texture2D}(${n}, uv);
    }`;return new u.GlslLibRoutine(g,["coordinates.packedUVfrom1D"])}getPackedSampler2D(l,n,e){const r=e.unpackedShape,o=[e.width,e.height],p=(0,d.getGlsl)(this.context.glContext.version),g=o[0],_=o[1];if(o!=null&&s.ArrayUtil.arraysEqual(r,o)){const T=`vec4 ${l}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${_}.0, ${g}.0);
        return ${p.texture2D}(${n}, uv);
      }`;return new u.GlslLibRoutine(T)}const b=o,y=Math.ceil(r[1]/2),w=`vec4 ${l}(int row, int col) {
      vec2 uv = packedUVfrom2D(${b[1]}, ${b[0]}, ${y}, row, col);
      return ${p.texture2D}(${n}, uv);
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            vec2 uv = (vec2(row, col) + halfCR) / vec2(${o[1]}.0, ${o[0]}.0);
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            int offset_${n} = coordsToOffset(TexCoords, ${b}, ${y});
            float index = dot(vec3(row, col, offset_${n}), vec3(${r[1]}, 1, 1));
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            int index = row * ${b} + col * ${_} + depth * ${g} +
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            vec2 uv = uvFromFlat(${e.width}, ${e.height}, index);
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          }
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        ${p.join("")}
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          int offset = indicesToOffset_${l}(m);
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        highp float Sign = step(0.0,-f);
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        highp vec4 rgba;
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        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)));
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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;
      }
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`)}}},5483:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.glslRegistry=void 0;const s=i(5107),u=i(7341),d=i(9894),a=i(2655),h=i(3891);t.glslRegistry={encoding:u.EncodingGlslLib,fragcolor:d.FragColorGlslLib,vec:h.VecGlslLib,shapeUtils:a.ShapeUtilsGlslLib,coordinates:s.CoordsGlslLib}},2655:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ShapeUtilsGlslLib=void 0;const s=i(8520);class u extends s.GlslLib{constructor(a){super(a)}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.bcastIndex()),this.bcastMatmulIndex()),this.offsetToIndices()),this.indicesToOffset()),this.incrementIndices())}getCustomTypes(){return{}}bcastIndex(){const a=this.context.outputTextureLayout.shape.length,h={};return this.context.programInfo.inputNames.forEach((f,c)=>{const l=this.context.inputTextureLayouts[c].unpackedShape;if(l.length<=a){const n=l.length,e=a-n,r=`bcastIndices_${f}`;let o="";for(let g=0;g<n;++g)o+=`
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        int offset = 0;
        ${c}
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      }
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      }
      `}incrementIndices(){const a={};return this.context.programInfo.inputNames.forEach((h,f)=>{const c=this.context.inputTextureLayouts[f].shape,l=c.length,n=`incrementIndices_${h}`;let e="";for(let o=0;o<l;++o)e+=`
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          TexCoords = textureCoord;
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      int y;
      int z;
      int w;
      int u;
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    struct ivec6
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      int x;
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      int z;
      int w;
      int u;
      int v;
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    `},t.getDefaultFragShaderMain=function(d,a){return`
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    return a + b;
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  vec4 ${T}(vec4 v1, vec4 v2) {
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  }
  `,name:T,type:u.FunctionType.ValueBased}}function f(){const T="div_";return{body:`
  float ${T}(float a, float b) {
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  vec4 ${T}(vec4 v1, vec4 v2) {
    return v1 / v2;
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  float ${T}(float a, float b) {
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  vec4 ${T}(vec4 v1, vec4 v2) {
    return v1 * v2;
  }
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  float ${T}(float a, float b) {
    return a - b;
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  vec4 ${T}(vec4 v1, vec4 v2) {
    return v1 - v2;
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  `,name:T,type:u.FunctionType.ValueBased}}function n(){const T="equal_";return{body:`
  float ${T}(float a, float b) {
    return float(a == b);
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  vec4 ${T}(vec4 v1, vec4 v2) {
    return vec4(equal(v1, v2));
  }
  `,name:T,type:u.FunctionType.ValueBased}}function e(){const T="greater_";return{body:`
  float ${T}(float a, float b) {
    return float(a > b);
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  vec4 ${T}(vec4 v1, vec4 v2) {
    return vec4( v1.r > v2.r ,
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      v1.b > v2.b,
      v1.a > v2.a );
  }
  `,name:T,type:u.FunctionType.ValueBased}}function r(){const T="less_";return{body:`
  float ${T}(float a, float b) {
    return float(a < b);
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  vec4 ${T}(vec4 v1, vec4 v2) {
    return vec4( v1.r < v2.r ,
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                v1.b < v2.b,
                v1.a < v2.a );
  }
  `,name:T,type:u.FunctionType.ValueBased}}function o(){const T="and_";return{body:`
  float ${T}(float a, float b) {
    return float( bool(a) && bool(b) );
  }
  vec4 ${T}(vec4 v1, vec4 v2) {
    bvec4 b1 = bvec4(v1);
    bvec4 b2 = bvec4(v2);
    return vec4( b1.r && b2.r ,
                b1.g && b2.g,
                b1.b && b2.b,
                b1.a && b2.a );
  }
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  float ${T}(float a, float b) {
    return float( bool(a) || bool(b) );
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  vec4 ${T}(vec4 v1, vec4 v2) {
    bvec4 b1 = bvec4(v1);
    bvec4 b2 = bvec4(v2);
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                b1.g || b2.g,
                b1.b || b2.b,
                b1.a || b2.a );
  }
  `,name:T,type:u.FunctionType.ValueBased}}function g(){const T="xor_";return{body:`
  float ${T}(float a, float b) {
    return float( bool(a) ^^ bool(b) );
  }
  vec4 ${T}(vec4 v1, vec4 v2) {
    bvec4 b1 = bvec4(v1);
    bvec4 b2 = bvec4(v2);
    return vec4( b1.r ^^ b2.r ,
                b1.g ^^ b2.g,
                b1.b ^^ b2.b,
                b1.a ^^ b2.a );
  }
  `,name:T,type:u.FunctionType.ValueBased}}function _(){return function(T){const S=`${T}_`;return{body:`
  float ${S}(float a, float b) {
    return ${T}(a, b);
  }
  vec4 ${S}(vec4 v1, vec4 v2) {
    return ${T}(v1, v2);
  }
  `,name:S,type:u.FunctionType.ValueBased}}("pow")}function b(){const T="prelu_";return{body:`
  float ${T}(float a, float b) {
    return a < 0.0 ? a * b: a;
  }
  vec4 ${T}(vec4 v1, vec4 v2) {
    return vec4(
      v1.r < 0.0 ? v1.r * v2.r: v1.r,
      v1.g < 0.0 ? v1.g * v2.g: v1.g,
      v1.b < 0.0 ? v1.b * v2.b: v1.b,
      v1.a < 0.0 ? v1.a * v2.a: v1.a
      );
  }
  `,name:T,type:u.FunctionType.ValueBased}}t.glslAdd=h,t.glslDiv=f,t.glslMul=c,t.glslSub=l,t.glslEqual=n,t.glslGreater=e,t.glslLess=r,t.glslAnd=o,t.glslOr=p,t.glslXor=g,t.glslPow=_,t.glslPRelu=b;const y=(T,S,A,P=S[0].type,x)=>{const M=T.session.pack?a.TextureType.packed:a.TextureType.unpacked;return{name:A.name,inputNames:["A","B"],inputTypes:[M,M],cacheHint:x,get:()=>w(T,S,A,P)}},w=(T,S,A,P=S[0].type)=>{const x=T.session.pack?a.TextureType.packed:a.TextureType.unpacked,M=!s.ShapeUtil.areEqual(S[0].dims,S[1].dims);let N=S[0].dims;const z=T.session.pack;if(M){const G=s.BroadcastUtil.calcShape(S[0].dims,S[1].dims,!1);if(!G)throw new Error("Can't perform binary op on the given tensors");N=G;const D=N.length,R=S[0].dims.length!==0?S[0].dims.length:1,Y=S[1].dims.length!==0?S[1].dims.length:1,V=S[0].dims.length!==0?"bcastIndices_A(indices, aindices);":"aindices[0] = 0;",J=S[1].dims.length!==0?"bcastIndices_B(indices, bindices);":"bindices[0] = 0;",Z=(0,d.getGlsl)(T.session.backend.glContext.version),le=z?`
      ${A.body}
      void main() {
        vec4 a = getAAtOutCoords();
        vec4 b = getBAtOutCoords();
        vec4 result = ${A.name}(a, b);
        ${Z.output} = result;
      }`:`
      ${A.body}
      float process(int indices[${D}]) {
        int aindices[${R}];
        int bindices[${Y}];
        ${V}
        ${J}
        return ${A.name}(_A(aindices), _B(bindices));
      }`;return{name:A.name,inputNames:["A","B"],inputTypes:[x,x],output:{dims:N,type:P,textureType:x},shaderSource:le,hasMain:z}}const $=(0,d.getGlsl)(T.session.backend.glContext.version),C=`
    ${A.body}
    void main() {
      vec4 v1 = ${$.texture2D}(A, TexCoords);
      vec4 v2 = ${$.texture2D}(B, TexCoords);
      vec4 result = ${A.name}(v1, v2);
      ${$.output} = result;
    }
    `;return{name:A.name,inputNames:["A","B"],inputTypes:[x,x],output:{dims:S[0].dims,type:P,textureType:x},shaderSource:C,hasMain:!0}};t.add=(T,S)=>[T.run(y(T,S,h()),S)],t.and=(T,S)=>[T.run(y(T,S,o(),"bool"),S)],t.div=(T,S)=>[T.run(y(T,S,f()),S)],t.equal=(T,S)=>[T.run(y(T,S,n(),"bool"),S)],t.greater=(T,S)=>[T.run(y(T,S,e(),"bool"),S)],t.less=(T,S)=>[T.run(y(T,S,r(),"bool"),S)],t.mul=(T,S)=>[T.run(y(T,S,c()),S)],t.or=(T,S)=>[T.run(y(T,S,p(),"bool"),S)],t.pow=(T,S)=>[T.run(y(T,S,_()),S)],t.pRelu=(T,S)=>[T.run(y(T,S,b()),S)],t.sub=(T,S)=>[T.run(y(T,S,l()),S)],t.xor=(T,S)=>[T.run(y(T,S,g(),"bool"),S)]},4196:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseCastAttributes=t.cast=void 0;const s=i(2517);t.cast=(d,a,h)=>(u(a),[d.cast(a[0],h)]),t.parseCastAttributes=d=>s.ProtoUtil.tensorDataTypeFromProto(d.attributes.getInt("to"));const u=d=>{if(!d||d.length!==1)throw new Error("Cast requires 1 input.");if(d[0].type==="string")throw new Error("Invalid input type.")}},1163:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createPackedConcatProgramInfoLoader=void 0;const s=i(5060),u=i(2039),d=i(9390),a=i(2827);t.createPackedConcatProgramInfoLoader=(f,c,l)=>{const n=(e=c.length,r=l.cacheKey,{name:"Concat (packed)",inputNames:Array.from({length:e},(o,p)=>`X${p}`),inputTypes:Array(e).fill(u.TextureType.packed),cacheHint:r});var e,r;return Object.assign(Object.assign({},n),{get:()=>((o,p,g,_)=>{const b=g[0].dims.slice();if(_>=b.length||_<-1*b.length)throw new Error("axis specified for concat doesn't match input dimensionality");_<0&&(_=b.length+_);const y=b.slice(0);for(let V=1;V<g.length;V++){const J=g[V].dims.slice();for(let Z=0;Z<b.length;Z++)if(Z===_)y[_]+=J[Z];else if(b[Z]!==J[Z])throw new Error("non concat dimensions must match")}const w=y.length,T=(0,a.getChannels)("coords",w),S=(0,d.getCoordsDataType)(w),A=(0,a.unpackFromChannel)(),P=g.map(V=>V.dims),x=(0,d.getGlChannels)(w),M=new Array(P.length-1);M[0]=P[0][_];for(let V=1;V<M.length;V++)M[V]=M[V-1]+P[V][_];const N=x[_],z=x.slice(-2),$=x.join();let C=`if (${N} < ${M[0]}) {
        return getChannel(
            getX0(${$}), vec2(${z.join()}));
        }`;for(let V=1;V<M.length;V++){const J=M[V-1];C+=`
            if (${N} < ${M[V]}  && ${N} >= ${M[V-1]}) {
              return getChannel(
                getX${V}(${h(x,N,J)}),
                vec2(${h(z,N,J)}));
            }`}const G=M.length,D=M[M.length-1];C+=`
            return getChannel(
              getX${G}(${h(x,N,D)}),
              vec2(${h(z,N,D)}));`;const R=(0,s.getGlsl)(o.session.backend.glContext.version),Y=`
          ${A}
          float getValue(${x.map(V=>"int "+V)}) {
            ${C}
          }

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

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

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

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

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

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

          return fetchDataFromCorrectTexture(textureIndex, indices);
        }`;return Object.assign(Object.assign({},y),{output:{dims:A,type:w[0].type,textureType:u.TextureType.unpacked},shaderSource:z})})(0,p,r,o.axis)})},h=e=>`int getTextureWhereDataResides(int index) {
      ${e.map((r,o)=>`if(index<${r}) {return ${o};}
`).join("")}
    }`,f=e=>h(e),c=(e,r)=>{const o=[`float fetchDataFromCorrectTexture(int textureIndex, int indices[${r}]) {`];for(let p=0;p<e;++p)p===0?o.push(`	if (textureIndex == ${p}) { return _X${p}(indices); }`):p===e-1?o.push(`	else { return _X${p}(indices); }`):o.push(`	else if (textureIndex == ${p}) { return _X${p}(indices); }`);return o.push("	}"),o.join(`
`)},l=e=>{const r=["int getSizeInConcatAxisValueFromIndex(int index) {"];for(let o=0;o<e.length;++o)o===0?r.push(`	if (index == ${o}) { return ${e[o]}; }`):o===e.length-1?r.push(`	else { return ${e[o]}; }`):r.push(`	else if (index == ${o}) { return ${e[o]}; }`);return r.push("	}"),r.join(`
`)};t.parseConcatAttributes=e=>(0,s.createAttributeWithCacheKey)({axis:e.attributes.getInt("axis")});const n=e=>{if(!e||e.length<1)throw new Error("too few inputs");const r=e[0].type,o=e[0].dims.length;if(r==="string")throw new Error("string tensor is not supported yet");for(const p of e){if(p.type!==r)throw new Error("input tensors should be one type");if(p.dims.length!==o)throw new Error("input tensors should have the same shape")}}},4770:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createUnpackedGroupedConvProgramInfoLoader=void 0;const s=i(6231),u=i(5060),d=i(2039),a=i(8138),h=i(2823);t.createUnpackedGroupedConvProgramInfoLoader=(f,c,l)=>{const n=(e=c.length>2,r=l.cacheKey,{name:"GroupedConv",inputNames:e?["X","W","Bias"]:["X","W"],inputTypes:e?[d.TextureType.unpacked,d.TextureType.unpacked,d.TextureType.unpacked]:[d.TextureType.unpacked,d.TextureType.unpacked],cacheHint:r});var e,r;return Object.assign(Object.assign({},n),{get:()=>((o,p,g,_)=>{const b=p.length>2?"value += getBias(output_channel);":"",y=p[0].dims.slice(),w=p[1].dims.slice(),T=w[0]/_.group;s.Logger.verbose("GroupedConv",`autpPad:${_.autoPad}, dilations:${_.dilations}, group:${_.group}, kernelShape:${_.kernelShape}, pads:${_.pads}, strides:${_.strides}`);const S=(0,a.calculateOutputShape)(y,w,_.dilations,_.pads,_.strides),A=(0,u.getGlsl)(o.session.backend.glContext.version),{activationFunction:P,applyActivation:x}=(0,h.getActivationSnippet)(_),M=`
  const ivec2 strides = ivec2(${_.strides[0]}, ${_.strides[1]});
  const ivec2 pads = ivec2(${_.pads[0]}, ${_.pads[1]});
  ${P}
  void main() {
    ivec4 coords = getOutputCoords();
    int batch = coords.x;
    int output_channel = coords.y;
    ivec2 xRCCorner = coords.zw * strides - pads;
    int group_id = output_channel / ${T};

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

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

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

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

    ivec2 loc = coords.zw + pads;

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

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

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

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

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

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

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

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

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

          `;const N=`
      ${P}

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

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

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

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

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

vec4 getBAtOutCoordsMatmul(int i) {
  ${xe} coords = getOutputCoords();
  ${Ue}
  ${qe}
  vec4 outputValue = getB(${Le});
  return outputValue;
}`}(C,D,_,A)}`:"",Z=P?"getAAtOutCoordsMatmul(i)":`getA(${function(xe,se){let we="";for(let be=0;be<se-2;be++)we+=`rc.${xe[be]}, `;return we+=`rc.${xe[se-2]}, i*2`,we}(D,N)})`,le=P?"getBAtOutCoordsMatmul(i)":`getB(${function(xe,se){let we="";for(let be=0;be<se-2;be++)we+=`rc.${xe[be]}, `;return we+=`i*2, rc.${xe[se-1]}`,we}(D,z)})`,Ae=`
            ${J}
            ${V}
            ${R}
            void main() {
              ${P?"":`${C} rc =
          getOutputCoords(); int lastDim = rc.${D[G-1]}; rc.${D[G-1]} =
          rc.${D[G-2]}; rc.${D[G-2]} = lastDim;
      `}

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

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

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

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

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

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

          float value = ${y};
          int pad = 0;
          ${N}
          ${M}
          ${z}
          ${b}
          return value;
        }
      `}{const T=u.ShapeUtil.size(g.kernelShape),S=u.ShapeUtil.computeStrides(g.kernelShape),A=S.length,P=g.pads.length,x=o(A),M=r(p,"inputDims"),N=r(g.pads,"pads"),z=r(S,"kernelStrides"),$=r(g.strides,"strides");let C="";return C=g.pads.reduce((G,D)=>G+D)?`
            if (x[j] >= inputDims[j] || x[j] < 0) {
              pad++;
              isPad = true;
              break;
            }
          }
          if (!isPad) {
            ${_}
          }`:`
          }
          ${_}
        `,`
        ${x}
        float process(int indices[${w}]) {
          int x[${w}];
          copyVec(indices, x);
          int offset[${A}];
          int pads[${P}];
          int inputDims[${w}];
          int kernelStrides[${A}];
          int strides[${A}];
          ${N}
          ${M}
          ${$}
          ${z}

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

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

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

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

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

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

        vec4 result = vec4(0.0);

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

      float norm_factor = _Norm(logical_row_index);

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

      return exp(_A(indices) - _Max(logical_row_index)) / norm_factor;
    }`;return Object.assign(Object.assign({},l),{output:{dims:_.dims,type:_.type,textureType:a.TextureType.unpacked},shaderSource:x})},p=g=>{if(!g||g.length!==1)throw new Error("Softmax requires 1 input.");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type")}},5975:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseSplitAttributes=t.split=void 0;const s=i(246),u=i(2517),d=i(2039),a={name:"Split",inputNames:["A"],inputTypes:[d.TextureType.unpacked]};t.split=(l,n,e)=>{c(n);const r=u.ShapeUtil.normalizeAxis(e.axis,n[0].dims.length),o=h(l,n,r,e),p=[];for(let g=0;g<o;++g)p.push(l.run(Object.assign(Object.assign({},a),{cacheHint:`${e.cacheKey};${g}`,get:()=>f(l,n[0],e,r,g)}),n));return p},t.parseSplitAttributes=l=>{const n=l.attributes.getInt("axis",0),e=l.attributes.getInts("split",[]),r=l.outputs.length;return(0,s.createAttributeWithCacheKey)({axis:n,split:e,numOutputs:r})};const h=(l,n,e,r)=>{const[,o]=u.SplitUtil.splitShape(n[0].dims,e,r.split,r.numOutputs);return o.length},f=(l,n,e,r,o)=>{const[p,g]=u.SplitUtil.splitShape(n.dims,r,e.split,e.numOutputs),_=g[o],b=p[o],y=`
      float process(int indices[${b.length}]) {
        indices[${r}] += ${_};
        return _A(indices);
      }
    `;return Object.assign(Object.assign({},a),{cacheHint:`${e.cacheKey}:${o}`,output:{dims:b,type:n.type,textureType:d.TextureType.unpacked},shaderSource:y})},c=l=>{if(!l||l.length!==1)throw new Error("Split requires one input.");if(l[0].type!=="int8"&&l[0].type!=="uint8"&&l[0].type!=="int16"&&l[0].type!=="uint16"&&l[0].type!=="int32"&&l[0].type!=="uint32"&&l[0].type!=="float32"&&l[0].type!=="float64"&&l[0].type!=="bool")throw new Error("Invalid input type.")}},3933:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseSqueezeAttributes=t.squeezeV13=t.squeeze=void 0;const s=i(2517);t.squeeze=(a,h,f)=>{u(h);const c=s.ShapeUtil.squeezeShape(h[0].dims,f);return[a.reshapeUnpacked(h[0],c)]},t.squeezeV13=(a,h)=>(d(h),(0,t.squeeze)(a,[h[0]],Array.from(h[1].integerData))),t.parseSqueezeAttributes=a=>a.attributes.getInts("axes");const u=a=>{if(!a||a.length!==1)throw new Error("Squeeze requires 1 input.");if(a[0].type==="string")throw new Error("invalid input tensor types.")},d=a=>{if(!a||a.length!==2)throw new Error("Squeeze requires 2 inputs.");if(a[1].type!=="int32")throw new Error("Invalid input type.")}},6558:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.sum=void 0;const s=i(5060),u=i(2039);t.sum=(h,f)=>{a(f);const c={name:"Sum",inputNames:f.map((l,n)=>`X${n}`),inputTypes:new Array(f.length).fill(u.TextureType.unpacked)};return[h.run(Object.assign(Object.assign({},c),{get:()=>d(h,f,c)}),f)]};const d=(h,f,c)=>{const l=(0,s.getGlsl)(h.session.backend.glContext.version),n=f[0].dims.slice(),e=`
      void main() {
        vec4 result = ${f.map((r,o)=>`${l.texture2D}(X${o},TexCoords)`).join(" + ")};
        ${l.output} = result;
      }
    `;return Object.assign(Object.assign({},c),{output:{dims:n,type:f[0].type,textureType:u.TextureType.unpacked},hasMain:!0,shaderSource:e})},a=h=>{if(!h||h.length===0)throw new Error("Sum requires inputs.");const f=h[0].dims.length;for(let c=1;c<h.length;c++){if(f!==h[c].dims.length)throw new Error("Input shapes are mismatched.");for(let l=0;l<f;l++)if(h[0].dims[l]!==h[c].dims[l])throw new Error("Input shapes are not matched.")}if(h[0].type!=="float32"&&h[0].type!=="float64")throw new Error("Invalid input type.");for(let c=1;c<h.length;c++)if(h[0].type!==h[c].type)throw new Error("Input types are not matched.")}},5723:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.tile=void 0;const s=i(782),u=i(2039);t.tile=(h,f)=>{a(f);const c={name:"Tile",inputNames:["A"],inputTypes:[u.TextureType.unpacked]};return[h.run(Object.assign(Object.assign({},c),{get:()=>d(h,f,c)}),f)]};const d=(h,f,c)=>{const l=f[0].dims.slice(),n=new Array(l.length),e=[];for(let p=0;p<l.length;p++)n[p]=l[p]*f[1].numberData[p],e.push(`inputIdx[${p}] = int(mod(float(outputIdx[${p}]), ${l[p]}.));`);const r=n.length,o=`
      float process(int outputIdx[${r}]) {
        int inputIdx[${r}];
        ${e.join(`
`)}
        return _A(inputIdx);
      }
    `;return Object.assign(Object.assign({},c),{output:{dims:n,type:f[0].type,textureType:u.TextureType.unpacked},shaderSource:o})},a=h=>{if(!h||h.length!==2)throw new Error("Tile requires 2 input.");if(h[1].dims.length!==1)throw new Error("The second input shape must 1 dimension.");if(h[1].dims[0]!==h[0].dims.length)throw new Error("Invalid input shape.");if(s.NUMBER_TYPES.indexOf(h[0].type)===-1)throw new Error("Invalid input type.");if(h[1].type!=="int32"&&h[1].type!=="int16")throw new Error("Invalid repeat type.")}},3738:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.parseTransposeAttributes=t.transpose=void 0;const s=i(246),u=i(2517),d=i(2039),a={name:"Transpose",inputNames:["A"],inputTypes:[d.TextureType.unpacked]};t.transpose=(e,r,o)=>(n(r),[e.run(Object.assign(Object.assign({},a),{cacheHint:o.cacheKey,get:()=>h(e,r[0],o.perm)}),r)]),t.parseTransposeAttributes=e=>(0,s.createAttributeWithCacheKey)({perm:e.attributes.getInts("perm",[])});const h=(e,r,o)=>{const p=r.dims;o=f(p,o);const g=c(p,o),_=p.length,b=`
      ${l("perm",o,_)}
      float process(int indices[${_}]) {
        int a[${_}];
        perm(a, indices);
        return _A(a);
      }`;return Object.assign(Object.assign({},a),{output:{dims:g,type:r.type,textureType:d.TextureType.unpacked},shaderSource:b})},f=(e,r)=>(r&&r.length!==e.length&&(r=[...e.keys()].reverse()),r),c=(e,r)=>(r=f(e,r),u.ShapeUtil.sortBasedOnPerm(e,r)),l=(e,r,o)=>{const p=[];p.push(`void ${e}(out int a[${o}], int src[${o}]) {`);for(let g=0;g<o;++g)p.push(`	a[${r[g]}]=src[${g}];`);return p.push("	}"),p.join(`
`)},n=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:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.encodeAsUint8=void 0;const s=i(5060),u=i(2039);t.encodeAsUint8=(d,a)=>{const h=a.shape,f=(0,s.getGlsl)(d.session.backend.glContext.version),c=`
    const float FLOAT_MAX = 1.70141184e38;
    const float FLOAT_MIN = 1.17549435e-38;

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

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

      highp float av = abs(v);

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

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

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

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

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

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

      return c / 255.0;
    }

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

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

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

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

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

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

      ${w}

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

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

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

      ${w}

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

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

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

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

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

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

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

      ${w}

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

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

      input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1;

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

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

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

      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[0]);
      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[0]);
      return y0 + float(x_offset) * (y1 - y0) / float(scales[1]);
    }`;return Object.assign(Object.assign({},a),{output:{dims:o,type:c[0].type,textureType:d.TextureType.unpacked},shaderSource:S,variables:[{name:"scales",type:"int",arrayLength:l.scales.length,data:l.scales.map(A=>Math.ceil(A))}]})};t.validateInputs=(f,c)=>{if(!f||c.opset<9&&f.length!==1||c.opset>=9&&c.opset<11&&f.length!==2||c.opset>=11&&f.length<2)throw new Error("invalid inputs.");if(c.scales.length>0&&f[0].dims.length!==c.scales.length)throw new Error("Invalid input shape.");if(f[0].type==="string")throw new Error("Invalid input tensor types.")},t.scalesValidation=(f,c,l)=>{if(l){for(const n of f)if(n<=0)throw new Error("Scale value should be greater than 0.")}else for(const n of f)if(n<1)throw new Error("Scale value should be greater than or equal to 1.");if(!(c!=="linear"&&c!=="cubic"||f.length===2||f.length===4&&f[0]===1&&f[1]===1))throw new Error(`'Linear' mode and 'Cubic' mode only support 2-D inputs ('Bilinear', 'Bicubic')         or 4-D inputs with the corresponding outermost 2 scale values being 1         in the ${l?"Resize":"Upsample"} opeartor.`)}},1958:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ProgramManager=void 0;const s=i(1670),u=i(6231),d=i(8879),a=i(5060);t.ProgramManager=class{constructor(h,f,c){this.profiler=h,this.glContext=f,this.textureLayoutStrategy=c,this.repo=new Map,this.attributesBound=!1}getArtifact(h){return this.repo.get(h)}setArtifact(h,f){this.repo.set(h,f)}run(h,f,c){var l;this.profiler.event("op",`ProgramManager.run ${(l=h.programInfo.name)!==null&&l!==void 0?l:"unknown kernel"}`,()=>{var n;const e=this.glContext.gl,r=h.program;e.useProgram(r);try{this.bindOutput(c),this.attributesBound||this.bindAttributes(h.attribLocations),this.bindUniforms(h.uniformLocations,(n=h.programInfo.variables)!==null&&n!==void 0?n:[],f)}catch(o){throw u.Logger.error("ProgramManager",h.programInfo.shaderSource),o}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,f,c){return this.profiler.event("backend","ProgramManager.build",()=>{const l=new d.GlslPreprocessor(this.glContext,h,f,c),n=l.preprocess(),e=this.compile(n);return{programInfo:h,program:e,uniformLocations:this.getUniformLocations(e,l.context.programInfo.inputNames,l.context.programInfo.variables),attribLocations:this.getAttribLocations(e)}})}compile(h){if(!this.vertexShader){u.Logger.verbose("ProrgramManager","Compiling and caching Vertex shader for the first time");const l=(0,a.getVertexShaderSource)(this.glContext.version);this.vertexShader=this.glContext.compileShader(l,this.glContext.gl.VERTEX_SHADER)}s.env.debug&&u.Logger.verbose("ProrgramManager",`FragShader:
${h}
`);const f=this.glContext.compileShader(h,this.glContext.gl.FRAGMENT_SHADER),c=this.glContext.createProgram(this.vertexShader,f);return this.glContext.deleteShader(f),c}bindOutput(h){const f=h.width,c=h.height;u.Logger.verbose("ProrgramManager",`Binding output texture to Framebuffer: w/h=${f}/${c}, shape=${h.shape}, type=${h.tensor.type}`),this.glContext.attachFramebuffer(h.texture,f,c)}bindAttributes(h){const f=h.position,c=h.textureCoord;this.glContext.setVertexAttributes(f,c),this.attributesBound=!0}bindUniforms(h,f,c){var l;const n=this.glContext.gl;let e=0;for(const{name:r,type:o,location:p,arrayLength:g}of h){const _=(l=f.find(b=>b.name===r))===null||l===void 0?void 0:l.data;if(o!=="sampler2D"&&!_)throw new Error(`variable '${r}' does not have data defined in program info`);switch(o){case"sampler2D":this.bindTexture(c[e],p,e),e++;break;case"float":g?n.uniform1fv(p,_):n.uniform1f(p,_);break;case"int":g?n.uniform1iv(p,_):n.uniform1i(p,_);break;default:throw new Error(`Uniform not implemented: ${o}`)}}}bindTexture(h,f,c){this.glContext.bindTextureToUniform(h.texture,c,f)}getAttribLocations(h){return{position:this.getAttribLocation(h,"position"),textureCoord:this.getAttribLocation(h,"textureCoord")}}getUniformLocations(h,f,c){const l=[];if(f)for(const n of f)l.push({name:n,type:"sampler2D",location:this.getUniformLocation(h,n)});if(c)for(const n of c)l.push(Object.assign(Object.assign({},n),{location:this.getUniformLocation(h,n.name)}));return l}getUniformLocation(h,f){const c=this.glContext.gl.getUniformLocation(h,f);if(c===null)throw new Error(`Uniform ${f} not found.`);return c}getAttribLocation(h,f){return this.glContext.gl.getAttribLocation(h,f)}}},6416:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.WebGLSessionHandler=void 0;const s=i(6231),u=i(1047),d=i(8316),a=i(1640),h=i(1958),f=i(7859),c=i(5702);t.WebGLSessionHandler=class{constructor(l,n){this.backend=l,this.context=n,this.layoutStrategy=new f.PreferLogicalStrategy(l.glContext.maxTextureSize),this.programManager=new h.ProgramManager(this.context.profiler,l.glContext,this.layoutStrategy),this.textureManager=new c.TextureManager(l.glContext,this.layoutStrategy,this.context.profiler,{reuseTextures:l.textureCacheMode==="full"}),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new Map,this.pack=l.pack,this.pack2unpackMap=new Map,this.unpack2packMap=new Map}createInferenceHandler(){return new d.WebGLInferenceHandler(this)}onGraphInitialized(l){const n=l.getValues().filter(e=>e.from===-1&&e.tensor).map(e=>e.tensor.dataId);this.initializers=new Set(n)}isInitializer(l){return!!this.initializers&&this.initializers.has(l)}addInitializer(l){this.initializers.add(l)}getTextureData(l,n){return n?this.packedTextureDataCache.get(l):this.unpackedTextureDataCache.get(l)}setTextureData(l,n,e=!1){s.Logger.verbose("WebGLSessionHandler","Storing Texture data in cache"),e?this.packedTextureDataCache.set(l,n):this.unpackedTextureDataCache.set(l,n)}dispose(){this.programManager.dispose(),this.textureManager.clearActiveTextures(),this.packedTextureDataCache.forEach(l=>this.textureManager.releaseTexture(l,!0)),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache.forEach(l=>this.textureManager.releaseTexture(l,!0)),this.unpackedTextureDataCache=new Map}resolve(l,n,e){const r=(0,u.resolveOperator)(l,n,a.WEBGL_OP_RESOLVE_RULES);return{impl:r.opImpl,context:r.opInit?r.opInit(l,e):l}}}},7769:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.Uint8DataEncoder=t.RGBAFloatDataEncoder=t.RedFloat32DataEncoder=void 0;const s=i(6231);t.RedFloat32DataEncoder=class{constructor(u,d=1){if(d===1)this.internalFormat=u.R32F,this.format=u.RED,this.textureType=u.FLOAT,this.channelSize=d;else{if(d!==4)throw new Error(`Invalid number of channels: ${d}`);this.internalFormat=u.RGBA32F,this.format=u.RGBA,this.textureType=u.FLOAT,this.channelSize=d}}encode(u,d){let a,h;return u.constructor!==Float32Array&&(s.Logger.warning("Encoder","data was not of type Float32; creating new Float32Array"),h=new Float32Array(u)),d*this.channelSize>u.length?(s.Logger.warning("Encoder","Source data too small. Allocating larger array"),h=u,a=this.allocate(d*this.channelSize),h.forEach((f,c)=>a[c]=f)):(h=u,a=h),a}allocate(u){return new Float32Array(4*u)}decode(u,d){return this.channelSize===1?u.filter((a,h)=>h%4==0).subarray(0,d):u.subarray(0,d)}},t.RGBAFloatDataEncoder=class{constructor(u,d=1,a){if(d!==1&&d!==4)throw new Error(`Invalid number of channels: ${d}`);this.internalFormat=u.RGBA,this.format=u.RGBA,this.channelSize=d,this.textureType=a||u.FLOAT}encode(u,d){let a=u;return this.channelSize===1&&(s.Logger.verbose("Encoder","Exploding into a larger array"),a=this.allocate(d),u.forEach((h,f)=>a[4*f]=h)),a}allocate(u){return new Float32Array(4*u)}decode(u,d){return this.channelSize===1?u.filter((a,h)=>h%4==0).subarray(0,d):u.subarray(0,d)}},t.Uint8DataEncoder=class{constructor(u,d=1){if(this.channelSize=4,d===1)this.internalFormat=u.ALPHA,this.format=u.ALPHA,this.textureType=u.UNSIGNED_BYTE,this.channelSize=d;else{if(d!==4)throw new Error(`Invalid number of channels: ${d}`);this.internalFormat=u.RGBA,this.format=u.RGBA,this.textureType=u.UNSIGNED_BYTE,this.channelSize=d}}encode(u,d){return new Uint8Array(u.buffer,u.byteOffset,u.byteLength)}allocate(u){return new Uint8Array(u*this.channelSize)}decode(u,d){if(u instanceof Uint8Array)return u.subarray(0,d);throw new Error(`Invalid array type: ${u.constructor}`)}}},7859:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.getBatchDim=t.sizeToSquarishShape=t.getRowsCols=t.sizeFromShape=t.isInt=t.parseAxisParam=t.squeezeShape=t.PreferLogicalStrategy=t.AlwaysKeepOriginalSizeStrategy=void 0;const s=i(6231),u=i(2517);function d(l,n){const e=[],r=[],o=n!=null&&Array.isArray(n)&&n.length===0,p=n==null||o?null:a(n,l).sort();let g=0;for(let _=0;_<l.length;++_){if(p!=null){if(p[g]===_&&l[_]!==1)throw new Error(`Can't squeeze axis ${_} since its dim '${l[_]}' is not 1`);(p[g]==null||p[g]>_)&&l[_]===1&&(e.push(l[_]),r.push(_)),p[g]<=_&&g++}l[_]!==1&&(e.push(l[_]),r.push(_))}return{newShape:e,keptDims:r}}function a(l,n){const e=n.length;return l=l==null?n.map((r,o)=>o):[].concat(l),(0,u.assert)(l.every(r=>r>=-e&&r<e),()=>`All values in axis param must be in range [-${e}, ${e}) but got axis ${l}`),(0,u.assert)(l.every(h),()=>`All values in axis param must be integers but got axis ${l}`),l.map(r=>r<0?e+r:r)}function h(l){return l%1==0}function f(l){if(l.length===0)return 1;let n=l[0];for(let e=1;e<l.length;e++)n*=l[e];return n}function c(l){const n=Math.ceil(Math.sqrt(l));return[n,Math.ceil(l/n)]}t.AlwaysKeepOriginalSizeStrategy=class{constructor(l){this.maxTextureSize=l}computeTextureWH(l,n){if(l.length===0)return[1,1];const e=this.maxTextureSize;if(n&&n.breakAxis!==void 0){const p=n.breakAxis>=l.length?1:l.slice(n.breakAxis).reduce((_,b)=>_*b),g=n.breakAxis<=0?1:l.slice(0,n.breakAxis).reduce((_,b)=>_*b);if(!(p>e||g>e))return[p,g];s.Logger.verbose("TextureLayout",`Given width/height preferences were unattainable: shape:${l}, breakAxis:${n.breakAxis}`)}const r=l.reduce((p,g)=>p*g);let o=Math.floor(Math.sqrt(r));for(;o<e&&o<r&&r%o!=0;o++);if(o>=e||r%o!=0)throw new Error(`The given dimensions are outside this GPU's boundaries: ${l}`);return[o,r/o]}},t.PreferLogicalStrategy=class{constructor(l){this.maxTextureSize=l}computeTextureWH(l,n){const e=this.computeTexture(l,n);return n&&n.isPacked&&(e[0]/=2,e[1]/=2),n&&n.reverseWH?[e[1],e[0]]:e}computeTexture(l,n){const e=n&&n.isPacked;if(l.length===0)return e?[2,2]:[1,1];let r=this.maxTextureSize;if(n&&n.breakAxis!==void 0){const g=n.breakAxis>=l.length?1:l.slice(n.breakAxis).reduce((b,y)=>b*y),_=n.breakAxis<=0?1:l.slice(0,n.breakAxis).reduce((b,y)=>b*y);if(!(g>r||_>r))return[g,_];s.Logger.verbose("TextureLayout",`Given width/height preferences were unattainable: shape:${l}, breakAxis:${n.breakAxis}`)}let o=l.slice(0);e&&(r*=2,o=o.map((g,_)=>_>=o.length-2?o[_]%2==0?o[_]:o[_]+1:o[_]),o.length===1&&(o=[2,o[0]])),o.length!==2&&(o=d(o).newShape);const p=f(o);return o.length<=1&&p<=r?[1,p]:o.length===2&&o[0]<=r&&o[1]<=r?o:o.length===3&&o[0]*o[1]<=r&&o[2]<=r?[o[0]*o[1],o[2]]:o.length===3&&o[0]<=r&&o[1]*o[2]<=r?[o[0],o[1]*o[2]]:o.length===4&&o[0]*o[1]*o[2]<=r&&o[3]<=r?[o[0]*o[1]*o[2],o[3]]:o.length===4&&o[0]<=r&&o[1]*o[2]*o[3]<=r?[o[0],o[1]*o[2]*o[3]]:e?c(p/4).map(g=>2*g):c(p)}},t.squeezeShape=d,t.parseAxisParam=a,t.isInt=h,t.sizeFromShape=f,t.getRowsCols=function(l){if(l.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[l.length>1?l[l.length-2]:1,l[l.length-1]]},t.sizeToSquarishShape=c,t.getBatchDim=function(l,n=2){return f(l.slice(0,l.length-n))}},4057:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createTextureLayoutFromShape=t.calculateTextureWidthAndHeight=t.createTextureLayoutFromTextureType=void 0;const s=i(2517),u=i(2039);t.createTextureLayoutFromTextureType=(d,a,h)=>{const f=h===u.TextureType.unpacked||h===u.TextureType.unpackedReversed?1:4,c=h===u.TextureType.packed,l=h===u.TextureType.unpackedReversed||h===u.TextureType.packed,n=h===u.TextureType.packedLastDimension?a.length-1:void 0,e=h===u.TextureType.packedLastDimension?a.map((r,o)=>o===a.length-1?4*r:r):void 0;return(0,t.createTextureLayoutFromShape)(d,a,f,e,{isPacked:c,reverseWH:l,breakAxis:n})},t.calculateTextureWidthAndHeight=(d,a,h)=>{const f=(0,t.createTextureLayoutFromTextureType)(d,a,h);return[f.width,f.height]},t.createTextureLayoutFromShape=(d,a,h=1,f,c)=>{const l=!(!c||!c.isPacked),[n,e]=d.computeTextureWH(l&&f||a,c),r=a.length;let o=a.slice(0);if(r===0&&(o=[1]),h===1)f=a;else if(l){if(h!==4)throw new Error("a packed texture must be 4-channel");f=a,r>0&&(o[r-1]=Math.ceil(o[r-1]/2)),r>1&&(o[r-2]=Math.ceil(o[r-2]/2))}else if(!f)throw new Error("Unpacked shape is needed when using channels > 1");return{width:n,height:e,channels:h,isPacked:l,shape:o,strides:s.ShapeUtil.computeStrides(o),unpackedShape:f,reversedWH:c&&c.reverseWH}}},5702:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.TextureManager=void 0;const s=i(6231);t.TextureManager=class{constructor(u,d,a,h){this.glContext=u,this.layoutStrategy=d,this.profiler=a,this.config=h,this.pendingRead=new Map,h.reuseTextures&&(this.inUseTextures=new Map,this.idleTextures=new Map,this.textureLookup=new Map)}createTextureFromLayout(u,d,a,h){const f=this.toEncoderType(u),c=this.glContext.getEncoder(f,d.channels||1,h);if(d.isPacked&&h===1)throw new Error("not implemented");const l=d.width,n=d.height;let e,r;if(this.config.reuseTextures){e=`${l}x${n}_${c.format}_${c.internalFormat}_${c.textureType}`,r=this.inUseTextures.get(e),r||(r=[],this.inUseTextures.set(e,r));const p=this.idleTextures.get(e);if(p&&p.length>0){const g=p.pop();return r.push(g),h===1&&this.glContext.updateTexture(g,l,n,c,this.toTextureData(u,a)),g}}s.Logger.verbose("TextureManager",`Creating new texture of size ${d.width}x${d.height}`);const o=this.glContext.allocateTexture(l,n,c,this.toTextureData(u,a));return this.config.reuseTextures&&(r.push(o),this.textureLookup.set(o,e)),o}readTexture(u,d,a){return a||(a=1),this.profiler.event("backend","TextureManager.readTexture",()=>{const h=u.shape.reduce((c,l)=>c*l)*a,f=this.glContext.readTexture(u.texture,u.width,u.height,h,this.toEncoderType(d),a);return this.toTensorData(d,f)})}async readTextureAsync(u,d,a){const h=u.tensor.dataId;if(a||(a=1),this.pendingRead.has(h)){const f=this.pendingRead.get(h);return new Promise(c=>f==null?void 0:f.push(c))}return this.profiler.event("backend","TextureManager.readTextureAsync",async()=>{this.pendingRead.set(h,[]);const f=u.shape.reduce((e,r)=>e*r)*a;await this.glContext.createAndWaitForFence();const c=this.glContext.readTexture(u.texture,u.width,u.height,f,this.toEncoderType(d),a),l=this.toTensorData(d,c),n=this.pendingRead.get(h);return this.pendingRead.delete(h),n==null||n.forEach(e=>e(l)),l})}readUint8TextureAsFloat(u){return this.profiler.event("backend","TextureManager.readUint8TextureAsFloat",()=>{const d=u.shape.reduce((h,f)=>h*f),a=this.glContext.readTexture(u.texture,u.width,u.height,4*d,"byte",4);return new Float32Array(a.buffer,a.byteOffset,d)})}releaseTexture(u,d){let a;if(this.config.reuseTextures&&(a=this.textureLookup.get(u.texture),a)){d&&this.textureLookup.delete(a);const h=this.inUseTextures.get(a);if(h){const f=h.indexOf(u.texture);if(f!==-1){h.splice(f,1);let c=this.idleTextures.get(a);c||(c=[],this.idleTextures.set(a,c)),c.push(u.texture)}}}a&&!d||(s.Logger.verbose("TextureManager",`Deleting texture of size ${u.width}x${u.height}`),this.glContext.deleteTexture(u.texture))}toTensorData(u,d){switch(u){case"int16":return d instanceof Int16Array?d:Int16Array.from(d);case"int32":return d instanceof Int32Array?d:Int32Array.from(d);case"int8":return d instanceof Int8Array?d:Int8Array.from(d);case"uint16":return d instanceof Uint16Array?d:Uint16Array.from(d);case"uint32":return d instanceof Uint32Array?d:Uint32Array.from(d);case"uint8":case"bool":return d instanceof Uint8Array?d:Uint8Array.from(d);case"float32":return d instanceof Float32Array?d:Float32Array.from(d);case"float64":return d instanceof Float64Array?d:Float64Array.from(d);default:throw new Error(`TensorData type ${u} is not supported`)}}toTextureData(u,d){if(d)return d instanceof Float32Array?d:new Float32Array(d)}toEncoderType(u){return"float"}clearActiveTextures(){this.glContext.clearActiveTextures()}}},2039:(m,t)=>{var i;Object.defineProperty(t,"__esModule",{value:!0}),t.TextureType=void 0,(i=t.TextureType||(t.TextureType={}))[i.unpacked=0]="unpacked",i[i.unpackedReversed=1]="unpackedReversed",i[i.packed=2]="packed",i[i.downloadUint8AsFloat=3]="downloadUint8AsFloat",i[i.packedLastDimension=4]="packedLastDimension"},9390:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.getGlChannels=t.getCoordsDataType=t.getSqueezedParams=t.squeezeInputShape=t.generateShaderFuncNameFromInputSamplerNameAtOutCoords=t.generateShaderFuncNameFromInputSamplerName=t.repeatedTry=t.getPackedShape=void 0;const s=i(2517);t.getPackedShape=function(u){const d=u.length;return u.slice(0,d-1).concat(u[d-1]/4)},t.repeatedTry=async function(u,d=h=>0,a){return new Promise((h,f)=>{let c=0;const l=()=>{if(u())return void h();c++;const n=d(c);a!=null&&c>=a?f():setTimeout(l,n)};l()})},t.generateShaderFuncNameFromInputSamplerName=function(u){return(0,s.assert)(u!==void 0&&u.length!==0,()=>"empty string found for sampler name"),"get"+u.charAt(0).toUpperCase()+u.slice(1)},t.generateShaderFuncNameFromInputSamplerNameAtOutCoords=function(u){return(0,s.assert)(u!==void 0&&u.length!==0,()=>"empty string found for sampler name"),"get"+u.charAt(0).toUpperCase()+u.slice(1)+"AtOutCoords"},t.squeezeInputShape=function(u,d){let a=JSON.parse(JSON.stringify(u));return a=d,a},t.getSqueezedParams=function(u,d){return d.map(a=>u[a]).join(", ")},t.getCoordsDataType=function(u){if(u<=1)return"int";if(u===2)return"ivec2";if(u===3)return"ivec3";if(u===4)return"ivec4";if(u===5)return"ivec5";if(u===6)return"ivec6";throw Error(`GPU for rank ${u} is not yet supported`)},t.getGlChannels=function(u=6){return["x","y","z","w","u","v"].slice(0,u)}},7305:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.createNewWebGLContext=t.createWebGLContext=void 0;const s=i(6231),u=i(1713),d={};function a(h){const f=function(){if(typeof document>"u"){if(typeof OffscreenCanvas>"u")throw new TypeError("failed to create canvas: OffscreenCanvas is not supported");return new OffscreenCanvas(1,1)}const n=document.createElement("canvas");return n.width=1,n.height=1,n}();let c;const l={alpha:!1,depth:!1,antialias:!1,stencil:!1,preserveDrawingBuffer:!1,premultipliedAlpha:!1,failIfMajorPerformanceCaveat:!1};if((!h||h==="webgl2")&&(c=f.getContext("webgl2",l),c))try{return new u.WebGLContext(c,2)}catch(n){s.Logger.warning("GlContextFactory",`failed to create WebGLContext using contextId 'webgl2'. Error: ${n}`)}if((!h||h==="webgl")&&(c=f.getContext("webgl",l)||f.getContext("experimental-webgl",l),c))try{return new u.WebGLContext(c,1)}catch(n){s.Logger.warning("GlContextFactory",`failed to create WebGLContext using contextId 'webgl' or 'experimental-webgl'. Error: ${n}`)}throw new Error("WebGL is not supported")}t.createWebGLContext=function h(f){let c;f&&f!=="webgl2"||!("webgl2"in d)?f&&f!=="webgl"||!("webgl"in d)||(c=d.webgl):c=d.webgl2,c=c||a(f),f=f||c.version===1?"webgl":"webgl2";const l=c.gl;return d[f]=c,l.isContextLost()?(delete d[f],h(f)):(l.disable(l.DEPTH_TEST),l.disable(l.STENCIL_TEST),l.disable(l.BLEND),l.disable(l.DITHER),l.disable(l.POLYGON_OFFSET_FILL),l.disable(l.SAMPLE_COVERAGE),l.enable(l.SCISSOR_TEST),l.enable(l.CULL_FACE),l.cullFace(l.BACK),c)},t.createNewWebGLContext=a},1713:function(m,t,i){var s=this&&this.__createBinding||(Object.create?function(l,n,e,r){r===void 0&&(r=e);var o=Object.getOwnPropertyDescriptor(n,e);o&&!("get"in o?!n.__esModule:o.writable||o.configurable)||(o={enumerable:!0,get:function(){return n[e]}}),Object.defineProperty(l,r,o)}:function(l,n,e,r){r===void 0&&(r=e),l[r]=n[e]}),u=this&&this.__setModuleDefault||(Object.create?function(l,n){Object.defineProperty(l,"default",{enumerable:!0,value:n})}:function(l,n){l.default=n}),d=this&&this.__importStar||function(l){if(l&&l.__esModule)return l;var n={};if(l!=null)for(var e in l)e!=="default"&&Object.prototype.hasOwnProperty.call(l,e)&&s(n,l,e);return u(n,l),n};Object.defineProperty(t,"__esModule",{value:!0}),t.WebGLContext=t.linearSearchLastTrue=void 0;const a=i(1670),h=d(i(7769)),f=i(9390);function c(l){let n=0;for(;n<l.length&&l[n]();++n);return n-1}t.linearSearchLastTrue=c,t.WebGLContext=class{constructor(l,n){this.frameBufferBound=!1,this.itemsToPoll=[],this.gl=l,this.version=n,this.getExtensions(),this.vertexbuffer=this.createVertexbuffer(),this.framebuffer=this.createFramebuffer(),this.queryVitalParameters()}allocateTexture(l,n,e,r){const o=this.gl,p=o.createTexture();o.bindTexture(o.TEXTURE_2D,p),o.texParameteri(o.TEXTURE_2D,o.TEXTURE_MIN_FILTER,o.NEAREST),o.texParameteri(o.TEXTURE_2D,o.TEXTURE_MAG_FILTER,o.NEAREST),o.texParameteri(o.TEXTURE_2D,o.TEXTURE_WRAP_S,o.CLAMP_TO_EDGE),o.texParameteri(o.TEXTURE_2D,o.TEXTURE_WRAP_T,o.CLAMP_TO_EDGE);const g=r?e.encode(r,l*n):null;return o.texImage2D(o.TEXTURE_2D,0,e.internalFormat,l,n,0,e.format,e.textureType,g),this.checkError(),p}updateTexture(l,n,e,r,o){const p=this.gl;p.bindTexture(p.TEXTURE_2D,l);const g=r.encode(o,n*e);p.texSubImage2D(p.TEXTURE_2D,0,0,0,n,e,r.format,r.textureType,g),this.checkError()}attachFramebuffer(l,n,e){const r=this.gl;r.bindTexture(r.TEXTURE_2D,l),r.bindFramebuffer(r.FRAMEBUFFER,this.framebuffer),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,l,0),this.checkError(),r.viewport(0,0,n,e),r.scissor(0,0,n,e)}readTexture(l,n,e,r,o,p){const g=this.gl;p||(p=1),this.frameBufferBound||this.attachFramebuffer(l,n,e);const _=this.getEncoder(o,p),b=_.allocate(n*e);return g.bindTexture(g.TEXTURE_2D,l),g.framebufferTexture2D(g.FRAMEBUFFER,g.COLOR_ATTACHMENT0,g.TEXTURE_2D,l,0),g.readPixels(0,0,n,e,g.RGBA,_.textureType,b),this.checkError(),_.decode(b,r)}isFramebufferReady(){return!0}getActiveTexture(){const l=this.gl;return"TEXTURE"+(l.getParameter(this.gl.ACTIVE_TEXTURE)-l.TEXTURE0)}getTextureBinding(){return this.gl.getParameter(this.gl.TEXTURE_BINDING_2D)}getFramebufferBinding(){return this.gl.getParameter(this.gl.FRAMEBUFFER_BINDING)}setVertexAttributes(l,n){const e=this.gl;e.vertexAttribPointer(l,3,e.FLOAT,!1,20,0),e.enableVertexAttribArray(l),n!==-1&&(e.vertexAttribPointer(n,2,e.FLOAT,!1,20,12),e.enableVertexAttribArray(n)),this.checkError()}createProgram(l,n){const e=this.gl,r=e.createProgram();return e.attachShader(r,l),e.attachShader(r,n),e.linkProgram(r),r}compileShader(l,n){const e=this.gl,r=e.createShader(n);if(!r)throw new Error(`createShader() returned null with type ${n}`);if(e.shaderSource(r,l),e.compileShader(r),e.getShaderParameter(r,e.COMPILE_STATUS)===!1)throw new Error(`Failed to compile shader: ${e.getShaderInfoLog(r)}
Shader source:
${l}`);return r}deleteShader(l){this.gl.deleteShader(l)}bindTextureToUniform(l,n,e){const r=this.gl;r.activeTexture(r.TEXTURE0+n),this.checkError(),r.bindTexture(r.TEXTURE_2D,l),this.checkError(),r.uniform1i(e,n),this.checkError()}draw(){this.gl.drawArrays(this.gl.TRIANGLE_STRIP,0,4),this.checkError()}checkError(){if(a.env.debug){const l=this.gl,n=l.getError();let e="";switch(n){case l.NO_ERROR:return;case l.INVALID_ENUM:e="INVALID_ENUM";break;case l.INVALID_VALUE:e="INVALID_VALUE";break;case l.INVALID_OPERATION:e="INVALID_OPERATION";break;case l.INVALID_FRAMEBUFFER_OPERATION:e="INVALID_FRAMEBUFFER_OPERATION";break;case l.OUT_OF_MEMORY:e="OUT_OF_MEMORY";break;case l.CONTEXT_LOST_WEBGL:e="CONTEXT_LOST_WEBGL";break;default:e=`Unknown WebGL Error: ${n.toString(16)}`}throw new Error(e)}}deleteTexture(l){this.gl.deleteTexture(l)}deleteProgram(l){this.gl.deleteProgram(l)}getEncoder(l,n,e=0){if(this.version===2)return new h.RedFloat32DataEncoder(this.gl,n);switch(l){case"float":return e===1||this.isRenderFloat32Supported?new h.RGBAFloatDataEncoder(this.gl,n):new h.RGBAFloatDataEncoder(this.gl,n,this.textureHalfFloatExtension.HALF_FLOAT_OES);case"int":throw new Error("not implemented");case"byte":return new h.Uint8DataEncoder(this.gl,n);default:throw new Error(`Invalid dataType: ${l}`)}}clearActiveTextures(){const l=this.gl;for(let n=0;n<this.maxTextureImageUnits;++n)l.activeTexture(l.TEXTURE0+n),l.bindTexture(l.TEXTURE_2D,null)}dispose(){if(this.disposed)return;const l=this.gl;l.bindFramebuffer(l.FRAMEBUFFER,null),l.deleteFramebuffer(this.framebuffer),l.bindBuffer(l.ARRAY_BUFFER,null),l.deleteBuffer(this.vertexbuffer),l.bindBuffer(l.ELEMENT_ARRAY_BUFFER,null),l.finish(),this.disposed=!0}createDefaultGeometry(){return new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0])}createVertexbuffer(){const l=this.gl,n=l.createBuffer();if(!n)throw new Error("createBuffer() returned null");const e=this.createDefaultGeometry();return l.bindBuffer(l.ARRAY_BUFFER,n),l.bufferData(l.ARRAY_BUFFER,e,l.STATIC_DRAW),this.checkError(),n}createFramebuffer(){const l=this.gl.createFramebuffer();if(!l)throw new Error("createFramebuffer returned null");return l}queryVitalParameters(){const l=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 supported");this.isBlendSupported=!this.isRenderFloat32Supported||this.checkFloat32Blend(),this.maxTextureSize=l.getParameter(l.MAX_TEXTURE_SIZE),this.maxTextureImageUnits=l.getParameter(l.MAX_TEXTURE_IMAGE_UNITS),this.version}getExtensions(){this.version===2?(this.colorBufferFloatExtension=this.gl.getExtension("EXT_color_buffer_float"),this.disjointTimerQueryWebgl2Extension=this.gl.getExtension("EXT_disjoint_timer_query_webgl2")):(this.textureFloatExtension=this.gl.getExtension("OES_texture_float"),this.textureHalfFloatExtension=this.gl.getExtension("OES_texture_half_float"))}checkFloatTextureAttachableToFrameBuffer(){const l=this.gl,n=l.createTexture();l.bindTexture(l.TEXTURE_2D,n);const e=this.version===2?l.RGBA32F:l.RGBA;l.texImage2D(l.TEXTURE_2D,0,e,1,1,0,l.RGBA,l.FLOAT,null);const r=l.createFramebuffer();l.bindFramebuffer(l.FRAMEBUFFER,r),l.framebufferTexture2D(l.FRAMEBUFFER,l.COLOR_ATTACHMENT0,l.TEXTURE_2D,n,0);const o=l.checkFramebufferStatus(l.FRAMEBUFFER)===l.FRAMEBUFFER_COMPLETE;return l.bindTexture(l.TEXTURE_2D,null),l.bindFramebuffer(l.FRAMEBUFFER,null),l.deleteTexture(n),l.deleteFramebuffer(r),o}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 l=this.gl;let n,e,r,o,p;try{n=l.createTexture(),e=l.createFramebuffer(),l.bindTexture(l.TEXTURE_2D,n);const g=this.version===2?l.RGBA32F:l.RGBA;return l.texImage2D(l.TEXTURE_2D,0,g,1,1,0,l.RGBA,l.FLOAT,null),l.bindFramebuffer(l.FRAMEBUFFER,e),l.framebufferTexture2D(l.FRAMEBUFFER,l.COLOR_ATTACHMENT0,l.TEXTURE_2D,n,0),l.enable(l.BLEND),r=l.createShader(l.VERTEX_SHADER),!!r&&(l.shaderSource(r,"void main(){}"),l.compileShader(r),o=l.createShader(l.FRAGMENT_SHADER),!!o&&(l.shaderSource(o,"precision highp float;void main(){gl_FragColor=vec4(0.5);}"),l.compileShader(o),p=l.createProgram(),!!p&&(l.attachShader(p,r),l.attachShader(p,o),l.linkProgram(p),l.useProgram(p),l.drawArrays(l.POINTS,0,1),l.getError()===l.NO_ERROR)))}finally{l.disable(l.BLEND),p&&l.deleteProgram(p),r&&l.deleteShader(r),o&&l.deleteShader(o),e&&(l.bindFramebuffer(l.FRAMEBUFFER,null),l.deleteFramebuffer(e)),n&&(l.bindTexture(l.TEXTURE_2D,null),l.deleteTexture(n))}}beginTimer(){if(this.version===2&&this.disjointTimerQueryWebgl2Extension){const l=this.gl,n=this.disjointTimerQueryWebgl2Extension,e=l.createQuery();return l.beginQuery(n.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 l=this.gl,n=this.disjointTimerQueryWebgl2Extension;l.endQuery(n.TIME_ELAPSED_EXT)}}isTimerResultAvailable(l){let n=!1,e=!1;if(this.version!==2||!this.disjointTimerQueryWebgl2Extension)throw new Error("WebGL1 profiling currently not supported");{const r=this.gl,o=this.disjointTimerQueryWebgl2Extension;n=r.getQueryParameter(l,r.QUERY_RESULT_AVAILABLE),e=r.getParameter(o.GPU_DISJOINT_EXT)}return n&&!e}getTimerResult(l){let n=0;if(this.version!==2)throw new Error("WebGL1 profiling currently not supported");{const e=this.gl;n=e.getQueryParameter(l,e.QUERY_RESULT),e.deleteQuery(l)}return n/1e6}async waitForQueryAndGetTime(l){return await(0,f.repeatedTry)(()=>this.isTimerResultAvailable(l)),this.getTimerResult(l)}async createAndWaitForFence(){const l=this.createFence(this.gl);return this.pollFence(l)}createFence(l){let n;const e=l,r=e.fenceSync(e.SYNC_GPU_COMMANDS_COMPLETE,0);return l.flush(),n=r===null?()=>!0:()=>{const o=e.clientWaitSync(r,0,0);return o===e.ALREADY_SIGNALED||o===e.CONDITION_SATISFIED},{query:r,isFencePassed:n}}async pollFence(l){return new Promise(n=>{this.addItemToPoll(()=>l.isFencePassed(),()=>n())})}pollItems(){const l=c(this.itemsToPoll.map(n=>n.isDoneFn));for(let n=0;n<=l;++n){const{resolveFn:e}=this.itemsToPoll[n];e()}this.itemsToPoll=this.itemsToPoll.slice(l+1)}async addItemToPoll(l,n){this.itemsToPoll.push({isDoneFn:l,resolveFn:n}),this.itemsToPoll.length>1||await(0,f.repeatedTry)(()=>(this.pollItems(),this.itemsToPoll.length===0))}}},1036:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ExecutionPlan=void 0;const s=i(6231);class u{constructor(a,h){this.op=a,this.node=h}}t.ExecutionPlan=class{constructor(d,a,h){this.graph=d,this.profiler=h,this.initialize(a)}initialize(d){this.profiler.event("session","ExecutionPlan.initialize",()=>{const a=this.graph.getNodes();if(a.length!==d.length)throw new Error("The size of nodes and OPs do not match.");this._ops=d.map((h,f)=>new u(h,a[f])),this.reset(),this._starter=[],this._ops.forEach((h,f)=>{let c=!0;for(const l of h.node.inputs)if(!this._values[l]&&this.graph.getInputIndices().indexOf(l)===-1){c=!1;break}c&&this._starter.push(f)})})}reset(){this._values=this.graph.getValues().map(d=>d.tensor)}async execute(d,a){return this.profiler.event("session","ExecutionPlan.execute",async()=>{this.reset();const h=d.createInferenceHandler(),f=this.graph.getInputIndices();if(a.length!==f.length)throw new Error(`number of input tensors don't match the number of inputs to the model: actual: ${a.length} expected: ${f.length}`);a.forEach((o,p)=>{const g=f[p];this._values[g]=o});const c=this._starter.slice(0),l=this.graph.getValues(),n=this.graph.getNodes();let e=0;for(;e<c.length;){const o=c[e++],p=this._ops[o],g=p.node.inputs.map(w=>this._values[w]);if(g.indexOf(void 0)!==-1)throw new Error(`unresolved input detected: op: ${p.node}`);const _=g;s.Logger.verbose("ExecPlan",`Runing op:${p.node.name} (${_.map((w,T)=>`'${p.node.inputs[T]}': ${w.type}[${w.dims.join(",")}]`).join(", ")})`);const b=await this.profiler.event("node",p.node.name,async()=>p.op.impl(h,_,p.op.context));if(b.length!==p.node.outputs.length)throw new Error("the size of output does not match model definition.");b.forEach((w,T)=>{const S=p.node.outputs[T];if(this._values[S])throw new Error(`output [${S}] already has value: op:${p.node.name}`);this._values[S]=w});const y=new Set;b.forEach((w,T)=>{const S=p.node.outputs[T];for(const A of l[S].to){const P=n[A];let x=!0;for(const M of P.inputs)if(!this._values[M]){x=!1;break}x&&y.add(A)}}),c.push(...y)}const r=[];for(let o=0;o<this.graph.getOutputIndices().length;o++){const p=this.graph.getOutputIndices()[o],g=this._values[p];if(g===void 0)throw new Error(`required output [${p}] does not have value`);p===0?await g.getData():g.data,r.push(g)}return s.Logger.verbose("ExecPlan","disposing of inferenceHandler"),h.dispose(),r})}}},7070:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.Graph=void 0;const s=i(1446),u=i(7778),d=i(9395),a=i(9162),h=i(2517);var f=d.onnxruntime.experimental.fbs;t.Graph={from:(e,r)=>new n(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 l{constructor(r,o){r instanceof s.onnx.NodeProto?(this.name=r.name,this.opType=r.opType,this.attributes=new u.Attribute(r.attribute)):r instanceof f.Node&&(this.name=o??r.name(),this.opType=r.opType(),this.attributes=new u.Attribute(h.ProtoUtil.tensorAttributesFromORTFormat(r))),this.inputs=[],this.outputs=[],this.executeNode=!0}}class n{constructor(r,o){if(!r)throw new TypeError("graph is empty");this.buildGraph(r),this.transformGraph(o),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 s.onnx.GraphProto)this.buildGraphFromOnnxFormat(r);else{if(!(r instanceof f.Graph))throw new TypeError("Graph type is not supported.");this.buildGraphFromOrtFormat(r)}}buildGraphFromOnnxFormat(r){const o=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const p=new Map;if(!r.input)throw new Error("missing information in graph: input");const g=[];for(const _ of r.input){if(o.has(_.name))throw new Error(`duplicated input name: ${_.name}`);const b=this._allData.push(new c(_))-1;o.set(_.name,b),g.push(_.name)}if(!r.initializer)throw new Error("missing information in graph: initializer");for(const _ of r.initializer){let b=o.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,o.set(_.name,b)}this._allData[b]._from=-1,this._allData[b].tensor=a.Tensor.fromProto(_)}for(let _=0;_<this._allData.length;_++)this._allData[_].tensor||(this._allInputIndices.push(_),this._allInputNames.push(g[_]));if(!r.output)throw new Error("missing information in graph: output");for(const _ of r.output){if(o.has(_.name))throw new Error(`duplicated output name: ${_.name}`);const b=this._allData.push(new c(_))-1;o.set(_.name,b),this._allOutputIndices.push(b),this._allOutputNames.push(_.name)}if(!r.node)throw new Error("missing information in graph: node");for(const _ of r.node){if(!_.name)for(let y=0;;y++){const w=`unnamed_${_.opType}_${y}`;if(!p.has(w)){_.name=w;break}}if(p.has(_.name))throw new Error(`duplicated node name: ${_.name}`);const b=this._nodes.push(new l(_))-1;p.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 w of y.output){let T=o.get(w);if(T===void 0&&(T=this._allData.push(new c)-1,o.set(w,T)),b.outputs.push(T),this._allData[T]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${T}`);if(this._allData[T]._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[T]._from=-1,this._allData[T].tensor=a.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: ${y.name}`);for(const w of y.input){const T=o.get(w);if(T===void 0){if(w===""&&y.input.length===3&&y.opType==="Resize")continue;throw new Error(`unrecognized input '${w}' for node: ${y.name}`)}b.inputs.push(T),this._allData[T]._to.push(_)}}return!0}buildGraphFromOrtFormat(r){var o,p,g;const _=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const b=new Map,y=[];for(let w=0;w<r.inputsLength();w++){const T=r.inputs(w);if(_.has(T))throw new Error(`duplicated input name: ${T}`);for(let S=0;S<r.nodeArgsLength();S++)if(((o=r.nodeArgs(S))===null||o===void 0?void 0:o.name())===T){const A=new c;if(((g=(p=r.nodeArgs(S))===null||p===void 0?void 0:p.type())===null||g===void 0?void 0:g.valueType())!==f.TypeInfoValue.tensor_type)throw new Error("Unexpected value type for the nodeArg.");const P=r.nodeArgs(S).type().value(new f.TensorTypeAndShape),x=h.ProtoUtil.tensorDataTypeFromProto(P.elemType()),M=P.shape(),N=[];for(let $=0;$<M.dimLength();$++)N.push(h.LongUtil.longToNumber(M.dim($).value().dimValue()));A.type={shape:{dims:N},tensorType:x};const z=this._allData.push(A)-1;_.set(T,z),y.push(T)}}for(let w=0;w<r.initializersLength();w++){const T=r.initializers(w);let S=_.get(T.name());if(S===void 0){const A=new c,P=h.ProtoUtil.tensorDimsFromORTFormat(T),x=h.ProtoUtil.tensorDataTypeFromProto(T.dataType());A.type={shape:{dims:P},tensorType:x},S=this._allData.push(A)-1,_.set(T.name(),S)}this._allData[S]._from=-1,this._allData[S].tensor=a.Tensor.fromOrtTensor(T)}for(let w=0;w<this._allData.length;w++)this._allData[w].tensor||(this._allInputIndices.push(w),this._allInputNames.push(y[w]));for(let w=0;w<r.outputsLength();w++){const T=r.outputs(w);if(_.has(T))throw new Error(`duplicated output name: ${T}`);const S=this._allData.push(new c)-1;_.set(T,S),this._allOutputIndices.push(S),this._allOutputNames.push(T)}if(!r.nodes)throw new Error("missing information in graph: node");for(let w=0;w<r.nodesLength();w++){const T=r.nodes(w);let S=T.name();if(!S)for(let P=0;S=`unnamed_${T.opType()}_${P}`,b.has(S);P++);if(b.has(S))throw new Error(`duplicated node name: ${S}`);const A=this._nodes.push(new l(T,S))-1;b.set(S,A)}for(let w=0;w<this._nodes.length;w++){const T=this._nodes[w],S=r.nodes(w);if(S==null)throw new Error(`No node exists at index ${w}`);if((S==null?void 0:S.outputsLength())===0)throw new Error(`missing output for node: ${S.name}`);for(let A=0;A<(S==null?void 0:S.outputsLength());A++){const P=S==null?void 0:S.outputs(A);let x=_.get(P);if(x===void 0&&(x=this._allData.push(new c)-1,_.set(P,x)),T.outputs.push(x),this._allData[x]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${x}`);if(this._allData[x]._from=w,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");T.outputs.pop(),T.executeNode=!1,this._allData[x]._from=-1,this._allData[x].tensor=a.Tensor.fromOrtTensor(S.attributes(0).t())}}}for(let w=0;w<this._nodes.length;w++){const T=this._nodes[w],S=r.nodes(w);if(S.inputsLength()===0)throw new Error(`missing input for node: ${S.name}`);for(let A=0;A<S.inputsLength();A++){const P=S.inputs(A),x=_.get(P);if(x===void 0)throw new Error(`unrecognized input '${P}' for node: ${S.name()}`);T.inputs.push(x),this._allData[x]._to.push(w)}}}checkIsAcyclic(){const r=new Set;this._allInputIndices.forEach(g=>{this._allData[g]._to.forEach(_=>{r.add(_)})});const o=Array.from(r),p=new Array(this._nodes.length).fill("white");for(;o.length>0;){const g=o.pop();p[g]==="gray"?p[g]="black":(o.push(g),p[g]="gray",this._nodes[g].outputs.forEach(_=>{const b=this._allData[_];if(b.tensor!==void 0)throw new Error("node outputs should not be initialized");if(b._from!==g)throw new Error("from property of the Value object doesn't match index of Node being processed");b._to.forEach(y=>{if(p[y]==="gray")throw new Error("model graph is cyclic");p[y]==="white"&&o.push(y)})}))}}transformGraph(r){this.removeAllIdentityNodes(),this.removeAllDropoutNodes(),this.fuseConvActivationNodes(),r&&r.transformGraph(this),this.finalizeGraph()}finalizeGraph(){let r=0;for(let o=0;o<this._nodes.length;o++)this._nodes[o].executeNode?r>0&&(this._nodes[o].inputs.forEach(p=>{const g=this._allData[p]._to.indexOf(o+r);g!==-1&&(this._allData[p]._to[g]=o)}),this._nodes[o].outputs.forEach(p=>{this._allData[p]._from&&this._allData[p]._from===o+r&&(this._allData[p]._from=o)})):(r++,this._nodes[o].outputs.forEach(p=>{this._allData[p]._from=-2}),this._nodes.splice(o,1),o--);r=0;for(let o=0;o<this._allData.length;o++)if(this._allData[o].from!==-2||this._allOutputIndices.indexOf(o+r)!==-1){if(r>0){let p=-1;this._allData[o].from!==void 0&&this._allData[o].from!==-1?(p=this._nodes[this._allData[o].from].outputs.indexOf(o+r),p!==-1&&(this._nodes[this._allData[o].from].outputs[p]=o)):(p=this._allInputIndices.indexOf(o+r),p!==-1&&(this._allInputIndices[p]=o)),this._allData[o].to.forEach(g=>{p=this._nodes[g].inputs.indexOf(o+r),p!==-1&&(this._nodes[g].inputs[p]=o)}),this._allData[o].to.length===0&&(p=this._allOutputIndices.indexOf(o+r),p!==-1&&(this._allOutputIndices[p]=o))}}else r++,this._allData.splice(o,1),o--}deleteNode(r){const o=this._nodes[r];if(o.outputs.length>1){for(let w=1;w<o.outputs.length;w++)if(this._allData[o.outputs[w]].to.length>0)throw new Error("Node deletion with more than one output connected to other nodes is not supported. ")}o.executeNode=!1;const p=o.inputs[0],g=o.outputs[0],_=this._allData[g].to,b=this._allData[p].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[p].to.splice(b,1),this._allData[g]._to=[];const y=this._allOutputIndices.indexOf(g);if(y!==-1&&(this._allOutputIndices[y]=p),_&&_.length>0)for(const w of _){const T=this._nodes[w].inputs.indexOf(g);if(T===-1)throw new Error("The Node object doesn't have the output Value in it's 'inputs' property ");this._nodes[w].inputs[T]=p,this._allData[p].to.push(w)}}removeAllDropoutNodes(){let r=0;for(const o of this._nodes){if(o.opType==="Dropout"){if(o.inputs.length!==1)throw new Error("Dropout nodes should only contain one input. ");if(o.outputs.length!==1&&o.outputs.length!==2)throw new Error("Dropout nodes should contain either 1 or 2 output(s)");if(o.outputs.length===2&&this._allData[o.outputs[1]]._to.length!==0)throw new Error("Dropout nodes's second output should not be referenced by other nodes");this.deleteNode(r)}r++}}removeAllIdentityNodes(){let r=0;for(const o of this._nodes)o.opType==="Identity"&&this.deleteNode(r),r++}isActivation(r){switch(r.opType){case"Relu":case"Sigmoid":case"Clip":return!0;default:return!1}}fuseConvActivationNodes(){for(const r of this._nodes)if(r.opType==="Conv"){const o=this._allData[r.outputs[0]]._to;if(o.length===1&&this.isActivation(this._nodes[o[0]])){const 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r=this.bb.__offset(this.bb_pos,14);return r?this.bb.__string(this.bb.__vector(this.bb_pos+r)+4*n,e):null}inputsLength(){let n=this.bb.__offset(this.bb_pos,14);return n?this.bb.__vector_len(this.bb_pos+n):0}outputs(n,e){let r=this.bb.__offset(this.bb_pos,16);return r?this.bb.__string(this.bb.__vector(this.bb_pos+r)+4*n,e):null}outputsLength(){let n=this.bb.__offset(this.bb_pos,16);return n?this.bb.__vector_len(this.bb_pos+n):0}sparseInitializers(n,e){let r=this.bb.__offset(this.bb_pos,18);return r?(e||new a.experimental.fbs.SparseTensor).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*n),this.bb):null}sparseInitializersLength(){let n=this.bb.__offset(this.bb_pos,18);return n?this.bb.__vector_len(this.bb_pos+n):0}static startGraph(n){n.startObject(8)}static addInitializers(n,e){n.addFieldOffset(0,e,0)}static createInitializersVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startInitializersVector(n,e){n.startVector(4,e,4)}static addNodeArgs(n,e){n.addFieldOffset(1,e,0)}static createNodeArgsVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startNodeArgsVector(n,e){n.startVector(4,e,4)}static addNodes(n,e){n.addFieldOffset(2,e,0)}static createNodesVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startNodesVector(n,e){n.startVector(4,e,4)}static addMaxNodeIndex(n,e){n.addFieldInt32(3,e,0)}static addNodeEdges(n,e){n.addFieldOffset(4,e,0)}static createNodeEdgesVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startNodeEdgesVector(n,e){n.startVector(4,e,4)}static addInputs(n,e){n.addFieldOffset(5,e,0)}static createInputsVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startInputsVector(n,e){n.startVector(4,e,4)}static addOutputs(n,e){n.addFieldOffset(6,e,0)}static createOutputsVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startOutputsVector(n,e){n.startVector(4,e,4)}static addSparseInitializers(n,e){n.addFieldOffset(7,e,0)}static createSparseInitializersVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startSparseInitializersVector(n,e){n.startVector(4,e,4)}static endGraph(n){return n.endObject()}static createGraph(n,e,r,o,p,g,_,b,y){return c.startGraph(n),c.addInitializers(n,e),c.addNodeArgs(n,r),c.addNodes(n,o),c.addMaxNodeIndex(n,p),c.addNodeEdges(n,g),c.addInputs(n,_),c.addOutputs(n,b),c.addSparseInitializers(n,y),c.endGraph(n)}}f.Graph=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(a){(function(h){(function(f){class c{constructor(){this.bb=null,this.bb_pos=0}__init(n,e){return this.bb_pos=n,this.bb=e,this}static getRootAsModel(n,e){return(e||new c).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsModel(n,e){return n.setPosition(n.position()+s.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(n.readInt32(n.position())+n.position(),n)}irVersion(){let n=this.bb.__offset(this.bb_pos,4);return n?this.bb.readInt64(this.bb_pos+n):this.bb.createLong(0,0)}opsetImport(n,e){let r=this.bb.__offset(this.bb_pos,6);return r?(e||new a.experimental.fbs.OperatorSetId).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*n),this.bb):null}opsetImportLength(){let n=this.bb.__offset(this.bb_pos,6);return n?this.bb.__vector_len(this.bb_pos+n):0}producerName(n){let e=this.bb.__offset(this.bb_pos,8);return e?this.bb.__string(this.bb_pos+e,n):null}producerVersion(n){let e=this.bb.__offset(this.bb_pos,10);return e?this.bb.__string(this.bb_pos+e,n):null}domain(n){let e=this.bb.__offset(this.bb_pos,12);return e?this.bb.__string(this.bb_pos+e,n):null}modelVersion(){let n=this.bb.__offset(this.bb_pos,14);return n?this.bb.readInt64(this.bb_pos+n):this.bb.createLong(0,0)}docString(n){let e=this.bb.__offset(this.bb_pos,16);return e?this.bb.__string(this.bb_pos+e,n):null}graph(n){let e=this.bb.__offset(this.bb_pos,18);return e?(n||new a.experimental.fbs.Graph).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}graphDocString(n){let e=this.bb.__offset(this.bb_pos,20);return e?this.bb.__string(this.bb_pos+e,n):null}static startModel(n){n.startObject(9)}static addIrVersion(n,e){n.addFieldInt64(0,e,n.createLong(0,0))}static addOpsetImport(n,e){n.addFieldOffset(1,e,0)}static createOpsetImportVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startOpsetImportVector(n,e){n.startVector(4,e,4)}static addProducerName(n,e){n.addFieldOffset(2,e,0)}static addProducerVersion(n,e){n.addFieldOffset(3,e,0)}static addDomain(n,e){n.addFieldOffset(4,e,0)}static addModelVersion(n,e){n.addFieldInt64(5,e,n.createLong(0,0))}static addDocString(n,e){n.addFieldOffset(6,e,0)}static addGraph(n,e){n.addFieldOffset(7,e,0)}static addGraphDocString(n,e){n.addFieldOffset(8,e,0)}static endModel(n){return n.endObject()}static createModel(n,e,r,o,p,g,_,b,y,w){return c.startModel(n),c.addIrVersion(n,e),c.addOpsetImport(n,r),c.addProducerName(n,o),c.addProducerVersion(n,p),c.addDomain(n,g),c.addModelVersion(n,_),c.addDocString(n,b),c.addGraph(n,y),c.addGraphDocString(n,w),c.endModel(n)}}f.Model=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(a){(function(h){(function(f){class c{constructor(){this.bb=null,this.bb_pos=0}__init(n,e){return this.bb_pos=n,this.bb=e,this}static getRootAsKernelCreateInfos(n,e){return(e||new c).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsKernelCreateInfos(n,e){return n.setPosition(n.position()+s.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(n.readInt32(n.position())+n.position(),n)}nodeIndices(n){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.readUint32(this.bb.__vector(this.bb_pos+e)+4*n):0}nodeIndicesLength(){let n=this.bb.__offset(this.bb_pos,4);return n?this.bb.__vector_len(this.bb_pos+n):0}nodeIndicesArray(){let n=this.bb.__offset(this.bb_pos,4);return n?new Uint32Array(this.bb.bytes().buffer,this.bb.bytes().byteOffset+this.bb.__vector(this.bb_pos+n),this.bb.__vector_len(this.bb_pos+n)):null}kernelDefHashes(n){let e=this.bb.__offset(this.bb_pos,6);return e?this.bb.readUint64(this.bb.__vector(this.bb_pos+e)+8*n):this.bb.createLong(0,0)}kernelDefHashesLength(){let n=this.bb.__offset(this.bb_pos,6);return n?this.bb.__vector_len(this.bb_pos+n):0}static startKernelCreateInfos(n){n.startObject(2)}static addNodeIndices(n,e){n.addFieldOffset(0,e,0)}static createNodeIndicesVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addInt32(e[r]);return n.endVector()}static startNodeIndicesVector(n,e){n.startVector(4,e,4)}static addKernelDefHashes(n,e){n.addFieldOffset(1,e,0)}static createKernelDefHashesVector(n,e){n.startVector(8,e.length,8);for(let r=e.length-1;r>=0;r--)n.addInt64(e[r]);return n.endVector()}static startKernelDefHashesVector(n,e){n.startVector(8,e,8)}static endKernelCreateInfos(n){return n.endObject()}static createKernelCreateInfos(n,e,r){return c.startKernelCreateInfos(n),c.addNodeIndices(n,e),c.addKernelDefHashes(n,r),c.endKernelCreateInfos(n)}}f.KernelCreateInfos=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(a){(function(h){(function(f){class c{constructor(){this.bb=null,this.bb_pos=0}__init(n,e){return this.bb_pos=n,this.bb=e,this}static getRootAsSubGraphSessionState(n,e){return(e||new c).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsSubGraphSessionState(n,e){return n.setPosition(n.position()+s.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(n.readInt32(n.position())+n.position(),n)}graphId(n){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,n):null}sessionState(n){let e=this.bb.__offset(this.bb_pos,6);return e?(n||new a.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startSubGraphSessionState(n){n.startObject(2)}static addGraphId(n,e){n.addFieldOffset(0,e,0)}static addSessionState(n,e){n.addFieldOffset(1,e,0)}static endSubGraphSessionState(n){let e=n.endObject();return n.requiredField(e,4),e}static createSubGraphSessionState(n,e,r){return c.startSubGraphSessionState(n),c.addGraphId(n,e),c.addSessionState(n,r),c.endSubGraphSessionState(n)}}f.SubGraphSessionState=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(a){(function(h){(function(f){class c{constructor(){this.bb=null,this.bb_pos=0}__init(n,e){return this.bb_pos=n,this.bb=e,this}static getRootAsSessionState(n,e){return(e||new c).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsSessionState(n,e){return n.setPosition(n.position()+s.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(n.readInt32(n.position())+n.position(),n)}kernels(n){let e=this.bb.__offset(this.bb_pos,4);return e?(n||new a.experimental.fbs.KernelCreateInfos).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}subGraphSessionStates(n,e){let r=this.bb.__offset(this.bb_pos,6);return r?(e||new a.experimental.fbs.SubGraphSessionState).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+r)+4*n),this.bb):null}subGraphSessionStatesLength(){let n=this.bb.__offset(this.bb_pos,6);return n?this.bb.__vector_len(this.bb_pos+n):0}static startSessionState(n){n.startObject(2)}static addKernels(n,e){n.addFieldOffset(0,e,0)}static addSubGraphSessionStates(n,e){n.addFieldOffset(1,e,0)}static createSubGraphSessionStatesVector(n,e){n.startVector(4,e.length,4);for(let r=e.length-1;r>=0;r--)n.addOffset(e[r]);return n.endVector()}static startSubGraphSessionStatesVector(n,e){n.startVector(4,e,4)}static endSessionState(n){return n.endObject()}static createSessionState(n,e,r){return c.startSessionState(n),c.addKernels(n,e),c.addSubGraphSessionStates(n,r),c.endSessionState(n)}}f.SessionState=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={})),function(a){(function(h){(function(f){class c{constructor(){this.bb=null,this.bb_pos=0}__init(n,e){return this.bb_pos=n,this.bb=e,this}static getRootAsInferenceSession(n,e){return(e||new c).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsInferenceSession(n,e){return n.setPosition(n.position()+s.flatbuffers.SIZE_PREFIX_LENGTH),(e||new c).__init(n.readInt32(n.position())+n.position(),n)}static bufferHasIdentifier(n){return n.__has_identifier("ORTM")}ortVersion(n){let e=this.bb.__offset(this.bb_pos,4);return e?this.bb.__string(this.bb_pos+e,n):null}model(n){let e=this.bb.__offset(this.bb_pos,6);return e?(n||new a.experimental.fbs.Model).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}sessionState(n){let e=this.bb.__offset(this.bb_pos,8);return e?(n||new a.experimental.fbs.SessionState).__init(this.bb.__indirect(this.bb_pos+e),this.bb):null}static startInferenceSession(n){n.startObject(3)}static addOrtVersion(n,e){n.addFieldOffset(0,e,0)}static addModel(n,e){n.addFieldOffset(1,e,0)}static addSessionState(n,e){n.addFieldOffset(2,e,0)}static endInferenceSession(n){return n.endObject()}static finishInferenceSessionBuffer(n,e){n.finish(e,"ORTM")}static finishSizePrefixedInferenceSessionBuffer(n,e){n.finish(e,"ORTM",!0)}static createInferenceSession(n,e,r,o){return c.startInferenceSession(n),c.addOrtVersion(n,e),c.addModel(n,r),c.addSessionState(n,o),c.endInferenceSession(n)}}f.InferenceSession=c})(h.fbs||(h.fbs={}))})(a.experimental||(a.experimental={}))}(t.onnxruntime||(t.onnxruntime={}))},7448:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.OnnxjsSessionHandler=void 0;const s=i(1670),u=i(9162);t.OnnxjsSessionHandler=class{constructor(d){this.session=d,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(d,a,h){const f=new Map;for(const n in d)if(Object.hasOwnProperty.call(d,n)){const e=d[n];f.set(n,new u.Tensor(e.dims,e.type,void 0,void 0,e.data))}const c=await this.session.run(f),l={};return c.forEach((n,e)=>{l[e]=new s.Tensor(n.type,n.data,n.dims)}),l}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(m,t,i)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.Session=void 0;const s=i(7067),u=i(1296),d=i(7091),a=i(1036),h=i(6231),f=i(2644);t.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,l,n){await this.profiler.event("session","Session.loadModel",async()=>{const e=await(0,d.resolveBackend)(this.backendHint);if(this.sessionHandler=e.createSessionHandler(this.context),this._model=new f.Model,typeof c=="string"){const r=c.endsWith(".ort");if(typeof fetch>"u"){const o=await(0,u.promisify)(s.readFile)(c);this.initialize(o,r)}else{const o=await fetch(c),p=await o.arrayBuffer();this.initialize(new Uint8Array(p),r)}}else if(ArrayBuffer.isView(c))this.initialize(c);else{const r=new Uint8Array(c,l||0,n||c.byteLength);this.initialize(r)}})}initialize(c,l){if(this._initialized)throw new Error("already initialized");this.profiler.event("session","Session.initialize",()=>{const n=this.sessionHandler.transformGraph?this.sessionHandler:void 0;this._model.load(c,n,l),this.sessionHandler.onGraphInitialized&&this.sessionHandler.onGraphInitialized(this._model.graph),this.initializeOps(this._model.graph),this._executionPlan=new a.ExecutionPlan(this._model.graph,this._ops,this.profiler)}),this._initialized=!0}async run(c){if(!this._initialized)throw new Error("session not initialized yet");return this.profiler.event("session","Session.run",async()=>{const l=this.normalizeAndValidateInputs(c),n=await this._executionPlan.execute(this.sessionHandler,l);return this.createOutput(n)})}normalizeAndValidateInputs(c){const l=this._model.graph.getInputNames();if(Array.isArray(c)){if(c.length!==l.length)throw new Error(`incorrect input array length: expected ${l.length} but got ${c.length}`)}else{if(c.size!==l.length)throw new Error(`incorrect input map size: expected ${l.length} but got ${c.size}`);const n=new Array(c.size);let e=0;for(let r=0;r<l.length;++r){const o=c.get(l[r]);if(!o)throw new Error(`missing input tensor for: '${name}'`);n[e++]=o}c=n}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 n=this._model.graph.getInputIndices(),e=this._model.graph.getValues(),r=new Array(n.length);for(let o=0;o<n.length;++o){const p=e[n[o]];r[o]=p.type.shape.dims,this.context.graphInputTypes.push(p.type.tensorType),this.context.graphInputDims.push(c[o].dims)}this.validateInputTensorDims(r,c,!0)}return this.validateInputTensorTypes(this.context.graphInputTypes,c),c}validateInputTensorTypes(c,l){for(let n=0;n<l.length;n++){const e=c[n],r=l[n].type;if(e!==r)throw new Error(`input tensor[${n}] check failed: expected type '${e}' but got ${r}`)}}validateInputTensorDims(c,l,n){for(let e=0;e<l.length;e++){const r=c[e],o=l[e].dims;if(!this.compareTensorDims(r,o,n))throw new Error(`input tensor[${e}] check failed: expected shape '[${r.join(",")}]' but got [${o.join(",")}]`)}}compareTensorDims(c,l,n){if(c.length!==l.length)return!1;for(let e=0;e<c.length;++e)if(c[e]!==l[e]&&(!n||c[e]!==0))return!1;return!0}createOutput(c){const l=this._model.graph.getOutputNames();if(c.length!==l.length)throw new Error("expected number of outputs do not match number of generated outputs");const n=new Map;for(let e=0;e<l.length;++e)n.set(l[e],c[e]);return n}initializeOps(c){const l=c.getNodes();this._ops=new Array(l.length);for(let n=0;n<l.length;n++)this._ops[n]=this.sessionHandler.resolve(l[n],this._model.opsets,c)}}},9162:function(m,t,i){var s=this&&this.__importDefault||function(p){return p&&p.__esModule?p:{default:p}};Object.defineProperty(t,"__esModule",{value:!0}),t.Tensor=void 0;const u=i(3442),d=s(i(3720)),a=i(1446),h=i(9395),f=i(2517);var c=h.onnxruntime.experimental.fbs;class l{get data(){if(this.cache===void 0){const g=this.dataProvider(this.dataId);if(g.length!==this.size)throw new Error("Length of data provided by the Data Provider is inconsistent with the dims of this Tensor.");this.cache=g}return this.cache}get stringData(){if(this.type!=="string")throw new TypeError("data type is not string");return this.data}get integerData(){switch(this.type){case"uint8":case"int8":case"uint16":case"int16":case"int32":case"uint32":case"bool":return this.data;default:throw new TypeError("data type is not integer (uint8, int8, uint16, int16, int32, uint32, bool)")}}get floatData(){switch(this.type){case"float32":case"float64":return this.data;default:throw new TypeError("data type is not float (float32, float64)")}}get numberData(){if(this.type!=="string")return this.data;throw new TypeError("type cannot be non-number (string)")}get(g){return this.data[f.ShapeUtil.indicesToOffset(g,this.strides)]}set(g,_){this.data[f.ShapeUtil.indicesToOffset(g,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=f.ShapeUtil.computeStrides(this.dims)),this._strides}constructor(g,_,b,y,w,T=u.Guid.create()){this.dims=g,this.type=_,this.dataProvider=b,this.asyncDataProvider=y,this.cache=w,this.dataId=T,this.size=f.ShapeUtil.validateDimsAndCalcSize(g);const S=this.size,A=b===void 0&&y===void 0&&w===void 0;if(w!==void 0&&w.length!==S)throw new RangeError("Input dims doesn't match data length.");if(_==="string"){if(!(w===void 0||Array.isArray(w)&&w.every(P=>typeof P=="string")))throw new TypeError("cache should be a string array");A&&(this.cache=new Array(S))}else{if(w!==void 0){const P=e(_);if(!(w instanceof P))throw new TypeError(`cache should be type ${P.name}`)}if(A){const P=new ArrayBuffer(S*function(x){switch(x){case"bool":case"int8":case"uint8":return 1;case"int16":case"uint16":return 2;case"int32":case"uint32":case"float32":return 4;case"float64":return 8;default:throw new Error(`cannot calculate sizeof() on type ${x}`)}}(_));this.cache=function(x,M){return new(e(M))(x)}(P,_)}}}static fromProto(g){if(!g)throw new Error("cannot construct Value from an empty tensor");const _=f.ProtoUtil.tensorDataTypeFromProto(g.dataType),b=f.ProtoUtil.tensorDimsFromProto(g.dims),y=new l(b,_);if(_==="string")g.stringData.forEach((w,T)=>{y.data[T]=(0,f.decodeUtf8String)(w)});else if(g.rawData&&typeof g.rawData.byteLength=="number"&&g.rawData.byteLength>0){const w=y.data,T=new DataView(g.rawData.buffer,g.rawData.byteOffset,g.rawData.byteLength),S=n(g.dataType),A=g.rawData.byteLength/S;if(g.rawData.byteLength%S!=0)throw new Error("invalid buffer length");if(w.length!==A)throw new Error("buffer length mismatch");for(let P=0;P<A;P++){const x=o(T,g.dataType,P*S);w[P]=x}}else{let w;switch(g.dataType){case a.onnx.TensorProto.DataType.FLOAT:w=g.floatData;break;case a.onnx.TensorProto.DataType.INT32:case a.onnx.TensorProto.DataType.INT16:case a.onnx.TensorProto.DataType.UINT16:case a.onnx.TensorProto.DataType.INT8:case a.onnx.TensorProto.DataType.UINT8:case a.onnx.TensorProto.DataType.BOOL:w=g.int32Data;break;case a.onnx.TensorProto.DataType.INT64:w=g.int64Data;break;case a.onnx.TensorProto.DataType.DOUBLE:w=g.doubleData;break;case a.onnx.TensorProto.DataType.UINT32:case a.onnx.TensorProto.DataType.UINT64:w=g.uint64Data;break;default:throw new Error("unspecific error")}if(w==null)throw new Error("failed to populate data from a tensorproto value");const T=y.data;if(T.length!==w.length)throw new Error("array length mismatch");for(let S=0;S<w.length;S++){const A=w[S];d.default.isLong(A)?T[S]=r(A,g.dataType):T[S]=A}}return y}static fromData(g,_,b){return new l(_,b,void 0,void 0,g)}static fromOrtTensor(g){if(!g)throw new Error("cannot construct Value from an empty tensor");const _=f.ProtoUtil.tensorDimsFromORTFormat(g),b=f.ProtoUtil.tensorDataTypeFromProto(g.dataType()),y=new l(_,b);if(b==="string")for(let w=0;w<g.stringDataLength();w++)y.data[w]=g.stringData(w);else if(g.rawDataArray()&&typeof g.rawDataLength()=="number"&&g.rawDataLength()>0){const w=y.data,T=new DataView(g.rawDataArray().buffer,g.rawDataArray().byteOffset,g.rawDataLength()),S=n(g.dataType()),A=g.rawDataLength()/S;if(g.rawDataLength()%S!=0)throw new Error("invalid buffer length");if(w.length!==A)throw new Error("buffer length mismatch");for(let P=0;P<A;P++){const x=o(T,g.dataType(),P*S);w[P]=x}}return y}}function n(p){switch(p){case a.onnx.TensorProto.DataType.UINT8:case a.onnx.TensorProto.DataType.INT8:case a.onnx.TensorProto.DataType.BOOL:return 1;case a.onnx.TensorProto.DataType.UINT16:case a.onnx.TensorProto.DataType.INT16:return 2;case a.onnx.TensorProto.DataType.FLOAT:case a.onnx.TensorProto.DataType.INT32:case a.onnx.TensorProto.DataType.UINT32:return 4;case a.onnx.TensorProto.DataType.INT64:case a.onnx.TensorProto.DataType.DOUBLE:case a.onnx.TensorProto.DataType.UINT64:return 8;default:throw new Error(`cannot calculate sizeof() on type ${a.onnx.TensorProto.DataType[p]}`)}}function e(p){switch(p){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(p,g){if(g===a.onnx.TensorProto.DataType.INT64||g===c.TensorDataType.INT64){if(p.greaterThanOrEqual(2147483648)||p.lessThan(-2147483648))throw new TypeError("int64 is not supported")}else{if(g!==a.onnx.TensorProto.DataType.UINT32&&g!==c.TensorDataType.UINT32&&g!==a.onnx.TensorProto.DataType.UINT64&&g!==c.TensorDataType.UINT64)throw new TypeError(`not a LONG type: ${a.onnx.TensorProto.DataType[g]}`);if(p.greaterThanOrEqual(4294967296)||p.lessThan(0))throw new TypeError("uint64 is not supported")}return p.toNumber()}function o(p,g,_){switch(g){case a.onnx.TensorProto.DataType.BOOL:case a.onnx.TensorProto.DataType.UINT8:return p.getUint8(_);case a.onnx.TensorProto.DataType.INT8:return p.getInt8(_);case a.onnx.TensorProto.DataType.UINT16:return p.getUint16(_,!0);case a.onnx.TensorProto.DataType.INT16:return p.getInt16(_,!0);case a.onnx.TensorProto.DataType.FLOAT:return p.getFloat32(_,!0);case a.onnx.TensorProto.DataType.INT32:return p.getInt32(_,!0);case a.onnx.TensorProto.DataType.UINT32:return p.getUint32(_,!0);case a.onnx.TensorProto.DataType.INT64:return r(d.default.fromBits(p.getUint32(_,!0),p.getUint32(_+4,!0),!1),g);case a.onnx.TensorProto.DataType.DOUBLE:return p.getFloat64(_,!0);case a.onnx.TensorProto.DataType.UINT64:return r(d.default.fromBits(p.getUint32(_,!0),p.getUint32(_+4,!0),!0),g);default:throw new Error(`cannot read from DataView for type ${a.onnx.TensorProto.DataType[g]}`)}}t.Tensor=l},2517:function(m,t,i){var s=this&&this.__importDefault||function(g){return g&&g.__esModule?g:{default:g}};Object.defineProperty(t,"__esModule",{value:!0}),t.decodeUtf8String=t.MAX_CLIP=t.MIN_CLIP=t.PoolConvUtil=t.ReduceUtil=t.SplitUtil=t.MathUtil=t.ShapeUtil=t.LongUtil=t.ProtoUtil=t.GemmUtil=t.arrayCopyHelper=t.BroadcastUtil=t.MatMulUtil=t.ArrayUtil=t.assert=t.checkInputsShape=void 0;const u=i(5686),d=s(i(3720)),a=i(1446),h=i(9162);t.checkInputsShape=function(g,..._){if(!g||g.length!==_.length)return!1;for(let b=0;b<g.length;b++)if(!g[b].dims||g[b].dims.length!==_[b])return!1;return!0},t.assert=function(g,_){if(!g)throw new Error(typeof _=="string"?_:_())},t.ArrayUtil=class{static arraysEqual(g,_){if(g.length!==_.length)return!1;for(let b=0;b<g.length;b++)if(g[b]!==_[b])return!1;return!0}};class f{static preprocessInputShapes(_,b){return[_.length===1?[1,_[0]]:_,b.length===1?[b[0],1]:b]}static postprocessOutputShape(_,b,y){b===1&&_.splice(_.length-2,1),y===1&&_.pop()}static calcMatMulShape(_,b){return _[1]!==b[0]?void 0:[_[0],b[1]]}}t.MatMulUtil=f;class c{static calcShape(_,b,y=!1){const w=_.length,T=b.length;if(w===0)return b;if(T===0)return _;const S=Math.max(_.length,b.length),A=new Array(S);if(y){if(w<2||T<2)return;const P=f.calcMatMulShape([_[w-2],_[w-1]],[b[T-2],b[T-1]]);if(P===void 0)return;[A[S-2],A[S-1]]=P}for(let P=y?3:1;P<=S;P++){const x=w-P<0?1:_[w-P],M=T-P<0?1:b[T-P];if(x!==M&&x>1&&M>1)return;A[S-P]=Math.max(x,M)}return A}static index(_,b){const y=new Array(b.length);return c.fillIndex(_,b,y),y}static fillIndex(_,b,y){const w=_.length-b.length;for(let T=0;T<b.length;T++)y[T]=_[w+T]%b[T]}static calc(_,b,y,w,T){const S=c.calcShape(_.dims,b.dims);if(S){if(w&&!e.areEqual(S,_.dims))return;const A=e.size(S),P=w?_:new h.Tensor(S,T||_.type);if(S.length===0)P.set([],y(_.get([]),b.get([])));else{const x=new Array(S.length),M=new Array(_.dims.length),N=new Array(b.dims.length);let z,$=0,C=0,G=!1,D=!1;_.dims.length===0&&($=_.get([]),G=!0),b.dims.length===0&&(C=b.get([]),D=!0);for(let R=0;R<A;R++){z=R;for(let Y=S.length-1;Y>=0;Y--)x[Y]=z%S[Y],z=Math.floor(z/S[Y]);G||(c.fillIndex(x,_.dims,M),$=_.get(M)),D||(c.fillIndex(x,b.dims,N),C=b.get(N)),P.set(x,y($,C))}}return P}}static isValidBroadcast(_,b){const y=_.length,w=b.length;if(y>w)return!1;for(let T=1;T<=y;T++)if(_[y-T]!==1&&_[y-T]!==b[w-T])return!1;return!0}static getBroadcastDims(_,b){const y=_.length,w=[];for(let T=0;T<y;T++){const S=y-1-T,A=_[S]||1;(b[b.length-1-T]||1)>1&&A===1&&w.unshift(S)}return w}}t.BroadcastUtil=c,t.arrayCopyHelper=function(g,_,b,y,w){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(y+w>_.length)throw new Error("source indices to be copied are outside bounds");if(b+w>g.length)throw new Error("target array is too small to hold result");for(let T=0;T<w;T++)g[b+T]=_[y+T]},t.GemmUtil=class{static getShapeOfGemmResult(g,_,b,y,w){if(g.length!==2||b.length!==2)throw new Error("shape need to be of size 2");let T,S,A;_?(T=g[1],S=g[0]):(T=g[0],S=g[1]);let P=-1;if(y?(A=b[0],P=1):(A=b[1],P=0),b[P]!==S)throw new Error("dimension mismatch");if(T<=0||A<=0||S<=0)throw new Error("invalid shape specified");if(w&&!c.isValidBroadcast(w,[T,A]))throw new Error("gemm: invalid bias shape for broadcast");return[T,A,S]}};class l{static tensorDataTypeFromProto(_){switch(_){case a.onnx.TensorProto.DataType.INT8:return"int8";case a.onnx.TensorProto.DataType.UINT8:return"uint8";case a.onnx.TensorProto.DataType.BOOL:return"bool";case a.onnx.TensorProto.DataType.INT16:return"int16";case a.onnx.TensorProto.DataType.UINT16:return"uint16";case a.onnx.TensorProto.DataType.INT32:return"int32";case a.onnx.TensorProto.DataType.UINT32:return"uint32";case a.onnx.TensorProto.DataType.FLOAT:return"float32";case a.onnx.TensorProto.DataType.DOUBLE:return"float64";case a.onnx.TensorProto.DataType.STRING:return"string";case a.onnx.TensorProto.DataType.INT64:return"int32";case a.onnx.TensorProto.DataType.UINT64:return"uint32";default:throw new Error(`unsupported data type: ${a.onnx.TensorProto.DataType[_]}`)}}static tensorDataTypeStringToEnum(_){switch(_){case"int8":return a.onnx.TensorProto.DataType.INT8;case"uint8":return a.onnx.TensorProto.DataType.UINT8;case"bool":return a.onnx.TensorProto.DataType.BOOL;case"int16":return a.onnx.TensorProto.DataType.INT16;case"uint16":return a.onnx.TensorProto.DataType.UINT16;case"int32":return a.onnx.TensorProto.DataType.INT32;case"uint32":return a.onnx.TensorProto.DataType.UINT32;case"float32":return a.onnx.TensorProto.DataType.FLOAT;case"float64":return a.onnx.TensorProto.DataType.DOUBLE;case"string":return a.onnx.TensorProto.DataType.STRING;case"int64":return a.onnx.TensorProto.DataType.INT64;case"uint64":return a.onnx.TensorProto.DataType.UINT64;default:throw new Error(`unsupported data type: ${_}`)}}static tensorDimsFromProto(_){return _.map(b=>d.default.isLong(b)?b.toNumber():b)}static tensorValueTypeFromProto(_){return{tensorType:l.tensorDataTypeFromProto(_.elemType),shape:{dims:l.tensorDimsFromProto(_.shape.dim.map(b=>b.dimValue))}}}static tensorDimsFromORTFormat(_){const b=[];for(let y=0;y<_.dimsLength();y++)b.push(n.longToNumber(_.dims(y)));return b}static tensorAttributesFromORTFormat(_){const b=[];for(let y=0;y<_.attributesLength();y++)b.push(_.attributes(y));return b}}t.ProtoUtil=l;class n{static longToNumber(_,b){return d.default.isLong(_)?_.toNumber():_ instanceof u.flatbuffers.Long?d.default.fromValue({low:_.low,high:_.high,unsigned:b!=null&&b}).toNumber():_}static isLong(_){return d.default.isLong(_)||_ instanceof u.flatbuffers.Long}}t.LongUtil=n;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 ${_.length} dimensions.`);return e.getSizeFromDimensionRange(_,0,b)}static getSizeFromDimensionRange(_,b,y){let w=1;for(let T=b;T<y;T++){if(_[T]<=0)throw new Error("cannot get valid size from specified dimension range. Most likely the range contains 0 or negative values in them.");w*=_[T]}return w}static computeStrides(_){const b=_.length;if(b===0)return[];if(b===1)return[1];const y=new Array(b);y[b-1]=1,y[b-2]=_[b-1];for(let w=b-3;w>=0;--w)y[w]=y[w+1]*_[w+1];return y}static transpose(_){return _.slice().reverse()}static indicesToOffset(_,b,y){y===void 0&&(y=_.length);let w=0;for(let T=0;T<y;++T)w+=b[T]*_[T];return w}static offsetToIndices(_,b){const y=b.length;if(y===0)return[];if(y===1)return[_*b[0]];const w=new Array(b.length);for(let T=0;T<w.length-1;++T)w[T]=Math.floor(_/b[T]),_-=w[T]*b[T];return w[w.length-1]=_,w}static normalizeAxis(_,b){if(_<-b&&_>=b)throw new Error("unsupported axis for this operation.");return _<0?_+b:_}static normalizeAxes(_,b){return _.map(y=>this.normalizeAxis(y,b))}static incrementIndex(_,b,y){if(b.length===0||_.length===0)throw new Error("Index incrementing unsupported for scalar Tensor");if(y===void 0)y=b.length;else if(y<=0||y>b.length)throw new Error("Incorrect axis to increment on");for(let w=y-1;w>=0&&(_[w]++,!(_[w]<b[w]));--w)_[w]=0}static calculateReshapedDims(_,b){if(b.length===0){if(_.length===0||e.size(_)===1)return[];throw new Error("cannot reshape to a scalar Tensor")}const y=b.length,w=new Array(y);let T=-1,S=1;for(let P=0;P<y;P++){if(b[P]<-1)throw new Error("a dimension in shape hints cannot be less than -1");if(b[P]===-1){if(T!==-1)throw new Error("at most one dimension in shape hints can be -1");T=P}else{if(b[P]===0){if(P>=_.length)throw new Error("the dimension with value zero exceeds the dimension size of the input tensor");w[P]=_[P]}else w[P]=b[P];S*=w[P]}}const A=e.size(_);if(T!==-1){if(A%S!=0)throw new Error(`the input tensor cannot be reshaped to the requested shape. Input shape: [${_}] Output shape: [${b}]`);w[T]=A/S}else if(S!==A)throw new Error("reshapedDims and originalDims don't have matching sizes");return w}static sortBasedOnPerm(_,b){return b?b.map(y=>_[y]):_.slice().reverse()}static padShape(_,b){const y=_.length;return _.map((w,T)=>w+b[T]+b[T+y])}static areEqual(_,b){return _.length===b.length&&_.every((y,w)=>y===b[w])}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((T,S)=>T*S,1),w=_.slice(b).reduce((T,S)=>T*S,1);return[y/w,w]}static squeezeShape(_,b){const y=new Array;b=e.normalizeAxes(b,_.length);for(let w=0;w<_.length;w++){const T=b.indexOf(w)>=0;if(T&&_[w]!==1)throw new Error("squeeze an axis of size different than 1");(b.length===0&&_[w]>1||b.length>0&&!T)&&y.push(_[w])}return y}static unsqueezeShape(_,b){const y=new Array(_.length+b.length);y.fill(0);for(let T=0;T<b.length;T++){const S=e.normalizeAxis(b[T],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 w=0;for(let T=0;T<y.length;T++)y[T]===0&&(y[T]=_[w++]);if(w!==_.length)throw new Error("the unsqueezed dimension could not be established");return y}}t.ShapeUtil=e,t.MathUtil=class{static sqr(g,_,b,y,w){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(y+w>_.length)throw new Error("source indices to be copied are outside bounds");if(b+w>g.length)throw new Error("target array is too small to hold result");for(let T=0;T<w;T++)g[b+T]+=Math.pow(_[y+T],2)}static axpy(g,_,b,y,w,T){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(y+w>_.length)throw new Error("source indices to be copied are outside bounds");if(b+w>g.length)throw new Error("target array is too small to hold result");for(let S=0;S<w;S++)g[b+S]+=T*_[y+S]}static powx(g,_,b,y,w,T){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(y+w>_.length)throw new Error("source indices to be copied are outside bounds");if(b+w>g.length)throw new Error("target array is too small to hold result");for(let S=0;S<w;S++)g[b+S]=Math.pow(_[y+S],T)}static mul(g,_,b,y,w){if(y<0||y>=_.length)throw new Error("sourceIndex out of bounds");if(b<0||b>=g.length)throw new Error("targetIndex out of bounds");if(y+w>_.length)throw new Error("source indices to be copied are outside bounds");if(b+w>g.length)throw new Error("target array is too small to hold result");for(let T=0;T<w;T++)g[b+T]=_[y+T]*g[b+T]}};class r{static splitShape(_,b,y,w){if(y.length===0){if(!w)throw new Error("need to know number of outputs when the 'split' attribute is not specified");r.determineSplit(_[b],w,y)}const T=[],S=[0];for(let A=0;A<y.length;++A){A!==0&&S.push(S[A-1]+y[A-1]);const P=_.slice();P[b]=y[A],T.push(P)}return[T,S]}static determineSplit(_,b,y){if(_%b!=0)throw new Error("cannot split tensor to equal sized parts");for(let w=0;w<b;++w)y.push(_/b)}}t.SplitUtil=r;class o{static calcReduce(_,b,y,w,T){const S=_.dims.slice(0);b.length===0&&S.forEach(($,C)=>b.push(C));const A=o.calcReduceShape(S,b,!0),P=e.size(A),x=new h.Tensor(A,_.type),M=e.computeStrides(A),N=e.computeStrides(S),z=new Array(S.length);for(let $=0;$<P;$++){const C=e.offsetToIndices($,M);c.fillIndex(C,S,z),x.set(C,o.calcReduceByAxis(_.numberData,b,S,0,e.indicesToOffset(z,N),w,T))}return y?x:new h.Tensor(o.calcReduceShape(S,b,y),x.type,void 0,void 0,x.data,x.dataId)}static calcReduceByAxis(_,b,y,w,T,S,A){let P=0;if(w>=b.length)return S(_[T]);const x=b[w],M=x>=y.length?1:e.size(y.slice(x+1));for(let N=0;N<y[x];N++)P=N===0?o.calcReduceByAxis(_,b,y,w+1,T,S,A):A(P,o.calcReduceByAxis(_,b,y,w+1,T,S,A)),T+=M;return P}static calcReduceShape(_,b,y){const w=_.slice();for(let T=0;T<b.length;T++)w[b[T]]=y?1:0;return w.filter(T=>T!==0)}}t.ReduceUtil=o;class p{static adjustPoolAttributes(_,b,y,w,T,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 A=0;A<b.length-2;A++)A>=y.length?y.push(b[A+2]):y[A]=b[A+2];for(let A=0;A<y.length;A++)if(A<w.length){if(w[A]<0)throw new Error("strides should be greater than or equal to 1")}else w.push(1);for(let A=0;A<y.length;A++)if(A<T.length){if(T[A]<0)throw new Error("dilations should be greater than or equal to 1")}else T.push(1);for(let A=0;A<2*y.length;A++)if(A<S.length){if(S[A]<0)throw new Error("pad should be greater than or equal to 1")}else S.push(0);for(let A=0;A<y.length;A++){if(y[A]<=0)throw new Error("kernel shapes need to be greater than 0");if(S[A]>=y[A]||S[A+y.length]>=y[A])throw new Error("pads should be smaller than kernel")}}static adjustPadsBasedOnAutoPad(_,b,y,w,T,S){if(S){if(T.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(w.length!==_.length-2)throw new Error("length of kernel shapes should be the length of data dimensions");for(let A=0;A<_.length-2;A++)p.adjustPadAndReturnShape(_[A+2],b[A],y[A],w[A],T,A,A+_.length-2,S)}}static computePoolOutputShape(_,b,y,w,T,S,A){if(b.length<=0)throw new Error("input shape must be of size greater than 0");const P=[b[0],b[1]];return p.computeShapeHelper(_,b,P,y,w,T,S,A),P}static computeConvOutputShape(_,b,y,w,T,S,A){if(_.length<=0||b.length<=0)throw new Error("invalid input tensor dims or invalid filter tensor dims");const P=[_[0],b[0]];return 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Error("Browser cache is not available in this environment.");try{u=await caches.open("transformers-cache")}catch(_){console.warn("An error occurred while opening the browser cache:",_)}}if(!u&&env$1.useFSCache&&(u=new FileCache(s.cache_dir??env$1.cacheDir)),!u&&env$1.useCustomCache)throw Error("`env.useCustomCache=true`, but `env.customCache` is not defined.");const d=s.revision??"main";let a=pathJoin(m,t),h=pathJoin(env$1.localModelPath,a),f=pathJoin(env$1.remoteHost,env$1.remotePathTemplate.replaceAll("{model}",m).replaceAll("{revision}",d),t),c=d==="main"?a:pathJoin(m,d,t),l,n=u instanceof FileCache?c:f,e=!1,r;u&&(r=await tryCache(u,h,n));const o=r!==void 0;if(r===void 0){if(isValidHttpUrl(a)){if(s.local_files_only)throw new Error(`\`local_files_only=true\`, but attempted to load a remote file from: ${a}.`)}else try{r=await getFile(h),l=h}catch(b){console.warn(`Unable to load from local path "${h}": "${b}"`)}if(r===void 0||r.status===404){if(s.local_files_only||!env$1.allowRemoteModels){if(i)throw Error(`\`local_files_only=true\` or \`env.allowRemoteModels=false\` and file was not found locally at "${h}".`);return null}if(r=await getFile(f),r.status!==200)return handleError(r.status,f,i);l=n}e=u&&typeof Response<"u"&&r instanceof Response&&r.status===200}dispatchCallback(s.progress_callback,{status:"download",name:m,file:t});const p={status:"progress",name:m,file:t};let g;return s.progress_callback?o&&typeof navigator<"u"&&/firefox/i.test(navigator.userAgent)?(g=new Uint8Array(await r.arrayBuffer()),dispatchCallback(s.progress_callback,{...p,progress:100,loaded:g.length,total:g.length})):g=await readResponse(r,_=>{dispatchCallback(s.progress_callback,{...p,..._})}):g=new Uint8Array(await r.arrayBuffer()),e&&l&&await u.match(l)===void 0&&await u.put(l,new Response(g,{headers:r.headers})).catch(_=>{console.warn(`Unable to add response to browser cache: ${_}.`)}),dispatchCallback(s.progress_callback,{status:"done",name:m,file:t}),g}async function getModelJSON(m,t,i=!0,s={}){let u=await getModelFile(m,t,i,s);if(u===null)return{};let a=new TextDecoder("utf-8").decode(u);return JSON.parse(a)}async function readResponse(m,t){const i=m.headers.get("Content-Length");i===null&&console.warn("Unable to determine content-length from response headers. Will expand buffer when needed.");let s=parseInt(i??"0"),u=new Uint8Array(s),d=0;const a=m.body.getReader();async function h(){const{done:f,value:c}=await a.read();if(f)return;let l=d+c.length;if(l>s){s=l;let e=new Uint8Array(s);e.set(u),u=e}u.set(c,d),d=l;const n=d/s*100;return t({progress:n,loaded:d,total:s}),h()}return await h(),u}function pathJoin(...m){return m=m.map((t,i)=>(i&&(t=t.replace(new RegExp("^/"),"")),i!==m.length-1&&(t=t.replace(new RegExp("/$"),"")),t)),m.join("/")}function interpolate_data(m,[t,i,s],[u,d],a="bilinear",h=!1){const f=d/s,c=u/i,l=new m.constructor(u*d*t),n=i*s,e=u*d;for(let r=0;r<u;++r)for(let o=0;o<d;++o){const p=r*d+o,g=(o+.5)/f-.5,_=(r+.5)/c-.5;let b=Math.floor(g),y=Math.floor(_);const w=Math.min(b+1,s-1),T=Math.min(y+1,i-1);b=Math.max(b,0),y=Math.max(y,0);const S=g-b,A=_-y,P=(1-S)*(1-A),x=S*(1-A),M=(1-S)*A,N=S*A,z=y*s,$=T*s,C=z+b,G=z+w,D=$+b,R=$+w;for(let Y=0;Y<t;++Y){const V=Y*n;l[Y*e+p]=P*m[V+C]+x*m[V+G]+M*m[V+D]+N*m[V+R]}}return l}function transpose_data(m,t,i){const s=new Array(i.length),u=new Array(i.length);for(let h=i.length-1,f=1;h>=0;--h)u[h]=f,s[h]=t[i[h]],f*=s[h];const d=i.map((h,f)=>u[i.indexOf(f)]),a=new m.constructor(m.length);for(let h=0;h<m.length;++h){let f=0;for(let c=t.length-1,l=h;c>=0;--c)f+=l%t[c]*d[c],l=Math.floor(l/t[c]);a[f]=m[h]}return[a,s]}function softmax(m){const t=max(m)[0],i=m.map(d=>Math.exp(d-t)),s=i.reduce((d,a)=>d+a,0);return i.map(d=>d/s)}function log_softmax(m){return softmax(m).map(s=>Math.log(s))}function getTopItems(m,t=0){return m=Array.from(m).map((i,s)=>[s,i]).sort((i,s)=>s[1]-i[1]),t>0&&(m=m.slice(0,t)),m}function min(m){if(m.length===0)throw Error("Array must not be empty");let t=m[0],i=0;for(let s=1;s<m.length;++s)m[s]<t&&(t=m[s],i=s);return[t,i]}function max(m){if(m.length===0)throw Error("Array must not be empty");let t=m[0],i=0;for(let s=1;s<m.length;++s)m[s]>t&&(t=m[s],i=s);return[t,i]}function isPowerOfTwo(m){return m>0&&(m&m-1)===0}class P2FFT{constructor(t){if(this.size=t|0,this.size<=1||!isPowerOfTwo(this.size))throw new Error("FFT size must be a power of two larger than 1");this._csize=t<<1,this.table=new Float64Array(this.size*2);for(let s=0;s<this.table.length;s+=2){const u=Math.PI*s/this.size;this.table[s]=Math.cos(u),this.table[s+1]=-Math.sin(u)}let i=0;for(let s=1;this.size>s;s<<=1)++i;this._width=i%2===0?i-1:i,this._bitrev=new Int32Array(1<<this._width);for(let s=0;s<this._bitrev.length;++s){this._bitrev[s]=0;for(let u=0;u<this._width;u+=2){const d=this._width-u-2;this._bitrev[s]|=(s>>>u&3)<<d}}}createComplexArray(){return new Float64Array(this._csize)}fromComplexArray(t,i){const s=i||new Array(t.length>>>1);for(let u=0;u<t.length;u+=2)s[u>>>1]=t[u];return s}toComplexArray(t,i){const s=i||this.createComplexArray();for(let u=0;u<s.length;u+=2)s[u]=t[u>>>1],s[u+1]=0;return s}completeSpectrum(t){const i=this._csize,s=i>>>1;for(let u=2;u<s;u+=2)t[i-u]=t[u],t[i-u+1]=-t[u+1]}transform(t,i){if(t===i)throw new Error("Input and output buffers must be different");this._transform4(t,i,1)}realTransform(t,i){if(t===i)throw new Error("Input and output buffers must be different");this._realTransform4(t,i,1)}inverseTransform(t,i){if(t===i)throw new Error("Input and output buffers must be different");this._transform4(t,i,-1);for(let s=0;s<t.length;++s)t[s]/=this.size}_transform4(t,i,s){const u=this._csize;let a=1<<this._width,h=u/a<<1,f,c;const l=this._bitrev;if(h===4)for(f=0,c=0;f<u;f+=h,++c){const n=l[c];this._singleTransform2(i,t,f,n,a)}else for(f=0,c=0;f<u;f+=h,++c){const n=l[c];this._singleTransform4(i,t,f,n,a,s)}for(a>>=2;a>=2;a>>=2){h=u/a<<1;const n=h>>>2;for(f=0;f<u;f+=h){const e=f+n-1;for(let r=f,o=0;r<e;r+=2,o+=a){const p=r,g=p+n,_=g+n,b=_+n,y=t[p],w=t[p+1],T=t[g],S=t[g+1],A=t[_],P=t[_+1],x=t[b],M=t[b+1],N=this.table[o],z=s*this.table[o+1],$=T*N-S*z,C=T*z+S*N,G=this.table[2*o],D=s*this.table[2*o+1],R=A*G-P*D,Y=A*D+P*G,V=this.table[3*o],J=s*this.table[3*o+1],Z=x*V-M*J,le=x*J+M*V,Ae=y+R,xe=w+Y,se=y-R,we=w-Y,be=$+Z,ke=C+le,Le=s*($-Z),ve=s*(C-le);t[p]=Ae+be,t[p+1]=xe+ke,t[g]=se+ve,t[g+1]=we-Le,t[_]=Ae-be,t[_+1]=xe-ke,t[b]=se-ve,t[b+1]=we+Le}}}}_singleTransform2(t,i,s,u,d){const a=t[u],h=t[u+1],f=t[u+d],c=t[u+d+1];i[s]=a+f,i[s+1]=h+c,i[s+2]=a-f,i[s+3]=h-c}_singleTransform4(t,i,s,u,d,a){const h=d*2,f=d*3,c=t[u],l=t[u+1],n=t[u+d],e=t[u+d+1],r=t[u+h],o=t[u+h+1],p=t[u+f],g=t[u+f+1],_=c+r,b=l+o,y=c-r,w=l-o,T=n+p,S=e+g,A=a*(n-p),P=a*(e-g);i[s]=_+T,i[s+1]=b+S,i[s+2]=y+P,i[s+3]=w-A,i[s+4]=_-T,i[s+5]=b-S,i[s+6]=y-P,i[s+7]=w+A}_realTransform4(t,i,s){const u=this._csize;let a=1<<this._width,h=u/a<<1,f,c;const l=this._bitrev;if(h===4)for(f=0,c=0;f<u;f+=h,++c){const n=l[c];this._singleRealTransform2(i,t,f,n>>>1,a>>>1)}else for(f=0,c=0;f<u;f+=h,++c){const n=l[c];this._singleRealTransform4(i,t,f,n>>>1,a>>>1,s)}for(a>>=2;a>=2;a>>=2){h=u/a<<1;const n=h>>>2;for(f=0;f<u;f+=h){const e=f+n-1;for(let r=f,o=0;r<e;r+=2,o+=a){const p=r,g=p+n,_=g+n,b=_+n,y=t[p],w=t[p+1],T=t[g],S=t[g+1],A=t[_],P=t[_+1],x=t[b],M=t[b+1],N=this.table[o],z=s*this.table[o+1],$=T*N-S*z,C=T*z+S*N,G=this.table[2*o],D=s*this.table[2*o+1],R=A*G-P*D,Y=A*D+P*G,V=this.table[3*o],J=s*this.table[3*o+1],Z=x*V-M*J,le=x*J+M*V,Ae=y+R,xe=w+Y,se=y-R,we=w-Y,be=$+Z,ke=C+le,Le=s*($-Z),ve=s*(C-le);t[p]=Ae+be,t[p+1]=xe+ke,t[g]=se+ve,t[g+1]=we-Le,t[_]=Ae-be,t[_+1]=xe-ke,t[b]=se-ve,t[b+1]=we+Le}}}}_singleRealTransform2(t,i,s,u,d){const a=t[u],h=t[u+d];i[s]=a+h,i[s+1]=0,i[s+2]=a-h,i[s+3]=0}_singleRealTransform4(t,i,s,u,d,a){const h=d*2,f=d*3,c=t[u],l=t[u+d],n=t[u+h],e=t[u+f],r=c+n,o=c-n,p=l+e,g=a*(l-e);i[s]=r+p,i[s+1]=0,i[s+2]=o,i[s+3]=-g,i[s+4]=r-p,i[s+5]=0,i[s+6]=o,i[s+7]=g}}class NP2FFT{constructor(t){const i=2*(t-1),s=2*(2*t-1),u=2**Math.ceil(Math.log2(s));this.bufferSize=u,this._a=i;const d=new Float64Array(s),a=new Float64Array(u);this._chirpBuffer=new Float64Array(u),this._buffer1=new Float64Array(u),this._buffer2=new Float64Array(u),this._outBuffer1=new Float64Array(u),this._outBuffer2=new Float64Array(u);const h=-2*Math.PI/t,f=Math.cos(h),c=Math.sin(h);for(let l=0;l<s>>1;++l){const n=(l+1-t)**2/2,e=Math.sqrt(f**2+c**2)**n,r=n*Math.atan2(c,f),o=2*l;d[o]=e*Math.cos(r),d[o+1]=e*Math.sin(r),a[o]=d[o],a[o+1]=-d[o+1]}this._slicedChirpBuffer=d.subarray(i,s),this._f=new P2FFT(u>>1),this._f.transform(this._chirpBuffer,a)}_transform(t,i,s){const u=this._buffer1,d=this._buffer2,a=this._outBuffer1,h=this._outBuffer2,f=this._chirpBuffer,c=this._slicedChirpBuffer,l=this._a;if(s)for(let n=0;n<c.length;n+=2){const e=n+1,r=n>>1,o=i[r];u[n]=o*c[n],u[e]=o*c[e]}else for(let n=0;n<c.length;n+=2){const e=n+1;u[n]=i[n]*c[n]-i[e]*c[e],u[e]=i[n]*c[e]+i[e]*c[n]}this._f.transform(a,u);for(let n=0;n<f.length;n+=2){const e=n+1;d[n]=a[n]*f[n]-a[e]*f[e],d[e]=a[n]*f[e]+a[e]*f[n]}this._f.inverseTransform(h,d);for(let n=0;n<h.length;n+=2){const e=h[n+l],r=h[n+l+1],o=c[n],p=c[n+1];t[n]=e*o-r*p,t[n+1]=e*p+r*o}}transform(t,i){this._transform(t,i,!1)}realTransform(t,i){this._transform(t,i,!0)}}class FFT{constructor(t){this.fft_length=t,this.isPowerOfTwo=isPowerOfTwo(t),this.isPowerOfTwo?(this.fft=new P2FFT(t),this.outputBufferSize=2*t):(this.fft=new NP2FFT(t),this.outputBufferSize=this.fft.bufferSize)}realTransform(t,i){this.fft.realTransform(t,i)}transform(t,i){this.fft.transform(t,i)}}function medianFilter(m,t){if(t%2===0||t<=0)throw new Error("Window size must be a positive odd number");const i=new m.constructor(m.length),s=new m.constructor(t),u=Math.floor(t/2);for(let d=0;d<m.length;++d){let a=0;for(let h=-u;h<=u;++h){let f=d+h;f<0?f=Math.abs(f):f>=m.length&&(f=2*(m.length-1)-f),s[a++]=m[f]}s.sort(),i[d]=s[u]}return i}function round(m,t){const i=Math.pow(10,t);return Math.round(m*i)/i}const DataTypeMap=new Map([["bool",Uint8Array],["float32",Float32Array],["float64",Float64Array],["string",Array],["int8",Int8Array],["uint8",Uint8Array],["int16",Int16Array],["uint16",Uint16Array],["int32",Int32Array],["uint32",Uint32Array],["int64",BigInt64Array]]),ONNXTensor$1=ONNX.Tensor;class Tensor extends ONNXTensor$1{constructor(...t){return t[0]instanceof ONNX.Tensor?super(t[0].type,t[0].data,t[0].dims):super(...t),new Proxy(this,{get:(i,s)=>{if(typeof s=="string"){let u=Number(s);if(Number.isInteger(u))return i._getitem(u)}return i[s]},set:(i,s,u)=>i[s]=u})}*[Symbol.iterator](){const[t,...i]=this.dims;if(i.length>0){const s=i.reduce((u,d)=>u*d);for(let u=0;u<t;++u)yield this._subarray(u,s,i)}else yield*this.data}_getitem(t){const[i,...s]=this.dims;if(t=safeIndex(t,i),s.length>0){const u=s.reduce((d,a)=>d*a);return this._subarray(t,u,s)}else return new Tensor(this.type,[this.data[t]],s)}indexOf(t){for(let i=0;i<this.data.length;++i)if(this.data[i]==t)return i;return-1}_subarray(t,i,s){let u=this.data.subarray(t*i,(t+1)*i);return new Tensor(this.type,u,s)}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 t=0;t<this.data.length;++t)this.data[t]=1/(1+Math.exp(-this.data[t]));return this}mul(t){return this.clone().mul_(t)}mul_(t){for(let i=0;i<this.data.length;++i)this.data[i]*=t;return this}add(t){return this.clone().add_(t)}add_(t){for(let i=0;i<this.data.length;++i)this.data[i]+=t;return this}clone(){return new Tensor(this.type,this.data.slice(),this.dims.slice())}slice(...t){let i=[],s=[];for(let f=0;f<this.dims.length;++f){let c=t[f];if(c==null)s.push([0,this.dims[f]]),i.push(this.dims[f]);else if(typeof c=="number")c=safeIndex(c,this.dims[f],f),s.push([c,c+1]);else if(Array.isArray(c)&&c.length===2){if(c[0]>c[1])throw new Error(`Invalid slice: ${c}`);let l=[Math.max(c[0],0),Math.min(c[1],this.dims[f])];s.push(l),i.push(l[1]-l[0])}else throw new Error(`Invalid slice: ${c}`)}let u=s.map(([f,c])=>c-f),d=u.reduce((f,c)=>f*c),a=new this.data.constructor(d);const h=this.stride();for(let f=0;f<d;++f){let c=0;for(let l=u.length-1,n=f;l>=0;--l){const e=u[l];c+=(n%e+s[l][0])*h[l],n=Math.floor(n/e)}a[f]=this.data[c]}return new Tensor(this.type,a,i)}transpose(...t){return transpose(this,t)}sum(t=null,i=!1){return this.norm(1,t,i)}norm(t="fro",i=null,s=!1){if(t==="fro")t=2;else if(typeof t=="string")throw Error(`Unsupported norm: ${t}`);if(i===null){let a=this.data.reduce((h,f)=>h+f**t,0)**(1/t);return new Tensor(this.type,[a],[])}i=safeIndex(i,this.dims.length);const u=this.dims.slice();u[i]=1;const d=new this.data.constructor(this.data.length/this.dims[i]);for(let a=0;a<this.data.length;++a){let h=0;for(let f=this.dims.length-1,c=a,l=1;f>=0;--f){const n=this.dims[f];if(f!==i){const e=c%n;h+=e*l,l*=u[f]}c=Math.floor(c/n)}d[h]+=this.data[a]**t}if(t!==1)for(let a=0;a<d.length;++a)d[a]=d[a]**(1/t);return s||u.splice(i,1),new Tensor(this.type,d,u)}normalize_(t=2,i=1){i=safeIndex(i,this.dims.length);const s=this.norm(t,i,!0);for(let u=0;u<this.data.length;++u){let d=0;for(let a=this.dims.length-1,h=u,f=1;a>=0;--a){const c=this.dims[a];if(a!==i){const l=h%c;d+=l*f,f*=this.dims[a]}h=Math.floor(h/c)}this.data[u]/=s.data[d]}return this}normalize(t=2,i=1){return this.clone().normalize_(t,i)}stride(){return dimsToStride(this.dims)}squeeze(t=null){return new Tensor(this.type,this.data,calc_squeeze_dims(this.dims,t))}squeeze_(t=null){return this.dims=calc_squeeze_dims(this.dims,t),this}unsqueeze(t=null){return new Tensor(this.type,this.data,calc_unsqueeze_dims(this.dims,t))}unsqueeze_(t=null){return this.dims=calc_unsqueeze_dims(this.dims,t),this}flatten_(t=0,i=-1){i=(i+this.dims.length)%this.dims.length;let s=this.dims.slice(0,t),u=this.dims.slice(t,i+1),d=this.dims.slice(i+1);return this.dims=[...s,u.reduce((a,h)=>a*h,1),...d],this}flatten(t=0,i=-1){return this.clone().flatten_(t,i)}view(...t){let i=-1;for(let s=0;s<t.length;++s)if(t[s]===-1){if(i!==-1)throw new Error("Only one dimension can be inferred");i=s}if(i!==-1){const s=t.reduce((u,d,a)=>a!==i?u*d:u,1);t[i]=this.data.length/s}return new Tensor(this.type,this.data,t)}neg_(){for(let t=0;t<this.data.length;++t)this.data[t]=-this.data[t];return this}neg(){return this.clone().neg_()}clamp_(t,i){for(let s=0;s<this.data.length;++s)this.data[s]=Math.min(Math.max(this.data[s],t),i);return this}clamp(t,i){return this.clone().clamp_(t,i)}round_(){for(let t=0;t<this.data.length;++t)this.data[t]=Math.round(this.data[t]);return this}round(){return this.clone().round_()}to(t){if(this.type===t)return this;const i=DataTypeMap.get(t);if(!i)throw new Error(`Unsupported type: ${t}`);return new Tensor(t,i.from(this.data),this.dims)}}function reshape(m,t){const i=m.length,s=t.reduce((d,a)=>d*a);if(i!==s)throw Error(`cannot reshape array of size ${i} into shape (${t})`);let u=m;for(let d=t.length-1;d>=0;d--)u=u.reduce((a,h)=>{let f=a[a.length-1];return f.length<t[d]?f.push(h):a.push([h]),a},[[]]);return u[0]}function transpose(m,t){const[i,s]=transpose_data(m.data,m.dims,t);return new Tensor(m.type,i,s)}function interpolate(m,[t,i],s="bilinear",u=!1){const d=m.dims.at(-3)??1,a=m.dims.at(-2),h=m.dims.at(-1);let f=interpolate_data(m.data,[d,a,h],[t,i],s,u);return new Tensor(m.type,f,[d,t,i])}function mean_pooling(m,t){let i=[m.dims[0],m.dims[2]],s=new m.data.constructor(i[0]*i[1]),[u,d,a]=m.dims,h=0;for(let f=0;f<u;++f){let c=f*a*d;for(let l=0;l<a;++l){let n=0,e=0,r=f*d,o=c+l;for(let g=0;g<d;++g){let _=Number(t.data[r+g]);e+=_,n+=m.data[o+g*a]*_}let p=n/e;s[h++]=p}}return new Tensor(m.type,s,i)}function calc_squeeze_dims(m,t){return m=m.slice(),t===null?m=m.filter(i=>i!==1):typeof t=="number"?m[t]===1&&m.splice(t,1):Array.isArray(t)&&(m=m.filter((i,s)=>i!==1||!t.includes(s))),m}function calc_unsqueeze_dims(m,t){return t=safeIndex(t,m.length+1),m=m.slice(),m.splice(t,0,1),m}function safeIndex(m,t,i=null){if(m<-t||m>=t)throw new Error(`IndexError: index ${m} is out of bounds for dimension${i===null?"":" "+i} with size ${t}`);return m<0&&(m=(m%t+t)%t),m}function cat(m,t=0){t=safeIndex(t,m[0].dims.length);const i=m[0].dims.slice();i[t]=m.reduce((a,h)=>a+h.dims[t],0);const s=i.reduce((a,h)=>a*h,1),u=new m[0].data.constructor(s),d=m[0].type;if(t===0){let a=0;for(let h of m)u.set(h.data,a),a+=h.data.length}else{let a=0;for(let h=0;h<m.length;++h){let f=m[h];for(let c=0;c<f.data.length;++c){let l=0;for(let n=f.dims.length-1,e=c,r=1;n>=0;--n){const o=f.dims[n];let p=e%o;n===t&&(p+=a),l+=p*r,r*=i[n],e=Math.floor(e/o)}u[l]=f.data[c]}a+=f.dims[t]}}return new Tensor(d,u,i)}function stack(m,t=0){return cat(m.map(i=>i.unsqueeze(t)),t)}function std_mean(m,t=null,i=1,s=!1){if(t===null){const c=m.data.reduce((r,o)=>r+o,0)/m.data.length,l=Math.sqrt(m.data.reduce((r,o)=>r+(o-c)**2,0)/(m.data.length-i)),n=new Tensor(m.type,[c],[]);return[new Tensor(m.type,[l],[]),n]}t=safeIndex(t,m.dims.length);const u=mean(m,t,s),d=m.dims.slice();d[t]=1;const a=new m.data.constructor(m.data.length/m.dims[t]);for(let f=0;f<m.data.length;++f){let c=0;for(let l=m.dims.length-1,n=f,e=1;l>=0;--l){const r=m.dims[l];if(l!==t){const o=n%r;c+=o*e,e*=d[l]}n=Math.floor(n/r)}a[c]+=(m.data[f]-u.data[c])**2}for(let f=0;f<a.length;++f)a[f]=Math.sqrt(a[f]/(m.dims[t]-i));return s||d.splice(t,1),[new Tensor(m.type,a,d),u]}function mean(m,t=null,i=!1){if(t===null){let d=m.data.reduce((a,h)=>a+h,0);return new Tensor(m.type,[d/m.data.length],[])}t=safeIndex(t,m.dims.length);const s=m.dims.slice();s[t]=1;const u=new m.data.constructor(m.data.length/m.dims[t]);for(let d=0;d<m.data.length;++d){let a=0;for(let h=m.dims.length-1,f=d,c=1;h>=0;--h){const l=m.dims[h];if(h!==t){const n=f%l;a+=n*c,c*=s[h]}f=Math.floor(f/l)}u[a]+=m.data[d]}if(m.dims[t]!==1)for(let d=0;d<u.length;++d)u[d]=u[d]/m.dims[t];return i||s.splice(t,1),new Tensor(m.type,u,s)}function dynamicTimeWarping(m){const[t,i]=m.dims,s=[t+1,i+1],u=new Tensor("float32",new Float32Array(s[0]*s[1]).fill(1/0),s),d=new Tensor("float32",new Float32Array(s[0]*s[1]).fill(-1),s);u[0].data[0]=0;for(let l=1;l<i+1;++l)for(let n=1;n<t+1;++n){const e=u[n-1][l-1].item(),r=u[n-1][l].item(),o=u[n][l-1].item();let p,g;e<r&&e<o?(p=e,g=0):r<e&&r<o?(p=r,g=1):(p=o,g=2),u[n].data[l]=m[n-1][l-1].item()+p,d[n].data[l]=g}let a=t,h=i;d.data.fill(2,0,s[1]);for(let l=0;l<s[0];++l)d[l].data[0]=1;let f=[],c=[];for(;a>0||h>0;)switch(f.push(a-1),c.push(h-1),d[a][h].item()){case 0:--a,--h;break;case 1:--a;break;case 2:--h;break;default:throw new Error(`Internal error in dynamic time warping. Unexpected trace[${a}, ${h}]. Please file a bug report.`)}return f.reverse(),c.reverse(),[f,c]}function dimsToStride(m){const t=new Array(m.length);for(let i=m.length-1,s=1;i>=0;--i)t[i]=s,s*=m[i];return t}function ones(m){const t=m.reduce((i,s)=>i*s,1);return new Tensor("int64",new BigInt64Array(t).fill(1n),m)}function ones_like(m){return ones(m.dims)}class PriorityQueue{constructor(t=(i,s)=>i>s){this._heap=[],this._comparator=t}get size(){return this._heap.length}isEmpty(){return this.size===0}peek(){return this._heap[0]}push(...t){return this.extend(t)}extend(t){for(const i of t)this._heap.push(i),this._siftUp();return this.size}pop(){const t=this.peek(),i=this.size-1;return i>0&&this._swap(0,i),this._heap.pop(),this._siftDown(),t}replace(t){const i=this.peek();return this._heap[0]=t,this._siftDown(),i}_parent(t){return(t+1>>>1)-1}_left(t){return(t<<1)+1}_right(t){return t+1<<1}_greater(t,i){return this._comparator(this._heap[t],this._heap[i])}_swap(t,i){const s=this._heap[t];this._heap[t]=this._heap[i],this._heap[i]=s}_siftUp(){let t=this.size-1;for(;t>0&&this._greater(t,this._parent(t));)this._swap(t,this._parent(t)),t=this._parent(t)}_siftDown(){let t=0;for(;this._left(t)<this.size&&this._greater(this._left(t),t)||this._right(t)<this.size&&this._greater(this._right(t),t);){const i=this._right(t)<this.size&&this._greater(this._right(t),this._left(t))?this._right(t):this._left(t);this._swap(t,i),t=i}}}class CharTrie{constructor(){this.root=CharTrieNode.default()}extend(t){for(let i of t)this.push(i)}push(t){let i=this.root;for(let s of t){let u=i.children.get(s);u===void 0&&(u=CharTrieNode.default(),i.children.set(s,u)),i=u}i.isLeaf=!0}*commonPrefixSearch(t){let i=this.root,s="";for(let u=0;u<t.length&&i!==void 0;++u){const d=t[u];s+=d,i=i.children.get(d),i!==void 0&&i.isLeaf&&(yield s)}}}class CharTrieNode{constructor(t,i){this.isLeaf=t,this.children=i}static default(){return new CharTrieNode(!1,new Map)}}class TokenLattice{constructor(t,i,s){this.sentence=t,this.len=t.length,this.bosTokenId=i,this.eosTokenId=s,this.nodes=[],this.beginNodes=Array.from({length:this.len+1},()=>[]),this.endNodes=Array.from({length:this.len+1},()=>[]);const u=new TokenLatticeNode(this.bosTokenId,0,0,0,0),d=new TokenLatticeNode(this.eosTokenId,1,this.len,0,0);this.nodes.push(u.clone()),this.nodes.push(d.clone()),this.beginNodes[this.len].push(d),this.endNodes[0].push(u)}insert(t,i,s,u){const d=this.nodes.length,a=new TokenLatticeNode(u,d,t,i,s);this.beginNodes[t].push(a),this.endNodes[t+i].push(a),this.nodes.push(a)}viterbi(){const t=this.len;let i=0;for(;i<=t;){if(this.beginNodes[i].length==0)return[];for(let h of this.beginNodes[i]){h.prev=null;let f=0,c=null;for(let l of this.endNodes[i]){const n=l.backtraceScore+h.score;(c===null||n>f)&&(c=l.clone(),f=n)}if(c!==null)h.prev=c,h.backtraceScore=f;else return[]}++i}const s=[],d=this.beginNodes[t][0].prev;if(d===null)return[];let a=d.clone();for(;a.prev!==null;)s.push(a.clone()),a=a.clone().prev.clone();return s.reverse(),s}piece(t){return this.sentence.slice(t.pos,t.pos+t.length)}tokens(){return this.viterbi().map(i=>this.piece(i))}tokenIds(){return this.viterbi().map(i=>i.tokenId)}}class TokenLatticeNode{constructor(t,i,s,u,d){this.tokenId=t,this.nodeId=i,this.pos=s,this.length=u,this.score=d,this.prev=null,this.backtraceScore=0}clone(){const t=new TokenLatticeNode(this.tokenId,this.nodeId,this.pos,this.length,this.score);return t.prev=this.prev,t.backtraceScore=this.backtraceScore,t}}async function loadTokenizer(m,t){return await Promise.all([getModelJSON(m,"tokenizer.json",!0,t),getModelJSON(m,"tokenizer_config.json",!0,t)])}function regexSplit(m,t){const i=[];let s=0;for(const u of m.matchAll(t)){const d=u[0];s<u.index&&i.push(m.slice(s,u.index)),d.length>0&&i.push(d),s=u.index+d.length}return s<m.length&&i.push(m.slice(s)),i}function createPattern(m,t=!0){if(m.Regex!==void 0){const i=m.Regex.replace(/\\([#&~])/g,"$1");return new RegExp(i,"gu")}else if(m.String!==void 0){const i=escapeRegExp(m.String);return new RegExp(t?i:`(${i})`,"gu")}else return console.warn("Unknown pattern type:",m),null}function objectToMap(m){return new Map(Object.entries(m))}function prepareTensorForDecode(m){const t=m.dims;switch(t.length){case 1:return m.tolist();case 2:if(t[0]!==1)throw new Error("Unable to decode tensor with `batch size !== 1`. Use `tokenizer.batch_decode(...)` for batched inputs.");return m.tolist()[0];default:throw new Error(`Expected tensor to have 1-2 dimensions, got ${t.length}.`)}}function clean_up_tokenization(m){return m.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(m){return m.replace(/[\u0300-\u036f]/g,"")}function lowercase_and_remove_accent(m){return remove_accents(m.toLowerCase())}function fuse(m,t){let i=[],s=0;for(;s<m.length;){if(i.push(m[s]),m[s]!==t){++s;continue}for(;s<m.length&&m[s]===t;)++s}return i}function whitespace_split(m){return m.match(/\S+/g)||[]}const PUNCTUATION_REGEX="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E";class TokenizerModel extends Callable{constructor(t){super(),this.config=t,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(t,...i){switch(t.type){case"WordPiece":return new WordPieceTokenizer(t);case"Unigram":return new Unigram(t,...i);case"BPE":return new BPE(t);default:if(t.vocab)return new LegacyTokenizerModel(t,...i);throw new Error(`Unknown TokenizerModel type: ${t.type}`)}}_call(t){return this.encode(t)}encode(t){throw Error("encode should be implemented in subclass.")}convert_tokens_to_ids(t){let i=t.map(s=>this.tokens_to_ids.get(s)??this.unk_token_id);return this.fuse_unk&&(i=fuse(i,this.unk_token_id)),i}convert_ids_to_tokens(t){return t.map(i=>this.vocab[i]??this.unk_token)}}class WordPieceTokenizer extends TokenizerModel{constructor(t){super(t),this.tokens_to_ids=objectToMap(t.vocab),this.unk_token_id=this.tokens_to_ids.get(t.unk_token),this.unk_token=t.unk_token,this.max_input_chars_per_word=t.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[i,s]of this.tokens_to_ids)this.vocab[s]=i}encode(t){let i=[];for(let s of t){let u=[...s];if(u.length>this.max_input_chars_per_word){i.push(this.unk_token);continue}let d=!1,a=0,h=[];for(;a<u.length;){let f=u.length,c=null;for(;a<f;){let l=u.slice(a,f).join("");if(a>0&&(l=this.config.continuing_subword_prefix+l),this.tokens_to_ids.has(l)){c=l;break}--f}if(c===null){d=!0;break}h.push(c),a=f}d?i.push(this.unk_token):i.push(...h)}return i}}class Unigram extends TokenizerModel{constructor(t,i){super(t);const s=t.vocab.length;this.vocab=new Array(s),this.scores=new Array(s);for(let u=0;u<s;++u){const d=t.vocab[u];this.vocab[u]=d[0],this.scores[u]=d[1]}this.unk_token_id=t.unk_id,this.unk_token=this.vocab[t.unk_id],this.tokens_to_ids=new Map(this.vocab.map((u,d)=>[u,d])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=i.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=min(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new CharTrie,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(t){const i=t.sentence,s=i.length;let u=0;for(;u<s;){let a=!1;for(let h of this.trie.commonPrefixSearch(i.slice(u))){const f=this.tokens_to_ids.get(h),c=this.scores[f],l=h.length;t.insert(u,l,c,f),!a&&l===1&&(a=!0)}a||t.insert(u,1,this.unkScore,this.unk_token_id),u+=1}}tokenize(t){const i=new TokenLattice(t,this.bosTokenId,this.eosTokenId);return this.populateNodes(i),i.tokens()}encode(t){let i=[];for(let s of t){const u=this.tokenize(s);i.push(...u)}return i}}const BYTES_TO_UNICODE=(()=>{const m=[...Array.from({length:94},(u,d)=>d+33),...Array.from({length:12},(u,d)=>d+161),...Array.from({length:82},(u,d)=>d+174)];let t=m.slice(),i=0;for(let u=0;u<256;++u)m.includes(u)||(m.push(u),t.push(256+i),i+=1);let s=t.map(u=>String.fromCharCode(u));return Object.fromEntries(m.map((u,d)=>[u,s[d]]))})(),UNICODE_TO_BYTES=reverseDictionary(BYTES_TO_UNICODE);class BPE extends TokenizerModel{constructor(t){super(t),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=objectToMap(t.vocab),this.unk_token_id=this.tokens_to_ids.get(t.unk_token),this.unk_token=t.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[i,s]of this.tokens_to_ids)this.vocab[s]=i;this.bpe_ranks=new Map(t.merges.map((i,s)=>[i,s])),this.merges=t.merges.map(i=>i.split(this.BPE_SPLIT_TOKEN)),this.end_of_word_suffix=t.end_of_word_suffix,this.continuing_subword_suffix=t.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.cache=new Map}bpe(t){if(t.length===0)return[];const i=this.cache.get(t);if(i!==void 0)return i;const s=Array.from(t);this.end_of_word_suffix&&(s[s.length-1]+=this.end_of_word_suffix);let u=[];if(s.length>1){const d=new PriorityQueue((f,c)=>f.score<c.score);let a={token:s[0],bias:0,prev:null,next:null},h=a;for(let f=1;f<s.length;++f){const c={bias:f/s.length,token:s[f],prev:h,next:null};h.next=c,this._add_node(d,h),h=c}for(;!d.isEmpty();){const f=d.pop();if(f.deleted||!f.next||f.next.deleted)continue;if(f.deleted=!0,f.next.deleted=!0,f.prev){const l={...f.prev};f.prev.deleted=!0,f.prev=l,l.prev?l.prev.next=l:a=l}const c={token:f.token+f.next.token,bias:f.bias,prev:f.prev,next:f.next.next};c.prev?(c.prev.next=c,this._add_node(d,c.prev)):a=c,c.next&&(c.next.prev=c,this._add_node(d,c))}for(let f=a;f!==null;f=f.next)u.push(f.token)}else u=s;if(this.continuing_subword_suffix)for(let d=0;d<u.length-1;++d)u[d]+=this.continuing_subword_suffix;return this.cache.set(t,u),u}_add_node(t,i){const s=this.bpe_ranks.get(i.token+this.BPE_SPLIT_TOKEN+i.next.token);s!==void 0&&(i.score=s+i.bias,t.push(i))}encode(t){let i=[];for(let s of t){let u=this.bpe(s);for(let d of u)this.tokens_to_ids.has(d)?i.push(d):this.byte_fallback?i.push(...Array.from(this.text_encoder.encode(d)).map(a=>`<0x${a.toString(16).toUpperCase().padStart(2,"0")}>`)):i.push(this.unk_token)}return i}}class LegacyTokenizerModel extends TokenizerModel{constructor(t,i){super(t),this.tokens_to_ids=objectToMap(i.target_lang?t.vocab[i.target_lang]:t.vocab),this.bos_token=i.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=i.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=i.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=i.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=new Array(this.tokens_to_ids.size);for(const[s,u]of this.tokens_to_ids)this.vocab[u]=s}encode(t){return t}}class Normalizer extends Callable{constructor(t){super(),this.config=t}static fromConfig(t){if(t===null)return null;switch(t.type){case"BertNormalizer":return new BertNormalizer(t);case"Precompiled":return new Precompiled(t);case"Sequence":return new NormalizerSequence(t);case"Replace":return new Replace(t);case"NFC":return new NFC(t);case"NFKC":return new NFKC(t);case"NFKD":return new NFKD(t);case"Strip":return new StripNormalizer(t);case"StripAccents":return new StripAccents(t);case"Lowercase":return new Lowercase(t);case"Prepend":return new Prepend(t);default:throw new Error(`Unknown Normalizer type: ${t.type}`)}}normalize(t){throw Error("normalize should be implemented in subclass.")}_call(t){return this.normalize(t)}}class Replace extends Normalizer{normalize(t){let i=createPattern(this.config.pattern);return i===null||(t=t.replaceAll(i,this.config.content)),t}}class NFC extends Normalizer{normalize(t){return t=t.normalize("NFC"),t}}class NFKC extends Normalizer{normalize(t){return t=t.normalize("NFKC"),t}}class NFKD extends Normalizer{normalize(t){return t=t.normalize("NFKD"),t}}class StripNormalizer extends Normalizer{normalize(t){return this.config.strip_left&&this.config.strip_right?t=t.trim():(this.config.strip_left&&(t=t.trimStart()),this.config.strip_right&&(t=t.trimEnd())),t}}class StripAccents extends Normalizer{normalize(t){return t=remove_accents(t),t}}class Lowercase extends Normalizer{normalize(t){return t=t.toLowerCase(),t}}class Prepend extends Normalizer{normalize(t){return t=this.config.prepend+t,t}}class NormalizerSequence extends Normalizer{constructor(t){super(t),this.normalizers=t.normalizers.map(i=>Normalizer.fromConfig(i))}normalize(t){return this.normalizers.reduce((i,s)=>s.normalize(i),t)}}class BertNormalizer extends Normalizer{_tokenize_chinese_chars(t){let i=[];for(let s=0;s<t.length;++s){let u=t[s],d=u.charCodeAt(0);this._is_chinese_char(d)?(i.push(" "),i.push(u),i.push(" ")):i.push(u)}return i.join("")}_is_chinese_char(t){return t>=19968&&t<=40959||t>=13312&&t<=19903||t>=131072&&t<=173791||t>=173824&&t<=177983||t>=177984&&t<=178207||t>=178208&&t<=183983||t>=63744&&t<=64255||t>=194560&&t<=195103}stripAccents(t){return t.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}normalize(t){return this.config.handle_chinese_chars&&(t=this._tokenize_chinese_chars(t)),this.config.lowercase?(t=t.toLowerCase(),this.config.strip_accents!==!1&&(t=this.stripAccents(t))):this.config.strip_accents&&(t=this.stripAccents(t)),t}}class PreTokenizer extends Callable{static fromConfig(t){if(t===null)return null;switch(t.type){case"BertPreTokenizer":return new BertPreTokenizer(t);case"Sequence":return new PreTokenizerSequence(t);case"WhitespaceSplit":return new WhitespaceSplit(t);case"Metaspace":return new MetaspacePreTokenizer(t);case"ByteLevel":return new ByteLevelPreTokenizer(t);case"Split":return new SplitPreTokenizer(t);case"Punctuation":return new PunctuationPreTokenizer(t);case"Digits":return new DigitsPreTokenizer(t);case"Replace":return new ReplacePreTokenizer(t);default:throw new Error(`Unknown PreTokenizer type: ${t.type}`)}}pre_tokenize_text(t){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(t){let i=[];return Array.isArray(t)?i=t.map(s=>this.pre_tokenize_text(s)):i=this.pre_tokenize_text(t),i.flat()}_call(t){return this.pre_tokenize(t)}}class BertPreTokenizer extends PreTokenizer{constructor(t){super(),this.pattern=new RegExp(`[^\\s${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]`,"gu")}pre_tokenize_text(t){return t.trim().match(this.pattern)||[]}}class ByteLevelPreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=new RegExp("'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)|\\s+","gu"),this.byte_encoder=BYTES_TO_UNICODE,this.text_encoder=new TextEncoder}pre_tokenize_text(t){return this.add_prefix_space&&!t.startsWith(" ")&&(t=" "+t),(this.use_regex?t.match(this.pattern)||[]:[t]).map(s=>Array.from(this.text_encoder.encode(s),u=>this.byte_encoder[u]).join(""))}}class SplitPreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t,this.pattern=createPattern(this.config.pattern,this.config.invert)}pre_tokenize_text(t){return this.pattern===null?[]:this.config.invert?t.match(this.pattern)||[]:regexSplit(t,this.pattern)}}class PunctuationPreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t,this.pattern=new RegExp(`[^${PUNCTUATION_REGEX}]+|[${PUNCTUATION_REGEX}]+`,"gu")}pre_tokenize_text(t){return t.match(this.pattern)||[]}}class DigitsPreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t;const i=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(i,"gu")}pre_tokenize_text(t){return t.match(this.pattern)||[]}}class PostProcessor extends Callable{constructor(t){super(),this.config=t}static fromConfig(t){if(t===null)return null;switch(t.type){case"TemplateProcessing":return new TemplateProcessing(t);case"ByteLevel":return new ByteLevelPostProcessor(t);case"RobertaProcessing":return new RobertaProcessing(t);case"BertProcessing":return new BertProcessing(t);default:throw new Error(`Unknown PostProcessor type: ${t.type}`)}}post_process(t,...i){throw Error("post_process should be implemented in subclass.")}_call(t,...i){return this.post_process(t,...i)}}class BertProcessing extends PostProcessor{constructor(t){super(t),this.cls=t.cls[0],this.sep=t.sep[0]}post_process(t,i=null){return t=mergeArrays([this.cls],t,[this.sep]),i!==null&&(t=mergeArrays(t,[this.sep],i,[this.sep])),t}}class RobertaProcessing extends BertProcessing{}class TemplateProcessing extends PostProcessor{constructor(t){super(t),this.single=t.single,this.pair=t.pair}post_process(t,i=null){let s=i===null?this.single:this.pair,u=[];for(let d of s)"SpecialToken"in d?u.push(d.SpecialToken.id):"Sequence"in d&&(d.Sequence.id==="A"?u=mergeArrays(u,t):d.Sequence.id==="B"&&(u=mergeArrays(u,i)));return u}}class ByteLevelPostProcessor extends PostProcessor{post_process(t){return t}}class Decoder extends Callable{constructor(t){super(),this.config=t,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=t.trim_offsets}static fromConfig(t){switch(t.type){case"WordPiece":return new WordPieceDecoder(t);case"Metaspace":return new MetaspaceDecoder(t);case"ByteLevel":return new ByteLevelDecoder(t);case"Replace":return new ReplaceDecoder(t);case"ByteFallback":return new ByteFallback(t);case"Fuse":return new FuseDecoder(t);case"Strip":return new StripDecoder(t);case"Sequence":return new DecoderSequence(t);case"CTC":return new CTCDecoder(t);case"BPEDecoder":return new BPEDecoder(t);default:throw new Error(`Unknown Decoder type: ${t.type}`)}}_call(t){return this.decode(t)}decode(t){return this.decode_chain(t).join("")}decode_chain(t){throw Error("`decode_chain` should be implemented in subclass.")}}class ReplaceDecoder extends Decoder{decode_chain(t){let i=createPattern(this.config.pattern);return i===null?t:t.map(s=>s.replaceAll(i,this.config.content))}}class ByteFallback extends Decoder{constructor(t){super(t),this.text_decoder=new TextDecoder}decode_chain(t){let i=[],s=[];for(let u of t){let d=null;if(u.length===6&&u.startsWith("<0x")&&u.endsWith(">")){let a=parseInt(u.slice(3,5),16);isNaN(a)||(d=a)}if(d!==null)s.push(d);else{if(s.length>0){let a=this.text_decoder.decode(Uint8Array.from(s));i.push(a),s=[]}i.push(u)}}if(s.length>0){let u=this.text_decoder.decode(Uint8Array.from(s));i.push(u),s=[]}return i}}class FuseDecoder extends Decoder{decode_chain(t){return[t.join("")]}}class StripDecoder extends Decoder{constructor(t){super(t),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(t){return t.map(i=>{let s=0;for(let d=0;d<this.start&&i[d]===this.content;++d){s=d+1;continue}let u=i.length;for(let d=0;d<this.stop;++d){const a=i.length-d-1;if(i[a]===this.content){u=a;continue}else break}return i.slice(s,u)})}}class WordPieceDecoder extends Decoder{constructor(t){super(t),this.cleanup=t.cleanup}decode_chain(t){return t.map((i,s)=>(s!==0&&(i.startsWith(this.config.prefix)?i=i.replace(this.config.prefix,""):i=" "+i),this.cleanup&&(i=clean_up_tokenization(i)),i))}}class ByteLevelDecoder extends Decoder{constructor(t){super(t),this.byte_decoder=UNICODE_TO_BYTES,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(t){let i=t.join(""),s=new Uint8Array([...i].map(d=>this.byte_decoder[d]));return this.text_decoder.decode(s)}decode_chain(t){let i=[],s=[];for(let u of t)this.added_tokens.includes(u)?(s.length>0&&(i.push(this.convert_tokens_to_string(s)),s=[]),i.push(u)):s.push(u);return s.length>0&&i.push(this.convert_tokens_to_string(s)),i}}class CTCDecoder extends Decoder{constructor(t){super(t),this.pad_token=this.config.pad_token,this.word_delimiter_token=this.config.word_delimiter_token,this.cleanup=this.config.cleanup}convert_tokens_to_string(t){if(t.length===0)return"";let i=[t[0]];for(let d=1;d<t.length;++d)t[d]!==i.at(-1)&&i.push(t[d]);let u=i.filter(d=>d!==this.pad_token).join("");return this.cleanup&&(u=clean_up_tokenization(u).replaceAll(this.word_delimiter_token," ").trim()),u}decode_chain(t){return[this.convert_tokens_to_string(t)]}}class DecoderSequence extends Decoder{constructor(t){super(t),this.decoders=t.decoders.map(i=>Decoder.fromConfig(i))}decode_chain(t){return this.decoders.reduce((i,s)=>s.decode_chain(i),t)}}class BPEDecoder extends Decoder{constructor(t){super(t),this.suffix=this.config.suffix}decode_chain(t){return t.map((i,s)=>i.replaceAll(this.suffix,s===t.length-1?"":" "))}}class MetaspacePreTokenizer extends PreTokenizer{constructor(t){super(),this.addPrefixSpace=t.add_prefix_space,this.replacement=t.replacement,this.strRep=t.str_rep||this.replacement}pre_tokenize(t){typeof t=="string"&&(t=t.trimStart().split(/\s+/));const i=[];for(let s of t){let u=s.replaceAll(" ",this.strRep);this.addPrefixSpace&&!u.startsWith(this.replacement)&&(u=this.strRep+u),i.push(u)}return i}}class MetaspaceDecoder extends Decoder{constructor(t){super(t),this.addPrefixSpace=t.add_prefix_space,this.replacement=t.replacement}decode_chain(t){let i=[];for(let s=0;s<t.length;++s){let u=t[s].replaceAll(this.replacement," ");this.addPrefixSpace&&s==0&&u.startsWith(" ")&&(u=u.substring(1)),i.push(u)}return i}}class Precompiled extends Normalizer{constructor(t){super(t),this.charsmap=t.precompiled_charsmap}normalize(t){return t=t.replace(/[\u0001-\u0008\u000B\u000E-\u001F\u007F\u008F\u009F]/gm,""),t=t.replace(/[\u0009\u000A\u000C\u000D\u1680\u200B\u200C\u200E\u200F\u2028\u2029\u2581\uFEFF\uFFFD]/gm," "),t.includes("～")?t=t.split("～").map(s=>s.normalize("NFKC")).join("～"):t=t.normalize("NFKC"),t}}class PreTokenizerSequence extends PreTokenizer{constructor(t){super(),this.tokenizers=t.pretokenizers.map(i=>PreTokenizer.fromConfig(i))}pre_tokenize_text(t){return typeof t=="string"&&(t=[t]),this.tokenizers.reduce((i,s)=>s.pre_tokenize(i),t)}}class WhitespaceSplit extends PreTokenizer{constructor(t){super()}pre_tokenize_text(t){return whitespace_split(t)}}class ReplacePreTokenizer extends PreTokenizer{constructor(t){super(),this.config=t,this.pattern=createPattern(this.config.pattern),this.content=this.config.content}pre_tokenize_text(t){return this.pattern===null?[t]:[t.replaceAll(this.pattern,this.config.content)]}}class PreTrainedTokenizer extends Callable{constructor(t,i){super(),this.normalizer=Normalizer.fromConfig(t.normalizer),this.pre_tokenizer=PreTokenizer.fromConfig(t.pre_tokenizer),this.model=TokenizerModel.fromConfig(t.model,i),this.post_processor=PostProcessor.fromConfig(t.post_processor),this.decoder=Decoder.fromConfig(t.decoder),this.decoder.end_of_word_suffix=this.model.end_of_word_suffix,this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(let s of t.added_tokens){let u=s.id,d=s.content;this.added_tokens.push(d),this.model.tokens_to_ids.set(d,u),this.model.vocab[u]=d,s.special&&(this.special_tokens.push(d),this.all_special_ids.push(u))}this.special_tokens.push(...i.additional_special_tokens??[]),this.special_tokens=[...new Set(this.special_tokens)],this.decoder.added_tokens=this.added_tokens,this.added_tokens_regex=this.added_tokens.length>0?new RegExp("("+this.added_tokens.map(escapeRegExp).join("|")+")"):null,this.mask_token=this.getToken(i,"mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken(i,"pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken(i,"sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.unk_token=this.getToken(i,"unk_token"),this.unk_token_id=this.model.tokens_to_ids.get(this.unk_token),this.model_max_length=i.model_max_length,this.remove_space=i.remove_space,this.clean_up_tokenization_spaces=i.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=i.do_lowercase_and_remove_accent??!1,this.padding_side="right"}getToken(t,...i){for(let s of i){let u=t[s];if(u)if(typeof u=="object"){if(u.__type==="AddedToken")return u.content;throw Error(`Unknown token: ${u}`)}else return u}return null}static async from_pretrained(t,{progress_callback:i=null,config:s=null,cache_dir:u=null,local_files_only:d=!1,revision:a="main"}={}){let h=await loadTokenizer(t,{progress_callback:i,config:s,cache_dir:u,local_files_only:d,revision:a});return new this(...h)}prepare_model_inputs(t){return t}_call(t,{text_pair:i=null,add_special_tokens:s=!0,padding:u=!1,truncation:d=null,max_length:a=null,return_tensor:h=!0}={}){let f;if(Array.isArray(t)){if(t.length===0)throw Error("text array must be non-empty");if(i!==null){if(Array.isArray(i)){if(t.length!==i.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");f=t.map((e,r)=>this.encode(e,i[r],{add_special_tokens:s}))}else f=t.map(e=>this.encode(e,null,{add_special_tokens:s}))}else{if(t===null)throw Error("text may not be null");if(Array.isArray(i))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");f=[this.encode(t,i,{add_special_tokens:s})]}let c=max(f.map(e=>e.length))[0];a===null&&(a=c),a=Math.min(a,this.model_max_length);let l=[];if(u||d)for(let e=0;e<f.length;++e)if(f[e].length===a){l.push(new Array(f[e].length).fill(1));continue}else if(f[e].length>a)d&&(f[e]=f[e].slice(0,a)),l.push(new Array(f[e].length).fill(1));else if(u){let r=a-f[e].length;this.padding_side==="right"?(l.push(new Array(f[e].length).fill(1).concat(new Array(r).fill(0))),f[e].push(...new Array(r).fill(this.pad_token_id))):(l.push(new Array(r).fill(0).concat(new Array(f[e].length).fill(1))),f[e].unshift(...new Array(r).fill(this.pad_token_id)))}else l.push(new Array(f[e].length).fill(1));else l=f.map(e=>new Array(e.length).fill(1));if(h){if(!(u&&d)&&f.some(r=>r.length!==f[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");let e=[f.length,f[0].length];f=new Tensor("int64",BigInt64Array.from(f.flat().map(BigInt)),e),l=new Tensor("int64",BigInt64Array.from(l.flat().map(BigInt)),e)}else Array.isArray(t)||(f=f[0],l=l[0]);let n={input_ids:f,attention_mask:l};return n=this.prepare_model_inputs(n),n}_encode_text(t){return t===null?null:(this.added_tokens_regex?t.split(this.added_tokens_regex).filter(u=>u):[t]).map(u=>{if(this.added_tokens.includes(u))return u;{this.remove_space===!0&&(u=u.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(u=lowercase_and_remove_accent(u)),this.normalizer!==null&&(u=this.normalizer(u));let d=this.pre_tokenizer!==null?this.pre_tokenizer(u):[u];return this.model(d)}}).flat()}encode(t,i=null,{add_special_tokens:s=!0}={}){let u=this._encode_text(t),d=this._encode_text(i),a=this.post_processor!==null&&s?this.post_processor(u,d):mergeArrays(u??[],d??[]);return this.model.convert_tokens_to_ids(a)}batch_decode(t,i={}){return t instanceof Tensor&&(t=t.tolist()),t.map(s=>this.decode(s,i))}decode(t,i={}){if(t instanceof Tensor&&(t=prepareTensorForDecode(t)),!Array.isArray(t)||t.length===0||!isIntegralNumber(t[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(t,i)}decode_single(t,{skip_special_tokens:i=!1,clean_up_tokenization_spaces:s=null}){let u=this.model.convert_ids_to_tokens(t);i&&(u=u.filter(a=>!this.special_tokens.includes(a)));let d=this.decoder(u);return this.decoder.end_of_word_suffix&&(d=d.replaceAll(this.decoder.end_of_word_suffix," "),i&&(d=d.trim())),(s??this.clean_up_tokenization_spaces)&&(d=clean_up_tokenization(d)),d}}function add_token_types(m){if(m.input_ids instanceof Tensor)m.token_type_ids=new Tensor("int64",new BigInt64Array(m.input_ids.data.length),m.input_ids.dims);else if(Array.isArray(m.input_ids))Array.isArray(m.input_ids[0])?m.token_type_ids=m.input_ids.map(t=>new Array(t.length).fill(0)):m.token_type_ids=new Array(m.input_ids.length).fill(0);else throw new Error("Input ids must be a Tensor or an Array");return m}class BertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class AlbertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class MobileBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class SqueezeBertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class DebertaTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class DebertaV2Tokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class HerbertTokenizer extends PreTrainedTokenizer{prepare_model_inputs(t){return add_token_types(t)}}class DistilBertTokenizer extends PreTrainedTokenizer{}class CamembertTokenizer extends PreTrainedTokenizer{}class XLMTokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}prepare_model_inputs(t){return add_token_types(t)}}class T5Tokenizer extends PreTrainedTokenizer{}class GPT2Tokenizer extends PreTrainedTokenizer{}class BartTokenizer extends PreTrainedTokenizer{}class MBartTokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter(s=>this.languageRegex.test(s)),this.lang_to_token=s=>s}_build_translation_inputs(t,i,s){return _build_translation_inputs(this,t,i,s)}}class MBart50Tokenizer extends MBartTokenizer{}class RobertaTokenizer extends PreTrainedTokenizer{}class BloomTokenizer extends PreTrainedTokenizer{constructor(t,i){var d,a;const s=".,!?…。，、।۔،",u=(a=(d=t.pre_tokenizer)==null?void 0:d.pretokenizers[0])==null?void 0:a.pattern;u&&u.Regex===` ?[^(\\s|[${s}])]+`&&(u.Regex=` ?[^\\s${s}]+`),super(t,i)}}class LlamaTokenizer extends PreTrainedTokenizer{}class CodeLlamaTokenizer extends PreTrainedTokenizer{}class XLMRobertaTokenizer extends PreTrainedTokenizer{}class MPNetTokenizer extends PreTrainedTokenizer{}class FalconTokenizer extends PreTrainedTokenizer{}class GPTNeoXTokenizer extends PreTrainedTokenizer{}function _build_translation_inputs(m,t,i,s){if(!("language_codes"in m)||!Array.isArray(m.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in m)||!(m.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in m)||typeof m.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const u=s.src_lang,d=s.tgt_lang;if(!m.language_codes.includes(d))throw new Error(`Target language code "${d}" is not valid. Must be one of: {${m.language_codes.join(", ")}}`);if(u!==void 0){if(!m.language_codes.includes(u))throw new Error(`Source language code "${u}" is not valid. Must be one of: {${m.language_codes.join(", ")}}`);for(let a of m.post_processor.config.single)if("SpecialToken"in a&&m.languageRegex.test(a.SpecialToken.id)){a.SpecialToken.id=m.lang_to_token(u);break}}return s.forced_bos_token_id=m.model.convert_tokens_to_ids([m.lang_to_token(d)])[0],m._call(t,i)}class NllbTokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(s=>this.languageRegex.test(s)),this.lang_to_token=s=>s}_build_translation_inputs(t,i,s){return _build_translation_inputs(this,t,i,s)}}class M2M100Tokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(s=>this.languageRegex.test(s)).map(s=>s.slice(2,-2)),this.lang_to_token=s=>`__${s}__`}_build_translation_inputs(t,i,s){return _build_translation_inputs(this,t,i,s)}}const WHISPER_LANGUAGES=[["en","english"],["zh","chinese"],["de","german"],["es","spanish"],["ru","russian"],["ko","korean"],["fr","french"],["ja","japanese"],["pt","portuguese"],["tr","turkish"],["pl","polish"],["ca","catalan"],["nl","dutch"],["ar","arabic"],["sv","swedish"],["it","italian"],["id","indonesian"],["hi","hindi"],["fi","finnish"],["vi","vietnamese"],["he","hebrew"],["uk","ukrainian"],["el","greek"],["ms","malay"],["cs","czech"],["ro","romanian"],["da","danish"],["hu","hungarian"],["ta","tamil"],["no","norwegian"],["th","thai"],["ur","urdu"],["hr","croatian"],["bg","bulgarian"],["lt","lithuanian"],["la","latin"],["mi","maori"],["ml","malayalam"],["cy","welsh"],["sk","slovak"],["te","telugu"],["fa","persian"],["lv","latvian"],["bn","bengali"],["sr","serbian"],["az","azerbaijani"],["sl","slovenian"],["kn","kannada"],["et","estonian"],["mk","macedonian"],["br","breton"],["eu","basque"],["is","icelandic"],["hy","armenian"],["ne","nepali"],["mn","mongolian"],["bs","bosnian"],["kk","kazakh"],["sq","albanian"],["sw","swahili"],["gl","galician"],["mr","marathi"],["pa","punjabi"],["si","sinhala"],["km","khmer"],["sn","shona"],["yo","yoruba"],["so","somali"],["af","afrikaans"],["oc","occitan"],["ka","georgian"],["be","belarusian"],["tg","tajik"],["sd","sindhi"],["gu","gujarati"],["am","amharic"],["yi","yiddish"],["lo","lao"],["uz","uzbek"],["fo","faroese"],["ht","haitian creole"],["ps","pashto"],["tk","turkmen"],["nn","nynorsk"],["mt","maltese"],["sa","sanskrit"],["lb","luxembourgish"],["my","myanmar"],["bo","tibetan"],["tl","tagalog"],["mg","malagasy"],["as","assamese"],["tt","tatar"],["haw","hawaiian"],["ln","lingala"],["ha","hausa"],["ba","bashkir"],["jw","javanese"],["su","sundanese"]],WHISPER_LANGUAGE_MAPPING=new Map(WHISPER_LANGUAGES),WHISPER_TO_LANGUAGE_CODE_MAPPING=new Map([...WHISPER_LANGUAGES.map(([m,t])=>[t,m]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);class WhisperTokenizer extends PreTrainedTokenizer{_decode_asr(t,{return_timestamps:i=!1,return_language:s=!1,time_precision:u=null,force_full_sequences:d=!0}={}){if(u===null)throw Error("Must specify time_precision");let a=null;const h=i==="word";function f(){return{language:a,timestamp:[null,null],text:""}}const c=[];let l=f(),n=0;const e=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let r=[],o=[],p=!1,g=null;const _=new Set(this.all_special_ids);for(let w of t){const T=w.tokens,S=h?w.token_timestamps:null;let A=null,P=e;if("stride"in w){const[N,z,$]=w.stride;if(n-=z,g=N-$,z&&(P=z/u+e),$)for(let C=T.length-1;C>=0;--C){const G=T[C];if(G>=e){if(A!==null&&(G-e)*u<g)break;A=G}}}let x=[],M=[];for(let N=0;N<T.length;++N){const z=T[N];if(_.has(z)){const $=this.decode([z]),C=WHISPER_LANGUAGE_MAPPING.get($.slice(2,-2));if(C!==void 0){if(a!==null&&C!==a&&!i){r.push(x);const G=this.findLongestCommonSequence(r)[0],D=this.decode(G);l.text=D,c.push(l),r=[],x=[],l=f()}a=l.language=C}}else if(z>=e){const $=(z-e)*u+n,C=round($,2);if(A!==null&&z>=A)p=!0;else if(p||r.length>0&&z<P)p=!1;else if(l.timestamp[0]===null)l.timestamp[0]=C;else if(C!==l.timestamp[0]){l.timestamp[1]=C,r.push(x),h&&o.push(M);const[G,D]=this.findLongestCommonSequence(r,o),R=this.decode(G);l.text=R,h&&(l.words=this.collateWordTimestamps(G,D,a)),c.push(l),r=[],x=[],o=[],M=[],l=f()}}else if(x.push(z),h){let $=round(S[N]+n,2),C;N+1<S.length?C=round(S[N+1]+n,2):C=null,M.push([$,C])}}if("stride"in w){const[N,z,$]=w.stride;n+=N-$}x.length>0?(r.push(x),h&&o.push(M)):r.every(N=>N.length===0)&&(l=f(),r=[],x=[],o=[],M=[])}if(r.length>0){if(d&&i)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[w,T]=this.findLongestCommonSequence(r,o),S=this.decode(w);l.text=S,h&&(l.words=this.collateWordTimestamps(w,T,a)),c.push(l)}let b=Object.create(null);const y=c.map(w=>w.text).join("");if(i||s){for(let w=0;w<c.length;++w){const T=c[w];i||delete T.timestamp,s||delete T.language}if(h){let w=[];for(let T of c)for(let S of T.words)w.push(S);b={chunks:w}}else b={chunks:c}}return[y,b]}findLongestCommonSequence(t,i=null){let s=t[0],u=s.length,d=[];const a=Array.isArray(i)&&i.length>0;let h=a?[]:null,f=a?i[0]:null;for(let c=1;c<t.length;++c){const l=t[c];let n=0,e=[u,u,0,0];const r=l.length;for(let w=1;w<u+r;++w){const T=w/1e4,S=Math.max(0,u-w),A=Math.min(u,u+r-w),P=s.slice(S,A),x=Math.max(0,w-u),M=Math.min(r,w),N=l.slice(x,M);if(P.length!==N.length)throw new Error("There is a bug within whisper `decode_asr` function, please report it. Dropping to prevent bad inference.");const z=P.filter((C,G)=>C===N[G]).length,$=z/w+T;z>1&&$>n&&(n=$,e=[S,A,x,M])}const[o,p,g,_]=e,b=Math.floor((p+o)/2),y=Math.floor((_+g)/2);d.push(...s.slice(0,b)),s=l.slice(y),u=s.length,a&&(h.push(...f.slice(0,b)),f=i[c].slice(y))}return d.push(...s),a?(h.push(...f),[d,h]):[d,[]]}collateWordTimestamps(t,i,s){let[u,d,a]=this.combineTokensIntoWords(t,s),h=[];for(let f=0;f<u.length;++f){const c=a[f];h.push({text:u[f],timestamp:[i[c.at(0)][0],i[c.at(-1)][1]]})}return h}combineTokensIntoWords(t,i,s=`"'“¡¿([{-`,u=`"'.。,，!！?？:：”)]}、`){i=i??"english";let d,a,h;return["chinese","japanese","thai","lao","myanmar"].includes(i)?[d,a,h]=this.splitTokensOnUnicode(t):[d,a,h]=this.splitTokensOnSpaces(t),this.mergePunctuations(d,a,h,s,u)}decode(t,i){let s;return i&&i.decode_with_timestamps?(t instanceof Tensor&&(t=prepareTensorForDecode(t)),s=this.decodeWithTimestamps(t,i)):s=super.decode(t,i),s}decodeWithTimestamps(t,i){const s=(i==null?void 0:i.time_precision)??.02,u=Array.from(this.all_special_ids).at(-1)+1;let d=[[]];for(let a of t)if(a>=u){let h=(a-u)*s;h=round(h,2),d.push(`<|${h}|>`),d.push([])}else d[d.length-1].push(a);return d=d.map(a=>typeof a=="string"?a:super.decode(a,i)),d.join("")}splitTokensOnUnicode(t){const i=this.decode(t,{decode_with_timestamps:!0}),s="�";let u=[],d=[],a=[],h=[],f=[],c=0;for(let l=0;l<t.length;++l){const n=t[l];h.push(n),f.push(l);const e=this.decode(h,{decode_with_timestamps:!0});(!e.includes(s)||i[c+e.indexOf(s)]===s)&&(u.push(e),d.push(h),a.push(f),h=[],f=[],c+=e.length)}return[u,d,a]}splitTokensOnSpaces(t){let[i,s,u]=this.splitTokensOnUnicode(t),d=[],a=[],h=[];const f=new RegExp(`^[${PUNCTUATION_REGEX}]$`,"gu");for(let c=0;c<i.length;++c){const l=i[c],n=s[c],e=u[c],r=n[0]>=this.model.tokens_to_ids.get("<|endoftext|>"),o=l.startsWith(" "),p=l.trim(),g=f.test(p);if(r||o||g||d.length===0)d.push(l),a.push(n),h.push(e);else{const _=d.length-1;d[_]+=l,a[_].push(...n),h[_].push(...e)}}return[d,a,h]}mergePunctuations(t,i,s,u,d){let a=structuredClone(t),h=structuredClone(i),f=structuredClone(s),c=a.length-2,l=a.length-1;for(;c>=0;)a[c].startsWith(" ")&&u.includes(a[c].trim())?(a[l]=a[c]+a[l],h[l]=mergeArrays(h[c],h[l]),f[l]=mergeArrays(f[c],f[l]),a[c]="",h[c]=[],f[c]=[]):l=c,--c;for(c=0,l=1;l<a.length;)!a[c].endsWith(" ")&&d.includes(a[l])?(a[c]+=a[l],h[c]=mergeArrays(h[c],h[l]),f[c]=mergeArrays(f[c],f[l]),a[l]="",h[l]=[],f[l]=[]):c=l,++l;return[a.filter(n=>n),h.filter(n=>n.length>0),f.filter(n=>n.length>0)]}get_decoder_prompt_ids({language:t=null,task:i=null,no_timestamps:s=!0}={}){let u=[];if(t){t=t.toLowerCase();let d=WHISPER_TO_LANGUAGE_CODE_MAPPING.get(t);if(d===void 0)if(WHISPER_LANGUAGE_MAPPING.has(t))d=t;else{const f=t.length===2?WHISPER_LANGUAGE_MAPPING.keys():WHISPER_LANGUAGE_MAPPING.values();throw new Error(`Language "${t}" is not supported. Must be one of: ${JSON.stringify(f)}`)}let a=this.model.tokens_to_ids.get(`<|${d}|>`);if(a===void 0)throw new Error(`Unable to find language "${d}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);u.push(a)}else u.push(null);if(i){if(i=i.toLowerCase(),i!=="transcribe"&&i!=="translate")throw new Error(`Task "${i}" is not supported. Must be one of: ["transcribe", "translate"]`);let d=this.model.tokens_to_ids.get(`<|${i}|>`);if(d===void 0)throw new Error(`Unable to find task "${i}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);u.push(d)}else u.push(null);if(s){let d=this.model.tokens_to_ids.get("<|notimestamps|>");if(d===void 0)throw new Error('Unable to find "<|notimestamps|>" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.');u.push(d)}return u.map((d,a)=>[a+1,d]).filter(d=>d[1]!==null)}}class CodeGenTokenizer extends PreTrainedTokenizer{}class CLIPTokenizer extends PreTrainedTokenizer{}class MarianTokenizer extends PreTrainedTokenizer{constructor(t,i){super(t,i),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter(s=>this.languageRegex.test(s)),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(t){if(t===null)return null;let[i,...s]=t.trim().split(this.languageRegex);if(s.length===0)return super._encode_text(i);if(s.length===2){let[u,d]=s;return this.supported_language_codes.includes(u)||console.warn(`Unsupported language code "${u}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),mergeArrays([u],super._encode_text(d))}}}class Wav2Vec2CTCTokenizer extends PreTrainedTokenizer{}class BlenderbotTokenizer extends PreTrainedTokenizer{}class BlenderbotSmallTokenizer extends PreTrainedTokenizer{}class SpeechT5Tokenizer extends PreTrainedTokenizer{}class NougatTokenizer extends PreTrainedTokenizer{}class AutoTokenizer{static async from_pretrained(t,{quantized:i=!0,progress_callback:s=null,config:u=null,cache_dir:d=null,local_files_only:a=!1,revision:h="main"}={}){let[f,c]=await loadTokenizer(t,{quantized:i,progress_callback:s,config:u,cache_dir:d,local_files_only:a,revision:h}),l=c.tokenizer_class.replace(/Fast$/,""),n=this.TOKENIZER_CLASS_MAPPING[l];return n||(console.warn(`Unknown tokenizer class "${l}", attempting to construct from base class.`),n=PreTrainedTokenizer),new n(f,c)}}he(AutoTokenizer,"TOKENIZER_CLASS_MAPPING",{T5Tokenizer,DistilBertTokenizer,CamembertTokenizer,DebertaTokenizer,DebertaV2Tokenizer,BertTokenizer,HerbertTokenizer,XLMTokenizer,MobileBertTokenizer,SqueezeBertTokenizer,AlbertTokenizer,GPT2Tokenizer,BartTokenizer,MBartTokenizer,MBart50Tokenizer,RobertaTokenizer,WhisperTokenizer,CodeGenTokenizer,CLIPTokenizer,MarianTokenizer,BloomTokenizer,NllbTokenizer,M2M100Tokenizer,LlamaTokenizer,CodeLlamaTokenizer,XLMRobertaTokenizer,MPNetTokenizer,FalconTokenizer,GPTNeoXTokenizer,Wav2Vec2CTCTokenizer,BlenderbotTokenizer,BlenderbotSmallTokenizer,SpeechT5Tokenizer,NougatTokenizer,PreTrainedTokenizer});async function loadConfig(m,t){return await getModelJSON(m,"config.json",!0,t)}class PretrainedConfig{constructor(t){this.model_type=null,this.is_encoder_decoder=!1,Object.assign(this,t)}static async from_pretrained(t,{progress_callback:i=null,config:s=null,cache_dir:u=null,local_files_only:d=!1,revision:a="main"}={}){let h=s??await loadConfig(t,{progress_callback:i,config:s,cache_dir:u,local_files_only:d,revision:a});return new this(h)}}class AutoConfig{static async from_pretrained(...t){return PretrainedConfig.from_pretrained(...t)}}class LogitsProcessorList extends Callable{constructor(){super(),this.processors=[]}push(t){this.processors.push(t)}extend(t){this.processors.push(...t)}_call(t,i){for(let s of i)this.processors.forEach(u=>u(t,s))}[Symbol.iterator](){return this.processors.values()}}class LogitsProcessor extends Callable{_call(t,i){throw Error("`_call` should be implemented in a subclass")}}class ForceTokensLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.force_token_map=Object.fromEntries(t??[])}_call(t,i){let s=this.force_token_map[t.length];return exists(s)&&(i.data.fill(-1/0),i.data[s]=0),i}}class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.bos_token_id=t}_call(t,i){return t.length===1&&(i.data.fill(-1/0),i.data[this.bos_token_id]=0),i}}class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(t,i){super(),this.max_length=t,this.forced_eos_token_id=i}_call(t,i){}}class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(t,i){super(),this.begin_suppress_tokens=t,this.begin_index=i}_call(t,i){if(t.length===this.begin_index)for(let s of this.begin_suppress_tokens)i.data[s]=-1/0;return i}}class WhisperTimeStampLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.eos_token_id=t.eos_token_id,this.no_timestamps_token_id=t.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(t.forced_decoder_ids||[]).length+2,t.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=t.max_initial_timestamp_index}_call(t,i){if(i.data[this.no_timestamps_token_id]=-1/0,t.length===this.begin_index-1)return i.data.fill(-1/0),i.data[this.timestamp_begin]=0,i;const s=t.slice(this.begin_index),u=s.length>=1&&s[s.length-1]>=this.timestamp_begin,d=s.length<2||s[s.length-2]>=this.timestamp_begin;if(u&&(d?i.data.subarray(this.timestamp_begin).fill(-1/0):i.data.subarray(0,this.eos_token_id).fill(-1/0)),t.length===this.begin_index&&this.max_initial_timestamp_index!==null){const c=this.timestamp_begin+this.max_initial_timestamp_index;i.data.subarray(c+1).fill(-1/0)}const a=log_softmax(i.data),h=Math.log(a.subarray(this.timestamp_begin).map(Math.exp).reduce((c,l)=>c+l)),f=max(a.subarray(0,this.timestamp_begin))[0];return h>f&&i.data.subarray(0,this.timestamp_begin).fill(-1/0),i}}class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.no_repeat_ngram_size=t}getNgrams(t){const i=t.length,s=[];for(let d=0;d<i+1-this.no_repeat_ngram_size;++d){const a=[];for(let h=0;h<this.no_repeat_ngram_size;++h)a.push(t[d+h]);s.push(a)}const u=new Map;for(const d of s){const a=d.slice(0,d.length-1),h=JSON.stringify(a),f=u.get(h)??[];f.push(d[d.length-1]),u.set(h,f)}return u}getGeneratedNgrams(t,i){const s=i.slice(i.length+1-this.no_repeat_ngram_size,i.length);return t.get(JSON.stringify(s))??[]}calcBannedNgramTokens(t){const i=[];if(t.length+1<this.no_repeat_ngram_size)return i;{const s=this.getNgrams(t);return this.getGeneratedNgrams(s,t)}}_call(t,i){const s=this.calcBannedNgramTokens(t);for(const u of s)i.data[u]=-1/0;return i}}class RepetitionPenaltyLogitsProcessor extends LogitsProcessor{constructor(t){super(),this.penalty=t}_call(t,i){for(const s of t)i.data[s]<0?i.data[s]*=this.penalty:i.data[s]/=this.penalty;return i}}class MinLengthLogitsProcessor extends LogitsProcessor{constructor(t,i){super(),this.min_length=t,this.eos_token_id=Array.isArray(i)?i:[i]}_call(t,i){if(t.length<this.min_length)for(const s of this.eos_token_id)i.data[s]=-1/0;return i}}class MinNewTokensLengthLogitsProcessor extends LogitsProcessor{constructor(t,i,s){super(),this.prompt_length_to_skip=t,this.min_new_tokens=i,this.eos_token_id=Array.isArray(s)?s:[s]}_call(t,i){if(t.length-this.prompt_length_to_skip<this.min_new_tokens)for(const u of this.eos_token_id)i.data[u]=-1/0;return i}}class NoBadWordsLogitsProcessor extends LogitsProcessor{constructor(t,i){super(),this.bad_words_ids=t,this.eos_token_id=Array.isArray(i)?i:[i]}_call(t,i){for(const s of this.bad_words_ids){let u=!0;for(let d=1;d<=s.length-1&&s.length<t.length;++d)if(s.at(-d-1)!==t.at(-d)){u=!1;break}u&&(i.data[s.at(-1)]=-1/0)}return i}}class GenerationConfig{constructor(t={}){this.max_length=t.max_length??20,this.max_new_tokens=t.max_new_tokens??null,this.min_length=t.min_length??0,this.min_new_tokens=t.min_new_tokens??null,this.early_stopping=t.early_stopping??!1,this.max_time=t.max_time??null,this.do_sample=t.do_sample??!1,this.num_beams=t.num_beams??1,this.num_beam_groups=t.num_beam_groups??1,this.penalty_alpha=t.penalty_alpha??null,this.use_cache=t.use_cache??!0,this.temperature=t.temperature??1,this.top_k=t.top_k??50,this.top_p=t.top_p??1,this.typical_p=t.typical_p??1,this.epsilon_cutoff=t.epsilon_cutoff??0,this.eta_cutoff=t.eta_cutoff??0,this.diversity_penalty=t.diversity_penalty??0,this.repetition_penalty=t.repetition_penalty??1,this.encoder_repetition_penalty=t.encoder_repetition_penalty??1,this.length_penalty=t.length_penalty??1,this.no_repeat_ngram_size=t.no_repeat_ngram_size??0,this.bad_words_ids=t.bad_words_ids??null,this.force_words_ids=t.force_words_ids??null,this.renormalize_logits=t.renormalize_logits??!1,this.constraints=t.constraints??null,this.forced_bos_token_id=t.forced_bos_token_id??null,this.forced_eos_token_id=t.forced_eos_token_id??null,this.remove_invalid_values=t.remove_invalid_values??!1,this.exponential_decay_length_penalty=t.exponential_decay_length_penalty??null,this.suppress_tokens=t.suppress_tokens??null,this.begin_suppress_tokens=t.begin_suppress_tokens??null,this.forced_decoder_ids=t.forced_decoder_ids??null,this.num_return_sequences=t.num_return_sequences??1,this.output_attentions=t.output_attentions??!1,this.output_hidden_states=t.output_hidden_states??!1,this.output_scores=t.output_scores??!1,this.return_dict_in_generate=t.return_dict_in_generate??!1,this.pad_token_id=t.pad_token_id??null,this.bos_token_id=t.bos_token_id??null,this.eos_token_id=t.eos_token_id??null,this.encoder_no_repeat_ngram_size=t.encoder_no_repeat_ngram_size??0,this.decoder_start_token_id=t.decoder_start_token_id??null,this.generation_kwargs=t.generation_kwargs??{}}}class Sampler extends Callable{constructor(t){super(),this.generation_config=t}_call(t,i=-1){return this.sample(t,i)}sample(t,i){throw Error("sample should be implemented in subclasses.")}getLogits(t,i){let s=t.dims.at(-1),u=t.data;if(i===-1)u=u.slice(-s);else{let d=i*s;u=u.slice(d,d+s)}return this.generation_config.temperature>0&&(u=u.map(d=>d/this.generation_config.temperature)),u}randomSelect(t){let i=t.reduce((u,d)=>u+d,0),s=Math.random()*i;for(let u=0;u<t.length;++u)if(s-=t[u],s<=0)return u;return 0}static getSampler(t){if(t.do_sample)return new MultinomialSampler(t);if(t.num_beams>1)return new BeamSearchSampler(t);if(t.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${t.num_return_sequences}.`);return new GreedySampler(t)}}class GreedySampler extends Sampler{sample(t,i=-1){let s=this.getLogits(t,i);return[[max(s)[1],0]]}}class MultinomialSampler extends Sampler{sample(t,i=-1){let s=t.dims.at(-1);this.generation_config.top_k>0&&(s=Math.min(this.generation_config.top_k,s));const u=this.getLogits(t,i),d=getTopItems(u,s),a=softmax(d.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},()=>{const h=this.randomSelect(a);return[d[h][0],Math.log(a[h])]})}}class BeamSearchSampler extends Sampler{sample(t,i=-1){let s=t.dims.at(-1);this.generation_config.top_k>0&&(s=Math.min(this.generation_config.top_k,s));const u=this.getLogits(t,i),d=getTopItems(u,s),a=softmax(d.map(h=>h[1]));return Array.from({length:this.generation_config.num_beams},(h,f)=>[d[f][0],Math.log(a[f])])}}const{InferenceSession,Tensor:ONNXTensor,env}=ONNX,MODEL_TYPES={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4},MODEL_TYPE_MAPPING=new Map,MODEL_NAME_TO_CLASS_MAPPING=new Map,MODEL_CLASS_TO_NAME_MAPPING=new Map;async function constructSession(m,t,i){let s=`onnx/${t}${i.quantized?"_quantized":""}.onnx`,u=await getModelFile(m,s,!0,i);try{return await InferenceSession.create(u,{executionProviders})}catch(d){if(executionProviders.length===1&&executionProviders[0]==="wasm")throw d;return console.warn(d),console.warn("Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback. "),await InferenceSession.create(u,{executionProviders:["wasm"]})}}function validateInputs(m,t){const i=Object.create(null),s=[];for(const a of m.inputNames){const h=t[a];if(!(h instanceof Tensor)){s.push(a);continue}i[a]=env.wasm.proxy?h.clone():h}if(s.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${s.join(", ")}.`);const u=Object.keys(t).length,d=m.inputNames.length;if(u>d){let a=Object.keys(t).filter(h=>!m.inputNames.includes(h));console.warn(`WARNING: Too many inputs were provided (${u} > ${d}). The following inputs will be ignored: "${a.join(", ")}".`)}return i}async function sessionRun(m,t){const i=validateInputs(m,t);try{let s=await m.run(i);return s=replaceTensors(s),s}catch(s){throw console.error(`An error occurred during model execution: "${s}".`),console.error("Inputs given to model:",i),s}}function replaceTensors(m){for(let t in m)m[t]instanceof ONNXTensor?m[t]=new Tensor(m[t]):typeof m[t]=="object"&&replaceTensors(m[t]);return m}function toI64Tensor(m){if(m instanceof Tensor)return m;if(m.length===0)throw Error("items must be non-empty");if(Array.isArray(m[0])){if(m.some(t=>t.length!==m[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' and/or 'truncation=True' to have batched tensors with the same length.");return new Tensor("int64",BigInt64Array.from(m.flat().map(t=>BigInt(t))),[m.length,m[0].length])}else return new Tensor("int64",BigInt64Array.from(m.map(t=>BigInt(t))),[1,m.length])}function prepareAttentionMask(m,t){let i=m.config.pad_token_id??null,s=m.config.eos_token_id??null;isIntegralNumber(s)&&(s=[s]);let u=t.indexOf(i)!==-1,d=s===null||!s.includes(i);if(u&&d){let a=BigInt64Array.from(t.data.map(h=>h!=i));return new Tensor("int64",a,t.dims)}else return ones_like(t)}function preparePositionIds(m,t,i){if(!m.inputNames.includes("position_ids"))return;const s=new BigInt64Array(t.attention_mask.data.length);for(let u=0;u<t.attention_mask.dims[0];++u){let d=u*t.attention_mask.dims[1],a=BigInt(0);for(let h=0;h<t.attention_mask.dims[1];++h){const f=d+h;t.attention_mask.data[f]===0n?s[f]=BigInt(1):(s[f]=a,a+=t.attention_mask.data[f])}}t.position_ids=new Tensor("int64",s,t.attention_mask.dims),i&&(t.position_ids=t.position_ids.slice(null,-1).unsqueeze_(-1))}function boolTensor(m){return new Tensor("bool",[m],[1])}async function seq2seqForward(m,t){let{encoder_outputs:i,past_key_values:s}=t;i||(i=(await encoderForward(m,t)).last_hidden_state);let u={input_ids:t.decoder_input_ids,encoder_hidden_states:i};const d=!!s;m.decoder_merged_session.inputNames.includes("use_cache_branch")&&(u.use_cache_branch=boolTensor(d)),m.decoder_merged_session.inputNames.includes("encoder_attention_mask")&&(u.encoder_attention_mask=t.attention_mask),preparePositionIds(m.decoder_merged_session,u,d),m.addPastKeyValues(u,s);const a=await sessionRun(m.decoder_merged_session,u);let h=a.logits;s=m.getPastKeyValues(a,s);const f=m.getAttentions(a);return new Seq2SeqLMOutput({logits:h,past_key_values:s,encoder_outputs:i,...f})}function seq2seqStartBeams(m,t,i,s){let u=[],d=0;const a=m.requires_attention_mask??!0;let h=i.decoder_input_ids??i.decoder_start_token_id??i.bos_token_id??i.eos_token_id;h instanceof Tensor?h=h.tolist().flat():Array.isArray(h)||(h=[h]);for(let f of t){f.dims=[1,...f.dims];let c={inputs:f,encoder_outputs:null,prev_model_outputs:null,output_token_ids:h,done:!1,score:0,id:d++};a&&(c.attention_mask=prepareAttentionMask(m,f)),u.push(c)}return u}async function seq2seqRunBeam(m,t){var a;const i=m.main_input_name;let s=t.output_token_ids;t.prev_model_outputs&&(s=s.slice(-1));let u={[i]:t.inputs,decoder_input_ids:toI64Tensor(s),encoder_outputs:t.encoder_outputs,past_key_values:(a=t.prev_model_outputs)==null?void 0:a.past_key_values};t.attention_mask&&(u.attention_mask=t.attention_mask);let d=await m.forward(u);return t.prev_model_outputs=d,t.encoder_outputs=d.encoder_outputs,d}function seq2seqUpdatebeam(m,t){m.output_token_ids=[...m.output_token_ids,t]}async function encoderForward(m,t){const i=Object.create(null);for(const s of m.session.inputNames)i[s]=t[s];return m.session.inputNames.includes("token_type_ids")&&!i.token_type_ids&&add_token_types(i),await sessionRun(m.session,i)}async function decoderForward(m,t){let{input_ids:i,past_key_values:s,attention_mask:u}=t,d={input_ids:i,attention_mask:u??prepareAttentionMask(m,i)};const a=!!s;m.session.inputNames.includes("use_cache_branch")&&(d.use_cache_branch=boolTensor(a)),preparePositionIds(m.session,d,a),m.addPastKeyValues(d,s);let h=await sessionRun(m.session,d),f=h.logits;return s=m.getPastKeyValues(h,s),{logits:f,past_key_values:s}}function decoderStartBeams(m,t,i,s,u){let d=[],a=0;for(let h of t){let f=h.tolist().map(Number);h.dims=[1,...h.dims];let c;u?(c=u[a],c.dims=[1,...c.dims]):c=prepareAttentionMask(m,h);let l={input:h,model_input_ids:h,attention_mask:c,prev_model_outputs:null,output_token_ids:f,num_output_tokens:s,done:!1,score:0,id:a++};d.push(l)}return d}async function decoderRunBeam(m,t){var d;let i=new BigInt64Array(t.output_token_ids.length).fill(1n),s={input_ids:t.model_input_ids,attention_mask:new Tensor("int64",i,[1,i.length]),past_key_values:(d=t.prev_model_outputs)==null?void 0:d.past_key_values},u=await m.forward(s);return t.prev_model_outputs=u,u}function decoderUpdatebeam(m,t){m.output_token_ids=[...m.output_token_ids,t],m.model_input_ids=new Tensor("int64",[BigInt(t)],[1,1])}class PreTrainedModel extends Callable{constructor(i,s){super();he(this,"main_input_name","input_ids");this.config=i,this.session=s;const u=MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor),d=MODEL_TYPE_MAPPING.get(u);this.can_generate=!1,this._runBeam=null,this._getStartBeams=null,this._updateBeam=null,this._forward=null,d===MODEL_TYPES.DecoderOnly?(this.can_generate=!0,this._runBeam=decoderRunBeam,this._getStartBeams=decoderStartBeams,this._updateBeam=decoderUpdatebeam,this._forward=decoderForward):d===MODEL_TYPES.Seq2Seq||d===MODEL_TYPES.Vision2Seq?(this.can_generate=!0,this._runBeam=seq2seqRunBeam,this._getStartBeams=seq2seqStartBeams,this._updateBeam=seq2seqUpdatebeam,this._forward=seq2seqForward):d===MODEL_TYPES.EncoderDecoder?this._forward=encoderForward:this._forward=encoderForward}async dispose(){let i=[];for(let s of Object.keys(this)){let u=this[s];u instanceof InferenceSession&&i.push(u.handler.dispose())}return await Promise.all(i)}static async from_pretrained(i,{quantized:s=!0,progress_callback:u=null,config:d=null,cache_dir:a=null,local_files_only:h=!1,revision:f="main",model_file_name:c=null}={}){let l={quantized:s,progress_callback:u,config:d,cache_dir:a,local_files_only:h,revision:f,model_file_name:c};const n=MODEL_CLASS_TO_NAME_MAPPING.get(this),e=MODEL_TYPE_MAPPING.get(n);let r;return e===MODEL_TYPES.DecoderOnly?r=await Promise.all([AutoConfig.from_pretrained(i,l),constructSession(i,l.model_file_name??"decoder_model_merged",l),getModelJSON(i,"generation_config.json",!1,l)]):e===MODEL_TYPES.Seq2Seq||e===MODEL_TYPES.Vision2Seq?r=await Promise.all([AutoConfig.from_pretrained(i,l),constructSession(i,"encoder_model",l),constructSession(i,"decoder_model_merged",l),getModelJSON(i,"generation_config.json",!1,l)]):e===MODEL_TYPES.EncoderDecoder?r=await Promise.all([AutoConfig.from_pretrained(i,l),constructSession(i,"encoder_model",l),constructSession(i,"decoder_model_merged",l)]):(e!==MODEL_TYPES.EncoderOnly&&console.warn(`Model type for '${n}' 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(i,l),constructSession(i,l.model_file_name??"model",l)])),new this(...r)}async _call(i){return await this.forward(i)}async forward(i){return await this._forward(this,i)}_get_logits_processor(i,s,u=null){const d=new LogitsProcessorList;if(i.repetition_penalty!==null&&i.repetition_penalty!==1&&d.push(new RepetitionPenaltyLogitsProcessor(i.repetition_penalty)),i.no_repeat_ngram_size!==null&&i.no_repeat_ngram_size>0&&d.push(new NoRepeatNGramLogitsProcessor(i.no_repeat_ngram_size)),i.bad_words_ids!==null&&d.push(new NoBadWordsLogitsProcessor(i.bad_words_ids,i.eos_token_id)),i.min_length!==null&&i.eos_token_id!==null&&i.min_length>0&&d.push(new MinLengthLogitsProcessor(i.min_length,i.eos_token_id)),i.min_new_tokens!==null&&i.eos_token_id!==null&&i.min_new_tokens>0&&d.push(new MinNewTokensLengthLogitsProcessor(s,i.min_new_tokens,i.eos_token_id)),i.forced_bos_token_id!==null&&d.push(new ForcedBOSTokenLogitsProcessor(i.forced_bos_token_id)),i.forced_eos_token_id!==null&&d.push(new ForcedEOSTokenLogitsProcessor(i.max_length,i.forced_eos_token_id)),i.begin_suppress_tokens!==null){let a=s>1||i.forced_bos_token_id===null?s:s+1;i.forced_decoder_ids!==null&&(a+=i.forced_decoder_ids[i.forced_decoder_ids.length-1][0]),d.push(new SuppressTokensAtBeginLogitsProcessor(i.begin_suppress_tokens,a))}return i.forced_decoder_ids!==null&&d.push(new ForceTokensLogitsProcessor(i.forced_decoder_ids)),u!==null&&d.extend(u),d}_get_generation_config(i){let s=new GenerationConfig(this.config);return"generation_config"in this&&Object.assign(s,this.generation_config),i!==null&&Object.assign(s,i),s}async generate(i,s=null,u=null,{inputs_attention_mask:d=null}={}){if(!this.can_generate){let _=`The current model class (${MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const b=this.config.model_type,y=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(b)??MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES.get(b)??MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES.get(b)??MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES.get(b);throw y&&(_+=` Please use the following class instead: '${y[0]}'`),Error(_)}if(!(i instanceof Tensor)&&!isTypedArray(i)&&!Array.isArray(i))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${i.constructor.name}".`);let a;if(this.config.is_encoder_decoder)a=0;else if(a=i instanceof Tensor?i.dims.at(-1):i.length,a===0)throw Error("Must supply a non-empty array of input token ids.");s=this._get_generation_config(s),u=u??new LogitsProcessorList,u=this._get_logits_processor(s,a,u);let h=s.eos_token_id;h!==null&&!Array.isArray(h)&&(h=[h]);let f=1;const c=f+(s.max_new_tokens??1/0),l=Number.isInteger(s.max_length)&&(s.max_new_tokens??null)===null;let n=Sampler.getSampler(s),e=this.getStartBeams(i,s,f,d);for(;e.some(g=>!g.done)&&f<c;){let g=[];for(let _ of e){if(_.done){g.push(_);continue}if(l&&_.output_token_ids.length>=s.max_length){_.done=!0,g.push(_);continue}let b=await this.runBeam(_);s.output_attentions&&this.addAttentionsToBeam(_,b),s.output_scores;let y=b.logits.slice(null,-1,null);u(_.output_token_ids,y);let w=n(y);for(let[T,S]of w){let A={..._};this.updateBeam(A,T),A.score+=S,h&&h.includes(T)&&(A.done=!0),g.push(A)}}++f,g=this.groupBeams(g).map(_=>_.sort((b,y)=>y.score-b.score).slice(0,s.num_beams)),e=g.flat(),s.callback_function&&s.callback_function(e)}const r=this.groupBeams(e),o=g=>r.map(_=>s.num_return_sequences>1?_.slice(0,s.num_return_sequences).map(b=>b[g]):[_[0][g]]).flat(),p=o("output_token_ids");if(s.return_dict_in_generate){const g=o("decoder_attentions"),_=o("cross_attentions");return{sequences:p,decoder_attentions:g,cross_attentions:_}}else return p}addAttentionsToBeam(i,s){if(this.config.is_encoder_decoder){if(!s.cross_attentions||s.cross_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce cross-attentions. This is most likely because the model was not exported with `output_attentions=True`.");i.cross_attentions||(i.cross_attentions=[]),i.cross_attentions.push(s.cross_attentions)}if(!s.decoder_attentions||s.decoder_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce decoder-attentions. This is most likely because the model was not exported with `output_attentions=True`.");i.decoder_attentions||(i.decoder_attentions=[]),i.decoder_attentions.push(s.decoder_attentions)}groupBeams(i){const s=Object.create(null);for(const u of i)s[u.id]===void 0?s[u.id]=[u]:s[u.id].push(u);return Object.values(s)}getPastKeyValues(i,s){const u=Object.create(null);for(const d in i)if(d.startsWith("present")){let a=d.replace("present","past_key_values");s&&d.includes("encoder")?u[a]=s[a]:u[a]=i[d]}return u}getAttentions(i){const s=Object.create(null);for(const u of["cross_attentions","decoder_attentions"]){const d=[];for(const a in i)if(a.startsWith(u)){const h=a.split(".").pop();d[h]=i[a]}s[u]=d}return s}addPastKeyValues(i,s){if(s)Object.assign(i,s);else if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??!0)){let d=[1,this.num_encoder_heads,0,this.encoder_dim_kv],a=[1,this.num_decoder_heads,0,this.decoder_dim_kv];for(let h=0;h<this.num_decoder_layers;++h)i[`past_key_values.${h}.encoder.key`]=new Tensor("float32",[],d),i[`past_key_values.${h}.encoder.value`]=new Tensor("float32",[],d),i[`past_key_values.${h}.decoder.key`]=new Tensor("float32",[],a),i[`past_key_values.${h}.decoder.value`]=new Tensor("float32",[],a)}else if(this.config.model_type==="falcon"){let d=[1*this.num_heads,0,this.dim_kv];for(let a=0;a<this.num_layers;++a)i[`past_key_values.${a}.key`]=new Tensor("float32",[],d),i[`past_key_values.${a}.value`]=new Tensor("float32",[],d)}else if(this.config.multi_query){let d=[1*this.num_heads,0,2*this.dim_kv];for(let a=0;a<this.num_layers;++a)i[`past_key_values.${a}.key_value`]=new Tensor("float32",[],d)}else if(this.config.model_type==="bloom"){let d=[1*this.num_heads,this.dim_kv,0],a=[1*this.num_heads,0,this.dim_kv];for(let h=0;h<this.num_layers;++h)i[`past_key_values.${h}.key`]=new Tensor("float32",[],d),i[`past_key_values.${h}.value`]=new Tensor("float32",[],a)}else{let d=[1,this.num_heads,0,this.dim_kv];for(let a=0;a<this.num_layers;++a)i[`past_key_values.${a}.key`]=new Tensor("float32",[],d),i[`past_key_values.${a}.value`]=new Tensor("float32",[],d)}}getStartBeams(i,s,u,d){return this._getStartBeams(this,i,s,u,d)}async runBeam(i){return await this._runBeam(this,i)}updateBeam(i,s){return this._updateBeam(i,s)}}class ModelOutput{}class BertPreTrainedModel extends PreTrainedModel{}class BertModel extends BertPreTrainedModel{}class BertForMaskedLM extends BertPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class BertForSequenceClassification extends BertPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class BertForTokenClassification extends BertPreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class BertForQuestionAnswering extends BertPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class CamembertPreTrainedModel extends PreTrainedModel{}class CamembertModel extends CamembertPreTrainedModel{}class CamembertForMaskedLM extends CamembertPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class CamembertForSequenceClassification extends CamembertPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class CamembertForTokenClassification extends CamembertPreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class CamembertForQuestionAnswering extends CamembertPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class DebertaPreTrainedModel extends PreTrainedModel{}class DebertaModel extends DebertaPreTrainedModel{}class DebertaForMaskedLM extends DebertaPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class DebertaForSequenceClassification extends DebertaPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class DebertaForTokenClassification extends DebertaPreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class DebertaForQuestionAnswering extends DebertaPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class DebertaV2PreTrainedModel extends PreTrainedModel{}class DebertaV2Model extends DebertaV2PreTrainedModel{}class DebertaV2ForMaskedLM extends DebertaV2PreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class DebertaV2ForSequenceClassification extends DebertaV2PreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class DebertaV2ForTokenClassification extends DebertaV2PreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class DebertaV2ForQuestionAnswering extends DebertaV2PreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class DistilBertPreTrainedModel extends PreTrainedModel{}class DistilBertModel extends DistilBertPreTrainedModel{}class DistilBertForSequenceClassification extends DistilBertPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class DistilBertForTokenClassification extends DistilBertPreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class DistilBertForQuestionAnswering extends DistilBertPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class DistilBertForMaskedLM extends DistilBertPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class MobileBertPreTrainedModel extends PreTrainedModel{}class MobileBertModel extends MobileBertPreTrainedModel{}class MobileBertForMaskedLM extends MobileBertPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class MobileBertForSequenceClassification extends MobileBertPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class MobileBertForQuestionAnswering extends MobileBertPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class MPNetPreTrainedModel extends PreTrainedModel{}class MPNetModel extends MPNetPreTrainedModel{}class MPNetForMaskedLM extends MPNetPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class MPNetForSequenceClassification extends MPNetPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class MPNetForTokenClassification extends MPNetPreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class MPNetForQuestionAnswering extends MPNetPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class SqueezeBertPreTrainedModel extends PreTrainedModel{}class SqueezeBertModel extends SqueezeBertPreTrainedModel{}class SqueezeBertForMaskedLM extends SqueezeBertPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class SqueezeBertForSequenceClassification extends SqueezeBertPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class SqueezeBertForQuestionAnswering extends SqueezeBertPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class AlbertPreTrainedModel extends PreTrainedModel{}class AlbertModel extends AlbertPreTrainedModel{}class AlbertForSequenceClassification extends AlbertPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class AlbertForQuestionAnswering extends AlbertPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class AlbertForMaskedLM extends AlbertPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class T5PreTrainedModel extends PreTrainedModel{}class T5Model extends T5PreTrainedModel{}class T5ForConditionalGeneration extends T5PreTrainedModel{constructor(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t){return new SequenceClassifierOutput(await super._call(t))}}class MBartPreTrainedModel extends PreTrainedModel{}class MBartModel extends MBartPreTrainedModel{}class MBartForConditionalGeneration extends MBartPreTrainedModel{constructor(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t){return new SequenceClassifierOutput(await super._call(t))}}class MBartForCausalLM extends MBartPreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,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(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t){return new MaskedLMOutput(await super._call(t))}}class RobertaForSequenceClassification extends RobertaPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class RobertaForTokenClassification extends RobertaPreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class RobertaForQuestionAnswering extends RobertaPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class XLMPreTrainedModel extends PreTrainedModel{}class XLMModel extends XLMPreTrainedModel{}class XLMWithLMHeadModel extends XLMPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class XLMForSequenceClassification extends XLMPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class XLMForTokenClassification extends XLMPreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class XLMForQuestionAnswering extends XLMPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}class XLMRobertaPreTrainedModel extends PreTrainedModel{}class XLMRobertaModel extends XLMRobertaPreTrainedModel{}class XLMRobertaForMaskedLM extends XLMRobertaPreTrainedModel{async _call(t){return new MaskedLMOutput(await super._call(t))}}class XLMRobertaForSequenceClassification extends XLMRobertaPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class XLMRobertaForTokenClassification extends XLMRobertaPreTrainedModel{async _call(t){return new TokenClassifierOutput(await super._call(t))}}class XLMRobertaForQuestionAnswering extends XLMRobertaPreTrainedModel{async _call(t){return new QuestionAnsweringModelOutput(await super._call(t))}}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(i,s,u,d){super(i,s);he(this,"requires_attention_mask",!1);he(this,"main_input_name","input_features");this.decoder_merged_session=u,this.generation_config=d,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(i,s=null,u=null){if(s=this._get_generation_config(s),s.return_timestamps??(s.return_timestamps=!1),s.return_timestamps&&(u=[new WhisperTimeStampLogitsProcessor(s)]),s.return_token_timestamps&&(s.output_attentions=!0,s.return_dict_in_generate=!0,s.task==="translate"&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),!s.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 d=await super.generate(i,s,u);return s.return_token_timestamps&&s.alignment_heads&&(d.token_timestamps=this._extract_token_timestamps(d,s.alignment_heads,s.num_frames)),d}_extract_token_timestamps(i,s,u=null,d=.02){if(!i.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 a=this.config.median_filter_width;a===void 0&&(console.warn("Model config has no `median_filter_width`, using default value of 7."),a=7);const h=i.cross_attentions.map(l=>{let n=Array.from({length:this.config.decoder_layers},(_,b)=>cat(l.map(y=>y[b]),2)),e=stack(s.map(([_,b])=>u?n[_].slice(null,b,null,[0,u]):n[_].slice(null,b)));e=e.transpose(1,0,2,3);let[r,o]=std_mean(e,-2,0,!0),p=e.clone();for(let _=0;_<p.dims[0];++_){let b=p[_];for(let y=0;y<b.dims[0];++y){let w=b[y];const T=r[_][y][0],S=o[_][y][0];for(let A=0;A<w.dims[0];++A){let P=w[A];for(let x=0;x<P.data.length;++x)P.data[x]=(P.data[x]-S.data[x])/T.data[x];P.data.set(medianFilter(P.data,a))}}}return mean(p,1)}),f=[i.sequences.length,i.sequences[0].length],c=new Tensor("float32",new Float32Array(f[0]*f[1]),f);for(let l=0;l<f[0];++l){const n=h[l].neg().squeeze_(0);let[e,r]=dynamicTimeWarping(n),o=Array.from({length:e.length-1},(_,b)=>e[b+1]-e[b]),p=mergeArrays([1],o).map(_=>!!_),g=[];for(let _=0;_<p.length;++_)p[_]&&g.push(r[_]*d);c[l].data.set(g,1)}return c}}class VisionEncoderDecoderModel extends PreTrainedModel{constructor(i,s,u,d){super(i,s);he(this,"main_input_name","pixel_values");this.decoder_merged_session=u,this.generation_config=d;const a=this.config.encoder,h=this.config.decoder,f=a.model_type;(MODEL_MAPPING_NAMES_ENCODER_ONLY.get(f)??MODEL_MAPPING_NAMES_ENCODER_DECODER.get(f))||console.warn(`Model type for encoder '${f}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`);const l=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(h.model_type);if(!l)throw new Error(`Unable to construct \`VisionEncoderDecoder\` due to unsupported decoder: "${this.config.decoder.model_type}"`);const n=l[1],e=new n(h,u,d);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(t,i={}){return i.model_file_name??(i.model_file_name="text_model"),super.from_pretrained(t,i)}}class CLIPVisionModelWithProjection extends CLIPPreTrainedModel{static async from_pretrained(t,i={}){return i.model_file_name??(i.model_file_name="vision_model"),super.from_pretrained(t,i)}}class GPT2PreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.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(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_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(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class GPTNeoXModel extends GPTNeoXPreTrainedModel{}class GPTNeoXForCausalLM extends GPTNeoXPreTrainedModel{}class GPTJPreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.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(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.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(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.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(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.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 BloomPreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.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(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.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(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class OPTModel extends OPTPreTrainedModel{}class OPTForCausalLM extends OPTPreTrainedModel{}class ViTPreTrainedModel extends PreTrainedModel{}class ViTModel extends ViTPreTrainedModel{}class ViTForImageClassification extends ViTPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class MobileViTPreTrainedModel extends PreTrainedModel{}class MobileViTModel extends MobileViTPreTrainedModel{}class MobileViTForImageClassification extends MobileViTPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class OwlViTPreTrainedModel extends PreTrainedModel{}class OwlViTModel extends OwlViTPreTrainedModel{}class OwlViTForObjectDetection extends OwlViTPreTrainedModel{}class BeitPreTrainedModel extends PreTrainedModel{}class BeitModel extends BeitPreTrainedModel{}class BeitForImageClassification extends BeitPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class DetrPreTrainedModel extends PreTrainedModel{}class DetrModel extends DetrPreTrainedModel{}class DetrForObjectDetection extends DetrPreTrainedModel{async _call(t){return new DetrObjectDetectionOutput(await super._call(t))}}class DetrForSegmentation extends DetrPreTrainedModel{async _call(t){return new DetrSegmentationOutput(await super._call(t))}}class DetrObjectDetectionOutput extends ModelOutput{constructor({logits:t,pred_boxes:i}){super(),this.logits=t,this.pred_boxes=i}}class DetrSegmentationOutput extends ModelOutput{constructor({logits:t,pred_boxes:i,pred_masks:s}){super(),this.logits=t,this.pred_boxes=i,this.pred_masks=s}}class DeiTPreTrainedModel extends PreTrainedModel{}class DeiTModel extends DeiTPreTrainedModel{}class DeiTForImageClassification extends DeiTPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class ResNetPreTrainedModel extends PreTrainedModel{}class ResNetModel extends ResNetPreTrainedModel{}class ResNetForImageClassification extends ResNetPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class SwinPreTrainedModel extends PreTrainedModel{}class SwinModel extends SwinPreTrainedModel{}class SwinForImageClassification extends SwinPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}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 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(t){return new SequenceClassifierOutput(await super._call(t))}}class ConvNextV2PreTrainedModel extends PreTrainedModel{}class ConvNextV2Model extends ConvNextV2PreTrainedModel{}class ConvNextV2ForImageClassification extends ConvNextV2PreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class YolosPreTrainedModel extends PreTrainedModel{}class YolosModel extends YolosPreTrainedModel{}class YolosForObjectDetection extends YolosPreTrainedModel{async _call(t){return new YolosObjectDetectionOutput(await super._call(t))}}class YolosObjectDetectionOutput extends ModelOutput{constructor({logits:t,pred_boxes:i}){super(),this.logits=t,this.pred_boxes=i}}class SamPreTrainedModel extends PreTrainedModel{}class SamModel extends SamPreTrainedModel{async _call(t){return new SamImageSegmentationOutput(await super._call(t))}}class SamImageSegmentationOutput extends ModelOutput{constructor({iou_scores:t,pred_masks:i}){super(),this.iou_scores=t,this.pred_masks=i}}class MarianPreTrainedModel extends PreTrainedModel{}class MarianModel extends MarianPreTrainedModel{}class MarianMTModel extends MarianPreTrainedModel{constructor(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t){return new CausalLMOutput(await super._call(t))}}class Wav2Vec2ForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class WavLMPreTrainedModel extends PreTrainedModel{}class WavLMModel extends WavLMPreTrainedModel{}class WavLMForCTC extends WavLMPreTrainedModel{async _call(t){return new CausalLMOutput(await super._call(t))}}class WavLMForSequenceClassification extends WavLMPreTrainedModel{async _call(t){return new SequenceClassifierOutput(await super._call(t))}}class SpeechT5PreTrainedModel extends PreTrainedModel{}class SpeechT5ForSpeechToText extends SpeechT5PreTrainedModel{}class SpeechT5ForTextToSpeech extends SpeechT5PreTrainedModel{constructor(t,i,s,u){super(t,i),this.decoder_merged_session=s,this.generation_config=u,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(t,i,{threshold:s=.5,minlenratio:u=0,maxlenratio:d=20,vocoder:a=null}={}){const h={input_ids:t},{encoder_outputs:f,encoder_attention_mask:c}=await encoderForward(this,h),l=f.dims[1]/this.config.reduction_factor,n=Math.floor(l*d),e=Math.floor(l*u),r=this.config.num_mel_bins;let o=[],p=null,g=null,_=0;for(;;){++_;const w=boolTensor(!!g);let T;g?T=g.output_sequence_out:T=new Tensor("float32",new Float32Array(r),[1,1,r]);let S={use_cache_branch:w,output_sequence:T,encoder_attention_mask:c,speaker_embeddings:i,encoder_hidden_states:f};this.addPastKeyValues(S,p),g=await sessionRun(this.decoder_merged_session,S),p=this.getPastKeyValues(g,p);const{prob:A,spectrum:P}=g;if(o.push(P),_>=e&&(Array.from(A.data).filter(x=>x>=s).length>0||_>=n))break}const b=cat(o),{waveform:y}=await sessionRun(a.session,{spectrogram:b});return{spectrogram:b,waveform:y}}}class SpeechT5HifiGan extends PreTrainedModel{constructor(){super(...arguments);he(this,"main_input_name","spectrogram")}}class TrOCRPreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_encoder_layers=this.num_decoder_layers=this.config.decoder_layers,this.num_encoder_heads=this.num_decoder_heads=this.config.decoder_attention_heads,this.encoder_dim_kv=this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads}}class TrOCRForCausalLM extends TrOCRPreTrainedModel{}class MistralPreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class MistralModel extends MistralPreTrainedModel{}class MistralForCausalLM extends MistralPreTrainedModel{}class FalconPreTrainedModel extends PreTrainedModel{constructor(t,i,s){super(t,i),this.generation_config=s,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class FalconModel extends FalconPreTrainedModel{}class FalconForCausalLM extends FalconPreTrainedModel{}class ClapPreTrainedModel extends PreTrainedModel{}class ClapModel extends ClapPreTrainedModel{}class ClapTextModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(t,i={}){return i.model_file_name??(i.model_file_name="text_model"),super.from_pretrained(t,i)}}class ClapAudioModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(t,i={}){return i.model_file_name??(i.model_file_name="audio_model"),super.from_pretrained(t,i)}}class PretrainedMixin{static async from_pretrained(t,{quantized:i=!0,progress_callback:s=null,config:u=null,cache_dir:d=null,local_files_only:a=!1,revision:h="main",model_file_name:f=null}={}){let c={quantized:i,progress_callback:s,config:u,cache_dir:d,local_files_only:a,revision:h,model_file_name:f};if(u=await AutoConfig.from_pretrained(t,c),c.config||(c.config=u),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let l of this.MODEL_CLASS_MAPPINGS){const n=l.get(u.model_type);if(n)return await n[1].from_pretrained(t,c)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${u.model_type}", attempting to construct from base class.`),await PreTrainedModel.from_pretrained(t,c);throw Error(`Unsupported model type: ${u.model_type}`)}}he(PretrainedMixin,"MODEL_CLASS_MAPPINGS",null),he(PretrainedMixin,"BASE_IF_FAIL",!1);const MODEL_MAPPING_NAMES_ENCODER_ONLY=new Map([["bert",["BertModel",BertModel]],["camembert",["CamembertModel",CamembertModel]],["deberta",["DebertaModel",DebertaModel]],["deberta-v2",["DebertaV2Model",DebertaV2Model]],["mpnet",["MPNetModel",MPNetModel]],["albert",["AlbertModel",AlbertModel]],["distilbert",["DistilBertModel",DistilBertModel]],["roberta",["RobertaModel",RobertaModel]],["xlm",["XLMModel",XLMModel]],["xlm-roberta",["XLMRobertaModel",XLMRobertaModel]],["clap",["ClapModel",ClapModel]],["clip",["CLIPModel",CLIPModel]],["mobilebert",["MobileBertModel",MobileBertModel]],["squeezebert",["SqueezeBertModel",SqueezeBertModel]],["wav2vec2",["Wav2Vec2Model",Wav2Vec2Model]],["wavlm",["WavLMModel",WavLMModel]],["audio-spectrogram-transformer",["ASTModel",ASTModel]],["detr",["DetrModel",DetrModel]],["vit",["ViTModel",ViTModel]],["mobilevit",["MobileViTModel",MobileViTModel]],["owlvit",["OwlViTModel",OwlViTModel]],["beit",["BeitModel",BeitModel]],["deit",["DeiTModel",DeiTModel]],["convnext",["ConvNextModel",ConvNextModel]],["convnextv2",["ConvNextV2Model",ConvNextV2Model]],["resnet",["ResNetModel",ResNetModel]],["swin",["SwinModel",SwinModel]],["swin2sr",["Swin2SRModel",Swin2SRModel]],["donut-swin",["DonutSwinModel",DonutSwinModel]],["yolos",["YolosModel",YolosModel]],["dpt",["DPTModel",DPTModel]],["glpn",["GLPNModel",GLPNModel]],["hifigan",["SpeechT5HifiGan",SpeechT5HifiGan]],["sam",["SamModel",SamModel]]]),MODEL_MAPPING_NAMES_ENCODER_DECODER=new Map([["t5",["T5Model",T5Model]],["longt5",["LongT5Model",LongT5Model]],["mt5",["MT5Model",MT5Model]],["bart",["BartModel",BartModel]],["mbart",["MBartModel",MBartModel]],["marian",["MarianModel",MarianModel]],["whisper",["WhisperModel",WhisperModel]],["m2m_100",["M2M100Model",M2M100Model]],["blenderbot",["BlenderbotModel",BlenderbotModel]],["blenderbot-small",["BlenderbotSmallModel",BlenderbotSmallModel]]]),MODEL_MAPPING_NAMES_DECODER_ONLY=new Map([["bloom",["BloomModel",BloomModel]],["gpt2",["GPT2Model",GPT2Model]],["gptj",["GPTJModel",GPTJModel]],["gpt_bigcode",["GPTBigCodeModel",GPTBigCodeModel]],["gpt_neo",["GPTNeoModel",GPTNeoModel]],["gpt_neox",["GPTNeoXModel",GPTNeoXModel]],["codegen",["CodeGenModel",CodeGenModel]],["llama",["LlamaModel",LlamaModel]],["mpt",["MptModel",MptModel]],["opt",["OPTModel",OPTModel]],["mistral",["MistralModel",MistralModel]],["falcon",["FalconModel",FalconModel]]]),MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForSpeechToText",SpeechT5ForSpeechToText]],["whisper",["WhisperForConditionalGeneration",WhisperForConditionalGeneration]]]),MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForTextToSpeech",SpeechT5ForTextToSpeech]]]),MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForSequenceClassification",BertForSequenceClassification]],["camembert",["CamembertForSequenceClassification",CamembertForSequenceClassification]],["deberta",["DebertaForSequenceClassification",DebertaForSequenceClassification]],["deberta-v2",["DebertaV2ForSequenceClassification",DebertaV2ForSequenceClassification]],["mpnet",["MPNetForSequenceClassification",MPNetForSequenceClassification]],["albert",["AlbertForSequenceClassification",AlbertForSequenceClassification]],["distilbert",["DistilBertForSequenceClassification",DistilBertForSequenceClassification]],["roberta",["RobertaForSequenceClassification",RobertaForSequenceClassification]],["xlm",["XLMForSequenceClassification",XLMForSequenceClassification]],["xlm-roberta",["XLMRobertaForSequenceClassification",XLMRobertaForSequenceClassification]],["bart",["BartForSequenceClassification",BartForSequenceClassification]],["mbart",["MBartForSequenceClassification",MBartForSequenceClassification]],["mobilebert",["MobileBertForSequenceClassification",MobileBertForSequenceClassification]],["squeezebert",["SqueezeBertForSequenceClassification",SqueezeBertForSequenceClassification]]]),MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForTokenClassification",BertForTokenClassification]],["camembert",["CamembertForTokenClassification",CamembertForTokenClassification]],["deberta",["DebertaForTokenClassification",DebertaForTokenClassification]],["deberta-v2",["DebertaV2ForTokenClassification",DebertaV2ForTokenClassification]],["mpnet",["MPNetForTokenClassification",MPNetForTokenClassification]],["distilbert",["DistilBertForTokenClassification",DistilBertForTokenClassification]],["roberta",["RobertaForTokenClassification",RobertaForTokenClassification]],["xlm",["XLMForTokenClassification",XLMForTokenClassification]],["xlm-roberta",["XLMRobertaForTokenClassification",XLMRobertaForTokenClassification]]]),MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES=new Map([["t5",["T5ForConditionalGeneration",T5ForConditionalGeneration]],["longt5",["LongT5ForConditionalGeneration",LongT5ForConditionalGeneration]],["mt5",["MT5ForConditionalGeneration",MT5ForConditionalGeneration]],["bart",["BartForConditionalGeneration",BartForConditionalGeneration]],["mbart",["MBartForConditionalGeneration",MBartForConditionalGeneration]],["marian",["MarianMTModel",MarianMTModel]],["m2m_100",["M2M100ForConditionalGeneration",M2M100ForConditionalGeneration]],["blenderbot",["BlenderbotForConditionalGeneration",BlenderbotForConditionalGeneration]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",BlenderbotSmallForConditionalGeneration]]]),MODEL_WITH_LM_HEAD_MAPPING_NAMES=new Map([["bloom",["BloomForCausalLM",BloomForCausalLM]],["gpt2",["GPT2LMHeadModel",GPT2LMHeadModel]],["gptj",["GPTJForCausalLM",GPTJForCausalLM]],["gpt_bigcode",["GPTBigCodeForCausalLM",GPTBigCodeForCausalLM]],["gpt_neo",["GPTNeoForCausalLM",GPTNeoForCausalLM]],["gpt_neox",["GPTNeoXForCausalLM",GPTNeoXForCausalLM]],["codegen",["CodeGenForCausalLM",CodeGenForCausalLM]],["llama",["LlamaForCausalLM",LlamaForCausalLM]],["mpt",["MptForCausalLM",MptForCausalLM]],["opt",["OPTForCausalLM",OPTForCausalLM]],["mbart",["MBartForCausalLM",MBartForCausalLM]],["mistral",["MistralForCausalLM",MistralForCausalLM]],["falcon",["FalconForCausalLM",FalconForCausalLM]],["trocr",["TrOCRForCausalLM",TrOCRForCausalLM]]]),MODEL_FOR_MASKED_LM_MAPPING_NAMES=new Map([["bert",["BertForMaskedLM",BertForMaskedLM]],["camembert",["CamembertForMaskedLM",CamembertForMaskedLM]],["deberta",["DebertaForMaskedLM",DebertaForMaskedLM]],["deberta-v2",["DebertaV2ForMaskedLM",DebertaV2ForMaskedLM]],["mpnet",["MPNetForMaskedLM",MPNetForMaskedLM]],["albert",["AlbertForMaskedLM",AlbertForMaskedLM]],["distilbert",["DistilBertForMaskedLM",DistilBertForMaskedLM]],["roberta",["RobertaForMaskedLM",RobertaForMaskedLM]],["xlm",["XLMWithLMHeadModel",XLMWithLMHeadModel]],["xlm-roberta",["XLMRobertaForMaskedLM",XLMRobertaForMaskedLM]],["mobilebert",["MobileBertForMaskedLM",MobileBertForMaskedLM]],["squeezebert",["SqueezeBertForMaskedLM",SqueezeBertForMaskedLM]]]),MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES=new Map([["bert",["BertForQuestionAnswering",BertForQuestionAnswering]],["camembert",["CamembertForQuestionAnswering",CamembertForQuestionAnswering]],["deberta",["DebertaForQuestionAnswering",DebertaForQuestionAnswering]],["deberta-v2",["DebertaV2ForQuestionAnswering",DebertaV2ForQuestionAnswering]],["mpnet",["MPNetForQuestionAnswering",MPNetForQuestionAnswering]],["albert",["AlbertForQuestionAnswering",AlbertForQuestionAnswering]],["distilbert",["DistilBertForQuestionAnswering",DistilBertForQuestionAnswering]],["roberta",["RobertaForQuestionAnswering",RobertaForQuestionAnswering]],["xlm",["XLMForQuestionAnswering",XLMForQuestionAnswering]],["xlm-roberta",["XLMRobertaForQuestionAnswering",XLMRobertaForQuestionAnswering]],["mobilebert",["MobileBertForQuestionAnswering",MobileBertForQuestionAnswering]],["squeezebert",["SqueezeBertForQuestionAnswering",SqueezeBertForQuestionAnswering]]]),MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",VisionEncoderDecoderModel]]]),MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",VisionEncoderDecoderModel]]]),MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES=new Map([["vit",["ViTForImageClassification",ViTForImageClassification]],["mobilevit",["MobileViTForImageClassification",MobileViTForImageClassification]],["beit",["BeitForImageClassification",BeitForImageClassification]],["deit",["DeiTForImageClassification",DeiTForImageClassification]],["convnext",["ConvNextForImageClassification",ConvNextForImageClassification]],["convnextv2",["ConvNextV2ForImageClassification",ConvNextV2ForImageClassification]],["resnet",["ResNetForImageClassification",ResNetForImageClassification]],["swin",["SwinForImageClassification",SwinForImageClassification]]]),MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES=new Map([["detr",["DetrForObjectDetection",DetrForObjectDetection]],["yolos",["YolosForObjectDetection",YolosForObjectDetection]]]),MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES=new Map([["owlvit",["OwlViTForObjectDetection",OwlViTForObjectDetection]]]),MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES=new Map([["detr",["DetrForSegmentation",DetrForSegmentation]]]),MODEL_FOR_MASK_GENERATION_MAPPING_NAMES=new Map([["sam",["SamModel",SamModel]]]),MODEL_FOR_CTC_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForCTC",Wav2Vec2ForCTC]],["wavlm",["WavLMForCTC",WavLMForCTC]]]),MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Wav2Vec2ForSequenceClassification]],["wavlm",["WavLMForSequenceClassification",WavLMForSequenceClassification]],["audio-spectrogram-transformer",["ASTForAudioClassification",ASTForAudioClassification]]]),MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES=new Map([["swin2sr",["Swin2SRForImageSuperResolution",Swin2SRForImageSuperResolution]]]),MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES=new Map([["dpt",["DPTForDepthEstimation",DPTForDepthEstimation]],["glpn",["GLPNForDepthEstimation",GLPNForDepthEstimation]]]),MODEL_CLASS_TYPE_MAPPING=[[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_TYPES.EncoderOnly],[MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_TYPES.EncoderDecoder],[MODEL_MAPPING_NAMES_DECODER_ONLY,MODEL_TYPES.DecoderOnly],[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_WITH_LM_HEAD_MAPPING_NAMES,MODEL_TYPES.DecoderOnly],[MODEL_FOR_MASKED_LM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Vision2Seq],[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_MASK_GENERATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_CTC_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq]];for(const[m,t]of MODEL_CLASS_TYPE_MAPPING)for(const[i,s]of m.values())MODEL_TYPE_MAPPING.set(i,t),MODEL_CLASS_TO_NAME_MAPPING.set(s,i),MODEL_NAME_TO_CLASS_MAPPING.set(i,s);const CUSTOM_MAPPING=[["CLIPTextModelWithProjection",CLIPTextModelWithProjection,MODEL_TYPES.EncoderOnly],["CLIPVisionModelWithProjection",CLIPVisionModelWithProjection,MODEL_TYPES.EncoderOnly],["ClapTextModelWithProjection",ClapTextModelWithProjection,MODEL_TYPES.EncoderOnly],["ClapAudioModelWithProjection",ClapAudioModelWithProjection,MODEL_TYPES.EncoderOnly]];for(const[m,t,i]of CUSTOM_MAPPING)MODEL_TYPE_MAPPING.set(m,i),MODEL_CLASS_TO_NAME_MAPPING.set(t,m),MODEL_NAME_TO_CLASS_MAPPING.set(m,t);class AutoModel extends PretrainedMixin{}he(AutoModel,"MODEL_CLASS_MAPPINGS",[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_MAPPING_NAMES_DECODER_ONLY]),he(AutoModel,"BASE_IF_FAIL",!0);class AutoModelForSequenceClassification extends PretrainedMixin{}he(AutoModelForSequenceClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForTokenClassification extends PretrainedMixin{}he(AutoModelForTokenClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForSeq2SeqLM extends PretrainedMixin{}he(AutoModelForSeq2SeqLM,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES]);class AutoModelForSpeechSeq2Seq extends PretrainedMixin{}he(AutoModelForSpeechSeq2Seq,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES]);class AutoModelForTextToSpectrogram extends PretrainedMixin{}he(AutoModelForTextToSpectrogram,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES]);class AutoModelForCausalLM extends PretrainedMixin{}he(AutoModelForCausalLM,"MODEL_CLASS_MAPPINGS",[MODEL_WITH_LM_HEAD_MAPPING_NAMES]);class AutoModelForMaskedLM extends PretrainedMixin{}he(AutoModelForMaskedLM,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_MASKED_LM_MAPPING_NAMES]);class AutoModelForQuestionAnswering extends PretrainedMixin{}he(AutoModelForQuestionAnswering,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES]);class AutoModelForVision2Seq extends PretrainedMixin{}he(AutoModelForVision2Seq,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES]);class AutoModelForImageClassification extends PretrainedMixin{}he(AutoModelForImageClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForImageSegmentation extends PretrainedMixin{}he(AutoModelForImageSegmentation,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES]);class AutoModelForObjectDetection extends PretrainedMixin{}he(AutoModelForObjectDetection,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES]);class AutoModelForZeroShotObjectDetection extends PretrainedMixin{}he(AutoModelForZeroShotObjectDetection,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES]);class AutoModelForCTC extends PretrainedMixin{}he(AutoModelForCTC,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_CTC_MAPPING_NAMES]);class AutoModelForAudioClassification extends PretrainedMixin{}he(AutoModelForAudioClassification,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES]);class AutoModelForDocumentQuestionAnswering extends PretrainedMixin{}he(AutoModelForDocumentQuestionAnswering,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES]);class AutoModelForImageToImage extends PretrainedMixin{}he(AutoModelForImageToImage,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES]);class AutoModelForDepthEstimation extends PretrainedMixin{}he(AutoModelForDepthEstimation,"MODEL_CLASS_MAPPINGS",[MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES]);class Seq2SeqLMOutput extends ModelOutput{constructor({logits:t,past_key_values:i,encoder_outputs:s,decoder_attentions:u=null,cross_attentions:d=null}){super(),this.logits=t,this.past_key_values=i,this.encoder_outputs=s,this.decoder_attentions=u,this.cross_attentions=d}}class SequenceClassifierOutput extends ModelOutput{constructor({logits:t}){super(),this.logits=t}}class TokenClassifierOutput extends ModelOutput{constructor({logits:t}){super(),this.logits=t}}class MaskedLMOutput extends ModelOutput{constructor({logits:t}){super(),this.logits=t}}class QuestionAnsweringModelOutput extends ModelOutput{constructor({start_logits:t,end_logits:i}){super(),this.start_logits=t,this.end_logits=i}}class CausalLMOutput extends ModelOutput{constructor({logits:t}){super(),this.logits=t}}const BROWSER_ENV=typeof self<"u",WEBWORKER_ENV=BROWSER_ENV&&self.constructor.name==="DedicatedWorkerGlobalScope";let createCanvasFunction,ImageDataClass,loadImageFunction;if(BROWSER_ENV)createCanvasFunction=(m,t)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this browser.");return new self.OffscreenCanvas(m,t)},loadImageFunction=self.createImageBitmap,ImageDataClass=self.ImageData;else if(sharp)loadImageFunction=async m=>{const i=(await m.metadata()).channels;let{data:s,info:u}=await m.raw().toBuffer({resolveWithObject:!0});const d=new RawImage(new Uint8ClampedArray(s),u.width,u.height,u.channels);return i!==void 0&&i!==u.channels&&d.convert(i),d};else throw new Error("Unable to load image processing library.");const RESAMPLING_MAPPING={0:"nearest",1:"lanczos",2:"bilinear",3:"bicubic",4:"box",5:"hamming"},CONTENT_TYPE_MAP=new Map([["png","image/png"],["jpg","image/jpeg"],["jpeg","image/jpeg"],["gif","image/gif"]]);class RawImage{constructor(t,i,s,u){this.data=t,this.width=i,this.height=s,this.channels=u}get size(){return[this.width,this.height]}static async read(t){if(t instanceof RawImage)return t;if(isString(t)||t instanceof URL)return await this.fromURL(t);throw new Error(`Unsupported input type: ${typeof t}`)}static async fromURL(t){let i=await getFile(t);if(i.status!==200)throw new Error(`Unable to read image from "${t}" (${i.status} ${i.statusText})`);let s=await i.blob();return this.fromBlob(s)}static async fromBlob(t){if(BROWSER_ENV){let i=await loadImageFunction(t);const s=createCanvasFunction(i.width,i.height).getContext("2d");return s.drawImage(i,0,0),new this(s.getImageData(0,0,i.width,i.height).data,i.width,i.height,4)}else{let i=sharp(await t.arrayBuffer());return await loadImageFunction(i)}}static fromTensor(t,i="CHW"){if(i==="CHW")t=t.transpose(1,2,0);else if(i!=="HWC")throw new Error(`Unsupported channel format: ${i}`);return new RawImage(t.data,t.dims[1],t.dims[0],t.dims[2])}grayscale(){if(this.channels===1)return this;let t=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let i=0,s=0;i<this.data.length;i+=this.channels){const u=this.data[i],d=this.data[i+1],a=this.data[i+2];t[s++]=Math.round(.2989*u+.587*d+.114*a)}break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,1)}rgb(){if(this.channels===3)return this;let t=new Uint8ClampedArray(this.width*this.height*3);switch(this.channels){case 1:for(let i=0,s=0;i<this.data.length;++i)t[s++]=this.data[i],t[s++]=this.data[i],t[s++]=this.data[i];break;case 4:for(let i=0,s=0;i<this.data.length;i+=4)t[s++]=this.data[i],t[s++]=this.data[i+1],t[s++]=this.data[i+2];break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,3)}rgba(){if(this.channels===4)return this;let t=new Uint8ClampedArray(this.width*this.height*4);switch(this.channels){case 1:for(let i=0,s=0;i<this.data.length;++i)t[s++]=this.data[i],t[s++]=this.data[i],t[s++]=this.data[i],t[s++]=255;break;case 3:for(let i=0,s=0;i<this.data.length;i+=3)t[s++]=this.data[i],t[s++]=this.data[i+1],t[s++]=this.data[i+2],t[s++]=255;break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,4)}async resize(t,i,{resample:s=2}={}){let u=RESAMPLING_MAPPING[s]??s;if(BROWSER_ENV){let d=this.channels,a=this.toCanvas();const h=createCanvasFunction(t,i).getContext("2d");return h.drawImage(a,0,0,t,i),new RawImage(h.getImageData(0,0,t,i).data,t,i,4).convert(d)}else{let d=this.toSharp();switch(u){case"box":case"hamming":(u==="box"||u==="hamming")&&(console.warn(`Resampling method ${u} is not yet supported. Using bilinear instead.`),u="bilinear");case"nearest":case"bilinear":case"bicubic":d=d.affine([t/this.width,0,0,i/this.height],{interpolator:u});break;case"lanczos":d=d.resize({width:t,height:i,fit:"fill",kernel:"lanczos3"});break;default:throw new Error(`Resampling method ${u} is not supported.`)}return await loadImageFunction(d)}}async pad([t,i,s,u]){if(t=Math.max(t,0),i=Math.max(i,0),s=Math.max(s,0),u=Math.max(u,0),t===0&&i===0&&s===0&&u===0)return this;if(BROWSER_ENV){let d=this.channels,a=this.toCanvas(),h=this.width+t+i,f=this.height+s+u;const c=createCanvasFunction(h,f).getContext("2d");return c.drawImage(a,0,0,this.width,this.height,t,s,h,f),new RawImage(c.getImageData(0,0,h,f).data,h,f,4).convert(d)}else{let d=this.toSharp().extend({left:t,right:i,top:s,bottom:u});return await loadImageFunction(d)}}async crop([t,i,s,u]){if(t=Math.max(t,0),i=Math.max(i,0),s=Math.min(s,this.width-1),u=Math.min(u,this.height-1),t===0&&i===0&&s===this.width-1&&u===this.height-1)return this;const d=s-t+1,a=u-i+1;if(BROWSER_ENV){const h=this.channels,f=this.toCanvas(),c=createCanvasFunction(d,a).getContext("2d");return c.drawImage(f,t,i,d,a,0,0,d,a),new RawImage(c.getImageData(0,0,d,a).data,d,a,4).convert(h)}else{const h=this.toSharp().extract({left:t,top:i,width:d,height:a});return await loadImageFunction(h)}}async center_crop(t,i){if(this.width===t&&this.height===i)return this;let s=(this.width-t)/2,u=(this.height-i)/2;if(BROWSER_ENV){let d=this.channels,a=this.toCanvas();const h=createCanvasFunction(t,i).getContext("2d");let f=0,c=0,l=0,n=0;return s>=0?f=s:l=-s,u>=0?c=u:n=-u,h.drawImage(a,f,c,t,i,l,n,t,i),new RawImage(h.getImageData(0,0,t,i).data,t,i,4).convert(d)}else{let d=this.toSharp();if(s>=0&&u>=0)d=d.extract({left:Math.floor(s),top:Math.floor(u),width:t,height:i});else if(s<=0&&u<=0){let a=Math.floor(-u),h=Math.floor(-s);d=d.extend({top:a,left:h,right:t-this.width-h,bottom:i-this.height-a})}else{let a=[0,0],h=0;u<0?(a[0]=Math.floor(-u),a[1]=i-this.height-a[0]):h=Math.floor(u);let f=[0,0],c=0;s<0?(f[0]=Math.floor(-s),f[1]=t-this.width-f[0]):c=Math.floor(s),d=d.extend({top:a[0],bottom:a[1],left:f[0],right:f[1]}).extract({left:c,top:h,width:t,height:i})}return await loadImageFunction(d)}}async toBlob(t="image/png",i=1){if(!BROWSER_ENV)throw new Error("toBlob() is only supported in browser environments.");return await this.toCanvas().convertToBlob({type:t,quality:i})}toCanvas(){if(!BROWSER_ENV)throw new Error("toCanvas() is only supported in browser environments.");let t=this.clone().rgba(),i=createCanvasFunction(t.width,t.height),s=new ImageDataClass(t.data,t.width,t.height);return i.getContext("2d").putImageData(s,0,0),i}_update(t,i,s,u=null){return this.data=t,this.width=i,this.height=s,u!==null&&(this.channels=u),this}clone(){return new RawImage(this.data.slice(),this.width,this.height,this.channels)}convert(t){if(this.channels===t)return this;switch(t){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(t){if(BROWSER_ENV){if(WEBWORKER_ENV)throw new Error("Unable to save an image from a Web Worker.");const i=t.split(".").pop().toLowerCase(),s=CONTENT_TYPE_MAP.get(i)??"image/png",u=await this.toBlob(s),d=URL.createObjectURL(u),a=document.createElement("a");a.href=d,a.download=t,a.click(),a.remove()}else{if(env$1.useFS)return await this.toSharp().toFile(t);throw new Error("Unable to save the image because filesystem is disabled in this environment.")}}toSharp(){if(BROWSER_ENV)throw new Error("toSharp() is only supported in server-side environments.");return sharp(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}}async function read_audio(m,t){if(typeof AudioContext>"u")throw Error("Unable to load audio from path/URL since `AudioContext` is not available in your environment. Instead, audio data should be passed directly to the pipeline/processor. For more information and some example code, see https://huggingface.co/docs/transformers.js/guides/node-audio-processing.");const i=await(await getFile(m)).arrayBuffer(),s=new AudioContext({sampleRate:t});typeof t>"u"&&console.warn(`No sampling rate provided, using default of ${s.sampleRate}Hz.`);const u=await s.decodeAudioData(i);let d;if(u.numberOfChannels===2){const a=Math.sqrt(2),h=u.getChannelData(0),f=u.getChannelData(1);d=new Float32Array(h.length);for(let c=0;c<u.length;++c)d[c]=a*(h[c]+f[c])/2}else d=u.getChannelData(0);return d}function hanning(m){if(m<1)return new Float64Array;if(m===1)return new Float64Array([1]);const t=m-1,i=Math.PI/t,s=new Float64Array(m);for(let u=0;u<m;++u){const d=2*u-t;s[u]=.5+.5*Math.cos(i*d)}return s}const HERTZ_TO_MEL_MAPPING={htk:m=>2595*Math.log10(1+m/700),kaldi:m=>1127*Math.log(1+m/700),slaney:(m,t=1e3,i=15,s=27/Math.log(6.4))=>m>=t?i+Math.log(m/t)*s:3*m/200};function hertz_to_mel(m,t="htk"){const i=HERTZ_TO_MEL_MAPPING[t];if(!i)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return typeof m=="number"?i(m):m.map(s=>i(s))}const MEL_TO_HERTZ_MAPPING={htk:m=>700*(10**(m/2595)-1),kaldi:m=>700*(Math.exp(m/1127)-1),slaney:(m,t=1e3,i=15,s=Math.log(6.4)/27)=>m>=i?t*Math.exp(s*(m-i)):200*m/3};function mel_to_hertz(m,t="htk"){const i=MEL_TO_HERTZ_MAPPING[t];if(!i)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return typeof m=="number"?i(m):m.map(s=>i(s))}function _create_triangular_filter_bank(m,t){const i=Float64Array.from({length:t.length-1},(a,h)=>t[h+1]-t[h]),s=Array.from({length:m.length},()=>new Array(t.length));for(let a=0;a<m.length;++a){const h=s[a];for(let f=0;f<t.length;++f)h[f]=t[f]-m[a]}const u=t.length-2,d=Array.from({length:u},()=>new Array(m.length));for(let a=0;a<m.length;++a){const h=s[a];for(let f=0;f<u;++f){const c=-h[f]/i[f],l=h[f+2]/i[f+1];d[f][a]=Math.max(0,Math.min(c,l))}}return d}function linspace(m,t,i){const s=(t-m)/(i-1);return Float64Array.from({length:i},(u,d)=>m+s*d)}function mel_filter_bank(m,t,i,s,u,d=null,a="htk",h=!1){if(d!==null&&d!=="slaney")throw new Error('norm must be one of null or "slaney"');const f=hertz_to_mel(i,a),c=hertz_to_mel(s,a),l=linspace(f,c,t+2);let n=mel_to_hertz(l,a),e;if(h){const o=u/(m*2);e=hertz_to_mel(Float64Array.from({length:m},(p,g)=>g*o),a),n=l}else e=linspace(0,Math.floor(u/2),m);const r=_create_triangular_filter_bank(e,n);if(d!==null&&d==="slaney")for(let o=0;o<t;++o){const p=r[o],g=2/(n[o+2]-n[o]);for(let _=0;_<m;++_)p[_]*=g}return r}function padReflect(m,t,i){const s=new m.constructor(m.length+t+i),u=m.length-1;for(let d=0;d<m.length;++d)s[t+d]=m[d];for(let d=1;d<=t;++d)s[t-d]=m[calculateReflectOffset(d,u)];for(let d=1;d<=i;++d)s[u+t+d]=m[calculateReflectOffset(u-d,u)];return s}function _db_conversion_helper(m,t,i,s,u){if(i<=0)throw new Error("reference must be greater than zero");if(s<=0)throw new Error("min_value must be greater than zero");i=Math.max(s,i);const d=Math.log10(i);for(let a=0;a<m.length;++a)m[a]=t*Math.log10(Math.max(s,m[a])-d);if(u!==null){if(u<=0)throw new Error("db_range must be greater than zero");const a=max(m)[0]-u;for(let h=0;h<m.length;++h)m[h]=Math.max(m[h],a)}return m}function amplitude_to_db(m,t=1,i=1e-5,s=null){return _db_conversion_helper(m,20,t,i,s)}function power_to_db(m,t=1,i=1e-10,s=null){return _db_conversion_helper(m,10,t,i,s)}function spectrogram(m,t,i,s,{fft_length:u=null,power:d=1,center:a=!0,pad_mode:h="reflect",onesided:f=!0,preemphasis:c=null,mel_filters:l=null,mel_floor:n=1e-10,log_mel:e=null,reference:r=1,min_value:o=1e-10,db_range:p=null,remove_dc_offset:g=null,max_num_frames:_=null,do_pad:b=!0,transpose:y=!1}={}){const w=t.length;if(u===null&&(u=i),i>u)throw Error(`frame_length (${i}) may not be larger than fft_length (${u})`);if(w!==i)throw new Error(`Length of the window (${w}) must equal frame_length (${i})`);if(s<=0)throw new Error("hop_length must be greater than zero");if(a){if(h!=="reflect")throw new Error(`pad_mode="${h}" not implemented yet.`);const D=Math.floor((u-1)/2)+1;m=padReflect(m,D,D)}const T=Math.floor(1+Math.floor((m.length-i)/s)),S=f?Math.floor(u/2)+1:u;let A=T,P=T;_!==null&&(_>T?b&&(P=_):P=A=_);const x=new FFT(u),M=new Float64Array(u),N=new Float64Array(x.outputBufferSize),z=new Array(A);for(let D=0;D<A;++D){const R=D*s;for(let V=0;V<i;++V)M[V]=m[R+V];if(g){let V=0;for(let Z=0;Z<i;++Z)V+=M[Z];const J=V/i;for(let Z=0;Z<i;++Z)M[Z]-=J}if(c!==null){for(let V=i-1;V>=1;--V)M[V]-=c*M[V-1];M[0]*=1-c}for(let V=0;V<t.length;++V)M[V]*=t[V];x.realTransform(N,M);const Y=new Array(S);for(let V=0;V<Y.length;++V){const J=V<<1;Y[V]=N[J]**2+N[J+1]**2}z[D]=Y}if(d!==null&&d!==2){const D=2/d;for(let R=0;R<z.length;++R){const Y=z[R];for(let V=0;V<Y.length;++V)Y[V]**=D}}const $=l.length,C=new Float32Array($*P),G=y?[P,$]:[$,P];for(let D=0;D<$;++D){const R=l[D];for(let Y=0;Y<A;++Y){const V=z[Y];let J=0;for(let Z=0;Z<S;++Z)J+=R[Z]*V[Z];C[y?Y*$+D:D*A+Y]=Math.max(n,J)}}if(d!==null&&e!==null){const D=Math.min(C.length,A*$);switch(e){case"log":for(let R=0;R<D;++R)C[R]=Math.log(C[R]);break;case"log10":for(let R=0;R<D;++R)C[R]=Math.log10(C[R]);break;case"dB":if(d===1)amplitude_to_db(C,r,o,p);else if(d===2)power_to_db(C,r,o,p);else throw new Error(`Cannot use log_mel option '${e}' with power ${d}`);break;default:throw new Error(`log_mel must be one of null, 'log', 'log10' or 'dB'. Got '${e}'`)}}return{data:C,dims:G}}function window_function(m,t,{periodic:i=!0,frame_length:s=null,center:u=!0}={}){const d=i?m+1:m;let a;switch(t){case"boxcar":a=new Float64Array(d).fill(1);break;case"hann":case"hann_window":a=hanning(d);break;default:throw new Error(`Unknown window type ${t}.`)}if(i&&(a=a.subarray(0,m)),s===null)return a;if(m>s)throw new Error(`Length of the window (${m}) may not be larger than frame_length (${s})`);return a}function center_to_corners_format([m,t,i,s]){return[m-i/2,t-s/2,m+i/2,t+s/2]}function post_process_object_detection(m,t=.5,i=null,s=!1){const u=m.logits,d=m.pred_boxes,[a,h,f]=u.dims;if(i!==null&&i.length!==a)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let c=[];for(let l=0;l<a;++l){let n=i!==null?i[l]:null,e={boxes:[],classes:[],scores:[]},r=u[l],o=d[l];for(let p=0;p<h;++p){let g=r[p],_=[],b;if(s){b=g.sigmoid().data;for(let y=0;y<b.length;++y)b[y]>t&&_.push(y)}else{let y=max(g.data)[1];if(y===f-1)continue;_.push(y),b=softmax(g.data)}for(const y of _){let w=o[p].data;w=center_to_corners_format(w),n!==null&&(w=w.map((T,S)=>T*n[(S+1)%2])),e.boxes.push(w),e.classes.push(y),e.scores.push(b[y])}}c.push(e)}return c}function validate_audio_inputs(m,t){var i;if(!(m instanceof Float32Array||m instanceof Float64Array))throw new Error(`${t} expects input to be a Float32Array or a Float64Array, but got ${((i=m==null?void 0:m.constructor)==null?void 0:i.name)??typeof m} instead.If using the feature extractor directly, remember to use \`read_audio(url, sampling_rate)\` to obtain the raw audio data of the file/url.`)}class FeatureExtractor extends Callable{constructor(t){super(),this.config=t}}class ImageFeatureExtractor extends FeatureExtractor{constructor(t){super(t),this.image_mean=this.config.image_mean,this.image_std=this.config.image_std,this.resample=this.config.resample??2,this.do_rescale=this.config.do_rescale??!0,this.rescale_factor=this.config.rescale_factor??1/255,this.do_normalize=this.config.do_normalize,this.do_resize=this.config.do_resize,this.do_thumbnail=this.config.do_thumbnail,this.size=this.config.size,this.size_divisor=this.config.size_divisor,this.do_center_crop=this.config.do_center_crop,this.crop_size=this.config.crop_size,this.do_convert_rgb=this.config.do_convert_rgb??!0,this.do_crop_margin=this.config.do_crop_margin,this.pad_size=this.config.pad_size,this.do_pad=this.config.do_pad,this.do_pad&&!this.pad_size&&this.size.width!==void 0&&this.size.height!==void 0&&(this.pad_size=this.size)}async thumbnail(t,i,s=2){const u=t.height,d=t.width,a=i.height,h=i.width;let f=Math.min(u,a),c=Math.min(d,h);return f===u&&c===d?t:(u>d?c=Math.floor(d*f/u):d>u&&(f=Math.floor(u*c/d)),await t.resize(c,f,{resample:s}))}async crop_margin(t,i=200){const s=t.clone().grayscale(),u=min(s.data)[0],a=max(s.data)[0]-u;if(a===0)return t;const h=i/255;let f=s.width,c=s.height,l=0,n=0;for(let e=0;e<s.height;++e){const r=e*s.width;for(let o=0;o<s.width;++o)(s.data[r+o]-u)/a<h&&(f=Math.min(f,o),c=Math.min(c,e),l=Math.max(l,o),n=Math.max(n,e))}return t=await t.crop([f,c,l,n]),t}pad_image(t,i,s,{mode:u="constant",center:d=!1,constant_values:a=0}={}){const[h,f,c]=i;let l,n;if(typeof s=="number"?(l=s,n=s):(l=s.width,n=s.height),l!==h||n!==f){const e=new Float32Array(l*n*c);if(Array.isArray(a))for(let p=0;p<e.length;++p)e[p]=a[p%c];else a!==0&&e.fill(a);const[r,o]=d?[Math.floor((l-h)/2),Math.floor((n-f)/2)]:[0,0];for(let p=0;p<f;++p){const g=(p+o)*l,_=p*h;for(let b=0;b<h;++b){const y=(g+b+r)*c,w=(_+b)*c;for(let T=0;T<c;++T)e[y+T]=t[w+T]}}if(u==="symmetric"){if(d)throw new Error("`center` padding is not supported when `mode` is set to `symmetric`.");const p=f-1,g=h-1;for(let _=0;_<n;++_){const b=_*l,y=calculateReflectOffset(_,p)*h;for(let w=0;w<l;++w){if(_<f&&w<h)continue;const T=(b+w)*c,S=(y+calculateReflectOffset(w,g))*c;for(let A=0;A<c;++A)e[T+A]=t[S+A]}}}t=e,i=[n,l,c]}return[t,i]}async preprocess(t){this.do_crop_margin&&(t=await this.crop_margin(t));const i=t.width,s=t.height;if(this.do_convert_rgb&&(t=t.rgb()),this.do_resize){let c,l;if(this.do_thumbnail){const{height:n,width:e}=this.size;c=Math.min(n,e)}else Number.isInteger(this.size)?(c=this.size,l=this.config.max_size??c):this.size!==void 0&&(c=this.size.shortest_edge,l=this.size.longest_edge);if(c!==void 0||l!==void 0){const n=c===void 0?1:Math.max(c/i,c/s),e=i*n,r=s*n,o=l===void 0?1:Math.min(l/e,l/r),p=Math.floor(Number((e*o).toFixed(2))),g=Math.floor(Number((r*o).toFixed(2)));t=await t.resize(p,g,{resample:this.resample})}else if(this.size!==void 0&&this.size.width!==void 0&&this.size.height!==void 0)t=await t.resize(this.size.width,this.size.height,{resample:this.resample});else if(this.size_divisor!==void 0){const n=Math.floor(i/this.size_divisor)*this.size_divisor,e=Math.floor(s/this.size_divisor)*this.size_divisor;t=await t.resize(n,e,{resample:this.resample})}else throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(this.size)}`)}if(this.do_thumbnail&&(t=await this.thumbnail(t,this.size,this.resample)),this.do_center_crop){let c,l;Number.isInteger(this.crop_size)?(c=this.crop_size,l=this.crop_size):(c=this.crop_size.width,l=this.crop_size.height),t=await t.center_crop(c,l)}let u=[t.height,t.width],d=Float32Array.from(t.data),a=[t.height,t.width,t.channels];if(this.do_rescale)for(let c=0;c<d.length;++c)d[c]=this.rescale_factor*d[c];if(this.do_normalize){let c=this.image_mean;Array.isArray(this.image_mean)||(c=new Array(t.channels).fill(c));let l=this.image_std;if(Array.isArray(this.image_std)||(l=new Array(t.channels).fill(c)),c.length!==t.channels||l.length!==t.channels)throw new Error(`When set to arrays, the length of \`image_mean\` (${c.length}) and \`image_std\` (${l.length}) must match the number of channels in the image (${t.channels}).`);for(let n=0;n<d.length;n+=t.channels)for(let e=0;e<t.channels;++e)d[n+e]=(d[n+e]-this.image_mean[e])/this.image_std[e]}this.do_pad&&this.pad_size&&([d,a]=this.pad_image(d,[t.width,t.height,t.channels],this.pad_size));const h=new Tensor("float32",d,a),f=transpose(h,[2,0,1]);return{original_size:[s,i],reshaped_input_size:u,pixel_values:f}}async _call(t,...i){Array.isArray(t)||(t=[t]);const s=await Promise.all(t.map(d=>this.preprocess(d)));return s.forEach(d=>d.pixel_values.dims=[1,...d.pixel_values.dims]),{pixel_values:cat(s.map(d=>d.pixel_values)),original_sizes:s.map(d=>d.original_size),reshaped_input_sizes:s.map(d=>d.reshaped_input_size)}}}class DPTFeatureExtractor extends ImageFeatureExtractor{}class GLPNFeatureExtractor extends ImageFeatureExtractor{}class CLIPFeatureExtractor extends ImageFeatureExtractor{}class ConvNextFeatureExtractor extends ImageFeatureExtractor{}class ConvNextImageProcessor extends ConvNextFeatureExtractor{}class ViTFeatureExtractor extends ImageFeatureExtractor{}class MobileViTFeatureExtractor extends ImageFeatureExtractor{}class OwlViTFeatureExtractor extends ImageFeatureExtractor{post_process_object_detection(...t){return post_process_object_detection(...t)}}class DeiTFeatureExtractor extends ImageFeatureExtractor{}class BeitFeatureExtractor extends ImageFeatureExtractor{}class DonutFeatureExtractor extends ImageFeatureExtractor{pad_image(t,i,s,u={}){const[d,a,h]=i;let f=this.image_mean;Array.isArray(this.image_mean)||(f=new Array(h).fill(f)),this.image_std,Array.isArray(this.image_std)||new Array(h).fill(f);const c=f.map((l,n)=>-l/this.image_std[n]);return super.pad_image(t,i,s,{center:!0,constant_values:c,...u})}}class NougatImageProcessor extends DonutFeatureExtractor{}class DetrFeatureExtractor extends ImageFeatureExtractor{async _call(t){const i=await super._call(t),s=[i.pixel_values.dims[0],64,64],u=new Tensor("int64",new BigInt64Array(s.reduce((d,a)=>d*a)).fill(1n),s);return{...i,pixel_mask:u}}post_process_object_detection(...t){return post_process_object_detection(...t)}remove_low_and_no_objects(t,i,s,u){let d=[],a=[],h=[];for(let f=0;f<t.dims[0];++f){let c=t[f],l=i[f],n=max(c.data)[1];if(n===u)continue;let r=softmax(c.data)[n];r>s&&(d.push(l),a.push(r),h.push(n))}return[d,a,h]}check_segment_validity(t,i,s,u=.5,d=.8){let a=[],h=0,f=0;for(let l=0;l<t.length;++l)t[l]===s&&(a.push(l),++h),i[s].data[l]>=u&&++f;let c=h>0&&f>0;return c&&(c=h/f>d),[c,a]}compute_segments(t,i,s,u,d,a=null,h=null){let[f,c]=h??t[0].dims,l=new Tensor("int32",new Int32Array(f*c),[f,c]),n=[];if(h!==null)for(let p=0;p<t.length;++p)t[p]=interpolate(t[p],h,"bilinear",!1);let e=new Int32Array(t[0].data.length),r=new Float32Array(t[0].data.length);for(let p=0;p<t.length;++p){let g=i[p];for(let _=0;_<t[p].data.length;++_)t[p].data[_]*=g,t[p].data[_]>r[_]&&(e[_]=p,r[_]=t[p].data[_])}let o=0;for(let p=0;p<s.length;++p){let g=s[p],[_,b]=this.check_segment_validity(e,t,p,u,d);if(_){++o;for(let y of b)l.data[y]=o;n.push({id:o,label_id:g,score:i[p]})}}return[l,n]}post_process_panoptic_segmentation(t,i=.5,s=.5,u=.8,d=null,a=null){d===null&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),d=new Set);const h=t.logits,c=t.pred_masks.sigmoid();let[l,n,e]=h.dims;if(e-=1,a!==null&&a.length!==l)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let r=[];for(let o=0;o<l;++o){let p=a!==null?a[o]:null,g=h[o],_=c[o],[b,y,w]=this.remove_low_and_no_objects(g,_,i,e);if(w.length===0){let[A,P]=p??_.dims.slice(-2),x=new Tensor("int32",new Int32Array(A*P).fill(-1),[A,P]);r.push({segmentation:x,segments_info:[]});continue}let[T,S]=this.compute_segments(b,y,w,s,u,d,p);r.push({segmentation:T,segments_info:S})}return r}post_process_instance_segmentation(){throw Error("Not implemented yet")}}class YolosFeatureExtractor extends ImageFeatureExtractor{post_process_object_detection(...t){return post_process_object_detection(...t)}}class SamImageProcessor extends ImageFeatureExtractor{async _call(t,i){let{pixel_values:s,original_sizes:u,reshaped_input_sizes:d}=await super._call(t),a=calculateDimensions(i);if(a.length===3)a=[1,...a],i=[i];else if(a.length!==4)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");for(let f=0;f<i.length;++f){let c=u[f],l=d[f],n=[l[0]/c[0],l[1]/c[1]];for(let e=0;e<i[f].length;++e)for(let r=0;r<i[f][e].length;++r)for(let o=0;o<i[f][e][r].length;++o)i[f][e][r][o]*=n[o]}let h=new Tensor("int64",BigInt64Array.from(i.flat(1/0).map(f=>BigInt(Math.round(f)))),a);return{pixel_values:s,original_sizes:u,reshaped_input_sizes:d,input_points:h}}post_process_masks(t,i,s,{mask_threshold:u=0,binarize:d=!0,pad_size:a=null}={}){let h=[];a=a??this.pad_size;let f=[a.height,a.width];for(let c=0;c<i.length;++c){let l=i[c],n=s[c],e=t[c],r=[];for(let p=0;p<e.dims[0];++p){let g=e[p],_=interpolate(g,f,"bilinear",!1);_=_.slice(null,[0,n[0]],[0,n[1]]),_=interpolate(e,l,"bilinear",!1),d&&(_=new Tensor("bool",Array.from(_.data).map(b=>b>u),_.dims)),_.dims=[1,..._.dims],r.push(_)}let o=cat(r);h.push(o)}return h}}class Swin2SRImageProcessor extends ImageFeatureExtractor{pad_image(t,i,s,u={}){const[d,a,h]=i;return super.pad_image(t,i,{width:d+(s-d%s)%s,height:a+(s-a%s)%s},{mode:"symmetric",center:!1,constant_values:-1,...u})}}class WhisperFeatureExtractor extends FeatureExtractor{constructor(t){var i;super(t),(i=this.config).mel_filters??(i.mel_filters=mel_filter_bank(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney")),this.window=window_function(this.config.n_fft,"hann")}_extract_fbank_features(t){const{data:i,dims:s}=spectrogram(t,this.window,this.config.n_fft,this.config.hop_length,{power:2,mel_filters:this.config.mel_filters,log_mel:"log10",max_num_frames:this.config.nb_max_frames}),u=max(i)[0];for(let d=0;d<i.length;++d)i[d]=(Math.max(i[d],u-8)+4)/4;return{data:i,dims:s}}async _call(t){validate_audio_inputs(t,"WhisperFeatureExtractor");let i;t.length>this.config.n_samples?(console.warn("Attempting to extract features for audio longer than 30 seconds. If using a pipeline to extract transcript from a long audio clip, remember to specify `chunk_length_s` and/or `stride_length_s`."),i=t.slice(0,this.config.n_samples)):(i=new Float32Array(this.config.n_samples),i.set(t));const{data:s,dims:u}=this._extract_fbank_features(i);return{input_features:new Tensor("float32",s,[1,...u])}}}class Wav2Vec2FeatureExtractor extends FeatureExtractor{_zero_mean_unit_var_norm(t){const s=t.reduce((d,a)=>d+a,0)/t.length,u=t.reduce((d,a)=>d+(a-s)**2,0)/t.length;return t.map(d=>(d-s)/Math.sqrt(u+1e-7))}async _call(t){validate_audio_inputs(t,"Wav2Vec2FeatureExtractor"),t instanceof Float64Array&&(t=new Float32Array(t));let i=t;this.config.do_normalize&&(i=this._zero_mean_unit_var_norm(i));const s=[1,i.length];return{input_values:new Tensor("float32",i,s),attention_mask:new Tensor("int64",new BigInt64Array(i.length).fill(1n),s)}}}class ASTFeatureExtractor extends FeatureExtractor{constructor(t){super(t);const i=this.config.sampling_rate,s=mel_filter_bank(256,this.config.num_mel_bins,20,Math.floor(i/2),i,null,"kaldi",!0);for(let u=0;u<s.length;++u)s[u].push(0);this.mel_filters=s,this.window=window_function(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}_extract_fbank_features(t,i){return spectrogram(t,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:i,transpose:!0})}async _call(t){validate_audio_inputs(t,"ASTFeatureExtractor");const i=this._extract_fbank_features(t,this.config.max_length);if(this.config.do_normalize){const s=this.std*2;for(let u=0;u<i.data.length;++u)i.data[u]=(i.data[u]-this.mean)/s}return{input_values:new Tensor("float32",i.data,[1,...i.dims])}}}class ClapFeatureExtractor extends FeatureExtractor{constructor(t){super(t),this.mel_filters=mel_filter_bank(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,null,"htk"),this.mel_filters_slaney=mel_filter_bank(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,"slaney","slaney"),this.window=window_function(this.config.fft_window_size,"hann")}_get_input_mel(t,i,s,u){let d,a=!1;const h=t.length-i;if(h>0)if(s==="rand_trunc"){a=!0;const f=Math.floor(Math.random()*(h+1));t=t.subarray(f,f+i),d=this._extract_fbank_features(t,this.mel_filters_slaney,this.config.nb_max_samples),d.dims=[1,...d.dims]}else throw new Error(`Truncation strategy "${s}" not implemented`);else{if(h<0){let f=new Float64Array(i);if(f.set(t),u==="repeat")for(let c=t.length;c<i;c+=t.length)f.set(t.subarray(0,Math.min(t.length,i-c)),c);else if(u==="repeatpad")for(let c=t.length;c<-h;c+=t.length)f.set(t,c);t=f}if(s==="fusion")throw new Error(`Truncation strategy "${s}" not implemented`);d=this._extract_fbank_features(t,this.mel_filters_slaney,this.config.nb_max_samples),d.dims=[1,...d.dims]}return{...d,longer:a}}_extract_fbank_features(t,i,s=null){return spectrogram(t,this.window,this.config.fft_window_size,this.config.hop_length,{power:2,mel_filters:i,log_mel:"dB",max_num_frames:s,do_pad:!1,transpose:!0})}async _call(t,{max_length:i=null}={}){validate_audio_inputs(t,"ClapFeatureExtractor");const s=this._get_input_mel(t,i??this.config.nb_max_samples,this.config.truncation,this.config.padding);return{input_features:new Tensor("float32",s.data,[1,...s.dims])}}}class SpeechT5FeatureExtractor extends FeatureExtractor{}class Processor extends Callable{constructor(t){super(),this.feature_extractor=t}async _call(t,...i){return await this.feature_extractor(t)}}class SamProcessor extends Processor{async _call(t,i){return await this.feature_extractor(t,i)}post_process_masks(...t){return this.feature_extractor.post_process_masks(...t)}}class WhisperProcessor extends Processor{async _call(t){return await this.feature_extractor(t)}}class Wav2Vec2ProcessorWithLM extends Processor{async _call(t){return await this.feature_extractor(t)}}class SpeechT5Processor extends Processor{async _call(t){return await this.feature_extractor(t)}}class OwlViTProcessor extends Processor{}class AutoProcessor{static async from_pretrained(t,{progress_callback:i=null,config:s=null,cache_dir:u=null,local_files_only:d=!1,revision:a="main"}={}){let h=s??await getModelJSON(t,"preprocessor_config.json",!0,{progress_callback:i,config:s,cache_dir:u,local_files_only:d,revision:a}),f=h.feature_extractor_type??h.image_processor_type,c=this.FEATURE_EXTRACTOR_CLASS_MAPPING[f];if(!c)if(h.size!==void 0)console.warn(`Feature extractor type "${f}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),c=ImageFeatureExtractor;else throw new Error(`Unknown Feature Extractor type: ${f}`);let l=this.PROCESSOR_CLASS_MAPPING[h.processor_class]??Processor,n=new c(h);return new l(n)}}he(AutoProcessor,"FEATURE_EXTRACTOR_CLASS_MAPPING",{WhisperFeatureExtractor,ViTFeatureExtractor,MobileViTFeatureExtractor,OwlViTFeatureExtractor,CLIPFeatureExtractor,ConvNextFeatureExtractor,ConvNextImageProcessor,DPTFeatureExtractor,GLPNFeatureExtractor,BeitFeatureExtractor,DeiTFeatureExtractor,DetrFeatureExtractor,YolosFeatureExtractor,DonutFeatureExtractor,NougatImageProcessor,SamImageProcessor,Swin2SRImageProcessor,Wav2Vec2FeatureExtractor,SpeechT5FeatureExtractor,ASTFeatureExtractor,ClapFeatureExtractor}),he(AutoProcessor,"PROCESSOR_CLASS_MAPPING",{WhisperProcessor,Wav2Vec2ProcessorWithLM,SamProcessor,SpeechT5Processor,OwlViTProcessor});async function prepareImages(m){return Array.isArray(m)||(m=[m]),m=await Promise.all(m.map(t=>RawImage.read(t))),m}class Pipeline extends Callable{constructor({task:t,model:i,tokenizer:s=null,processor:u=null}){super(),this.task=t,this.model=i,this.tokenizer=s,this.processor=u}async dispose(){await this.model.dispose()}async _call(t,...i){let s=this.tokenizer(t,{padding:!0,truncation:!0}),u=await this.model(s);return[s,u]}}class TextClassificationPipeline extends Pipeline{async _call(t,{topk:i=1}={}){let s=this.model.config.problem_type==="multi_label_classification"?f=>f.sigmoid().data:f=>softmax(f.data),[u,d]=await super._call(t),a=this.model.config.id2label,h=[];for(let f of d.logits){let c=s(f),n=getTopItems(c,i).map(function(e){return{label:a[e[0]],score:e[1]}});i===1?h.push(...n):h.push(n)}return Array.isArray(t)||i===1?h:h[0]}}class TokenClassificationPipeline extends Pipeline{async _call(t,{ignore_labels:i=["O"]}={}){let s=Array.isArray(t);s||(t=[t]);let u=this.tokenizer,[d,a]=await super._call(t),h=a.logits,f=this.model.config.id2label,c=[];for(let l=0;l<h.dims[0];++l){let n=d.input_ids[l],e=h[l],r=[];for(let o=0;o<e.dims[0];++o){let p=e[o],g=max(p.data)[1],_=f[g];if(i.includes(_))continue;let b=u.decode([n[o].item()],{skip_special_tokens:!0});if(b==="")continue;let y=softmax(p.data);r.push({entity:_,score:y[g],index:o,word:b,start:null,end:null})}c.push(r)}return s?c:c[0]}}class QuestionAnsweringPipeline extends Pipeline{async _call(t,i,{topk:s=1}={}){let u=this.tokenizer(t,{text_pair:i,padding:!0,truncation:!0}),d=await this.model(u),a=[];for(let h=0;h<d.start_logits.dims[0];++h){let f=u.input_ids[h],c=f.indexOf(this.tokenizer.sep_token_id),l=Array.from(softmax(d.start_logits[h].data)).map((r,o)=>[r,o]).filter(r=>r[1]>c),n=Array.from(softmax(d.end_logits[h].data)).map((r,o)=>[r,o]).filter(r=>r[1]>c),e=product(l,n).filter(r=>r[0][1]<=r[1][1]).map(r=>[r[0][1],r[1][1],r[0][0]*r[1][0]]).sort((r,o)=>o[2]-r[2]);for(let r=0;r<Math.min(e.length,s);++r){let[o,p,g]=e[r],_=[...f].slice(o,p+1),b=this.tokenizer.decode(_,{skip_special_tokens:!0});a.push({answer:b,score:g})}}return s===1?a[0]:a}}class FillMaskPipeline extends Pipeline{async _call(t,{topk:i=5}={}){let[s,u]=await super._call(t),d=this.tokenizer,a=[];for(let h=0;h<s.input_ids.dims[0];++h){let f=s.input_ids[h],c=f.indexOf(this.tokenizer.mask_token_id);if(c===-1)throw Error(`Mask token (${d.mask_token}) not found in text.`);let n=u.logits[h][c],e=getTopItems(softmax(n.data),i);a.push(e.map(r=>{let o=[...f];return o[c]=r[0],{score:r[1],token:r[0],token_str:d.model.vocab[r[0]],sequence:d.decode(o,{skip_special_tokens:!0})}}))}return Array.isArray(t)?a:a[0]}}class Text2TextGenerationPipeline extends Pipeline{constructor(){super(...arguments);he(this,"_key","generated_text")}async _call(i,s={}){Array.isArray(i)||(i=[i]),this.model.config.prefix&&(i=i.map(c=>this.model.config.prefix+c));let u=this.model.config.task_specific_params;u&&u[this.task]&&u[this.task].prefix&&(i=i.map(c=>u[this.task].prefix+c));let d={padding:!0,truncation:!0},a;this instanceof TranslationPipeline&&"_build_translation_inputs"in this.tokenizer?a=this.tokenizer._build_translation_inputs(i,d,s).input_ids:a=this.tokenizer(i,d).input_ids;let h=await this.model.generate(a,s),f=this.tokenizer.batch_decode(h,{skip_special_tokens:!0});return this._key!==null&&(f=f.map(c=>this._key===null?c:{[this._key]:c})),f}}class SummarizationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);he(this,"_key","summary_text")}}class TranslationPipeline extends Text2TextGenerationPipeline{constructor(){super(...arguments);he(this,"_key","translation_text")}}class TextGenerationPipeline extends Pipeline{async _call(t,i={}){let s=typeof t=="string"||t instanceof String;s&&(t=[t]);const u=i.add_special_tokens??!1;this.tokenizer.padding_side="left";let d=this.tokenizer(t,{add_special_tokens:u,padding:!0,truncation:!0}),a=d.input_ids,h=d.attention_mask,f=await this.model.generate(a,i,null,{inputs_attention_mask:h});const c=this.tokenizer.batch_decode(f,{skip_special_tokens:!0}),l=Array.from({length:t.length},n=>[]);for(let n=0;n<c.length;++n){const e=Math.floor(n/f.length*t.length);l[e].push({generated_text:c[n]})}return s&&l.length===1?l[0]:l}}class ZeroShotClassificationPipeline extends Pipeline{constructor(t){super(t),this.label2id=Object.fromEntries(Object.entries(this.model.config.label2id).map(([i,s])=>[i.toLowerCase(),s])),this.entailment_id=this.label2id.entailment,this.entailment_id===void 0&&(console.warn("Could not find 'entailment' in label2id mapping. Using 2 as entailment_id."),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,this.contradiction_id===void 0&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(t,i,{hypothesis_template:s="This example is {}.",multi_label:u=!1}={}){let d=Array.isArray(t);d||(t=[t]),Array.isArray(i)||(i=[i]);let a=i.map(c=>s.replace("{}",c)),h=u||i.length===1,f=[];for(let c of t){let l=[];for(let r of a){let o=this.tokenizer(c,{text_pair:r,padding:!0,truncation:!0}),p=await this.model(o);h?l.push([p.logits.data[this.contradiction_id],p.logits.data[this.entailment_id]]):l.push(p.logits.data[this.entailment_id])}let n;h?n=l.map(r=>softmax(r)[1]):n=softmax(l);let e=n.map((r,o)=>[r,o]).sort((r,o)=>o[0]-r[0]);f.push({sequence:c,labels:e.map(r=>i[r[1]]),scores:e.map(r=>r[0])})}return d?f:f[0]}}class FeatureExtractionPipeline extends Pipeline{async _call(t,{pooling:i="none",normalize:s=!1}={}){let[u,d]=await super._call(t),a=d.last_hidden_state??d.logits;if(i!=="none")if(i==="mean")a=mean_pooling(a,u.attention_mask);else throw Error(`Pooling method '${i}' not supported.`);return s&&(a=a.normalize(2,-1)),a}}class AudioClassificationPipeline extends Pipeline{constructor(t){super(t)}async _preprocess(t,i){return isString(t)&&(t=await read_audio(t,i)),t}async _call(t,{topk:i=5}={}){let s=!Array.isArray(t);s&&(t=[t]);const u=this.model.config.id2label,d=this.processor.feature_extractor.config.sampling_rate;let a=[];for(let h of t){h=await this._preprocess(h,d);const f=await this.processor(h),l=(await this.model(f)).logits[0];let e=getTopItems(softmax(l.data),i).map(function(r){return{label:u[r[0]],score:r[1]}});i===1?a.push(...e):a.push(e)}return!s||i===1?a:a[0]}}class ZeroShotAudioClassificationPipeline extends Pipeline{constructor(t){super(t)}async _preprocess(t,i){return isString(t)&&(t=await read_audio(t,i)),t}async _call(t,i,{hypothesis_template:s="This is a sound of {}."}={}){const u=!Array.isArray(t);u&&(t=[t]);const d=i.map(c=>s.replace("{}",c)),a=this.tokenizer(d,{padding:!0,truncation:!0}),h=this.processor.feature_extractor.config.sampling_rate,f=[];for(let c of t){c=await this._preprocess(c,h);const l=await this.processor(c),n=await this.model({...a,...l}),e=softmax(n.logits_per_audio.data);f.push([...e].map((r,o)=>({score:r,label:i[o]})))}return u?f[0]:f}}class AutomaticSpeechRecognitionPipeline extends Pipeline{constructor(t){super(t)}async _preprocess(t,i){return isString(t)&&(t=await read_audio(t,i)),t}async _call(t,i={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(t,i);case"wav2vec2":return this._call_wav2vec2(t,i);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(t,i={}){i.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),i.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');let s=!Array.isArray(t);s&&(t=[t]);const u=this.processor.feature_extractor.config.sampling_rate;let d=[];for(let a of t){a=await this._preprocess(a,u);const h=await this.processor(a),c=(await this.model(h)).logits[0],l=[];for(let e of c)l.push(max(e.data)[1]);const n=this.tokenizer.decode(l);d.push({text:n})}return s?d[0]:d}async _call_whisper(t,i={}){let s=i.return_timestamps??!1,u=i.chunk_length_s??0,d=i.stride_length_s??null,a=i.chunk_callback??null,h=i.force_full_sequences??!1;s==="word"&&(i.return_token_timestamps=!0);let f=pop(i,"language",null),c=pop(i,"task",null);if(f||c||s){if(i.forced_decoder_ids)throw new Error("Cannot specify `language`/`task`/`return_timestamps` and `forced_decoder_ids` at the same time.");let p=this.tokenizer.get_decoder_prompt_ids({language:f,task:c,no_timestamps:!s});p.length>0&&(i.forced_decoder_ids=p)}let l=!Array.isArray(t);l&&(t=[t]);const n=this.processor.feature_extractor.config.sampling_rate,e=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,r=this.processor.feature_extractor.config.hop_length;let o=[];for(let p of t){p=await this._preprocess(p,n);let g=[];if(u>0){if(d===null)d=u/6;else if(u<=d)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const y=n*u,w=n*d,T=y-2*w;let S=0;for(;S<p.length;){let A=p.subarray(S,S+y),P=await this.processor(A),x=S===0,M=S+T>=p.length;g.push({stride:[A.length,x?0:w,M?0:w],input_features:P.input_features,is_last:M}),S+=T}}else g=[{stride:[p.length,0,0],input_features:(await this.processor(p)).input_features,is_last:!0}];for(let y of g){i.num_frames=Math.floor(y.stride[0]/r);let w=await this.model.generate(y.input_features,i);s==="word"?(y.tokens=w.sequences[0],y.token_timestamps=w.token_timestamps.tolist()[0].map(T=>round(T,2))):y.tokens=w[0],y.stride=y.stride.map(T=>T/n),a!==null&&a(y)}let[_,b]=this.tokenizer._decode_asr(g,{time_precision:e,return_timestamps:s,force_full_sequences:h});o.push({text:_,...b})}return l?o[0]:o}}class ImageToTextPipeline extends Pipeline{constructor(t){super(t)}async _call(t,i={}){let s=Array.isArray(t);t=await prepareImages(t);let{pixel_values:u}=await this.processor(t),d=[];for(let a of u){a.dims=[1,...a.dims];let h=await this.model.generate(a,i),f=this.tokenizer.batch_decode(h,{skip_special_tokens:!0}).map(c=>({generated_text:c.trim()}));d.push(f)}return s?d:d[0]}}class ImageClassificationPipeline extends Pipeline{constructor(t){super(t)}async _call(t,{topk:i=1}={}){let s=Array.isArray(t);t=await prepareImages(t);let{pixel_values:u}=await this.processor(t),d=await this.model({pixel_values:u}),a=this.model.config.id2label,h=[];for(let f of d.logits){let l=getTopItems(softmax(f.data),i).map(function(n){return{label:a[n[0]],score:n[1]}});i===1?h.push(...l):h.push(l)}return s||i===1?h:h[0]}}class ImageSegmentationPipeline extends Pipeline{constructor(t){super(t),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(t,{threshold:i=.5,mask_threshold:s=.5,overlap_mask_area_threshold:u=.8,label_ids_to_fuse:d=null,target_sizes:a=null,subtask:h=null}={}){if(Array.isArray(t)&&t.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");t=await prepareImages(t);let c=t.map(p=>[p.height,p.width]),{pixel_values:l,pixel_mask:n}=await this.processor(t),e=await this.model({pixel_values:l,pixel_mask:n}),r=null;if(h!==null)r=this.subtasks_mapping[h];else for(let[p,g]of Object.entries(this.subtasks_mapping))if(g in this.processor.feature_extractor){r=this.processor.feature_extractor[g].bind(this.processor.feature_extractor),h=p;break}let o=[];if(h==="panoptic"||h==="instance"){let p=r(e,i,s,u,d,a??c)[0],g=p.segmentation,_=this.model.config.id2label;for(let b of p.segments_info){let y=new Uint8ClampedArray(g.data.length);for(let T=0;T<g.data.length;++T)g.data[T]===b.id&&(y[T]=255);let w=new RawImage(y,g.dims[1],g.dims[0],1);o.push({score:b.score,label:_[b.label_id],mask:w})}}else throw Error(h==="semantic"?"semantic segmentation not yet supported.":`Subtask ${h} not supported.`);return o}}class ZeroShotImageClassificationPipeline extends Pipeline{constructor(t){super(t)}async _call(t,i,{hypothesis_template:s="This is a photo of {}"}={}){let u=Array.isArray(t);t=await prepareImages(t);let d=i.map(l=>s.replace("{}",l)),a=this.tokenizer(d,{padding:!0,truncation:!0}),{pixel_values:h}=await this.processor(t),f=await this.model({...a,pixel_values:h}),c=[];for(let l of f.logits_per_image){let n=softmax(l.data);c.push([...n].map((e,r)=>({score:e,label:i[r]})))}return u?c:c[0]}}class ObjectDetectionPipeline extends Pipeline{constructor(t){super(t)}async _call(t,{threshold:i=.9,percentage:s=!1}={}){let u=Array.isArray(t);if(u&&t.length!==1)throw Error("Object detection pipeline currently only supports a batch size of 1.");t=await prepareImages(t);let d=s?null:t.map(e=>[e.height,e.width]),{pixel_values:a,pixel_mask:h}=await this.processor(t),f=await this.model({pixel_values:a,pixel_mask:h}),c=this.processor.feature_extractor.post_process_object_detection(f,i,d),l=this.model.config.id2label;const n=c.map(e=>e.boxes.map((r,o)=>({score:e.scores[o],label:l[e.classes[o]],box:get_bounding_box(r,!s)})));return u?n:n[0]}}class ZeroShotObjectDetectionPipeline extends Pipeline{constructor(t){super(t)}async _call(t,i,{threshold:s=.1,topk:u=null,percentage:d=!1}={}){const a=Array.isArray(t);t=await prepareImages(t);const h=this.tokenizer(i,{padding:!0,truncation:!0}),f=await this.processor(t),c=[];for(let l=0;l<t.length;++l){const n=t[l],e=d?null:[[n.height,n.width]],r=f.pixel_values[l].unsqueeze_(0),o=await this.model({...h,pixel_values:r}),p=this.processor.feature_extractor.post_process_object_detection(o,s,e,!0)[0];let g=p.boxes.map((_,b)=>({score:p.scores[b],label:i[p.classes[b]],box:get_bounding_box(_,!d)})).sort((_,b)=>b.score-_.score);u!==null&&(g=g.slice(0,u)),c.push(g)}return a?c:c[0]}}class DocumentQuestionAnsweringPipeline extends Pipeline{constructor(t){super(t)}async _call(t,i,s={}){t=(await prepareImages(t))[0];const{pixel_values:u}=await this.processor(t),d=`<s_docvqa><s_question>${i}</s_question><s_answer>`,a=this.tokenizer(d,{add_special_tokens:!1,padding:!0,truncation:!0}).input_ids,h=await this.model.generate(u,{...s,decoder_input_ids:a,max_length:this.model.config.decoder.max_position_embeddings}),c=this.tokenizer.batch_decode(h)[0].match(/<s_answer>(.*?)<\/s_answer>/);let l=null;return c&&c.length>=2&&(l=c[1].trim()),[{answer:l}]}}class TextToAudioPipeline extends Pipeline{constructor(i){super(i);he(this,"DEFAULT_VOCODER_ID","Xenova/speecht5_hifigan");this.vocoder=i.vocoder??null}async _call(i,{speaker_embeddings:s=null}={}){if(this.vocoder||(console.log("No vocoder specified, using default HifiGan vocoder."),this.vocoder=await AutoModel.from_pretrained(this.DEFAULT_VOCODER_ID,{quantized:!1})),(typeof s=="string"||s instanceof URL)&&(s=new Float32Array(await(await fetch(s)).arrayBuffer())),s instanceof Float32Array)s=new Tensor("float32",s,[1,s.length]);else if(!(s instanceof Tensor))throw new Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");const{input_ids:u}=this.tokenizer(i,{padding:!0,truncation:!0}),{waveform:d}=await this.model.generate_speech(u,s,{vocoder:this.vocoder}),a=this.processor.feature_extractor.config.sampling_rate;return{audio:d.data,sampling_rate:a}}}class ImageToImagePipeline extends Pipeline{async _call(t){t=await prepareImages(t);let i=await this.processor(t),s=await this.model(i),u=[];for(let d of s.reconstruction){const a=d.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");u.push(RawImage.fromTensor(a))}return u.length>1?u:u[0]}}class DepthEstimationPipeline extends Pipeline{async _call(t){t=await prepareImages(t);const i=await this.processor(t),{predicted_depth:s}=await this.model(i),u=[];for(let d=0;d<t.length;++d){const a=interpolate(s[d],t[d].size.reverse(),"bilinear",!1),h=a.mul_(255/max(a.data)[0]).to("uint8");u.push({predicted_depth:s[d],depth:RawImage.fromTensor(h)})}return u.length>1?u:u[0]}}const SUPPORTED_TASKS={"text-classification":{tokenizer:AutoTokenizer,pipeline:TextClassificationPipeline,model:AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:AutoTokenizer,pipeline:TokenClassificationPipeline,model:AutoModelForTokenClassification,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:AutoTokenizer,pipeline:QuestionAnsweringPipeline,model:AutoModelForQuestionAnswering,default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:AutoTokenizer,pipeline:FillMaskPipeline,model:AutoModelForMaskedLM,default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:AutoTokenizer,pipeline:SummarizationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:AutoTokenizer,pipeline:TranslationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:AutoTokenizer,pipeline:Text2TextGenerationPipeline,model:AutoModelForSeq2SeqLM,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:AutoTokenizer,pipeline:TextGenerationPipeline,model:AutoModelForCausalLM,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotClassificationPipeline,model:AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:AudioClassificationPipeline,model:AutoModelForAudioClassification,processor:AutoProcessor,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotAudioClassificationPipeline,model:AutoModel,processor:AutoProcessor,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:AutoTokenizer,pipeline:AutomaticSpeechRecognitionPipeline,model:[AutoModelForSpeechSeq2Seq,AutoModelForCTC],processor:AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:AutoTokenizer,pipeline:TextToAudioPipeline,model:[AutoModelForTextToSpectrogram],processor:AutoProcessor,default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:AutoTokenizer,pipeline:ImageToTextPipeline,model:AutoModelForVision2Seq,processor:AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:ImageClassificationPipeline,model:AutoModelForImageClassification,processor:AutoProcessor,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:ImageSegmentationPipeline,model:AutoModelForImageSegmentation,processor:AutoProcessor,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:AutoTokenizer,pipeline:ZeroShotImageClassificationPipeline,model:AutoModel,processor:AutoProcessor,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:ObjectDetectionPipeline,model:AutoModelForObjectDetection,processor:AutoProcessor,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"zero-shot-object-detection":{tokenizer:AutoTokenizer,pipeline:ZeroShotObjectDetectionPipeline,model:AutoModelForZeroShotObjectDetection,processor:AutoProcessor,default:{model:"Xenova/owlvit-base-patch32"},type:"multimodal"},"document-question-answering":{tokenizer:AutoTokenizer,pipeline:DocumentQuestionAnsweringPipeline,model:AutoModelForDocumentQuestionAnswering,processor:AutoProcessor,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"image-to-image":{pipeline:ImageToImagePipeline,model:AutoModelForImageToImage,processor:AutoProcessor,default:{model:"Xenova/swin2SR-classical-sr-x2-64"},type:"image"},"depth-estimation":{pipeline:DepthEstimationPipeline,model:AutoModelForDepthEstimation,processor:AutoProcessor,default:{model:"Xenova/dpt-large"},type:"image"},"feature-extraction":{tokenizer:AutoTokenizer,pipeline:FeatureExtractionPipeline,model:AutoModel,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"}},TASK_ALIASES={"sentiment-analysis":"text-classification",ner:"token-classification",vqa:"visual-question-answering",asr:"automatic-speech-recognition","text-to-speech":"text-to-audio",embeddings:"feature-extraction"};async function pipeline(m,t=null,{quantized:i=!0,progress_callback:s=null,config:u=null,cache_dir:d=null,local_files_only:a=!1,revision:h="main"}={}){m=TASK_ALIASES[m]??m;let f=SUPPORTED_TASKS[m.split("_",1)[0]];if(!f)throw Error(`Unsupported pipeline: ${m}. Must be one of [${Object.keys(SUPPORTED_TASKS)}]`);t||(t=f.default.model,console.log(`No model specified. Using default model: "${t}".`));let c={quantized:i,progress_callback:s,config:u,cache_dir:d,local_files_only:a,revision:h};const l=new Map([["tokenizer",f.tokenizer],["model",f.model],["processor",f.processor]]);let n=await loadItems(l,t,c);n.task=m,dispatchCallback(s,{status:"ready",task:m,model:t});let e=f.pipeline;return new e(n)}async function loadItems(m,t,i){const s=Object.create(null),u=[];for(let[d,a]of m.entries()){if(!a)continue;let h;Array.isArray(a)?h=new Promise(async(f,c)=>{let l;for(let n of a)try{f(await n.from_pretrained(t,i));return}catch(e){l=e}c(l)}):h=a.from_pretrained(t,i),s[d]=h,u.push(h)}await Promise.all(u);for(let[d,a]of Object.entries(s))s[d]=await a;return s}self.addEventListener("message",async m=>{let t=await MyTranslationPipeline.getInstance(s=>{self.postMessage(s)}),i=await t(m.data.text,{tgt_lang:m.data.tgt_lang,src_lang:m.data.src_lang,callback_function:s=>{self.postMessage({status:"update",output:t.tokenizer.decode(s[0].output_token_ids,{skip_special_tokens:!0})})}});self.postMessage({status:"complete",output:i})});class MyTranslationPipeline{static async getInstance(t=null){return this.instance===null&&(this.instance=pipeline(this.task,this.model,{progress_callback:t})),this.instance}}he(MyTranslationPipeline,"task","translation"),he(MyTranslationPipeline,"model","Xenova/nllb-200-distilled-600M"),he(MyTranslationPipeline,"instance",null)})();